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4,436 | https://bio-protocol.org/en/bpdetail?id=4436&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
Time-off-pick Assay to Measure Caenorhabditis elegans Motility
AW Alyssa C. Walker
RB Rohan Bhargava
AB Amanda S. Brust
AO Ali A. Owji
DC Daniel M. Czyż
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4436 Views: 2118
Reviewed by: Juan Facundo Rodriguez AyalaMatthias RieckherRajesh Ranjan
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Original Research Article:
The authors used this protocol in PLOS Pathogens May 2021
Abstract
Caenorhabditis elegans is a simple metazoan that is often used as a model organism to study various human ailments with impaired motility phenotypes, including protein conformational diseases. Numerous motility assays that measure neuro-muscular function have been employed using C. elegans. Here, we describe “time-off-pick" (TOP), a novel assay for assessing motility in C. elegans. TOP is conducted by sliding an eyebrow hair under the mid-section of the worm and counting the number of seconds it takes for the worm to crawl completely off. The time it takes for the worm to crawl off the eyebrow hair is proportional to the severity of its motility defect. Other readouts of motility include crawling or swimming phenotypes, and although widely established, have some limitations. For example, worms that are roller mutants are less suitable for crawling or swimming assays. We demonstrated that our novel TOP assay is sensitive to age-dependent changes in motility, thus, providing another more inclusive method to assess motor function in C. elegans.
Graphical abstract:
Conceptual overview of the “time-off-pick” (TOP) assay. Various C. elegans models exhibit age-dependent defects in motility. The time it takes for a worm to crawl off of an eyebrow pick that is slid under its mid-section is measured in TOP seconds. A greater TOP is indicative of a greater motility defect. Eventually, worms with phenotypes that lead to paralysis will not be able to leave the pick.
Keywords: Caenorhabditis elegans Motility Muscle function Motility defect Motility assessment
Background
Caenorhabditis elegans is a 1-mm long nematode often used as a model organism for studying various human diseases or conditions that induce neuro-muscular defects. As such, motility assays are commonly used to assess motor impairments in C. elegans. Common motility assays measure parameters associated with swimming and crawling phenotypes, which have proven to be very successful and effective readouts (Cohen et al., 2012; Winter et al., 2016). However, the aforementioned assays can be time-consuming, may require specialized equipment, and are less compatible with certain C. elegans phenotypes, such as the roller phenotype, which is commonly used as a selection marker when generating transgenic C. elegans lines. The protocol presented in this paper, “time-off-pick” (TOP), describes a novel phenotypic assay for measuring motility in C. elegans. Our method is less elaborate, does not require specialized equipment, and is more inclusive to a variety of genetic backgrounds, including those that exhibit the roller phenotype. TOP involves sliding an eyebrow hair under the mid-section of the worm and counting the number of seconds it takes for the worm to crawl off (Video 1). The worm is not lifted by the eyebrow hair; rather, the hair remains stationary after being gently placed between the worm and the surface of the agar on nematode-growth media (NGM) plates, with care taken not to poke the side of the worm with the eyebrow hair. A longer TOP is indicative of a greater motility impairment. This method allows the experimenter to study C. elegans strains, mutations, conditions, or treatments that alter motility.
Video 1. Time-off-pick (TOP) demonstration.
To demonstrate the feasibility of our method, we used C. elegans strains that are known to affect motility: lines carrying transgenic polyglutamine (polyQ) tracts (Morley et al., 2002; Brignull et al., 2006; Mohri-Shiomi and Garsin, 2008) and a mutant strain that manifests in a temperature-sensitive motility defect (Macleod et al., 1977). PolyQ tracts aggregate in a polyQ length- and an age-dependent manner, and increased polyQ aggregation is associated with increased motility defects (Morley et al., 2002; Brignull et al., 2006; Mohri-Shiomi and Garsin, 2008). In our previous work, we demonstrated that the results obtained from the TOP assay matched those from the swimming assay (“thrashing”) (Walker et al., 2021). Here, we show our TOP method can successfully assess changes in age- and polyQ length-dependent motility in worms harboring polyQ tracts in the intestine (Figure 1A), muscle (Figure 1B), and neurons (Figure 1C). To demonstrate the versatility of our method, we used a strain (CB1301) that expresses a temperature-sensitive mutation in myosin heavy chain gene, unc-54 (e1301), that results in impaired motility at restrictive temperatures (Macleod et al., 1977; Gidalevitz et al., 2006). We found that TOP detected a temperature-induced motility impairment 1 h after worms were placed at the restrictive temperature (Figure 1D). Together, these results demonstrate the use and efficacy of the TOP phenotype, which provides a validated and sensitive addition to existing motility assays.
Figure 1. TOP measurement in C. elegans expressing polyQ and a temperature-sensitive mutation. (A–C) The TOP phenotype positively correlates with C. elegans age and polyQ length in the (A) intestine (rollers): polyQ44: AM738 rmIs297[vha-6p::q44::yfp; rol-6 (su1006)]; polyQ33: AM712 rmIs281[vha-6p::q33::yfp; rol-6 (su1006)], (B) muscle: polyQ40: AM141 rmIs133[unc-54p::q40::yfp]; polyQ35: AM140 rmIs132[unc-54p::q35::yfp]; polyQ0: AM134 rmIs126[unc-54p::q0::yfp], and (C) neurons: polyQ40: AM101 rmIs110[F25B3.3P::q40::yfp]; polyQ0: AM52 rmIs182[F25B3.3p::q0::yfp]. Worms were cultured and maintained at 22.5°C. (D) Motility of worms (CB1301) expressing a temperature-sensitive mutation (ts) in myosin heavy chain, unc-54(e1301). Nematodes cultured and maintained at 20°C harboring the mutation display a significant increase in TOP (seconds) after 1 h at a restrictive temperature of 22.5°C (data point immediately to the right of the red, dashed line), whereas wild-type worms (N2), exhibit no significant change. Motility impairment continues to worsen over the next 48 h at the restrictive temperature. Data are represented as the average TOP per worm. Each data point is an average of two independent experiments with a total of 30 worms. Error bars represent standard error of the mean (SEM). Statistical analysis was calculated using one-way analysis of variants (ANOVA) followed by multiple comparison Dunnett’s post-hoc test (*P < 0.05, ***P < 0.001, **** P < 0.0001).
Materials and Reagents
Note: Unless otherwise specified, all reagents are stored at room temperature.
Erlenmeyer flasks (2,000 mL and 1,000 mL)
6 cm Petri dishes (Genesee Scientific, catalog number: 32-105G)
Magnetic stir bar
Autoclave tape
Caenorhabditis elegans
500 mL Olympus vacuum filter flasks (Genesee Scientific, catalog number: 25-227)
Agar (Fisher Scientific, catalog number: BP1423)
Double distilled water (ddH2O)
NaCl (Fisher Scientific, catalog number: S671-500)
Trypticase-peptone (Gibco, catalog number: 211921)
Cholesterol (MP Biomedicals, catalog number: ICN10138201)
Ethanol, 200-proof (Decon Laboratories, catalog number: 04-355-223)
CaCl2·2H2O (Fisher Scientific, catalog number: C79-500)
MgSO4·7H2O (Fisher Scientific, catalog number: A14491)
KH2PO4 (Fisher Chemical, catalog number: P285-3)
NA2HPO4·7H2O (Fisher Scientific, catalog number: S373-500)
M9 Minimal Medium (see Recipes)
Cholesterol Stock Solution (see Recipes)
1 M CaCl2 Stock Solution (see Recipes)
1 M MgSO4 Stock Solution (see Recipes)
1 M KH2PO4, pH 6.0 Stock Solution (see Recipes)
Eyebrow hair pick (see Recipes)
NGM Plates (see Recipes)
Equipment
Zeiss Stemi 305 stereo microscope (Zeiss, catalog number: 435063-9010-000)
Incubators for C. elegans (15–25°C)
Ethanol candle (DWK Life Sciences, catalog number: 04-245-1)
Autoclave
pH meter (Thermo Electric Corporation)
Fisher Scientific Isotemp Stirrer (Fisher Scientific, catalog number: 11-100-49S)
Pasteur pipette (Fisher Scientific, catalog numer: 22-378893)
Soft and thin eyebrow hair
Tape
Second counter (such as a YouTube video or app that beeps every second)
Platinum wire worm pick (made in-house as described in Wollenberg et al., 2013)
Software
GraphPad Prism v8.4.3. (GraphPad Software, Inc.)
BioRender (www.biorender.com)
Procedure
Notes:
Unless otherwise specified, all steps are conducted outside of a biological safety cabinet (BSC) using aseptic techniques.
This protocol assumes nematodes have already been cultured and grown to the age of interest on solid nematode growth media (NGM) plates.
Nematodes used for the data presented herein were cultured and maintained on E. coli OP50 and in accordance with methods we have used previously (Walker et al., 2021) .
C. elegans size will affect TOP measurements; therefore, we recommend using this assay on adult worms only. Also, the experimenter has to use proper size-matched controls when testing conditions that affect worm size.
Worm preparation
To reduce error, transfer worms using platinum wire pick onto a new NGM plate seeded with bacteria of interest. Make sure there is an equal number of worms per plate as well as an equal amount of bacteria on each plate that is consistent between test and control worms.
Note: Make sure to flame the worm pick between samples to avoid cross-contaminating with bacteria or worm strains.
Motility assessment
Note: This step is performed using a dissection microscope and a ticking second timer.
Using a pick with an eyebrow hair taped to it (Figure 2), put an NGM plate that contains worms in view. Slide the eyebrow hair under the mid-section of a worm and count the number of seconds it takes for the worm to crawl off entirely.
Note: It is important to make sure that the worm is not poked in the side with the eyebrow hair; instead, the hair should delicately be placed gently underneath the worm. Additionally, ensure that the eyebrow hair is not going into the agar, is on top of the agar at all times, and remains stationary between the surface of the agar and the worm. Do not lift the worm with the eyebrow hair.
Record the number of seconds it takes the worm to crawl off. Continue with worms and samples as desired.
Figure 2. Picture of the eyebrow hair-pick used in the TOP assay.
Data analysis
The TOP assay allows the experimenter to assess changes in motility by measuring the number of seconds it takes for a worm to completely move off an eyebrow pick. The TOP measurement is proportional to motility—the more time it takes, the larger the defect. The results are analyzed by comparing the measurements of the experimental group with those of the control. We used various C. elegans strains to demonstrate the feasibility of the TOP assay. Data are representative of two independent experiments with a minimum of 30 worms total. The data are represented as standard error of the mean (SEM), and the statistical significance was calculated using student’s t-test (see legend in Figure 1).
Notes
All reagents should be sterile to avoid contamination of samples. All other precautionary notes are contained within corresponding steps of the protocol in “Procedure”.
Recipes
M9 Minimal Medium
Combine 5.8 g of Na2HPO4·7H2O, 3.0 g of KH2PO4, 5.0 g of NaCl, and 0.25 g of MgSO4·7H2O in a 1 L flask.
Add a magnetic stir bar and fill to 1 L with ddH2O.
Place on stir plate and let mix until all reagents are dissolved.
Filter sterilize into two 500 mL bottles.
Aliquot into smaller sterile bottles if desired, and store at RT.
Cholesterol Stock Solution
Dissolve cholesterol in 200-proof ethanol to a final concentration of 5 mg/mL cholesterol. Store at -20°C until use.
1 M CaCl2 Stock Solution
Add 147 g of CaCl2·2H2O to a 1 L flask.
Fill to 1 L with ddH2O.
Add a magnetic stir bar.
Place on stir plate until reagent dissolves.
Aliquot and screw caps loosely on bottles.
Adhere autoclave tape.
Autoclave fluid cycle for 30 min.
Let cool, fully screw caps on, and store at RT until use.
1 M MgSO4 Stock Solution
Add 246.5 g of MgSO4·7H2O to a 1 L flask.
Fill to 1 L with ddH2O.
Add a magnetic stir bar.
Place on stir plate until reagent dissolves.
Aliquot and screw caps loosely on bottles.
Adhere autoclave tape.
Autoclave using a fluid cycle for 30 min at 121°C.
Let cool, fully screw caps on, and store at RT until use.
1 M KH2PO4, pH 6.0 Stock Solution
Add 136.1 g of KH2PO4 to a 1 L flask.
Dissolve in 800 mL of ddH2O.
Add a magnetic stir bar.
Place on stir plate until reagent dissolves.
Adjust pH to 6.0 with 10 g of KOH. Add ddH2O up to 1 L.
After reagents are completely dissolved, and pH is adjusted to 6.0, aliquot and screw caps loosely on bottles.
Adhere autoclave tape.
Autoclave using a fluid cycle for 30 min at 121°C.
Let cool, fully screw caps on, and store at RT until use.
Eyebrow hair pick
Place soft and relatively thin eyebrow hair in the smaller tip of a glass Pasteur pipette, root-first. Secure with tape.
NGM Plates
In a 2 L flask, combine 3.0 g of NaCl, 2.5 g of trypticase-peptone, and 17.0 g of agar.
Fill ddH2O up to 1 L.
Add a magnetic stir bar.
Place on stir plate and let reagents mix for several minutes.
Place cap (loosely screwed on) or foil on the opening of the bottle.
Adhere autoclave tape.
Autoclave using a fluid cycle for 30 min at 121°C.
Cool to 50°C.
Add 1 mL of 5 mg/ mL cholesterol stock solution, 1 mL of 1 M CaCl2 stock solution, 1 mL of 1 M MgSO4 stock solution, and 25 mL of 1M KH2PO4, pH 6.0 stock solution.
Note: Let cholesterol stock solution (5 mg/mL) reach room temperature and ensure cholesterol re-dissolves in solution before adding to NGM.
Cover and put back on stir plate for one minute.
Pour into 60 mm Petri dishes.
Let cool and store upside down in a plastic box, with lid at 4°C.
Acknowledgments
This work was supported in part by the Infectious Diseases Society of America, The National Institutes of Health (R03AG070580-01), and Start-up funding provided by the Microbiology and Cell Science Department at the University of Florida Institute of Food and Agricultural Sciences to DMC. Walker et al. (2021) is the original research paper from where this protocol was derived. The Graphical Abstract figure was created using BioRender.com.
Competing interests
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have declared that no competing interests exist.
References
Cohen, E., Yemini, E., Schafer, W., Feitelson, D. G. and Treinin, M. (2012). Locomotion analysis identifies roles of mechanosensory neurons in governing locomotion dynamics of C. elegans. J Exp Biol 215(Pt 20): 3639-3648.
Winter, P. B., Brielmann, R. M., Timkovich, N. P., Navarro, H. T., Teixeira-Castro, A., Morimoto, R. I. and Amaral, L. A. (2016). A network approach to discerning the identities of C. elegans in a free moving population. Sci Rep 6: 34859.
Mohri-Shiomi, A. and Garsin, D. A. (2008). Insulin signaling and the heat shock response modulate protein homeostasis in the Caenorhabditis elegans intestine during infection. J Biol Chem 283(1): 194-201.
Morley, J. F., Brignull, H. R., Weyers, J. J. and Morimoto, R. I. (2002). The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans. Proc Natl Acad Sci U S A 99(16): 10417-10422.
Brignull, H. R., Moore, F. E., Tang, S. J. and Morimoto, R. I. (2006). Polyglutamine proteins at the pathogenic threshold display neuron-specific aggregation in a pan-neuronal Caenorhabditis elegans model. J Neurosci 26(29): 7597-7606.
MacLeod, A. R., Waterston, R. H., Fishpool, R. M. and Brenner, S. (1977). Identification of the structural gene for a myosin heavy-chain in Caenorhabditis elegans. J Mol Biol 114(1): 133-140.
Walker, A. C., Bhargava, R., Vaziriyan-Sani, A. S., Pourciau, C., Donahue, E. T., Dove, A. S., Gebhardt, M. J., Ellward, G. L., Romeo, T. and Czyz, D. M. (2021). Colonization of the Caenorhabditis elegans gut with human enteric bacterial pathogens leads to proteostasis disruption that is rescued by butyrate. PLoS Pathog 17(5): e1009510.
Gidalevitz, T., Ben-Zvi, A., Ho, K. H., Brignull, H. R. and Morimoto, R. I. (2006). Progressive disruption of cellular protein folding in models of polyglutamine diseases. Science 311(5766): 1471-1474.
Wollenberg, A. C., Visvikis, O., Alves, A.-M. F. and Irazoqui, J. E. (2013). Staphylococcus aureus Killing Assay of Caenorhabditis elegans. Bio-protocol 3(19): e916.
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4,437 | https://bio-protocol.org/en/bpdetail?id=4437&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
Plasma Membrane Wounding and Repair Assays for Eukaryotic Cells
SS Stine Lauritzen Sønder
ME Malene Laage Ebstrup
CD Catarina Dias
AH Anne Sofie Busk Heitmann
JN Jesper Nylandsted
Published: Vol 12, Iss 11, Jun 5, 2022
DOI: 10.21769/BioProtoc.4437 Views: 1917
Reviewed by: Alka Mehra Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Science Advances Jul 2021
Abstract
Damage to the plasma membrane and loss of membrane integrity are detrimental to eukaryotic cells. It is, therefore, essential that cells possess an efficient membrane repair system to survive. However, the different cellular and molecular mechanisms behind plasma membrane repair have not been fully elucidated. Here, we present three complementary methods for plasma membrane wounding, and measurement of membrane repair and integrity. The first protocol is based on real time imaging of cell membrane repair kinetics in response to laser-induced injury. The second and third protocols are end point assays that provide a population-based measure of membrane integrity, after either mechanical injury by vortex mixing with glass beads, or by detergent-induced injury by digitonin in sublytic concentrations. The protocols can be applied to most adherent eukaryotic cells in culture, as well as cells in suspension.
Keywords: Cell injury Plasma membrane damage Membrane wounding Plasma membrane repair assays Imaging Membrane integrity
Background
Unlike prokaryotic cells, which are protected by a cell wall, eukaryotic cells lack this shield, and are thus more vulnerable to membrane lesions (Cooper and McNeil, 2015). The plasma membrane of eukaryotic cells is composed of a phospholipid bilayer with integrated transmembrane proteins, which essentially constitutes the physical barrier separating the cell from the extracellular environment, and sustains an essential osmotic gradient to the outside (Khan et al., 2013). The integrity of the plasma membrane is frequently compromised during the lifetime of most cells by different means. Cells that reside in mechanically active tissue environments, e.g., muscle and lung cells, frequently experience injuries to their plasma membrane (McNeil and Khakee, 1992; Gajic et al., 2003). Both mechanical stresses and chemical stresses, such as pore-forming toxins secreted by invading pathogens (Bischofberger et al., 2009), can each induce membrane damage, which poses an immediate threat to cell survival if not repaired. Hence, cells have developed effective plasma membrane repair mechanisms to cope with membrane injuries and ensure cellular homeostasis. Repair mechanisms are strictly dependent on the influx of extracellular calcium ions (Ca2+) into the cell through the wound, and involve several cellular processes, including cytoskeleton reorganization (Abreu-Blanco et al., 2011b), exocytosis (Bi et al., 1995; Andrews et al., 2014), endocytosis (Idone et al., 2008), and membrane shedding (Scheffer et al., 2014; Jimenez et al., 2014; Sønder et al., 2019). The different repair mechanisms appear to be utilized in combination, depending on the kind of injury imposed on the membrane (Cooper and McNeil, 2015; Boye and Nylandsted, 2016). Furthermore, the influx of extracellular Ca2+ triggers rapid recruitment of various Ca2+-activated repair proteins to the damaged membrane, including members of the annexin family, which are directly involved in the immediate repair response, to seal the hole within seconds (A. K. McNeil et al., 2006; Bouter et al., 2011; Jaiswal et al., 2014; Boye et al., 2017; Sønder et al., 2019). The early repair responses occur within seconds to a few minutes after injury, and both the efficiency and underlying mechanisms of repair determine cellular fate: either cell death, or successful cell repair and restructuring. After initial membrane resealing, where annexins play a major role, cells need to restructure and remove damaged membrane, involving both exocytic and endocytic events, including macropinocytosis. To this end, we recently found that breast cancer cells use macropinocytosis coupled to components of the non-canonical autophagy system (a process termed LC3-associated macropinocytosis), to remove damaged parts of the plasma membrane, and restore membrane integrity (Sønder et al., 2021).
As loss of cell membrane integrity in vivo occurs due to a variety of physiological stressors, several experimental methods have been developed to mimic these conditions. These methods include cell-confined induced injury by passing cells through a narrow bore syringe, scraping attached cells from the substrate, or exposing cell monolayers to rolling glass beads (P. L. McNeil, 2001; P. L. McNeil et al., 2001; Corrotte et al., 2015; Jaiswal et al., 2014). However, these injury methods can be challenging to reproduce exactly, as they depend, for example, on the forces that are applied to the syringe, the cell confluency before scraping, or rolling with glass beads, resulting in great variability in the population of injured cells between samples. On the other hand, more controlled membrane lesions can be obtained using bacterial pore-forming toxins, e.g., Streptolysin O (SLO), which results in approximately 30 nm pores (Tweten, 2005; Idone et al., 2008). However, approaches using pore-forming toxins do not mimic mechanically-induced injuries in vivo, as these toxins chemically alter the cell membrane, by extracting lipids such as cholesterol (Gonzalez et al., 2008; Babiychuk et al., 2011). Thus, the choice of injury type is of great importance, since it can affect what can be learned about the repair response.
The first protocol presented here (Protocol A) is a method to monitor cell membrane repair kinetics in living cells, following UV ablation laser-induced plasma membrane injury. The two following protocols (Protocol B and Protocol C) are end point assays that can be used to identify, e.g., a deficit in the repair ability in different cellular conditions. Laser-induced injury is a very useful experimental approach, as it creates localized and well controlled injuries, which can be combined with live-cell imaging to follow fluorescently tagged proteins during the repair process (Jaiswal et al., 2014; Sønder et al., 2019). The laser injury approach has been used for monitoring cell membrane repair in various studies, in both mammalian and invertebrate organisms (McNeil et al., 2003; Abreu-Blanco et al., 2011a).
To analyze the extent of membrane damage and the kinetics of membrane repair, different fluorescent membrane impermeable dyes can be applied, including Hoechst 33258, propidium iodide (PI), FM1-43, and FM4-64. When the membrane is breached, Hoechst 33258 and PI, which are both membrane impermeant, can enter the cell and bind to nucleic acids. Here, the resulting fluorescence in the nuclei can be quantified as a measure of increased membrane permeability, i.e., poor membrane integrity. The FM dyes are styryl lipophilic dyes that increase in fluorescence intensity upon phospholipid binding. They will enter the cell through a membrane breach, thereby functioning as a read-out of the extent of injury and healing response, from which the repair kinetics can be calculated (Betz et al., 1996; Corrotte et al., 2015). However, FM dyes bind to the plasma membrane and are also taken up by the cell via endocytic mechanisms, which results in intense intracellular staining independent of membrane lesions over the long term. Thus, FM dyes are best suitable for measuring repair kinetics in short term assays. For long term assays, impermeable Hoechst 33258 or PI should be used instead, since these dyes only stain nucleic acids, and do not appear in internalized vesicles, as FM dyes do. For the laser-induced injury protocol, the cell membrane is injured by a high intensity single photon nanosecond pulsed laser, in presence of cell impermeant dye. The injury causes the impermeant dye to enter the cell, and repair restricts further dye entry, resulting in a fluorescence plateau. In contrast, failure to repair causes a continuous entry of the dye into the injured cell, and intracellular dye fluorescence will steadily increase.
The last two protocols presented here are end point assays, and provide a population-based measure for monitoring plasma membrane repair. End point assays are used to gain insight into the involvement of cellular and molecular processes in membrane repair. Their simplicity is an advantage when investigating novel repair proteins, and mechanisms involved in cellular repair, especially when investigating several conditions at the same time. However, the cellular repair response is a complex process that cannot be fully monitored without temporal resolution, which can be achieved using methods that enable controlled local injury of the cell membrane, and allow real time monitoring of the repair response. In both end point assays presented here, membrane integrity is measured using the membrane permeant dye Hoechst 33342, and membrane impermeant dye PI. By using a microscopy-based plate reader (Celigo® Imaging Cytometer), the number of total cells (Hoechst 33342 positive cells) and permeabilized cells (PI positive cells) are measured per well. An advantage of using image-based assays, to quantify membrane permeabilization and cell death, is that it provides information at the single cell level, as compared to enzymatic assays. In the first protocol, cells are mechanically injured by vortex mixing with glass beads (Protocol B), and in the second assay the cells are chemically injured using the detergent digitonin (Protocol C). Digitonin, a saponin from Digitalis purpurea (Sudji et al., 2015), is typically used in most laboratories to completely lyse cell membranes. However, it can also be used in sublytic concentrations, creating plasma membrane damage that can be repaired by cells (Boye et al., 2017; Heitmann et al., 2021). The exact mechanism of digitonin hole formation is still not clear, but known to be dependent on cholesterol in the membrane (Sudji et al., 2015). Therefore, the extent of membrane damage is dependent both on the cholesterol content in the plasma membrane, and digitonin concentration.
With these three protocols, we describe different plasma membrane wounding methods and membrane integrity assays. We have used these methods combined with siRNA knockdown of genes of interest, and pharmacological treatments [e.g., 5-(N-Ethyl-N-isopropyl) amiloride (EIPA), and trifluoperazine (TFP)], to elucidate the role of different repair proteins, including S100A11, and members of the annexin protein family, in membrane repair response to different types of injury (Jaiswal et al., 2014; Sønder et al., 2019; Boye et al., 2017; Heitmann et al., 2021; Sønder et al., 2021).
Protocol A: Plasma membrane repair kinetics upon laser injury in live cells
Materials and Reagents
RPMI 1640, without Phenol Red (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 32404014)
Trypsin, TrypLETM Express Enzyme (1×), no phenol red (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 12604013) (storage 4°C)
Fetal Bovine Serum (FBS) (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 10270106, 6%, storage 4°C)
GlutaMax (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 35050061, 2 mM, storage 4°C)
HEPES buffer solution stock 1 M (Sigma-Aldrich, catalog number: H3375, dissolved in H2O, storage 4°C)
Calcium-free imaging media (e.g., Hanks’ balanced salt solution (HBSS), without calcium, magnesium, nor phenol red (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 14175095, storage 4°C, use pre-heated to 37°C)
Cells tested in the current protocol
MCF7 human breast carcinoma cells
HeLa human cervix carcinoma cells
SH-SY5Y is a thrice-subcloned human cell line derived from the SK-N-SH neuroblastoma cell line
FM1-43 (Invitrogen, catalog number: T3163, 1.6 µM, store in aliquots -20°C)
FM4-64 (Invitrogen, catalog number: T13320, 2.5 µM, store in aliquots -20°C)
Propidium iodide (PI) (Sigma-Aldrich, catalog number: P4864, 0.5 µg/mL, stock 1 mg/mL, dissolved in H2O, storage 4°C)
Hoechst 33258 (Sigma-Aldrich, catalog number: 861405, 2.5 µg/mL, storage 4°C)
Cell imaging media (CIM) (see Recipes)
Equipment
Cell culture incubator set at 37°C, 5% CO2
35 mm, No. 1.0 Coverslip, 14 mm glass bottom, uncoated MatTek dish (MatTek Corporation, p35G-1.0-14-C)
Confocal microscope equipped with a spinning disk, ablation laser and a 63× water objective. In this protocol we use the following microscope and equipment:
Inverted microscope Eclipse Ti-E (Nikon) with a 63× water objective
UltraVIEW VoX Spinning Disk (PerkinElmer)
355 nm UV ablation laser (Rapp OptoElectronic)
Heated chamber (37°C) for live cell imaging
Software
Volocity software (PerkinElmers)
SysCon software (Rapp OptoElectronic)
Prism (GraphPad Software, Inc) or Microsoft Excel (Microsoft)
Procedure
A. Real time kinetics of plasma membrane repair following laser injury using live cell imaging
Seed 1 × 105 cells in a 35-mm MatTek imaging-culture dish with a glass bottom, and allow cells to adhere overnight in a cell culture incubator at 37°C.
Set up 2–3 dishes per condition. Depending on the cell line, the number of seeded cells should be adjusted to obtain approximately 50% confluency on the day of the experiment.
Optional step: Pretreat cells with an inhibitor, or apply siRNA to knockdown a gene of interest.
Next day (on the day of experiment) prepare imaging media: preheat cell imaging media (CIM, see Recipes) at 37°C.
Prepare FM dye solution in preheated CIM.
The optimal dye concentration varies between dyes and cell lines, and should be optimized. For MCF7 and HeLa cells, FM1-43 at 1.6 µM works well. In this example, we use the FM1-43 dye in MCF7 cells.
Note: Depending on your experimental setup, other impermeable dyes, such as FM4-63, impermeable Hoechst 33258, or PI, can be used as well.
Wash cells with preheated CIM, and add 1–2 mL of CIM containing the FM dye to the dish.
Place the dish in the microscope holder in the stage maintained at 37°C, and set the focus to visualize plasma membrane-associated FM dye (Figure 1A; and Videos 1 & 2). We use a 63× water objective in an inverted microscope Eclipse Ti-E (Nikon) equipped with a top incubator, to maintain a steady temperature.
Note: The following steps provide a general outline of the experiment. Details will change depending on the microscope used, so the user should get training for their particular setup before performing the experiment.
Select a 1–2 µm region of interest within the plasma membrane of any intact single cell, orient the laser to that region, and irradiate with a 355 nm UV ablation laser for <4 ns, using an optimal laser power. The laser power of the instrument should be adjusted, to obtain a reproducible and non-lethal injury.
Notes:
The ablation laser is always calibrated before starting the experiments. Settings of the ablation laser are instrument- and cell line-dependent, and must be optimized. In our laboratory, we use the following setting at our system for MCF7 and HeLa cells: 2.6% power, 200 Hz repetition rate, pulse energy >60 µJ, and pulse length <4 ns.
Our system allows making laser stripes, rectangles, and spot injuries. We use the spot laser injury consistently (laser injury site indicated by arrow in Figure 1A, or star on videos), with the laser settings indicated above. However, in other systems, e.g., 3i laser ablation system, the injury area can be adjusted at will.
When working with lasers, you should always have laser safety in place, especially when working with pulsed lasers, as these can reach very high power in each short pulse, making them very dangerous. Some safety precautions include having an incubation chamber with laser interlock, and laser safety goggles, which should be used when there is a risk of potential exposure to the eyes.
Monitor the repair kinetics by imaging every 5 s in bright field and epifluorescence, starting prior to injury, and continuing for 5 min following injury.
For a negative control (i.e., no repair), repeat steps A4–A8 using Ca2+-free CIM containing the FM dye. Repeat steps A7–A8 for at least 10 cells per condition, obtained in three independent experiments.
Note: If the assay is combined with any pre-treatment, the researcher should include samples with control cells without laser injury, to rule out plasma membrane injury resulting from the pre-treatment alone.
Images are acquired with the inverted microscope Eclipse Ti-E (Nikon) paired with the UltraVIEW VoX Spinning Disk (PerkinElmer), using the 63× water objective.
Data analysis
Representative data
Protocol A describes how to measure the kinetics of plasma membrane repair upon laser injury and subsequent repair in live cells, by monitoring the entry of FM dye in the cells.
To quantify plasma membrane permeability (a read-out of membrane integrity), measure the intracellular FM dye fluorescence intensity at a single cell level across time points, using appropriate imaging software, e.g., Volocity. The intracellular FM dye fluorescence intensity is measured by selecting a specific region of interest inside the cell at the site of injury (the region where FM dye starts entering the cell: area outlined by the white dashed line in Figure 1A). Calculate the change in fluorescence intensity (F/F0) during the course of imaging, by normalizing the fluorescence intensity for each time point (F) to the fluorescence intensity before injury (F0). At least 10 cells per condition should be measured.
Figure 1. Example of real time imaging of cell membrane repair in response to laser injury.
(A) MCF7 cells were injured by ablation with an UV laser in media containing FM1-43, and in the presence (top panel), or absence (bottom panel) of Ca2+. Representative images of injured MCF7 cells showing intracellular FM1-43 accumulation over time (before and after the injury). White arrows indicate injury sites, while yellow arrows indicate FM1-43 accumulation. The area outlined by the white dashed line illustrates the area used for FM1-43 fluorescence intensity quantification. See Videos 1 & 2. (B) Quantification of single cell membrane repair kinetics upon laser injury in a MCF7 cell, in media with or without Ca2+, measured as the change in FM1-43 dye fluorescence intensity (F/F0) over time, in the region where FM1-43 dye enters the cell (site of damage). The black arrow indicates the injury time point. Scale bar =4.6 µm.
Plot the mean or individual cell changes in fluorescence intensity (F/F0: y-axis) over time (x-axis) (Figure 1B). When representing as means, at least 10 cells per condition obtained from three independent experiments must be considered, and the standard error of mean (SEM) must be plotted. For statistical analysis, area under the curve (AUC) analysis followed by unpaired t-test with Welch’s correction are calculated. For example of quantification of more cells, and a plot representing mean fluorescence intensity, see Figure 1A in Sønder et al. (2021).
Representative images for each condition are selected at different time points starting before injury, to assemble a panel of images showing the influx of FM dye under the different conditions (with or without Ca2+) (Figure 1A). The representative images are annotated to demonstrate how the region of interest is selected (Figure 1A).
Video 1. Uptake of FM1-43 dye after laser injury in media with Ca2+ in a MCF7 cell
Video 2. Uptake of FM1-43 dye after laser injury in media without Ca2+ in a MCF7 cell
Notes
The FM dyes bind to lipid membranes, but does not diffuse across intact plasma membranes. However, FM dyes are also taken up by the cell via endocytosis, making the assay for measuring repair kinetics only suitable for short term assays. The timescale for performing the experiment depends on how fast the cell of choice is taking up the FM dye without any damage. In our laboratory, where we use MCF7 or HeLa cells, we normally only use a dish for laser-induced injury experiments for 20–30 min after addition of FM-dye; after this time, it becomes difficult to measure the additional influx of FM-dye after injury.
For long term assays, impermeable Hoechst 33258 or PI should be used. The assay can also be combined with different pre-treatments, such as trifluoperazine (TFP), or knockdown of a gene of interest by siRNAs. For examples where the assay is combined with different pre-treatments, see Sønder et al. (2019), Heitmann et al. (2021), and Sønder et al. (2021).
Recipes
Cell imaging media (CIM)
Colorless RPMI 1640 supplemented with 6% FBS, 2 mM GlutaMax, and 25 mM HEPES.
Protocol B: Membrane integrity following mechanical injury using vortex mixing with glass beads
Materials and Reagents
6-well cell culture plates or 10-cm cell culture dishes
Eppendorf tubes
Falcon tubes
96-well cell culture plates clear flat bottom
Multichannel pipette
RPMI 1640 (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 11875085)
Fetal Bovine Serum (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 10270106) (6%, storage 4°C)
Hanks’ balanced salt solution (HBSS), no calcium, no magnesium, no phenol red (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 14175095) (storage 4°C, use pre-heated to 37°C)
Trypsin, TrypLETM Express Enzyme (1×), no phenol red (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 12604013) (storage 4°C)
DPBS, no calcium, no magnesium (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 14190144) (storage 4°C)
Cells tested in the current protocol
MCF7 human breast carcinoma cells
HeLa human cervix carcinoma cells
MDA-MB-231 cells, originating from breast carcinoma
425-600 µm glass beads (Sigma-Aldrich, catalog number: G8772) (Storage RT)
bisBenzimide H 33342 trihydrochloride (hereafter Hoechst, catalog number: 33342) [Sigma-Aldrich, catalog number: B2261, 6.25 µg/mL, stock (25 mg/mL), dissolved in H2O}. Store at -20°C long term, and at 4°C for a short time, where it is stable for 1 month.
Propidium iodide (PI) [Sigma Aldrich, P4864, 0.25 µg/mL, stock (1 mg/mL), dissolved in H2O]. Store at 4°C.
Equipment
Balance
Cell culture incubator set at 37°C, 5 % CO2
V-shape reservoirs
Vortex mixer
Timer
Plate-based bright field and fluorescent imaging cytometer, with minimum two fluorescent channels (excitation 377/50 and emission 477/22, and excitation 531/40 and emission 629/53), e.g., Celigo® Imaging Cytometer (Brooks Life Science Systems).
Software
Celigo Software (Brooks Life Science Systems)
Prism (GraphPad Software, Inc), or Microsoft Excel (Microsoft)
Procedure
B. Membrane integrity following mechanical injury using vortex mixing with glass beads
Note: All cell culture incubations should be performed in a humidified 37°C, 5% CO2 incubator, unless otherwise specified. See Figure 2A for flowchart of the protocol.
Prepare 1.5-mL Eppendorf tubes with 250 mg glass beads (425–600 µm).
Note: Prepare at least three Eppendorf tubes per cell line per condition.
Seed an appropriate amount of cells in either a 6-well culture plate, or 10-cm culture dish, depending on the experiment.
Note: The cells should not be more than 80% confluent on the day of the experiment.
Optional step: Pretreat cells with an inhibitor, or perform siRNA knockdown of a gene of interest.
On the day of experiment, trypsinize adherent cells of interest.
Remove all media from the cell culture dish.
Wash the adherent cell monolayer once, with a small volume of DPBS without Ca2+ and Mg2+, to remove any residual FBS that may inhibit the action of trypsin.
Note: Wash cells in a buffered salt solution that is Ca2+- and Mg2+-free, as Ca2+ and Mg2+ in the salt solution can cause cells to stick together.
Add enough trypsin to the cell culture, to cover the adherent cell layer.
Incubate cells in a cell culture incubator for 2–5 min.
Tap the bottom of the plate on the countertop to dislodge cells.
Note: Check the cell culture with an inverted microscope to be sure that cells are rounded up and detached from the surface. If cells are not sufficiently detached, return the cell culture to the incubator for an additional minute or two.
Add appropriate culture media, and resuspend the cells.
Count cells and separate them into two falcon tubes, one tube for cells in media with Ca2+, and one tube for cells in media without Ca2+
Note: If the cells have been pretreated with an inhibitor or by siRNA knockdown of a gene of interest, they should be counted for each condition.
Spin the cells down at 300 × g at room temperature for 4 min, and resuspend cells in media, either with or without Ca2+. HEPES is added to both falcon tubes to a final concentration of 25 mM.
Load 7 × 104 cells in suspension with 250 mg glass beads (425–600 µm) in a 1.5-mL Eppendorf tube, at a density of 200,000 cells/mL.
Notes:
The number of cells should be optimized for different cell lines. The appropriate number of cells needs to be loaded to the glass beads in a volume of 350–400 µL. For MCF7 and HeLa cells, we use 7 × 104 cells in suspension with 250 mg glass beads (425–600 µm), loading 350 µL resuspended cells at a density of 200,000 cells/mL on the glass beads.
As negative control of no repair, include samples with cells in Ca2+-free media loaded on glass beads.
Incubate tubes in a cell culture incubator for 10 min.
Note: The cells are incubated to maintain optimal cell conditions, including temperature (37°C), before injury by vortex mixing.
Meanwhile, add 50 µL of media, either with or without Ca2+, to the respective wells in a 96-well plate.
Injure the cells by vortex mixing at maximum speed for 0, 30, or 60 s.
The vortex time might need optimization, as some types of cells are more fragile than others, and the repair efficiency also varies between different cell lines. The optimal vortex time should result in 10–30% permeabilized cells in media with Ca2+ without any other pre-treatment, since most cells need to be able to repair their membrane damage in this condition. This balance results from the fact that a certain amount of cells need to be permeabilized to ensure that the cells have been damaged, but, on the other hand, there should still be room for an increase in permeabilized cells, when other conditions where the cells are compromised in their membrane repair are included in the assay.
Immediately after injury, plate 10,000 cells per well in a 96-well plate. Make triplicates for each condition. Shake the plate by hand to distribute the cells in the wells.
Note: Each 96-well should contain 50 µL of media with resuspended cells (10,000 cells), and the 50 µL culture media added in step B9.
Incubate the 96-well plate in a cell culture incubator for 5 min, for the cells to repair.
Prepare PI and Hoechst 33342 dye mix, in media with and without Ca2+.
Note: Final concentrations should be 0.25 µg/mL PI, and 6.25 µg/mL Hoechst 33342.
Carefully add 50 µL of the respective PI/Hoechst dye mix to the respective wells in the 96-well plate, and incubate in a cell culture incubator for 5 min.
Measure membrane integrity using an imaging cell cytometer (e.g., Celigo®), by determining membrane integrity using the number of total cells (Hoechst 33342 positive cells: excitation 350 nm, emission 461 nm), and the number of permeabilized cells (PI positive cells: excitation 535 nm, emission 617 nm) per well.
The Celigo® is a multichannel imaging cell cytometer that can be used to perform whole-well live cell analysis, using optical microscopy. In this experiment, cells are labeled with permeable Hoechst 33342 dye, and impermeable PI dye, prior to scanning and analysis. The cytometer scans the selected area, e.g., a 96-well in the selected channels. The software can then be used to identify labeled cells in the selected channel, thereby calculating the number of total cells (Hoechst positive cells), and the number of permeabilized cells (PI positive cells).
Note: The user should get particular training in their equipment before setting up the experiment.
Data analysis
Representative data
Protocol B describes how to monitor membrane integrity after mechanical-induced injury by vortex mixing with glass beads.
Calculate the mean values of the triplicate measurements for PI (permeabilized cells) and Hoechst 33342 (total cells) positive cells.
Calculate the percentage of permeabilized cells per condition, by relating the total number of PI positive cells to the total number of Hoechst 33342 positive cells per condition. For statistical analysis, at least three independent experiments should be performed, and standard deviations should be plotted. For examples where statistical analysis has been applied, and the assay is combined with different pre-treatments, see Heitmann et al. (2021), and Sønder et al. (2021).
Figure 2. Example of membrane integrity assay, following mechanically-induced injury by vortex with glass beads.
(A) Flowchart of the protocol. (B) Membrane integrity assay sample setup in a typical 96-well format in media with and without Ca2+. (C) Plasma membrane integrity in MCF7 cells in suspension exposed to vortex with glass beads for 0, 0.5, or 1 min, in media with or without Ca2+. The percentage of permeabilized cells is calculated based on the number of cells containing impermeable PI, and the total number of cells (detected by the permeable Hoechst 33342 dye). Data represent means of triplicate measurements, and error bars indicate SD values. The optimal vortex time is the time that results in 10–30% permeabilized cells for cells in media with Ca2+ without any other pre-treatment, since most cells need to be able to repair their membrane damage in this condition. Here, 1 min of vortex mixing is the optimal vortex time for MCF7 cells, as this results in approximately 12% permeabilized cells in media with Ca2+ after vortex mixing with glass beads.
Notes
The assay can also be combined with different pre-treatments, e.g., inhibitors of different biological processes, such as 5-(N-Ethyl-N-isopropyl) amiloride (EIPA), that inhibits macropinocytosis, or e.g., knockdown of a gene of interest by siRNAs. For examples where the assay is combined with different pre-treatments, see Heitmann et al. (2021), and Sønder et al. (2021).
Protocol C: Membrane integrity following detergent induced injury using digitonin
It should be noted that the ability of digitonin to permeabilize cellular membranes depends not only on the digitonin concentration, but also on the total amount of digitonin molecules per cell. Thus, digitonin should always be used in the same volume per cell.
Materials and Reagents
Eppendorf tubes
96-well cell culture plates clear flat bottom
Multichannel pipette
RPMI 1640 (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, 11875085)
Fetal Bovine Serum (Gibco® by Life Technologies, purchased via Thermo Fisher Scientific, catalog number: 10270106) (6%, storage 4°C)
Cells tested in the current protocol
MCF7 human breast carcinoma cells
HeLa human cervix carcinoma cells
NCI-H1299 originating from non-small-cell lung cancer
MDA-MB-231 cells originating from breast carcinoma
Digitonin (Sigma-Aldrich), Digitonin Stocks (5 and 50 mg/mL), dissolved in H2O. Store at -20°C. Digitonin usually precipitates, and must be redissolved by heating and occasional vortexing. Immediately before use, heat the digitonin stock to 95°C for 5 min, to dissolve precipitates.
Hoechst 33342 (Sigma-Aldrich, catalog number: B2261, 6.25 µg/mL, stock (25 mg/mL), dissolved in H2O. Store at -20°C long term, and 4°C short time (stable for 1 month).
Propidium iodide (PI) (Sigma-Aldrich, catalog number: P4864, 0.25 µg/mL, stock (1 mg/mL), dissolved in H2O. Store at 4°C.
Equipment
Cell culture incubator set at 37°C, 5% CO2
V-shape reservoirs
Vortex mixer
Heat block
Timer
Plate-based bright field and fluorescent imaging cytometer, with a minimum of two fluorescent channels (excitation 377/50 and emission 477/22, and excitation 531/40 and emission 629/53), e.g., Celigo® Imaging Cytometer (Brooks Life Science Systems)
Software
Celigo Software (Brooks Life Science Systems)
Prism (GraphPad Software, Inc) or Microsoft Excel (Microsoft)
Procedure
C. Membrane integrity following detergent induced injury using digitonin
Part 1: Determining the optimal digitonin concentration for creating plasma membrane damage that most cells are able to repair (see Figure 3A for flowchart of the protocol).
The following procedure is necessary to determine the optimal digitonin concentration for creating plasma membrane damage that can be repaired by most cells (~80%) in Ca2+ containing media, without any pre-treatments. The procedure should be performed regularly, as reagents (e.g., digitonin stocks) and cellular conditions may change over time. Performing this procedure ensures consistency of the number of injured cells, and reproducibility of the results obtained. The procedure should be performed for each cell line separately.
Seed 6 × 103 cells per well in 100 µL of culture media in a 96-well plate, and allow cells to adhere overnight in a cell culture incubator at 37°C. Make two plates: one plate is used for determining optimal digitonin concentration, and the other plate is used for measuring membrane integrity.
Adjust the number of cells per well for each cell line, as the cells need to be 50% confluent on the day of the experiment.
Immediately before use, heat up the digitonin stock (5 µg/µL) to 95°C for 5 min to dissolve any precipitates.
Note: Digitonin usually precipitates and needs to be redissolved by heating and occasional mixing by vortexing.
Prepare the following ten dilutions of digitonin in preheated culture media (37°C): 0, 5, 7.5, 10, 12.5, 15, 20, 25, 30, and 100 µg/mL digitonin,
Note: A digitonin solution of 100 µg/mL is used for total/complete permeabilization of cells.
Add 100 µL of digitonin dilutions per well in triplicates. Add the digitonin solution to the side of the well to avoid detachment of adherent cells.
Incubate in a cell culture incubator at 37°C for 30 min. In the meanwhile, prepare media with PI and Hoechst 33342 dye dilutions; the final concentrations should be: 0.25 µg/mL PI, and 6.25 µg/mL Hoechst 33342.
Carefully add 50 µL of PI/Hoechst dye mix to each well in the 96-well plate, and incubate in a cell culture incubator for 5 min.
Measure membrane integrity using the Celigo® cytometer, by measuring the number of total cells [Hoechst 33342 (excitation 350 nm, emission 461 nm) positive cells] and the number of permeabilized cells [PI (excitation 535 nm, emission 617 nm) positive cells] per well.
Determine optimal digitonin concentration.
Calculate the percentage of PI positive cells for the different conditions. The digitonin concentration that enables approximately 80% of the cells to repair [i.e., around 20 % of permeabilized cells (PI positive)] is optimal.
In this example, where MCF7 cells are treated with digitonin for 30 min, an optimal digitonin concentration is 7.5–10 µg/mL (see Figure 3C).
Part 2: Measuring membrane integrity following detergent induced injury using digitonin
In the following procedure, the membrane integrity is measured for cells treated with digitonin in media with or without Ca2+. The assay can also be combined with different pre-treatments, such as trifluoperazine (TFP), or knockdown of a gene of interest by siRNAs. For examples where the assay is combined with different pre-treatments, see Sønder et al. (2019), and Heitmann et al. (2021). See Figure 4A for a flowchart of the protocol.
Optional step: pretreat cells with an inhibitor.
Prepare digitonin solutions (using the optimal concentration obtained in step C8) in media containing Ca2+ and in Ca2+-free media. Immediately before use, heat up the digitonin stock (5 µg/µL) to 95°C for 5 min, to dissolve any precipitates.
Notes:
Digitonin usually precipitates and needs to be redissolved by heating and occasional mixing by vortexing.
As negative control (i.e., no repair) include samples with cells in Ca2+-free media.
Wash cells twice in HBSS without Ca2+. In the final wash, only add HBSS without Ca2+ to the wells that will be treated with digitonin in media without Ca2+. The rest of the wells should contain normal culture media.
Add 100 µL of each digitonin dilution per well, in triplicates, as descripted in step C4. Add the digitonin solution to the side of the well to avoid detachment of adherent cells.
Incubate in a cell culture incubator at 37°C for 30 min. In the meanwhile, prepare PI and Hoechst 33342 dye dilutions, in media with and without Ca2+. The final concentrations should be 0.25 µg/mL PI, and 6.25 µg/mL Hoechst 33342.
Carefully add 50 µL of the respective PI/Hoechst dye mixes to the respective wells in the 96-well plate, and incubate in a cell culture incubator for 5 min.
Measure membrane integrity using an imaging cell cytometer (e.g., Celigo®) by determining membrane integrity using the number of total cells (Hoechst 33342 positive cells: excitation 350 nm, emission 461 nm) and the number of permeabilized cells (PI positive cells: excitation 535 nm, emission 617 nm) per well.
The Celigo® is a multichannel imaging cell cytometer that can be used to perform whole-well live cell analysis using optical microscopy. In this experiment, cells are labeled with permeable Hoechst 33342 dye and impermeable PI dye, prior to scanning and analysis. The cytometer scan the selected area, e.g., a 96-well in the selected channels. Then, the software can be used to identify labeled cells in the selected channel, and thereby calculating the number of total cells (Hoechst positive cells) and the number of permeabilized cells (PI positive cells).
Note: The user should get particular training in their equipment before setting up the experiment.
Data analysis
Representative data
Protocol C describes how to monitor membrane integrity of cells after chemical-induced injury by the detergent digitonin. First, the optimal digitonin concentration for creating plasma membrane damage that can be repaired by the cells is determined.
Calculate the mean values of the triplicate measurements for PI (permeabilized cells) and Hoechst (total cells) positive cells per condition.
Calculate the percentage of permeabilized cells per condition, by relating the total number of PI positive cells to the total number of Hoechst positive cells. For statistical analysis, at least three independent experiments should be performed, and standard deviations should be plotted. For examples where statistical analysis has been applied, and the assay is combined with a pre-treatment, see Heitmann et al. (2021).
Representative images for each condition are selected to assemble a panel of images showing the incorporation of Hoechst 33342 and PI dye at a single cell level in the presence and absence of Ca2+, before and after digitonin treatment (Figure 4D).
Figure 3. Example of an optimization experiment, used to determine the optimal digitonin concentration for a membrane integrity assay using MCF7 cells.
(A) Flowchart of the protocol. (B) Membrane integrity assay sample setup in a typical 96-well format for determining optimal digitonin concentration. 6 × 103 MCF7 cells per well were seeded in a 96-well plate. (C) Plasma membrane integrity in MCF7 cells treated with digitonin in indicated concentrations, or left untreated in media with Ca2+ for 30 min. The percentage of permeabilized cells is assayed using cell impermeable PI and permeable Hoechst 33342 dye (i.e., by calculating the number of PI positive cells relative to the total number of Hoechst 33342 positive cells) for each condition. Numbers represent mean of triplicate measurements, and error bars indicate SD values. All cells were permeabilized already at 30 µg/mL digitonin. A digitonin concentration that creates plasma membrane damage that can be repaired by most cells (approximately 80%) is determined. Here, 7.5–10 µg/mL is optimal for MCF7 cells.
Figure 4. Example of membrane integrity assay following digitonin-induced injury.
(A) Flowchart of the protocol. (B) Membrane integrity assay sample setup in a typical 96-well format in media without and with Ca2+. (C) Plasma membrane integrity in MCF7 cells treated with 7.5 or 10 µg/mL digitonin, or left untreated in media with or without Ca2+ for 30 min. The percentage of permeabilized cells is assayed using cell impermeable PI and permeable Hoechst 33342 dyes, and calculated by relating the measurement for PI to the measurement for Hoechst positive cells for each condition. Numbers represent means of triplicate measurements, and error bars indicate SD values. (D) Representative images showing the incorporation of Hoechst 33342 and PI dyes at a single cell level in the presence and absence of Ca2+, before and after digitonin treatment (7.5 µg/mL digitonin for 30 min). Scale bar = 500 µm.
Notes
The above methods must be used with care, when using treatment that influences cellular cholesterol content, or drugs that have detergent-like properties, such as cationic amphiphilic drugs (CADs) (Petersen et al., 2013), as such treatment may interfere with the digitonin damaging ability. Protocol C describes how membrane integrity following detergent induced injury using digitonin is measured. However, this protocol can also be adjusted to study membrane integrity following toxin-induced injury, by substituting digitonin treatment with treatment with SLO, or another pore-forming toxin.
Acknowledgments
The protocols presented here were applied in our recent papers (Sønder et al., 2021; Heitmann et al., 2021; and Sønder et al., 2019). We thank both present and former colleagues from the Membrane Integrity Group, Danish Cancer Society Research Center, for optimizing and fine tuning the methods presented here. Further, we thank colleagues and collaborators within the membrane repair field for sharing their methods and knowledge, in particular Jyoti K. Jaiswal, Children’s National Research Institute. The work was supported by the Danish Council for Independent Research (6108-00378A, 9040-00252B), the Novo Nordisk Foundation (NNF18OC0034936), and the Scientific Committee Danish Cancer Society (R90-A5847-14-S2, R269-A15812).
Competing interests
The authors have nothing to disclose.
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McNeil, A. K., Rescher, U., Gerke, V. and McNeil, P. L. (2006). Requirement for annexin A1 in plasma membrane repair. J Biol Chem 281(46): 35202-35207.
McNeil, P. L. (2001). Direct introduction of molecules into cells. Curr Protoc Cell Biol Chapter 20: Unit 20 21.
McNeil, P. L., Clarke, M. F. and Miyake, K. (2001). Cell wound assays. Curr Protoc Cell Biol Chapter 12: Unit 12 14.
McNeil, P. L. and Khakee, R. (1992). Disruptions of muscle fiber plasma membranes. Role in exercise-induced damage. Am J Pathol 140(5): 1097-1109.
McNeil, P. L., Miyake, K. and Vogel, S. S. (2003). The endomembrane requirement for cell surface repair. Proc Natl Acad Sci U S A 100(8): 4592-4597.
Petersen, N. H., Olsen, O. D., Groth-Pedersen, L., Ellegaard, A. M., Bilgin, M., Redmer, S., Ostenfeld, M. S., Ulanet, D., Dovmark, T. H., Lonborg, A., et al. (2013). Transformation-associated changes in sphingolipid metabolism sensitize cells to lysosomal cell death induced by inhibitors of acid sphingomyelinase. Cancer Cell 24(3): 379-393.
Scheffer, L. L., Sreetama, S. C., Sharma, N., Medikayala, S., Brown, K. J., Defour, A. and Jaiswal, J. K. (2014). Mechanism of Ca2+-triggered ESCRT assembly and regulation of cell membrane repair. Nat Commun 5: 5646.
Sudji, I. R., Subburaj, Y., Frenkel, N., Garcia-Saez, A. J. and Wink, M. (2015). Membrane Disintegration Caused by the Steroid Saponin Digitonin Is Related to the Presence of Cholesterol. Molecules 20(11): 20146-20160.
Sønder, S. L., Boye, T. L., Tölle, R., Dengjel, J., Maeda, K., Jäättelä, M., Simonsen, A. C., Jaiswal, J. K. and Nylandsted, J. (2019). Annexin A7 is required for ESCRT III-mediated plasma membrane repair. Sci Rep 9(1): 6726.
Sønder, S. L., Häger, S. C., Heitmann, A. S. B., Frankel, L. B., Dias, C., Simonsen, A. C. and Nylandsted, J. (2021). Restructuring of the plasma membrane upon damage by LC3-associated macropinocytosis. Sci Adv 7(27): eabg1969
Tweten, R. K. (2005). Cholesterol-dependent cytolysins, a family of versatile pore-forming toxins. Infect Immun 73(10): 6199-6209.
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Assessing the Presence of Hematopoietic Stem and Progenitor Cells in Mouse Spleen
IM Isabelle J. Marié
LB Lara Brambilla
DL David E. Levy
Published: Vol 12, Iss 11, Jun 5, 2022
DOI: 10.21769/BioProtoc.4438 Views: 2071
Reviewed by: Chiara AmbrogioDhruv Rajanikant PatelKuo-Ching "KC" Mei
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Original Research Article:
The authors used this protocol in eLIFE Aug 2021
Abstract
Transplantation of hematopoietic material into recipient mice is an assay routinely used to determine the presence and function of hematopoietic stem and progenitor cells (HSPCs) in vivo. The principle of the method is to transplant donor cells being tested for HSPCs into a recipient mouse following bone marrow ablation and testing for reconstitution of hematopoiesis. Congenic mouse strains where donor and recipient differ by a distinct cell surface antigen (commonly CD45.1 versus CD45.2) are used to distinguish between cells derived from the donor and any residual recipient cells. Typically, the transplantation is performed using bone marrow cells, which are enriched for HSPCs. Here, we describe an analogous procedure using hematopoietic material from spleen, allowing detection of functional progenitors and/or stem cells in the spleen that can occur under certain pathologies. Key to the success of this procedure is the prior removal of mature T cells from the donor sample, to minimize graft versus host reactions. As such, this protocol is highly analogous to standard bone marrow transplant procedures, differing mainly only in the source of stem cells (spleen rather than bone marrow) and the recommendation for T cell depletion to avoid potential immune incompatibilities.
Graphical abstract:
Schematic overview for assessment of stem cells in spleen by transplantation. Single cell suspensions from spleens are depleted of potentially pathogenic mature T lymphocytes by magnetic bead immunoselection using biotinylated antibodies against CD4 and CD8, followed by streptavidin magnetic beads, which are subsequently removed by using a magnet (MojoSort, Biolegend). Successful T cell depletion is then evaluated by Fluorescence Activated Cell Sorting (FACS). T-cell depleted cell suspension is injected intravenously through the retro-orbital sinus into lethally irradiated recipients. Recipients are analyzed for successful engraftment by FACS analysis for the presence of donor-derived mature hematopoietic lineages in the peripheral blood. A second serial transplantation can be used to document the presence of long-term reconstituting stem cells in the periphery of the original donor mice.
Keywords: Spleen transplantation Hematopoiesis Hematopoietic stem cells Hematopoietic progenitor cells T cell depletion Inflammatory disease
Background
The hematopoietic system of mice can be regenerated from hematopoietic stem and progenitor cells (HSPCs). In adult mice, HSPCs largely reside in the bone marrow, where they are maintained in a largely quiescent state. However, during some inflammatory pathologies, HSPCs become mobilized and can colonize various peripheral lymphoid organs, such as spleen. Definitive assessment of the presence and function of HSPCs is accomplished by observing their ability to reconstitute the full hematopoietic system of an irradiated recipient mouse (so the HSPCs of the recipient mouse are depleted) following transplantation. Committed progenitors will give rise to only a subset of hematopoietic lineages in this assay, while true hematopoietic stem cells (HSCs) will be capable of reconstituting all mature blood lineages. Stem cells with long-term reconstitution ability can be distinguished from short-term stem cells by secondary transplantation. While short-term HSCs are capable of reconstituting hematopoiesis in an initial transplant, only long-term HSCs will give rise to pluripotent stem cells that are capable of reconstituting a secondary recipient.
The present protocol, adapted from a recent publication (Marié et al., 2021), describes a method for assessing the presence of HSPCs in mouse spleens by serial engraftment in recipient mice whose hematopoietic system has been ablated by x-ray irradiation. Antigenic differences between donor and recipients allow the detection of donor cells following engraftment by a simple flow cytometry analysis. Flow cytometry is also used to assess the presence of major hematopoietic lineages derived from donor cells through analysis of characteristic cell surface markers. Following primary reconstitution, the presence of short-term versus long-term HSPCs can be assessed by conducting a secondary engraftment and observing the reconstitution of hematopoietic lineages in the secondary recipients. Moreover, the ability of the donor HSPCs to home to the bone marrow versus secondary lymphoid organs can be assessed by performing secondary reconstitutions with cells derived from either bone marrow or spleen. In all transplantations involving cells from peripheral organs, it is essential to deplete mature T lymphocytes to minimize graft versus host reactions. A potential limitation of this technique is that its sensitivity has not yet been strictly defined. At present, the minimum threshold of stem cell abundance in the spleen capable of triggering a successful transplant needs to be defined. This limitation could be addressed by including serial dilution studies.
Materials and Reagents
35 mm culture dish (Falcon, catalog number: 3001)
3 mL syringe (BD Biosciences, catalog number: 305270)
1 mL syringes (BD, catalog number: 320933)
15 mL conical tubes (BD Biosciences, Falcon®, catalog number: 352196)
50 mL conical tubes (BD Biosciences, Falcon®, catalog number: 430829)
70 μM nylon strainers (BD Biosciences, Falcon®, catalog number: 352350)
Eppendorf tubes 1.5 mL (Axygen®, catalog number: MCT-175-C)
FACS tubes 5 mL (BD Biosciences, catalog number: 352054)
C57BL6 (CD45.2) donor mice (bred in our laboratory by mating a male and a female both CD45.2)
C57BL6 (CD45.1) recipient mice (bred in our laboratory by mating a male and a female both CD45.1)
Antibiotic suspension of Sulfamethoxazole (40 mg/mL) and Trimethoprim (8 mg/mL) in 0.03% ethanol, Ani Pharmaceuticals
Phosphate Buffered Saline (PBS) (without Ca2+ and Mg2+) (Sigma-Aldrich, catalog number: D8537)
BV711 mouse anti-mouse CD45.1 (cloneA20) (Biolegend, catalog number: 110739) 0.2 mg/mL
BV605 mouse anti-mouse CD45.2 (clone104) (Biolegend, catalog number: 109841) 0.2 mg/mL
Biotin rat anti-mouse CD4 (clone RM4-5) (Biolegend, catalog number:100508) 0.5 mg/mL
Biotin rat anti-mouse CD8a (clone 53-6.7) (Biolegend, catalog number: 100704) 0.5 mg/mL
PE Cy5 rat anti-mouse CD4 (clone RM4-5) (Biolegend, catalog number: 100514) 0.2 mg/mL
APC rat anti-mouse CD8a (clone 53-6.7) (Biolegend, catalog number: 100712) 0.2 mg/mL
PE Cy7 rat anti-mouse CD11b (M1/70) (Biolegend, catalog number: 101215) 0.2 mg/mL
APC-eFluor 780 rat anti-mouse B220 (RA3-6B2) (eBiosciences, catalog number: 47-0452-82) 0.2 mg/mL
Fetal Bovine Serum (FBS) (Gibco, catalog number: 10437-028)
Red Blood Cell (RBC) lysing buffer (BD PharmLyseTM lysing buffer, BD Biosciences, catalog number: 555899)
MojoSortTM Buffer (Biolegend, catalog number: 480017)
DMEM medium (Corning, Cellgro, catalog number: 10-013-CV)
MojoSortTM Streptavidin nanobeads (Biolegend, catalog number: 480016)
Needles (27G1/2) (BD Biosciences, catalog number: 305109)
Goldenrod animal lancet 5mm (Medipoint)
BD EDTA-coated Microtainer (BD Biosciences, catalog number: 365974)
FACS buffer (see Recipes)
Equipment
Forceps and sharp scissors
Inverted microscope
Ice bucket
Hemacytometer (Sigma-Aldrich, catalog number: Z359629-1EA)
Centrifuge (low-speed for 15 and 50 mL tubes)
Centrifuge for microcentrifuge tubes (1.5 mL)
MojoSort Magnet (Biolegend, catalog number: 480019), cooled at 4°C the day before
Mice Irradiation machine (Faxitron MR350 X-ray irradiator)
BD LSR II flow cytometer
Software
FACSDiva software
FlowJo software
Procedure
Part I: Transplantation of spleen cells
The following protocol has been adapted from the more traditional bone marrow transplantation protocol (Duran-Struuck and Dysko, 2009). Bone marrow transplantation is routinely used to assess the presence and efficiency of progenitors/stem cells in a given bone marrow sample. While normally virtually absent in the spleen, HSPCs may accumulate in the spleen during some pathological processes, for example, during inflammation, splenomegaly, or extramedullary hematopoiesis. Our protocol aims at detecting the presence of functional progenitors and/or stem cells in the spleen.
It is important to note that spleens contain more reactive T cells than bone marrow, which can lead to adverse effects during engraftment, such as graft versus host disease (Baker et al., 1996). To avoid such potential problems, mature T cells are depleted before transplantation.
Irradiation of host mice
The hematopoietic system of recipient mice is ablated by lethal irradiation applied in two fractional doses separated by 4 h.
Irradiate C57BL6 (CD45.1) 8- to 12-week-old host mice, 20 to 25 g, sex irrelevant (10 mice per transplantation group) with a first dose of 4.5 Gy total body irradiation (TBI), (Faxitron MR350 X-ray irradiator using SnCuAl filter) using a mouse irradiation pie cage (Figure 1). Following irradiation, supplement the drinking water with 1:200 dilution of antibiotic suspension of Sulfamethoxazole and Trimethoprim (Materials and Reagents #11).
Irradiate host mice with a second dose of 4.5 Gy 4 h later, just before transplantation. In the meantime, proceed to the preparation of donor material.
Figure 1. Mouse irradiation pie cage. Mice are placed in an irradiation pie cage prior to exposure to x-ray irradiation.
Preparation of donor material
The whole procedure has to be carried out under sterile conditions
Sacrifice C57BL6 donor mice (CD45.2) by CO2 euthanasia. Collect the spleen (Figure 2A) and place in PBS on ice. Trim away any remaining connective tissue or fat from the spleen.
Figure 2. Mouse bleeding, injection, and spleen recovery procedures. (A) Illustration of post-mortem spleen collection. (B) Fluid injection into the retro-orbital sinus. (C) Puncturing the submandibular vein with a lance. (D) Blood collection from a pierced submandibular vein.
Transfer the spleen into a sterile 35 mm culture dish containing 5 mL of FACS buffer (see Recipes below) or DMEM medium containing 2% FBS.
Remove the plunger from a 3 mL syringe. Use the flat rubber end of the plunger to crush the spleen by using gentle circular motions. This will disrupt the pulp and release the splenocytes.
Pass the 5 mL of cell suspension through a 70 μm nylon strainer fitted on top of a 50 mL conical tube to obtain a uniform single-cell suspension. Gently help the suspension pass through the strainer by pressing in a circular manner with the syringe plunger. A video presentation of this method can be seen at https://www.stemcell.com/prepare-single-cell-suspension-from-mouse-spleen.html.
Wash the 35 mm culture dish with 2 mL of FACS buffer or DMEM medium containing 2% FBS
and pass through the strainer. Repeat this step twice.
Centrifuge the tube at 300 × g for 10 min at 4°C.
Discard the supernatant and flick the tube to loosen the pellet. Resuspend the pellet in a volume of 200 μL to 1 mL of medium containing 3% FBS, depending on the spleen size, and store on ice.
Count the cells after diluting an aliquot of the cell suspension 1:100 with PBS. Count all nine squares of the hemacytometer under an inverted light microscope. One normal spleen (approximately 100 mg) typically produces around 100 million cells. We recommend using a live dye such as trypan blue (1:1 v/v) to exclude potential dead cells (Figure 3).
Note: Since the cell suspension has not undergone red blood cell lysis, it is important to make sure that the red blood cells (smaller than the white blood cells) are not counted (Figure 3).
The cell count per mL is the number of cells counted × dilution factor × 104 (the dilution factor being 100 in this case).
Figure 3. Peripheral blood cell counting with a hematocytometer. Viable leukocytes are counted on a hematocytometer grid. Red arrow points to a red blood cell, and black arrow points to a trypan blue-stained dead cell, neither of which are included in the leukocyte count.
T cell depletion
Transfer 108 cells resuspended in 500 μL of MojoSort Buffer into a 5 mL (12 × 75 mm) polystyrene tube. Add 5 μL each of biotin-anti CD4 and biotin-anti CD8a to the tube, mix well, and incubate on ice for 15 min.
Note: Keep a small aliquot (106 cells) of starting material prior to depletion (step B7) on ice, to be used from step 20 onward, to assess the extent of the depletion after the procedure.
Wash the cells by adding 3.5 mL of MojoSort buffer and centrifuge at 300 × g for 5 min at 4°C.
Discard the supernatant and resuspend in 500 μL of MojoSort Buffer.
Resuspend the Streptavidin Nanobeads by vortexing, at maximum speed, five touches. Add 50 μL of beads to the cell suspension, mix well, and incubate for 15 min on ice.
Wash the cells by adding 3 mL of MojoSort Buffer; Centrifuge at 300 × g for 5 min at 4°C, discard the supernatant and resuspend in 3 mL of MojoSort Buffer.
Place the tube in a cold MojoSort magnet (see Equipment) for 5 min.
Collect the cells by pouring out the liquid into a 15 mL conical tube. These are your cells of interest, depleted of T cells that are retained on the magnet.
To increase yield if needed, add 3 mL of MojoSort Buffer to the beads, repeat steps 16 and 17, and pool the flow-through fractions.
Count the cells obtained after depletion as indicated in steps B8 to B10.
Assessment of T cell depletion by FACS
Take an aliquot containing 100,000 to 500,000 cells from the sample set aside before T cell depletion (step B7) and from the T cell-depleted sample (step B18). Set up three additional tubes, one for unstained control and two for single color controls containing each 50,000 to 100,000 cells per tube.
Centrifuge the pre- and post- depletion samples, as well as the two single color controls at 200 × g for 5 min at 4°C. Resuspend the pre- and post- depletion samples in 50 μL of staining solution containing PeCy5 anti-mouse CD4 (diluted 1:250) and APC anti-mouse CD8a (diluted 1:250) in FACS buffer.
Resuspend one single color control in 50 μL of PeCy5 anti-mouse CD4 (diluted 1:250) and the other single color control in 50 μL of APC anti-mouse CD8a (diluted 1:250).
Incubate on ice for 15 to 30 min, protected from light.
Wash all tubes with 300 μL of FACS buffer by centrifugation.
Resuspend in 200 μL of FACS buffer and transfer to FACS tubes by passing through a mesh filter to remove any clumps of cells.
Analyze all tubes on a flow cytometer.
On the BD LSR II software, select 'New Experiment'.
Select for Area, Height, and Width for FSC and SSC; select for Log and Area for the colors Pe-Cy5 and APC.
Create compensation controls and adjust the gating for unstained blood cells (adjust FSC and SSC voltages as necessary).
Adjust each color of single stains in the voltage panel so that the positive peak is at the 104 mark.
Analyze single color controls.
Record the desired voltages after any adjustments for each of the single stains and then calculate compensation controls.
Events are now ready to be recorded. Set up to collect 5,000–10,000 events per sample for each pre- and post-depletion sample.
Note: Typically, the procedure depletes over 95% of CD4 and CD8 T cells. The overall depletion procedure is illustrated in the following video: https://www.youtube.com/watch?v=cH6rlIFNVp0.
Transplantation into irradiated mice
Centrifuge the cell suspension of T cell-depleted splenocytes for 5 min at 200 × g at 4°C, remove supernatant, and resuspend in sterile PBS containing 2% of FBS at a cell concentration of 2 × 106 per 100 μL. Keep on ice.
Set up an isoflurane anesthesia machine.
Place an irradiated mouse within the anesthesia chamber.
Turn on the oxygen to flow at 1–2 L/min and the isoflurane gauge to 2–5%.
The animal should become anesthetized within a few minutes.
Load 100 μL of spleen cell suspension into a 1 mL syringe fitted with a 27 G needle.
When the mouse is anesthetized, remove it from the chamber. Promptly, place the animal on absorbent paper, head tilted sideways. With one hand, retract the fur around the eye to make it protrude a little. With the other hand, insert the needle at a 45° angle in the inner corner of the eye to penetrate the retro-orbital sinus (Yardeni et al., 2011). See Figure 2B.
Slowly and smoothly inject the 100 μL of spleen cell suspension (approx. 5 s) and return the mouse to the cage as soon as it starts waking up.
Repeat the procedure for each irradiated animal to be transplanted.
Following injection, the recipient mice are left to recover for 4–6 weeks. Antibiotics can be removed from drinking water after two weeks. Monitor the viability of the transplanted mice every day. The presence of adequate stem cells in the test sample being evaluated should result in greater than 80% recipient survival.
Remember to have proper irradiation controls. These mice are comparable to the ones used for the transplant (same age and sex) that will be irradiated with the experimental mice, but they will not be transplanted. They should become moribund after 10–14 days, at which point they are euthanized.
Part II: Blood reconstitution analysis
First analysis of total blood donor reconstitution is done between 4–6 weeks following cell transplantation. This analysis aims to determine whether donor cells have engrafted by assessing the presence of CD45.2 cells (from the donor) in the recipient blood.
Obtaining total white blood cells for flow cytometry
Blood collection is performed by puncture of the facial vein that runs from the submandibular vein across the cheek (Regan et al., 2016). See Figure 2C and 2D.
Hold the mouse firmly by the scruff in a vertical position and puncture skin at the rear of the jawbone, at the intersection of two virtual lines, one originating at the external corner of the eye and the other one at the hairless spot close to the mouth, with a Goldenrod animal lancet.
Collect blood into an EDTA-coated BD microtainer; 200 µL is sufficient (approximately four drops).
Keep doing the same for all the recipient mice of the experiment. In addition, bleed a non-transplanted CD45.2 mouse and a non-transplanted CD45.1 mouse to perform the controls for flow cytometry.
Transfer blood samples into 15 mL conical tubes. Perform red blood cell lysis by adding 1mL of BD PharmLyse lysing solution diluted 1:10 in water. Gently vortex each tube and incubate on ice, protected from light, for 15 min.
Centrifuge the tubes at 200 × g for 5 min at 4°C. Carefully aspirate the supernatant without disturbing the pellet (which should appear almost white) and add 2 mL of 1× PBS containing 1% heat-inactivated FBS and 0.1% sodium azide.
Labeling cells for flow cytometry
Centrifuge the tubes at 200 × g for 5 min at 4°C. Carefully aspirate the supernatant without disturbing the pellet and resuspend in 50 µL of staining solution made of a mix of BV711 anti-mouse CD45.1 antibody (diluted 1:200) and BV605 anti-mouse CD45.2 antibody (diluted 1:200) in FACS buffer.
Prepare two samples for single color controls by adding 50 µL of BV711 anti-mouse CD45.1 antibody (diluted 1:200) in the CD45.1 blood sample and 50 µL of BV605 anti-mouse CD45.2 antibody (diluted 1:200) in the CD45.2 blood and retain one sample as unstained.
Incubate on ice for 15 to 30 min, protected from light.
Wash with 300 µL of FACS buffer. Centrifuge the cells, 200 × g, 5 min at 4°C. Aspirate the supernatant.
Resuspend in 200 µL of FACS buffer and transfer to FACS tubes through a mesh filter to remove clumps of cells.
Analyze on Flow cytometer as previously described (steps B27 to B33).
Part III: Long-term engraftment data analysis
This analysis aims at determining whether the engrafted transplanted cells gave rise to all lineages of white blood cells and is performed at least 4 months following transplantation.
Bleed animals and perform red blood cell lysis as previously described (steps A1 to A6).
Stain blood with a staining mix composed of PE-Cy5 anti-mouse CD4 (diluted 1:200), APC anti-mouse CD8a (diluted 1:200), PE-Cy7 anti-mouse CD11b (diluted 1:500), APC-eFluor 780 anti-mouse B220 (diluted 1:200), and BV605 anti-mouse CD45.2 (diluted 1:200) in FACS buffer.
Proceed as detailed in part II-B.
This analysis will determine the percentage of CD4 and CD8 T cells, B cells, and myeloid cells originating from the CD45.2-positive transplanted cells. The presence of all major lineages indicates the presence of HSPCs in the donor material, while the presence of only myeloid cells of donor origin indicates that only committed progenitors were present in the experimental spleen.
To firmly assert that multipotent stem cells were present in the donor spleen, we recommend performing a secondary transplant using the spleen and/or bone marrow of the primary recipients and recapitulating the entire procedure. The presence of blood cell lineages from donor cells in recipients following secondary transplant provides definitive evidence for the presence of totipotent hematopoietic stem cells in the spleens of the primary animals. Depending on the experimental system being studied, the long-term HSCs engrafted during the primary transplant may reside exclusively in the bone marrow or may have also been homed to peripheral organs, which can be evaluated by performing secondary engraftments using either bone marrow or spleen cells.
It will be of interest to apply this protocol to additional secondary lymphoid organs other than spleen. In particular, this technique could be applied to measure the potential presence of hematopoietic stem cells in lymph nodes or other tissues with abundant hematopoietic cells, such as the small and large intestine.
Recipes
FACS buffer
Bovine Serum Albumin (BSA) 0.5% (w/v)
1 mM EDTA
0.05% sodium azide (w/v)
Dissolved in PBS
Filter sterilize using a 0.2 μm filter
Acknowledgments
The protocol was adapted from the previously published paper: Marié et al. (2021). This work was supported in part by National Institutes of Health grants R01AI28900 and Lupus Research Alliance grant 579817 to DEL, and by the Laura and Isaac Perlmutter Comprehensive Cancer Center support grant P30CA016087 from the National Cancer Institute.
Competing interests
The authors declare no competing interests.
Ethics
All work in the development of this protocol was approved by the Institutional Animal Care and Use Committee of NYU Grossman School of Medicine.
References
Baker, M. B., Altman, N. H., Podack, E. R. and Levy, R. B. (1996). The role of cell-mediated cytotoxicity in acute GVHD after MHC-matched allogeneic bone marrow transplantation in mice. J Exp Med 183(6): 2645-2656.
Duran-Struuck, R. and Dysko, R. C. (2009). Principles of bone marrow transplantation (BMT): providing optimal veterinary and husbandry care to irradiated mice in BMT studies. J Am Assoc Lab Anim Sci 48(1): 11-22.
Marié, I. J., Brambilla, L., Azzouz, D., Chen, Z., Baracho, G. V., Arnett, A., Li, H. S., Liu, W., Cimmino, L., Chattopadhyay, P., et al. (2021). Tonic interferon restricts pathogenic IL-17-driven inflammatory disease via balancing the microbiome. Elife 10: e68371.
Regan, R. D., Fenyk-Melody, J. E., Tran, S. M., Chen, G. and Stocking, K. L. (2016). Comparison of Submental Blood Collection with the Retroorbital and Submandibular Methods in Mice (Mus musculus). J Am Assoc Lab Anim Sci 55(5): 570-576.
Yardeni, T., Eckhaus, M., Morris, H. D., Huizing, M. and Hoogstraten-Miller, S. (2011). Retro-orbital injections in mice. Lab Anim (NY) 40(5): 155-160.
Article Information
Copyright
Marie et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
How to cite
Category
Immunology > Animal model > Mouse
Stem Cell > Adult stem cell > Hematopoietic stem cell
Cell Biology > Cell Transplantation > Isograft transplantation
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4,439 | https://bio-protocol.org/en/bpdetail?id=4439&type=0 | # Bio-Protocol Content
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Peer-reviewed
Efficient Superovulation and Egg Collection from Mice
MS Miyuki Shindo
KM Kenji Miyado
WK Woojin Kang
MF Maki Fukami
MM Mami Miyado
Published: Vol 12, Iss 11, Jun 5, 2022
DOI: 10.21769/BioProtoc.4439 Views: 2425
Reviewed by: Pilar Villacampa AlcubierreWilliam C. W. ChenSrinidhi Rao Sripathy Rao
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Original Research Article:
The authors used this protocol in microPublication Biology Feb 2021
Abstract
Superovulation is a method used to reduce the number of mice used per experiment by increasing the egg number. Conventionally, superovulation for obtaining mouse eggs involves the use of equine chorionic gonadotropin (eCG) for stimulation and human CG for induction. Female mice of the C57BL/6 inbred strain spontaneously ovulate approximately 10 eggs. The average number of eggs ovulated using the conventional superovulation method is approximately twice as high as that obtained by spontaneous ovulation. Here, we describe the conventional and non-conventional methods of intraperitoneal injection of superovulation reagents in mice and subsequent egg collection. The non-conventional superovulation method combining anti-inhibin serum (AIS) plus eCG for stimulation is more efficient than conventional superovulation. Appropriate intervals from each injection to sampling induce large numbers of high-quality eggs. Immediately after ovulation, eggs are surrounded by cumulus cells, forming an egg-cumulus complex. These cumulus cells are then removed from the egg-cumulus complex by treatment with hyaluronidase to obtain the exact number of eggs. This protocol is suitable for further manipulations such as intracytoplasmic sperm injection and cryopreservation of eggs, as well as for the analyses of responsivity to superovulation reagents in genetically modified mice obtained by genome editing.
Keywords: Mouse Egg Oocyte Cumulus cells Superovulation Anti-inhibin serum Chorionic Gonadotropin Hyaluronidase
Background
Superovulation, involving the stimulation of follicle development and induction of ovulation, is used to increase the number of eggs in animals, including mice. Conventionally, superovulation of mice involves the use of equine chorionic gonadotropin (eCG) that has a follicle-stimulating hormone (FSH)-like activity and human CG (hCG) for stimulation and induction, respectively. Anti-inhibin serum (AIS) neutralizes the function of inhibin, regulates FSH secretion, and increases the number of ovulated eggs (Wang et al., 2001). Thus, an efficient superovulation method involving the combined use of AIS with eCG for stimulation, increases the number and improves the quality of ovulated eggs, and reduces the number of mice used in animal experiments compared with the conventional superovulation method (Takeo and Nakagata, 2015). Furthermore, we and other researchers have compared the responsivity of multiple mouse strains to these superovulation reagents (Takeo and Nakagata, 2015; Shindo et al., 2021). Eggs obtained from superovulation reagent-treated female mice are used for subsequent applications such as intracytoplasmic sperm injection (ICSI) and cryopreservation of eggs. Considering that the demand for mouse egg manipulation will continue increasing to produce mouse modelsthat reproduce human diseases and to perform in vivo functional studies using genome editing techniques in the future, as well as the application for in vitro fertilization, we describe an efficient protocol for the superovulation of mice and subsequent egg collection.
Materials and Reagents
Glass pipettes (Drummond Scientific Company, MICROCAPS®, catalog number: 1-000-0500)
1.5 mL microcentrifuge tubes (WATSON, catalog number: 131-815C)
50 mL tubes (Greiner, catalog number: 227261)
10 mL plastic pipettes (FALCON, catalog number: 357551)
1,000 µL pipette tips (WATSON, catalog number: 110-7-6C)
200 µL pipette tips (WATSON, catalog number: 110-705C)
10 µL pipette tips (WATSON, catalog number: 110-207C)
Kimwipes (NIPPON PAPER CRECIA Co., Ltd., catalog number: 62020)
Paper towels (ASKUL, catalog number: 1944368)
35 mm dishes (IWAKI, catalog number: 1000-035)
60 mm dishes (CORNING, catalog number: 351007)
Syringes with needles (Terumo Corporation, 1 mL syringe with 26-gauge 1/2-inch needle, catalog number: SS-01T2613S)
Disposable gloves (AXEL, catalog number: 61-7347-30)
C57BL/6N and C57BL/6J female mice (Japan SLC, Inc.): 4–6 and ≥10 weeks of age (excluding 7–9 weeks of age because they are unsuitable for superovulation)
eCG (ASKA Animal Health Co., Ltd., SEROTROPIN®, 1,000 IU × 10 vials, catalog number: No application), store at 4°C
AIS plus eCG (Kyudo Co., Ltd., CARD HyperOva®, 1 mL, catalog number: F021), store at -20°C
hCG (ASKA Animal Health Co., Ltd., Gonadotropin for animal, 3,000 IU × 5 vials, catalog number: No application), store at 4°C
Saline (Otsuka Pharmaceutical Co., Ltd., 20 mL × 50 vials, catalog number: Not applicable): Store at room temperature
CARD mHTF medium (Kyudo Co., Ltd., 2 mL, catalog number: GA017), store at 4°C
M2 medium (Merck, EmbryoMax® M2 Medium, catalog number: MR-015-D), store at -20°C
Hyaluronidase (Sigma-Aldrich, catalog number: H3506-100MG), store at -20°C
Liquid paraffin (Nacalai Tesque, Inc., Specially prepared reagent, catalog number: 26137-85): Store at room temperature and in the dark, away from sunlight
70% ethanol (Yoshida Pharmaceutical Company, Ecosyoueta disinfectant solution, catalog number: 14987288980046)
Aluminum foil (AXEL, catalog number: 6-713-01)
Equipment
Protective equipment (e.g., masks, goggles, and lab coats)
CO2 incubator (ASTEC Co., Ltd., model: SCA-165DS)
Stereo microscope (Nikon, model: SMZ645)
Dry-heat sterilizer (Panasonic, model: MOV-212S-PJ)
Precision balance (AXEL, model: 1-1726-01)
Ampoule cutter (AXEL, model: 5-124-22)
Alcohol lamp (AXEL, model: 6-487-01)
Pipette controller (FALCON, model: 357469)
P-1000 pipette (GILSON, model: F120602)
P-200 pipette (GILSON, model: F123601)
Micropipette (Eppendorf, model: 4920000024)
Mouth pipette (Drummond, model: 2-040-000)
Filter (Millipore, model: SLGPR33RS)
Ampoule glass cutter (AXEL, model: 5-124-22)
Large straight scissors (Natsume Seisakusho Co., Ltd., model: B-3)
Small straight scissors (Natsume Seisakusho Co., Ltd., model: B-12)
Curved tip tweezers (AXEL, model: 6-531-19)
Tweezers (AXEL, model: 2-529-12)
Precision tweezers (DUMONT, model: NO.5-INOX)
Needle (AXEL, model: 2-013-01)
Dispenser for paraffin liquid (Nichiryo Co., Ltd., model: 00-DP-2B)
Mechanical tally counter (AXEL, model: 63-1584-34)
Plastic cages (Clea Japan, Inc., model: CL-0103-2 Mouse TPX)
Software
Microsoft Excel (Microsoft Corporation)
Procedure
Animals
Breed the C57BL/6 strain (2–4 mice per cage) under the following specific pathogen-free conditions: at 23 ± 1°C controlled temperature, 12 h light-dark cycles (light on at 8:00 and off at 20:00), and ad libitum access to food and water.
Preparation of eCG (7.5 IU/100 µL)
Open three vials containing eCG powder and two bottles of saline.
Add 2 mL of saline into each eCG vial using a P-1000 pipette with a 1,000 µL tip, mix by pipetting, and transfer the solution (a total volume of 6 mL) to a 50 mL tube.
Repeat Step B2 twice to collect all the eCG, i.e., dissolve eCG powder (3,000 IU) in 18 mL of saline.
Add 22 mL of saline into the 50 mL tube using a pipette controller with a 10 mL plastic pipette to obtain an eCG working solution, i.e., dissolve eCG powder (3,000 IU) in 40 mL of saline.
Prepare 1.2 mL aliquots (7.5 IU/100 µL per mouse) in 1.5 mL microcentrifuge tubes and store at -20°C until use, for up to six months.
When needed, thaw the eCG solution completely at room temperature and mix well before use.
Preparation of hCG (7.5 IU/100 µL)
Open a vial containing hCG powder and two bottles of saline.
Add 2 mL of saline into the hCG vial using the P-1000 pipette with a new 1,000 µL tip, mix by pipetting, and transfer the solution to a new 50 mL tube.
Repeat Step C2 twice to collect all the hCG, i.e., dissolve hCG powder (3,000 IU) in 6 mL of saline.
Add 34 mL of saline into the 50 mL tube using the pipette controller with a new 10 mL plastic pipette to obtain the hCG working solution, i.e., dissolve hCG powder (3,000 IU) in 40 mL of saline.
Prepare 1.2 mL aliquots (7.5 IU/100 μL per mouse) in 1.5 mL microcentrifuge tubes and store at -20°C until use, for up to six months.
When needed, thaw the hCG solution completely at room temperature and mix well before use.
Preparation of M2 medium containing hyaluronidase
Measure 0.5 mg of hyaluronidase and add to a new 50 mL tube.
Thaw M2 medium and add 50 mL to the tube containing hyaluronidase (1% solution).
Mix thoroughly by gentle inversion.
Prepare 1 mL aliquots in 1.5 mL microcentrifuge tubes and store at -20°C until use.
When needed, thaw the solution completely at room temperature and mix well before use.
Note: Hyaluronidase is sterile but non-filtered because this reagent is adjusted on a clean bench.
Preparation of glass pipettes for egg handling (see Video 1)
Cut the glass pipettes in the middle using an ampoule glass cutter (Figure 1A).
Heat the cut edge of glass pipettes with the flame of an alcohol lamp to smooth.
Hold both sides of the glass pipette with one hand and a pair of curved tip tweezers.
Heat the middle of the pipette until it is softened slightly (Figure 1B), remove from the flame, and immediately pull both ends horizontally.
Cut the excess part of the pipette, heat, and smooth the tip slightly. The smooth tip is less likely to damage the eggs and dishes.
Check the tip under a stereomicroscope (Figure 1C) and choose glass pipettes with an inner diameter of approximately 150–200 µm.
Wrap the glass pipettes with aluminum foil (Figure 1D), dry-heat sterilize (180°C, 30 min), and store in a new 15 mL tube at room temperature.
Note: Pipettes with proper inner diameter enable to handle eggs easily. Multiple glass pipettes should be prepared for one experiment to replace the pipette with a new one when operation is not easy (e.g., cumulus cells adhere to the tip).
Video 1. Making glass pipettes.
Figure 1. Making glass pipettes. (A) Cut glass pipettes. (B) Heat and soften a glass pipette. Insert, pulled glass pipettes. (C) Tips of glass pipettes. Insert, an enlarged view of the pipette tips. (D) Wrap glass pipettes.
Superovulation
Thaw eCG or CARD HyperOva® solutions at room temperature and mix well.
Aspirate the required amount of eCG or HyperOva® (100 μL per mouse) with a syringe; for example, aspirate 1 mL of eCG or HyperOva® for 10 female mice (Figure 2A).
Hold a mouse and inject 100 µL of eCG or HyperOva® into the peritoneal cavity (Figure 2B and 2C).
Return mice to their cages.
At 48 h after injecting eCG or HyperOva®, inject 100 µL of hCG in the same manner (Figure 2A, 2B, and 2C).
Return mice to their cages.
Note: Either wrong dosage or inadequate timing of hormone injection reduces the number of normal eggs ovulated.
Figure 2. Superovulation procedure and egg collection. (A) Filling a syringe. (B) Intraperitoneal injection of female mice. (C) Time schedule of superovulation reagent injections and egg collection. AIS, anti-inhibin serum; eCG, equine chorionic gonadotropin; hCG, human chorionic gonadotropin.
Preparation of dishes
Add paraffin liquid to an empty 35 mm dish (Figure 3A and 3B).
Place four and six CARD mHTF medium drops (100 µL per drop) in two 60 mm dishes and cover these drops with paraffin liquid (Figure 3A, 3C, 3D, and 3E).
Incubate these dishes in a CO2 incubator at 37°C with 5% CO2 for at least 30 min before collecting the egg-cumulus complex (Figure 3F).
Thaw the M2 medium containing hyaluronidase and place four drops (200 µL per drop) in a new 60 mm dish (Figure 3G and 3H).
Note: Prepare this just before washing the eggs. There is no need to cover M2 medium drops with paraffin liquid and to place them in the CO2 incubator. As M2 medium is a 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid-based medium, it can be used for a long time at room temperature outside the CO2 incubator (Carter et al., 1993).
Figure 3. Dishes utilized in this experiment. (A) Dispensing paraffin liquid. (B) Keeping dish for isolated oviducts. (C, E) Dish for collecting the egg-cumulus complex. (D) Dish for washing eggs. (F) CO2 incubator. (G, H) Dish for removing cumulus cells from the egg.
Collection of the egg-cumulus complex
Place scissors and tweezers on the bench (Figure 4A) and wear gloves (and other protective equipment as necessary).
At 14–16 h after injecting hCG, sacrifice female mice (Figure 2C).
Disinfect the abdomen with 70% ethanol and cut the abdominal skin of mice using large scissors.
Pull two sides of the cut skin and access the mouse peritoneum.
Cut the peritoneum using small scissors.
Locate the V-shaped uterus, oviducts, and ovaries by shifting the position of the gut and internal organs.
Hold the utero-tubal junction with a pair of precision tweezers, cut the utero-tubal and isthmic-ampullary junctions, and separate the oviducts from the uterus (Figure 5A and 5B).
Clean the oviducts by removing adipose tissue, blood, and tissue fluid, and transfer oviducts to the keeping dish moved from the CO2 incubator.
Note: Reduce the exposure time of the collecting dish to room temperature using the keeping dish.
Move the collecting dish from the CO2 incubator to the bench and transfer oviducts to liquid paraffin on the collecting dish using the pair of precision tweezers and place the oviducts on the bottom of this dish.
Take out the egg-cumulus complex from the ampulla using a needle under the stereomicroscope (Video 2 and Figure 4B) and add the egg-cumulus complex to one drop of CARD mHTF medium on the collecting dish (Figure 6A and 6B). Superovulation treatment induces an average of 20–50 eggs per female mouse (Shindo et al., 2021), and one drop includes <100 eggs.
Move the collecting dish to the CO2 incubator.
Repeat Steps H2–H11 for all female mice.
Note: Prepare the CARD mHTF medium drops corresponding to the number of superovulated mice.
Figure 4. Tools utilized in this experiment. (A) Anatomical set for abdominal exploration. (B) Stereo microscope. Insert, handling set for the egg-cumulus complex. (C) Mouth pipetting set for egg transfer. (D) Glass pipette with aspirated medium. Arrow, liquid surface of the medium.
Figure 5. Pictures of ovary, oviduct, and uterus. (A) Serial view of ovary, oviduct, and uterus. Each junction is represented by dashed lines. (B) Separated view of the oviduct. Arrow indicates the ampulla.
Video 2. Removing the egg-cumulus complex from the ampulla.
Removing cumulus cells and counting eggs
Move the collecting and washing dishes from the CO2 incubator to the bench.
Aspirate the M2 medium containing hyaluronidase using a mouth pipetting set (Figure 4C), and transfer the egg-cumulus complex from the CARD mHTF medium drop on the collecting dish to the drop of M2 medium with hyaluronidase on the removing dish.
Note: Aspirate the M2 medium containing hyaluronidase until the wide part of the glass pipette for easy handling of the eggs (Figure 4D).
Remove cumulus cells from the egg-cumulus complex by mouth pipetting and transfer the eggs to the drops of CARD mHTF medium on the washing dish (Figure 6C).
Wash the eggs by moving them between three drops of CARD mHTF medium on the washing dish.
Repeat steps I2–I4 for all egg-cumulus complexes.
Count the number of normal eggs per drop using a mechanical tally counter and record the results in Microsoft Excel. Normal and abnormal eggs are easily distinguished by morphology (Figure 6D and 6E).
Note: If the number of normal eggs is reduced, check the expiration date for solutions used, the timing of superovulation, and whether the age of mice is suitable for superovulation.
Figure 6. Eggs manipulation. (A) Removing the egg-cumulus complex from the ampulla. This drop contains 47 eggs. (B) The egg-cumulus complex before hyaluronidase treatment. (C) Eggs after hyaluronidase treatment. (D) Normal eggs. (E) Abnormal eggs.
Data analysis
Perform Student’s t-test or Mann-Whitney’s U-test using Microsoft Excel (Shindo et al., 2021).
Notes
Inject twice the amount (200 µL per mouse) of superovulation reagents into mice with a body weight of 35 g or more.
Apply one drop for each mouse if you need to count the number of eggs per mouse.
Reduce the exposure time of eggs to room temperature to avoid a reduction in developmental efficiency when performing ICSI.
Take pictures with a microscope camera if necessary.
Acknowledgments
This work was supported in part by JSPS KAKENHI (Grant Numbers: JP19K09682 and JP19H01067) and the National Center for Child Health and Development (2021C-27). This protocol was adapted from two original articles (Shindo et al., 2019 and 2021). We would like to thank Editage (www.editage.com) for English language editing.
Competing interests
The authors declare no competing interests.
Ethics
All animal experiments were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of the National Research Institute for Child Health and Development (experimental numbers, A2005-007 and A2020-005).
References
Carter, D. A. (1993). Preparation of culture media for fertilized one-cell mouse eggs. Methods Mol Biol 18: 141-143.
Shindo, M., Inui, M., Kang, W., Tamano, M., Tingwei, C., Takada, S., Hibino, T., Yoshida, M., Yoshida, K., Okada, H., et al. (2019). Deletion of a seminal gene cluster reinforces a crucial role of SVS2 in male fertility. Int J Mol Sci 20(18): 4557.
Shindo, M., Tsumura, H., Miyado, K., Kang, W., Kawano, N., Yoshida, T., Fukami, M. and Miyado, M. (2021). Similar responsiveness between C57BL/6N and C57BL/6J mouse substrains to superovulation. MicroPubl Biol 2021.
Takeo, T. and Nakagata, N. (2015). Superovulation using the combined administration of inhibin antiserum and equine chorionic gonadotropin increases the number of ovulated oocytes in C57BL/6 female mice. PLoS One 10: e0128330.
Wang, H., Herath, C. B., Xia, G., Watanabe, G. and Taya, K. (2001). Superovulation, fertilization and in vitro embryo development in mice after administration of an inhibin-neutralizing antiserum. Reproduction 122(5): 809-816.
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Developmental Biology > Reproduction
Cell Biology > Cell isolation and culture > Cell isolation
Biological Sciences > Biological techniques
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How can superovulation be induced in aged mice?
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4,440 | https://bio-protocol.org/en/bpdetail?id=4440&type=0 | # Bio-Protocol Content
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Flow Cytometric Characterization of Macrophages Infected in vitro with Salmonella enterica Serovar Typhimurium Expressing Red Fluorescent Protein
NB Natascha Brigo
CP Christa Pfeifhofer-Obermair
ED Egon Demetz
PT Piotr Tymoszuk
GW Günter Weiss
Published: Vol 12, Iss 11, Jun 5, 2022
DOI: 10.21769/BioProtoc.4440 Views: 1653
Reviewed by: Tomas AparicioSonal Patel PatelSaskia F. Erttmann
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Original Research Article:
The authors used this protocol in Cells Jul 2021
Abstract
Macrophages are important for host defense against intracellular pathogens like Salmonella and can be differentiated into two major subtypes. M1 macrophages, which are pro-inflammatory and induce antimicrobial immune effector mechanisms, including the expression of inducible nitric oxide synthase (iNOS), and M2 macrophages, which exert anti-inflammatory functions and express arginase 1 (ARG1). Through the process of phagocytosis, macrophages contain, engulf, and eliminate bacteria. Therefore, they are one of the first lines of defense against Salmonella. Infection with Salmonella leads to gastrointestinal disorders and systemic infection, termed typhoid fever. For further characterization of infection pathways, we established an in vitro model where macrophages are infected with the mouse Salmonella typhi correlate Salmonella enterica serovar Typhimurium (S.tm), which additionally expresses red fluorescent protein (RFP). This allows us to clearly characterize macrophages that phagocytosed the bacteria, using multi-color flow cytometry.
In this protocol, we focus on the in vitro characterization of pro- and anti-inflammatory macrophages displaying red fluorescent protein-expressing Salmonella enterica serovar Typhimurium, by multi-color flow cytometry.
Keywords: Salmonella Typhimurium Macrophages Infection Control Arginase 1 Inducible Nitric Oxide Synthase
Background
The intracellular Gram-negative bacterium Salmonella typhi can cause severe and often life-threatening disease in humans. Globally, approximately 200,000 deaths are caused by the bacterium every year. The intracellular pathogen is ingested through contaminated food, and transmitted from person to person. The mouse correlate of human Salmonella typhi is Salmonella enterica serovar Typhimurium (S.tm). The intracellular bacteria are phagocytosed by macrophages and are able to evade antimicrobial defense by inhibiting fusion of lysosome and phagosome. Therefore, S.tm is able to survive and replicate inside the host (Buchmeier and Heffron, 1991; Navarre et al., 2010; Lahiri et al., 2010; Mastroeni and Grant, 2011; Bhutta et al., 2018).
In general, the immune system is divided into cells of the innate immune system (monocytes, macrophages, dendritic cells, and natural killer cells), and the acquired immune system (B lymphocytes, and T lymphocytes). Macrophages are phagocytic cells of the innate immune system, and one of the body's first defense mechanisms, when a pathogen crosses the host’s skin barrier. They can be classified into two types: (I) M1 pro-inflammatory macrophages, which are responsible for killing bacterial and viral pathogens, and express inducible nitric oxide synthase (iNOS), and (II) M2 macrophages, which support the wound healing process, and have an anti-inflammatory effect. Importantly, M2 macrophages express the enzyme arginase 1 (ARG1) (Mosser and Edwards, 2008; Mills, 2012; Weiss and Schaible, 2015; Gordon and Martinez-Pomares, 2017; Murray, 2017; Hannemann et al., 2019).
The cytosolic enzyme ARG1 is primarily expressed in liver tissue. During infection, ARG1 upregulation promotes pathogen survival in macrophages, by hydroxylating l-arginine to urea and ornithine, which therefore lowers l-arginine levels for the synthesis of nitric oxide (NO) by iNOS. A fully functional iNOS needs an adequate l-arginine supply to produce NO that kills pathogens. Interferon gamma (IFNγ) and tumor necrosis factor alpha (TNFα) are potent inducers of iNOS (Nairz et al., 2013; Bogdan, 2015; Brigo et al., 2021). ARG1 is induced by interleukin 4 (IL-4), which is produced by type 2 T helper cells. TNFα and IFNγ inhibit the transcription of ARG1, by interfering with IL-4–induced chromatin remodeling (Ostuni and Natoli, 2011; Schleicher et al., 2016; Piccolo et al., 2017). Additionally, several studies show that increased ARG1 activity is associated with an increased concentration of various pathogens, such as Streptococcus pneumoniae, Mycobacterium bovis, Mycobacterium tuberculosis, or Toxoplasma gondii (Iniesta et al., 2005; El Kasmi et al., 2008; De Muylder et al., 2013; Schleicher et al., 2016; Paduch et al., 2019). However, it has been reported that deletion or pharmacological inhibition of ARG1 does not lead to a better control of Salmonella infection in macrophages, or in mice, in a septicemia model (Brigo et al., 2021).
Current treatment against invasive salmonellosis with antibiotics has become more difficult, due to resistance against conventional antibiotics. Therefore, the identification of new mechanisms to better understand the host-pathogen interplay in Salmonella infection, and the detailed characterization of the cells involved in the defense against this infection are urgently needed. Herein, we describe a method that identifies pro- and anti-inflammatory bone marrow-derived macrophage subtypes, during an infection with Salmonella enterica serovar Typhimurium. Furthermore, Salmonella expressing red fluorescent protein allows the visualization of phagocytosed Salmonella in these subtypes. This method supports further research on the involvement of pro- and anti-inflammatory macrophages in the defense against Salmonella.
Materials and Reagents
250 mL Erlenmeyer flask (Stoelzle Medical, catalog number: 21226368000)
0.5 mL Eppendorf tubes (Eppendorf, catalog number: 0030121.023)
Disposable cuvette (BRAND, catalog number: 759015)
1.5 mL Eppendorf tubes (Eppendorf, catalog number: 0030120.086)
Cell scraper (Sarstedt, catalog number: 83.3951)
15 mL Polypropylene conical tube (Falcon, catalog number: 352096)
Cell strainer 40 µm (Falcon, catalog number: 352360)
96-well BRAND plate (Life Science Products, catalog number: 781602)
5 mL disposable syringe (BD, catalog number: 309050)
Luna cell counting slides (Biocat, catalog number: L201B1C3GB)
6-cm dish (TTP, catalog number: 93060)
Salmonella enterica serovar Typhimurium SL1344 expressing red fluorescent protein (RFP) (Birmingham et al., 2006; Wu et al., 2017)
Lysogeny broth (LB Broth) Lennox (Roth, catalog number: X964.2)
Glycerol (Sigma, catalog number: G5516-100ML)
Phosphate buffer saline (PBS; Lonza, catalog number: 17-515 F)
Agar-Agar Kobe I (Roth, catalog number: 5210.3)
CASY Cup (OMNI Life Science, catalog number: 5651794)
CASY Ton Buffer (OMNI Life Science, catalog number: 5651808)
Aqua bidest (Fresenius Kabi, catalog number: 16.231)
Gentamicin (Gibco, catalog number: 15750-037)
L-glutamine (Lonza, catalog number: BE17-605E)
Dulbecco′s Modified Eagle′s Medium (DMEM, Pan BiotechTM, catalog number: P04-01500)
Fetal bovine serum (FBS, Pan BiotechTM, catalog number: P30-3031)
BV650 anti-mouse/human CD11b (BioLegend, catalog number: 101239)
APC-R700 rat anti-mouse CD45 (BDHorizonTM, catalog number: 565478)
BV421 rat anti-mouse F4/80 (BD Biosciences; catalog number: 565411)
PerCP-eFluorTM 710 anti-mouse Ly6G (Invitrogen; catalog number: 46-9668-82)
FITC anti-mouse CD3 (BioLegend, catalog number: 100204)
FITC anti-mouse CD19 (ImmunoTools, catalog number: 22220193S)
FITC anti-mouse CD49b (BioLegend, catalog number: 103503)
PE-Cyanine7 anti-mouse iNOS (Invitrogen; catalog number: 25-5920-80)
APC anti-mouse ARG1 (Invitrogen, catalog number: 17-3697-82)
BD Cytofix/CytopermTM (BD Biosciences, catalog number: 51-2091K7)
BD PermWashTM (BD Biosciences, catalog number: 51-2090K7)
50 mL Polypropylene conical tube (Falcon, catalog number: 352070)
Ketamine (Livisto, catalog number: 6680219)
Xylazine (Animedica, catalog number: 7630517)
Omnican F syringes (Braun, catalog number: 91615025)
Disposable hypodermic needle 100 Sterican R (Braun, catalog number: 4657519)
Pen-Strep (Lonza, catalog number: DE17-602E)
Erythrocyte lysis buffer (R&D, catalog number: WL2000)
Acridine Orange/propidium iodide stain (Biocat, catalog number: F23001)
LB medium (see Recipes)
LB-medium with 30% Glycerol (see Recipes)
Equipment
Laminar Flow Cabinet; EuroClone Safe Mate Eco 1.2 (Politakis Laborgeräte, catalog number: EN 12 469)
Shaking incubator (VWR, catalog number: GFL 3031)
Heraeus® HERAcell® CO2 Incubator (Thermo Fisher Scientific, catalog number: 3615-45)
Photometer (Eppendorf, BioPhotometer D30, catalog number: 6133000001)
Centrifuge (Hettich Micro 200R and Rotanta 460R, catalog number: Z652113, Z623520)
CASY TT counting system (OMNI Life Science, catalog number: TT-20A-2571)
CytoFLEX S V4-B4-R2-I2 Flow Cytometer (13 detectors, 4 lasers, Beckman Coulter, catalog number: C01161)
LUNA Automated Cell Counter (Biocat, L10001-LG)
Software
FlowJo v10.7.0 (BD Biosciences, https://www.flowjo.com/solutions/flowjo)
Note: Any software package for analyzing flow cytometry data can be used with this protocol.
Procedure
Preparation of Salmonella Typhimurium (S.tm) stock
Take an aliquot of Salmonella enterica serovar Typhimurium SL1344 expressing red fluorescent protein (RFP) from -20°C storage.
Thaw the aliquot at room temperature.
Pipette 10 µL of S.tm into 10 mL of LB-medium in a 250-mL Erlenmeyer flask.
Cover the top of the flask using tin foil.
Incubate in a shaking incubator at 200 rpm and 37°C overnight.
The following day, pipette 50 µL of the overnight culture into 10 mL of fresh LB-medium into a 250-mL Erlenmeyer flask.
Discard the overnight culture of S.tm. Wash and sterilize the 250-mL Erlenmeyer flask.
Cover the top of the flask using tin foil.
Incubate the culture in a shaking incubator at 200 rpm and 37°C for 1–2 h.
Calibrate a photometer, using 500 µL of LB-medium in a disposable cuvette as blank.
Measure OD600, to check if S.tm reached 0.5.
S.tm reaches the optimal logarithmic growth phase when OD600 is between 0.5–0.7.
Note: If the OD600 value is below 0.5, continue the incubation of the culture in the 250-mL Erlenmeyer flask as described above, until an OD600 value of 0.5 is reached. Of note, S.tm density duplicates every 20 min. If the OD600 value is above 0.7, dilute the culture 1:1 with LB-medium, and incubate it in the 250-mL Erlenmeyer flask, until an OD600 value of 0.5.
Transfer the culture into a 50-mL conical tube.
Centrifuge the S.tm culture at 4,967 × g at room temperature for 5 min.
Discard the supernatant.
Resuspend the pellet in 1 mL of freshly prepared LB-medium + 30% glycerol.
Prepare aliquots of 50 µL in 0.5-mL Eppendorf tubes, and store them at -20°C.
Culture of S.tm to the optimal growth phase
Thaw one aliquot of the S.tm stock.
Pipette 10 µL of this aliquot into 10 mL of LB-medium in a 250-mL Erlenmeyer flask, and cover the top of the flask using tin foil.
Incubate in a shaking incubator at 200 rpm and 37°C overnight.
The following day, pipette 50 µL of this overnight culture into 10 mL of LB-medium in a 250-mL Erlenmeyer flask, and cover the top of the flask using tin foil.
Discard the overnight culture of S.tm. Wash and sterilize the 250 mL Erlenmeyer flask.
Incubate in a shaking incubator at 200 rpm and 37°C for 1–2 h.
Calibrate a photometer, using 500 µL of LB medium in a disposable cuvette as blank.
Measure OD600 to check if S.tm reached 0.5, which is equivalent to the optimal logarithmic growth phase.
Note: If the OD600 value is below 0.5, continue the incubation of the culture in the 250-mL Erlenmeyer flask as described above, until an OD600 value of 0.5 is reached. Of note, S.tm density duplicates every 20 min. If the OD600 value is above 0.7, dilute the culture 1:1 with LB-medium, and incubate it in the 250-mL Erlenmeyer flask, until an OD600 value of 0.5.
Counting viable S.tm using a Casy counting system
Use the 45-µm capillary.
Measure the background by placing a new Casy cup with 10 mL of fresh Casy ton buffer under the measuring unit.
Select the program for background measurement (Table 1 Background Measurement).
Measure the background. This should be below 30 counts and 1 µm in size. Otherwise, wash the system.
Prepare a new Casy cup with 10 mL of Casy ton buffer, and add 5 µL of S.tm OD600 0.5.
Shake gently.
Place the sample under the measuring unit.
Select the program for measuring between 1–3 µm (Table 1S.tm Measurement).
Measure.
Click next, to get the number of viable counts/mL = viable S.tm /mL.
Note: Viable counts from a freshly prepared S.tm culture with an OD600 of 0.5 should be between 2.5 × 108–3 × 108 viable counts/mL.
After the measurement is finished, remove the sample cup, and add a fresh Casy cup with 10 mL of Casy ton buffer.
Perform Casy Clean up to five times.
Select the program for washing (Table 1 Washing Program).
After the washing is completed, check the background again.
If the background is below 30, the Casy counting system can be turned off. Otherwise, continue the washing.
Table 1. Programs CASY TT Counting system
Background
Measurement
Measurement
of S. Typhimurium
Washing Program
Capillary 45 µm X-Axis: 5 µm 45 µm X-Axis: 3 µm 45 µm X-Axis: 5 µm
Sample Volume 200 µL Cycles: 1 200 µL Cycles: 3 200 µL Cycles: 10
Dilution 1.001e+00 2.001e+03 1.001e+00
Y-Axis Auto Auto Auto
Eval.Cursor 1.00–4.89 µm 0.75–2.93 µm 0.00–5.00 µm
Norm. Cursor 0.5–4.89 µm 0.3–2.93 µm 0.00–5.00 µm
%Calculation %Via Debris: On %Via Debris: On %Via Debris: On
Aggr. Correct: Auto Auto Auto P
Interface Par P.Feed: On Par P.Feed: On Par P.Feed: On
Print Mode Manual Graphic: On Manual Graphic: On Manual Graphic: On
Preparation of bone marrow-derived macrophages (BMDM)
Note: Preparation of BMDM has been described by Zanoni et al. (2012; doi:10.21769/BioProtoc.225.).
A video demonstrating the procedure can be found at: https://www.jove.com/de/v/52347/isolation-intravenous-injection-murine-bone-marrow-derived.
A schematic illustration of the generation of bone marrow-derived macrophages and infection with S.tm is shown in Figure 1.
Figure 1. Schematic representation of the experimental setup, showing the generation of bone marrow-derived macrophages and infection with S.tm.
The different morphological shapes of uninfected and infected BMDM are visualized in a ScanR Imaging Platform (pictures kindly provided by Demetz E.).
Anesthetize a wildtype C57Bl/6N mouse, by intraperitoneally injecting 50 µL of 100 mg/kg Ketamine + 10 mg/kg Xylazine.
Note: A video demonstrating the procedure in general can be found at Intraperitoneal Injection in the Mouse: https://researchanimaltraining.com/articles/intraperitoneal-injection-in-the-mouse/.
Perform euthanization of the deeply anesthetized mouse by cervical dislocation. Therefore, place a large tweezer behind the base of the anesthetized mouse's skull, and pull sharply back on the tail at a 45° angle.
Fixate the animal on a Styrofoam panel, and spray the surface of the animal with 75% alcohol.
Remove skin and muscle tissue from one leg, by cutting upwards from the heel with sterile scissors.
Cut around the femur head.
Cut in the middle of the knee joint. Be careful not to damage the bones.
Cut the ankle joint.
Remove excess muscles with tissue paper.
Pull on the upper leg, to remove the femur head from the hip joint.
Place the bones into PBS containing 1% penicillin and 1% streptomycin on ice.
Move to a laminar flow hood, and perform all steps on ice.
Open the ends of the bones, by cutting with a pair of sterile scissors.
Place a 40-µm cell strainer on a 50-mL Falcon-tube.
Flush out the bone marrow:
Use a disposable hypodermic needle and a 5-mL syringe.
Fill the syringe with PBS containing 1% penicillin and 1% streptomycin.
Place a needle on one end of the opened bone.
Flush the bone marrow out onto the 40-µm cell strainer.
Repeat flushing of the bone, until it is completely white.
Wash the cell strainer with 10 mL of PBS containing 1% penicillin and 1% streptomycin.
Using the plunger of the syringe, strain the cells through the cell strainer.
Wash the cell strainer with 10 mL of PBS containing 1% penicillin and 1% streptomycin.
Centrifuge the 50-mL conical tube containing your flushed bone marrow at 300 × g and 4°C for 5 min.
Dilute Erythrocyte Lysis Buffer 1:10 with double distilled water
Discard the supernatant.
Resuspend the pellet in 2 mL of diluted Erythrocyte Lysis Buffer.
Incubate at room temperature for 3 min.
Add 15 mL of PBS containing 1% penicillin and 1% streptomycin on top of the Erythrocyte Lysis Buffer.
Centrifuge the 50-mL conical tube containing your flushed bone marrow at 300 × g and 4°C for 5 min.
Discard the supernatant.
Resuspend the pellet in 15 mL of PBS containing 1% penicillin and 1% streptomycin.
Repeat steps 24–26.
Centrifuge the 50-mL conical tube again, and discard the supernatant.
Resuspend the cell pellet in 45 mL of DMEM media supplemented with 10% FBS, 1% L-glutamine, 1% penicillin, 1% streptomycin, and 50 ng/mL recombinant murine M-CSF.
Pipette 15 mL of the cell suspension into each of three 20-cm Falcon dishes.
Change the medium every second day.
On day 5, cells can be harvested (Procedure E).
Harvesting and counting of cells
Remove the culture media from the cell culture dishes.
Wash the cells twice with 10 mL of PBS.
Add 8 mL of DMEM medium supplemented with 10% FBS and 1% L-glutamine.
Scrape the cells using a disposable cell scraper.
Wash the dishes with another 2 mL of DMEM medium supplemented with 10% FBS and 1% L-glutamine.
Transfer the cells into a 50-mL conical tube.
Close the tube, and invert the cells 2–3 times.
Place 9 µL of the cell suspension in a 0.5-µL Eppendorf tube.
Mix 1 µL of Acridine Orange/ Propidium Iodide stain solution with the cell aliquot.
Place 10 µL of the mixture into a Luna cell counting slide.
Count the cells using the LUNA-FL fluorescent and bright field automated cell counter.
Note: Approximately 4.5 × 107 cells are obtained from one mouse, after isolating and culturing the bone marrow of both hind legs.
Seed the cells in 6-cm dishes, at a density of 1.5 × 106 cells/mL in DMEM medium supplemented with 10% FBS and 1% L-glutamine.
Seed four additional dishes for fluorescent minus one (FMO) control (see step G3).
Let the cells settle in a cell incubator overnight.
In vitro infection of bone marrow-derived macrophages with S.tm
Infect BMDM with S.tm at a multiplicity of infection 10 (MOI 10). Therefore, add 10 times more S.tm than cells.
Note: Unused S.tm culture with OD600 of 0.5 can be used for preparing new S.tm aliquots (Procedure A), or be discarded.
Incubate the cells in a cell incubator (5% CO2, 37°C) for 1 h.
Remove the medium containing non-phagocytosed S.tm.
Wash the cells twice with 1 mL of PBS + 25 µg/mL gentamicin.
Add 1 mL of DMEM medium supplemented with 10% FBS, 1% L-glutamine, and 25 µg/mL gentamicin.
Incubate the cells in a cell incubator for 4 h.
Flow Cytometry staining of cultured BMDM
Extracellular staining
Harvest the BMDM by scraping in culture medium, using a disposable cell scraper.
Transfer the cells to a 15-mL Falcon tube, and pellet by centrifugation at 300 × g and 4°C for 5 min.
Discard the supernatant.
Resuspend the pellet in 1 mL of PBS, and transfer it into an 1.5-µL Eppendorf tube.
Pellet the cells by short spinning at 10,860 × g and 4°C for 30 s.
Discard the supernatant.
Resuspend the pellet in 50 µL of surface antibody mix (all antibodies 1:200 in PBS; Table 2).
Table 2. Antibodies for flow cytometry – extracellular stain.
Antibody Clone Company Catalog number expressed on
CD3 FITC 17.A2 BioLegend 100204 T cells
CD19 FITC PeCa1 ImmunoTools 22220193S B cells
CD49b FITC HMa2 BioLegend 103503 NK cells
CD11b BV650 M170 BioLegend 101239 neutrophils, monocytes
CD45 APC-R700 30-F11 BD Horizon 565478 leukocytes
F4/80 BV421 T45-2342 BD Horizon 565411 macrophages
Ly6G PerCP-eFlour 710 1AB-Ly6g Invitrogen 46-9668-82 neutrophils
Note: To be sure that the bone marrow-derived macrophages are not contaminated by T cells, B cells, or NK cells, antibodies against CD3, CD19, and CD49b are added to the flow cytometry panel. All these antibodies are labeled with FITC; therefore, all FITC+ cells can be excluded in the gating strategy (Figure 2). The typical cell distribution of a BMDM culture (uninfected and infected with S.tm) is shown in Table 4.
Incubate in the dark at 4°C for 10 min.
Wash with 500 µL of PBS.
Pellet the cells by short spinning (10,860 × g, 4°C, 30 s).
Discard the supernatant.
Resuspend the pellet in 100 µL of Cytofix/CytoPermTM Buffer, to permeabilize and fix the cells.
Incubate in the dark at 4°C for 20 min.
Dilute the PermWashTM Buffer 1:10 with Aqua bidest.
Add 500 µL of the diluted PermWashTM Buffer on top of the 100 µL of Cytofix/CytoPermTM Buffer.
Pellet the cells by short spinning (10,860 × g, 4°C, 30 s).
Discard the supernatant.
Intracellular stain
Prepare the intracellular antibody mix in diluted PermWashTM Buffer (iNOS 1:100, and ARG1 1:100; Table 3).
Table 3. Antibodies for flow cytometry – intracellular stain.
Antibody Clone Company Catalog number expressed on
iNOS PE-Cyanine7 CXNFT Invitrogen 25-5920-80 pro-inflammatory macrophages
ARG1 APC A1exF5 Invitrogen 17-3697-82 anti-inflammatory macrophages
Resuspend the samples in 50 µL of intracellular antibody mix.
Incubate the samples protected from light at room temperature for 45 min.
Wash the cells once with 500 µL of diluted PermWashTM. Pellet the cells by short spinning (10,860 × g, 4°C, 30 s).
Discard the supernatant, and resuspend the pellets in 200 µL of PBS.
Transfer the samples into a flat bottom 96-well plate, via a 40-µm strainer.
Analyze directly in a flow cytometry device.
Fluorescent minus one (FMO) control
Perform extracellular staining of BMDM, as described in step G1, in the additionally seeded uninfected and infected BMDM samples (see step E13).
Discard the supernatant after washing with diluted PermWashTM Buffer on top of the 100 µL of Cytofix/CytoPermTM Buffer.
Resuspend one uninfected and one infected BMDM cell pellets in the intracellular antibody mix with only the antibody against ARG1. Resuspend the other uninfected and infected BMDM cell pellets in the intracellular antibody mix with only the antibody against iNOS.
Incubate the samples protected from light at room temperature for 45 min.
Wash the cells once with 500 µL of diluted PermWashTM.
Pellet the cells by short spinning (10860 × g, 4°C, 30 s).
Discard the supernatant, and resuspend the pellets in 200 µL of PBS.
Transfer the samples into a flat bottom 96-well plate, via a 40-µm strainer.
Analyze directly in a flow cytometry device.
Figure 2. Gating strategy for the infected bone marrow-derived macrophages – upper panel, and the uninfected bone marrow-derived macrophages – lower panel.
After exclusion of doublets, the leukocytes are described as CD45+. T-cells, B-cells, and NK cells are excluded (CD3–CD19–CD49b–), and macrophages are gated as Ly6G–CD11b+F4/80+. Depending on the research question, there is the possibility to characterize pro-inflammatory macrophages as iNOS-expressing cells, and anti-inflammatory macrophages as ARG1–expressing cells. Furthermore, macrophages containing S.tm are characterized by expression of the red fluorescent protein (RFP) in the PE channel.
Data analysis
The FlowJo software was used to analyze the data. The gating strategy is described in Figure 2.
In BMDM generated from C57BL/6N mice that were either left uninfected or were infected with S.tm, and afterwards further incubated for 4h, typical values for analyzed cell subsets are depicted in Table 4.
Table 4. Typical cell distribution of a BMDM culture.
Cell type Gating Mean ± SEM Uninfected Mean ± SEM Infected
Cells FSC-A to SSC-A 94.7 ± 2.1 95.2 ± 2.1
Single Cells FSC-A to FSC-H 90.0 ± 2.7 91.7 ± 2.2
Leukocytes CD45 to FSC-A 98.6 ± 1.3 99.5 ± 0.3
FITC- negative cells FITC (CD3, CD19, CD49b) to FSC-A 98.6 ± 0.7 97.7 ± 0.6
Monocytes (Ly6G-) Ly6G to FSC-A 98.8 ± 0.7 98.4 ± 0.5
Macrophages F4/80 to CD11b 98.0 ± 0.9 98.8 ± 1.1
Anti-inflammatory macrophages ARG1 to FSC-A 1.8 ± 0.5 1.4 ± 0.3
Pro-inflammatory macrophages iNOS to FSC-A 4.2 ± 2.3 77.7 ± 3.8
Salmonella containing macrophages STR to FSC-A 0 24.7 ± 1.78
Troubleshooting
Cultivation of S.tm (see Procedures A and B)
Salmonella grow best at 37°C, and need oxygen for optimal growth. Therefore, they should be cultivated in an Erlenmeyer flask which is covered with tin foil. The temperature of 37°C must be strictly ensured.
Preparation of BMDM (see Procedure D)
For the generation of bone marrow-derived macrophages, it is important to work in a sterile manner. Cells should only be handled in a laminar flow cabinet. It is important to isolate the entire tibiae and femura, and to cut them open only under sterile conditions, using autoclaved scissors and tweezers.
Harvesting, counting, and seeding of BMDM (see Procedure E)
Harvesting of BMDM by scraping needs to be performed rather gently, to obtain high cell viability. We recommend scraping away from one’s body, exerting not much force on the disposable cell scraper.
Cells are seeded for infection in antibiotic free media. Therefore, the day before seeding, it is recommended to incubate 5 mL of the antibiotic free medium in a cell culture dish placed in a cell incubator overnight, to be sure that the medium is not contaminated by bacteria.
Infection of BMDM (see Procedure F)
After infection, it is necessary to thoroughly wash away the unphagocytosed S.tm. It is important to remove the medium completely, and wash the cells at least twice with PBS + gentamicin. A microscope can be used to see whether S.tm are still present in the culture. If yes, washing steps should be repeated.
It is important to add gentamicin to the PBS for washing, and to the DMEM for further incubation. Gentamicin inhibits the proliferation of S.tm, by blocking protein biosynthesis.
Recipes
LB medium
a.d. with
2% LB-Broth
Autoclave (at 121°C for 20 min, and at 50°C for 10 min)
LB medium with 30% Glycerol
Add 300 µL of Glycerol to 700 µL of LB medium
Acknowledgments
G.W. is supported by grants from the Christian Doppler Society and an ERA-NET grant by the FWF (EPICROSS, I-3321), and N.B. was supported by the FWF doctoral college project W1253 HOROS.
Salmonella Typhimurium expressing red fluorescent protein were a kind gift from Prof. Dr. Dirk Bumann (University of Basel, Switzerland). This protocol was adapted and modified after Fritsche et al. (2008).
Competing interests
The authors declare no conflicts of interest.
References
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Click-iT® Plus OPP Alexa Fluor® Protein Synthesis Assay in Embryonic Cells
YL Yan Li *
XJ Xu Ji *
LC Lu Chang
JT Jianan Tang
MH Min-Min Hua
JL Jing Liu
CO Christopher O’Neil
XH Xuefeng Huang
XJ Xingliang Jin
(*contributed equally to this work)
Published: Vol 12, Iss 11, Jun 5, 2022
DOI: 10.21769/BioProtoc.4441 Views: 1921
Reviewed by: Giusy TornilloTien Anh NgoSilvia Olivera-Bravo
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Original Research Article:
The authors used this protocol in Development Jun 2021
Abstract
This protocol describes a method to assess relative changes in the level of global protein synthesis in the preimplantation embryo using the Click-iT® Plus OPP Protein Synthesis Assays. In this assay, O-propargyl-puromycin (OPP), an analog of puromycin, is efficiently incorporated into the nascent polypeptide of newly translated proteins in embryonic cells. OPP is fluorescently labeled with a photostable Alexa FluorTM dye and detected with fluorescence microscopy. The intensity of the fluorescence is quantitatively analyzed. This is a fast, sensitive, and non-radioactive method for the detection of protein synthesis in early embryo development. It provides a tool for analyzing the temporal regulation of protein synthesis, as well as the effects of changes in the embryonic microenvironment, and pharmacological and genetic modulations of embryo development.
Graphical abstract:
Figure 1. Brief overview of the procedures of the Click-iT® Plus OPP Alexa Fluor® protein synthesis assay in embryonic cells. (A) Set up OPP treatments: (1) Set up microdrops containing 50 µL of OPP working solution and label different treatments on the back of culture dishes (e.g., T0, T1, T2, and T3); (2) The drops are overlain with 2–3 mm heavy paraffin oil and then equilibrated in incubator for 2 h; (3) Collect the embryos from female reproductive tracts or following in vitro culture in desired treatments; (4) Culture embryos in the equilibrated OPP working solution for 2–6 h. (B) Example of OPP detection procedures working with 60-well plates labeled as T0, T1, T2, T3, T4, and T5 for different treatments: (1) The first 60-well plate is used for the procedures of washing, fixation, permeabilization, and Click-iT® OPP detection. (2) The second 60-well plate is for DNA staining and washing. (C) Slide preparation: (1) Label the required number of slides and set up vaseline coverslip supports; (2) Add mounting medium; (3) Transfer embryos into mounting medium; (4) Set coverslip; (5) Seal the coverslip with nail polish.
Keywords: Embryo development Maternal-embryonic transition O-propargyl-puromycin Protein synthesis
Background
Fertilization triggers embryonic genome activation, whereby most maternal transcripts and proteins are degraded, followed by the generation of a new transcriptome and resulting proteome (Gao et al., 2017; Svoboda, 2018). These processes are required for the transition from maternal to embryonic control of development and create a cellular environment conducive of the totipotent state of the early embryo. There has been extensive analysis and development of tools for monitoring the changes to transcription at this time, but changes in translation have received less attention. New protein synthesis during the process of maternal to embryonic transition is tightly regulated and can be quantitatively evaluated with several methods, such as 35S-Methionine (Crosby et al., 1988), two-dimensional gel electrophoresis (Latham et al., 1991), and mass spectrometry (Gao et al., 2017). Here we report the development and use of a rapid alternative method for the analysis of global changes in the level of protein synthesis in the early embryo. The Click-iT® Plus OPP Protein Synthesis Assay is a non-toxic and non-radioactive method for the detection of nascent protein synthesis utilizing fluorescence microscopy and high-throughput imaging. O-propargyl-puromycin (OPP) is a membrane-permeable alkyne puromycin analog that forms covalent bonds with nascent polypeptide chains with cells. The addition of the Alexa Fluor® picolyl azide and the Click reaction reagents leads to a chemoselective ligation or “click” reaction between the picolyl azide dye and the alkyne OPP, and the modified proteins are detected by imaged-based analysis. The assay has been demonstrated to preserve cell morphology and has been used in NIH3T3, HeLa, C2C12 cells, BPAE, U-2 OS, CHO-M1, and A549 (Mateu-Regue et al., 2019; Enam et al., 2020; Liu et al., 2012), and the embryonic cells of preimplantation development (Li et al., 2021).
This protocol is designed to semi-quantitatively assess the relative changes in protein synthesis during the period of mouse maternal to embryonic transition. The first stage is to test and optimize the concentration of the OPP, then confirm the specificity of the assay by use of the known protein synthesis inhibitor Cycloheximide and inhibitor of translation elongation, 4EGI-1 (eIF4E inhibitor) (Li et al., 2021).
Materials and Reagents
Plastic and glass ware
60-well culture plates (Nunc, Naperville, IL, USA, LUX 5260)
35 cm × 10 mm Petri dishes (Thermo Scientific, catalog number: 150318)
Cover glasses, 18 × 18 mm (Merck, BR470045)
Microscope slides, 25 mm × 75 mm (Merck, S8902)
Animals
Six-eight-week-old female mice
Click-iT® Plus OPP Alexa Fluor® protein synthesis assay (Thermo Scientific, catalog number: C10456), including
Component A: Click-iT® OPP Reagent, 20 mM in DMSO
Component B: Alexa Fluor® 488 picolyl azide in DMSO solution
Component C: Click-iT® OPP Reaction Buffer (10× solution containing Tris-buffered saline)
Component D: Copper Protectant
Component E: Click-iT® Reaction Buffer Additive
Component F: Click-iT® Reaction Rise Buffer, containing 2 mM sodium azide.
Component G: NuclearMaskTM Blue Stain, 2,000× concentrate in water
Chemicals and reagents
Dulbecco′s Phosphate Buffered Saline (PBS) (Sigma, catalog number: D5773)
Triton X-100 (Sigma, catalog number: T8787)
Bovine serum albumin (BSA) (Sigma, catalog number: B2064)
Paraformaldehyde (PFA) (Sigma, catalog number: P6148)
DMSO (Sigma, catalog number: D8418)
Click-iT® Plus OPP Alexa Fluor® protein synthesis assay kit (see Recipes)
Fixation buffer (10 mL) (see Recipes)
1× PBS (50 mL) (see Recipes)
Permeabilization buffer (1 mL) (see Recipes)
Washing solution (10 mL) (see Recipes)
KSOM medium (see Recipes)
Equipment
Dissection microscope (Olympus, SZx7)
Nikon ECLIPSE 80i microscope, Plan Apo 40×/1.0 oil objective (Nikon, Tokyo, Japan)
pH meter SevenDirect SD20 (Mettler Toledo)
Incubator, Cytomat 2 C470-LiN (Themo Fisher Scientific)
Software
ImageJ (http://imagej.net/Fiji)
SPSS for Windows (Version 22.0, SPSS Inc., Chicago, IL, USA)
Procedure
ANIMALS AND TREATMENTS
Animals and embryo collection
Six-eight-week-old female mice were superovulated by intraperitoneal injection of 5 IU equine chorionic gonadotropin (eCG) (Ningbo Second Hormone Factory, China) and 44–48 h later, 5 IU human chorionic gonadotrophin (hCG) (Livzon, Zhuhai, China), and then placed with fertile males overnight. Pregnancy was confirmed by the presence of a copulation plug in mated females the following morning. Zygotes or two-cell embryos were recovered 20 h and 40 h post-hCG from mated females, respectively. The embryos were collected in HEPES-buffered modified human tubal fluid medium (HEPES-HTF) (O’Neill, 1997), and all components of the media were tissue culture grade (Sigma Chemical Company, St Louis, MO, USA) and contained 3 mg bovine serum albumin/mL (Sigma).
Medium preparation and treatments
Calibrate the concentration of OPP for embryo treatment
To minimize the embryonic toxicity of OPP during the period of embryo treatment, several doses of OPP should be tested. For example, dilute Component A (20 mM) with KSOM medium (Lawitts and Biggers, 1993) to produce a range of OPP concentrations (e.g., 50, 37.5, and 25 μM) to 400 µL of final working solutions (Table 1).
Table 1. Prepare a series of working solutions of Click-iT® OPP (Component A)
OPP (μM) KSOM (µL) Component A (µL) DMSO (µL) Total volume (µL)
0 399 0 1 400
25 399 0.5 0.5 400
37.5 399 0.75 0.25 400
50 399 1 0 400
The example is to prepare three doses of OPP. The control is 0 μM OPP in KSOM medium. Adjust the concentration of DMSO to 0.25% (v/v) in all working solutions.
Note: Total volume can be proportionally adjusted depending on the number of treatments; The concentration of OPP can be readjusted or optimized for the different experimental designs. A range of culture medium types are suitable for use depending upon the experimental design (e.g., hTF medium and KSOM, supplemented with or without amino acids).
OPP treatment (Figures 1 A1-4)
Set up microdrops on culture dishes. Each drop contains 50 µL of OPP working solutions overlaid with 2 mm of heavy paraffin oil (Sigma).
Optional: use 60-well Terasaki plates (LUX 5260, Nunc, Naperville, IL, USA), each containing 10 µL of OPP working solutions.
Equilibrate in 5% CO2 incubator at 37°C for 2 h.
Transfer the embryos into OPP working solutions.
Optional: embryo density is optional, e.g., 1–10 embryos in 10 µL of working solutions. Keep the same density in all treatments.
Culture and treat the embryos for 2–6 h at 37°C, with 5% CO2 in air tension.
CRITICAL: (1) It was suggested that the incubation periods with OPP be between 30 min and 1 h to maximize detection and minimize toxicity (Liu et al., 2012; Signer et al., 2014). However, translation in preimplantation embryos may be different from the somatic cells. In simple formulated medium, 2-cell embryo expressed a peak signal after 6 h treatment with 37.5 µM OPP (Li et al., 2021). Thus, we recommend testing different incubation periods (Figure 2B) with different concentrations of OPP (Figure 2 A) and doses of drugs (Figure 2C) for each stage of embryo development used before the final experimental design is determined (as in the example in Table 1). (2) Similar calibrations are suggested if the experiments are performed in different oxygen concentrations, as this protocol was designed for the OPP treatment in air tension before final experimental design is determined.
STEP-BY-STEP METHOD DETAILS
Note: To facilitate systematically processing embryos, we use 60-well Terasaki plates (Figure 1 B1–2). Each well can contain 10 µL of solution and 1–10 embryos. Transfer embryos with minimal solution into the well of the next step and use clean pipettes for each transfer stage.
Proceed to embryo fixation and permeabilization (Figure 1 B1–2)
Work at room temperature. Transfer embryos treated with OPP into washing solution and rinse once to remove the media.
Transfer embryos into 10 µL fixation buffer/well. Incubate for 15 min at room temperature.
Wash embryos twice with washing solution to remove fixative.
Transfer embryos into 10 µL of permeabilization buffer and incubate for 20 min at room temperature.
Click-iT® OPP Detection (Figure 1 B1–2)
Prepare Click-iT® reaction cocktail according to Table 2.
Table 2. Click-iT® reaction cocktail
Reaction components (as supplied in kit) Number of wells
10 wells 50 wells 100 wells
Click-iT® OPP Reaction Buffer (1× concentrate) 88 µL 0.44 mL 0.88 mL
Copper Protectant (Component D) 2 µL 10 µL 20 µL
Alexa Fluor® picolyl azide (Component B) 0.25 µL 1.25 µL 2.5 µL
Click-iT® Reaction Buffer Additive (10× solution) 10 µL 50 µL 0.1 mL
Total reaction volume 0.1 mL 0.5 mL 1 mL
Note: Use the Click-iT® reaction cocktail within 15 min of preparation. The number of wells can vary depending on the experiment. It is important to calculate the number of wells you will plate before you start the experiment.
Wash embryos twice with 10 µL of washing solution
Transfer embryos into 10 µL of Click-iT® reaction cocktail.
Incubate for 30 min at room temperature. Protected from light.
Wash once with 10 µL per well of Click-iT® reaction rise buffer (Component F).
DNA Staining (Figure 1 B1-2)
Note: The following protocol is based upon 10 µL of HCS NuclearMaskTM Blue Stain working solution per well.
Dilute HCS NuclearMaskTM Blue Stain (Component G) solution (1:2,000, v/v) in 1× PBS to obtain a 1× HCS NuclearMaskTM Blue Stain working solution.
Transfer embryos into 10 µL of 1× HCS NuclearMaskTM Blue Stain working solution. Incubate for 30 min at room temperature, protected from light.
Wash twice with washing solution and proceed to Imaging and Analysis (below).
Imaging
Make slides (Figure 1 C1–5)
Clean the glass slides and the coverslips with ethanol.
Use an insulin syringe with 18–22 G needle filled with vaseline. Make two parallel lanes of vaseline on the slide to support the coverslip. The vaseline lane should 1–2 mm thick.
Add a drop of 7 µL 1× PBS onto a slide. (Optional: use standard anti-fade mounting media).
Transfer 10 embryos/drop and gently put an 18 × 18 mm coverslip on with forceps; remove any excess fluid from edges of the coverslip with a lint-free absorbent tissue.
Seal with nail polish (optional: PathTech, https://www.pathtech.com.au). Take care not to move the coverslip to avoid squashing the embryos).
Scan the slide under fluorescence microscope with filters appropriate for DAPI/Hoechst and FITC for Alexa Fluor® 488 (Figures 2 A–C).
Whole section image is captured with mercury lamp UV illumination on a Nikon ECLIPSE 80i microscope with a Nikon Plan Apo 40×/1.0 oil objective. (Any similar fluorescent microscope systems are suitable)
Fluorescence measurement and Data analysis
Measure the intensity of the fluorescent OPP stain
The fluorescent intensity of nascent protein synthesis in the fluorescent channel in the nucleus or whole embryo can be measured by suitable analysis software, e.g., ImageJ and ImagePro Plus (Media Cybernetics, Inc.).
With ImageJ, open the images of the embryo with dual staining of OPP and NuclearMask blue stain.
In the Analyze menu, open Set Measurements and tick “Area”, “Integrated density”, “Mean gray value”, and Standard deviation”.
In the image of NuclearMask blue stain, outline the single nucleus using freehand selection of region of interest (ROI). From Analyze > Tool, open ROI Manager. Add this ROI to ROI Manager and rename it.
Allocate the ROI for the outlined nuclei from ROI Manager to the image of OPP stain of same embryo. This is the exact localization of the nucleus for the dual staining images of same embryo.
Select “Measure” from the analyze menu. The results are shown as a popup box with a stack of values for that nucleus of the embryo cell. The same way to measure the fluorescence of OPP stain of another nucleus.
Directly measure the fluorescent stain of the outlined whole embryo using freehand selection of ROI.
Record and copy the integrated density (stand for the fluorescent intensity of OPP stain) from the popup box for ROI of each nucleus or whole embryo. Set up an Excel spreadsheet for data analysis from all treatments and controls.
Subtract the values in the control treatment of 0 µM OPP from the values from all treatments and controls in the same experiments. The resulting values are used for analysis.
Statistical analysis
Statistical analysis was performed using SPSS for Windows (SPSS Inc., Chicago, IL, USA) (Optional: other Statistic software). Fluorescence intensity (AU, arbitrary units of optical density of staining) was quantitatively analyzed by univariate analysis of variance. This parameter was set as the dependent variable, while the test treatments and drug doses were the independent variables. Experimental replicates were incorporated into the model as covariates. Differences between individual independent variables were analyzed by the least significance difference test. Less than a 5% probability (P < 0.05) was considered significant.
Critical: The results from quantitative analysis of fluorescent intensity can vary between experiments due to a range of uncontrollable variables. It is therefore important that embryos from each treatment were processed at the same time and in parallel. All treatments were exposed to the same preparations and dilutions of all reagents. Similarly, all preparations from an experiment were examined microscopically within the same session, and identical microscope and camera settings were used. All image analysis was carried out in an identical manner for each embryo within an experiment. All preparations were carried out by the same experienced operator throughout the study.
Figure 2. Analysis of OPP staining in the embryonic cells. (A) Whole-section images representative of fluorescence changes in wild-type two-cell embryos treated either without or with a range of OPP concentrations for 24 h. There were at least ten embryos in each treatment group. All embryos were arrested at 2-cell stage in the 50 µM OPP group. (B) Two-cell embryos were collected from female reproductive tracts and treated with 37.5 µM OPP for 0, 2, 4, and 6 h. The images are representative of a total of 30 embryos from three independent replicates. (C) Two-cell embryos were treated with either the 4EGI-1 (EIF4E inhibitor) (Li et al., 2021) cycloheximide (CHX) (Schneider-Poetsch et al., 2010) for 6 h. Images are representative of three independent replicates for ten embryos for each treatment. (D) OPP staining intensity in embryos treated with 4EGI-1 or CHX) in (C), compared with the control (no inhibitor). Data are Mean ± S.E.M. (univariate analysis of variance). * Statistically different (P < 0.001) from all other treatments. Scale bars: 10 μm.
Recipes
Click-iT® Plus OPP Alexa Fluor® protein synthesis assay kit
Allow reagent vials to completely thaw and warm to room temperature before opening.
Prior to use, briefly centrifuge Click-iT® OPP Reagent (Component A) and NuclearMaskTM Blue Stain (Component G) to maximize reagent recovery.
Prepare a 10× stock solution of the Click-iT® Reaction Buffer Additive (Component E). Add 2 mL of deionized water to the vial (containing 400 mg) and mix until completely dissolved. After use, aliquot 50 µL/each, store any remaining stock solution at ≤ –20°C.
Note: When stored as directed, this stock solution is stable for up to 1 year.
Prepare 1× Click-iT® OPP Reaction Buffer.
Transfer all the solution in the Component C bottle (4 mL) to 36 mL of deionized water. Rinse the Component C bottle with some of the diluted Click-iT® OPP Reaction Buffer to ensure the transfer of all the 10× concentrate.
Note: Use the Click-iT® reaction cocktail within 15 min of preparation. To prepare smaller amounts of 1× Click-iT® OPP Reaction Buffer, dilute 1 volume from the Component C bottle with nine volumes of deionized water. After use, store any remaining 1× solution at 2°C–8°C. When stored as directed, 1× Click-iT® OPP Reaction Buffer is stable for 6 months.
Prepare working solution of NuclearMaskTM Blue Stain (Component G).
Prepare it just prior to use. Dilute HCS NuclearMaskTM Blue Stain (Component G) solution 1:2,000 in PBS to obtain a 1× HCS NuclearMaskTM Blue Stain working solution.
Fixation buffer [3.6% (w/v) Paraformaldehyde in PBS] (10 mL)
Weigh Paraformaldehyde 0.37 g.
Add to MilliQ H2O 10 mL in a glass container.
Add 1.0 M NaOH 14 µL.
Warm and stir on a 50–60°C hotplate until completely dissolved. It takes about 20 min.
Add PBS 0.096 g and stir until completely dissolved.
Cover the container and leave until it reaches room temperature.
Adjust pH at 7.4 with 1 N HCl at room temperature.
1× PBS (50 mL)
Weigh 0.4798 g PBS powder.
Add into 50 mL MilliQ H2O and mix well.
Permeabilization buffer (1 mL)
Prepare prior to use.
5 µL of Triton X-100
Add into 995 µL of 1× PBS and mix well.
Washing solution (10 mL)
Weigh 0.3 g BSA
Add into 10 mL of 1× PBS. Make sure it is completely dissolved before use.
Note: Always use the fume hood and follow safety measures when preparing and handling paraformaldehyde. Personal protection equipment should be used during use.
Composition of KSOM medium (100 mL)
555 mg of NaCl
18.5 mg of KCl
4.75 mg of KH2PO4
4.95 mg of MgSO4•7H2O
25 mg of CaCl2•2H2O
210 mg of NaHCO3
3.6 mg of Glucose
2.2 mL of Na-Pyruvate
0.174 mL of DL-Lactic Acid
4 mg of EDTA
14.6 mg of GL-Glutamine and 100 mg Bovine serum albumin
Note: All reagents were purchased from Sigma.
Add MilliQ purified water to 100 mL, mix well, and sterilize by filtration with 22 mm Millex-GV Filter, 0.22 µm (MERCK).
Acknowledgments
We thank Nanjing Your Bio-tech Development Ltd. Co (Jiangbei New District, Nanjing, Jiangsu Province, China) for the generous donation of all embryonic culture media: KSOM, HEPES-HTF, and HTF.
FUNDING: This work was supported by grants from the National Natural Science Foundation of China awarded to X.J (81471458), and Zhejiang Provincial Natural Science Foundation of China (LQ21H040010) to Y.L.
Competing interests
The authors declare no competing interests
AUTHOR CONTRIBUTIONS: X. Jin. and C.O. supervised the study. X. Jin. C.O. and X.H. designed and wrote the manuscript. Y.L., X.J. L.C., J.T., M.H., and J.L. performed the experiments.
Ethics
Animal experiments were approved by and conducted according to ethics guidelines from relevant research institutes and universities. Hybrid (C57BL/6 X CBA/He) mice were housed and bred at the Wenzhou Medical University.
References
Crosby, I. M., Gandolfi, F. and Moor, R. M. (1988). Control of protein synthesis during early cleavage of sheep embryos. J Reprod Fertil 82(2): 769-775.
Enam, S. U., Zinshteyn, B., Goldman, D. H., Cassani, M., Livingston, N. M., Seydoux, G. and Green, R. (2020). Puromycin reactivity does not accurately localize translation at the subcellular level. Elife 9: e60303.
Gao, Y., Liu, X., Tang, B., Li, C., Kou, Z., Li, L., Liu, W., Wu, Y., Kou, X., Li, J., et al. (2017). Protein Expression Landscape of Mouse Embryos during Pre-implantation Development.Cell Rep 21(13): 3957-3969.
Latham, K. E., Garrels, J. I., Chang, C. and Solter, D. (1991). Quantitative analysis of protein synthesis in mouse embryos. I. Extensive reprogramming at the one- and two-cell stages. Development 112(4): 921-932.
Lawitts, J. A. and Biggers, J. D. (1993). Culture of preimplantation embryos. Methods Enzymol 225: 153-164.
Li, Y., Tang, J., Ji, X., Hua, M. M., Liu, M., Chang, L., Gu, Y., Shi, C., Ni, W., Liu, J., et al. (2021). Regulation of the mammalian maternal-to-embryonic transition by eukaryotic translation initiation factor 4E. Development 148(12).
Liu, J., Xu, Y., Stoleru, D. and Salic, A. (2012). Imaging protein synthesis in cells and tissues with an alkyne analog of puromycin.Proc Natl Acad Sci U S A 109(2): 413-418.
Mateu-Regue, A., Christiansen, J., Bagger, F. O., Winther, O., Hellriegel, C. and Nielsen, F. C. (2019). Single mRNP Analysis Reveals that Small Cytoplasmic mRNP Granules Represent mRNA Singletons. Cell Rep 29(3): 736-748 e734.
O'Neill, C. (1997). Evidence for the requirement of autocrine growth factors for development of mouse preimplantation embryos in vitro.Biol Reprod 56(1): 229-237.
Schneider-Poetsch, T., Ju, J., Eyler, D. E., Dang, Y., Bhat, S., Merrick, W. C., Green, R., Shen, B. and Liu, J. O. (2010). Inhibition of eukaryotic translation elongation by cycloheximide and lactimidomycin. Nat Chem Biol 6(3): 209-217.
Signer, R. A., Magee, J. A., Salic, A. and Morrison, S. J. (2014). Haematopoietic stem cells require a highly regulated protein synthesis rate. Nature 509(7498): 49-54.
Svoboda, P. (2018). Mammalian zygotic genome activation.Semin Cell Dev Biol 84: 118-126.
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Correction Notice: In vitro Dephosphorylation Assay of c-Myc
Peng Liao
WW Weichao Wang
XG Xin Ge
Published: Jun 5, 2022
DOI: 10.21769/BioProtoc.4442 Views: 287
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In the manuscript "In vitro Dephosphorylation Assay of c-Myc" (https://bio-protocol.org/e2011), the affiliation of Peng Liao and Weichao Wang were incorrect. The correct affiliations for Peng Liao and Weichao Wang are Department of Clinical Laboratory Medicine, Shanghai Tenth People’s Hospital of Tongji University, Shanghai, China.
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Protocol to Study Spatial Subgoal Learning Using Escape Behavior in Mice
PS Philip Shamash
TB Tiago Branco
Published: Vol 12, Iss 12, Jun 20, 2022
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The authors used this protocol in Nature Neuroscience Jul 2021
Abstract
Rodent spatial navigation is a key model system for studying mammalian cognition and its neural mechanisms. Of particular interest is how animals memorize the structure of their environments and compute multi-step routes to a goal. Previous work on multi-step spatial reasoning has generally involved placing rodents at the start of a maze until they learn to navigate to a reward without making wrong turns. It thus remains poorly understood how animals rapidly learn about the structure of naturalistic open environments with goals and obstacles. Here we present an assay in which mice spontaneously memorize two-step routes in an environment with a shelter and an obstacle. We allow the mice to explore this environment for 20 min, and then we remove the obstacle. We then present auditory threat stimuli, causing the mouse to escape to the shelter. Finally, we record each escape route and measure whether it targets the shelter directly (a ‘homing-vector’ escape) or instead targets the location where the obstacle edge was formerly located (an ‘edge-vector’ escape). Since the obstacle is no longer there, these obstacle-edge-directed escape routes provide evidence that the mouse has memorized a subgoal location,i.e., a waypoint targeted in order to efficiently get to the shelter in the presence of an obstacle. By taking advantage of instinctive escape responses, this assay probes a multi-step spatial memory that is learned in a single session without pretraining. The subgoal learning phenomenon it generates can be useful not only for researchers working on navigation and instinctive behavior, but also for neuroscientists studying the neural basis of multi-step spatial reasoning.
Keywords: Spatial memory Mouse Behavior Navigation Escape Defensive behavior Subgoals Neuroscience
Background
In previous work, rodent escape behavior has been used to study goal-directed spatial navigation in the context of obstacle-free environments. In the standard Barnes Maze assay (Barnes, 1979; Harrison et al., 2006), rodents are placed in an open-field arena with an underground shelter and presented with an ongoing aversive stimulus such as a bright light. Rodents locate the enclosed space in the environment (the shelter), instinctively adopt it as their home base, and run to it when faced with threatening stimuli such as loud sounds. Over multiple sessions, animals learn to navigate efficiently to the shelter using spatial memory. Work from our laboratory has provided three updates to this protocol (Vale et al., 2017, 2018): the learning period and escape testing all occur within a single session; the mouse’s self-motivated exploratory behavior proceeds without having to remove the mouse from the arena; and sudden-onset threat stimuli are used to evoke robust, shelter-directed escape paths. Our new protocol builds on that assay by adding (and dynamically modifying) structure in the environment. In this environment with an obstacle, mice learn a hierarchy of goals: the ultimate goal (the shelter) and two subgoal locations (the sides of the obstacle) that the animal uses to plan efficient routes to the ultimate goal. Thus, our protocol can allow researchers to investigate how animals rapidly learn multi-step routes to a shelter during a single session of self-motivated exploration.
Unlike this approach, prior work on multi-step spatial reasoning has focused on repeatedly placing an animal at the start of a constrained maze environment and testing how it learns to reach a food reward while minimizing erroneous turns (Tolman and Honzik, 1930; Sharma et al., 2010). These assays have several advantages: they assess long-term memory over multiple sessions/days; they induce stereotyped paths across animals; and they rely on a particularly stable and controllable source of motivation,i.e., hunger. However, they also leave out several key aspects of spatial reasoning. For one, they disregard how animals explore and rapidly compute routes in natural environments, which include both open space (allowing a much wider range of possible actions) and obstacles (necessitating multi-step reasoning). In addition, they lack a stimulus that can trigger immediate, goal-directed behavior. Thus, it is unclear if the animal’s ‘errors’ reflect a lack of understanding or merely a decision not to exploit a known route to the goal. Our assay—escape to shelter in the presence of obstacles—complements previous work on maze learning by incorporating these elements into the study of multi-step route learning.
Finally, escape to shelter in the presence of obstacles has been studied before, with gerbils (Ellard and Eller, 2009). Our protocol differs from this work primarily in its methods for evoking immediate and robust escape responses, ruling out visual-guided strategies, and quantitatively measuring subgoal learning. Our protocol was initially developed in Shamash et al. (2021) and then improved upon in Shamash and Branco (2021), which includes the automated threat presentation and removable obstacle panel features described below.
Materials and Reagents
Paper towels
C57BL/6J adult male or female mice, purchased from Charles River, 8–12 weeks of age. Animals were tested during the light phase of a 12-h light/dark cycle and had been singly housed for ≥5 days by the time of testing (see Note 1). No pretraining or habituation is necessary.
70% ethanol
Equipment
Behavioral arenas
A 92 cm diameter circular arena, made of 5 mm thick white acrylic, with a 10 cm × 50 cm rectangular hole cut from the middle; and a similar 92 cm diameter circular arena without a hole in it, to be placed beneath the platform with the hole ( Figure 1 ).
Panel with obstacle
50 cm long × 10 cm wide panel with a 50 cm-long × 12.5 cm tall obstacle attached along the central axis, made of 5 mm thick white acrylic (Figure 1).
Flat panel
An identical 50 cm long × 10 cm wide panel (Figure 1B).
Stand to support the elevated behavioral arena, ≥20 cm tall
The stand should stably support the 92 cm diameter arena without sticking out beyond the perimeter of the arena. For example, a 62.5 cm cubic base would work (igure 1A).
Shelter
10 cm long × 10 cm wide × 15 cm tall cube of transparent red acrylic (opaque to the mouse). It includes a mouse-hole-shaped entrance at the front (Figure 1).
Video camera
acA1300-60gmNIR, Basler, with a near-infrared selective filter, positioned 1 m above the behavioral arena (Figure 1A).
Amplifier (Topaz AM10, Cambridge Audio) and speaker (L60, Pettersson) hooked up to the computer used to control the experiment.
Infrared LED illuminators (TV6700, Abus; 850 nm light) distributed above the platform for infrared video recording (we use six illuminators).
Sound level meter (Castle GA213)
Auditory stimulus sound files (Supplementary Audio 1-2). Two sounds were downloaded from soundbible.com (‘smashing’ and ‘crackling fireplace’). They were then edited manually in Audacity 2.3.0, such that they were 1.5 s long and continuously loud.
Recommended: Infrared LED (850 nm OSLON PowerStar IR LED), hooked up to the auditory threat signal coming from the amplifier and therefore flashing infrared light toward the video camera whenever an auditory stimulus occurs.
Optional : A large, sound-proof box (160 cm wide × 165 cm deep × 190 cm tall). Alternatively, surround the arena with any dark material such as thin black plastic, at least 30 cm above the height of the arena, to make the environment less exposed and so less stressful for the mice.
Optional: Projector (BenQ) and projector screen (Xerox). We used a projector to illuminate the arena, because we also perform experiments with visual stimuli in the same arena. However, illuminating the arena with a lamp should be sufficient. During experiments, the screen was illuminated with uniform, gray light at 5 cd m-2 (this measures the incoming light from the projector coming onto the projector screen). A rectangular hole was cut in the projector screen, and the video camera and speaker were placed just above this hole, 1 m above the center of the behavioral arena.
Figure 1. Shelter + obstacle environment. A. Schematic of the relative positions of the equipment used to build and record from the shelter + obstacle environment. B. Top view of the behavioral arena. During the obstacle removal experiment, the obstacle panel is replaced with the flat panel, by the experimenter. The suggested threat zone (not visibly marked on the actual platform) is 50 cm long and extends 15 cm from rightmost point of the platform. C. Picture of the platform with the obstacle panel in place and the mouse peeking out of the shelter.
Software
Video recording and automated stimulus presentation program, written using Bonsai 2.4.1. Online mouse tracking was based on the mouse being darker than the white acrylic platform (sample code available at github.com/philshams/bonsai-behavior).
Post-hoc animal tracking, DeepLabCut (Mathis et al. , 2018)
https://github.com/philshams/behavior-opto-analysis )
Procedure
Perform two types of experiments, in two groups of mice: a baseline-escape experiment in which escapes are triggered in an arena with no obstacle present, and an obstacle removal experiment in which mice explore the arena with an obstacle present for 20 min, and then the obstacle is removed and escapes are triggered. We recommend performing these experiments in two separate groups of mice. If it is necessary to reuse mice, allow 3–7 days in-between experimental sessions.
Set up and test the behavioral rig
Place the acrylic arena with no hole on top of the stand and the arena with the rectangular hole on top of that. Obstacle removal experiment: Place the panel with the obstacle in the hole. Baseline-escape experiment: Place the flat panel in the hole.
Test the auditory stimuli through the overhead speaker by placing the sound level meter on the perimeter of the arena, pointing towards the speaker. Ensure that it is playing at a volume of 84 dB.
Test the video and automated stimulus presentation program, by moving a black, mouse-sized object into the threat zone and ensuring that an auditory stimulus is triggered.
Ensure that the arena is lit just well enough for the mouse to easily see and target the obstacle (~5 cd m-2 ; see Equipment 12 and Notes).
Clean the arena, shelter, and obstacle by wiping them with 70% ethanol, and then wait at least 5 min before beginning an experiment.
Begin the behavioral session with a spontaneous exploration period
Place the mouse in the arena in a consistent location across sessions, e.g. , in between the obstacle and shelter, and initiate the behavioral program. Mice were picked up by the base of the tail, with a hand positioned to support their body as they were placed onto the arena. Previous handling of mice was limited to routine animal husbandry.
The mouse should spontaneously enter the shelter within the first 7 min, and henceforth treat it as its preferred location. If this does not consistently occur, see the Notes below for help.
Obstacle removal experiment: Allow the mouse to spontaneously explore the arena for 20 min total. Baseline-escape experiment: Allow the mouse to spontaneously explore the arena for 7 min total.
Throughout the session: if the mouse does not leave the shelter for 5 min or does not enter the threat zone for 10 min, scatter one pinch (1 g) of bedding from its home cage in the threat area, for a maximum of once per session.
Obstacle removal experiment : Remove the obstacle from the arena
After 20 min, as soon as the mouse enters the shelter, quietly lift and remove the obstacle panel and replace it with the flat panel. If this is not done stealthily, it could frighten the mouse, causing it to stay in the shelter for most of the experiment. Details will depend on the layout of the experimental room, but typically, this should be done with 15 s. If the mouse starts to leave the shelter after the panel switch was already initiated, we recommend calmly completing the switch.
Trigger auditory threat stimuli
Use an automated software program (we use custom software in Bonsai) to track the mouse location online and trigger a threat stimulus in the following conditions: the mouse is currently in the threat zone, the mouse was in the threat zone 1.5 s prior, and the mouse has positive velocity in the direction opposite of the shelter.
The threat stimulus consists of 1.5-s sounds, automatically played on repeat until the mouse gets within 20 cm of the shelter, or for a maximum of 9 s. A ‘crash’ sound and a ‘smash’ sound (Supplementary Audio 1-2) are alternated every other trial, to prevent stimulus habituation.
If the mouse does not successfully escape during the stimulus, increase the stimulus volume by 2 dB, up to a maximum of 88 dB.
End the experiment after one hour or six successful escape trials, whichever comes first.
Data analysis
Post-hoc tracking
Use DeepLabCut to track the position of the mouse at each frame in the video. We find that averaging across multiple tracked body parts leads to more robust tracking. Specifically, we average 13 points: nose, left eye, right eye, left ear, right ear, neck, left upper limb, right upper limb, upper back, left lower limb, right lower limb, lower back, and tail base. However, a single point in the area of the mouse’s neck or upper back will work as well.
Compute the mouse’s speed at each frame in the video and its speed relative to the shelter location, convert these to cm s-1 , and smooth these data with a Gaussian filter (σ = 100 ms, length = 800 ms).
Escape target score and trajectory classification
To quantify escape trajectories, calculate the ‘initial escape target score’ (Figure 2). This is a metric where a vector aimed directly at the shelter receives a value of 0; one aimed at either obstacle edge receives a value of 1.0; a vector halfway between these scores 0.5; and a vector that points beyond the edge receives a value greater than 1.0. The initial escape target was computed by taking the mouse’s position when it is 10 cm in front of the obstacle and comparing the offset between this latter position to where it would have been if it escaped directly toward the shelter or toward the obstacle edge. This is calculated as
where offset HV is the distance from the mouse to the line between the mouse’s starting position and the shelter (the ‘shelter direction’ line in Figure 2); offset EV is the distance from the mouse to the line between the mouse’s starting position and the obstacle edge vector (the ‘edge direction’ line in Figure 2); and offset HV–EV is the distance from the shelter-direction line to the edge-direction line (Figure 2). If the escape path deviates to the left of the homing-vector path, then the left obstacle edge is used to calculate offset EV and offset HV–EV (and vice versa). Each data point receiving a score corresponds to one escape route.
To classify an escape as either an edge vector or homing vector, threshold the initial escape target score using the 95th percentile of scores from a group of mice escaping in an environment with no obstacle. In our hands, this value was 0.65. Expect 40–60% edge-vector responses in the subgoal-learning group.
Computing where the mouse would have been if it ran directly toward the shelter or obstacle edge requires first identifying the escape initiation point. For a simple measurement of escape initiation, use the point at which the mouse exceeds a speed of 20 cm s−1 relative to (towards) the shelter location. This is computed by taking the frame-by-frame difference in the mouse’s distance from the shelter. The key is to use a metric that is approximately where the escape begins but does not include the non-escape movements that sometimes occur after threat onset but before escape initiation.
Statistical permutation test
Use a non-parametric permutation test to give more weight to mice that have performed more escape trials, while still scaling the degrees of freedom with the number of mice. Alternative tests do not work as well here: using each trial’s data in a t-test or Mann-Whitney test would improperly scale the degrees of freedom with the number of trials, and using a repeated-measures ANOVA would impose a Gaussian-noise assumption that the data are unlikely to follow. To test if group A and group B have different propensities to perform edge-vector escapes, use the signed difference in the groups’ mean pooled edge-vector probability as the test statistic (i.e., group B% edge vectors – group A% edge vectors). Generate a null distribution of this value by randomly shuffling the group labels for each mouse (i.e., in each shuffle, all of a given mouse’s escape trials are assigned to either group A or B). Then, find the percentile that the actual difference in means occupies within this distribution—this is the p-value for the hypothesis that group B does more edge vectors than group A.
Additional parameters
Data exclusion: exclude mice with zero successful escape trials.
Number of replicates: use 8–14 mice per condition.
Figure 2. Classifying escape trajectories. The initial escape target uses the mouse’s position 10 cm in front of the obstacle (gray and green dots), normalized between 0 (direct path from the escape initiation point to shelter) and 1 (direct path from the escape initiation point to the obstacle edge location). Escape initiation (mouse silhouette on top) is where the mouse’s speed relative to the shelter exceeds 20 cm/s. The dotted line represents the location where the obstacle had been during the 20-min exploration period. A. A homing-vector escape response, with an initial escape target of 0.53. This is less than the threshold value of 0.65 at which point escapes are classified as edge vectors. B. An edge-vector escape response. C. Closeup of the offset distances used to compute the escape target score. Offset EV (green) is the distance from the mouse to the edge-vector line. Offset HV (gray) is the distance from the mouse to the homing-vector line. Offset HV-EV (blue) is the length of the line connecting the edge-vector and homing-vector lines, with the constraint that this line must pass through the average of the two vectors at the point 10 cm in front of the obstacle (i.e., it must pass through the point corresponding to an escape target score of 0.5). Figure adapted from Shamash and Branco (2021).
Notes
There is one key ‘dimension’ along which mouse behavior tends to vary across individuals: shelter-resting vs. vigorously exploring. Both extremes can be problematic in terms of producing enough escape trials. Mice that stay in the shelter may never enter the threat zone. On the other hand, mice that prefer exploration to being in the shelter may fail to escape to shelter in response to the threat stimulus. For example, group-housed mice explore more but may fail to respond to multiple trials of threat stimuli, while singly housed mice explore less but respond more consistently to threat stimuli. Additional factors that promote shelter resting include: adding a pinch of bedding from the mouse’s cage into the shelter, increasing the background illumination, and using a mouse in multiple behavioral sessions. Factors that promote exploration include: adding a pinch of bedding to the threat zone, decreasing background illumination, performing experiments during the dark phase of the light-dark cycle, using food-restricted mice and using young (7–8 week old) mice.
Acknowledgments
Our laboratory used this protocol to assess subgoal learning in two recent publications ( Shamash and Branco, 2021 ; Shamash et al. , 2021 ). The work was supported by a Wellcome Senior Research Fellowship (214352/Z/18/Z) and by the Sainsbury Wellcome Centre Core Grant from the Gatsby Charitable Foundation and Wellcome (090843/F/09/Z) (T.B.) and the Sainsbury Wellcome Centre PhD Programme. We thank R. Vale and other members of the Branco lab for help in developing this assay; and J. Aloor for comments on the manuscript.
Competing interests
The authors declare that there are no any conflicting and/or competing interests.
Ethics
All experiments were performed under the UK Animals (Scientific Procedures) Act of 1986 (PPL 70/7652) after local ethical approval by the Sainsbury Wellcome Centre Animal Welfare Ethical Review Body.
References
Barnes, C. A. (1979). Memory deficits associated with senescence: a neurophysiological and behavioral study in the rat. J Comp Physiol Psychol 93(1): 74-104.
Ellard, C. G. and Eller, M. C. (2009). Spatial cognition in the gerbil: computing optimal escape routes from visual threats. Anim Cogn 12(2): 333-345.
Harrison, F. E., Reiserer, R. S., Tomarken, A. J. and McDonald, M. P. (2006). Spatial and nonspatial escape strategies in the Barnes maze. Learn Mem 13(6): 809-819.
Mathis, A., Mamidanna, P., Cury, K. M., Abe, T., Murthy, V. N., Mathis, M. W. and Bethge, M. (2018). DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat Neurosci 21(9): 1281-1289.
Shamash, P., Olesen, S. F., Iordanidou, P., Campagner, D., Banerjee, N. and Branco, T. (2021). Mice learn multi-step routes by memorizing subgoal locations. Nat Neurosci 24(9): 1270-1279.
Shamash, P. and Branco, T. (2021) Mice identify subgoal locations through an action-driven mapping process. preprint. Neuroscience.
Sharma, S., Rakoczy, S. and Brown-Borg, H. (2010). Assessment of spatial memory in mice. Life Sci 87(17-18): 521-536.
Tolman, E. C. and Honzik, C. H. (1930). Introduction and removal of reward, and maze performance in rats. University of California Publications in Psychology 4: 257-275.
Vale, R., Evans, D. and Branco, T. (2018). A Behavioral Assay for Investigating the Role of Spatial Memory During Instinctive Defense in Mice. J Vis Exp (137): 56988.
Vale, R., Evans, D. A. and Branco, T. (2017). Rapid Spatial Learning Controls Instinctive Defensive Behavior in Mice. Curr Biol 27(9): 1342-1349.
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Quantitative Analysis of Redox Pool (NAD+, NADH Content) in Plant Samples Under Aluminum Stress
Jay Prakash Awasthi
BS Bedabrata Saha
HK Hiroyuki Koyama
SP Sanjib Kumar Panda
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4444 Views: 2116
Reviewed by: Khyati Hitesh ShahAbhijit Arun DasputeTaraka Ramji Moturu
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Original Research Article:
The authors used this protocol in Scientific Reports Jun 2019
Abstract
Nicotinamide adenine dinucleotide (NAD) is an essential cofactor of numerous enzymatic reactions found in all living cells. Pyridine nucleotides (NAD+ and NADH) are also key players in signaling through reactive oxygen species (ROS), being crucial in the regulation of both ROS-producing and ROS-consuming systems in plants. NAD content is a powerful modulator of metabolic integration, protein de-acetylation, and DNA repair. The balance between NAD oxidized and reduced forms, i.e., the NADH/NAD+ ratio, indicates the redox state of a cell, and it is a measurement that reflects the metabolic health of cells. Here we present an easy method to estimate the NAD+ and NADH content enzymatically, using alcohol dehydrogenase (ADH), an oxido-reductase enzyme, and with MTT (3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide) as the substrate and 1-methoxy PMS (1-Methoxy-5-methylphenazinium methyl sulfate) as the electron carrier. MTT is reduced to a purple formazan, which is then detected. We used Arabidopsis leaf samples exposed to aluminum toxicity and under untreated control conditions. NADH/NAD+ connects many aspects of metabolism and plays vital roles in plant developmental processes and stress responses. Therefore, it is fundamental to determine the status of NADH/NAD+ under stress.
Keywords: NAD+ NADH Stress Aluminum Arabidopsis Redox status
Background
Nicotinamide adenine dinucleotide (NAD) is an important coenzyme ubiquitously found in all living cells. The balance between the oxidized and reduced forms of NAD (the NADH/NAD+ ratio) is crucial to cell survival. This ratio is an important component that indicates the redox state of a cell, important for major cellular processes like signal transduction and epigenetics, and reflects both the metabolic activities and the health of cells. NAD+ is responsible for the transfer of electrons between molecules during metabolic processes; therefore, its levels are essential for maintaining normal cellular respiratory function. Furthermore, NAD functions in modulating cellular redox status and controlling signaling and transcriptional events (Awasthi et al., 2019).
Depletion of NAD in cells is a major cause of cell death. Quantifying the generation and consumption of pyridine nucleotides, NADH and NAD+, is important to monitor enzymatic reactions or screen the modulator or product of these enzyme reactions. Pyridine nucleotides are involved in other defense and signaling reactions, such as nitric oxide production and metabolism of reactive lipid derivatives. NAD status can alter photosynthesis and plant stress responses (Dutilleul et al., 2003), suggesting that NAD content is a powerful modulator of metabolic integration (Dutilleul et al., 2005). NADH and NAD+ are also key players in signaling through reactive oxygen species (ROS) (Moller, 2001; Apel and Hirt, 2004; Mittler et al., 2004; Foyer and Noctor, 2005). NAD-consuming reactions are of importance in stress conditions for signaling in interactions with ROS and other redox components. A balance in the rates of oxidation and reduction of these nucleotides is a prerequisite for the continuation of both catabolic and anabolic processes. Therefore, the NADH/NAD+ ratio is a proxy for the metabolic state of plant cells, and determining its content under stress is fundamental for understanding stress response mechanisms.
Materials and Reagents
96-well plate (Tarsons Product, India)
50 mL centrifuge tubes (Tarsons Product, India)
1.5/2 mL tubes (Tarsons Product, India)
Root sample of Arabidopsis genotype Col-0
Double distilled water
Planton box (Tarsons Product, catalog number: 020080, size: 75 × 75 × 100mm)
Sodium hypochlorite (NaOCl) (Himedia Laboratories, catalog number: PCT1311-5X50M)
Calcium chloride (CaCl2) (Himedia Laboratories, catalog number: PCT0004-500G)
Aluminum chloride (AlCl3) (Merck, catalog number: 8010810100)
Nicotinamide adenine dinucleotide (NAD) (Sigma-Aldrich, catalog number: NAD100-RO-1G)
Nicotinamide adenine dinucleotide hydrogen (NADH) (Sigma-Aldrich, catalog number: 10107735001-500MG)
Magnesium sulphate heptahydrate (MgSO4·7H2O) (Himedia Laboratories, catalog number: RM684-5KG)
Manganese (II) Sulphate pentahydrate (MnSO4·5H2O) (FUJIFILM Wako Pure Chemical Corporation, catalog number:139-00825)
Ferrous sulphate heptahydrate (FeSO4·7H2O) (Himedia Laboratories, catalog number: GRM3917-500G)
Zinc sulphate hepta hydrate (ZnSO4·7H2O) (Himedia Laboratories, catalog number: PCT0118-1KG)
Copper (II) sulphate pentahydrate (CuSO4·5H2O) (Himedia Laboratories, catalog number: RM630-500G)
Potassium nitrate (KNO3) (Himedia Laboratories, catalog number: RM1401-500G)
Boric acid (H3BO3) (Himedia Laboratories, catalog number: MB007-1KG)
Sodium phosphate monobasic anhydrous (NaH2PO4) (Himedia Laboratories, catalog number: MB183-500G)
Ammonium molybdate tetrahydrate ((NH4)6Mo7O24·4H2O) (Sigma-Aldrich, catalog number: 431346)
Cobalt (II) chloride hexahydrate (CoCl2·6H2O) (Himedia Laboratories, catalog number: PCT0103-500G)
EDTA, disodium salt hydrate (Na2EDTA) (Sigma-Aldrich, catalog number: E5134)
Sodium nitrate (NaNO3) (Himedia Laboratories, catalog number: GRM1184-500G)
Sodium phosphate monobasic dihydrate (NaH2PO4·2H2O) (Sigma-Aldrich, catalog number: 71505)
Sodium phosphate dibasic dodecahydrate (Na2HPO4·12H2O) (Sigma-Aldrich, catalog number: 71649)
Calcium chloride dihydrate (CaCl2·2H2O) (Himedia Laboratories, catalog number: MB034-500G)
Sodium hydroxide pellets (NaOH) (Himedia Laboratories, catalog number: MB095-500G)
Hydrochloric acid (HCl) (Himedia Laboratories, catalog number: AS004-2.5L)
Tris base (Sigma-Aldrich, catalog number: T1503)
Bicine (Sigma-Aldrich, catalog number: B3876)
3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) (Sigma-Aldrich, catalog number: 1.11714-1G)
1-Methoxy-5-methylphenazinium methyl sulfate (1-methoxy PMS) (Sigma-Aldrich, catalog number: M8640-100MG)
Alcohol dehydrogenase (ADH), from Yeast (Sigma-Aldrich, catalog number: A7011)
0.2 M NaOH solution
Modified MGRL solution (see Recipe 1)
Bicine/NaOH buffer (see Recipe 2)
1 M Tris-HCl (see Recipe 3)
10 M Ethanol (see Recipe 4)
80 mM EDTA-2Na (see Recipe 5)
ADH solution (see Recipe 6)
Reaction Mixture (see Recipe 7)
NAD standard (see Recipe 8)
NADH standard (see Recipe 9)
Equipment
Weighing balance (Sartorious, 0.1 mg–220 g)
Pipettes/multi-channel pipette (Gilson, Pipettman, 2-2020-200 and 100–1000 µL)
pH meter (pH Tutor, Eutech Instrument)
Centrifuge (Eppendorf 5424 Microcentrifuge)
Magnetic stirrer with hot plate (Tarsons Product, India)
Micro pestle (Tarsons Product, India)
Autoclave (Equitron, Equitron Medica Pvt. Ltd., India)
Water bath (Equitron unstirred water bath, Equitron Medica Pvt. Ltd., India)
pH test paper (Himedia Laboratories, India)
Microtiter plate reader (SUNRISE microplate reader, TECAN)
Nylon mesh (100 µM pore size)
Fuji film plastic mounts, 35 mm (Fuji photo Co. Ltd. Japan)
Procedure
Surface sterilize viable Arabidopsis seeds in a 1.5 mL centrifuge tube with 1% Sodium hypochlorite for 3 min and rinse five times in autoclaved distilled water. Carry out all procedures inside a laminar flow hood to avoid contamination. Keep the rinsed seeds at 4°C for vernalization in dark conditions. After 2 days, place the vernalized seeds on the nylon mesh mounted on Fujifilm plastic mounts, and allow them to float on a Planton box already filled with modified MGRL solution (Recipe 1) in aseptic conditions, at 20 ± 2°C, with a photoperiod of 14 h, and with a photon flux density of 220 μmol m-2 sec-1 (PAR). After 5 days, with one hand decant the modified MGRL and replace with the treatment solution (10 μM AlCl3 solution containing 100 μM CaCl2, pH 5.0); while replacing the solution, hold the Fujifilm plastic mounts with the mesh bearing the seedlings on the other hand, using forceps. Harvest samples (whole plant tissue) for the redox pool assay at 6 and 12 h after the beginning of the treatment (Figure 1).
Grind samples (whole plant tissue, 100 mg) in liquid nitrogen with a micro pestle in a 1.5 mL centrifuge tube, and then extract with 1 mL of 0.2 N HCl. Centrifuged the homogenate at 16,000 × g and 4°C for 10 min; make multiple aliquots of the supernatant (0.2 mL each) for replicates.
Figure 1. Arabidopsis plant grown in aseptic condition on MGRL hydroponic solution.
For the NAD+ assay, incubate 0.2 mL of extract in boiling water (98–100°C) for 1 min, and then cool it rapidly and neutralize it by adding 20 µL of 0.2 M NaH2PO4 (pH 5.6), followed by the stepwise addition of 0.2 M NaOH aliquots. Vortex the sample after each addition and check pH with pH indicator paper. The final pH should be between 5 and 6, which requires approximately 0.16 mL of 0.2 M NaOH.
To measure NADH, extract leaf samples as for NAD+ but with 0.2 M NaOH as the extraction medium, and neutralize the heated supernatant aliquot with 0.2 N HCl to a final pH of 7–8 for all samples. This requires approximately 0.14 mL of 0.2 N HCl. Vortex the sample after each addition and verify pH with pH indicator paper.
Prepare the enzymatic reaction mixture as follows:
Add MTT and 1-Methoxy PMS in separate tubes and dissolve in water (prepare these solutions at room temperature) (see Recipe 7).
Add 2 mL of 1 M Bicine/NaOH Buffer, 0.4 mL of 1 M tris, 1 mL of 80 mM EDTA, and 1 mL of 10 M ethanol in a 50 mL centrifuge tube (see Recipe 7).
Add the dissolved MTT and 1-Methoxy PMS to the 50 mL centrifuge tube, adjust the final volume to 20 mL, and incubate in a water bath at 25°C until further use (see Recipe 7). This solution will act as the reaction mixture.
Prepare the ADH solution and keep it on ice (see Recipe 6).
Add 40 μL of each standard sample (see Recipe 8 for NAD+, 9 for NADH), plant sample (from step 3 for NAD+ and from step 4 for NADH), and blank sample (40 μL water) to a 96-well plate.
Add ADH (4 µL) to the reaction mixture (156 µL) and gently mix.
Add 160 µL of enzymatic reaction mixture into each sample well of the 96-well plate and immediately measure the absorbance using a microtiter plate reader.
Set the parameter for measurement of absorbance as: measurement filter, 570 nm; and kinetics, 10 measurements at 1 min intervals, shaking for 5 s before every reading.
Plot the standard graphs of NAD+ and NADH in a Microsoft Excel spreadsheet and further evaluate the plant sample contents (Figure 2).
Figure 2. Standard curve for NAD+ (A) and NADH (B). Absorbance measured at 570 nm.
Data analysis
All analysis and graph plotting was done using Microsoft Office Excel 2016 spreadsheets. Each experiment was repeated thrice and the data presented are mean ± standard error (SE). Significance was tested with one-way ANOVAs. Duncan’s multiple range test (DMRT) was performed for comparison among the set of experiments (Figure 3).
Figure 3. Example of NAD+ and NADH content and their ratio in Arabidopsis WT (Col-0) root samples.
Absolute quantification of NAD+ and NADH and their ratio using a microtiter plate reader coupled enzyme assay in different replicates (a, b, and c). Values are means ± SE (n = 3) of three separate experiments. Means denoted by the same letter were not significantly different at P < 0.05 according to Duncan’s multiple range test.
Recipes
MGRL solution
Sr. No. Chemical constituents SolutionStock Conc. SolutionFinal conc.
Required volume for the preparation of 1 L solution, pH 5.8
1 MgSO4·7H2O 0.15 M 0.03 mM 200 µL
2 Mn SO4·5H2O 1.03 mM 0.206 µM 200 µL
3 FeSO4·7H2O 0.86 mM 0.172 µM 200 µL
4 ZnSO4·7H2O 0.1 mM 0.02 µM 200 µL
5 CuSO4·5H2O 0.1 mM 0.02 µM 200 µL
6 KNO3 0.3 M 0.06 mM 200 µL
7 H3BO3 3.0 mM 0.6 µM 200 µL
8 (NH4)6Mo7O24·4H2O 2.4 µM 0.48 nM 200 µL
9 CoCl2·6H2O 13 µM 2.6 nM 200 µL
10 Na2EDTA 6.7 mM 1.34 µM 200 µL
11 NaNO3 0.4 M 80 µM 200 µL
12
Na-PO4 (pH 5.8)
NaH2PO4·2H2O
Na2HPO4·12H2O
0.175 M
0.175 M
0.035 mM
0.035 mM
200 µL
13 CaCl2·2H2O 1 M 200 µM 200 µL
Prepare adequate amounts of nutrient solution according to sample size and plant species; adjust pH to 5.8.
1 M Bicine/NaOH (pH 8.0) Buffer
Dissolve 16.317 g of Bicine (MW = 163.17 g/mol]) in 75 mL of distilled water
Adjust to pH 8.0 using 10 N NaOH
Fill to final volume of 100 mL with dH2O
Filter sterilize (recommended) or autoclave
Store at 4°C
1 M Tris-HCl
Dissolve 12.1 g Tris Base (TRIZMA) in 70 mL of distilled water and add concentrated HCl to pH 8.0
Fill up to volume 1 L with distilled water
Store at room temperature.
10 M Ethanol
For the preparation of this solution, take 58.4 mL of absolute Ethanol and make up to 100 mL with distilled water.
80 mM EDTA-2Na
The dissolve 29.77 g of Na2EDTA in 80 mL of distilled water and adjust the pH to 8.0 with NaOH
Adjust volume to 100 mL with distilled water, stir vigorously on a magnetic stirrer, and store at 4°C for longer storage.
Adjust the pH of the solution to 8.0 by the addition of NaOH to completely dissolve the Na2EDTA.
ADH solution
Add 8 mg of ADH to a 1.5 mL tube and dissolve in 1 mL of bicine/NaOH. After dissolving, keep on ice for immediate use.
Reaction Mixture preparation
Chemicals constituents Total 20 mL Final concentration
MTT mg 3.48 (dissolve in 6 mL of water) 0.42 mM
1-Methoxy PMS mg 3.72 (dissolve in 6 mL of water) 0.55 mM
1 M Bicine/NaOH mL 2 0.1 M
1 M Tris mL 0.4 20 mM
80 mM EDTA-2Na mL 1 4 mM
10 M EtOH mL 1 0.5 M
H2O (MilliQ) mL 3.6
NAD standard: NAD+ standard
Standard curve (pmol/mL) blank 50 100 150 200 250 300 350 400
1 µM NAD+ (µL) 0 5 10 15 20 25 30 35 40
H2O (MilliQ) (µL) 100 95 90 85 80 75 70 65 60
Take 40 µL of sample from each concentration.
NADH standard: NADH standard
Standard curve (pmol/mL) blank 10 20 40 60 80 100 120 140
100 nM NADH (µL) 0 10 20 40 60 80 100 12 (1 µM stock) 14
H2O (MilliQ) (µL) 100 90 80 60 40 20 0 88 86
Take 40 µL of sample from each concentration.
Acknowledgments
This protocol was adapted from Hampp et al. (1984) and Takita et al. (1999).
Competing interests
The authors declare no conflicts of interest or competing interests.
References
Apel, K. and Hirt, H. (2004). Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu Rev Plant Biol 55: 373-399.
Awasthi, J. P., Saha, B., Panigrahi, J., Yanase, E., Koyama, H. and Panda, S. K. (2019). Redox balance, metabolic fingerprint and physiological characterization in contrasting North East Indian rice for Aluminum stress tolerance. Sci Rep 9(1): 8681.
Dutilleul, C., Garmier, M., Noctor, G., Mathieu, C., Chetrit, P., Foyer, C. H. and de Paepe, R. (2003). Leaf mitochondria modulate whole cell redox homeostasis, set antioxidant capacity, and determine stress resistance through altered signaling and diurnal regulation. Plant Cell 15(5): 1212-1226.
Dutilleul, C., Lelarge, C., Prioul, J. L., De Paepe, R., Foyer, C. H. and Noctor, G. (2005). Mitochondria-driven changes in leaf NAD status exert a crucial influence on the control of nitrate assimilation and the integration of carbon and nitrogen metabolism. Plant Physiol 139(1): 64-78.
Foyer, C. H. and Noctor, G. (2005). Redox homeostasis and antioxidant signaling: a metabolic interface between stress perception and physiological responses. Plant Cell 17(7): 1866-1875.
Hampp, R., Goller, M. and Fullgraf, H. (1984). Determination of compartmented metabolite pools by a combination of rapid fractionation of oat mesophyll protoplasts and enzymic cycling. Plant Physiol 75(4): 1017-1021.
Mittler, R., Vanderauwera, S., Gollery, M. and Van Breusegem, F. (2004). Reactive oxygen gene network of plants. Trends Plant Sci 9(10): 490-498.
Moller, I. M. (2001). PLANT MITOCHONDRIA AND OXIDATIVE STRESS: Electron Transport, NADPH Turnover, and Metabolism of Reactive Oxygen Species. Annu Rev Plant Physiol Plant Mol Biol 52: 561-591.
Takita, E., Koyama, H. and Hara, T. (1999). Organic Acid Metabolism in Aluminum-Phosphate Utilizing Cells of Carrot (Daucus carota L.). Plant and Cell Physiology 40(5): 489-495.
Article Information
Copyright
© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Plant Science > Plant biochemistry > Metabolite
Plant Science > Plant physiology > Abiotic stress
Biochemistry > Other compound > NAD+/NADH
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4,445 | https://bio-protocol.org/en/bpdetail?id=4445&type=1 | # Bio-Protocol Content
Improve Research Reproducibility
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Identification of Expression QTL by QTLtools in a Rice Recombinant Inbred Line Population
FX Feng Xiong
HZ Hu Zhao
WX Weibo Xie
Published: Jun 20, 2022
DOI: 10.21769/BioProtoc.4445 Views: 693
Reviewed by: Chao JiangHassan RasouliJinfeng Chen
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Abstract
Expression QTL (eQTL) analysis assesses the association between the expression levels of target genes and genotypes of genetic markers to identify loci that regulate the expression of target genes. eQTL results can be used to construct genetic regulatory networks as well as increase our understanding of the regulatory mechanisms of phenotypic variation. In this protocol, we demonstrate how to use the R packages QTLtools and qqman to identify eQTLs and visualize the results using expression profiles of flag leaves from 210 rice recombinant inbred lines at the heading stage.
Keywords: eQTL Expression variation Rice RIL population QTL mapping Flag leaf
Background
A comprehensive eQTL study requires first obtaining genetic markers and expression profiles for each individual in the population, then taking the expression of each target gene as a trait (termed an expression trait, eTrait) and determining whether some markers are statistically associated with the eTrait by association analysis, and finally identifying candidate genes or regulatory sequences around the associated markers through various additional evidence. Usually, eQTL can be classified into two types: cis and trans. A cis-acting eQTL is an eQTL for a gene that is localized around that gene, indicating that sequence differences around that gene result in changes in expression levels. A trans-acting eQTL is an eQTL that is positioned distantly from the target gene it regulates, indicating that the expression level of the target gene is genetically regulated by distal factors (e.g., upstream transcription factors).
Many methods have been developed for eQTLs analysis, such as Matrix eQTL (Shabalin, 2012), FastQTL (Ongen et al., 2016), and QTLtools (Delaneau et al., 2017). To date, Matrix eQTL has been used in several large-scale studies (GTEx Consortium, 2015; Lappalainen et al., 2013), and it supports additive linear and ANOVA models with covariates, including models with correlated and heteroskedastic errors, and addresses the issue of multiple testing by calculating false discovery rates. However, the method lacks an efficient built-in permutation scheme. Another tool, fastQTL, is a user-friendly QTL mapper that implements a fast and efficient permutation scheme, capable of calculating and adjusting P-values for all significant levels with a short time (Ongen et al., 2016). The recently developed QTLtools is a modular framework that are implemented based on C++ and thus faster than the previous two tools (Delaneau et al., 2017). It also provides extensive functions, including checking the quality of the sequence data, quantifying gene expression, stratifying individuals, and integrating QTLs with GWAS results and other functional data.
In the following protocol, we explain how to use QTLtools to identify cis- and trans- eQTL and use qqman to visualize the results. The relevant code and instructions are available on GitHub (https://github.com/Bio-protocol/eQTL_Analysis_for_Rice_RIL_population).
Equipment
Personal computer, preferably with multiple processors (CPUs) to speed up computations. A Unix/Linux operating system is preferred.
Software
QTLtools (Delaneau et al., 2017) https://qtltools.github.io/qtltools/binaries/QTLtools_1.2_CentOS7.8_x86_64.tar.gz
G++ 4.8.5 (https://gcc.gnu.org/gcc-4.8/changes.html)
Glibc 2.17 (https://sourceware.org/glibc/wiki/Release/2.17)
R 3.6.1(http://www.R-project.org/)
Htslib (Bonfield et al., 2021) https://github.com/samtools/htslib/releases/download/1.12/htslib-1.12.tar.bz2
Samtools (Danecek et al., 2021) https://github.com/samtools/samtools/releases/download/1.12/samtools-1.12.tar.bz2
Bcftools (Danecek et al., 2021) https://github.com/samtools/bcftools/releases/download/1.12/bcftools-1.12.tar.bz2
Note: Before installing QTLtools, you will need to install some dependencies such as G++ 4.8.5, Glibc 2.17, HTSlib 1.9, and R 3.6.1. Details on how to install these dependencies are available in the respective software links. Installation details for Htslib, Samtools, and Bcftools can be found athttps://github.com/samtools. We recommend using Anaconda (https://www.anaconda.com/) to install the software, and the installation command is shown in the command box below.
## Installing Anaconda
wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-4.1.0-Linux-x86.sh
bash Anaconda3-4.1.0-Linux-x86.sh
echo 'export PATH="~/anaconda2/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc
## Installing Htslib
conda install -c bioconda htslib
## Installing Bcftools
conda install -c bioconda bcftools
## Installing Samtools
conda install -c bioconda samtools
## Installing R 3.6.1
conda install r-base=3.6.1
## Installing QTLtools(download and unzip to use)
wgethttps://qtltools.github.io/qtltools/binaries/QTLtools_1.2_CentOS7.8_x86_64.tar.gz
tar xzvf QTLtools_1.2_CentOS7.8_x86_64.tar.gz
cd QTLtools_1.2_CentOS7.8_x86_64
ln -s QTLtools_1.2_CentOS7.8_x86_64 QTLtools
echo 'export PATH="~/QTLtools_1.2_CentOS7.8_x86_64:$PATH"' >> ~/.bashrc
source ~/.bashrc
Data source
A population with 210 rice recombinant inbred lines (RILs) derived from a cross between two indica rice lines (Zhenshan 97 and Minghui 63) was used in this protocol (Xing et al., 2002). Expression profiles of flag leaves at the heading stage (the day of the panicle emergence) were obtained for each RIL using the Affymetrix GeneChip Rice Genome Array. The raw data are available from the National Center for Biotechnology Information Gene Expression Omnibus database under the accession number GSE49020 (Wang et al., 2014). On the microarray, the expression of a gene is measured by a group of probe pairs called a probe set. Probe sets flagged as “Present” or “Marginal” by the MAS 5.0 algorithm for at least one-third of the RILs were used as eTarits for eQTL analysis (Wang et al., 2014). A bin map with 1619 bins and 210 RILs was used as genotype data in this analysis, which was constructed from an ultrahigh-density SNP map, with complete linkage SNPs defined as a bin (Yu et al., 2011).
Preparing input files
Genotype data (VCF/BCF format, see Supplementary file)
Either the VCF or BCF format is accepted. The following example shows the format of a VCF file. Details of the VCF file can be obtained from http://vcftools.sourceforge.net/specs.html.
Figure 1. A screenshot of the genotype data file (VCF format).
Note: The VCF/BCF file can be viewed by Bcftools.
Bcftools view myGenotypes.vcf.gz | less -SBcftools view myGenotypes.vcf.gz | less -S
eTrait/phenotype data (BED format, see Supplementary file)
eTrait/phenotype data is specified using an extended UCSC BED format. One eTrait per line. The first six columns are,
Chromosome ID [string; required]
Start genomic position of each eTrait gene (e.g., the transcription start site of gene1) [integer; required]
End genomic position of each eTrait gene (e.g., the transcription termination site of gene1) [integer; required]
eTrait/phenotype ID [string; required]
Gene ID [string; optional]
Strand orientation. Missing values should be encoded as NA [+/-; optional]
The latter columns are the eTrait data of each sample.
The following is an example of a BED file.
Figure 2. A screenshot of the eTrait data file (BED format).
Procedure
Data preparation
We constructed the genotype data file (named “eQTL_genotype.vcf” in VCF/BCF format) and the eTrait/phenotype data file (“flag_leaf_eTrait.bed” in BED format) according to the example files given in the section “Preparing input files” (Figure 1, Figure 2). Besides the genotype and eTrait files, we need information on gene annotations and association of genes and probe sets, which can be extracted from CREP database (Wang et al., 2010) or array annotation files from Affymetrix.
Note: Considering the huge number of bins and eTraits, the generated VCF files and BED files also take up a large amount of space, and we compressed and indexed both using “bgzip” and “tabix” tools (“eQTL_genotype.vcf.gz” and “flag_leaf_eTrait.bed.gz”).
bgzip eQTL_genotype.vcf && tabix -p vcf eQTL_genotype.vcf.gz
bgzip flag_leaf_eTrait.bed && tabix -p flag_leaf_eTrait.bed.gz
cis-eQTL identification with QTLtools
QTLtools cis --vcf eQTL_genotype.vcf.gz --bed flag_leaf_eTrait.bed.gz --permute 1000 --out flag_leaf_eTrait_cis_permutation.txt
The meaning of each parameter in the above command is as follows,
--vcf The input genotype file [required]
--bed The input eTrait/phenotype file [required]
--permute Number of permutations per eTrait/phenotype [required]
--out The name of the output file [required]
--normal Enforce the input eTraits/phenotypes to normal distributions N(0, 1) [optional]
Note: We can also use --normal to enforce the eTraits/phenotypes to be normally distributed (this parameter can also be used in trans eQTL identification). For example, “QTLtools cis --vcf eQTL_genotype.vcf.gz --bed flag_leaf_eTrait.bed.gz --permute 1000 --out flag_leaf_eTrait_cis_permutation.txt --normal”.
The output file “flage_leaf_cis_permutation.txt” is shown in Figure 3. The columns of this file include,
eTrait ID
Chromosome ID of the eTrait gene
Start position of the eTrait gene
End position of the eTrait gene
Strand orientation of the eTrait gene
Total number of bins tested in cis
Distance between the eTrait gene and the tested bin
The top bin ID sorted by P-values
The top bin chromosome
The top bin start position
The top bin end position
The number of degrees of freedom used to compute the P-values
Dummy
The first parameter value of the fitted beta distribution
The second parameter value of the fitted beta distribution
The nominal P-value of association between the eTrait gene and the top bin in cis
Figure 3. A screenshot of flag_leaf_eTrait_cis_permutation.txt. Note that the first line in the figure is used to indicate the column number and is not in the actual file.
trans-eQTL identification with QTLtools
## We can run the following commands on a Linux device with QTLtools installed
##command 1
QTLtools trans --vcf eQTL_genotype.vcf.gz --bed flag_leaf_eTrait.bed.gz --nominal --threshold 0.05 --out flag_leaf005.trans.nominal.hits.txt.gz
##command 2
for i in {1..100};do
QTLtools trans --vcf eQTL_genotype.vcf.gz --bed flag_leaf_eTrait.bed.gz --threshold 0.05 --permute --out flag_leaf005_trans_perm_${i} --seed ${i}
done
##command 3
zcat flag_leaf005_trans_perm_*.hits.txt.gz | gzip -c > flag_leaf005_permutations_all.txt.gz
Rscript runFDR_ftrans.R flag_leaf005.trans.nominal.hits.txt.gz flag_leaf005_permutations_all.txt.gz flag_leaf_trans_005_permutations_all.txt
The meaning of each parameter in the above commands is as follows,
--vcf The input genotype file [required]
--bed The input eTrait data file [required]
--nominal This enforces the eTraits to be normally distributed [required]
--threshold This defines the threshold to bin (in *.bins.txt.gz files) or report nominal P-values (in *.hits.txt.gz) [optional; default is 1e-5]
--out The name of the output file [required]
--seed Set random number seed [optional]
The command 1 will generate three output files, one named “*.best.txt.gz” containing the top eQTL for each eTrait, one named “*.bins.txt.gz” containing all eQTLs with P-values below the specified threshold, and the last named “*.hits.txt.gz”, containing the details of all eQTLs with P-values above the specified threshold. The command 2 permutes all eTraits and generate three files like the command 1. The command 3 will generate the file “flag_leaf_trans_005_permutations_all.txt” which contains the data in “*.hits.txt.gz” and with an additional column that gives the estimated false discovery rate (FDR) for each eTrait by 100 permutations.
Note: The above three commands can be run on the server by copying the commands into a shell script or typing them manually directly from the command line interface. The R script (“runFDR_ftrans.R”) required to run is already included in QTLtools.
The main output files are shown in Figure 4 and Figure 5; the first 9 columns of these files are,
eTrait ID
Chromosome ID of the eTrait gene
Sart position of the eTrait gene
Bin ID
Bin chrID
Bin position
Nominal P-value
Dummy here. Field used in approximated mapping in trans
Regression slope
In Figure 5, the 10th column is the FDR values.
Figure 4. A screenshot of flag_leaf_eTrait_005.trans.nominal.hits.txt. Note that the first line in the figure is used to indicate the column number and is not in the actual file.
Figure 5. A screenshot of flag_leaf_trans_005_permutations_all.txt. Note that the first line in the figure is used to indicate the column number and is not in the actual file.
Draw Manhattan diagram with R script
Manhattan plot is a common display method to visualize the eQTL mapping results. We used the key gene for rice flowering time regulation, Ehd1 (Nemoto et al., 2016), as an example to demonstrate the Manhattan plot. We first identified the probe set OsAffx.30643.1.S1_at corresponding to Ehd1 and extracted its corresponding eQTL results from the “flag_leaf_eTrait_005_trans.nominal.hit.txt.gz” file, which was generated in the "C. trans-eQTL identification with QTLtools" step. We then transformed the results to the format required by the qqman package (Turner, 2018) (extracting columns 4–7), named it “Ehd1_eQTL_result.txt” (Figure 6), and generated the Manhattan plot using the “manhattan” function of qqman (Figure 7). The Manhattan plot shows that Ehd1 has a significant signal surrounding Bin893 on chromosome 6. This region harbors Hd1 which has been reported to function as an Ehd1 repressor (Nemoto et al., 2016).
Note: The Bash command (command 1) in the command box below was used to extract the eQTL results for Ehd1. The Manhattan plot (Figure 7) could be generated by opening the R software and entering the R code (command 2). A threshold value is usually used in eQTL analysis to determine the statistical significance of the analysis and to control for false positives. The most accepted method to determine the threshold is to use Bonferroni correction based on the number of independent markers across the genome. Guo et al. (2017) suggested using a P-value of 1 / number of markers as a suggestive threshold for genome-wide association analysis. In addition, permutation tests that have a non-parametric nature are also frequently used to assess thresholds (Dudbridge, 2008). Permutation tests involve randomly permuting the expression values of individuals many times to obtain a null distribution of the P-values, from which a threshold is then estimated. In our example, 100 permutations were done then a threshold corresponding to FDR=0.05 was obtained, i.e., five permutations yielded a minimum p-value less than this threshold. Smaller permutation-based FDR could be estimated from a larger number of permutations.
#Command 1 in Bash
zcat flag_leaf005.trans.nominal.hits.txt.gz | grep OsAffx.30643.1.S1_at > Ehd1_eQTL_result.txt
#Command 2 in R
#Note: To improve the layout of the graph, we have modified the Manhattan function of qqman package, which can be found on GitHub (https://github.com/Bio-protocol/eQTL_Analysis_for_Rice_RIL_population/blob/master/lib/Manhattan_function.R).
source('Manhattan_function.R')
data <- read.table(" Ehd1_eQTL_result.txt ")
data <-data[,c(4,5,6,7)]
colnames(data)<-c('SNP','CHR','BP','P')
manhattan(data,main = "Manhattan Plot",suggestiveline =-log10(6.17e-04),genomewideline = -log10(6.12e-04),cex.lab=1.2, cex.axis=1.5,cex.main=1.5,annotatePval = 5e-40,annotateTop = FALSE,xlim=c(32284500,155000000),ylim=c(0,50),cex = 1.5)
Figure 6. A screenshot of Ehd1_eQTL_result.txt.
The meanings of the columns are the same as in Figure 4. Note that the first line in the figure is used to indicate the column number and is not in the actual file.
Figure 7. Manhattan plot of OsAffx.30643.1.S1_at.
The blue line represents the suggested threshold value (P = 6.17e-04), calculated using -log10(1 / number of markers) (Guo et al., 2017). The red dash line represents the P-value (P = 6.12e-04) corresponding to FDR = 0.05 obtained in 100 permutations. The two lines overlap in the figure because they are too close.
Notes
Due to the limitation of recombination and population size, eQTL intervals often contain tens or hundreds of candidate genes. Therefore, it is difficult to obtain regulatory relationships directly from these results. In order to obtain which gene in the eQTL interval actually plays a regulatory role, we need to integrate more information. For example, we can combine the functional annotation of genes in the eQTL interval to determine which genes may be associated with the trait of interest, either with information on whether the gene is expressed in the target tissue or with information on co-expression of the genes, and then follow up with experimental validation. We note that some tools for this purpose have been reported in plants, such as POCKET software (https://github.com/zhaouu/POCKET) that integrates gene function information, gene expression information, and variant annotation information to finally score and rank the genes in the eQTL region in an integrated manner, which can help to further experimental validation of regulatory relationships (Tang et al., 2021). Combining these methods may make the eQTL results more interpretable.
Acknowledgments
This work was supported by grants from the National Key Research and Development Program of China (2016YFD0100803) and the National Natural Science Foundation of China (31771755).
Competing interests
The authors declare that there are no conflicts of interest or competing interests.
References
Bonfield, J. K., Marshall, J., Danecek, P., Li, H., Ohan, V., Whitwham, A., Keane, T. and Davies, R. M. (2021). HTSlib: C library for reading/writing high-throughput sequencing data. GigaScience 10(2).
Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., et al. (2021). Twelve years of SAMtools and BCFtools. GigaScience 10(2).
Delaneau, O., Ongen, H., Brown, A. A., Fort, A., Panousis, N. I. and Dermitzakis, E. T. (2017). A complete tool set for molecular QTL discovery and analysis. Nat Commun 8: 15452.
GTEx Consortium. (2015). Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348(6235): 648-660.
Lappalainen, T., Sammeth, M., Friedländer, M. R., t Hoen, P. A., Monlong, J., Rivas, M. A., Gonzàlez-Porta, M., Kurbatova, N., Griebel, T., Ferreira, P. G., et al. (2013). Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501(7468): 506-511.
Nemoto, Y., Nonoue, Y., Yano, M. and Izawa, T. (2016). Hd1,a CONSTANS ortholog in rice, functions as an Ehd1 repressor through interaction with monocot-specific CCT-domain protein Ghd7. Plant J 86(3): 221-233.
Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T. and Delaneau, O. (2016). Fast and efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics 32(10): 1479-1485.
Shabalin, A. A. (2012). Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28(10): 1353-1358.
Tang, S., Zhao, H., Lu, S., Yu, L., Zhang, G., Zhang, Y., Yang, Q. Y., Zhou, Y., Wang, X., Ma, W., et al. (2021). Genome- and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus. Mol Plant 14(3): 470-487.
Turner, S. D. (2018). qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. J Open Source Softw 3: 731.
Wang, J., Yu, H., Weng, X., Xie, W., Xu, C., Li, X., Xiao, J. and Zhang, Q. (2014). An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice recombinant inbred line population. J Exp Bot 65(4): 1069-1079.
Wang, L., Xie, W., Chen, Y., Tang, W., Yang, J., Ye, R., Liu, L., Lin, Y., Xu, C., Xiao, J. et al. (2010). A dynamic gene expression atlas covering the entire life cycle of rice. Plant J 61(5): 752-766.
Xing, Y., Tan, Y., Hua, J., Sun, X., Xu, C. and Zhang, Q. (2002). Characterization of the main eVects, epistatic eVects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor Appl Genet 105: 248-257.
Yu, H., Xie, W., Wang, J., Xing, Y., Xu, C., Li, X., Xiao, J. and Zhang, Q. (2011). Gains in QTL detection using an ultra-high density SNP map based on population sequencing relative to traditional RFLP/SSR markers.PLoS One 6(3): e17595.
Guo, Y., Huang, Y., Hou, L., Ma, J., Chen, C., Ai, H., Huang, L. and Ren, J. (2017). Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches. Genet Sel Evol 49(1): 21.
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Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/eQTL_Analysis_for_Rice_RIL_population.git.
Article Information
Copyright
© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Plant Science > Plant molecular biology > Genetic analysis
Systems Biology > Transcriptomics > Microarray
Systems Biology > Genomics > Functional genomics
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4,446 | https://bio-protocol.org/en/bpdetail?id=4446&type=1 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
GO/KEGG Enrichment Analysis on Gene Lists from Rice (Oryza Sativa)
YL Yahui Li
Published: Jun 20, 2022
DOI: 10.21769/BioProtoc.4446 Views: 2307
Reviewed by: Yizhou WangJinfeng Chen Anonymous reviewer(s)
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Abstract
In RNA-seq data analysis, functional enrichment analysis on genes has become a routine. Many enrichment analysis software and web-applications have emerged. However, gene annotation information is only easily accessible for the most well-studied organisms, such as human and mouse, but is lacking for some plant species. With poor gene annotation information, performing a functional enrichment analysis is challenging. As such, I use rice, a mode plant organism, as an example to show how to obtain comprehensive Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation for the enrichment analysis. I obtain the gene annotation information from two sources, 1. rice public annotation databases, including RAP-DB and OryzaBase; and 2. a R package containing gene annotation information of various species,i.e., AnnotationHub. I utilize clusterProfiler R package for the enrichment calculation and result visualization. This protocol can be directly used for GO/KEGG enrichment analysis on gene lists from rice, and can also be used as a reference for similar analysis on other plant species.
Keywords: KEGG Functional enrichment analysis clusterProfiler Rice RNA-seq
Background
RNA-seq data analysis has been streamlined, and functional enrichment analysis is a critical step to provide biological insights into the results. Enrichment analysis, or over-representative analysis, is to examine whether a gene ontology or a biological pathway is enriched in the target gene list more than is expected by chance. Many tools were developed to contain both annotation files and enrichment test functions to streamline this process. However, some plant species may still lack of gene annotation information, which could be an obstacle for the functional enrichment analysis. For instance, only 20 GO annotation databases were available under OrgDb from Bioconductor, where only one is the plant species Arabidopsis. In this protocol, I focus on performing functional enrichment analysis on genes of rice, a model organism for the grass family, using one of the most commonly used enrichment analysis R software clusterProfiler (Yuet al., 2012). I provide a step-by-step instruction using annotation information obtained from two different ways. The scripts are mainly the R scripts, with some Bash command lines for curating a GO annotation file.
Software
clusterProfiler (Yu et al. , 2012; v3.16.1; https://guangchuangyu.github.io/software/clusterProfiler/documentation/)
GO.db (Carlson et al. , 2019; v3.11.4; https://bioconductor.org/packages/release/data/annotation/html/GO.db.html)
AnnotationHub (Morgan et al. , 2021, v 2.20.1, https://bioconductor.org/packages/release/bioc/vignettes/AnnotationHub/inst/doc/AnnotationHub.html)
dplyr (R package, v1.0.7)
data.table (R package, v1.14.0)
ggplot2 (R package, v3.3.5)
Input data:
Target gene list (genes.txt), background gene list (bkgd.txt, optional but recommended). The gene IDs are the RAP IDs in this protocol, e.g ., Os01g0102500, Os01g0106300.
The gene annotation file obtained from The Rice Annotation Project (RAP) Database (RAP-DB), including the GO annotation information and RAP gene ID to transcript ID conversion information. This file is a large data table, where each row is an individual transcript ID, and each column is a gene annotation information, and "GO" is the column that contains the GO annotations, which are extracted into self-curated annotation files.
https://rapdb.dna.affrc.go.jp/download/archive/irgsp1/IRGSP-1.0_representative_annotation_2021-11-11.tsv.gz
The gene annotation file from the OryzaBase website. This file is also a large data table, where each row is for a "Trait Gene ID", with annotations of "RAP ID" and "Gene Ontology", which are used for generating self-curated annotation files. https://shigen.nig.ac.jp/rice/oryzabase/download/gene
RAP ID to Entrez ID conversion table from the He Lab at Fujian Agriculture and Forestry University, China. http://bioinformatics.fafu.edu.cn/riceidtable/
Procedure
Case study:
GO enrichment analysis using self-curated annotation files.
Prepare rice gene GO annotation files curated from public annotation databases.
Extract the rice gene GO annotations from two public rice gene annotation databases, RAP-DB and OryzaBase, and then combine them together as one single GO annotation file.
The RAP-DB GO annotation is collected by the following steps. First, download the genome annotation file from the RAP-DB website, and then unzip the file. Next, extract the GO annotation information and make it a two-column tabular file (GO ID, Gene ID). The OryzaBase GO annotation is gathered in the same way. The two files are then combined together into one file with duplicated rows removed. The format of the output annotation file is shown in Table 1 .
Table 1.Gene annotations table containing the GO ID to gene ID mapping information.
GO ID Gene ID
GO:0000003 Os02g0242600
GO:0000003 Os02g0268100
GO:0000003 Os02g0281000
GO:0000023 Os02g0729400
GO:0000023 Os04g0459900
Prepare the GO ID to GO name mapping files (in total of three, one for each GO subcategory). Also, split the curated GO annotation file into three files based on GO subcategories.
First, obtain the GO ID to GO name mapping information from “GO.db” R package. This file provides the TERM2NAME information in the universal enrichment function from clusterProfiler software. The format of the file is shown in Table 2.
Next, split the GO annotation file (Step 1a) into three subcategories, i.e ., Biological Process (BP), Molecular Function (MF), Cellular Component (CC). These tables provide the TERM2GENE information in the universal enrichment function from clusterProfiler. The format of these tables is the same as the original GO annotation table (Table 1).
Table 2. GO ID to GO name mapping table.
GO ID GO name
GO:0000001 mitochondrion inheritance
GO:0000002 mitochondrial genome maintenance
GO:0000003 reproduction
GO:0000011 vacuole inheritance
GO:0000012 single strand break repair
Read the input gene lists and the self-provided GO annotation files. Here, the GO: BP annotation file is used to perform GO enrichment analysis, specially for the BP category.
Run universal enrichment function from clusterProfiler package, enricher . Save and visualize the results.
GO enrichment analysis using annotations from AnnotationHub package.
Read in the required input data, including input gene lists and OrgDb object.
First, find rice OrgDb object from AnnotationHub. There are three databases available for Oryza Sativa japonica subspecies, where I pick the first one as all three are very similar. As the key types in the OrgDb do not include the “RAP” ID type, the gene IDs are further converted into the “Entrez” ID type using a rice ID mapping table obtained from the He Lab at Fujian Agriculture and Forestry University, China. (Input data 4).
Run enrichment function, enrichGO .
Select the BP ontology in the input parameter. Here, no enriched GO terms are found in the result.
KEGG enrichment analysis
The clusterProfiler package can automatically retrieve KEGG annotation data from the KEGG database when running the KEGG enrichment analysis function, enrichKEGG . The KEGG database contains large number of organisms, including 687 Eukaryotes, 6664 Bacteria, and 369 Archaea, where rice is covered. The following steps show how to run KEGG enrichment analysis with clusterProfiler using annotations from the KEGG database.
Find the KEGG organism information from KEGG database. https://www.genome.jp/kegg/catalog/org_list.html . There are “dosa” and “osa” for rice genome. I select “dosa” (KEGG Genes Database: T02163, Oryza sativa japonica (Japanese rice) (RAPDB)). Next, check the ID type used in “dosa”. Here, the ID type is the RAP transcript ID. Accordingly, input genes’ IDs are converted to the RAP transcript IDs using the RAP ID mapping table (Input data 2).
Run the enrichment test function enrichKEGG , and then save and visualize the results.
Results interpretation:
With the input gene list, twenty-nine GO terms are enriched from the GO enrichment analysis using the self-provided annotation files. The result table of the top 10 most statistically significant enriched GO terms (BP) ranked by p-values is shown in Figure 1 ; the top results are visualized by the dot plot, where the terms were re-ordered by GeneRatios (Figure 2). To note, not all genes have GO annotations, which leads to less genes used in the test, i.e. , the input gene number changes from 3368 to 1699, and the background gene number changes from 24891 to 13440, respectively.
Figure 1. Screenshot of the result table showing the top 10 most statistically significant enriched GO terms (BP).
The terms are ordered by p-values. GeneRatio: the ratio of input genes with the target annotation to all input genes; BgRatio: the ratio of background genes with the target annotation to all background genes; p.adjust: multiple testing corrected p-value using method specified by the “pAdjustMethod” argument. The default is the “BH” method; qvalue: the local FDR corrected p-value.
Figure 2. Visualizing the top 10 most statistically significant enriched GO terms (BP) by dot plot.
The terms are ordered by GeneRatio (the ratio of the input genes with the target GO annotation to the total number of input genes).
In the KEGG enrichment analysis result, eleven KEGG terms are enriched, and the top 10 most statically significant enriched KEGG pathways are listed in the table, ranked by p-values (Figure 3). These enriched KEGG pathways are visualized by the dot plot, where the terms are re-ordered by GeneRatios (Figure 4).
Figure 3. Screenshot of the result table showing the top 10 most statistically significant enriched KEGG pathway terms.
The terms are ordered by p-values. GeneRatio: the ratio of input genes with the target annotation to all input genes; BgRatio: the ratio of background genes with the target annotation to all background genes; p.adjust: multiple testing corrected p-value using method specified by the “pAdjustMethod” argument. The default is the “BH” method; qvalue: the local FDR corrected p-value.
Figure 4. Visualizing the top 10 most statistically significant enriched KEGG pathway terms by dot plot.
The terms are ordered by GeneRatio (the ratio of the input genes with the target KEGG annotation to the total number of input genes).
Discussion:
Here, I provide a detailed protocol to perform GO and KEGG enrichment analysis for genes of the rice species. I find that using self-collected GO annotation files outperforms the annotation file from the AnnotationHub, which should be used as the preferred approach here. The self-provided GO annotated files are collected from two rice annotation databases, the RAP-DB and OryzaBase. If there are more well-maintained sources of annotations, they should be added as well to gain a more comprehensive result.
Rice is relatively well-annotated among all plant species, making curating annotation file from public sources possible. However, when there is no available annotation files for the species of target, then researchers can acquire the predicted gene annotations based on protein sequence alignment to that of the annotated species using software such eggNOG-mapper, Interproscan. Lastly, it is worth noting that several web applications have been developed for functional enrichment analysis, with built-in annotation files for some plant species, such as agriGO and g:Profiler. Research can refer to those tools to check if the plant species under study is covered.
Acknowledgments
The author thanks He Lab at Fujian Agriculture and Forestry University, China, for its RAP ID to Entrez ID conversion table which was applied in this protocol.
Competing interests
The author declares no conflict of interest.
References
Yu, G., Wang, L. G., Han, Y. and He, Q. Y. (2012). clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16(5): 284-287.
Carlson. M. (2019). GO.db: A set of annotation maps describing the entire Gene Ontology. R package version 3.8.2.
Morgan. M. and Shepherd, L. (2022). AnnotationHub: Client to access AnnotationHub resources. R package version 3.4.0.
Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/GO_KEGG_enrichment_analysis_for_rice_genes.git
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Plant Science
Systems Biology > Transcriptomics > RNA-seq
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Hello, great work. Can you please clarify if i can proceed with MSU ids as i don't have RAP-DB ids and also don't have access to get RAP-DB ids.
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4,447 | https://bio-protocol.org/en/bpdetail?id=4447&type=0 | # Bio-Protocol Content
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Fluorescent Labeling of Small Extracellular Vesicles (EVs) Isolated from Conditioned Media
JS John Santelices
MO Mark Ou
WH Winnie W. Hui
GM Gustavo H. B. Maegawa
ME Mariola J. Edelmann
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4447 Views: 3864
Reviewed by: Alba BlesaSeda Ekici Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in PLOS Pathogens May 2021
Abstract
Extracellular vesicles (EVs), such as exosomes, are produced by all known eukaryotic cells, and constitute essential means of intercellular communication. Recent studies have unraveled the important roles of EVs in migrating to specific sites and cells. Functional studies of EVs using in vivo and in vitro systems require tracking these organelles using fluorescent dyes or, alternatively, transfected and fluorescent-tagged proteins, located either intravesicularly or anchored to the EV bilayer membrane. Due to design simplicity, the fluorescent dye might be a preferred method if the cells are difficult to modify by transfection or when the genetic alteration of the mother cells is not desired. This protocol describes techniques to label cultured cell-derived EVs, using lipophilic DiR [DiIC18(7) (1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindotricarbocyanine Iodide)] fluorophore. This technique can be used to study the cellular uptake and intracellular localization of EVs, and their biodistribution in vivo, which are crucial evaluations of any isolated EVs.
Keywords: Extracellular vesicles Exosomes Labeling Lipophilic dye DiR
Background
There are several subtypes of extracellular vesicles (EVs), and among them, exosomes are one of the smallest ones, with a size range between 30 nm and 120 nm (reviewed in Théry et al., 2002). Exosomes contain signature molecules, such as tetraspanins (CD9, CD63, and CD81), and are characterized by specific biogenesis originating in the endosomal pathway (reviewed in Huotari and Helenius, 2011). The EVs can carry and transfer various cargo to other cells, including proteins, metabolites, miRNA, and lipids. One of the exciting research areas is the affinity of exosomes to specific tissues and regions, depending on the characteristics of these EVs. Hence, the biodistribution of EVs should be studied, and EV imaging is required to accomplish this goal. Several methods can be used to track EVs in animal cells and tissues. For instance, bioluminescence imaging (BLI) (Gangadaran et al., 2017) is one of the methods with the highest signal-to-noise ratio, but it suffers from low temporal resolution. Magnetic resonance imaging (MRI) (Busato et al., 2016, 2017) can also be used, but this method is associated with low sensitivity and high operation cost. Finally, fluorescence-based imaging of EVs provides a sensitive method with the highest spatial resolution (Corso et al., 2019). Among the fluorescence-based techniques, GFP protein can be expressed with the lowest penetration, which does not allow for noninvasive in vivo imaging, but has high resolution. Near-infrared (NIR) fluorescence imaging using lipophilic dyes, such as DiR [DiIC18(7) (1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindotricarbocyanine Iodide)], can also be used. The two long 18-carbon chains insert into the vesicle membrane avidly, resulting in a negligible dye transfer between EVs. The near IR fluorescent lipophilic carbocyanine DiOC18(7) ('DiR') is weakly fluorescent in water but highly fluorescent and quite photostable when incorporated into membranes. The sulfonate residues incorporated into this DiI analog improve water solubility. Moreover, DiI has an extremely high extinction coefficient and short excited-state lifetimes (~1 nanosecond) in the lipid-rich environment. The DiR shows excitation/emission at 710/760 nm, which, along with its NIR properties, makes this an ideal fluorophore for in vivo EV imaging studies, given the significantly reduced auto-fluorescence from the animal at higher wavelengths (Cook et al., 2015; Somanchi, 2016; Zhao et al., 2021). While there is no perfect method, DiR–based labeling can provide a flexible and low-cost alternative to other methods used for systematic studies of exosomes. This paper describes a technique that uses a lipophilic DiR dye to stain EVs obtained from cell culture, such as cultured macrophages. This approach can be used to track the vesicles for in vitro uptake and in vivo biodistribution studies in animal models.
Materials and Reagents
Polypropylene open-top ultracentrifuge tubes (Beckman Coulter, catalog number: 326823)
Nalgene Rapid-Flow Sterile Single Use Vacuum 0.2 µm Filter 500 mL Unit (Thermo Fisher, catalog number: 566-0020)
Amicon Ultra Centrifugal Filter Ultracell 10,000 MWCO (Millipore Sigma, catalog number: UFC801024)
Syringe Filters, Polyethersulfone (PES) membrane, 0.22 µm (GenClone, catalog number: 25-244)
Greiner Bio-One CellStar μClear 96-Well, Cell Culture-Treated, Flat-Bottom Microplate (Greiner Bio-One, catalog number: 655090)
DiR'; DiIC18(7) (1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindotricarbocyanine Iodide) (Thermo Fisher Scientific, catalog number: D12731)
Pierce Protease Inhibitor Tablets (Thermo Fisher Scientific, catalog number: A32963)
1× Dulbecco’s Phosphate Buffered Saline (DPBS) with Calcium and Magnesium (Thermo Fisher Scientific, catalog number: 14040117)
OptiMEM I Reduced Serum Medium, no phenol red (Thermo Fisher, catalog number: 11058021)
Phosphate Buffered Saline (PBS, 1×), sterile filtered (Thermo Fisher, catalog number: J61196.AP)
DAPI solution (1 mg/mL, Thermo Fisher, catalog number: 62248)
Pierce Protease Inhibitor Tablets, EDTA-Free (Thermo Fisher, catalog number: A32955) (See Recipes)
MicroBCA Protein Assay Kit (Thermo Fisher, catalog number: 23235)
Media containing exosome-depleted fetal bovine serum (FBS) and penicillin/streptomycin (see Recipes)
Control Sample for NanoSight quantification (see Recipes)
Protease inhibitor cocktail (PI) from Pierce Protease Inhibitor Tablets, EDTA-Free (see Recipes)
Equipment
Optima XPN-90 IVD ultracentrifuge (Beckman, catalog number: B10052) with SW 32 Ti swinging-bucket rotor (Beckman, catalog number: 369650)
Sorvall Legend Micro 21R Microcentrifuge (Thermo Scientific, catalog number: 75002447)
Cytation 5 multi-mode reader (Agilent, catalog number: BTCYT5V)
NanoSight LM10 (Malvern Panalytical, catalog number: EOS3085)
Software
GraphPad Prism 9 (GraphPad Software)
Gen5 Software (Agilent)
Procedure
The overall scheme for the EV purification and labeling with DiR dye is presented in Figure 1.
Figure 1. Experimental setup for the EV purification and labeling with DiR. A. The EV purification and labeling scheme. B. The EV is labeled with a DiR or a similar fluorogenic dye.
Collection of the cell culture conditioned media
Set the ultracentrifuge and benchtop refrigerated centrifuge to 4°C, approximately 30 min before collecting the supernatant. Prepare a bucket with ice before collecting the cell culture media (conditioned cell culture media; see Recipes for an example of media).
Notes:
Use sterile reagents and proper aseptic technique at all steps to avoid contamination.
Before loading the tubes, it is recommended to refrigerate the rotor and the tubes.
Collect 15 mL of conditioned cell culture media at the desired time (such as 24 h). Add the protease inhibitor cocktail (PI) at 1% (v/v) to the conditioned media.
Centrifuge media at 500 × g and 4°C for 10 min, to remove cells. Carefully decant supernatant to sterile centrifuge tubes—a 25 mL serological pipette can be used.
Centrifuge supernatant at 4,000 × g and 4°C for 10 min. Carefully decant supernatant to new sterile centrifuge tubes.
Centrifuge supernatant at 16,000 × g and 4°C for 30 min. Carefully decant supernatant to new sterile centrifuge tubes.
Filter-sterilize the supernatant through a 0.22 µm PES filter into a new sterile centrifuge tube.
DiR labeling
Prepare DiIC18(7) (1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindotricarbocyanine Iodide) (DiR) stock at 2.5 mg/mL (2.47 mM) in ethanol.
Add the appropriate volume of DiR stock to the filtered supernatant from the steps above, to reach a 5 µM final concentration. Mix by pipetting.
Incubate DiR with the filtered supernatant in the dark at room temperature (RT) for 30 min, with gentle inversion every 5 minutes.
Purification of small EVs
Sterilize items for ultracentrifugation by UV light exposure of buckets, centrifuge tubes, and forceps (for removing ultracentrifuge tubes from buckets/rotor) for at least 30 min.
Fill the ultracentrifuge tubes to a volume of approximately 37 mL.
Note: When there is not enough supernatant to fill a tube, fill the balance of the volume with sterile PBS. Ultracentrifuge tubes can collapse if not filled almost to capacity and if not correctly balanced.
Weigh the buckets, writing down the weights so opposing buckets are balanced. Opposing buckets should be within 0.01 g of each other.
In the BSL-2 cabinet or clean bench, so the tubes are not contaminated, add PBS to the lighter tubes in buckets as necessary to balance the centrifuge rotor.
Transfer the rotor containing the samples into the ultracentrifuge, and centrifuge the supernatant at 100,000 × g and 4°C for 3 h.
For the centrifuging step, decant and discard the supernatant carefully and in sterile conditions. Use a micropipette with a sterile tip to remove the liquid that forms at the tip of the tube but does not drop off.
Note: Be careful not to contaminate the tube. In this step, free DiR goes away with the decanted supernatant, so the solution can be decanted, but always be careful not to lose the pellet.
Add 400 µL (360 µL) PI to each tube, and resuspend the pellet by gentle pipetting up and down. Add about 36.5 mL (35 mL) of PBS to each tube.
Weigh the buckets, and add PBS appropriately to balance the rotor to a precision of 0.01 g.
Centrifuge at 100,000 × g and 4°C for 18 h. Very carefully, decant the supernatant, and remove the residual liquid at the lip with a pipetter.
Resuspend the pellets with 100–150 µL PI (protease inhibitor cocktail) in PBS (see Recipes). Gently pipette the solution up and down. Use the tip to gently scrape around the bottom of the tube, to resuspend the vesicles. If desired, combine all samples into one microfuge tube.
Wash DiR-labeled exosomes in Amicon Ultra 4 with 10,000 MWCO, to remove free DiR. Add the sample to Amicon Ultra, and bring the volume to 4 mL total volume, using PBS supplemented with 1% (v/v) PI (i.e., if 2 mL is needed to bring to 4 mL total, add 2 mL of PBS and 20 µL of PI).
Centrifuge DiR-labeled exosomes in Amicon Ultra at 4,000 × g (in swinging bucket rotor, check × g limit if using a fixed angle rotor) at 4°C, in approximately 3-min intervals. Check the volume, and ensure the top chamber does not run dry because that is where the EVs are located. Reduce volume to about 250–400 µL. Discard the lower chamber filtrate and proceed to the next steps.
Transfer the sample containing DiR labeled exosomes in the upper chamber to a fresh microfuge tube, by gently pipetting and using the tip to gather as much liquid from the chamber as possible. Some free DiR may be seen as an insoluble precipitate.
To remove precipitated free DiR dye from DiR labeled exosomes, centrifuge the sample at 16,000 × g and 4°C for 20 min. Gently pipette the supernatant to a fresh microfuge tube.
Note: The supernatant may appear only very light blue to bluish at this stage.
Proceed to protein concentration determination using a micro BCA protein assay kit (Thermo Fisher). Use a nanoparticle characterization system (e.g., NanoSight LM10) to count the particles.
Performing EV uptake experiments
Prepare a 96-well plate of cells at 70% confluency the day before the cellular uptake experiment. The confluency required might depend on the cell type used.
Determine EV concentration through nanoparticle tracking analysis, such as NanoSight, to prepare a standardized number of EVs for cellular uptake experiments.
Prepare a 10-mL solution of 2e7 EVs (2e6/mL EVs) in serum-free OptiMEM containing appropriate antibiotics, for application to the cells.
Remove media from cells growing on a 96-well plate, and wash twice with sterile 1× PBS.
Add 100 µL of a prepared solution of 2e6/mL EVs in serum-free OptiMEM containing appropriate antibiotics to each well in a 96-well plate.
As a control for the DiR-labeled exosomes, a 500-µL solution of 5 µM DiR in OptiMEM can be used, in addition to the labeled exosome samples.
Cells can be imaged over 24 h using a Cytation5 instrument set to 5% CO2 and 37°C for every 2 h. See Figures 2 and 3, where L442 mouse-derived lymphocytes are used.
After imaging of the live cell uptake has been completed, the cells can be fixed with 4% PFA (paraformaldehyde) at room temperature for 15 min, and stained with DAPI in the dark at room temperature for 10 min to count DAPI objects, and normalize EV count to 1,000 cells.
Data and statistical analysis are performed using Microsoft Excel and GraphPad Prism.
Figure 2. Experimental setup for the EV uptake experiment.
Figure 3. Quantifying the abundance of EVs in cells. (A) Labeled exosome abundance detected per 1,000 cells over 24-h, according to specific parameters in Cytation5. Three replicates of L442 mouse lymphocytes were prepared on a 96-well plate, and grown to 70% confluency prior to the addition of exosomes. A specific serum-free OptiMEM with antibiotics containing 2e6 labeled exosomes per mL was added to the cells. Cells were imaged under 10× magnification, with brightfield and the CY7 fluorescent filter, every 2 h up to the 16-h timepoint, then every 4 h up to 24 h after that. After the 24-h reading was complete, the cells were washed and fixed with 4% PFA, and stained with DAPI, to normalize the exosome count to 1,000 cells. The graph here shows the average exosome abundance across the three wells of L442 mouse lymphocytes (GraphPad Prism). (B) A representative image of fluorescent exosomes in L442 mouse lymphocytes at the 12-h time point. (C) A fully processed image of cellular uptake of exosomes with exosomes specifically detected in the Cytation5 software is highlighted by a yellow border. A 3 × 3 area of 10× magnified images was acquired, preprocessed, deconvoluted, and stitched for each well.
Recipes
Media containing exosome-depleted fetal bovine serum (FBS) and penicillin/streptomycin
In a BSL-2 cabinet, prepare 500 mL of OptiMEM with 3% (v/v) exosome-depleted FBS, and 1% (v/v) of penicillin/streptomycin antibiotic solution. The media can then be sterile filtered through a vacuum filter and stored at 4°C before use.
Control Sample for NanoSight quantification
Control can be prepared using DiR and PBS with 1% (v/v) PI.
From the stock DiR of 2.5 mg/mL, prepare a 5 µM dilution in the PBS and PI solution, then incubate in the dark at room temperature for 30 min, with occasional gentle inversion. Follow steps C11 through C13 of the procedure to clean and condense the control sample, as for the DiR-treated sample. After the sample has been prepared, it can be used in NanoSight experiments as a blank for the DiR-treated samples.
Protease inhibitor cocktail (PI) from Pierce Protease Inhibitor Tablets, EDTA-Free
A protease inhibitor cocktail (PI) can be prepared from Pierce Protease Inhibitor Tablets by dissolving one tablet per 5 mL of PBS to make 10% stock. This PI is added at 1% (v/v) to the conditioned media and to each wash step (for example, 500 µL of PI is added to 50 mL of conditioned media).
Acknowledgments
This work was supported by U. S. Public Health Grant R03 AI-135610 (MJE), R01 AI158749-02 (MJE), and 1R21NS113649-01 from the National Institutes of Health. The funders had no role in study design, data collection, analysis, decision to publish, or manuscript preparation.
Competing interests
The authors have declared that no competing interests exist.
References
Busato, A., Bonafede, R., Bontempi, P., Scambi, I., Schiaffino, L., Benati, D., Malatesta, M., Sbarbati, A., Marzola, P. and Mariotti, R. (2016). Magnetic resonance imaging of ultrasmall superparamagnetic iron oxide-labeled exosomes from stem cells: a new method to obtain labeled exosomes.Int J Nanomedicine 11: 2481-2490.
Busato, A., Bonafede, R., Bontempi, P., Scambi, I., Schiaffino, L., Benati, D., Malatesta, M., Sbarbati, A., Marzola, P. and Mariotti, R. (2017). Labeling and Magnetic Resonance Imaging of Exosomes Isolated from Adipose Stem Cells. Curr Protoc Cell Biol 75: 3.44.41-43.44.15.
Cook, R. L., Householder, K. T., Chung, E. P., Prakapenka, A. V., DiPerna, D. M. and Sirianni, R. W. (2015). A critical evaluation of drug delivery from ligand modified nanoparticles: Confounding small molecule distribution and efficacy in the central nervous system. J Control Release 220(Pt A): 89-97.
Corso, G., Heusermann, W., Trojer, D., Görgens, A., Steib, E., Voshol, J., Graff, A., Genoud, C., Lee, Y., Hean, J., et al. (2019). Systematic characterization of extracellular vesicle sorting domains and quantification at the single molecule - single vesicle level by fluorescence correlation spectroscopy and single particle imaging. J Extracell Vesicles 8(1): 1663043.
Gangadaran, P., Li, X. J., Lee, H. W., Oh, J. M., Kalimuthu, S., Rajendran, R. L., Son, S. H., Baek, S. H., Singh, T. D., Zhu, L., et al. (2017). A new bioluminescent reporter system to study the biodistribution of systematically injected tumor-derived bioluminescent extracellular vesicles in mice. Oncotarget 8(66): 109894-109914.
Huotari, J. and Helenius, A. (2011). Endosome maturation. EMBO J 30(17): 3481-3500.
Somanchi, S. S. (2016). Noninvasive In Vivo Fluorescence Imaging of NK Cells in Preclinical Models of Adoptive Immunotherapy. Methods Mol Biol 1441: 307-316.
Théry, C., Zitvogel, L. and Amigorena, S. (2002). Exosomes: composition, biogenesis and function. Nat Rev Immunol 2(8): 569-579.
Zhao, Q., Hai, B., Kelly, J., Wu, S. and Liu, F. (2021). Extracellular vesicle mimics made from iPS cell-derived mesenchymal stem cells improve the treatment of metastatic prostate cancer. Stem Cell Res Ther 12(1): 29.
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This is a correction notice. See the corrected protocol.
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Correction Notice: An Optimized Tat/Rev Induced Limiting Dilution Assay for the Characterization of HIV-1 Latent Reservoirs
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YG Yuvrajsinh Gohil
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Published: Jun 5, 2022
DOI: 10.21769/BioProtoc.4448 Views: 394
Reviewed by: Alessandro DidonnaNarayan SubramanianSalim Gasmi
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I am writing regarding our manuscript ''An Optimized Tat/Rev Induced Limiting Dilution Assay for the Characterization of HIV-1 Latent Reservoirs (https://bio-protocol.org/e4391)" which was published in Volume: 12, Issue: 8 of the Bio-protocol.
There has been a small mistake in the name and catalog number of an enzyme. The name and catalog number of the enzyme have been mentioned as My TaqTM DNA Polymerase (Bioline, catalog number: BIO-21105), instead of My TaqTM HS DNA Polymerase (Bioline, catalog number: BIO-21111) in the materials and reagents section of the protocol.
Accordingly, we need to make correction as follows (in Materials and Reagents): My TaqTM HS DNA Polymerase (Bioline, catalog number: BIO-21111).
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Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4449 Views: 2132
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The authors used this protocol in Development Feb 2022
Abstract
In this study, we present a detailed protocol for live imaging and quantitative analysis of floral meristem development in Aquilegia coerulea, a member of the buttercup family (Ranunculaceae). Using confocal microscopy and the image analysis software MorphoGraphX, we were able to examine the cellular growth dynamics during floral organ primordia initiation, and the transition from floral meristem proliferation to termination. This protocol provides a powerful tool to study the development of the meristem and floral organ primordia, and should be easily adaptable to many plant lineages, including other emerging model systems. It will allow researchers to explore questions outside the scope of common model systems.
Keywords: Live imaging Confocal imaging Floral meristem Aquilegia MorphoGraphX
Background
Meristems are groups of pluripotent stem cells, typically located at the tips of shoots (Steeves and Sussex, 1989). Many fundamental features of meristems are shared across all vascular plants, e.g., the maintenance of a pool of undifferentiated cells, regulated cell proliferation and expansion, and control of post-embryonic organogenesis. However, there remains a great deal of unexplored variation in meristem structure and behavior across land plants. Exploring this diversity is hampered by the reliance on common developmental techniques, such as fixed tissue sectioning and imaging, that do not allow processes such as spatial and temporal patterns of cell division and expansion to be directly observed. In model systems such as Arabidopsis thaliana, genetic and molecular tools have been coupled with advancements in live imaging techniques to allow analyses of both cell behaviors and gene expression in real time. These tools have provided considerable progress in our understanding of meristem development (e.g., Prunet et al., 2016; Geng and Zhou, 2019; Shi et al., 2020; Caggiano et al., 2021; Silveira et al., 2022). However, these advancements are currently limited to a small number of model species, and there is a pressing need to develop quantitative live imaging techniques in non-model systems, and specifically, approaches that may be broadly practical across a range of plant taxa. Here, we present a detailed protocol for live imaging and analysis of floral meristems in Aquilegia coerulea, a member of the buttercup family (Ranunculaceae). This protocol provides a powerful tool to study the development of the meristem and initiation of floral organs, and should be easily adaptable to many plant lineages, including other emerging model systems. This protocol will allow researchers to explore questions outside the scope of common model systems.
Materials and Reagents
35 × 10 mm Petri dish (Corning, product number: 430588)
100 × 15 mm Petri dish (Fisher Scientific, catalog number: FB0875712)
1.5 mL microcentrifuge Eppendorf tubes
Parafilm
Kimwipe
Microscope slides (no special coating required)
Aluminum foil
128 cell plug trays and 4-inch plant plots
Seeds of Aquilegia × coerulea ‘Kiragami’ can be purchased from Swallowtail Garden Seeds (Santa Rosa, CA, USA)
Agar (Invitrogen, catalog number: 16500-100)
Linsmaier & Skoog medium (Caisson Labs, catalog number: L2P03)
Sucrose (Macron Fine Chemicals, catalog number: 57-50-1)
NaOH (Sigma-Aldrich, catalog number: 221465)
Kinetin (Sigma, catalog number: K0753-1G)
Gibberellic Acid (Sigma, catalog number: G7645-1G)
100% EtOH
Sterile ddH2O
Bleach
Propidium Iodide (Sigma-Aldrich, catalog number: P4864)
Note: Potential carcinogen; avoid contact with skin and eyes; wear suitable protective clothing, gloves, and eye/face protection.
Glue (any type of glue that can glue Petri dish to the glass slides)
Culture medium (see Recipes)
Equipment
Scalpel with No. 10 blade (BioQuip Products, catalog number: 2723A)
Straight dissecting needle (Carolina, catalog number: 627201)
Precision Watchmaker's Forceps, Extra-Fine Point (Carolina, catalog number: 624791)
0.5 mm Glass beads (Sigma-Aldrich, catalog number: 18406)
Razor blades
Microscope (Zeiss Stemi DV4 Stereo)
Microscope (LSM 980 NLO Multi-photon with a water immersion lens W Plan-Apochromat 20×/1.0 DIC UV-IR M27 75mm)
Software
FIJI (https://imagej.net/software/fiji/) or ImageJ (https://imagej.net/software/imagej/)
MorphographX (MGX) https://morphographx.org/software/.
Procedure
Plant materials and growth conditions
Seeds of Aquilegia × coerulea ‘Kiragami’ can be purchased from Swallowtail Garden Seeds (Santa Rosa, CA, USA), and germinated in wet soil in plug trays, which generally takes two to three weeks.
When the seedlings develop their first two true leaves, they are transplanted from plug trays to five-inch pots. Seedlings and young plants are grown in growth chambers with 16-h daylight at 18°C, 8-h dark at 13°C, and humidity under 40%. In these regular growth conditions, the plants are watered twice per week.
Once the plants develop five to six true leaves, they are transferred into the vernalization chamber, which is set at 16-h daylight at 6°C, and 8-h dark at 6°C. They should be well watered (i.e., the soil is fully hydrated) before being moved into cold conditions, and are generally not watered during the vernalization period.
Plants stay in vernalization for three to four weeks, and are then moved back into regular growth chambers for flowering. We usually put a small amount of controlled-release fertilizer in each pot post vernalization. Generally, inflorescences start to develop three weeks after vernalization.
Dead leaves should be actively removed, to prevent fungal or pest infections.
Preparation of culture/imaging plates
Take an empty 1,000 μL pipette rack and gently press the foil square into each one of the rack holes, to create a round well (Figure 1a, b). Cut small squares of aluminum foil (1 × 1 cm). Carefully store foil squares in an autoclavable container (such as a glass Petri dish) and autoclave (Figure 1c).
Autoclave glass beads and ddH2O.
Prepare the culture media according to Recipe 1.
While still molten, fill the 35 × 10 mm Petri dishes half way with agar, quickly place one foil square in the center of the Petri dish, concave side up. With sterile tweezers, place a glass bead into the depression in the foil square (Figure 1). This is sufficient to ensure that the convex side of the foil is pressing into the agar. Once the bead is on the foil square, the foil will automatically gravitate to the center of the plate. Let the plates cool and solidify inside the sterile hood. Once solid, using tweezers, remove the glass beads and carefully peel off the foil square. This leaves a shallow well in the agar for mounting the meristems.
Solidified plates can be stored at 4°C for 2 months.
Figure 1. Making plates for live imaging. (a) Take an empty 1,000 μL pipette rack and gently press the foil square into each one of the rack holes, to create a round well. (b) A strip of wells. (c) Foil squares are autoclaved and stored in a glass Petri dish. (d) Examples of plates solidifying in a sterile hood with foil squares and glass beads in place. (e) A 35 × 10 mm Petri dish with blue dye to show the well in the center, where the meristems will be positioned. (f) The 35 × 10 mm Petri dish will then be glued onto a microscope slide. The slide is labeled with dates, and A1–A4 are the meristem label and their relative locations in the well.
Tissue dissection and mounting
The forceps, surgical needles, and dissection blades are all sterilized in 10% bleach, washed in ddH2O, and dried with Kimwipes before dissection.
Young axillary inflorescences or whole inflorescences are excised off the plant using forceps or scissors, for meristem dissections (Figure 2).
Figure 2. Developmental stages for dissecting FMs for imaging. Axillary meristems can be obtained from either a lateral inflorescence branch (a, b) or a young inflorescence (c, d). Leaves that should be removed before or after the 10% bleach wash are indicated. Red dash lines indicate the locations where the floral axis will be excised for the bleach wash. (e) Example of a FM undergoing the stages from continuously producing more whorls of floral organs to the early developmental phase of carpels. This FM was imaged every two days.
Inflorescences are washed in freshly prepared 10% bleach in a 100 × 15 mm Petri dish for 20 min. Any leaves and bracts on the stem should be removed using the forceps, but the attachment points of the petioles should be left on the stem (Figure 2); if the petiole is completely removed from the stem, we found that the bleach solution will enter the wound and spread through the cells quickly, which kills the axillary meristems as well.
The stems are then washed with double-distilled water (ddH2O) three times in the same 100 × 15 mm Petri dish, to completely remove the bleach residue, after which the stems are kept immersed in sterile ddH2O.
When dissecting, put one stem under the microscope (the rest remaining in distilled water), and carefully remove the bracts and sepals of each floral meristem, using the tip of a dissecting needle. Then, excise the meristem off the branch with the scalpel, and transfer it onto a 35 × 10 mm Petri dish with the culture medium. Ensure the base of the stem (usually there is about 1 mm of stem remaining) holding the meristem is pushed into the agar. We typically mount four floral meristems per dish.
Glue the Petri dish to a microscope slide, and label the date and the meristems on the slide (Figure 1c).
Staining
Meristems should be stained for 1–3 min in the Petri dish, by applying 50 μL propidium iodide (0.5 mg/mL) directly to the meristems, to ensure the meristems are fully immersed. The mounting well should sufficiently contain the stain, so that it creates a dome over the meristems. Take care of there being sufficient stain, so that the meristems are fully immersed in stain throughout the whole staining period. It is important to note that the staining time will likely be specific to the plant and tissue being imaged, so here we just give a general time range; it is recommended that the staining time be optimized for each experiment. We would recommend starting with a low concentration for 1 min, and adding time only if the tissue seems under-stained. Another important optimization is the staining for subsequent imaging time points. Aquilegia meristems were stained for 2.5 min for time point 1, then 2 min for time points 2 and 3, and 2–3 min for time-point 4.
Carefully pipette off the stain, and wash the meristems by pipetting with ddH2O three times.
Imaging
Note: Imaging will differ depending on the type of confocal and objective lenses available, as well as the type of tissue or stain used.
Meristems were imaged immediately after staining, using a LSM 980 NLO Multi-photon confocal laser scanning microscope (Ziess, Germany) equipped with a water immersion objective (W Plan-Apochromat 20×/1.0 DIC UV-IR M27 75mm, Ziess).
The Petri dishes were filled with ddH2O while imaging, and the water was immediately removed after imaging.
A DPSS 514nm laser was used for excitation, and emission was collected between 580–670nm.
Scans were frame averaged 2× and z-sections taken at 2-µm intervals. This interval will vary depending on the size of the tissue, and we found that 2 µm was sufficient for downstream analysis, while also minimizing the time the tissue was subjected to the laser. On average, it takes 2 min to image a young Aquilegia FM, and about 4 min to image a young Aquilegia bud with early carpel development.
After imaging, the remaining water in the Petri dishes was carefully removed by pipetting using a P20 pipette, and the Petri dishes were returned to the tissue culture growth chamber.
Samples were imaged every 48 h, typically for 3–5 time-points.
Image processing
Note: The following protocol for conducting segmentation and lineage tracing of the confocal images was adapted from (de Reuille et al., 2014; Strauss et al., 2019), and the user manual at https://www.mpipz.mpg.de/MorphoGraphX/help, all of which detailed the structure of MorphoGraphX (MGX), including how the image data are stored, extracted, and processed. Here, we focus on the steps and parameters that are specific to processing confocal images of Aquilegia floral meristems, and steps to reproduce figures in Min et al. (2022). We will use two original .czi files from our study as an example, which can be downloaded from this google drive link: https://drive.google.com/drive/folders/1WjaCieLGrnTW7d51143b8HOn-dYmsMU-?usp=sharing Images of individual time points will be processed separately first, then loaded together for lineage tracing (details in the following section Parent Labeling & Lineage Tracing).
Software installation and equipment setup
Download the newest version of MGX from https://morphographx.org/software/. Since the software improvements have mostly been implemented in the Linux versions, installation of the Linux operating system is preferred. To run, MGX requires a computer nVIDIA graphics card that supports CUDA, with at least 2 Gb of video memory and 8 Gb of the main memory of the computer itself. A larger video memory, a larger main computer memory, and/or a multi-core CPU can significantly shorten the processing time for some of the steps.
Processing a large amount of imaging data with MGX can be time-consuming, and we strongly recommend readers have a comfortable workstation with proper office ergonomics if possible. An ultrawide monitor, or a dual-monitor setup, can be extremely helpful, especially during the parental lineage tracing error correction process.
Load image into MorphoGraphX
Convert the format of the stack image: Open the stack image (e.g., the 20210207_r8_A1.czi files) with FIJI (https://imagej.net/Fiji) or ImageJ: (https://imagej.net/Welcome), adjust the brightness and contrast, and save the image as 20210207_r8_A1.tif format.
Note: The images we acquired from the confocal microscope can be dim because we wanted to minimize tissue damage from both laser power and laser exposure time (which, in turn, slows down the growth), and thus the adjustment in brightness and contrast was almost always needed. Images that look slightly over-saturated in FIJI/ImageJ after adjusting for brightness and contrast, look better when loaded in MGX (Figure 3).
Figure 3. Comparison of how a confocal stack looks in ImageJ and MGX before and after adjusting the brightness and contrast. Images that appear to be slightly over-saturated in ImageJ generally look good in MGX.
Load the stack into MorphoGraphX: either drag the 20210207_r8_A1.tif file directly onto the MGX interface (Figure 4), or Stack1 → open → choose the image.
Figure 4. Overall layout of MorphgraphX interface.
If the stack still appears to be dark, there are two ways to directly adjust the brightness in MGX, instead of adjusting the brightness/contrast in Fiji, and loading the stacks again: 1) under the Main tab, under Work, change Opacity; 2) go to the View tab, and change the brightness and contrast under View Quality.
You can rotate the stack by using the left click of your mouse, move the stack to different parts of the screen with the right-click, and zoom in and out with the scroll wheel. By default, Stack 1 will appear green, and Stack 2 will be red; the setting of the colors can be changed using the Main Stack Colormap, under the Main tab.
Extract the surface
Go to tab, Process → Stack → Filters → Gaussian Blur Stack; change all the X/Y/Z Sigma parameters (appears at the right bottom corner; double click the cell to change) to 1; run the process twice (either by double-clicking the processor, or hitting the “Run” arrow on the upper right corner).
Note: It is important to blur each stack the same number of times, especially when dealing with images for lineage tracing.
Run Process → Morphology → Edge Detect, which creates a solid global shape of the object.
Optional: Remove unwanted parts. For example, if we only want the top part of the meristem, we could remove the extra stamen/staminode primordia by clicking on “Voxel Edit ” on the top bar; Press Alt-key and left click the mouse, to erase parts that you don’t want.
Note: 1) If the Alt-key is not working, it is likely due to a conflict in the hotkey setting in your operating system, which already assigned a function to the Alt-key, and thus prevents it from being used for selection in MorphoGraphX. You can change this setting in your operating system by assigning other keys to avoid the conflict. 2) Removing unwanted parts using the voxel edit can increase the speed of downstream processes, but the removal of parts is not reversible, so this step is generally not recommended unless there is a significant constraint on computer capacity.
Optional: If there are holes on the shape, run Stack → Morphology → Fill Holes. Skip if no hole is observed.
Note: The adjustable parameters in this step are the X/Y-Radius. The bigger they are, the more likely they can fill the holes. However, the bigger they are, the more possible it is going to change your surface shape.
Go to Mesh → Creation → Marching Cubes Surface, change the threshold parameter to 20,000, run the process.
Trim off the bottom. In the Main tab, ensure that the Mesh checkbox and “View” option are set to “All”. This will enable the visualization of the mesh. Click the “Select points in mesh (Alt+V)” tool on the left toolbar, and hold the Alt-key to select the bottom vertices of the apex. The selected vertices should turn red. Hit the delete key on the keyboard to remove them. To make this easier, it is better to have the apex in a horizontal position. You can do this by left-double clicking on it. Try to delete the bottom cleanly. Save the mesh as “20210207_r8_A1_s.c6.mgxm”.
Note: Since many meshes will be saved during the process, we tried to name the files in a clear way, so that one can easily recognize that a given mesh is produced by a specific step. In this example, the information is recorded as “s.c6”: s stands for single time point and c6 refers to step 6 of part C “Extract the surface” of this protocol.
Run Mesh → Structure → Subdivide. Then go to Mesh → Structure → Smooth Mesh, change the Passes number to 10 (the default is 1), and run the process. Repeat this subdivide step and then smooth the process twice more (i.e., three times in total). By now, the total number of vertices (shown in the bottom left window) in the mesh for an early stage FM should be above 500,000, while for an older stage FM should be approximately 1,000,000.
Note: Each subdivision increases the total number of vertices by approximately four-fold. The last round of subdividing and smoothing can be demanding on computational power. The vertices look like little triangles when magnified.
Save the mesh as “20210207_r8_A1_s.c8.mgxm”.
Go to the Main tab, Unselect “Mesh”. Make sure “Main” and “Surf” are selected, but “Work” is not. Then run Process → Mesh → Signal → Project Signal, to project the signals to the surface.
Note: The default Max Dist (µm): 6.0 is good for Aquilegia floral meristems, since they have relatively large cells, especially when compared to Arabidopsis meristem cells. If visualizing a tissue with smaller cells, the Max Dist can be decreased accordingly.
Save the mesh as “20210207_r8_A1_s.c10.mgxm”.
Cell segmentation
Go to Process → Mesh → Segmentation → Auto-segmentation and change the following parameters from default: normalize to “No”, auto-seeding to 3.0, blur cell radius to 3.0, combine to 1.1. Run the process.
Note: The auto-segmentation process can be demanding on the computational power. For Aquilegia floral meristems, depending on the developmental stages, we obtained good results by changing the auto-seeding and blur cell radius to 2.0, 2.5, or 3.0. The radius for auto-seeding and blur cells should be the same.
Save the mesh as “20210207_r8_A1_s.d2.mgxm”.
Correct segmentation errors
No matter how good the image stack is, there are likely to be segmentation errors, especially with samples such as Aquilegia floral meristems, that contain hundreds to thousands of cells in a stack. It is very important to correct as many errors as possible at this step, since it will greatly reduce the time that will likely be needed in future processes to correct parental labeling errors (which is relatively more time-consuming compared to correcting segmentation errors). It is also important to constantly save the newer version of the mesh (e.g., 20210207_r8_A1_s.e0.mgxm). The two processes with opposite functions, “Watershed Segmentation” and “Segmentation Clear”, are located right next to each other on the list, and it is not impossible to click the wrong button during processing. If the “Segmentation Clear” is run by accident on the whole mesh, while the newest version of the corrected mesh has not been saved, it means starting over again.
Checking segmentation errors can be done by zooming in on one part of the mesh and selecting “Vtx” under the Surface panel of the Main tab, and then accessing the Mesh panel under the “Cells” option. By toggling back and forth between the checked and unchecked options in the Mesh checkbox, you can compare the cell wall positions and segment boundaries. Correct all the possible errors in that region, then move to another part of the mesh, and repeat the process. There are a few types of common segmentation errors (Figures 5–7):
If a cell is over-segmented: If cell A is over-segmented into A1 and A2, select “Add label to selection ” on the left toolbar, press Alt-key, and click on A1 (or A2). Then select “Fill label (Alt+M) ” on the left toolbar, press Alt-key, and click on A2 (or A1) (Figure 5).
Figure 5. Examples of over-segmented cells. (a) How over-segmented cells (outlined in red) look under the Surface/Cells view. (b) How over-segmented cells (outlined in red) look under the Surface/Vtx view. (c) How the mesh looks. Over-segmented cells can be easily spotted by comparing between (c) and (b). (d) How cells look after over-segmentation has been corrected.
If a cell is under-segmented: This is a relatively common situation for cells at the boundary of the stack (due to faint signals), and at the organ boundaries (because the cells at the boundary are much smaller than the auto-segmentation radius). Click “Select points in mesh (Alt+V)” on the left toolbar, press Alt-Key, and select parts of the cell that need to be corrected (as long as some vertices in that cell were selected, it is fine). Then, under the Process tab, run Mesh → Selection → Extend to Whole Cells, which selects all the vertices in that target cell (Figure 6). On the left toolbar, click on “Erase selected ” to remove the labels from the cell. Labels can also be removed by running Mesh → Segmentation → Segmentation Clear under the same Process tab (Figure 6). Then choose “Add new seed (Alt+B) ” from the left toolbar, press the Alt-key and the left click of the mouse, to draw the outlines of the cells (Figure 6). Theoretically, the cells can be segmented as long as there is at least one seed inside, but drawing out the rough outlines of the cells can help with correct segmentation, because sometimes the cell boundaries are faint. Lastly, under the Process tab, run Mesh → Segmentation → Watershed Segmentation (Figure 6).
Figure 6. Examples of under-segmented cells. (a) An under-segmented cell outlined in red. (b) Under-segmented cells can be easily spotted by comparing the segmented outlines to the original mesh. (c) The label of the under-segmented cell being cleared. (d) The two cells being re-seeded. (e) How the labels look after the under-segmentation is corrected.
If the boundary of a cell is incorrect: This is most likely due to a faint signal in the cell wall staining (Figure 7). On the left toolbar, click “Add label to selection ”, then press the Alt-key, and click the cell that needs to be corrected. Then choose “Add current seed (Alt+N) ” from the left toolbar, use the left click of the mouse to fill in the gaps, and draw the correct boundary (Figure 7). Then, under the Process tab, run Mesh → Segmentation → Watershed Segmentation (Figure 7).
Figure 7. Example of a cell with incorrect boundary. (a) Red arrow pointing to the incorrect boundary of a cell. (b) How the original segmentation looked. (c) How the corrected segmentation looked.
Remove the cells on the boundary of the mesh: After all visible errors are corrected on the mesh, run Mesh → Cell Mesh → Fix Corners Classic, under the Process tab. Then click “Select points in mesh (Alt+V) ” on the left toolbar, press Alt-key, and select cells on the boundary of the mesh. Then, under the Process tab, run Mesh →selection → Extend to whole cells. After the cells are selected, click “Delete selected” on the left toolbar, and save the mesh as “20210207_r8_A1_s.e4.mgxm”.
This last step is important because the sizes of the cells on the boundary are likely to be inaccurate due to several reasons: 1) the confocal Z-stack may have stopped scanning at this point, without including the entire cell on the boundary; and 2) we arbitrarily trimmed off the bottom of the stack in step C6, which may have trimmed off parts of cells located on the boundary (Figure 8).
After the first layer of cells on the boundary is removed, run Mesh → Cell Mesh → Fix Corners Classic, under the Process tab again, and save the mesh again. This will be the mesh (i.e., 20210207_r8_A1_s.e4.mgxm) that is used to conduct lineage tracing.
Figure 8. Removing cells on the boundary of the mesh. (a, b) How the labels look before removing the cells on the boundary, which had unnatural shapes. (c) How the labels looked after removing the cells on the boundary.
Parent labeling & Lineage tracing
After processing the stacks and meshes from both time-point 1 (20210207_r8_A1_s.e4.mgxm) and time-point 2 (20210209_r8_A1_s.e4.mgxm), they are ready to conduct parental labeling and lineage tracing.
Parental labeling
Go to the Main toolbar, load the segmented mesh for time point 1 on Mesh 1, and the segmented mesh for time point 2 on Mesh 2. Both meshes are now loaded as meshes of Stacks 1 and 2 under the Main tab, respectively. The main stacks (i.e., the original .tif files) can also be loaded using the Main toolbar for Stacks 1 and 2. It is a personal preference whether or not to load the main stacks, because they are not required for the lineage tracing process, but it might look nicer to have the main stack shown when taking pictures.
Go to the View tab, and check “Stack1” in the Control-Key-Interaction panel. This allows you to move the meshes separately. Using the right click of the mouse alone will move both meshes together, but using the right click of the mouse while pressing the Control-key on the keyboard will only move Stack 1. Use the control key and the mouse to move Stacks 1 and 2 side by side on the screen.
Go to the Main tab Stack 1, next to the Mesh checkbox, click Colors Editor to change the colors of Mesh 1 and/or Mesh 2, so that they are different from each other.
Go to the Main tab Stack 1, make sure the checkboxes of Main, Work, and Surface panels are all unchecked, but the one for Mesh is checked. Make sure that “Cells” is selected as the view option for both the Mesh and the Surface panels, and the view option for Cells is selected as “Label”.
Go to the Main tab Stack 2, uncheck Main and Work, but check Surface and Mesh. The view options for Surface and Mesh should be “Label” and “Cells” as well, respectively. Then check the checkbox of Parents to the right of the Surface checkbox. The colored segmented cells in Stack 2 should disappear after this.
When the meshes of the meristems are first loaded, we see the front view of the meristems. Use the left click on the mouse and the Control key to adjust the orientations of both meshes, so that the side views are shown.
Use the left click of the mouse and the Control key to move Mesh 1 above Mesh 2. Then, use the left click of the mouse alone to rotate both meshes, so that the front views are shown again.
Look for a few cells on Meshes 1 and 2 that appear to be the same. Usually, the large cells at the center of the meristems are the most easily recognizable. Transfer Mesh 1 on top of Mesh 2, by pressing the Control-key and using the right click of the mouse to match those recognized cells on both meshes.
Adjust the orientation and angles of Mesh 1 using the left click of the mouse and the Control-key, to make more cells on both meshes overlap. If the growth between the two time points is rather large, adjust the size of Mesh 1 by going to the Main tab Stack 1, check the Scale checkbox, and increase the X values (adjusting Y or Z is also fine, since all axes are linked).
To transfer labels from Mesh 1 to Mesh 2, go to the Main tab Stack 2, so that Stack 2 is active. Select “Grab Label ” from the left toolbar, hold the Alt-key, and click on the cells that are aligned on both meshes. If a cell at time-point 1 appears to have divided at time-point 2, click both cells and they will appear to be the same color.
Transfer labels of all possible cells from Mesh 1 to Mesh 2. Because of the meristem’s 3D structure, it is impossible to grab labels of all matching cells without adjusting the angles and orientation of the meshes. We recommend that users deal with one subregion of the mesh at a time (just like when correcting the segmentation errors): start from the center of the meristem, move down from the center to one edge of the mesh, label all possible cells in that region, then move on to the adjacent region. It is also possible that different regions of the samples require independent adjustments to the mesh sizes, which will require the user to use the Scale function (step A9) repeatedly. For example, when tracing cells on the newly initiated primordia, the size of Mesh 1 will likely need to be greatly scaled up, to match the cells on Mesh 2; but when tracing cells on the boundary regions, Mesh 1 will most likely not need to be scaled. A video demonstration of lineage tracing can be found on: https://www.youtube.com/watch?v=KDiCyGrALYk&t=26s.
Save the parents' labels by running Mesh → Lineage Tracking → Save Parents under the Process tab. Make sure Stack 2 is active when saving the parents (otherwise, an empty file will be saved). Use caution when saving, because the Save Parents option is listed adjacent to Reset Parents, and the consequences of accidentally running the wrong process can be detrimental. Make sure to label the lineage tracing file informatively, and identify the version, since multiple versions may need to be saved when correcting lineage tracing errors (because there is no undo button!). For instance: r8-A1-0207to0209-v1.csv.
Correcting lineage tracing errors
Although it is not necessary to correct lineage tracing errors to generate a growth heat map, it is important to correct all errors before running any analysis, to ensure the accuracy of the results. To check the correspondence of the traced cells, make sure Stack 1 is active, and under the Process tab, run Mesh → Cell Axis → PDG → Check Correspondence. The cells with errors will be highlighted in red on both meshes. To correct the errors, the original meshes of time-point 1 and time-point 2 need to be opened in two separate MorphoGraphX windows, which is why we have recommended that users have an ultrawide monitor or a dual-monitor setup. Opening the meshes in additional windows is necessary, because the meshes in the lineage tracing window have been simplified, so that only the vertices at the junctions between cells are present. Therefore, any modification of the meshes should be done on the original mesh, rather than the mesh being checked for correspondence.
The error correction process consists of repetitive steps of 1) zoom in on one region of the meshes of the lineage tracing window, 2) identify the sources of errors, 3) correct the error on the original mesh 1 or 2, 4) save the updated versions of the original mesh and load it in the lineage tracing MorphoGraphX window again, 5) re-run “Check Correspondence” to make sure all the cells in the region are blue, and 6) move on to the next region with errors in the lineage tracing window until all the errors are corrected.
There are a few common types of errors in check correspondence:
Parental labeling error or segmentation error on the original meshes. If either kind of error occurs, the area on Mesh 1 will look as in Figure 9a. Turn on the checkbox for Surface for both Stacks 1 and 2, make sure Cells are selected, and the view option is set to Label. Compare the colors of the cells in that location, to determine whether a cell was wrongly labeled, or the original mesh was wrongly segmented.
If the cells on Mesh 2 had the wrong parental label, repeat steps 8 to 10 in Part A (Parental labeling) but only for the cells with error. Make sure Stack 2 is active and save the parents’ labels by running Mesh → Lineage Tracking → Save parents under the Process tab. We recommend saving the new version of the parental labels as a new file, no matter how trivial the modification may have seemed to be.
If the error is due to segmentation error on the original mesh, it would be because either a cell on Mesh 1 is under-segmented, or the cell on Mesh 2 is over-segmented. Check the original meshes as described in step 5, and save the modified mesh as a new, separate file.
Errors at the cell junctions. This is likely to be the most common error in Check Correspondence and the junctions in question will be indicated in Mesh 1. They are usually due to tiny differences in how neighboring cells connect to each other in Mesh 1 and 2 (Figure 9b). Zoom in on the junction in question in both Meshes 1 and 2, and compare check and uncheck the Mesh checkbox, to identify which mesh should be corrected. Then use “Add label to selection ” on the left tool bar, press the Alt-key, and click the cell that needs to be corrected. Then choose “Add current seed (Alt+N) ” from the left toolbar, and the left click of the mouse to fill in the junction. Then, under the Process tab, run Mesh → Cell Mesh → Fix Corners Classic, and save the modified mesh as a new, separate file.
Figure 9. Examples of lineage tracing errors. (a) Two major types of errors. Left: Most likely due to incorrect parental labeling or in correct segmentation, e.g., Stack 1 is over-segmented, but only one of the cells can be mapped to Stack 2. Right: Most likely due to incorrect cell junctions. (b) An example of why junction error can occur. In Stack 1, Cell A and D were physically connected to each other, but C and B were not, while in Stack 2, C and B were physically connected to each other.
Data analysis
After all the errors are corrected, reload Meshes 1 and 2 to Stacks 1 and 2, respectively. Make sure Stack 2 is active and the Parents box is checked. Under the Process tab, run Mesh → Lineage Tracking → Load parents, and load the latest version of the parental tracing file.
For all the heat maps, the scale of the values can be changed in Process → Mesh → Heat Map → Heat Map Range; the styles can be changed by clicking the Colors Editor next to the view option of Cells in the Surface panel; and screenshots can be taken by clicking the Save screenshot on the main toolbar. All the original images from Min et al. (2022) were saved as .PNG in 2700 px (width) × 2500 px (height).
Heat maps of cell area expansion and cell proliferation
To create a heat map for cell area expansion, under the Process tab, run Process → Mesh → Heat Map → Heat Map Classic. Select “Area” for the heat map type and “Geometry” for the visualization. Differences in various change map options can be found on the MorphoGraphX manual. Also select the “Change map” checkbox. This tells MorphoGraphX to make a heat map comparing Stack1 and Stack2. The heat map can be visualized on either the first (typically, Stack 1) or second (Stack 2) time points. For the growth sample here, select “Increasing” if Stack 1 (i.e., time-point 1) is active or “Decreasing” if Stack 2 (i.e., time-point 2) is active.
To create a map of cell proliferation, make sure Stack 2 is active, and run Process → Mesh → Lineage Tracking→ Heat Map Proliferation.
To create images such as Figure 3 in Min et al. (2022), in which divided cells are highlighted on a cell area extension heat map, first run cell area expansion heat map on Stack 2. Check “Report to spreadsheet” so that the values of cell area expansion for each cell can be saved. Give the spreadsheet an informative name, such as “r8-A1-tp1_tp2-growth-allcells.csv”. Then create a map of cell proliferation by running Process → Mesh → Lineage Tracking→ Heat Map Proliferation. Subsequently, run Process → Mesh → Heat Map → Heat Map Select, and change the range values: Lower Threshold to 2, and Upper Threshold to 3 or higher. This step will select all the cells that have experienced cell division. Then, go to Process → Mesh → Heat Map → Heat Map Load, load “r8-A1-tp1_tp2-growth-allcells.csv” as the Heat Map file, and make sure the Column to load is set as “Value”.
The aesthetics of the growth heat map and cell outlines can be changed in the Main tab. To change the cell outlines, go to Main → Stack 1 → the Colors Editor by the Mesh panel. To change the heat map styles, go to Main → Stack 2 (if heat map is displayed on Stack 2) → the Colors Editor by the Cells in the Surface panel. Sometimes, the heatmap color scale appears to be incorrect on the screen. This is most likely to happen when both Stack 1 and Stack 2 are displaying heat maps, and the color scale of Stack 1 will cover the color scale of Stack 2. This can be simply solved by unclicking the Surface panel under Stack 1.
Heat maps of principle direction of growth and anisotropy
Make sure the parental file has been loaded to Stack 2, and then switch to Stack 1 to designate it as the active stack. Under the Process tab, run Mesh → Cell Axis → PDG → Check Correspondence, No error should show up since the meshes have been corrected. Make sure the active Stack is the stack that you want to display the heat map on, so if you want to display heat map on time-point 2, make Stack 2 as the active stack. Then run Mesh → Cell Axis → PDG → Compute Growth Directions. The PDG values can also be saved by running Mesh → Cell Axis → Cell Axis Save. Detailed explanations of the PDG parameters can be found in the MorphGraphX manual.
To change the display of the PDG map, go to Mesh → Cell Axis → PDG → Display Growth Directions. The PDG heat maps in Min et al. (2022) were displayed as Anisotropy, which is the ratio between StretchMax and StretchMin. A ratio of 1 means no deformation, 2 means an elongation of 100%, and 0.8 a shrinkage of 20%. The color and size of the PDG vectors can also be modified. By default, vectors corresponding to expansion (stretch ratio > 1) are displayed in white, while red is used to draw the direction of shrinkage (stretch ratio < 1). The “Threshold” parameter is used to display PDGs axis only in cells for which the anisotropy is above a given value. Since we save each image at a relatively high resolution (2700 × 2500), we found that a Line Width of at least 10 px is needed for good visualization on the final screenshot.
Perspectives
In this study, we presented the first quantitative live-imaging protocol of floral buds of A. coerulea, which offers considerable potential for application to other non-traditional plant systems. This step-by-step guide offers an important source of basic information for non-model researchers who can take the core of the protocol and adapt it according to the needs of their system. Some aspects of any live imaging project will be specific to the species and/or tissue; therefore, dissection methods, sterilization time, media recipes, and staining times are all likely to be elements that will require optimization. Additionally, there is still room for improvement to obtain higher quality quantitative data. First, our samples were stained with propidium iodide (PI), which generally gave good signal in most of the tissue, but cells in the organ boundary regions were often under-stained. Repetitive long-term staining with PI is known to become toxic to tissues and thus slow growth (Grandjean et al., 2004; Bureau et al., 2018), which was also the primary factor that restricted the length of the analyzed developmental window. Further development of transgenic markers for the plasma membrane would help to solve these issues. Second, our analysis was limited to surface reconstruction of the cells, although the behavior of cells under the epidermal layer is an indispensable part of fully understanding meristem morphogenesis. Third, due to the imaging mechanisms of the available confocal microscope, cell walls perpendicular to the focal axis of the microscope were often not detected. Combined with the fact that cells at the organ boundary were often poorly stained, we were often unable to segment and analyze cells in many boundary regions on the abaxial side of some primordia. Except for the issue with PI staining, all of the other limitations described here are, in fact, challenges faced by similar studies in the established model systems (Rambaud-Lavigne and Hay, 2020; Prunet and Duncan, 2020). Fortunately, rapid development in microscopes that allow long-term, deep-tissue, minimally invasive scanning, as well as software developments that can segment and reconstruct multiple cell layers in 3D from the imaging data, are in progress. A comprehensive understanding of "the genetics of geometry" (Coen et al., 2004) of morphogenesis in a diverse set of plant systems is hopefully underway.
Recipes
Culture medium
To make up 1 L of the culture medium, dissolve 2.375 g of Linsmaier & Skoog medium (Fisher Scientific; final strength: 0.5×) and 30 g of sucrose (final concentration: 3%) in 1 L of ddH2O. The Linsmaier & Skoog medium should provide buffering capacity such that the pH of the solution should be approximately 5.8. If the pH is too high, adjust it with 1N NaOH solution. Then, add 8 g of agar (final concentration: 0.8%), and autoclave.
Once the autoclaved medium has cooled to a degree that is not too hot to be touched by a bare hand, add 10-6 M kinetin (Sigma) and 10-7 M gibberellic acid (GA3, Sigma). Do not reheat the culture media once hormones have been added. Mix well and pour the plates in a fume hood, to avoid contamination. 10-6 M kinetin and 10-7 M GA3 can be diluted as follows:
10-6 M kinetin
Make 10-1 M stock solution: dissolve 21.52 mg kinetin in 1 mL of 1 N NaOH in an Eppendorf tube. Seal the tube tightly with parafilm. This stock solution can be stored at 4°C for a few months.
Add 1 µL of the stock solution in 100 µL of ddH2O, to reach the concentration of 10-3 M.
Add 1 µL of 10-3 M solution in every 1 mL of culture medium, to reach a concentration of 10-6 M.
10-7 M GA3:
Make 10-1 M stock solution: dissolve 34.64 mg GA3 in 1 mL of EtOH in a 1.6 mL Eppendorf tube. Seal the tube tightly with parafilm. This stock solution can be stored at 4°C for a few months.
Add 1 µL of the stock solution in 1 mL of ddH2O to reach the concentration of 10-4 M.
Add 1 µL of 10-4 M solution in every 1 mL of culture medium, to reach a concentration of 10-7 M.
Acknowledgments
This study was funded by the Emerging Models Grant from the Society of Developmental Biology.
Competing interests
The authors declare no conflicts of interest.
References
Bureau, C., Lanau, N., Ingouff, M., Hassan, B., Meunier, A. C., Divol, F., Sevilla, R., Mieulet, D., Dievart, A. and Perin, C. (2018). A protocol combining multiphoton microscopy and propidium iodide for deep 3D root meristem imaging in rice: application for the screening and identification of tissue-specific enhancer trap lines. Plant Methods 14: 96.
Caggiano, M. P., Yu, X., Ohno, C., Sappl, P. and Heisler, M. G. (2021). Live Imaging of Arabidopsis Leaf and Vegetative Meristem Development. Methods Mol Biol 2200: 295-302.
Coen, E., Rolland-Lagan, A. G., Matthews, M., Bangham, J. A. and Prusinkiewicz, P. (2004). The genetics of geometry.Proc Natl Acad Sci U S A 101(14): 4728-4735.
Geng, Y. and Zhou, Y. (2019). Confocal Live Imaging of Shoot Apical Meristems from Different Plant Species. J Vis Exp(145): e59369.
Grandjean, O., Vernoux, T., Laufs, P., Belcram, K., Mizukami, Y. and Traas, J. (2004). In Vivo Analysis of Cell Division, Cell Growth, and Differentiation at the Shoot Apical Meristem in Arabidopsis. The Plant Cell 16(1): 74-87.
Min, Y., Conway, S. J. and Kramer, E. M. (2022) Quantitative live-imaging of floral organ initiation and floral meristem termination in Aquilegia. Development 149 (4): dev200256
Prunet, N. and Duncan, K. (2020). Imaging flowers: a guide to current microscopy and tomography techniques to study flower development. J Exp Bot 71(10): 2898-2909.
Prunet, N., Jack, T. P. and Meyerowitz, E. M. (2016). Live confocal imaging of Arabidopsis flower buds. Dev Biol 419(1): 114-120.
Rambaud-Lavigne, L. and Hay, A. (2020). Floral organ development goes live. J Exp Bot 71(9): 2472-2478.
de Reuille, P. B., Robinson, S. and Smith, R. S. (2014). Quantifying cell shape and gene expression in the shoot apical meristem using MorphoGraphX. Methods Mol Biol 1080: 121-134.
Steeves, T. A. and Sussex, I. M. (1989). Patterns in plant development. Cambridge University Press.
Strauss, S., Sapala, A., Kierzkowski, D. and Smith, R. S. (2019). Quantifying Plant Growth and Cell Proliferation with MorphoGraphX. Methods Mol Biol 1992: 269-290.
Shi, B., Wang, H. and Jiao, Y. (2020). Live Imaging of Arabidopsis Axillary Meristems. Methods Mol Biol 2094: 59-65.
Silveira, S. R., Le Gloanec, C., Gomez-Felipe, A., Routier-Kierzkowska, A. L. and Kierzkowski, D. (2022). Live-imaging provides an atlas of cellular growth dynamics in the stamen. Plant Physiol 188(2): 769-781.
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4,450 | https://bio-protocol.org/en/bpdetail?id=4450&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Protocol for High Throughput Screening of Antibody Phage Libraries
VS Vanshika Singh
SG Sonal Garg
NR Nisha Raj
AL Asha Lukose
DJ Deepti Jamwal
RP Reshma Perween
SD Samridhi Dhyani
HP Hilal Ahamed Parray
CS Chandresh Sharma
RK Rajesh Kumar
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4450 Views: 3891
Reviewed by: Alba Blesa Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Biotechnology Progress May 2021
Abstract
Phage display is a proven and widely used technology for selecting specific antibodies against desired targets. However, an immense amount of effort is required to identify and screen the desired positive clones from large and diverse combinatorial libraries. On the other hand, the selection of positive binding clones from synthetic and semi-synthetic libraries has an inherent bias toward clones with randomly produced amber stop codons, making it more difficult to identify desirable binding antibodies. To overcome the screening of desired clones with amber codons, we present a step-by-step approach for effective phage library screening to isolate useful antibodies. The procedure calls for creating a simple new vector system for soluble production of phage ELISA positive binding clones with one or more amber stop codons in their single-chain antibody fragment (scFv) gene sequences, which is otherwise difficult in standard screening.
Graphical abstract:
Keywords: Phage display Amber codon scFv High-throughput screening Novel vector system
Background
Biomolecules based on monoclonal antibodies are commonly utilized for disease detection and prevention (Borghardt et al., 2018; Parray et al., 2020; Kumaret al., 2022). The single-chain variable fragment (scFv) antibody is one of the most often exploited biomolecules because it is the smallest antibody unit and has low immunogenicity and low-cost production properties (Kumar et al., 2019b; Parray et al., 2020). The scFv is the most commonly employed combinatorial therapeutic entity, either alone or in combination with other medications (Frenzel et al., 2016; Kumar et al., 2019b). An antibody in the form of scFv has variable heavy (VH) and light-chain (VL) sections that are linked by an efficient linker that can be effectively produced in E. coli (Kumar et al., 2012; Kumaret al., 2019a). The phage display technique is the most popular and successful way of generating scFv antibody fragments among all in vitro display methods. The size and functional diversity of the library used for screening enhances the efficiency of isolating scFv molecules from phage display antibody libraries. The most common issue with the soluble expression of scFv clones from phage libraries is the higher frequency of amber codons within the scFv gene, resulting in the premature expression of scFv clones in non-suppressor E. coli strains. This is more common in the case of synthetic and semi-synthetic libraries because these libraries are constructed randomly at few residues—particularly at NNN, NNK, NWG, NWC, and NSG codons—which increase the biased inclusion of amber codons (Marcus et al., 2006). Due to the frequent presence of amber codons within antibody gene sequences, the isolation of functional soluble scFv molecules is the most prevalent problem encountered during the screening of synthetic and semi-synthetic libraries, resulting in premature expression of scFv clones in non-suppressor E. coli strains (Barderas et al., 2006; Perween et al., 2021a). However, the inclusion of an amber stop codon does not affect the display of scFvs on the phage surface in E. coli suppressor strains, but it reduces the overall yield in terms of the total number of functional soluble scFv protein-expressing clones.
Directing individual scFv genes to be resynthesized or using Kunkel mutagenesis are two popular ways to solve this problem. Both of these processes become expensive and time demanding, considering when the purpose is to screen a substantial proportion of clones, especially in viral targets where a large amount of screening is essential to generate a small number of neutralizing clones (Reader et al., 2019).
In this Bio-protocol, we describe a novel strategy for rapid screening of scFvs containing amber codons and turning them into usable soluble scFvs that can be applied to several phage antibody libraries. We discuss a fast and reliable screening strategy that can be used to screen a large number of phage antibody libraries with amber stop codons (TAG) in the encoding series.
Materials and Reagents
All chemicals are of Analytical Reagent Molecular Biology/Tissue culture grade.
PRODUCT NAME CATALOGUE NUMBER COMPANY NAME
(3-(N-morpholino) propane sulphonic acid) MOPs M1254 Sigma-Aldrich
2× YT media G034-500G Himedia
Absolute ethanol 24102 Sigma-Aldrich
Acetic acid W200603-1KG-K Sigma-Aldrich
Acrylamide A8887-100G Sigma-Aldrich
Agarose MB080-100G Himedia
Alkaline Phosphatase Blue Membrane substrate solution
AB0300
Sigma-Aldrich
Ampicillin SD002 Himedia
Anti-rabbit HRP Code: 111-035-144 Jackson Immune Research
Beta-mercapto ethanol 21985023 ThermoFisher
Bis-Acrylamide A2792-100ml Sigma-Aldrich
Boric acid MB007 Himedia
Bovine Serum Albumin (BSA) A3059-10G Sigma-Aldrich
Bright-Glo Luciferase assay system E2610 Promega
Bromophenol Blue B0126-25G Sigma-Aldrich
Calcium chloride GRM710 Himedia
Cut smart buffer B6004S New England Biolabs
Cyclosporine RM8155 Himedia
DEAE-dextran MB145 Himedia
Diethanolamine RM8218 Himedia
Diethyl pyro carbonate (DEPC) D43060 RPI – Research Products International
Dimethyl sulphoxide (DMSO) 673439 Sigma-Aldrich
DpnI enzyme R0176S New England Biolabs
Dulbecco’s Modified Eagle Medium (DMEM) 11965118 GibcoTM
Ethylene diamine tetra acetic acid GRM678 Himedia
EXpi 293F cells 100044202 ThermoFisher
Ficoll 26873-85-8 Sigma-Aldrich
Gel extraction kit 28706X4 Qiagen
Gelatin G2500 Sigma-Aldrich
Glucose MB037 Himedia
Glycerol MB060 Himedia
Glycine MB013 Himedia
HisPurTM Ni-NTA Magnetic Beads 88832 Thermo ScientificTM
Histopaque 10771 Sigma-Aldrich
Hydrocortisone RM556 Himedia
Hydrogen chloride 18-603-211 ThermoFisher
Imidazole MB019-100G Himedia
Isopropyl β-D-thiogalactoside RM2578 Himedia
Kanamycin Sulphate MB105 Himedia
L-glutamine 25030081 GibcoTM
Ligase 15224017 InvitrogenTM
Ligase buffer 46300018 InvitrogenTM
LMB3 primer Custom DNA oligos Integrated DNA Technologies IDT
Luria Broth M1245 Himedia
Luria Broth Agar M1151-500G Himedia
Magnesium chloride MB237 Himedia
Magnesium sulphate GRM1281 Himedia
Methanol 322415-250ml Sigma-Aldrich
Mini prep kit 27106X4 Qiagen
Mono Sodium Phosphate GRM3964 Himedia
NcoI-HF® R3193S New England Biolabs
Ni NTA beads 88221 ThermoFisher
NotI-HF® R3189S New England Biolabs
Penicillin SD028 Himedia
PHEN primer Custom DNA oligos Integrated DNA Technologies IDT
Phosphate buffered saline TS1101-20L Himedia
Phytohemagglutinin (PHA) 10576015 GibcoTM
PierceTM Protein G Magnetic Beads 88848 Thermo ScientificTM
Polybrene (Hexadimethrine bromide) H9268 Sigma-Aldrich
Polyethylene glycol MB149-500G Himedia
Potassium Acetate W292001 Sigma-Aldrich
Potassium chloride P3911-25G Sigma-Aldrich
Potassium dihydrogen phosphate PO662-25G Sigma-Aldrich
RNase A EN0531 ThermoFisher
RPMI-1640 medium 11875093 GibcoTM
Skim milk GRM1254 Himedia
SnakeSkinTM Dialysis Tubing 88244 Thermo ScientificTM
Sodium Azide GRM1038 Himedia
Sodium bicarbonate GRM849 Himedia
Sodium carbonate GRM851 Himedia
Sodium chloride MB023-1KG Himedia
Sodium dodecyl-sulphate 0227-10G VWR Life science
Sodium hydroxide 72064 Sigma-Aldrich
Sodium phosphate dibasic Bio Reagent NIST2186II Sigma-Aldrich
Stop solution N600 Thermo Fisher Scientific
Streptomycin Sulphate CMS220 Himedia
Sucrose MB025 Himedia
TG1 Electrocompetent Cells 23227 Lucigen
TMB (Tetramethylbenzidine) Substrate solution N301 Thermo Fisher Scientific
Tris base TC072 Himedia
Tris Buffered Saline R017R.0000 ThermoFisher
Tris free base MB029-500G Himedia
Tris-HCl MB030 Himedia
Triton X100 MB031 Himedia
Trypan blue T8154 Sigma-Aldrich
Trypsin TC598 Himedia
Tween 20 MB067 Himedia
Goat affinity purified Antibody to human IgG Fc, alkaline phosphatase conjugated goat affinity purified antibody to IgG Fc, and purified human IgG whole molecule were purchased from Cappel, MP Bio, USA.
A human mAb 1418 against parvovirus B19 was gifted by Dr. Zolla Pazner, NYU SoM, USA
Plasticware
All plasticware used is disposable (glassware is not used in this work).
NAME CATALOGUE NUMBER COMPANY NAME
96 well flat bottom Immunol plate for ELISA CLS3370 Corning
96 well round bottom Immunol plate for ELISA CLS3367 Corning
96 well tissue culture plate CLS 3628 Corning
Disposable pipettes of 5 mL, 10 mL and 20 mL CLS4487 Corning
Microfuge tubes 1.5 mL CLS3620 Corning
PCR tubes of 0.2 mL PCR-02-A Axygen
Petri dishes 460062 Tarson
Pipette tips 0.5–10 μL AXYT300RS Corning
Pipette tips 1–200 μL CLS4860 Corning
T-25 cm3 tissue culture flask C6231 Corning
T-75 cm3 tissue culture flask C7231 Corning
BUFFERS
10× stock of gel loading dye (see Recipes)
2× Sample buffer (see Recipes)
Acrylamide:Bis (100 mL) (see Recipes)
Antibiotic concentration (see Recipes)
Buffer for Agarose Gel Electrophoresis (see Recipes)
Coating Buffer (see Recipes)
Composition of Reagents (see Recipes)
Counting of Expi293FTM Human Cells (see Recipes)
Destaining solution I (see Recipes)
Elution Buffer (1 L) (see Recipes)
Lower Gel Buffer [pH 8.8] 200 mL (see Recipes)
Lysis buffer (1 L) (see Recipes)
Phosphate buffered saline (see Recipes)
Purification of scFvs (see Recipes)
Tank Buffer 1× 2L (pH 8.3) (see Recipes)
Upper Gel Buffer [pH 6.8] 100 mL (see Recipes)
Wash Buffer (1 L) (see Recipes)
Wash Buffer (see Recipes)
Western Blotting solution (see Recipes)
Procedure
HELPER PHAGE PRODUCTION
A helper phage is necessary for transferring phagemid particles into E. coli. Phagemid particles contain (i) an antibiotic maker, (ii) antibody-G3P fusion protein, and (iii) phage origin of replication.
The phagemid libraries are amplified along with the antibody-G3P fusion protein and helper phage genes, which are required for infection, replication, assembly, and budding.
Take three Corning® 50 mL Falcon centrifuge tubes (FCTs) and label them A, B, and C.
Add 5 mL of 2× YT media to each FCT tube.
Take B and C as negative controls by adding ampicillin to one and kanamycin to the other.
Add 20 μL of TG1 E. coli cells to all three FCTs.
Incubate the FCTs at 37°C with shaking for overnight growth.
Subculture 20 μL of the previously inoculated TG1 cells in FCT A (Step A1) in 5 mL of fresh 2× YT media; incubate for 2–4 h at 37°C with shaking.
Then, add 40 μL of helper phage to the cultured TG1 cells.
Grow for 30 min at 37°C without shaking.
Grow for 30 min at 37°C with shaking.
Add this culture to 200 mL of fresh 2× YT media with kanamycin in a 50 μg/mL working concentration.
Allow to grow overnight at 30°C with shaking.
Remove the flask from the incubator, collect the culture in an autoclaved caesium bottle.
Centrifuge at 14,260 × g for 30 min at 4°C.
Pour the supernatant into another fresh caesium bottle and centrifuge at 14,260 × g and 4°C for 30 min.
Without disturbing the pellet, collect the supernatant in a glass bottle and add PEG/NaCl [20% (wt/vol) Polyethylene glycol 6000, 2.5 M NaCl], keeping the ratio of the supernatant and PEG/NaCl as 50:15.
Store in a cold room at 4°C for 4–5 h, or overnight for better results.
Spin the culture at 14,260 × g and 4°C for 1 h to allow the cells to settle down.
Without disturbing the pellet, discard the supernatant, and resuspend the pellet with 1× PBS, keeping it in 1.5 mL tubes.
Centrifuge the microtubes at 16,200 × g for 5 min. In case a pellet is formed, transfer the supernatant into fresh tubes and store at 4°C ( Figure 1 ).
Figure 1. Schematic representation of the steps involved in Helper Phage preparation.
GROWING TOMLINSON I + J AND MAKING SECONDARY STOCK
Take 100 mL of 2× YT media containing ampicillin and 1% (vol/vol) glucose. To this media, add 500 μL of the Tomlinson I + J phage library stock.
Incubate for 1–2 h at 37°C with shaking, until the O.D. at 600 nm is approximately 0.4.
Divide the 100 mL of culture media into two parts. First, use 50 mL to grow the library; then, use the remaining media to make secondary stocks of the library.
Growing the library (phage stocks):
Take 50 mL of the 100 mL of grown media and add 200 μL of helper phage.
Incubate for 30 min at 37°C without shaking.
Centrifuge at 1,200 × g for 10 min.
Carefully discard the supernatant without disturbing the pellet.
Dissolve the pellet in 100 mL of 2× YT media containing 100 μg/mL ampicillin, 50 μg/mL kanamycin, and 0.1% (wt/vol) glucose.
Incubate the resuspended pellet overnight at 30°C with shaking.
After overnight incubation, transfer the culture to a centrifuge bottle (caesium bottle) and centrifuge at 14,260 × g and 4°C for 30 min.
Transfer the supernatant to another caesium bottle and centrifuge again at 14,260 × g and 4°C for 30 min.
Carefully transfer the supernatant into another autoclaved glass bottle and discard the pellet. Add PEG/NaCl (20% Polyethylene glycol 6000, 2.5 M NaCl) to the supernatant collected (15 mL of PEG/NaCl to 50 mL supernatant).
Store this in a cold room at 4°C for 4–5 h, or overnight for better results.
Spin the culture at 14,260 × g and 4°C for 1 h to allow the cells to settle down.
Without disturbing the pellet, discard the supernatant and resuspend the pellet with 1× PBS; keep it in 1.5 mL tubes.
Centrifuge the microtubes at 16,200 × g for 10 min. In case a pellet is formed, transfer the supernatant into fresh tubes and store at 4°C for short term storage. Add 15% (vol/vol) glycerol for longer storage at -80°C ( Figure 2 ).
Making secondary stocks of phage library:
Grow the remaining 50 mL of media further for 2 h at 37°C with shaking.
Allow the cells to settle down by centrifuging the culture at 1,500 × g for 15 min.
Resuspend the pellet in 3 mL of 2× YT media containing 15% (vol/vol) glycerol.
Store at -80°C until further use ( Figure 2 ).
Figure 2. Schematic representation of the steps involved in library amplification for screening purposes and library secondary stock preparation.
BIO-PANNING
In this step, the target proteins are immobilized onto the surface of the microtiter plate. The first step is the addition of the rescued Tomlinson phage library. The second step involves binding, where the phage displaying scFvs, the highest affinity antibodies, bind the epitopes of the antigen, and those with low binding affinity are removed by washing. The antigen bound phage are eluted by enzymatic digestion using trypsin. The eluted phage are infected to TG1 followed by addition of helper phage for amplification. To accumulate phage displaying high-affinity antibody fragments, these steps were repeated three times with the amplified phage from the preceding round of panning, and each time, the number of washing cycles is increased.
ROUND 1
One day before the experiment, coat one row (say row C) of the ELISA plate, namely plate A, with the required antigen (100 μL per well), with a concentration of 5 μg. Coat the antigen with coating buffer.
Incubate plate A at 4°C overnight.
Next day, make 3% BSA in 5 mL of PBS and incubate for 10 min at 37°C. Then, coat another plate, i.e. , plate B; coat two rows (say rows C and D) and incubate the plate at 37°C for 1 h.
Plate C: coat one row (say row C) with a pinch of skim milk in 1 mL of autoclaved PBS + 700 μL of phage stock. Coat 100 μL per well.
Incubate plate C at room temperature for 30 min. Then, transfer the coating from row C to any other row, say row D. Incubate for 30 min more.
After 1 h of coating plate B, wash the plate once with autoclaved PBS (250 μL per well) and transfer the content of plate C onto row C of plate B.
Again, incubate plate B at room temperature for 30 min and then transfer the content of row C onto row D, followed by another 30 min incubation.
While washing plate B, simultaneously wash plate A, by using autoclaved PBS (250 μL per well) and then block with 3% (wt/vol) BSA (200 μL per well). Incubate at room temperature for 1 h.
Wash plate A three times with autoclaved PBS.
Then, transfer plate B content onto plate A; followed by incubation for 1 h at room temperature.
After incubation, wash plate A with PBST 10 times. Make 1 mL of PBS containing 50 μL of trypsin and add 95 μL of this solution to each well.
Keep the plate for 10 min at 37°C.
Then, collect all the trypsinized content into one aliquot. This will be the output of bio-panning round 1.
Use the output of bio-panning 1 to calculate the transducing unit (TU) ( Figure 3 ).
Figure 3. Schematic representation of the steps involved in the bio-panning process.
Preparation of the next round of bio-panning
Add 500 μL of bio-panning output into 5 mL of TG1 cell growth media.
Keep for 30 min at 37°C with shaking.
Centrifuge at 700 × g for 10 min.
Use 1 mL of supernatant to dissolve the pellet formed during centrifugation and throw the rest of the supernatant out.
Spread this on a bioassay dish containing 2× YT agar with ampicillin.
Allow the bacteria to grow at 37°C overnight.
Next day, add 3–5 mL of 2× YT media containing 15% glycerol onto the bioassay dish and scrape all the colonies grown overnight. Collect them in a fresh tube.
Use 100 μL of the scraped colonies and store the rest.
Add 100 μL of scraped colonies to 50 mL of 2× YT media containing ampicillin (100 µg/mL) and 1% (vol/vol) glucose.
Allow it to grow for 2 h at 37°C with shaking.
Take 10 mL of the above culture and add a 40 μL of helper phage. Incubate for 30 min at 37°C without shaking.
Centrifuge the culture at 700 × g for 15 min and discard the supernatant without disturbing the pellet.
Dissolve the pellet in 50 mL of 2× YT media containing 100 µg/mL ampicillin, 50 µg/mL kanamycin, and 0.1% glucose. Incubate overnight at 30°C with shaking.
Centrifuge the overnight grown culture at 14,260 × g and 4°C for 30 min, collect the supernatant in a fresh cesium bottle and centrifuge again at 14,260 × g and 4°C for 30 min.
Carefully transfer the supernatant into an autoclaved glass bottle and discard the pellet. Add PEG/NaCl (20% Polyethylene glycol 6000, 2.5 M NaCl) to the supernatant collected (15 mL of PEG/NaCl to 50 mL of supernatant).
Store this in a cold room at 4°C for 4–5 h, or overnight for better results.
Spin the culture at 14,260 × g for 1 h at 4°C to allow the cells to settle down.
Without disturbing the pellet, discard the supernatant and resuspend the pellet with 1× PBS, keeping it in 1.5 mL tubes.
Centrifuge the microtubes at 16,200 × g for 10 min. In case a pellet is formed, transfer the supernatant into fresh tubes and store it at 4°C.
The collected phage is to be used as an input in the next round of bio-panning by coating this on plate C instead of phage stock.
Note: With each bio-panning round, decrease the antigen coating concentration (for example, round 1 with 5 μg/μL, round 2 with 3 μg/μL, and round 3 with 1.5 μg/μL) and calculate the TU of every input and output used during phage selection.
SCREENING BY PHAGE ELISA
Day 0: One day before performing ELISA
For the phage selection process, grow the colonies of the last bio-panning round output. Inoculate the colonies formed during the last round of bio-panning output; each inoculation is done in 5 mL of 2× YT media containing 100 μg/mL ampicillin.
Incubate for 30 min at 37°C without shaking. Wait until OD 600 of the culture reaches 0.4–0.6.
Back up set: At this step, take 200 μL of the culture of each clone and add 200 μL of autoclaved 50% (vol/vol) glycerol solution to make a stock and store at -80°C for future experiments
Add 20 μL of helper phage.
Incubate again for 30 min at 37°C with shaking.
Add 50 μg/mL of kanamycin and incubate overnight at 30°C with shaking at 140–160 × g .
Coat the 96 well assay plate with the required antigen with a concentration of 2 μg/μL. Do BSA coating as negative control and keep the plate overnight at 4°C ( Figure 4 ).
Figure 4. Schematic representation of the steps involved in the Phage ELISA screening process.
ELISA
Next day, take the antigen-coated plate out of 4°C and wash once with PBS.
Block the plate with 200 μL of 5% skim milk in PBS per well.
Incubate the plate for 1 h at room temperature.
Take all the colony inoculation out of the incubator and centrifuge the tubes at 3,900 × g for 20 min.
After 1 h blocking, wash the ELISA plate three times with PBS (250 μL).
Note: Blocking can be extended to 90 min if required, based on the timing of the parallel steps
After 1 h of incubation, wash the plate three times with PBS.
Then add 100 μL of primary antibody per well, i.e. , 50 μL of supernatant from all the centrifuged tubes and 50 μL of skim milk (diluted in 1:1).
Incubate for 1 h at room temperature.
Wash the plate with 250 μL of 0.1% PBST four times.
Add 100 μL of secondary antibody per well (1:2,000). Follow with a 1 h incubation at room temperature in the dark.
Wash the plate with 250 μL of 0.1% PBST six times.
Add 100 μL of the substrate (TMB) to each well.
Allow the reaction to take place for 15–20 min in the dark.
To stop the reaction, add 50 μL of stop solution (2 NH2SO4 ) per well, and read the plate at 450 nm on a multimode ELISA reader.
ISOLATION OF PLASMID DNA
Identify the positive binding clones in Phage ELISA (at least four times more than the negative control).
Take two FCTs and label them A and B; add 5 mL of 2× YT media to each FCT.
Take B and add ampicillin (100 µg/mL) and C as negative control by adding kanamycin (50 µg/mL) in it.
In FCTs A and B, inoculate from a glycerol stock that is preserved at -80°C.
Incubate the FCT at 37°C with shaking for overnight growth.
Next morning, check tubes A and B. Tube A culture should be turbid, and in tube B, there should be no growth.
Spin down by centrifuging the culture at 2,820 × g for 15 min.
For plasmid isolation, use the Qiagen Miniprep kit following the manufacturer’s instructions.
Check the quality and concentration of the isolated plasmid DNA using a nanodrop spectrophotometer. The 260/280 ratio of the isolated DNA should be 1.8.
Prepare a 0.8% Agarose gel and check the quality of the isolated plasmid DNA on the gel.
Make a 10 μL aliquot of the plasmid DNA, and use LMB3 and PHEN sequencing primers for sequencing the scFv insert sequence.
Soluble ELISA
Perform ELISA as described in the phage ELISA section.
Add 100 μL of purified scFv and incubate for 1 h at room temperature.
Wash the plate three times with 0.1% PBST.
Use a 1:1,000 dilution of primary antibody (anti-His tag) in 2% MPBS and incubate at room temperature.
Wash three times with 0.1% PBST.
Use 1:2,000 diluted anti-rabbit-HRP conjugated secondary antibody in 2% MPBS and incubate at room temperature, followed by washing, as mentioned above.
Add 100 µL of TMB substrate and allow the color to develop. Once the color appears, add 8 NH2SO4 to stop the reaction.
Read the plate at 450 nm in ELISA reader.
DILUTION AND PLATING FOR TRANSDUCING UNIT (TU) CALCULATION
Figure 5. Representative image showing dilution preparation strategy for helper phage/library TU calculation.
The plating of each dilution is done on a different plate containing ampicillin.
Pour the mixture of phage and bacteria on a plate and spread slowly using a spreader. Label each plate with the dilution that it contains.
Incubate the plates at 37°C for overnight growth. Next day, count the colonies for TU calculation ( Figure 5 ).
CALCULATE TRANSDUCING UNIT
TU = (No. of colony × 1000)/(10 × dilution). For a 10-8 dilution plate, we got nine colonies;
Then the TU is calculated as: (9 × 1000)/(10 × 10-8 ) = 9 × 1010
PREPARATION OF COMPETENT CELLS
Streak E. coli TG1 cells on an LB plate and allow cells to grow at 37°C overnight.
Inoculate a single colony in 5 mL of LB media and grow overnight at 37°C.
Subculture in 100 mL of LB by inoculating 1 mL of an overnight culture of E. coli , and grow at 37°C on a shaker until the O.D. at 600 nm reaches approximately 0.6.
Cool culture on ice immediately, and harvest cells by centrifugation at 4,200 × g and 4°C for 5 min.
Remove the supernatant carefully; remove any traces of supernatant by inverting the centrifuge tube on paper towels.
Resuspend the bacterial pellet in 10 mL of ice-cold 0.1 M CaCl2 (autoclaved) and incubate on ice for 30 min.
Recover cells by centrifugation as described above, resuspended in 5 mL of 0.1 M CaCl2 , and aliquot 200 μL of cells in microcentrifuge tubes.
VECTOR DESIGN
A representative strategy for vector design is shown in Figure 6 .
A set of designed PCR primers to replace TAG amber codon into TAA in the junction of the scFv-pIII junction is used for vector construction.
Forward Primer: 5’CACATCATCATCACCATCACGGGTAATAAGAACAAAAACTCATCTC3’
Reverse primer: 5’GAGATGAGTTTTTGTTCTTATTACCCGTGATGGTGATGATGATGTG3’.
PCR Reaction setup:
Steps Initial Denaturation Cycling 16× Extension Hold
Temperature 95°C 95°C 52°C 72°C 72°C 10°C
Time 2 min 30 s 50 s 4 min 5 min ∞
The PCR product is digested by Dpn 1 enzyme
PCR product 20 µL
Dpn 1 enzyme 1 µL
Cut smart buffer 2.5 µL
Incubate the reaction mixture at 37°C for 2 h. Tap the tube in between.
Thaw two vials of competent cells from the -80°C freezer on ice for 5–10 min. DO NOT tap at this step.
Add 5 µL of Dpn 1 digested product into one tube, and keep the other tube as blank or negative control. Incubate the cells on ice for 30 min.
After 30 min, place both the tubes in the floater to heat shock for 60 s (at this step, set water bath at 42°C).
Immediately place the tubes in ice for 5 min; at this step, pre-warm the media at 37°C.
Add 900 µL of pre-warmed 2× YT medium to the cells in the tube.
Incubate the tubes in the shaker for 60 min at 220 rpm to grow the cells.
Take out the tubes from the shaker, aspirate 100 µL of cell suspension, and plate/spread on LB-Agar-ampicillin plates. Incubate plates in a 37°C incubator for 16 h or overnight.
Next morning, take out the plates, count the colonies, and store at 4°C until further use.
Add 5 mL of 2× YT supplemented with a standard concentration of ampicillin to five tubes. Pick a single colony for inoculation and culture of the colony obtained on the plates; incubate at 37°C with 220 rpm shaking. Incubate also one tube of media as a control.
Next morning, isolate the plasmid DNA from all four tubes using the Qiagen plasmid isolation kit as per the manufacturer’s instructions.
Check the quality of the isolated plasmid using a spectrophotometer by observing the 260/280 DNA ratio.
Aliquot the DNA and send these samples for sequencing using vector-specific primers.
Analyze the DNA sequence data for point mutations and mark the positive clones for further use. Discard the negative clones.
Digestion of designed vector
Reaction mixture for restriction digestion:
Component Volume (μL)
Plasmid DNA (250 ng·μL-1) 10 μL
10× CutSmart Buffer (NEB) 5 μL
Nco I-HF (NEB) 2 μL
Not I-HF (NEB) 2 μL
Nuclease free water 31 μL
Incubate the reaction at 37°C for 2 h.
After 2 h, add 10 μL of 5× gel loading dye and run the sample on a 0.8% Agarose gel, at 100 V for approximately 60 min.
Cut and excise the digested vector DNA from the agarose gel using a sharp surgical blade. Place the excised fragment in a 1.5 mL Eppendorf tube. Purify the digested vector from the excised DNA using the Qiagen Gel extraction kit as per the manufacturer’s protocol.
Evaluate the quality of the purified digested vector DNA using the spectrophotometer by calculating the 260/280 ratio. This purified vector is used for future cloning reactions.
Digestion of scFv clones
The phage ELISA binding positive clone that showed no binding in soluble ELISA was further used to isolate plasmid DNA from single colonies, as described in this section.
The digestion reaction is set up as described below:
Component Volume ( μL)
Plasmid DNA (250 ng·μL-1 ) 10 μL
10× CutSmart Buffer (NEB) 5 μL
Nco I-HF (NEB) 2 μL
Not I-HF (NEB) 2 μL
Nuclease free water 31 μL
After 2 h add 10 μL of 5× gel loading dye and run the sample on a 1% Agarose gel, at 100 V for approximately 40–60 min.
Two bands should be observed in the agarose gel, one band size of approximately 4 kb corresponding to vector DNA and another of 800 bp corresponding to scFv DNA.
Excise the agarose gel slice containing the relevant DNA Fragments (scFv insert 800 bp) and remove extra agarose to minimize the gel slice.
Transfer the gel slice into a microcentrifuge tube and purify using the Qiagen gel extraction kit as per the manufacturer's instructions.
Use this purified scFv DNA for cloning into a newly designed vector.
Cloning of scFv DNA into newly designed vector
Component Volume ( μL)
scFv DNA insert 10 μL
Designed vector 5 μL
10× Ligase buffer 2 μL
Ligase 2 μL
Nuclease free water 31 μL
Incubate the ligation reaction mixture at room temperature for 4–6 h. Alternatively, this can be kept at room temperature overnight.
After 4–6 h incubation, thaw the TG1 competent cells on the ice for 5 min.
Add 5 μL of ligation mixture to one tube and keep the second tube without insert and/or ligation mixture as a negative control.
Heat-shock the cells for 60 s and immediately keep on ice for 5 min.
Add 900 μL of 2× YT medium and incubate the tubes in a shaker incubator at 37°C for 1 h.
After 1 h, centrifuge the tube at 2,400 × g for 5 min. Decant the supernatant and resuspend the pellet in reaming leftover media. Plate this on pre-warmed 2× YT-Agar plates supplemented with ampicillin, or optionally you can use LB-Agar plates with ampicillin.
Incubate the plates in a 37°C incubator overnight or 12–16 h.
Next morning, count the colonies on the reaction plate. NO COLONIES should be there in the control plate; otherwise, repeat the experiment with all new and freshly prepared reagents.
Inoculate the single colony in 5 mL of 2× YT containing a standard concentration of ampicillin in two 50 mL FCTs. Label one tube as reaction and the other as blank, and incubate both tubes in a shaker incubator (200 to 220 rpm) at 37°C overnight.
Transfer a small inoculum (approximately 4 mL) from the overnight primary culture to a 2 L flask (400 mL media) 2× TY containing 100 μg/mL ampicillin and 0.1% glucose. Grow shaking (250 rpm) at 37°C until the OD600 is approximately 0.9 (approximately 3 to 3.5 h).
Once the OD of the culture reaches 0.9, add isopropyl β-D-thiogalactoside at a final concentration of 1 mM IPTG. Continue shaking (250 rpm) at 30°C overnight.
Harvest the cells by centrifugation at 4,000 × g for 15 min. Store the cell pellet at -20°C if desired or process immediately.
Figure 6. Schematic representation of the modified vector design strategy. Diagram depicting a modified method for soluble expression of scFv genes with amber stop codons. The amber stop codon (TAG) between the scFv-pIII gene in the original vector is altered to TAA, which prohibits the creation of scFv-pIII fusion proteins. The scFv genes are cloned directly into the modified vector using the same restriction site Nco1/Not1 that is used to clone the scFv gene into the original vector (Perween et al. , 2021a).
Resuspension of cell pellet and cell extract preparation
Adjust pH to 8.0 using NaOH.
Resuspend the pellet in 30 mM Tris-HCl, 20% (wt/vol) sucrose, pH 8.0, at 80 mL/gram of wet weight. Incubate on ice and add 500 mM EDTA dropwise to a final concentration of 1 mM; then incubate the cells on ice for 20 min with gentle agitation.
Clarify the cell suspension by centrifuging at 8,000 × g and 4°C for 20 min.
Collect the supernatant and resuspend the cells in the same volume of ice-cold 5 mM MgSO4 and incubate on ice for 20 min with gentle agitation.
Centrifuge the cells at 8,000 × g and 4°C for 20 min. Collect the supernatant (supernatant is osmotic shock fluid containing periplasmic proteins) and dialyze extensively against lysis buffer.
Filter the dialyzed supernatant through a 0.2 μm filter before continuing with the purification. Equilibrate the resin with lysis buffer (50 mM NaH2PO4 , 300 mM NaCl, 10 mM Imidazole, and pH = 8.0) prior the use of the Ni++ ions.
Purification OfscFvs
For purification, use Ni-NTA beads; add 5 mL of 50% slurry of Ni-NTA-Agarose resin in a purification column and allow the beads to settle down.
Wash the beads using MilliQ (MQ) water; add 10 column volume (CV) of MQ.
Use 10 CV of binding buffer (20 mM Tris; pH = 7.2, 500 mM NaCl and 10 mM Imidazole) to equilibrate the column. Thus, the same pH and buffer composition as that of the Ni++ ion resin ensuring that the sample binds properly
Add the filtered supernatant into the column and allow it to pass through gravitational force.
After the supernatant has been passed, wash the column to remove any impurity. Add 20–30 CV of washing buffer (20 mM Tris; pH = 7.2, 500 mM NaCl, and 25 mM Imidazole).
Elute the bound protein from beads, and use 5–6 CV of elution buffer (20 mM Tris pH = 7.2, 500 mM NaCl, and 500 mM Imidazole). Analyze the protein quality in terms of purity on a 15% Tri-glycine SDS-PAGE.
Dialyze the protein using activated dialysis tubing, clip both the ends of the tube tightly, and put it in a beaker containing cold PBS. With the help of a magnetic stirrer, allow it to spin overnight at 4°C in a cold room.
Mount the Superdex75 Increase column in AKTA FPLC system. Wash the pump thoroughly with PBS.
Use 2 CV of PBS to equilibrate the column; load approximately 500 μL of the purified concentrated protein through the loop with 0.5 mL of fraction volume.
Collect the different factions and analyze through SDS PAGE. Store the protein at -80°C in aliquots for further use. Mix 30 µL of sample with 5× SDS gel loading dye (6 µL). Heat the sample for 10 min at 100°C before loading.
Recipes
Lysis buffer (1 L)
50 mM NaH2PO4 (6.90 g of NaH2PO4·H2O; MW 137.99 g mol-1)
300 mM NaCl (17.54 g of NaCl; MW 58.44 g mol-1)
10 mM Imidazole (0.68 g of Imidazole; MW 68.08 g mol-1)
Adjust pH to 8.0 using NaOH.
Wash Buffer (1 L)
50 mM NaH2PO4 (6.90 g of NaH2PO4·H2O; MW 137.99 g mol-1)
300 mM NaCl (17.54 g of NaCl; MW 58.44 g mol-1)
30 mM Imidazole (2.04 g of Imidazole; MW 68.08 g mol-1)
Adjust pH to 8.0 using NaOH.
Elution Buffer (1 L)
50 mM NaH2PO4 (6.90 g of NaH2PO4·H2O; MW 137.99 g mol -1)
300 mM NaCl (17.54 g of NaCl; MW 58.44 g mol-1)
300 mM Imidazole (20.4 g of Imidazole; MW 68.08 g mol -1)
Buffer for Agarose Gel Electrophoresis
TBE (Tris Boric acid EDTA) Buffer, pH = 8.0
For 10× TBE Buffer, dissolve 108 g Tris base, 55 g Boric acid, and 7.4 g of EDTA in 750 mL of water. Adjust the pH of the solution to 8.0 and make the final volume up to one liter. 1× TBE buffer is used as the working solution.
Wash Buffer
PBS-Tween-20, pH = 7.4
200 mL of 10× PBS
1 mL of Tween 20
Adjust volume to 2 L with MQ water
Coating Buffer
Carbonate Buffer, pH = 9.6
1.59 g Na2CO3
2.93 g NaHCO3
0.2 g NaN3
Adjust volume to 1 L with MQ water
Counting of Expi293FTM Human Cells.
Aspirate 0.1 mL of cell suspension from the single cell suspension and stain with 0.1 mL of trypan blue (0.4%).
Count both Dead and live cells for percentage viability calculations.
Calculations:
Cell counting = No. of viable cells × 2 × 104 Cells per mL
10× stock of gel loading dye (10 mL):
Weigh 25 mg of bromophenol blue and dissolve in 7 mL of ddH2O in a 30 mL screwcap tube.
Add 2.5 g of Ficoll and dissolve it (keep in shaker overnight to allow it to dissolve completely).
Measure the volume using a pipette and make up to 10 mL using sterile ddH2O. Label and store at 4°C.
The final concentration would be 0.25%.
Bromophenol blue and 25% Ficoll.
Antibiotic concentration
Stock concentration= 100 mg/mL
Working concentration= 100 μg/mL
Therefore, for 2 mL
N1V1=N2V2
X*100000 = 200*100
X = 200 μL
Phosphate buffered saline [pH 7.2]
NaCl = 8.0 g
KCl = 0.2 g
Na2HPO4 = 1.15 g
KH2PO4 = 0.2 g
All the components were dissolved in 700 mL of distilled water, and the pH was checked to be at 7.2 and made up to 1,000 mL.
Acrylamide:Bis (100 mL, 30% stock)
Acrylamide = 29.2 g
Bis acrylamide = 0.8 g
ddH2O = 7 mL
Acrylamide and Bis acrylamide were weighed and dissolved in 70 mL of water, and the volume was made up to 100 mL. The solution was filtered through Whatman No.2 paper and stored at 4°C in an amber bottle.
Upper Gel Buffer [pH 6.8] 100 mL
This is nothing but the stacking gel buffer, i.e., 0.5 Molar Tris-HCl (4×). 6.6 g of Tris base was dissolved in 70 mL of ddH2O, and pH was checked and adjusted to 6.8 using 5 N HCl. The volume was made up to 100 mL and stored at 4°C.
Lower Gel Buffer [pH 8.8] 200 mL
Separating gel buffer (1.5 M Tris-HCl (4×))
36.3 g of Tris was dissolved in 125 mL of ddH2O. pH was adjusted to 8.8 using 5 N HCl. Volume was made up to 200 mL and autoclaved. The solution was stored at 4°C.
Tank Buffer 1× (pH 8.3) 2 L
Tris base = 6.0 g Final conc. 0.025 M
Glycine = 28.8 g Final conc. 0.192 M
SDS = 2 g Final conc. 0.1 M
ddH2O = 1,750 mL
pH was checked to be approximately 8.3 and volume was made up to 2 L.
Destaining solution I
Methanol = 250 mL (50%)
Acetic acid = 35 mL (7%)
ddH2O= 215 mL
2× Sample buffer (5 mL)
Tris-HCl (pH 6.8) = 1.25 mL (0.12 M)
SDS = 0.2 g (4%)
BME = 500 µL (10%)
Glycerol = 1 mL (20%)
Bromophenol blue (0.15%) = 500 µL (0.015%)
ddH2O = 1.75 mL
Total = 5 mL
This was dissolved into aliquots and frozen in -20°C [0.15% Bromophenol Blue is prepared by dissolving 15 mg in 0.2 mL methanol and then adding 9.8 mL of water].
Western Blotting solution Preparation
Transfer Buffer
Tris = 0.6 g (0.025 M)
Glycine = 2.88 g (0.192 M)
Methanol = 40 mL (20%)
SDS = 60 mg (0.03%)
Volume was made upto 160 mL and autoclaved. To this, 40 mL of methanol was added and stored at 4°C.
TBS (Tris Buffer Saline) (400 mL)
Tris = 4.84 g (0.1 M)
NaCl = 3.6 g (0.9%)
Components were dissolved, pH was adjusted to 7.5 with HCl, and volume was made up to 400 mL.
TTBS (250 mL)
TBS = 250 mL
Tween 20 = 250 µL
Blocking solution (30 mL)
TTBS = 12 mL
5% Gelatin = 18 mL (3%)
Composition of Reagents:
Buffer P1 [Resuspension buffer]
50 mM Tris-HCl (pH 8)
10 mM EDTA
100 µL/mL RNase A
Buffer P2 [Lysis buffer]
200 mM NaOH
1% SDS (w/v)
Buffer P3 [Neutralization buffer]
3 mM potassium acetate (pH 5.5)
Buffer QBT [Equilibrium buffer]
750 mM NaCl
50 mM Mops (pH 7)
15% isopropanol (v/v)
0.15% Triton X-100 (v/v)
Buffer QC [ Wash buffer]
1 mM NaCl
50 mM Mops (pH 7)
15% isopropanol (v/v)
Acknowledgments
We thank the Medical Research Council of the United Kingdom for allowing us to use the Tomlinson libraries. We thank Prof. S Sinha, department of Biochemistry, AIIMS, New Delhi for his critical inputs during screening of the libraries. information—This work was supported by the Department of Biotechnology and by a Translational Health Science & Technology Institute core grant.
Competing interests
There are no conflicts of interest or competing interests.
References
Barderas, R., Shochat, S., Martinez-Torrecuadrada, J., Altschuh, D., Meloen, R. and Ignacio Casal, J. (2006). A fast mutagenesis procedure to recover soluble and functional scFvs containing amber stop codons from synthetic and semisynthetic antibody libraries. J Immunol Methods 312(1-2): 182-189.
Borghardt, J. M., Kloft, C. and Sharma, A. (2018). Inhaled Therapy in Respiratory Disease: The Complex Interplay of Pulmonary Kinetic Processes. Can Respir J 2018: 2732017.
Frenzel, A., Schirrmann, T. and Hust, M. (2016). Phage display-derived human antibodies in clinical development and therapy. MAbs 8(7): 1177-1194.
Kumar, R., Andrabi, R., Tiwari, A., Prakash, S. S., Wig, N., Dutta, D., Sankhyan, A., Khan, L., Sinha, S. and Luthra, K. (2012). A novel strategy for efficient production of anti-V3 human scFvs against HIV-1 clade C. BMC Biotechnol 12: 87.
Kumar, R., Kumari, R., Khan, L., Sankhyan, A., Parray, H. A., Tiwari, A., Wig, N., Sinha, S. and Luthra, K. (2019a). Isolation and Characterization of Cross-Neutralizing Human Anti-V3 Single-Chain Variable Fragments (scFvs) Against HIV-1 from an Antigen Preselected Phage Library. Appl Biochem Biotechnol 187(3): 1011-1027.
Kumar, R., Parray, H., Narayan, N., Garg, S., Rizvi, Z. A., Shrivastava, T., Kushwaha, S., Singh, J., Murugavelu, P., Anantharaj, A., et al. (2022). A broadly neutralising monoclonal antibody overcomes the mutational landscape of emerging SARS-CoV2 variant of concerns. Research Square. DOI: 10.21203/rs.3.rs-1431974/v1.
Kumar, R., Parray, H. A., Shrivastava, T., Sinha, S. and Luthra, K. (2019b). Phage display antibody libraries: A robust approach for generation of recombinant human monoclonal antibodies. Int J Biol Macromol 135: 907-918.
Marcus, W. D., Lindsay, S. M. and Sierks, M. R. (2006). Identification and repair of positive binding antibodies containing randomly generated amber codons from synthetic phage display libraries. Biotechnol Prog 22(3): 919-922.
Parray, H. A., Shukla, S., Samal, S., Shrivastava, T., Ahmed, S., Sharma, C. and Kumar, R. (2020). Hybridoma technology a versatile method for isolation of monoclonal antibodies, its applicability across species, limitations, advancement and future perspectives. Int Immunopharmacol 85: 106639.
Perween, R., Ahmed, S., Shrivastava, T., Parray, H. A., Singh, B., Pindari, K. S., Sharma, C., Shukla, S., Sinha, S., Panchal, A., K. et al. (2021a). A rapid novel strategy for screening of antibody phage libraries for production, purification, and functional characterization of amber stop codons containing single-chain antibody fragments. Biotechnol Prog 37(3): e3136.
Reader, R. H., Workman, R. G., Maddison, B. C. and Gough, K. C. (2019). Advances in the Production and Batch Reformatting of Phage Antibody Libraries. Mol Biotechnol 61(11): 801-815.
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Protocol for Initiating and Monitoring Bumble Bee Microcolonies with Bombus impatiens (Hymenoptera: Apidae)
DL David M. Lehmann
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4451 Views: 2003
Reviewed by: Alba BlesaKai YuanAlexandros Alexandratos
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Original Research Article:
The authors used this protocol in PLOS ONE Oct 2020
Abstract
Populations of some bumble bee species are in decline, prompting the need to better understand bumble bee biology and for assessing the effects of environmental stressors on these important pollinators. Microcolonies have been successfully used for investigating a range of endpoints, including behavior, gut microbiome, nutrition, development, pathogens, and the effects of pesticide exposure on bumble bee health. Here, we present a step-by-step protocol for initiating, maintaining, and monitoring microcolonies with Bombus impatiens. This protocol has been successfully used in two pesticide exposure-effects studies and can be easily expanded to investigate other aspects of bumble bee biology.
Disclaimer: The views expressed in this article are those of the author(s) and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
Keywords: Bumble bee Bombus Microcolony Pollinators Pesticides
Background
Bumble bees are valuable pollinators in agricultural and natural settings (Kleijn et al., 2015). Disconcertingly, populations of some bumble bee species are in serious decline (Cameron et al., 2011). Many factors are believed to contribute to the reported population declines, including poor nutrition, parasites, pathogens, and pesticides (Brown and Paxton, 2009; Goulson, 2005, 2013, 2015; Meeus et al., 2011; Wood et al., 2019). Recognizing their importance and the number and complexity of factors affecting their populations, there is a need to better understand bumble bee biology and the effects of environmental stressors on bumble bees.
Microcolonies are formed when a small group of bumble bee workers is isolated in a queenless environment. Under these conditions, the workers self-organize to build nest structures and lay unfertilized eggs that produce drones (Free, 1955). The model is versatile, offering the ability to investigate a range of endpoints, including behavior, the gut microbiome, nutrition, development, pathogens, and pesticide exposure (reviewed in Klinger et al., 2019).
Currently, there are no detailed protocols for initiating and monitoring microcolonies published for any bumble bee species, only condensed protocols in the methods sections of research publications (Gradish et al., 2012, 2013; Smagghe et al., 2007). Here, we detail a step-by-step protocol for initiating and monitoring bumble bee microcolonies with the common eastern bumble bee (Bombus impatiens Creson) (Hymenoptera: Apidae). We also provide detailed instructions for preparing microcolony food provisions. An overview of the procedures for initiating and monitoring microcolonies can be found in Figure 1. The protocols presented here were originally described in two peer-reviewed publications (Camp et al., 2020a, 2020c) and a subsequent publication comparing these two studies (Weitekamp et al., 2022). While these protocols were designed for assessing the effects of pesticide exposure on bumble bees, they can be easily expanded to investigate other aspects of bumble bee biology, including behavior, nutrition, development, pathogens, and gut microbiome (reviewed in Klinger et al., 2019).
Figure 1. Overview of procedures for initiating and monitoring microcolonies. (A and B) Prepare syrup and pollen stocks for provisioning the microcolonies. Although syrup can be prepared in advance and stored at 4°C, pollen patties should be made fresh on the day of use. Transfer pollen to dishes and collect the weight. (C) Use only age-matched, newly emerged B. impatiens workers when using this protocol. To facilitate experimental manipulation, chill workers on ice. Distribute five bees to each microcolony chamber. Provision microcolony chambers with a ~3 g pollen patty for nest building and a syringe feeder filled with 50/50 inverted syrup. Supplement the nest with ~2 g of pollen paste on day 5. (D) Provide microcolonies with pollen patties for feeding (starting on Day 7) and 50/50 inverted syrup every Monday, Wednesday, and Friday for the duration of the experiment (recommend no more than 49 days). Collect the weight of the old syringe feeders and pollen dishes to use when calculating food consumption. (E) Investigators are encouraged to collect data on worker mortality and drone production (i.e., timing to emergence of 1st drone, number of drones emerged, and drone weight). Syrup and pollen consumption values should be corrected for evaporation and worker mortality. The black vertical arrow on the righthand side indicates the order of operations for initiating and monitoring microcolonies.
Part I: Protocol for microcolony food preparation
Materials and Reagents
Fresh or fresh-frozen honey bee-collected corbicular pollen (see Protocol for Microcolony Food Preparation Notes #1) either sourced from investigator-maintained honey bee colonies or a commercial vendor (Swarmbustin’ Honey, catalog number: BP-DKLB).
Sorbic acid (Amresco, catalog number: 0667-500G)
Citric acid anhydrous (Fisher, catalog number: A940-500)
Pure cane sugar (e.g., Domino Sugar)
Distilled water (Gibco, catalog number: 15230)
Potassium Sorbate Solution (see Recipes)
Equipment
Laminar flow hood
4°C laboratory refrigerator (Thermo Scientific, catalog number: TSV18CPSA)
-20°C laboratory freezer (Thermo Scientific, catalog number: TSX3020FARP)
Basic coffee grinder or (ideally) commercial blender (Waring, catalog number: 7010S)
Vacuum food sealer (FoodSaver, catalog number: FM2100)
Freezer storage bags for vacuum food sealer (FoodSaver, catalog number: FSFSBF0226NP)
Analytical top loading scale/balance (Ohaus, catalog number: AX2202/E)
Analytical balance standards: 200 mg, 500 mg, 1 g, 2 g, 10 g, 20 g, 30 g, 100 g, 200 g, 300 g, 500 g, and 1 kg
Hand-operated, electronic pipet for large volumes (Drummond Pipet-Aid, catalog number: 4-000-101)
Hot plate with stir function (2) (Cimarec, catalog number: SP195025)
pH meter (Orion Star, catalog number: STARA2110)
pH meter calibration standards: pH 4.0 and pH 7.0 (VWR, catalog number: E452-500ML and E459-500ML)
General supplies
N95 disposable respirator (VWR, catalog number: 89201-508)
Mortar and pestle (VWR, catalog number: 470019-978)
Sterile bottletop 0.45 µm filters (VWR, catalog number: 10042-462)
60 mL Luer slip syringe with tips cut off (Exel International, catalog number: ES60)
25 mL graduated glass pipet (VWR, catalog number: 76003-570)
Aluminum foil
Disposable paper mats for covering working surfaces (Versi-Dry Lab Table Soakers, catalog number: 62080-00)
2 L Pyrex bottle (Corning, catalog number: 1395-2L)
Magnetic stir bars (Komet, catalog number: 50087909)
35 mm × 10 mm disposable Petri dish lids (Falcon, catalog number: 351008)
43 mm aluminum weigh dishes (QORPAK, catalog number: MET-03105)
1 L Pyrex beakers (2) (Corning, catalog number: 1000-1L)
Procedure
50/50 Inverted Syrup: 1 L Bottles (1.5 L produced)
For easier clean-up, cover the hot plate with aluminum foil prior to use.
Combine 1,000 mL distilled water with 850 g pure cane sugar and stir on a hot plate until all sugar granules are dissolved.
Add 0.85 g citric acid anhydrous and continue stirring while heating to a rolling boil.
Cover beaker with aluminum foil and boil for 20 min (see Figure 2).
Figure 2. Syrup at rolling boil and treated with citric acid.
Allow to cool on a room temperature stir plate, while covered and stirring with a stir bar.
Once cooled, add 7.5 mL (5 mL per 1 L produced) Potassium Sorbate Solution (see Recipes below).
Record the pH and label the container appropriately (see Protocol for Microcolony Food Preparation Notes #2).
Parafilm bottle cap and store 50/50 inverted syrup at 4°C for up to 14 days once opened (30 days unopened).
Preparing Pollen (see Protocol for Microcolony Food Preparation Notes #3 and 4)
Grind frozen pollen to a fine powder with a coffee grinder or (ideally) commercial blender (Figure 3A-C).
Figure 3. Pollen consistency. (A) Frozen fresh collected honey bee corbicular pollen. (B) Honey bee orbicular pollen in a blender cup. (C) Honey bee corbicular pollen ground to a fine powder for making patties and paste.
Calibrate the analytical balance prior to use.
Store ground pollen in vacuum seal freezer bags at a weight of 500 g per bag.
Store ground pollen at -20°C until ready to use.
Preparing Pollen Paste for Nest Initiation and Routine Feeding
Remove one vacuum-sealed bag of freshly collected honey bee pollen from the -20°C freezer when ready to use.
Weigh out the desired amount of frozen pollen in 100 g increments at a time.
Reseal any unused ground pollen in a new vacuum seal bag, label appropriately, and store at -20°C.
Use a commercial blender to blend the pollen to a fine powder consistency (Figure 4A-C).
Add 38.5 mL of 50/50 inverted syrup to 100 g of ground pollen and mix with a spoon to a peanut butter-like consistency (Figure 4A).
Place a damp paper towel over the pollen paste while working to prevent evaporation.
Transfer the pollen paste to disposable 43 mm aluminum weigh dishes. For nest initiation, weigh out 3.0–3.25 g of pollen paste and place offset to one side in the lid of a pre-weighed 35 mm × 10 mm disposable Petri dish (Figure 4B). For routine feeding, fill to the top of the dish, but leave a small space on one side for transfer with forceps to the microcolony chambers (Figure 4C). If using pollen as the dosing vehicle for a pesticide exposure-effects study, either work from the lowest concentration to the highest concentration or use clean forceps when switching to a new dose group.
Figure 4. Pollen processing. (A) Pollen paste with peanut butter-like consistency. (B) Pollen paste for routine feeding in a feeding dish. A small void is left to allow manipulating the feeding dishes with forceps while minimizing the risk of cross-contaminating exposure groups. (C) Nest dish with initiation patty offset to allow space for adding additional pollen paste on day 5.
Pollen patties for nest initiation and paste for routine feeding and nest initiation should be made fresh on the day of initiation or feeding.
Protocol for Microcolony Food Preparation Notes
Fresh-frozen pollen should be stored in vacuum sealer bags or other air-tight containers at -20°C for up to 2 years. If stored longer, investigators should confirm palatability relative to freshly collected pollen before committing to a large, time-consuming experiment.
The pH of 50/50 inverted syrup should be between 4 and 5.
To maximize continuity within an experiment, all pollen needed for one study should be pooled and blended to produce a single, uniform food stock.
Grinding pollen in advance and distributing it into either single-use bags or bags sufficient to cover experimental needs for one week at a time will save a significant amount of time during the experiment.
Part II: Protocol for microcolony initiation and monitoring
Materials and Reagents
Newly emerged B. impatiens workers (Biobest (Romulus, MI), Koppert Biological Systems (Howell, MI) or another commercial vendor; see Protocol for Microcolony Initiation and Monitoring Notes #3).
50/50 inverted syrup and pollen paste/patties prepared as described in Part I (above)
Data sheets for recording data (see Supporting information figures 1–6)
Head lamp (e.g., Petzl Tactikka) and/or small handheld flashlight with red light filter (e.g., Mini Maglight PRO LED)
Parafilm wrap (Masterflex, catalog number: PM992)
Mortar and pestle (VWR, catalog number: 470019-978)
Disposable paper mats for covering working surfaces (Versi-Dry Lab Table Soakers, catalog number: 62080-00)
20 mL oral dosing syringes (Medi-dose, catalog number: NAW-2000) with manufacturer-supplied tight-fitting caps (drill a hole in each syringe 1/8” hole located at the 2 mL mark prior to use)
43 mm aluminum weigh dishes (Qorpak, catalog number: MET-03105)
Specimen forceps (12” length; VWR, catalog number: 82027-382)
General-purpose laboratory tape (VWR, catalog number: 89097-912)
Rectangular ice pan, approximate dimensions 15” L × 10” W × 6” D (VWR, catalog number: 10146-216)
Rectangular plastic container, approximate dimensions 7.5” L × 5” W × 2.5” D (Cambro, catalog number: 42PP190)
50 mL conical tubes (Corning, catalog number: 352070)
Disposable 35 mm × 10 mm Petri dishes (Falcon, catalog number: 351008)
43 mm aluminum weigh dishes (QORPAK, catalog number: MET-03105)
Equipment
4°C laboratory refrigerator (Thermo Scientific, catalog number: TSV18CPSA)
-20°C laboratory freezer (Thermo Scientific, catalog number: TSX3020FARP)
Analytical top loading scale/balance, 0.1 mg (OHAUS, catalog number: 30100604)
Analytical balance standards: 10 g, 20 g, and 30 g
5” stainless-steel geology sieve (1.57” depth × 5” diameter), #10 mesh (SciOptic, ASTM 10, catalog number: 305 stainless steel)
Clear observation tops for geology sieves with access lids (see Protocol for Microcolony Initiation and Monitoring Notes #1).
Bottom plates with holes drilled for ventilation for geology sieves to sit on top of (see Protocol for Microcolony Initiation and Monitoring Notes #2).
Environmental chamber with temperature and humidity controls
Software
Microsoft Excel Spreadsheet Software® (v16.0; Redmond, WA)
GraphPad Prism® (v6; La Jolla, CA)
Procedure
Prepare nest provisions and feeders (see Protocol for Microcolony Initiation and Monitoring Notes #4)
Prepare syrup feeders using 20 mL oral dosing syringes with a pre-drilled 1/8” hole located at the 2 mL mark. Holes should be parafilmed to facilitate filling syringes with either control 50/50 inverted syrup or, if the experiment calls for it, test article-containing 50/50 inverted syrup.
Fill syringe feeders by submerging the syringe tip into a beaker or conical tube containing 50/50 inverted syrup or test article-containing 50/50 inverted syrup by pulling up on the plunger. Cap syringes after filling with syrup.
Remove the parafilm and record the syrup weight in the datasheet for the experiment (see Supporting information figure 1 for an example data collection sheet).
Prepare pollen patties as described in Part I (above).
Prepare microcolony chambers for nest initiation
Label each microcolony observation top with the date of initiation and assigned microcolony number.
Place stainless steel sieve on the bottom plate with an absorbent paper towel placed in between the pieces, and clear observation lid on top.
Place the lid of a 35 mm × 10 mm disposable Petri dish marked with the microcolony number on the bottom, in the microcolony chamber with a 3–3.25 g nest initiation patty for nest building (Figure 5).
Figure 5. Microcolony chamber components. Stainless steel geology sieve (1.57” depth × 5” diameter) with pass-through floor (#10 mesh), bottom plate with holes drilled for ventilation, see-through top for collecting observations, removable lid for accessing chamber interior, and syringe feeder. Design adopted from Bayer CropSciences.
Weighing and seeding microcolonies with newly emerged B. impatiens workers (Protocol for Microcolony Initiation and Monitoring Notes #5)
Fill the ice pan and place the rectangular plastic container in the center of the ice pan with 50 mL conical tubes positioned around the inside edge of the ice pan for storing collected newly emerged workers.
Transfer enough newly emerged workers to the 4°C refrigerator for 10–15 min to support the experiment (i.e., Number of workers needed = [(5 workers/microcolony × the number of microcolonies desired) + 10% extra bees to account for dead/injured bees]).
Remove bees from 4°C and transfer them to the shallow rectangular plastic container on ice.
Next, transfer five randomly selected bees at a time to the 50 mL conical tubes. Transfer the conical tubes to the lab bench to allow the bees to become active again.
Check the conical tubes for any dead or damaged bees prior to weighing; replace dead or damaged bees as needed.
Weigh the conical tube with the five newly emerged bees for the first microcolony. Add the bees to their microcolony and then weigh the empty conical tube to determine the weight of the bees. Record these numbers in the datasheet for the experiment (see Supporting Information figure 2 for an example data collection sheet).
Supplementing the nest initiation patty
Five days after microcolony initiation, supplement the nest initiation patty with an additional ~2 g of pollen paste.
Microcolony routine feeding (see Protocol for Microcolony Initiation and Monitoring Notes #6–9)
Seven days after microcolony initiation, give each microcolony ~2 g pollen paste for feeding in a disposable 43 mm aluminum weigh dish.
Provide microcolonies with fresh, pre-weighed ~3.5 g pollen paste and either control 50/50 inverted syrup or test article-containing 50/50 inverted syrup every Monday, Wednesday, and Friday starting one-week post initiation.
Record the weight of the new dish with new pollen paste and new syrup feeder into the datasheet for the experiment (see Supporting information figure 1 for an example data collection sheet).
Record the weight of the old pollen paste with the original dish and previous syrup feeder to determine consumption.
To more accurately quantify pollen/syrup consumption levels, include two evaporation controls in the study design. These controls should be set up and processed exactly like all other microcolonies, except they do not contain bees (see Supporting information figures 3 and 4 for an example data collection sheet).
Monitoring microcolonies and data collection (see Protocol for Microcolony Initiation and Monitoring Notes #10–12)
Using an environmental chamber, maintain microcolonies in darkness at 25°C ± 0.5°C and 50% ± 5% relative humidity throughout the duration of the study. Red light may be used when microcolonies are outside of the environmental chamber on the bench. Avoid white light where possible.
Evaluate each microcolony from initiation to study termination (see Supporting information figure 5 for an example data collection sheet).
During each observation, collect the following information: 1) number of dead workers; 2) days to first drone emergence; 3) number of drones emerged; and 4) drone weight.
Optional, additional information can be collected, including 1) time to first uncapped egg chamber; 2) days to first capped egg chamber; 3) days to first larval mass; and 4) days to first pupal cell.
Any drones that emerge should be removed when the microcolonies are fed (i.e., Monday, Wednesday, and Friday). After removal, weigh each drone individually (see Supporting information figure 6 for an example data collection sheet).
Optional but encouraged: randomly select and photographically track at least one microcolony from each experimental group (Wednesdays recommended) to capture microcolony progression and developmental milestones.
Terminating microcolonies
When the experiment is complete, after 42 or 49 days, either proceed to additional assay endpoints or euthanize the workers, drones, and remaining brood by CO2 narcosis followed by transfer to -80°C.
Protocol for Microcolony Initiation and Monitoring Notes
The observation tops can be made according to the specifications detailed in Figure 6A and 6B. As designed, the tops have a recessed 5” diameter ring that prevents the lids from slipping off the top of the sieve. However, other designs for the top can be used, provided they 1) are large enough to cover the sieve [bees will be housed in the space between the mesh floor of the sieve and the observation top (see Figure 7)], have an opening for the syringe feeder, and have ventilation holes to allow air circulation.
Figure 6. Materials and measurements for the microcolony observation top, removable lid, and bottom plate. Microcolony chamber observation tops (A), removable lids (B), and bottom plates and (C) used previously (Camp et al., 2020a, 2020c; Weitekamp et al., 2022) can be reconstructed according to the specifications shown. dia. = diameter.
Bottom plates can be made according to the specifications detailed in Figure 6C. The bottom plates were designed to prevent bee waste and other debris that pass through the perforated floor of the sieve from contaminating other microcolonies and from fouling the environmental chamber. The design of the bottom plates includes a recessed 5” diameter ring that the sieve drops into. However, investigators can use any bottom plate design, provided the bottoms have ventilation holes to allow air circulation and are large enough for the sieve to sit on top of it.
Microcolonies should not be initiated with randomly aged workers when using this protocol. Using age-matched, newly emerged workers reduces the possibility of confusing age-related deaths for treatment effects and promotes consistency across microcolonies within an experiment and across experiments. When using this protocol, investigators should use fresh or fresh-frozen honey bee-collected corbicular pollen with this protocol. Provisioning microcolonies with old (i.e., >2 years old) or improperly stored pollen may impact microcolony progression and productivity.
Pollen patties for nest initiation and paste for routine feeding should be made fresh on the day of initiation or feeding.
Since worker size can impact microcolony nest development and food consumption rates by workers (Peat and Goulson, 2005; Couvillon and Dornhaus, 2010; Amsalem and Hefetz, 2011; Roger et al., 2017a, 2017b), protocol users are encouraged to seed microcolonies with bees of a similar mass.
Microcolonies must be provided ad libitum access to pollen and syrup for the duration of the experiment. Restricting access to food provisions will disrupt microcolony development, reduce productivity, and complicate the interpretation of experimental results.
The delay in providing pollen specifically for feeding is to reduce the likelihood that the workers will attempt to lay eggs on both the pollen for feeding and nest initiation patty.
Microcolonies consume significantly more pollen when feeding developing larvae. Therefore, it is best to give productive microcolonies ~3.5 g of pollen paste to minimize the risk that they will run out of pollen.
Unless retention is required for additional analysis, dispose of the old pollen dish.
To help keep the bees calm when manipulating the microcolonies, place the chambers on a disposable paper mat that will absorb vibrations.
To promote consistency across microcolonies, rotate the position of individual microcolonies within the environmental chamber.
If a founding worker dies in the first 24 h, replace it with a new newly emerged worker (obtain weight of new worker).
Because the number of worker bees in a microcolony can impact nest productivity (Gradish et al., 2013) and food consumption rates, protocol users are encouraged to track the number of dead workers throughout the experiment.
Production of drones is a key metric of microcolony success. The time to first drone emergence, the number of drones emerged, and drone weight can all be readily quantified. Importantly, all these measures can be affected by experimental treatments providing insights into how a test material impacted the microcolony.
Data analysis
This pair of protocols was developed to explore the effects of pesticide exposure on microcolony progression and productivity (see Camp et al., 2020a, 2020c; Eitekamp et al., 2022). While that is the case, these protocols can easily be used to address a variety of research questions, thereby enabling investigators to gain significant insight into other aspects of bumble bee biology. Based on experience using this system, 8–10 microcolonies should be used per experimental group. Below is an overview of how to process and analyze data collected from pesticide exposure-effects studies using this protocol. Detailed methods for processing and analyzing data for these endpoints can be found in Camp et al. (2020a, 2020c) and Weitekamp et al. (2022). To aid new investigators, sample data collection sheets along with guidance on how to record and process microcolony data are provided as supplementary information at the end of this protocol.
Analysis of microcolony data can be broken down into two interrelated parts. For the first part, microcolonies should be visually inspected and photographed to identify treatment-related effects on nest progression. Microcolonies established according to this protocol will progress according to the timeline shown in Figure 7. When collecting observations weekly, uncapped egg chambers will appear by the end of week 1. Capped egg chambers sometimes appear late in week 1, but most often by the end of week 2. Larval masses can be detected during weeks 2 and 3. Pupal cells will appear during weeks 3 and 4. The first drones appear during week 5 and will continue to emerge for the remainder of the study. If desired, observations can be collected more frequently to tease out subtle effects on microcolony development. However, collecting observations is time-consuming, and frequent disruptions may impact worker behavior and ultimately study outcome.
Figure 7. Microcolony progression through seven weeks of development. Microcolonies were initiated with five newly emerged B. impatiens workers and provisioned with a nest initiation patty of pollen paste (3 g) and 50/50 inverted syrup to stimulate nest building. After 5 days, nests were given an additional 2 g of pollen paste. Starting on day 7, microcolonies were given fresh pollen paste and syrup every Monday, Wednesday, and Friday. Starting from Day 0 (i.e., nest initiation), photos show microcolony progression from uncapped egg chambers to study termination on day 49. Bars with labels above indicate the range when feature typically appears. Numbered circles indicate features of the microcolony, including 1 = nest initiation patty, 2 = pollen supplement given on day 5, 3 = uncapped egg chamber, 4 = larval mass, 5 = pupal cell, and 6 = evacuated pupal cell.
In addition to qualitatively assessing microcolony status, data from various endpoints should be analyzed statistically, including microcolony development milestones (i.e., time to first uncapped egg chamber, days to first capped egg chamber, days to first larval mass, and days to first pupal cell), syrup and pollen consumption, drone production and weight, and worker survival. These data should be expressed as mean ± standard deviation (STDEV). Using GraphPad Prism® (v6; La Jolla, CA), differences between the control and treatment groups can be assessed with One-way Analysis of Variance (ANOVA) and Dunn’s multiple comparison test. If, according to the Brown-Forsythe or Bartlett’s tests, variances are significantly different, instead use the non-parametric Kruskal-Wallis with Dunnett’s multiple comparisons test.
Data reporting
To allow comparisons to be made between studies and to facilitate study replication, investigators are encouraged to report the 1) syrup formulation used for feeding, 2) pollen source and age, 3) age and source of the worker bees, and 4) environmental conditions (i.e., temperature, relative humidity, and light regimen) used during the experiment. In addition, the start, end, and data collection dates should also be recorded and reported. All data should be made available to other investigators either as supplemental information or through a public repository for scientific data.
Data Analysis Notes
When investigating the effects of pesticide exposure on microcolony development and productivity, investigators should include an untreated control group, a positive control group, and, if applicable, a solvent control group in the study design. Evaporation controls should also be included to correct food consumption estimates when conducting pesticide exposure studies.
When desired, the pesticide can be delivered to the microcolony through the syrup and/or pollen provisions. Dosing pesticides via syrup is generally easier than with pollen. However, not all pesticides are water-soluble, and, for that reason, solvents may be required to solubilize the test material. In that event, investigators will need to empirically identify a suitable solvent concentration for use in their experiment [e.g., 1% acetone (Camp et al., 2020b)].
When evaluating the effects of pesticide exposure on microcolonies, the delivery vehicle (i.e., pollen or syrup) can impact study outcome. Developing bumble bee brood consumes large amounts of pollen and, for that reason, delivering test material through the pollen may target the brood. To that point, acetamiprid delivered in the pollen, but not when delivered in the syrup, reduced average drone weight (Camp et al., 2020a, 2020c; Weitekamp et al., 2022). Consequently, important brood effects could be missed when only dosing through the syrup.
Syrup and pollen consumption values should be corrected for evaporation and, when determining consumption on a per bee basis, worker mortality. Also, if a syrup-filled syringe leaked, leading to an inaccurate consumption value, the value should be replaced with the average syrup consumption value for that treatment group and day.
Published results suggest that the microcolony model may only be appropriate for assessing brood effects for substances with low toxicity to adult workers (Krueger et al., 2021).
Recipes
Potassium Sorbate Solution
Prepare a 25% w/v sorbic acid and potassium salt solution by dissolving 25 g of sorbic acid in distilled water to achieve a final volume of 100 mL; sterile filter (0.45 µm) and store at 4°C for up to 90 days.
Acknowledgments
The author thanks Drs. J. E. Simmons, C. Weitekamp, and YH. Kim for thoughtful and critical review of this manuscript. The author is also grateful to Drs. D. Schmehl, A. Cabrera, J. Strange, and D. Cox-Foster for their generosity and guidance. This protocol was adapted from previous work published peer-reviewed journals (Camp et al., 2020a, 2020c; Weitekamp et al., 2022).
Competing interests
The authors declare no conflict of interest.
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4,452 | https://bio-protocol.org/en/bpdetail?id=4452&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
ATAC-Seq of a Single Myofiber from Mus musculus
KS Korin Sahinyan *
DB Darren M. Blackburn *
VS Vahab D. Soleimani
(*contributed equally to this work)
Published: Vol 12, Iss 12, Jun 20, 2022
DOI: 10.21769/BioProtoc.4452 Views: 3191
Reviewed by: Pilar Villacampa AlcubierreMohan BabuNootan Pandey
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Original Research Article:
The authors used this protocol in eLIFE Feb 2022
Abstract
Chromatin accessibility is a key determinant of gene expression that can be altered under different physiological and disease conditions. Skeletal muscle is made up of myofibers that are highly plastic and adaptive. Therefore, assessing the genome-wide chromatin state of myofibers under various conditions is very important to gain insight into the epigenetic state of myonuclei. The rigid nature of myofibers, as well as the low number of myonuclei that they contain, have rendered genome-wide studies with myofibers challenging. In recent years, ATAC-Seq from whole muscle and single nucleus ATAC-Seq have been performed. However, these techniques cannot distinguish between different fiber and cell types present in the muscle. In addition, due to the limited depth capacity obtained from single nucleus ATAC-Seq, an extensive comparative analysis cannot be performed. Here, we introduce a protocol where we combine the isolation of a single myofiber with OMNI ATAC-Seq. This protocol allows for genome-wide analysis of accessible chromatin regions of a selected single myofiber at a sufficient depth for comparative analysis under various physiological and disease conditions. This protocol can also allow for a specific myofiber to be selected, such as a regenerating myofiber. In the future, this protocol can help identify global changes in chromatin state under various conditions, as well as between different types of myofibers.
Graphical abstract:
Keywords: Single myofiber ATAC-Seq Skeletal Muscle Epigenetics Chromatin Accessibility
Background
Skeletal muscle is the largest tissue in the body and it is primarily composed of myofibers (Buckingham et al., 2003). Myofibers are highly adaptive, and therefore studying changes in myofibers under different stimuli is crucial for understanding how the skeletal muscle adapts and responds to different conditions and diseases (Deschenes, 2004; Wilson et al., 2012). Epigenetics and chromatin accessibility play a key role in the regulation of gene expression and tissue function (Zhu et al., 2018), making it crucial to study chromatin accessibility of different cell types, including myofibers under various stimuli. ATAC-Seq is the commonly used gold-standard method for genome-wide analysis of accessible chromatin regions, and is based on a hyperactive transposase, Tn5 (Buenrostro et al., 2015; Corces et al., 2017). The advancements in sequencing and single cell technologies have allowed for ATAC-Seq to be performed at the whole muscle (Ramachandran et al., 2019) and at the single nucleus levels in recent years (Dos Santos et al., 2020). However, both methods have limitations: whole muscle sequencing does not distinguish between different cell types present in the muscle, and single nucleus ATAC-Seq has lower sequencing depth, restricting its ability for comparative analysis. Therefore, these methods can not assess the chromatin state of only the muscle fibers and can not distinguish different myofiber types. The rigid structure of myofibers (Janssen et al., 2000; Keire et al., 2013) and the low number of myonuclei that a single myofiber contains (200–300 myonuclei) (Neal et al., 2012; Cramer et al., 2020), have made it challenging to perform ATAC-Seq on a single myofiber.
Here, we introduce a method, single myofiber ATAC-Seq (smfATAC-Seq), where we combine the isolation of a single myofiber with OMNI ATAC-Seq (Corces et al., 2017) to analyze the genome-wide accessible chromatin regions of a selected single myofiber without the confounding effects of other cell types present in the muscle. Additionally, this method allows for the selection of a specific myofiber, such as a regenerating myofiber, through the patterning of centrally located myonuclei (Roman and Gomes, 2018). Furthermore, it provides sufficient sequencing depth for peak calling and for comparative analysis of myofibers under various physiological and disease conditions. We have successfully used this method to compare the chromatin accessibility between resting and regenerating myofibers as well as between myofibers isolated from a mouse model of Duchenne Muscular Dystrophy (mdx) and wild-type mice. smfATAC-Seq can allow researchers to assess the chromatin state of a single myofiber and compare the epigenetic changes that occur in myofibers under various biological and disease conditions. Therefore, in the future, smfATAC-Seq might help identify novel mechanistic insights on the role of myonuclei in regulating the plasticity of myofibers under various states.
Materials and Reagents
Materials
6-well plate (Sarstedt, catalog number: 83.3920)
1.5 mL microtubes (Sarstedt, catalog number: 72.690.300)
200 μL strip tubes (Progene, catalog number: 87-C200-8-TB)
Pipette tips (Sarstedt, catalog numbers: 70.3010 [10 μL], 70.3030 [200 μL], 70.3050 [1,000 μL])
Small and Large Glass Pasteur pipettes (VWR, catalog number: 14672-200)
0.22 μm filter (Ultident, catalog number: 229747)
1 mL syringe with 26G needle (BD Biosciences, catalog number: 309625)
Microplate (Corning, catalog number: 3676)
Animals
C57BL/6 mice were acquired from the Jackson Laboratories. The procedure is performed on 4-week-old mice that have gone through intra-muscular cardiotoxin mediated injury on the left hind limb (the procedure has also been successfully performed on 4-week-old uninjured C57BL/6, C57BL/10ScSn-Dmdmdx, and C57BL/10ScSn mice acquired from the Jackson Laboratories). This protocol could be adapted to various strains, but it will be important to adjust the Tn5 dose and incubation time if there is a severe skeletal muscle fiber phenotype.
Reagents
For Cardiotoxin-mediated injury
Cardiotoxin (CTX) (Sigma, catalog number: 11061-96-4)
Isoflurane (Fresenius Kabi, catalog number: CP0406V2)
PBS (Wisent, catalog number: 311-425-CL)
Carprofen (Zoetis, RIMADYL)
Ethanol (Commercial Alcohols, catalog number: P016EAAN)
For digestion and isolation of extensor digitorum longus (EDL)
Collagenase from Clostridium histolyctium (Sigma, catalog number: C0130-1G)
PBS (Wisent, catalog number: 311-425-CL)
Horse Serum (Wisent, catalog number: 065-250)
DMEM (Invitrogen, catalog number: 11995073)
Trypsin (Gibco, catalog number: 15090-046)
Isoflurane (Fresenius Kabi, catalog number: CP0406V2)
CO2 (Praxair, catalog number: GP-700500)
Digestion Buffer (see Recipes)
Coating media (see Recipes)
For selection of injured vs. uninjured myofibers
Hoechst (Molecular Probes, catalog number: H1399)
PBS (Wisent, catalog number: 311-425-CL)
For lysis and permeabilization of the myofiber
PBS (Wisent, catalog number: 311-425-CL)
Triton X-100 (Sigma, catalog number: T9284)
Permeabilization Buffer (see Recipes)
For transposition
Tagment DNA Buffer and Tn5 transposase (Illumina, catalog number: 20034197)
Tween-20 (Sigma, catalog number: P1379-1L)
Digitonin (Promega, catalog number: G9441)
PBS (Wisent, catalog number: 311-425-CL)
Nuclease free water
Transposition mixture (see Recipes)
For DNA purification
QIAquick PCR Purification Kit (Qiagen, catalog number: 28104)
Ethanol (Commercial Alcohols, catalog number: P016EAAN)
For sequencing-ready library preparation
Q5 High fidelity DNA polymerase (New England Biolabs, catalog number: M0491S)
Deoxynucleotide (dNTP) solution mix (New England Biolabs, catalog number: N0447L)
Nextera XT Index Kit (Illumina, catalog number: FC-131-1001)
Nuclease free water
PCR reaction mixture (see Recipes)
For library purification and size selection
Ampure XP Beads (Beckman Coulter Life Sciences, catalog number: A63880)
Ethanol (Commercial Alcohols, catalog number: P016EAAN)
Nuclease free water
For quality control of the sequencing libraries
Quant-IT Picogreen dsDNA Assay kit (Invitrogen, catalog number: P7589)
Tris (Hydroxymethyl) Amino Methane (Multicell, catalog number: 600-125-LG)
Glacial acetic acid (Fisherbrand, catalog number: 351272-212)
Na2EDTA·2H2O (Bioshop, catalog number: EDT 001)
100 bp DNA ladder (GenedireX, catalog number: DM001-R500)
Agarose (Bioshop, catalog number: AGA001.500)
Orange G (Sigma, catalog number: O3756-25G)
Glycerol (Bioshop, catalog number: GLY001.1)
EDTA (Invitrogen, catalog number: AM9260G)
HCl (Honeywell-Fluka, catalog number: 72787)
GelGreen Nucleic Acid Gel Stain (Biotium, catalog number: 41005)
Primers (Integrated DNA Technologies, standard desalting, 25 nmole)
VEGFA_TSS_Forward CCGCTGAATAGTCTGCCTTG
VEGFA_TSS_Reverse GAGAAGCGCAGAGGCTTG
Chromosome17qE5_Forward TCATCATGTGTCCTGAAGTTGA
Chromosome17qE5_Reverse GCTTCTCTCCACAGAATTTGC
DNA Loading Dye (see Recipes)
TE Buffer (see Recipes)
TAE Buffer (see Recipes)
Equipment
Pipettes (P20, P200, P1000)
Microscope (Fisher Scientific, inverted microscope, equipped with transmitted light and a 4× objective)
EVOS FLoid Microscope (Life Technologies, catalog number: 4471136)
Dissection tools
Fine point high precision forceps (Fisher Scientific, catalog number: 22-327379)
Sharp-pointed dissecting scissors (Fisher Scientific, catalog number: 08-935)
Cell incubator (Thermo Scientific, Forma Series II Water-Jacketed CO2 Incubator, catalog number: 3110)
Heat block (Fisher Scientific, catalog number: 11-718-2)
Centrifuge (Thermo Scientific, Sorval Legend Micro 21R Microcentrifuge, catalog number: 75002447)
Thermocycler (Bio-Rad, C1000 Touch Thermal Cycler, catalog number: 1851148)
Magnetic rack (Thermo Fisher, DynaMag-2 Magnet, catalog number: 12321D)
Microplate reader (BioTek, synergy4)
Power supply (Bio-Rad, PowerPac, catalog number: 1645050)
Bioanalyzer (Agilent, BioAnalyzer 2100)
Gel Imager (LI-COR, Odyssey FC Imaging System)
Procedure
Intra-muscular injury of mouse Extensor Digitorum Longus (EDL) muscle (optional)
Note: This step is required if performing ATAC-Seq on regenerating myofibers. If not, you may skip to section B.
Prepare a working solution of 10 µM cardiotoxin (CTX) in PBS; store at -80°C.
Perform a subcutaneous injection of 100 µL per 20 g of mouse body weight of Carprofen (4 mg/mL) and wait 20 min.
Note: Carprofen is a non-steroidal anti-inflammatory drug (NSAID) used to manage the pain and inflammation that can be associated with the injury.
Anesthetize the mouse using an institutionally approved method. In this protocol, the mouse was anesthetized with 3% isoflurane in an induction chamber.
Spray the hindlimb that is to be injured with 70% ethanol and inject 50 µL of CTX through the Tibialis Anterior (TA) muscle into the EDL using a 1 mL syringe.
Monitor the mouse for 10 min.
Allow the muscle to regenerate for the desired period of time. We performed this on mouse skeletal muscle 7 days post injury; however, different time points after the injury can be used.
Dissection and digestion of Extensor Digitorum Longus (EDL) myofibers from Mus musculus
Prepare a digestion buffer of 1000 U/mL of collagenase from Clostridium histolyctium in unsupplemented DMEM (Recipe 1). Transfer 800 µL of digestion buffer into a 1.5 mL microtube and place it in an incubator at 37°C and 5% CO2.
Coat a 6-well plate with coating media of 10% Horse Serum (HS) in unsupplemented DMEM (Recipe 2). This will prevent the isolated myofibers from sticking to the plate and becoming difficult to handle.
Notes:
Pure HS or FBS can also be used.
Make sure that the plate is coated for at least 30 min prior to use.
Sacrifice the mouse.
Using a small pair of dissection scissors, remove the skin on the hindlimb and expose the muscles (Video 1).
Dissect the Tibialis Anterior (TA) muscle by cutting the distal tendon, being careful to not cut the adjacent EDL tendon (Video 1).
Peel the TA muscle upwards towards the knee using a pair of forceps. Then cut the TA muscle as close to the knee as possible (Video 1).
Using a pair of forceps, detach the biceps femoris muscle from the knee to expose the proximal tendon of the EDL muscle (Video 1).
Cut the distal EDL tendon and gently pull the EDL upwards towards the knee using a pair of forceps. Ensure that there is a bit of tension in the EDL as you are pulling it up without tugging too hard as that may damage the myofibers (Video 1).
Cut the proximal EDL tendon as close to the knee as possible (Video 1).
Video 1. Dissection of the EDL muscle.
The procedure in the video was approved by McGill University Animal Care Committee (UACC) under the protocol #7512.
Place the EDL in the 1.5 mL microtube containing the digestion buffer from step B1. Add trypsin to the digestion buffer at a final concentration of 0.25%.
Notes:
Trypsin is added to remove the Muscle Stem Cells (MuSCs) associated with the myofibers.
Make sure to add the trypsin at this step and not at Step B1, as Trypsin can digest the collagenase and render it ineffective.
Incubate the EDL muscle with the digestion buffer containing trypsin at 37°C and 5% CO2 for 1 h. Invert the tube periodically for mixing.
During the incubation period, remove the coating media from the 6-well plate and replace it with 2 mL of PBS 1×. Place the plate into the incubator at 37°C and 5% CO2.
Notes:
The coating media can be kept in the fridge and reused for future myofiber isolations.
Make sure that the plate is placed in the incubator for at least 30 min.
After the 1 h incubation time, transfer the EDL muscle to one of the coated wells of the 6-well plate using a large-bore glass pipette. Coat the large-bore glass pipette with HS prior to use (Figure 1A).
Note: Coating is very important because myofibers are very sticky in nature.
Gently pipette the EDL muscle up and down with the large-bore glass pipette coated with HS (Figure 1F).
Using a small-bore glass pipette coated with HS, serially transfer a small number of isolated myofibers to the remaining wells of the 6-well plate. This will act as a wash step to remove debris and other cell types.
Figure 1. Myofiber isolation and selection. (A) Typical isolated EDL myofibers in a 6-well plate. (B) Live individual myofiber in a 0.2 mL microtube. (C) Single myofiber in a 0.2 mL microtube post permeabilization. (D) Hoechst staining of an uninjured myofiber. (E) Hoechst staining of a regenerating myofiber, displaying the hallmark of centrally located myonuclei. (F) Glass pipettes used in the procedure. Small-bore glass pipette can be obtained by flame polishing the uncut glass pipette on a Bunsen burner. Large-bore glass pipette can be obtained by cutting a glass pipette and then flame polishing on the Bunsen burner.
Myofiber selection
Add 2 μL of Hoechst (5 mg/mL) into one well of the 6-well plate containing isolated myofibers in 2 mL of PBS 1× (optional).
Note: If you do not wish to select for a specific myofiber such as a regenerating myofiber, you may skip to step 5.
Place the 6-well plate in a 37°C with 5% CO2 incubator for 5 min.
Remove the 6-well plate from the incubator and place it under the microscope.
If the desired myofiber is an injured myofiber, identify the myofibers with centrally located myonuclei along the length of the myofiber, as opposed to the non-regenerating myofibers with no specific myonuclei patterning (Figure 1D–1E).
Note: During injury, not all the myofibers undergo regeneration simultaneously or to the same degree. However, regenerating myofibers are characterized by the pattern of centrally located myonuclei. Thus, you may select the regenerating myofiber using this hallmark as a marker.
Coat a small-bore glass pipette with HS.
While visualizing the myofibers under the microscope, select the desired myofiber and transfer it into a 200 μL PCR strip tube using the coated small-bore glass pipette.
Visualize the PCR tube under the microscope to ensure that you have selected and transferred a single myofiber into the tube (Figure 1B).
Myofiber lysis and permeabilization
Using a P200 pipette, remove the excess PBS 1× from the PCR tube under the microscope. Make sure not to remove the myofiber.
Using a P20 pipette, add 20 μL of the permeabilization buffer (Recipe 3) into the tube with the myofiber. Pipette the fiber up and down five times.
Incubate on ice for 15 min (Figure 1C).
Remove the permeabilization buffer with a P20 pipette under the microscope while being careful not to remove the myofiber.
Wash the myofiber by adding 200 μL of PBS 1× using a P200 pipette.
Place the tube on ice for 5 min.
Remove the PBS 1× by using a P200 pipette under the microscope.
Repeat steps 5–7 two times.
Note: During the 5 min incubation of the washes, you may start the next step for the preparation of the transposition mixture (Recipe 4).
Myofiber transposition by the Tn5 transposase
Prepare the transposition mixture (Recipe 4).
Using a P20 pipette, add 6 μL of the transposition mixture into the tube containing the myofiber. Slowly pipette the myofiber up and down six times.
Place the tube into the heat block set to 37°C for 56 min. Gently shake the tube by flicking it every 5–7 min.
Note: The Tn5 transposase will cut the accessible chromatin regions and add adaptors simultaneously.
DNA purification
After the transposition, column purify the DNA using the QIAquick PCR Purification Kit according to the manufacturer’s guidelines. Briefly,
Add 70 μL of PB binding buffer into the tube containing the myofiber in the transposition mixture.
Transfer the entire contents of the tube into the column provided by the kit.
Centrifuge the column at 16,000 × g for 1 min.
Discard the flow-through.
Place the column back in the same tube.
Add 700 μL of PE wash buffer into the column.
Centrifuge the column at 16,000 × g for 1 min.
Discard the flow-through. Place the column back in the same tube.
Centrifuge again at 16,000 × g for 1 min.
Discard the flow-through.
Place the column into an empty 1.5 mL microtube.
Add 20 μL of elution buffer into the column. Incubate at room temperature for 5 min.
Note: You may place the tube at 37°C for 2 min for better elution.
Centrifuge at 16,000 × g for 1 min.
Using a P200 pipette, take out the 20 μL of eluted DNA from the collection tube and add it back into the column for second elution.
Note: Double elution can help increase the yield.
Elute the DNA again by centrifuging at 16,000 × g for 1 min.
Note: This is a stopping point. The eluted DNA can be left at 4°C overnight or at -20°C until library preparation.
Preparation of sequencing ready libraries
To amplify and incorporate indices for sequencing, prepare the PCR reaction mix (Recipe 5).
Add 30 μL of PCR reaction mix to the 20 μL of eluted DNA from the previous step for a final volume of 50 μL.
Note: When preparing the sequencing libraries, make sure that each sample has a different i5 and i7 adaptor combination. In addition, when combining samples in a sequencing lane, make sure that i5 and i7 adaptor combinations for the samples are color balanced for the type of sequencer that is being used (two or four channels). For more information, please visit:
https://support.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/experiment-design/index-adapters-pooling-guide-1000000041074-05.pdf.
Run the PCR program on the thermocycler using the following steps:
72°C for 5 min
98°C for 30 s
98°C for 10 s
63°C for 30 s 15 cycles
72°C for 60 s
Hold at 4°C
Note: This is a stopping point. The libraries can be left at 4°C overnight or at -20°C until library purification.
Library purification and size selection
Add AMPure XP beads into the PCR tube at a ratio of 0.85× (v/v). Mix well.
Note: This ratio is used specifically to remove fragments that are below the size of 200 bp.
Incubate at room temperature for 8 min (Figure 2A).
Place the tube on the magnetic rack. Wait for the solution to become clear (Figure 2B).
Discard the supernatant.
Wash the beads with 200 μL of 80% ethanol.
Remove the ethanol from the tube.
Repeat steps H5–H6. Make sure to remove all the ethanol after the second wash.
Let the beads dry for 2 min.
Note: Be careful not to over-dry the beads since this leads to lower elution efficiency. However, if the beads do get overdried (a sign of this is the cracking on the beads), do the elution at 37°C for 5–10 min as this can increase the elution efficiency.
Elute the DNA with 15 μL of elution buffer that is provided with the QIAquick PCR Purification Kit. Mix well until beads go into the solution.
Incubate at room temperature for at least 5 min.
Note: You may place the tubes at 37°C for 2–5 min for better elution.
Place the tube on the magnetic rack. Wait for the solution to become clear.
Keep the supernatant; this is your eluted DNA.
Note: You may proceed to the quality control steps, or you can store at -20°C until sequencing.
Figure 2. Size selection and purification of ATAC-Seq libraries by AMPure XP beads. (A) AMPure beads in solution. (B) AMPure beads separated from the solution on the magnetic rack.
Quantification and quality control of the ATAC-Seq libraries
Quantify the libraries by using the Quant-IT Picogreen dsDNA Assay kit (Table 1).
Prepare 1× TE buffer from the 20× TE stock solution that is provided with the kit.
Prepare DNA standards by diluting the stock DNA that is provided in 1× TE to the desired concentration.
Note: You may prepare DNA standards of 10 ng/μL, 5 ng/μL, 2 ng/μL, 1.5 ng/μL, 1.0 ng/μL, 0.75 ng/μL, 0.5 ng/μL, 0.25 ng/μL, 0.1 ng/μL, and 0.05 ng/μL.
Pipette 5 µL of TE 1× buffer into each well of a microplate. Calculate the number of wells needed depending on the number of samples you have. Usually, each standard and sample is run in triplicates.
Note: Due to the small concentration of DNA following smf-ATAC-Seq , you may run the samples in duplicates instead in order to not waste the samples.
Add 1 μL of the sample and the standards to the corresponding wells containing 5 μL of 1× TE buffer.
Thaw the stock Picogreen dye solution and mix well. Then make a 1:200 dilution of the stock Picogreen in 1× TE buffer.
Note: Make sure to not expose the Picogreen Dye to direct light for long periods of time.
Pipette 5 μL of the diluted Picogreen solution into each well. Quantify the amount of DNA in each sample by using a microplate reader.
Note: We usually get a final concentration of 3–7 ng/μL (Table 1).
Table 1. Representative final concentrations of single myofiber ATAC-Seq libraries
Sample Concentration (ng/μL)
Fiber 1 3.59
Fiber 2 4.61
Fiber 3 3.76
Fiber 4 6.97
Fiber 5 3.39
Fiber 6 5.66
Fiber 7 4.08
To verify the library size, run 11 ng of the sample on 1.25% agarose gel with dsGreen (1:10000 dilution) (Figure 3A–3B).
Notes:
The minimum amount is 11 ng; depending on the amount of DNA, you may run up to 20 ng of the sample on the gel.
Make sure to run only 3 μL of the DNA ladder that is diluted 1:2. This will ensure that the DNA ladder does not wash out the signal from the samples.
To check the enrichment for open regions of chromatin, you may run a qPCR for marker genes in the myofibers (Figure 3C).
Note: Since myofibers express VEGFA (Lazure et al., 2020), we use the Transcription Start Site (TSS) of VEGFA to check for enrichment. You may use the TSS of other expressed genes in the myofibers. As a negative control, we use a closed region on chromosome 17. We have also included the fold enrichment for the input DNA, which corresponds to the myofibers that were not transposed with the Tn5, called uncut DNA. In a successful ATAC-Seq, you will observe much higher fold enrichments in your sample for your marker gene compared to the enrichment in the Uncut DNA sample.
Run the sequencing libraries on a bioanalyzer (Figure 3D–3F).
Figure 3. Quality control of smfATAC-Seq libraries. (A–B) Representative pictures of smfATAC-seq libraries after size selection, visualized on an agarose gel. (C) qPCR for the TSS of VEGFA compared with a negative control region of Chromosome 17 qE5 for the smfATAC-Seq libraries (n = 5 biological replicates. Error bars = ± SD). (D–F) Examples of bioanalyzer profiles of smfATAC-Seq.
Data analysis
Follow the standard Encode ATAC-Seq pipeline for the analysis. For more information, visit: https://www.encodeproject.org/atac-seq/.
Recipes
Digestion buffer
Dissolve powdered collagenase from Clostridium histolyctium at a final concentration of 1,000 U/mL.
Add trypsin to the buffer at a final concentration of 0.25% once the muscle has been placed in the digestion buffer; this will prevent the trypsin from digesting the collagenase beforehand.
Note: Always prepare the digestion buffer fresh, immediately before sacrificing the mouse.
Coating media
Dilute HS into un-supplemented DMEM at a final concentration of 10% (V/V).
Permeabilization buffer
Prepare a stock solution of 10% Triton X-100 in ddH2O.
Prepare a working solution of permeabilization buffer from the 10% stock solution to a final concentration of 0.5% Triton X-100 in ddH2O.
Transposition mixture
Prepare a transposition mixture for six fibers in a total of 40 μL.
Add 20 μL of Tagment DNA Buffer (TD buffer)
Add 13.3 μL of PBS 1×
Add 4.61 μL of Nuclease free H2O
Add Digitonin for a final concentration of 0.02%
Add Tween-20 for a final concentration of 0.2%
Add 1.39 μL of Tn5
Note: Add the Tn5 enzyme at the end.
PCR reaction mix (1 reaction, 30 μL)
10 μL of Q5 Buffer
10 μL of Q5 enhancer
1 μL of dNTP’s
2.5 μL of i7 index
2.5 μL of i5 index
3.5 μL of nuclease-free water
0.5 μL of Q5 High Fidelity DNA polymerase
DNA loading dye
50% TE Buffer (see Recipe 7)
50% Glycerol
Orange G
TE buffer
1 mL of Tris-HCl pH 8.0, 1M
200 μL of EDTA pH 8.0, 0.5 M
Complete to 100 mL with dH2O
TAE buffer
242 g of Tris base
57.1 mL of Glacial acetic acid
37.2 g of anhydrous Na2EDTA
Complete to 1 L total volume with dH2O
Acknowledgments
This work was funded by a discovery grant from the Natural Sciences and Engineering Research Council (NSERC) to VDS.
This method has been successfully used to analyze the chromatin state of mouse single myofibers under injury and disease conditions (Sahinyan et al., 2022).
Competing interests
The authors declare no competing interests.
Ethics
All procedures that were performed on animals were approved by the McGill University Animal Care Committee (UACC) under the protocol #7512, valid through July/1/2021 – July/1/2022.
References
Buckingham, M., Bajard, L., Chang, T., Daubas, P., Hadchouel, J., Meilhac, S., Montarras, D., Rocancourt, D. and Relaix, F. (2003). The formation of skeletal muscle: from somite to limb. J Anat 202(1): 59-68.
Buenrostro, J. D., Wu, B., Chang, H. Y. and Greenleaf, W. J. (2015). ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide. Curr Protoc Mol Biol 109: 21 29 21-21 29 29.
Corces, M. R., Trevino, A. E., Hamilton, E. G., Greenside, P. G., Sinnott-Armstrong, N. A., Vesuna, S., Satpathy, A. T., Rubin, A. J., Montine, K. S., Wu, B., et al. (2017). An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat Methods 14(10): 959-962.
Cramer, A. A. W., Prasad, V., Eftestol, E., Song, T., Hansson, K. A., Dugdale, H. F., Sadayappan, S., Ochala, J., Gundersen, K. and Millay, D. P. (2020). Nuclear numbers in syncytial muscle fibers promote size but limit the development of larger myonuclear domains. Nat Commun 11(1): 6287.
Deschenes, M. R. (2004). Effects of aging on muscle fibre type and size. Sports Med 34(12): 809-824.
Dos Santos, M., Backer, S., Saintpierre, B., Izac, B., Andrieu, M., Letourneur, F., Relaix, F., Sotiropoulos, A. and Maire, P. (2020). Single-nucleus RNA-seq and FISH identify coordinated transcriptional activity in mammalian myofibers. Nat Commun 11(1): 5102.
Janssen, I., Heymsfield, S. B., Wang, Z. M. and Ross, R. (2000). Skeletal muscle mass and distribution in 468 men and women aged 18-88 yr. J Appl Physiol (1985) 89(1): 81-88.
Keire, P., Shearer, A., Shefer, G. and Yablonka-Reuveni, Z. (2013). Isolation and culture of skeletal muscle myofibers as a means to analyze satellite cells. Methods Mol Biol 946: 431-468.
Lazure, F., Blackburn, D. M., Corchado, A. H., Sahinyan, K., Karam, N., Sharanek, A., Nguyen, D., Lepper, C., Najafabadi, H. S., Perkins, T. J., et al. (2020). Myf6/MRF4 is a myogenic niche regulator required for the maintenance of the muscle stem cell pool. EMBO Rep 21(12): e49499.
Neal, A., Boldrin, L. and Morgan, J. E. (2012). The satellite cell in male and female, developing and adult mouse muscle: distinct stem cells for growth and regeneration. PLoS One 7(5): e37950.
Ramachandran, K., Senagolage, M. D., Sommars, M. A., Futtner, C. R., Omura, Y., Allred, A. L. and Barish, G. D. (2019). Dynamic enhancers control skeletal muscle identity and reprogramming. PLoS Biol 17(10): e3000467.
Roman, W. and Gomes, E. R. (2018). Nuclear positioning in skeletal muscle. Semin Cell Dev Biol 82: 51-56.
Sahinyan, K., Blackburn D. M. and Soleimani V. D. (2022). Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution. eLife 11: e72792.
Wilson, J. M., Loenneke, J. P., Jo, E., Wilson, G. J., Zourdos, M. C. and Kim, J. S. (2012). The effects of endurance, strength, and power training on muscle fiber type shifting. J Strength Cond Res 26(6): 1724-1729.
Zhu, F., Farnung, L., Kaasinen, E., Sahu, B., Yin, Y., Wei, B., Dodonova, S. O., Nitta, K. R., Morgunova, E., Taipale, M., et al. (2018). The interaction landscape between transcription factors and the nucleosome. Nature 562(7725): 76-81.
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Sahinyan et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
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Molecular Biology > DNA > Chromatin accessibility
Systems Biology > Epigenomics
Developmental Biology > Cell growth and fate > Myofiber
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A Robust Nanoparticle-based Magnetic Separation Method for Intact Lysosomes
TL The Son Le
MT Mari Takahashi
SM Shinya Maenosono
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4453 Views: 2043
Reviewed by: Alessandro DidonnaAmberley D. Stephens Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in ACS Nano Jan 2022
Abstract
Lysosome isolation is a preresiquite for identifying lysosomal protein composition by mass spectroscopic analysis, to reveal lysosome functions, and their involvement in some diseases. Magnetic nanoparticle-based fractionation has received great attention for lysosome isolation, owing to its high efficiency, purity, and preservation of lysosomal structures. Understanding the intracellular trafficking of magnetic probes is the key point of this technique, to determine the appropriate time for magnetic isolation of lysosomes, because this parameter changes depending on different cell lines used. The traditional magnetic probes, such as superparamagnetic iron oxide nanoparticles (SPIONs), require surface modification by fluorescent dyes to enable the investigation of their intracellular trafficking, which has some disadvantages, including the possible alternation of their bio-interaction, and the instability of fluorescence properties in the lysosomal environment. To overcome those limitations, we present a protocol that employs magnetic-plasmonic nanoparticles (MPNPs) to investigate intracellular trafficking using their intrinsic imaging capability, followed by quick lysosome isolation using a magnetic column. This protocol can be easily applied to isolate the intact lysosomes of any adherent cell lines.
Graphical abstract:
Keywords: Lysosomes Nanoparticles Magnetic separation Plasmonic imaging Endocytosis Endolysosomal pathway Intracellular trafficking
Background
Since their discovery by Christian de Duve in the 1950s (De Duve et al., 1955), the role of lysosomes in cellular function has been explored extensively, which led to the change of the view of lysosomes from a static digestive system, to the dynamic regulator of cellular metabolism. As indicated in various studies, lysosomal dysfunctions are found to be linked with the group of metabolic disorders known as lysosomal storage diseases (Mukherjee et al., 2019). Therefore, understanding lysosomal biology in both normal and pathogenic conditions is crucial to figuring out the mechanistic insights of lysosomal activity, to facilitate diagnostic methods, or establish a new therapeutic strategy.
The rapid and efficient isolation of lysosomes is a prerequisite to identify lysosomal protein composition, using proteomic analysis to reveal their involvement in cellular functions or disease progression. So far, several strategies have been developed to isolate lysosomes, including density-gradient centrifugation, immunoaffinity purification, and magnetic nanoparticle-based fractionation. Among these approaches, a nanoparticle-based method that delivers magnetic nanoparticles to the lumen of lysosomes, through an endocytic pathway, followed by a separation process, using a magnetic column, has been proven to be able to isolate lysosomes with the highest yield and purity, while efficiently preserving their integrity (Singh et al., 2020).
The accurate understanding of intracellular trafficking of magnetic nanoparticles is a key step to prevent contamination by other organelles (i.e., endosomes) in the magnetic nanoparticles-based fractionation of lysosomes. Generally, SPIONs are used as magnetic probes, which generally requires employing fluorescent dye-based techniques to monitor their intracellular trafficking. However, it has been suggested that the lysosomal environment could lead to quenching and/or distortion of fluorescence dye signals, which may cause an ensuing effect on the interpretation of the data (Milosevic et al., 2017). In addition, the surface modification of nanoparticles with dye molecules may influence the nano-bio interactions, which results in the alteration of the cellular uptake and intracellular trafficking of nanoparticles (Snipstad et al., 2017; Thomsen et al., 2021). Herein, to further refine the magnetic nanoparticle-based fractionation, the magnetic-plasmonic Ag/FeCo/Ag core/shell/shell nanoparticles (MPNPs) are used as multifunctional probes for lysosome isolation. Owing to their plasmonic properties, the intracellular trafficking of MPNPs can be easily investigated using confocal laser scanning microscopy, to confirm the accumulation of MPNPs in lysosomes, prior to magnetic isolation.
This protocol outlines the optimized procedures for preparation of MPNPs, intracellular trafficking study of MPNPs, and magnetic isolation of lysosomes. The time required for completing magnetic isolation of lysosomes after cell homogenization is within 30 min, which is significantly shorter than that of the density-gradient centrifugation technique. The amount of protein obtained was sufficient for mass spectroscopy, to identify protein composition. More importantly, this protocol was demonstrated to be easily adaptable to other adherent cell lines (Le et al., 2022).
Materials and Reagents
Glass syringe with lock tip 2 mL (Cadence Science, Stock Keeping Unit: 2407)
Glass syringe with lock tip 5 mL (Cadence Science, Stock Keeping Unit: 2417)
Stainless steel 304 syringe needle, noncoring point 2 inch 12G (Sigma-Aldrich, catalog number: Z116947-1EA)
Stainless steel 304 syringe needle, noncoring point 6 inch 20G (Sigma-Aldrich, catalog number: Z102709-1EA)
Centrifuge tube 50 mL (AS One, catalog number: 2-3939-03)
Microtube 1.5 mL (AS One, L-2057)
VIOLAMO 5 mL tube (AS One, catalog number: 2-4118-01)
Centrifuge tube 15 mL (AS One, catalog number: 1-3500-21)
Round cover glass Φ12mm No.1 (Matsunami, catalog number: C012001)
White slide glass edge grinding S1111 (AS One, catalog number: 2-154-01)
Terumo syringe with needle 2.5 mL 23G blue (AS One, catalog number: 1-2044-03)
Parafilm membrane (Amcor, Parafilm M, catalog number: PM996)
CELLect® Fetal bovine serum, 500 mL (FBS; MP Biomedicals, catalog number: 2917354H)
High-purity Ar gas, >99.9999 vol.%
Cobalt (II) acetylacetonate, 97% (Co precusor; Sigma-Aldrich, catalog number: 227129-50G)
Iron (III) acetylacetonate, 99.99% (Fe precusor; Sigma-Aldrich, catalog number: 517003-50G)
Silver nitrate, 99.9999% (Ag precusor; Sigma-Aldrich, catalog number: 204390-10G)
1,2-hexadecanediol, 90% (Sigma-Aldrich, catalog number: 213748-50G)
Oleylamine, 70% (Sigma-Aldrich, catalog number: O7805-500G), stored at 4°C
Oleic acid, 90% (Sigma-Aldrich, catalog number: 364525-1L), stored at 4°C
Tetraethylene glycol (Sigma-Aldrich, catalog number: 110175-1KG)
Acetone, 99.5% (Kanto Chemical, catalog number: 01026-70)
Hexane, 96% (Kanto Chemical, catalog number: 18041-70)
Chloroform, 99% (Kanto Chemical, catalog number: 07278-70)
Toluene, 99% (Wako Pure Chemical, catalog number: 201-01871)
1,2-dioleoyl-sn-glycerol-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-350] (PEG350-DOPE; Avanti, catalog number: 880430O-25MG), stored at −20°C
1,2-dioleoyl-sn-glycerol-3-phosphoethanolamine-N-(glutaryl) (18:1 Glutaryl PE; Avanti, catalog number: 870242C-25MG), stored at -20°C
2-morpholinoethanesulfonic acid, monohydrate, (MES; Dojindo, catalog number: 341-01622)
N-hydroxysuccinimide (NHS; Thermo Fisher Scientific, catalog number: 24500), stored at 4°C
Ethyl-3-(3-dimethyl aminopropyl) carbodiimide (EDC; Dojindo, catalog number: 346-03632), stored at 4°C
Amino dextran, MW. 10,000 (aDxt; Thermo Fisher Scientific, catalog number: D1860), stored at 4°C
Dulbecco’s phosphate buffer (PBS; Nissui Pharmaceutical, catalog number: 05913), stored at 4°C
Dulbecco’s modified Eagle’s medium (DMEM; Nacalai Tesque, catalog number: 08456-36), stored at 4°C
COS-1 cells (available from American Type Culture Collection, catalog number: CRL-1650)
Poly-L-lysine (PLL) solution, 0.01% (Sigma-Aldrich, catalog number: P4832-50ML)
4%-paraformaldehyde phosphate buffer, 500 mL (PFA; Nacalai Tesque, catalog number: 09154-85), stored at 4°C
Digitonin (Wako Pure Chemical, catalog number: 043-21376), stored at 4°C
Ammonium chloride (NH4Cl, Wako Pure Chemical, catalog number: 015-02991)
Bovine serum albumin (BSA; Sigma-Aldrich, catalog number: A8022-50G), stored at 4°C
Alexa Fluor® 647 mouse anti-human CD107A (AF647@CD107A; BD Biosciences, catalog number: 562622), stored at 4°C
4’,6-diamidino-2-phenylindole (DAPI; Thermo Fisher Scientific, catalog number: D1306), stored at 4°C
VECTASHIELD® Antifade mounting medium (Vector Laboratories, catalog number: H-1700), stored at 4°C
MES buffer (0.1 M, pH ~6) (see Recipes)
PBS buffer (see Recipes)
Digitonin solution (see Recipes)
Ammonium chloride solution (see Recipes)
DAPI staining solution (see Recipes)
Protease inhibitor solution (PIS) (see Recipes)
Note: The specific storage temperatures are indicated. Otherwise, chemicals are stored at room temperature (RT).
Equipment
Analytical balance (Sartorius, model: ME253P)
Three-neck round bottom flask 50 mL with angled side necks, center joint: ST/NS 29/42, side joints: ST/NS 15/25 (Tokyo Garasu Kikai, catalog number: 371-13-06-01)
Strong magnetic stirrer oval Φ12 × 25 mm (AS One, catalog number: 4-2687-04)
Laboran screw tube bottle 13.5 mL (glass vials; AS One, catalog number: 9-852-06)
Liebig condenser 300 mm, bottom joint: 29/42, top joint: 19/38 (Tokyo Garasu Kikai, catalog number: 330-15-51-14)
Digital high accuracy temperature controller (AS One, TJA-550, catalog number: 1-6124-01)
Mantle heater 50 mL (Tokyo Technological Labo, model: S-05)
High power stirrer (AS One, HPS-100, catalog number: 1-4136-01)
Flowmeter (Kofloc, model: RK1250)
Septum rubber, white, natural, for 18 mm tube (FUJIFILM Wako Pure Chemical, catalog number: 195-11771, Japanese Article Number: 4987481378957)
FisherbrandTM Pasteur pipets (Fisher Scientific, catalog number: 22-063156)
Double element thermocouple WK-Φ3.2×200 (AS One, catalog number: 3-9391-14)
Trap sphere, top and bottom joints: 29/42 (Tokyo Garasu Kikai, catalog number: 330-15-91-07)
Refrigerated centrifuge (Kubota, model: 5910 (with RS-410M rotor))
Ultraviolet-visible absorption spectrophotometer (JASCO, model: V-750)
Two-neck round bottom flask 50 mL with an angled side neck, center joint, and side joints: 14/24
TS one-neck round bottom flask 100 mL,15/25, with the glass stopper (Climbing Co., ltd., CL0070-05-11)
Sonicator (AS One, Ultrasonic Cleaner ASU-6, oscillation frequency: 40 kHz)
High-speed micro centrifuge (Hitachi Koki, model: Himac CF15RXII (with T16A31 rotor))
Ultracentrifuge (Eppendorf Himac Technologies, model: CS100FNX (with S100AT4-2004 rotor))
37°C and 5% CO2 incubator (ESPEC, model: BNA-111)
Confocal laser scanning microscope (CLSM; Olympus, model: FV1000D)
Cell Lifter (Corning, product number: 3008)
MidiMACS separator starting kits (Miltenyi Biotec, catalog number: 130-042-301)
MS Column (Miltenyi Biotec, catalog number: 130-042-201)
High-speed refrigerated micro centrifuge [Tomy Seiko, model: MDX-310 (with AR015-24 rotor)]
Software
Fiji (NIH/https://imagej.net/software/fiji/), with color clustering and coloc 2 plugins
Procedure
Preparation of MPNPs, by a combination of a polyol, and a one-pot synthesis
Note: The details on the formation mechanism of MPNPs using this method can be found in Takahashi et al. (2015).
The glassware for synthesizing MPNPs were shown in Figure 1.
Figure 1. Glassware for preparation of MPNPs.
(A) Trap sphere, (B) Three-neck round bottom flask, (C) Liebig type reflux condenser, (D) Glass syringes with needles, (E) Clamp, (F) Oval magnetic stir bar, (G) Pasteur pipette, (H) Glass vials, (I) Septum rubbers, (J) Needle, and (K) Thermocouple.
Weigh 0.1 mmol of silver nitrate, and 1.0 mmol of 1,2-hexadecanediol.
Place an oval magnetic stir bar in the three-neck round bottom flask, and transfer the weighed silver nitrate followed by 1,2-hexadecanediol into the flask. Then, sequentially, add 10 mL of tetraethylene glycol, 10 mmol (3.29 mL) of oleylamine, and 8 mmol (2.55 mL) of oleic acid, using a pipette.
Note: After removing oleyamine and oleic acid bottles from the refrigerator, place them into a water bath at 35°C until completely melted, then take the required volume using a pipette.
Prepare two 13.5-mL glass vials.
Weigh 0.2 mmol of cobalt (II) acetylacetonate, and 0.2 mmol of iron (III) acetylacetonate. Transfer them to a glass vial labeled as Co and Fe precursors. Then, sequentially, add 2 mL of oleylamine, and 1 mL of toluene.
Weigh 0.1 mmol of silver nitrate, and transfer it to the remaining glass vial labeled as Ag precursor. Then, sequentially, add 1 ml of oleylamine, and 1 mL of toluene.
Seal the caps of the two vials with a parafilm membrane, and place them in a sonicator with High Power Mode, for complete dissolution of all the reagents.
Note: To dissolve the reagents quickly, the vials could be warmed at approximately 40°C during this process. There is no time limit for this step, but they should be ready before the injection steps.
Prepare two septums, as shown in Figure 2.
Note: Use the 12G-needle to make a hole, to insert the Pasteur pipette into the rubber septum. Adding some ethanol to the hole makes the insertion easier. Ethanol will evaporate after insertion.
Figure 2. The septum rubbers prepared for Ar bubbling. Later on, the needle is removed from the septum (top) to insert a thermocouple.
Place the three-neck round bottom flask containing the raw reaction materials (prepared in Step A2) on the mantle heater.
Connect the trap sphere to the center neck of the flask, and hold them with a clamp. Then, plug in the condenser tube, and connect the other end of the condenser to a trapper containing liquid paraffin (Figure 3).
Note: The reflux condenser uses air without running water.
Figure 3. The illustration (A) and photograph (B) of the experimental setup for preparing MPNPs.
Seal the two remaining open necks using the septums shown in Figure 2.
Note: The tip of the Pasteur pipette for Ar bubbling should be dipped into reaction solution, but not touch the magnetic stir bar.
Turn on the magnetic stirrer at a speed of 150 rpm, and pump in Ar gas through the Pasteur pipette, at a flow rate of 0.35 L/min. The gas flows out through the 12G-needle. Leave it for 5 min, to complete the replacement of the atmosphere in the flask with Ar gas.
Remove the needle, and insert a thermocouple.
Turn on the temperature controller, and set the temperature to 100°C.
Note: Due to the high viscosity of the solution at RT, the stirring speed cannot be set immediately at 500 rpm. Therefore, while the temperature increases, increase the stirring speed slowly. At 50°C, the stirring speed could be fully set at 500 rpm. The heating rate of this step is about 12−13°C/min.
From the moment the temperature reaches 100°C, maintain it for 10 min. During this step, the silver seeds are formed.
Note: Overheating may be observed, in which the temperature is elevated above 100°C. Slightly lowering the heating mantel to reduce its contact with the flask will reduce the temperature.
After 10 min, increase the temperature to 250°C, by setting the temperature controller at 300°C.
Note: The purpose of this setting is to linearly rise the temperature up to 250°C (Figure 4).
Figure 4. Temperature profile of the preparation process of MPNPs.
During the temperature increase, once it reaches 170°C, inject the pre-prepared mixture of Fe and Co precursors, using a glass syringe and 20 G-needle.
Note: The needle is inserted via the septum containing the thermocouple. Inject the solution drop by drop at a fast pace, for a duration of 1 min. The temperature should be kept around 170°C, by slightly lowering the heating mantle to reduce contact with the flask. The heating rate from 100°C to 170°C is about 12°C/min.
Once the temperature reaches 250°C, inject the pre-prepared Ag precursor using a glass syringe and another 20G-needle. Then, immediately reset the temperature of the controller to 230°C. Maintain the reaction for 10 min.
Note: This is the most important step. The injection of Ag precursor is normally done in about 20 s. It should not be less than 10 s, or longer than 30 s. After the injection, slightly lower the heating mantle to reduce contact with the flask to avoid overheating. We confirmed that reaction time can be prolonged to 15 min, but the quality of the MPNPs was not influenced. The heating rate from 170°C to 250°C is about 9°C/min.
Set the temperature controller to 0°C to stop heating, and remove the mantle heater. Wait for the reaction system to cool off naturally, while continuing stirring and Ar bubbling. At this time, some of the synthesized particles will be attached to the magnetic stirring bar, but they will be redispersed again during the cooling process.
Once the temperature of the reaction solution is less than 70°C, stop Ar gas flow, and turn off the magnetic stirrer.
Carefully disassemble the setup, and use a pipette to transfer the reaction solution from the three-neck flask to two 50-mL centrifuge tubes evenly.
Add acetone, to fill the tube to 45 mL. Then, perform centrifugation using a Kubota 5910 at 4,640 × g and RT for 5 min.
Discard all supernatant, and add 400 µL of hexane to each tube, for redispersion of MPNPs.
Use a micropipette to transfer 200 µL of redispersed MPNP solution to two other 50-mL tubes. Subsequently, fill with acetone up to 45 mL in total, and perform centrifugation using Kubota 5910 at 4,640 × g and RT for 5 min.
Discard the supernatant, and redisperse the obtained MPNPs in 3 mL of chloroform. Determine the concentration of MPNP dispersion through the absorption spectrum, using an ultraviolet-visible absorption spectrophotometer.
Note: The concentration of MPNPs was determined using a calibration curve of y = 0.024x, where y was the absorption peak value of localized surface plasmon resonance of MPNPs, and x was the concentration of MPNPs (µg/mL).
Store obtained MPNPs in chloroform at 4°C, in a glass vial with closed-top cap. Seal it with Parafilm.
Encapsulation of MPNPs in PEGylated phospholipids
Prepare a 50-mL two-neck round bottom flask (Figure 5A).
Pour 3 mL of MPNPs dispersed in chloroform at a concentration of 1 mg/mL into the flask. Subsequently, add 1,350 µL of 18:1 glutaryl PE (5.5 mM) in chloroform, and 900 µL of PEG350-DOPE (5.5 mM) in chloroform to the dispersion.
Seal using septum rubbers, place the septum containing the Pasteur pipette in the center neck, and the septum containing the needle in the angled neck.
Note: The tip of the Pasteur pipette should not dip in the dispersion.
Pump in Ar gas at a rate of 0.5 L/min, to completely evaporate the chloroform (Figure 5B).
Note: In this step, the inert gas could be either Ar or N2.
Figure 5. The glassware (A) and the experimental setup (B) for encapsulation of MPNPs in PEGylated phospholipids.
Add 1.5 mL of deionized water to redisperse the obtained precipitation. Collect the dispersion into two 1.5-mL centrifuge tubes.
Centrifuge at 1,400 × g and RT for 5 min, using the Hitachi CF15RXII high-speed micro centrifuge, to eliminate big aggregated particles.
Carefully transfer the supernatant from the centrifugated tubes into two new 1.5-mL tubes. Then, centrifuge at 86,600 × g and 4°C for 10 min, using the CS100FNX ultracentrifuge, to remove empty micelles.
Note: In this step, if the MPNPs were not completely collected, increase the centrifugation speed up to 100,000 × g.
Discard the supernatant, and redisperse the obtained particles in 1 mL of deionized water.
Determine the concentration of phospholipid encapsulated MPNPs from the absorption spectrum.
Conjugation of aDxt using EDC coupling reaction
Add 20 mL of MES buffer (pH ~6) to a 100-mL one-neck round bottom flask, containing a magnetic stirrer.
Set the magnetic stirrer to 600 rpm.
Add 1 mL of phospholipid encapsulated MPNPs dispersion (1 mg/mL) into the flask. Then, sequentially add 125 µL of EDC (200 mM) in deionized water, and 250 µL of NHS (200 mM) in MES buffer. Leave it at RT for 30 min.
Note: After taking them out from the refrigerator, equilibrate the EDC and NHS to RT before use.
Transfer the obtained reaction mixture into 20 × 1.5-mL tubes.
Centrifuge at 86,600 × g and 4°C for 10 min, using the CS100FNX, and carefully remove the supernatant.
Use a micropipette to collect, and redisperse the obtained particles in 1 mL of PBS.
Prepare a 100-mL one-neck round-bottom flask, containing 19 mL of PBS.
Add 50 mg of aDxt into the PBS solution in the flask (prepared in Step C7), and wait for it to completely dissolve under magnetic stirring.
Add the PBS dispersion of MPNPs (prepared in Step C6) into the PBS solution of aDxt (prepared in Step C8). Then, maintain the reaction at RT for 90 min.
Transfer the obtained mixture to 20 × 1.5-mL tubes. Then, perform centrifugation at 60,000 × g and 4°C for 10 min, using the CS100FNX. Collect, and redisperse the obtained particles in 1 mL of PBS.
Determine the concentration of aDxt-conjugated MPNPs (aDxt-MPNPs) in the dispersion, using the absorption spectrum.
Pulse-chase experiments for studying intracellular trafficking of MPNPs
Notes:
In a pulse-chase experiment, the pulse is the incubation of aDxt-MPNPs with COS-1 cells for a certain period (tload). After the loading step, the excess amount of aDxt-MPNPs that are not incorporated in the cells is removed. Cells are further incubated in a fresh culture medium for a given period, tchase. The purpose of this experiment is to find the optimal tchase, for aDxt-MPNPs to reach lysosomal compartments through the endolysosomal pathway.
These experiments are performed on a clean bench under sterile conditions.
Place 10–20 sterilized round cover glasses into a 10-cm culture dish.
Add 5 mL of 0.01% PLL solution into the 10-cm dish, and dip the round cover glasses in PLL solution at RT for 5 min, using a tweezer.
Remove the PLL solution, cover with aluminum foil, with the foil partially opened, and naturally dry overnight on a clean bench.
The next day, wash the PLL coated cover glasses three times, using 5 mL of PBS buffer.
Place the four cover glasses in each well of a 24-well plate using a tweezer, which correspond to different tchase values of 1 h, 2 h, 4 h, and 7 h.
Note: The number of cover glasses increases according to the number of investigated tchase. In the case of COS-1 cells, the maximum tchase was performed at 7 h. However, it should be noted that the length of tchase depends on different cell lines. Therefore, the incubation time of this experiment could be customized easily.
Seed 20,000 COS-1 cells/well and incubate overnight in DMEM (+10% FBS) at 37°C under 5% CO2.
Check the health and confluency of cells, under a bright-field microscope (Keyence, model: BZ-X810) in advance.
The next day, remove the culture medium, and wash cells with 500 µL of PBS at RT.
For cell starvation, add 0.5 mL of pre-warmed DMEM without FBS, and incubate for 30 min at 37°C under 5% CO2.
Approximately 10 min before finishing the starvation process, add MPNPs to DMEM (+10% FBS), to prepare a dispersion of MPNPs with the concentration of 100 µg/mL.
Immediately affter starvation, replace DMEM without FBS with 500 µL of MPNPs dispersion in DMEM (+10% FBS) (prepared in Step D10), and incubate for tload = 1 h at 37°C under 5% CO2.
After 1 h incubation, remove the dispersion, and wash with 500 µL of PBS once. Then, add 500 µL of pre-warmed DMEM (+10% FBS), and incubate for tchase: 0 h, 2 h, 4 h, and 7 h at 37°C under 5% CO2.
Note: The tchase would be varied in different cell lines. Therefore, the incubation period could be customized appropriately.
After completing the tchase, wash with 500 µL of PBS three times, and add 500 µL of 4% PFA at RT to each well for 15 min.
Note: Since PFA is a toxic chemical, personnel must wear a lab coat and chemically protective gloves. This step should be performed in a clean bench equipped with a ventilation system and a protective sash. Additionally, keep PFA solution away from flame or heat sources. The PFA should be properly disposed of as hazardous waste. After fixation, the following steps could be performed outside the clean bench. The sterile conditions are not required.
Wash with 500 µL of PBS three times, add 500 µL of 50 µg/mL digitonin-PBS for permeabilization to each well, and wait for 5 min.
Wash with 500 µL of PBS three times, add 500 µL of 50 mM NH4Cl-PBS to each well, and wait for 10 min.
Wash with 500 µL of PBS three times, and perform blocking by adding 500 µL of 3 wt% BSA-PBS to each well, and waiting for 30 min.
For each well, add 500 µL of 3 wt% BSA-PBS containing 2 µL of AF647@CD107A for staining the lysosomes, and 0.25 µL of 100 µg/mL DAPI for staining the nuclei. Wait at RT for 1 h, or keep it at 4°C overnight.
Wash with 500 µL of PBS three times. For each washing step, wait for 5 min after adding PBS.
Add a drop of antifade mounting medium onto a white slide glass edge grinding, carefully take the cover glass using tweezers, and place it onto the glass substrate for observation with the cell-facing surface in contact with the mounting medium. Ensure there are no bubbles and remove extra fluid if necessary.
Leave it in a dark place for several hours until it is completely dry. Then, observe the samples using a CLSM.
Observation of MPNPs-loaded cells under CLSM
Select 405, 473, and 635 nm lasers for the excitation of DAPI, aDxt-MPNPs, and AF647, respectively.
For DAPI dye, select the barrier filter (BA) 435–455 nm.
For plasmonic scattering signal of aDxt-MPNPs, select no barrier filter, as, unlike the fluorescent dye, the scattering signal from aDxt-MPNPs has the same wavelength as the laser wavelength.
For AF647 dye, select BA 655–755 nm.
Capture CLSM images of more than five different randomly-selected regions. Record DAPI signal separately to plasmonic scattering signal and AF647 fluorescence (Figure 6).
Perform colocalization analysis of aDxt-MPNPs and lysosomes, by determining the threshold Manders’ colocalization coefficient (Rt), using ImageJ software.
Figure 6. CLSM images of aDxt-MPNP-loaded COS-1 cells at different tchase values of 0 h, 2 h, 4 h, and 7 h, captured by CLSM (scale bar: 20 µm). Nuclei (blue) and lysosomes (red) are stained by DAPI and AF647, respectively, as described in the text. aDxt-MPNPs were observed by plasmonic scattering signals. The merged images were obtained using ImageJ. Adapted with permission from Le et al. (2022). Copyright 2022 American Chemical Society.
Accumulation of aDxt-MPNPs to lysosomes, homogenization, and magnetic isolation of lysosomes
Seed 2 × 106 COS-1 cells/dish for two 10-cm dishes, and incubate in DMEM (+10% FBS) for 24 h.
Check the health and confluency of cells under a bright-field microscope (Keyence, model: BZ-X810) in advance.
Note: The health of COS-1 cells was checked by confirming their adherent status on a cell dish, using bright-field microscopy. In addition, the possibility of contamination was also checked at the same time. The confluency of cells was estimated to be less than 80% in this particular experiment. However, it would change depending on the cell type. The desired confluency of cells would be ranging from 70% to 80%. If cells are well adhered on the dish without being contaminated, and with around 70-80% confluency, one can go to the next step.
For cell starvation, add 5 mL of pre-warmed DMEM without FBS to each cell dishes, and incubate at 37°C under 5% CO2 for 30 min.
About 10 min before finishing the starvation process, add MPNPs to DMEM (+10% FBS), to prepare a 10-mL of dispersion of MPNPs, with a concentration of 100 µg/mL.
Immediately after starvation, replace DMEM without FBS with 5 mL of MPNPs dispersion in DMEM (+10% FBS) (prepared in Step F4) to each cell dish, and incubate at 37ºC under 5% CO2 for 8 h.
Note: In this study, we chose the tload = 8 h for loading. tload strongly affects the isolation yield of lysosomes. This parameter could be prolonged depending on the cytotoxicity of MPNPs to the cells.
Discard the aDxt-MPNPs containing medium, and wash with pre-warmed PBS once.
Add 5 mL of DMEM (+10% FBS), and incubate further for tchase = 7 h. The optimal tchase has been already determined in the pulse-chase experiment section. Depending on the cell type, this parameter may vary.
Place necessary equipment, including the magnetic column, MidiMACS separator, 2.5-mL syringe with 23G-needle (Terumo syringe with needle 2.5 mL 23G blue), and 5-mL tubes, into the cold room, where the temperature is maintained at 4°C, for at least 30 minutes before the pulse-chase experiment, to equilibrate the temperature. If a cold room is not available, use an ice-box to store the equipment instead.
Discard the medium, and wash the cells with PBS.
Add 1.5 mL of cold PBS to each culture dish, and place them on ice.
Scrape off the cells using a Cell Lifter, and transfer them from both culture dishes to a 15-mL centrifuge tube. Centrifuge at 190 × g and 4°C for 4 min, using the Kubota 5910 with a ST-720 swinging bucker rotor.
Note: In this step, the amount of particle uptake could be qualitatively evaluated via the color of the cell pellet (Figure 7). The darker the color, the higher number of particles internalized. If the cell color is still white, it means a very low uptake efficiency. The isolation of lysosomes may fail.
Discard the supernatant, and add 1 mL of ice-cold PIS to re-suspend the cell pellet. Then, transfer to a 5-mL tube, and keep in an icebox.
Note: After this step, the experiments are continued in a low-temperature room, where the temperature is maintained at 4°C.
Figure 7. A photograph of aDxt-MPNPs loaded COS-1 cells with tload = 8 h and tchase = 7 h.
Use a 2.5-mL syringe with a 23G-needle, and repeatedly (15 passages) pass the cell suspension through the syringe, to homogenize the cells.
Note: The optimal number of passages must be determined experimentally (Figure 8). The low homogenization efficiency could obviously affect the yield of lysosome isolation. In contrast, homogenization efficiency enhanced by increasing the number of passages may also lead to lysosomes being broken. Therefore, in this study, a small portion of unbroken cells or large cell fragments is left over.
Figure 8. The bright-field image of COS-1 cells under phase contrast mode. Before (A) and after (B) homogenization using a syringe with a 23G-needle (15 passages). Before homogenization, cells can clearly be seen as a high density of dark areas encircled by bright halos. After homogenization, the number of cells is reduced, and the cell mixture becomes a slurry, due to the breaking of the cell membranes. Consequently, the number of bright halos decreases significantly. A small portion of either unbroken cells or large cell fragments in the slurry can still be observed. Scale bar, 100 µm.
Place an MS Column in a MidiMACS separator.
Note: Another type of MACS® Column, such as LS Column, could also be used in this experiment.
Equilibrate the MS Column, by adding 1 mL of PIS. Discard the flow-through.
Transfer the cell lysate (prepared in Step F13) to the MS Column, using the micropipette, and allow the cell lysate to pass through the column. The magnetic fraction will be trapped inside the column, while the nonmagnetic fraction will pass through the column.
Discard the flow through. Wash the column using 1 mL of PIS twice, to further eliminate unbound materials.
Remove the MS Column from the MidiMACS separator.
Add 0.5 mL of PIS, and insert the plunger to collect the magnetic fraction containing lysosomes in a 1.5-mL microtube. Repeat this step once again.
Centrifuge the obtained suspension at 5,000 × g and 4°C for 10 min, using an MDX-310 system.
Note: This step is to remove the remaining soluble proteins in the isolated fraction.
Discard the supernatant, and redisperse the obtained lysosome pellet in 100 µL of PIS.
Note: If the isolated lysosome fraction is subjected to proteome analysis, re-suspend the pellet in 50 mM triethylammonium bicarbonate.
Data analysis
The colocalization analysis of aDxt-MPNPs and lysosomes is performed using ImageJ. First, open the image, then choose “Plugin” → “Segmentation” → “Color Clustering”. Afterward, in the new window, in the “Channel” section, choose the appropriate color for the image. For this specific case, the illustrated colors of aDxt-MPNPs and lysosomes are green and red, respectively. Next, press “Run”, and then choose “Show result” to obtain the segmented image. Note that only one image of either aDxt-MPNPs or lysosomes can be processed at once (Figure 9). After obtaining segmented images, the Rt represents the percentage of lysosomes overlapped with aDxt-MPNPs. To open color clustered images of aDxt-MPNPs and lysosomes, select “Analyze” → “Colocalization” → “Coloc 2”. In the new window, choose the image of aDxt-MPNPs for channel 1, and the image of lysosomes for channel 2, then check the Manders’ correlation box, and press OK (Figure 10). Repeat this step for five pairs of images from each experimental condition.
Figure 9. Segmentation of CLSM images using color clustering. (A) Select “Plugin” > “Segmentation” > “Color Clustering”. (B) For an aDxt-MPNP image, the illustrated color of nanoparticles is green, therefore, select green (in the channel section), and click “Run”. Repeat this step for the CLSM image of stained lysosomes, and select the appropriate color for segmentation accordingly.
Figure 10. The process to determine the Rt using Coloc 2 plugin in ImageJ software. (A) Open two segmented images in the previous steps, select “Analyze” > “Colocalization” > “Coloc 2”. (B) In the new window, select images for channel 1 and channel 2. Then, check the Manders’ correlation box, and click OK.
After completing the image analysis, a graph of Rt-versus-incubation time can be constructed (Figure 11A). The incubation time is the sum of tload and tchase. As aDxt-MPNPs are transported to lysosomes, the Rt value increases. However, due to the limited spatial resolution of the CLSM image, the Rt value is saturated. From this graph, the value tchase can be determined. Normally, the tchase is chosen after one time when Rt reaches a plateau. The reasoning behind this is that, in the endolysosomal pathway, late-endosomes are fused with lysosomes, which could also result in the high colocalization of aDxt-MPNPs with lysosomes. However, it is recommended that, after obtaining the isolated lysosome fraction, the level of late endosomes should be evaluated using Western blot analysis (Figure 11B). If the late endosome still exists, a further prolonged tchase is necessary.
Figure 11. Time-lapse colocalization of aDxt-MPNPs with lysosomes and Western blot of cell lysate, PS, and NS fractions. (A) The graph of Rt-versus-incubation time. The accumulation of aDxt-MPNPs in lysosomes is indicated by the increase of Rt over time. (B) A western blot of the isolated lysosome fraction. PS: positive selection (magnetic fraction); NS: negative selection (nonmagnetic fraction); GAPDH: glyceraldehyde-3-phosphate dehydrogenase (cytosolic protein as a control); LAMP2: lysosomal associated membrane protein 2 (lysosome marker), Rab7: late endosome marker protein. Adapted with permission from Le et al. (2022). Copyright 2022 American Chemical Society.
Recipes
MES buffer (0.1 M, pH ~6)
Dissolve 3.90 g MES in 180 mL of deionized water. Monitor the pH of the solution using a pH meter, then take 10 N sodium hydroxide aqueous solution using a micropipette, to adjust the pH of the solution to approximately 6. Then, add water up to 200 mL. Sterilize the solution by filtration through a 0.2-µm filter before use. Store in a dark colored bottle.
PBS buffer
Dissolve 9.6 g of PBS in 1 L of deionized water. The solution should be sterilized by an autoclave before use. Store the solution at 4°C.
Digitonin solution
Dissolve 25 mg of digitonin in 500 µL of dimethyl sulfoxide (DMSO). Divide the solution into microtubes, at 15 µL/tube. Store the solution at -20°C. It is diluted with PBS, for permeabilization.
Ammonium chloride solution
Dissolve 0.160 g NH4Cl in 60 mL of PBS buffer. Store the solution at 4°C.
DAPI staining solution
From the commercial product, prepare the DAPI stock solution with a concentration of 100 µg/mL, store in the refrigerator at 4°C. For nucleus staining, dilute the stock solution 2000 times further.
Protease inhibitor solution (PIS)
Prepare 20 mL of PBS in a 50-mL tube.
Add 20 μL of 0.1 M phenylmethylsulfonyl fluoride and 100 µL of protease inhibitor cocktail to the tube. The dilution factor is about 1000× and 200× for phenylmethylsulfonyl fluoride and protease inhibitor cocktail, respectively.
Disperse the solution homogeneously using a vortex. Then, keep the solution in an ice box.
Note: This solution should be prepared at the time of use. Long-term storage is not recommended. The composition of the inhibitor cocktail is: 0.1 mg/mL leupeptin hemisulfate monohydrate; 0.14 mg/mL pepstatin A; 14 mg/mL N-p-tosyl-L-phenylalanine chloromethyl ketone; 15 mg/mL Nα-p-tosyl-L-arginine methyl ester hydrochloride; 0.4 mg/mL aprotinin; 32 mg/mL benzamidine dissolved in DMSO. The inhibitor cocktail can be prepared in advance and stored in small tubes at -20°C.
Acknowledgments
This protocol is derived from the original research paper, Le et al. “Quick and Mild Isolation of Intact Lysosomes Using Magnetic−Plasmonic Hybrid Nanoparticles” ACS Nano 2022 Jan 3; 16(1): 885–896. doi: 10.1021/acsnano.1c08474 (Le et al., 2022). This work was partly funded by the Grant-in-Aid for Young Scientists from the Japan Society for the Promotion of Science (grant no. 21K14506) to M.T.
Competing interests
The authors declare no competing interests.
Ethics
No human or vertebrate animal subjects are used in this study.
References
De Duve, C., Pressman, B. C., Gianetto, R., Wattiaux, R. and Appelmans, F. (1955). Tissue fractionation studies. 6. Intracellular distribution patterns of enzymes in rat-liver tissue. Biochem J 60(4): 604-617.
Le, T. S., Takahashi, M., Isozumi, N., Miyazato, A., Hiratsuka, Y., Matsumura, K., Taguchi, T. and Maenosono, S. (2022). Quick and Mild Isolation of Intact Lysosomes Using Magnetic–Plasmonic Hybrid Nanoparticles. ACS Nano 16(1): 885-896.
Milosevic, A. M., Rodriguez-Lorenzo, L., Balog, S., Monnier, C. A., Petri-Fink, A. and Rothen-Rutishauser, B. (2017). Assessing the Stability of Fluorescently Encoded Nanoparticles in Lysosomes by Using Complementary Methods. Angew Chem Int Ed Engl 56(43): 13382-13386.
Mukherjee, A. B., Appu, A. P., Sadhukhan, T., Casey, S., Mondal, A., Zhang, Z. and Bagh, M. B. (2019). Emerging new roles of the lysosome and neuronal ceroid lipofuscinoses. Mol Neurodegener 14(1): 4.
Singh, J., Kaade, E., Muntel, J., Bruderer, R., Reiter, L., Thelen, M. and Winter, D. (2020). Systematic Comparison of Strategies for the Enrichment of Lysosomes by Data Independent Acquisition. J Proteome Res 19(1): 371-381.
Snipstad, S., Hak, S., Baghirov, H., Sulheim, E., Morch, Y., Lelu, S., von Haartman, E., Back, M., Nilsson, K. P. R., Klymchenko, A. S., et al. (2017). Labeling nanoparticles: Dye leakage and altered cellular uptake. Cytometry A 91(8): 760-766.
Takahashi, M., Higashimine, K., Mohan, P., Mott, D. M. and Maenosono, S. (2015). Formation mechanism of magnetic–plasmonic Ag@FeCo@Ag core–shell–shell nanoparticles: fact is more interesting than fiction. CrystEngComm 17(36): 6923-6929.
Thomsen, T., Ayoub, A. B., Psaltis, D. and Klok, H. A. (2021). Fluorescence-Based and Fluorescent Label-Free Characterization of Polymer Nanoparticle Decorated T Cells. Biomacromolecules 22(1): 190-200.
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Quality Control and Preprocessing of Sequencing Reads
ZH Zhiqiang Hao
XL Xiaojuan Liang
GL Guanglin Li
Published: Jul 5, 2022
DOI: 10.21769/BioProtoc.4454 Views: 2505
Reviewed by: Prashanth N SuravajhalaGuotian LiJinfeng Chen
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Abstract
Quality control and preprocessing of sequences are essential before analyzing high-throughput sequence data. After raw read data is generated from high-through sequencing platforms, quality control and preprocessing of sequencing reads should be implemented, for clean data to be produced for subsequent bioinformatic analysis. Different tools have been developed for this, such as FastQC, iTools, fastp, cutadapt, and FASTX. However, the usage of these approaches is difficult for first time users. To address this, transcriptome data from Illumina Hiseq 2000 paired end sequencing in the model plant Arabidopsis thaliana were used as a practical case, to show the functions and usages of these tools, which are used widely and have many features, such as good performance, wide applicability, high speed, and low requirements. For example, FastQC provides a modular set of analyses on quality control checks and gives a quick overview to show in which areas there may be problems. iTools integrates algorithms and abundant sub-functions and provides a solid foundation for special demands. Cutadapt finds and removes adapter sequences, primers, poly-A tails, and other types of unwanted sequences from high-throughput sequencing reads. Fastp provides fast all-in-one preprocessing for FastQ files, and has high performance. FASTX provides a series of functions for preprocessing reads before mapping the sequences to the genome, which manipulate the sequences to produce better mapping results. Although these tools are widely used with good performance for short reads in next-generation sequences, their applications are limited to long reads generated by third-generation sequencing, except FastQC for quality control. The codes or commands used in this study help new learners to understand these tools.
Graphical abstract:
The pipeline of quality control and preprocessing sequencing reads.
Keywords: Quality control Preprocessing Sequencing reads FastQC Cutadapt
Background
As next generation sequencing technology is being widely used, sequencing data quality control and preprocessing are needed. Low data quality may be generated from adapter contamination, base content biases, overrepresented sequences, and errors in library preparation or sequencing steps. Quality control and preprocessing are effective ways to eliminate possible sequencing errors. Some relevant tools for quality control and preprocessing have been developed. For example, FastQC (Andrews, 2014) provides per-base and per-read quality profiling features. Cutadapt is used as an adapter trimmer (Martin, 2011); Trimmomatic is another trimming adapter tool (Bolger et al., 2014). FASTX-Toolkit is a collection of Linux command line tools for processing FASTQ files (Gordon and Hannon, 2010). iTools calculates the quality score of fastq and includes multiple functions by analyzing other data formats (He et al., 2013). Fastp is an ultra-fast preprocessor, which can perform quality control, adapter trimming, quality filtering, and other functions (Chen et al., 2018). Cutadapt can meet the demand of users who only need to remove the adapters in reads. Fastp can perform all aspects of preprocessing in one step, such as adapter trimming, base correction, overlapping analysis, polyG tail trimming, sliding window cutting, and global trimming. Fastx provides many command line tools for preprocessing, such as fastq-to-fasta converter, fastq/a collapser, fastq/a rename, fastq/a reverse-complement, fastq quality changer, and fastq quality trimmer. Users can use those tools with self-defined parameters.
In this article, we show how to use these common tools in quality control and preprocessing of sequencing reads. Some of them share functions, and others have specific functions. Users can choose the tools to use based on the specific demands of their analysis. As fastq format is universal for sequencing data, we use fastq data as the input for all tools. As the Ubuntu system is widely used among Linux branches, this system is used here.
Equipment
Computer (OS: Linux-branches, such as Centos and Ubuntu. We recommend at least 16GB RAM and multiple cores)
Software
FastQC (Andrews, 2014)
FastQC is a program designed to spot potential problems in high throughput sequencing datasets. If java is not installed, you can add it by doing the following:
Ubuntu: sudo apt install default-jre
The software is available for download at https://codeload.github.com/s-andrews/FastQC/zip/refs/heads/master (last accessed date: 31/10/2021) or https://github.com/s-andrews/FastQC.git downloaded by git (terminal command: git clone https://github.com/s-andrews/FastQC.git) (last accessed date: 31/10/2021). To install FastQC, unzip the zip file. A wrapper script called ‘fastqc’ is included in the top level directory of FastQC installation. You may need to make this file executable: chmod 755 fastqc. If you have conda installed on your computer, the easy recommended way is:
conda activate
conda install fastqc
iTools (He et al., 2013)
In this study, we use iTools to provide useful statistics of sequence data, which includes the Fqtools module to deal with fastq files. The Fqtools module provides multiple functions, as follows: a) summarizes the quality and amount of data, as well as the GC content; b) filters or trims the reads according to sequencing quality; c) removes reads contaminated with adapter sequences; and d) splits reads according to the index sequence. The software is available for download at https://github.com/BGI-shenzhen/Reseqtools/blob/master/iTools_Code20180520.tar.gz (last accessed date: 31/10/2021) and installation instructions are in the Install.Readme file.
Cutadapt (Martin, 2011)
Cutadapt searches for the adapter sequences in all reads and removes them. The software is available for download at https://codeload.github.com/jamescasbon/cutadapt/zip/refs/heads/master (last accessed date: 31/10/2021), and the git clone command is: https://github.com/marcelm/cutadapt.git (last accessed date: 31/10/2021). Installation is done by: python setup.py install –user
The easiest way to install cutadapt is to use pip on the command line:
pip install –user –upgrade
Fastp (Chen et al., 2018)
A tool designed to provide fast all-in-one preprocessing for fastq files. The software is available for download at https://codeload.github.com/OpenGene/fastp/zip/refs/heads/master (last accessed date: 31/10/2021), and the git clone command is: git clone https://github.com/OpenGene/fastp.git (last accessed date: 31/10/2021). Installation instructions are in the README.md file. Another way to install fastp with conda:
conda install -c bioconda fastp
FASTX (Gordon and Hannon, 2010)
The FASTX-Toolkit is a collection of command line tools for short reads Fasta/FastQ files preprocessing. The software is available for download at: https://codeload.github.com/agordon/fastx_toolkit/zip/refs/heads/master (last accessed date: 31/10/2021), and the git clone command is: git clone https://github.com/agordon/ fastx_toolkit. git (last accessed date: 31/10/2021). Installation instructions are in the README file.
Input data
FastQ format
This is the most widely used format in sequence analysis. The format contains more information than the fasta format, through integrating quality scores. Each sequence requires at least four lines:
The first line is the sequence header which starts with an ‘@’.
The second line is the sequence.
The third line starts with ‘+’.
The fourth line contains the quality scores.
We downloaded two transcriptome fastq data by wget. The SRR accession number or Project number could be described in published studies with SRA data uploaded into NCBI. The user can find the SRR accession number in the SRA database, based on Project number in NCBI, and download the fastq format data from EBI website (https://www.ebi.ac.uk) as alternative access. The user should search by the SRR number, and download links can be found on the result page. The users can record the download links of fastq files to download data in the terminal. In this study, the run accession numbers we used are SRR2061397 and SRR2061398. The sequencing platform is Illumina Hiseq 2000 paired end sequencing. The organism is Arabidopsis thaliana, and the method to download links is as follows (last accessed date: 15/7/2021):
wget -c http://ftp.sra.ebi.ac.uk/vol1/fastq/SRR206/007/SRR2061397/SRR2061397_1.fastq.gz
wget -c http://ftp.sra.ebi.ac.uk/vol1/fastq/SRR206/007/SRR2061397/SRR2061397_2.fastq.gz
wget -c http://ftp.sra.ebi.ac.uk/vol1/fastq/SRR206/008/SRR2061398/SRR2061398_1.fastq.gz
wget -c http://ftp.sra.ebi.ac.uk/vol1/fastq/SRR206/008/SRR2061398/SRR2061398_2.fastq.gz
Case study
FastQC provides a modular set of analyses, which can be used to give a quick impression of whether the data has any problems that you should be aware of before doing any further analysis. The main functions of FastQC are:
Import data from BAM, SAM, or FastQ files.
Providing a quick overview to tell you in which areas there may be problems.
Summary graphs and tables to quickly assess your data.
Export of result to an HTML-based permanent report.
FastQC can be run either as an interactive graphical application. Alternatively, you can run the program in a non-interactive way.
You can run it directly:
./fastqc
If you do not specify any files to process, the program will try to open the interactive application. Click the file button and choose fastq files located on your computer. Click the confirm button, and wait several minutes for your reports.
Run fastqc from the command line, like this:
fastqc -t 8 -o outdir SRR2061397_1.fastq SRR2061397_2.fastq SRR2061398_1.fastq\ SRR2061397_2.fastq
Parameter description: -t for CPU number, -o for output directory.
iTools is a toolkit for analyzing next-generation sequencing data. One module of iTools is Fqtools, which processes the fastq sequence file. Here, we show one of its functions as follows: summarizes the quality and amount of data, as well as the GC content.
Run iTools from the command line like this:
iTools Fqtools stat -InFq SRR2061397_1.fastq -InFq SRR2061397_2.fastq -InFq\ SRR2061398_1.fastq -InFq SRR2061398_2.fastq -OutStat read.info -CPU 8
Parameter description: -InFq for input file, -OutStat for the output file, -CPU: CPU number
Cutadapt searches for the adapter sequence in all reads and removes it.
The command-line for cutadapt is:
cutadapt -a AGATCGGAAGAGC -A AGATCGGAAGAGC -q 30 -m 20 –trim-n -O 10\ -o SRR2061397_1trimmed.fastq -p SRR2061397_2¬trimmed.fasq SRR2061397_1.fastq SRR2061397_2.fastq
Parameter description: -a for sequence of an adapter ligated to the 3’ end, -A 3’ adapter to be removed from second read in a pair, -q trim low-quality bases from 5’ and 3’ ends of each read. -m 20 for discard trimmed reads that are shorter than 20. -O MINLENGTH if the overlap between the read and the adapter is shorter than MINLENGTH, the read is not modified, reduces the number of bases trimmed due to random adapter match. -o output file -p paired-output.
Users need to provide an adapter string, and the adapter may vary for different types of sequences.
fastp can perform quality control, adapter trimming, quality filtering, and per-read quality pruning with a single scan of fastq data.
The command-line for fastp is:
fastp -i SRR2061397_1.fastq -I SRR2061397_2.fastq -o SRR2061397_1clean.fastq -O\ SRR2061397_2clean.fastq
Parameter description: -i read1 input file, -I read2_inputfile, -o read1 output file, -O read2_output file.
Different tools in the FASTX-Toolkit perform a list of preprocessing tasks, such as converting fastq files to fasta files, removing sequencing adapters, filtering sequences based on quality, shortening reads, and trimming sequences based on quality.
Here, one tool as example is shown, as follows:
fastx_clipper -a AGATCGGAAGAGC -l 25 -d 0 -Q 33 -i SRR2061397_1.fastq -o SRR2061397_1trimmed.fastq
Parameter: -a for adapter string, -l for discard sequence shorter than N nucleotides. -d N keep the adapter and N bases after it. -i input file, -o output file.
Result Interpretation
Here, we use two tools (FastQC and iTools) to perform quality control and three other tools (cutadapt, fastp, and FASTX) for preprocessing of sequencing reads. Command-line examples are provided to show the basic usages of these tools.
For the FastQC, an HTML report can be generated by running FastQC in non-interactive mode. It includes different modules, such as basic statistics, per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, per base N content, sequence duplication levels, overrepresented sequences, and adapter content. A warning or failure icon on the modules indicates some kind of systematic problem. Users can interpret FastQC reports via the link (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/).
For iTools, a txt file is generated by running iTools in the command line. This file contains multiple information, such as GC content, base quality distribution, and read quality distribution. The percentage of reads with a quality score Q30 (99.9% base accuracy) of SRR2061397_1 and SRR2061397_1 is 93.83% and 88.24%, separately (Table 1). The quality score is important to evaluate the reliability of reads, and a high score represents high sequence quality.
Table 1. Read quality distribution generated by iTools.
Quality score SRR2061397_1 SRR2061397_2
ReadQ:0--10 118,45 (0.12%) 205,370 (2.09%)
ReadQ:10--20 105,784 (1.08%) 266,545 (2.71%)
ReadQ:20--30 489,384 (4.98%) 683,440 (6.96%)
ReadQ:30--40 9,217,936 (93.82%) 8,669,973 (88.24%)
ReadQ:40--50 492 (0.01%) 113 (0.00%)
For cutadapt, new fastq files are generated by removing adapters. Standard out shows the summary of reads processed: 0.2% of reads contain adapters, and 6.4% of reads are trimmed with low quality (Table 2). The reads satisfying ≥Q30 were considered in our analysis. Reads with low quality (<Q30) and adapters are trimmed.
Table 2. Summary of cutadapt output.
Summary
Total read pairs processed 9,825,441
Read 1 with adapter 17,669 (0.2%)
Read 2 with adapter 15,187 (0.2%)
Pairs that were too short 639,968 (6.5%)
Pairs written (passing filters) 9,185,473 (93.5%)
Quality-trimmed 125,590,727 bp (6.4%)
Fastp supports automatic adapter trimming and works faster than other preprocessing tools, such as Trimmomatic or Cutadapt. Fastp improves the read quality to some extent (Table 3). The total reads and total bases are provided before and after filtering. Q20 and Q30 quality scores for reads and bases are also shown. There are 18,655,502 reads passing the filter. Other reads with low quality and too many N are discarded.
Table 3. Summary of fastp output.
Summary of fastp output
Read1 before filtering: Read1 after filtering:
total reads: 9,825,441 total reads: 9,327,751
total bases: 982,544,100 total bases: 930,706,316
Q20 bases: 961,474,687 (97.8556%) Q20 bases: 920,234,151 (98.8748%)
Q30 bases: 918,941,057 (93.5267%) Q30 bases: 885,474,154 (95.14%)
Read2 before filtering: Read2 after filtering:
total reads: 9,825,441 total reads: 9,327,751
total bases: 982,544,100 total bases: 930,706,316
Q20 bases: 927,573,105 (94.4052%) Q20 bases: 910,151,132 (97.7914%)
Q30 bases: 869,710,432 (88.5162%) Q30 bases: 857,626,618 (92.1479%)
Filtering result:
reads passed filter: 18,655,502
reads failed due to low quality: 991,868
reads failed due to too many N: 3,512
reads failed due to being too short: 0
reads with adapter trimmed: 160,162
bases trimmed due to adapters: 4,215,756
FASTX provides a fastx_clipper tool to remove adapters and low-quality reads. Here, iTools shows the quality distribution of fastq files filtered by fastx_clipper (Table 4). Compared with data before filter, the quality after filter improves it to some degree (Table 1 and Table 4).
Table 4. The read quality summary of fastx_clipper.
SRR2061397_1 SRR2061397_2
ReadQ:0--10: 9,236 (0.10%) ReadQ:0--10: 163,020 (1.81%)
ReadQ:10--20: 81,765 (0.91%) ReadQ:10--20: 210,196 (2.34%)
ReadQ:20--30: 411,863 (4.56%) ReadQ:20--30: 590,471 (6.57%)
ReadQ:30--40: 8,461,300 (93.69%) ReadQ:30--40: 7,991,767 (88.93%)
ReadQ:40--50: 67,254 (0.74%) ReadQ:40--50: 306,81 (0.34%)
Discussion
Here, we displayed five tools for quality control and preprocessing. The examples in this study exemplified how to use these tools. Users can explore more complex usage after learning the basic commands. The detail information for input, output, and sample data can be accessed via the website GitHub (https://github.com/Bio-protocol/Bioinformatics-Recipes-for-Plant-Genomics/tree/master).
Notes
Data used in this study are available in published databases (NCBI/EBI), and users can download them freely via different ways. Results in this study were generated by the tools described above; no additional tool was used. As the common functions of tools, the users could choose part tools, such as FastQC for quality control and fastp for preprocessing. After preprocessing, users could check their data quality by running FastQC again. We provide two ways (web page download or git clone in terminal) to download the tools in GitHub. Before using conda, anaconda should be installed (https://repo.anaconda.com/archive/Anaconda3-2021.05-Linux-x86_64.sh). Run the file (Anaconda3-2021.05-Linux-x86_64.sh) to install anaconda in the terminal by command: sh Anaconda3-2021.05-Linux-x86_64.sh, it will be installed in a default place, and the user can activate the conda environment by command: conda activate. Then, users can ask conda to install the tools needed.
Acknowledgments
This work was funded by the National Science Foundation of China (No.31770333, No.31370329, and No.11631012), the Program for New Century Excellent Talents in University (NCET-12-0896), and the Fundamental Research Funds for the Central Universities (No. GK201403004). This paper describes protocols from https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (last accessed date: 31/10/2021) and other references (Gordon and Hannon, 2010; Martin, 2011; He et al., 2013; Chen et al., 2018).
Competing interests
The authors declare no competing interests.
References
Andrews, S. (2014). FastQC A Quality Control tool for High Throughput Sequence Data.
Bolger, A. M., Lohse, M. and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15): 2114-2120.
Chen, S., Zhou, Y., Chen, Y. and Gu, J. (2018). fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34(17): i884-i890.
Gordon, A. and Hannon, G. J. (2010). Fastx-toolkit. FASTQ/A short-reads pre-processing tools.
He, W., Zhao, S., Liu, X., Dong, S., Lv, J., Liu, D., Wang, J. and Meng, Z. (2013). ReSeq Tools: An integrated toolkit for large-scale next-generation sequencing based resequencing analysis. Genet Mol Res 12(4): 6275-6283.
Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. Embnet Journal 17(1).
Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/Bioinformatics-Recipes-for-Plant-Genomics.
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4,455 | https://bio-protocol.org/en/bpdetail?id=4455&type=1 | # Bio-Protocol Content
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Differential Expression Analysis: Simple Pair, Interaction, Time-series
HQ Han Qu
MQ Meng Qu
SW Shibo Wang
LY Lei Yu
QJ Qiong Jia
XW Xuesong Wang
ZJ Zhenyu Jia
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Published: Jul 5, 2022
DOI: 10.21769/BioProtoc.4455 Views: 1213
Reviewed by: Hassan RasouliSaumik BasuAftab NadeemJinfeng Chen
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Original Research Article:
The authors used this protocol in Bioinformatics Jul 2018
Abstract
Identifying differentially expressed (DE) genes across specific conditions is vital in understanding phenotypic variation. The fast-growing RNA sequencing (RNA-seq) provides much information that efficiently quantifies gene expression. Methods and tools dedicated to differential gene expression analysis from RNA-seq data have also increased rapidly. More than 30 DE methods have been published; however, many comparison studies highlight that no single method outperforms others in all circumstances. In this study, we test and compare the performances of three widely used R packages: edgeR, DESeq2, and limma voom, with published Cumbie's Arabidopsis thaliana data. Even though the standard DE analysis has been extensively used and improved over the past years, time course RNA-seq can also provide an advanced understanding of gene regulation, biological development, and identifying DE genes. Therefore, we also conducted a time course analysis using another published Ursache's Arabidopsis time course dataset. These methods are initiated in separate R packages, with detailed R codes and explanations constructed to help build a more convenient user experience.
Keywords: RNA-seq Bioinformatics Benchmarking Differential gene expression Significantly expressed genes Time course
Background
In recent years, RNA sequencing has become the leading choice for genome-wide relative quantification of gene expression and, in particular, the analysis of differential gene expression (DGE) across multiple conditions of interest (Casassola et al., 2013; Van den Berge et al., 2019; Chung et al., 2021). RNA-seq has mainly been applied to study new disease biology, including studies on disease-related DGE analysis and cancer biomarker discovery, cancer heterogeneity and evolution, drug resistance, the cancer microenvironment and immunotherapy, and neoantigens (Hong et al., 2020). It can also identify host-pathogen interactions in eukaryotic cells, including the immune response (Costa et al., 2013). In addition, it plays a significant role in studying quantitative trait loci associated with gene expression in complex diseases (Costa et al., 2013). DGE analysis is one of the most common applications of RNA-seq. DE genes can be identified from different species, tissues, and periods, revealing their function, potential molecular mechanisms, and potential as biomarkers.
RNA-seq data analysis routinely involves a few steps: trimming adaptor sequences and poor-quality nucleotides; alignment to reference genome, or transcriptome, or assembling them de novo; counting mapped reads; normalization to remove possible bias; and identifying significant differences between two or more conditions (Costa-Silva et al., 2017). Regularly, DGE analysis is the final step in RNA-seq studies, aiming to determine which genes have a statistically significant difference, and provide pairwise magnitudes of difference for each gene.
The substantial expansion in RNA-seq has generated more than 30 algorithms and tools for DGE analysis (Lamarre et al., 2018). Table 1 lists essential information from several generally accepted tools dedicated to DGE analysis, and summarizes assumed distributions, and default normalization strategies. There are four main categories of methods: (1) assume the data follow a negative binomial distribution, like DESeq2 and edgeR; (2) assume the data follow a log-normal distribution, like limma voom; (3) assume the data follow a Poisson distribution, like Cufflinks; (4) are non-parametric, such as SAM-Seq.
Table 1. RNA-seq DGE tools discussed in this study
DEG tools References Assumed distribution Normalization Citations (Dec, 2021)
edgeR (Robinson et al., 2010) Negative binomial RLE 32,222
DESeq2 (Love et al., 2014) Negative binomial TMM 23,247
limma voom (Ritchie et al., 2015) Log-normal TMM 14,853
Cufflinks (Trapnell et al., 2010) Poisson FPKM 12,191
SAM-Seq (Li and Tibshirani, 2013) None Internal 467
Consequently, many comparison studies have been done, but there is no gold standard. Gierlinski et al. (2015) and Froussios et al. (2019) tried to tackle the obstacle of choosing the best probabilistic model. They recommend using tools based on the negative binomial, and log-normal distributions for the cross-replicate variability of RNA-seq read counts in yeast (Saccharomyces cerevisiae) and Arabidopsis thaliana. Non-parametric methods are seldomly used, and require higher replicate samples for reasonably good performance, so they can be used as alternatives when the data do not fit the negative binomial law (Lamarre et al., 2018). The purpose of this protocol is to demonstrate the principal steps needed to generate diverse DGE results using different methods, and provide a global representation of the expression changes across multiple conditions, especially for plant species. From previous comparison studies (Table 1), we determined the most widely used were these three R packages: edgeR, DESeq2, and limma voom with Arabidopsis thaliana data. This paper will walk the users through an RNA-seq differential expression analysis using three R packages, and implement a comparison of the three methods. Time course sequencing data is a particular type of RNA-seq data, which can provide an opportunity to evaluate gene expression patterns at specific stages of development, or at different time points after a specific treatment (Spies et al., 2017). We will also provide an example of analyzing Arabidopsis time course data.
Procedure
Case study 1: A comparison of three methods for DGE analysis
Input data
To demonstrate, here we use the Arabidopsis thaliana RNA-Seq data published by Cumbie et al. (2011). Summarized count data is available as an R dataset, and readers can download the data using the link http://bioinf.wehi.edu.au/edgeR/UserGuideData/arab.rds. In Cumbie’s experiment, they inoculate six-week-old Arabidopsis plants with the mutant of Pseudomonas syringae. Control plants were inoculated with a mock pathogen. Each treatment was done as biological triplicates, with each pair of replicates done at separate times, and derived from independently grown plants and bacteria.
Figure 1. Workflow of DGE analysis for RNA-seq data.
Pink boxes correspond to pipelines for count-based models (e.g., DESeq2 and edgeR), while blue boxes correspond to a linear-model-based pipeline (e.g., limma voom)
The general workflow involves the following steps (Figure 1): deciphering RNA-seq data characteristics, checking data quality, filtering and normalization, specification of the statistical model and estimation of model parameters, statistical inference of the parameters, multiple testing, and visualization of the analysis results.
Exploring RNA-seq count data
Loading all required R packages
# Loading R packages
library(GEOquery)
library(DESeq2)
library(edgeR)
library(limma)
library(ggplot2)
library(pheatmap)
library(Glimma)
library(dplyr)
library(readr)
Downloading and importing of RNA-seq count data
A matrix of counts summarizing the gene-level expression in each dataset sample is needed to start a differential gene expression analysis. We can download and import the processed read counts as ‘arab.rds’ file.
The rows in the count data correspond to genes, and the columns correspond to samples, in which we want to see if differences across conditions are significant. The integer value in each matrix position represents the number of sequence reads that originated from a particular gene in a specific sample.
Characteristics of RNA-seq count data
To illustrate typical features of Arabidopsis count data, we could start with a counts histogram for a single sample (‘mock1’).
ggplot(data.frame(raw_counts)) +
geom_histogram(aes(x = mock1), stat = "bin", bins = 200) +
xlab("Raw counts") +
ylab("Number of genes")
Figure 2. Histogram of the counts for the single sample (‘mock1’).
As expected, RNA-seq count data usually contains a large number of genes associated with a small number of counts (Figure 2). Another vital property that could be accessed here is the relationship between mean and variance. It can help demonstrate which distribution is appropriate for modeling the count data in RNA-seq. For example, three replicates of ‘mock’ control group are used here.
Figure 3. Scatterplot of the mean vs. the variance.
In Figure 3, we can conclude that genes with higher mean expression tend to have higher variance than the mean across replicates. Therefore, our data fails to satisfy the Poisson distribution criteria, in which mean equals variance. For our data, negative binomial and log-normal distributions could be a better fit.
Quality assessment
To ensure that the replicates of each group are reasonable, principal component analysis (PCA), hierarchical clustering, and MDS analysis are performed here. Biological replicates are expected to be similar to each other, even if experimental errors cannot be ignored. Potential outliers can also be identified, and a determination of whether they need to be removed made prior to DGE analysis. These unsupervised methods are run using regularized log (rlog) transformed normalized counts as input for better visualization, and avoiding bias from the abundance of low-counts genes. The initial purpose of count normalization is to accurately compare gene expression among samples. More than five methods are now available for normalization, such as CPM, TPM, FPKM, TMM, and DESeq2’s median of ratios method (Van den Berge et al., 2019). DESeq2’s median of ratios method is chosen here for an example.
Input data for DEseq2 consists of non-normalized read counts, at either gene or transcript levels. The input, intermediate, and result data are stored in a pre-specified data slot (DESeq object), which can be accessed and retrieved using specific package-defined functions.
Principal Component Analysis (PCA)
Principal Component Analysis (PCA) is used to identify strong patterns in a dataset, and distill the features down to important ones, without losing essential traits. By default, plotPCA() uses the top 500 most variable genes. You can add the ntop= argument, and specify how many genes are being displayed.
### Plot PCA
plotPCA(rld, intgroup="group")
Figure 4. Principal Component Analysis (PCA) for ‘mock’ and ‘hrcc’ samples.
When interpreting PCA plots (Figure 4), if two samples have similar expression levels for the genes that contribute significantly to the variation represented by a particular PC (Principal Component), they will be plotted close together. For the example displayed above, when visualizing PC1 and PC2, we can see examples separated by treatment, and are optimistic about the DGE analysis.
Multidimensional scaling (MDS) plot
Similar to PCA, the multidimensional scaling (MDS) plot is frequently used to explore differences in samples. When data has been MDS-transformed, the first two dimensions explain the most significant variance among all samples. An interactive R widget for generating plots is created and exported as HTML documents (Su et al., 2017).
glimmaMDS(dds)
We get two plots (Figure 5), showing two MDS dimensions, and the other one of each dimension’s eigenvalues. For the example displayed above, when visualizing dim1 and dim2, we can see samples separated by treatment, and are optimistic about the DGE analysis.
Figure 5. Screenshot of the HTML page generated by the glimmaMDS() function in Glimma.
Hierarchical Clustering Heatmap
Hierarchical clustering heatmaps display the correlation of gene expression for all pairwise combinations of samples in the dataset.
### Extract the rlog matrix from the object
rld_mat <- assay(rld)
### Compute pairwise correlation values
rld_cor <- cor(rld_mat)
### Plot heatmap using the correlation matrix and the metadata object
pheatmap(rld_cor, annotation_col =colData)
Overall, we observe pretty high correlations across the board (>0.985), suggesting no outlying samples (Figure 6). Also, you see the clustering of the samples together by sample group, except for the ‘hrcc2’ sample. Together with the PCA and MDS plot, it is suggested that the RNA-seq data are of good quality, and we have the green light to proceed to differential expression analysis.
Figure 6. Hierarchical clustering heatmap for the correlation of gene expression for all pairwise sample combinations.
Differential gene expression (DGE) analysis
The final step in the differential expression analysis workflow is fitting the raw counts to the specific model, and performing the statistical test for differentially expressed genes. In this step, we essentially want to determine whether the mean expression levels of different sample groups are significantly different.
DESeq2 method
The DESeq2 is one of the most popular tools for DGE analysis, and is modeled based on the negative binomial distribution. It builds on the design on dispersion estimation and use of Generalized Linear Models, from the DSS and edgeR methods. Briefly, DESeq2 will model the raw counts, using normalization factors for accounting for differences in library depth. Then, it will estimate the gene-wise dispersions, and shrink these estimates, to generate more accurate estimates of dispersion to model the counts. Finally, DESeq2 will fit the negative binomial model, and perform hypothesis testing, using the Wald test or Likelihood Ratio Test.
To get our differential expression results from our raw count data, only one line of code is needed.
NOTE: DESeq2 does not use normalized counts; instead, it uses the raw counts, and models the normalization inside the Generalized Linear Model (GLM). Furthermore, the Wald test is the default used for hypothesis testing when comparing two groups.
## Run pipeline for differential expression steps
dds <- DESeq(dds)
## estimating size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
Estimating the Dispersion
As shown in the printed out message, six steps are performed. The second and third steps are about dispersion, which accounts for a gene’s variance and mean expression level to identify DE genes accurately. A dispersion plot can ensure if the data is a good fit for the DESeq2 model. You expect the data to generally scatter around the curve, with the dispersion decreasing with increasing mean expression levels. If you see a cloud or different shapes, we will suspect a contamination (mitochondrial, etc.), or outlier samples.
## Plot dispersion estimates
plotDispEsts(dds)
Figure 7. Dispersion estimates plot derived by DESeq2.
Each black dot is a gene in Figure 7, where the dispersion is plotted against the mean expression, across within-group replicates per gene. We see a nice decrease in dispersion with increasing mean expression, which is good, as we expected. We also see strong shrinkage, likely because we only have three replicates for each group. The more replicates the data has, the less shrinkage is applied to the dispersion estimates, and the more DE genes can be identified in the model.
Extracting results
We set the alpha argument to 0.05 (FDR < 0.05) when creating our results table. The summary() function summarizes the number of up- and down-regulated genes, tested genes, and genes not included in multiple test corrections due to a low mean count.
Filtering the data
It will increase the power to detect DE genes, by filtering genes that have little or no chance of being detected as differentially expressed. We recommend omitting genes with zero counts, extreme count outliers, and low mean normalized counts in all samples.
Extracting significant DE genes
We are setting the FDR cutoff to < 0.05, which means that the proportion of false positives we expect amongst our DE genes is 5%.
Visualizing the results
MA plot
The MA plot plots the log2 foldchanges for all genes tested, against the mean of the normalized counts across all the samples. The genes that are significantly DE are colored to be easily targeted (Figure 8).
# MA plot
plotMA(res)
Figure 8. MA plot shows the log2 fold changes attributable to a given variable over the mean of normalized counts for all the samples.
Points will be colored blue if the adjusted p-value is less than 0.1. Points which fall out of the window are plotted as open triangles, pointing either up or down.
Heatmap
We could also extract the normalized values of all the significant genes, and plot a heatmap (Figure 9) of their expression using pheatmap().
Figure 9. Heatmap of normalized expression values of significant genes across all samples.
Volcano plot
The Volcano plot (Figure 10) has the log-transformed adjusted p-values plotted on the y-axis, and the log2 fold change values on the x-axis. The genes that are significantly DE are colored to be easily targeted.
Figure 10. Volcano plot showing both significantly increased and decreased genes.
edgeR method
The edgeR is another famed Bioconductor package, designed to analyze replicated count-based expression data. The RNA-seq count data is modeled as a negative binomial distribution. Then, edgeR estimates the gene-wise dispersions by conditional maximum likelihood. An empirical Bayes procedure is effectively employed, to shrink the dispersions for a consensus value. Finally, an exact test, analogous to Fisher’s exact test, is used for accessing DE genes.
Like DESeq2, all the information in edgeR should be contained in a simple list-based data object called a DGEList, defined as variable d. When we use any function from this package later, the function passes everything already in d, but adds one more element to the list.
Loading RNA-seq data
Filtering the data
First, get rid of genes that do not occur frequently enough. In this example, we keep genes with at least ten counts per million (CPM) on any particular gene.
# keeping a gene if it has a cpm of 1 or greater for at least two samples
keep <- rowSums(cpm(d.full)> 10) >= 2
d <- d.full[keep, , keep.lib.sizes=FALSE]
Normalizing the data
The filtered genes have very little power to detect DE genes, so little information is lost. After filtering, it is a good idea to reset the library sizes. Note that the “size factor” from DESeq is not equal to the “norm factor” in edgeR. In edgeR, the library size and additional normalization scaling factors are separate. Instead, the multiplication of lib.size and norm.factors is similar to DESeq’s size factor.
The edgeR is concerned with relative changes in expression levels between conditions, but not directly with estimating absolute expression levels. The calcNormFactors() function normalizes RNA composition, by finding a set of scaling factors for the library sizes that minimize the log-fold changes between the samples for most genes. The default method for computing these scale factors uses a trimmed mean of M-values (TMM) between each pair of samples.
Estimating the Dispersion (GLM)
Several dispersion estimating strategies are available in edgeR, such as the typical and tagwise dispersion, and the generalized linear model (GLM). We use GLM as an example here.
plotBCV() plots the tagwise biological coefficient of variation (square root of dispersions) against log2-CPM.
plotBCV(d)
Figure 11. Dispersion estimates plot derived by edgeR.
In Figure 11, we see that the estimate for the coefficient of variation is a pretty good model, since tagwise dispersion follows the model, and decreases as the counts per million (CPM) increase. Experiments with low biological variation tend to result in decreasing solid trends. A typical dispersion between 0.2 and 0.4 is reasonable, and can detect more DE genes.
GLM testing for DE genes
Once the dispersions are estimated, we can test procedures for determining differential expression.
We now get our DE genes. After fitting the model, we use the topTags() function to explore the results and set the cutoff to identify significant DE genes. Finally, we can plot the log-fold changes of all the genes, and significant DE genes are highlighted in red (Figure 12).
Figure 12. Scatterplot highlighting both significantly increased and decreased genes.
Limma voom method
Limma is an R package initially developed for DE analysis of microarray data. To deal with RNA-seq data, we can use a function called voom in the limma package. Limma-voom is also a choice for DE analyses, because it allows for incredibly flexible model specifications, including categorical and continuous variables. It can also maintain the false discovery rate at or below the nominal rate. In addition, Empirical Bayes smoothing of gene-wise standard deviations can provide increased power.
Preprocessing
Steps before normalization in limma-voom are precisely the same as in the edgeR method.
Voom transformation
When operating on a DGEList-object, voom converts raw counts to log-CPM values, by automatically extracting library sizes and normalization factors from itself. Firstly, counts are transformed to log2 counts per million reads (CPM). Next, a linear model is fitted to the log2 CPM for each gene, and the residuals are calculated. Then, a smoothed curve is fitted to the residual standard deviation by average expression (red line in plot). The smoothed curve is used to obtain weights for each gene and sample that are passed into limma.
v <- voom(dge, design, plot=TRUE, normalize="quantile")
Figure 13. The voom plot.
The smoothed curve is used to obtain weights for each gene and sample that are passed into limma, along with the log2 CPMs.
Figure 13 presents a good voom plot, since the standard deviation decreases as log2 CPM increases.
Fitting linear models
Linear modeling in limma is carried out using the lmFit() and contrasts.fit() functions, which can be used for microarray and RNA-seq data. Firstly, it fits a separate model to the expression values for each gene. Next, empirical Bayes moderation is carried out, by borrowing information across all the genes, to obtain more precise estimates of gene-wise variability.
The model’s residual variances are plotted against average expression values below (Figure 14), with significant DE genes highlighted. We can see that the variance is not dependent on the mean expression level.
plotMD(efit, column=1, status=dt[,1], main=colnames(efit)[1], xlim=c(-8,13))
Figure 14. Scatterplot highlighting both significantly increased and decreased genes.
A comparison of the three methods
Visualization of DGE results using the three selected DGE tools provides valuable insights into their generated results. As seen in Figures 15A, B, the three methods detect similar numbers of DE genes, and most of them are identical. When we set the FDR cutoff to 0.05, they would behave differently. DESeq2 detects the most DE genes, while the limma voom detects the least. However, the significant genes detected by limma voom could almost be found by edgeR and DESeq2 (Figures 15C). Then we could infer that limma voom is more critical than the other two when calling significant DE genes.
Figure 15. Visualization of DGE results for DESeq2, edgeR and limma voom methods.
(A) Numbers of DE and significantly DE genes detected by three selected methods. (B) Numbers of overlapping and different DE genes between the three methods. (C) Numbers of overlapping and different significant DE genes between the three methods (FDR < 0.05).
Let us look at the detected fold changes from all three methods. Here, the genes are colored differently to label which methods find them significant. Supposing that a gene is colored yellow-wish green, this means that both methods find it. Matching the results in Figure 15, the outputs of DESeq2 and edgeR are very close indeed, since their fold changes correlate much better than the other two methods (Figure 16A, B, C). All three methods behaved well in finding the significant DE genes, while DESeq2 caught more candidates than the other two. It turns out that the genes detected only by DESeq2 have pretty low counts. The DESeq2 goes through the logic of independent filtering within results() to save from multiple test corrections on genes with no power, showing that the likelihood of a gene being significantly differentially expressed is related to how strongly it is expressed. It advocates discarding extremely lowly expressed genes, because the differential expression is likely not statistically detectable, so it is unnecessary to pre-filter low count genes, as recommended in the vignette. However, in edgeR and limma voom, we performed a minimal count-based pre-filtering to keep only rows with a CPM of at least ten, for at least two samples total. After filtering, the candidate genes with apparently moderate fold changes detected by DESeq2 are removed in edgeR and limma voom. We suggest users try different methods with variable parameters, and then choose the most suitable one.
Figure 16. The comparison of DESeq2, edgeR and limma voom methods.
(A) Scatterplot of the log fold change of DESeq2 verse the log fold change of edgeR. (B) Scatterplot of the log fold change of DESeq2 verse the log fold change of limma voom. (C)
Scatterplot of the log fold change of limma voom verse the log fold change of edgeR.
Case study 2: Time course analysis
Input data
Here, we demonstrate a fundamental time course analysis with an Arabidopsis dataset, containing gene counts for an RNA-seq time course. This experiment aimed to uncover whether the differentiated endodermal cells have a distinct transcriptional response to auxin treatment. A time series of 10 µM NAA treatment was performed, and samples collected at t = 0, 2, 4, 8, 16, and 24 hrs after NAA treatment (Ursache et al., 2021). For the time series, we compared roots of the solitary root 1 (slr-1) mutant to the CASP1::shy2-2/slr-1 double mutant. The raw data from the NCBI database (Ursache et al., 2021) was processed, and saved as a RangedSummarizeExperiment RData file. The processed data can be downloaded from Github, through this link: https://github.com/hanqu24/RNA-seq-analysis/blob/main/Arabidopsis%20time%20course%20analysis/arab_time.RData.
When working with time course RNA-seq data, the Likelihood Ratio Test (LRT) is predominantly desirable. We can choose the LRT (in DESeq() function) to explore any significant differences across a series of time points, and further evaluate differences observed between sample groups. Here, we demonstrate a fundamental time course analysis with an Arabidopsis dataset, containing gene counts for an RNA-seq time course.
We use a design formula that models the strain difference at time 0, over time, and any strain-specific differences (the interaction term strain: hour).
Many other options for modeling the counts include an interaction term of the condition with the smooth function of time, using spline basis functions within R, and another more modern approach, using Gaussian processes.
For better understanding, we can plot the counts of the groups over time for the gene with the smallest adjusted p-value, testing for condition-dependent time profile, and accounting for differences at time 0 (Figure 17). The double mutant group changes dramatically over time compared to the single mutation group, suggesting that double mutations are more sensitive to the NAA treatment, especially after 10hrs.
Figure 17. Line graph of the two groups’ count changes over time for the gene with the smallest adjusted p-value.
Normalized counts for a gene with condition-specific changes over time. Wald tests for the log2 fold changes at individual time points can be investigated, using the test argument to results.
We can furthermore cluster significant genes by their profiles.
We can now plot the log2 fold changes for genes with the smallest adjusted p-value in a heatmap (Figure 18).
Figure 18. Heatmap of log2 fold changes for top 20 significant DE genes.
We can detect several clusters in the heatmap (Figure 18). If we look at these clusters’ gene ontology (GO) annotations, you might observe terms linked to auxin signaling and lateral root development, as expected.
Discussion
With the rising of RNA-seq technology, the sequencing protocols have been continuously improved. Ching et al. (2014) underlined that no single software consistently showed the best performance across the datasets they had studied (Ching et al., 2014). By looking at the considerations of citation numbers and opinions from other researchers, we then decided to compare the following three widely used methods: DESeq2, edgeR, and limma voom. Like other studies, edgeR and DESeq2 give roughly similar results, while limma voom seems more stringent when calling significant DE genes. Furthermore, the edgeR and limma voom work faster compared to DESeq2, for fitting GLM models. Regardless, it seems that some tools are particularly suitable in certain circumstances. Limma voom performs better with large sample sizes, and even a limited number of replicates (Soneson and Delorenzi, 2013; Seyednasrollah et al., 2015). DESeq2 is the safest choice with a small number of replicates, ensuring adequately significant DE genes (Seyednasrollah et al., 2015). The edgeR gives variable results with small replicates, but it has superior specificity and sensitivity than limma voom when there are more replicates (Rapaport et al., 2013; Seyednasrollah et al., 2015). We suggest users try different tools taking into account the actual conditions of their data, for example, replicate numbers, library size, the distances between the biological conditions, and the variance of each replicate.
Acknowledgments
This protocol was derived from the research in Dr. Zhenyu Jia’s lab, University of California, Riverside. The authors thank Harvard Chan Bioinformatics Core (HBC) for the valuable DGE workshops.
Competing interests
The authors declare that there are no conflicts of interest or competing interests.
References
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Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/Differential-Expression-Analysis.
Article Information
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Qu, H., Qu, M., Wang, S., Yu, L., Jia, Q., Wang, X. and Jia, Z. Differential Expression Analysis: Simple Pair, Interaction, Time-series. Bio-101: e4455. DOI: 10.21769/BioProtoc.4455.
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4,456 | https://bio-protocol.org/en/bpdetail?id=4456&type=1 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Maize Genome Assembly with PacBio Reads
YH Ying Hu
MJ Marcio F. R. Resende Jr.
Published: Jul 5, 2022
DOI: 10.21769/BioProtoc.4456 Views: 787
Reviewed by: Weijia SuYong-Xin LiuSanzhen Liu
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Abstract
Assembly of high-quality genomes is critical for the characterization of structural variations (SV), for the development of a high-resolution map of polymorphisms, and to serve as the foundation for gene annotation. In recent years, the advent of high-quality, long-read sequencing has enabled an affordable generation of highly contiguous de novo assemblies, as evidenced by the release of many reference genomes, including from species with large and complex genomes. The long-read sequencing technology is instrumental in accurately profiling highly abundant repetitive sequences, which otherwise challenge sequence alignment and assembly programs in eukaryotic genomes. In this protocol, we describe a step-by-step pipeline to assemble a maize genome with PacBio long reads using Canu, and polish the genome using Arrow and ntEdit. Our protocol provides an optional procedure for genome assembly, and could be adapted for other plant species.
Keywords: Long-read sequencing PacBio Genome assembly Canu Arrow ntEdit
Background
Maize is one of the most important crops in the world, and has a long history serving as a classical model organism in genetic studies. As a diploid with 10 chromosomes, approximately 85% of the maize genome is composed of transposable elements (TEs) (Schnable et al., 2009). Such abundant, repetitive, and mobile sequences pose computational challenges for accurately assembling the maize genome sequence. The first draft of the maize genome, released in 2009, was sequenced based on Sanger sequencing of bacterial artificial chromosomes and fosmids (Schnable et al., 2009). Since then, the long-read sequencing technologies, such as PacBio and Oxford Nanopore, have greatly contributed to improving maize genome assemblies. The approach generates reads with lengths of tens of kilobases, making it suitable to improve the genome continuity, close the gaps in the current reference genomes, and identify the structural variations between genomes. In recent years, high-quality genome assemblies of more than thirty maize inbred lines, based mostly using PacBio sequencing, have been released (Jiao et al., 2017; Sun et al., 2018; Springer et al., 2018; Yang et al., 2019; Haberer et al., 2020; Hufford et al., 2021; Hu et al., 2021; Lin et al., 2021).
Compared to Illumina short reads, PacBio long reads usually have a relatively higher error rate, although recent improvements in chemistry and base-calling algorithms have significantly improved long-read sequencing quality. Furthermore, a large proportion of sequencing errors tend to be randomly distributed (Korlach et al., 2013), which can be corrected by increasing the sequencing coverage or by polishing the assembly Illumina short reads with higher accuracy. Nowadays, several assembly tools have been designed for PacBio long reads, including Canu (Koren et al., 2017), Falcon (Chin et al., 2016), and WTDBG2 (Ruan and Li, 2020). This protocol describes the step-by-step pipeline to assemble a maize genome with PacBio long reads using Canu version 1.8, and polish the genome using Arrow and ntEdit (Warren et al., 2019). This approach was previously used for the sweet corn genome assembly (Hu et al., 2021). Other protocols in the literature are available, and have also resulted in high-quality assemblies, such as using Falcon to correct PacBio subreads, Canu version 1.8 for trimming and assembly, and Pilon (Walker et al., 2014) for genome polishing (Hufford et al., 2021). To be noticed, this protocol will be specifically applicable to genome assembly using traditional PacBio long reads, rather than the PacBio HiFi reads generated by the PacBio Sequel System.
Software
All the software can be downloaded/used from following locations:
SMRT Tools (version 10.1.0; https://www.pacb.com/support/software-downloads/)
SequelTools (Hufnagel et al., 2020; version 1.1.0; https://github.com/ISUgenomics/SequelTools)
Canu (Koren et al., 2017; version 1.8; https://canu.readthedocs.io/en/latest/)
BUSCO (Simão et al., 2015; version 3.0.2; https://busco.ezlab.org/)
Pbalign (version 0.3.2; https://smrt.lbi.iq.usp.br/smrtanalysis/doc/bioinformatics-tools/pbalign/doc/howto.html)
Sambamba (Tarasov et al., 2015; version 0.6.9; https://github.com/biod/sambamba)
Samtools (Li et al., 2009; version 1.12; https://github.com/samtools/samtools)
Arrow (version 2.3.3; https://smrt.lbi.iq.usp.br/smrtanalysis/doc/bioinformatics-tools/GenomicConsensus/doc/index.html )
ntHits (version 1.2.1; https://github.com/bcgsc/ntHits)
ntEdit (Warren et al., 2019; version 1.2.1; https://github.com/bcgsc/ntEdit)
Case study
A workflow of given pipelines is shown in Figure 1. The raw file (PacBio BAM files) is subjected to three major steps: (i) Pre-processing of the PacBio raw reads: First, convert the PacBio raw BAM files to fastq files, using bam2fastq. Then, check the quality metrics of fastq files using SequalTools. (ii) Genome assembly, which includes the three phases of Canu (correction, trimming, and assembly). (iii) Genome assembly polishing using Arrow and ntEdit, and quality assessment using BUSCO. The protocol provides the general instruction of each software and useful tips for genome assembly and polishing. The running time of each step of Canu will depend on user’s dataset and computing power. Canu ran for 21 days to finish a maize genome assembly (~2.3 Gb) on a 32-processor server with 187 Gb RAM.
Figure 1. Flowchart showing various steps for pre-processing of the PacBio raw reads, genome assembly, and polishing.
The three major steps are described in this flowchart. Programs/software/algorithms used are indicated next to the arrows in blue.
Pre-processing of the PacBio raw reads
This protocol uses the data files generated by the PacBio Sequel System, to show how to perform pre-processing of the PacBio raw reads. The raw data of each SMRT-cell include files named *.subreads.bam, *.subreads.pbi, and *.subreadset.xml. One subreads.bam file contains multiple copies of subreads, generated from the single SMRTBell from high-quality regions. It is analysis-ready, and will be used directly for the following analysis. Subreads containing unaligned base calls outside of high-quality regions, or excised adapter and barcode sequences are retained in a scraps.bam file.
Convert the *.subreads.bam files to fastq or fasta files, with the PacBio tool bam2fastq or bam2fasta, which is part of the free SMRT Tools.
$ bam2fastq -c 9 -o raw_PacBio_1 raw_PacBio_1.subreads.bam
$ bam2fasta -c 9 -o raw_PacBi_1 raw_PacBio_1.subreads.bam
We use -c 9 to get all the subreads, and then let the assembler decide which reads are good for genome assembly. The command bam2fastq will generate a fastq file (raw_PacBio_1.fastq, in our example), and the command bam2fasta will generate a fasta file (raw_PacBio_1.fasta, in our example). To be noticed, only fastq files will be used for the downstream analysis.
Quality check: It is necessary to perform appropriate quality checking on the PacBio sequencing data, for producing successful downstream bioinformatics analytical results. FastQC (Andrews, 2010) works well for quality control of the short reads, but is not suitable for quality control of the PacBio long reads, which do not have a meaningful Phred quality score. Therefore, we use SequelTools, to perform quality control of the PacBio Sequel raw sequencing data from multiple SMRTcells. This tool will provide several statistics for each SMRTcell, including the number of reads, total bases, mean and median read length, N50, L50, PSR (polymerase-to-subread ratio), and ZOR (ZMW-occupancy-ratio). PSR is used to determine the effectiveness of library preparation, and ZOR is used to measure the effectiveness of introducing template into the ZMW. The QC tool of SequelTools requires *.subreads.bam files, and *scraps.bam files are optional. While SequelTools will take longer with the *.scraps.bam files, more information will be provided by the *.scraps.bam files for QC plots.
Generate a file with a list of locations of *.subreads.bam files and *.scraps.bam files.
$ find $PWD/*.subreads.bam > subFiles.txt
$ find $PWD/*.scraps.bam > scrFiles.txt
In the above commands, $PWD is an environment variable that stores the path of the current directory.
Run the QC tool of SequelTools with *.scraps.bam files.
$ ./SequelTools.sh -t Q -u subFiles.txt -c scrFiles.txt
Run the QC tool of SequelTools without *.scraps.bam files.
$ ./SequelTools.sh -t Q -u subFiles.txt
The argument -t is mandatory to specify which tool is being used. We use -t Q to use the QC tool specifically. The argument -u is also mandatory to identify a file listing the locations of the subread BAM files. The argument -c is optional to identify a file listing the locations of the scraps BAM files. To be noticed, SequelTools requires Samtools, R, and Python (version 2 or 3) pre-installed in the path.
Genome assembly
To perform the maize genome assembly, we provide instructions for the Canu version 1.8 that was used for the sweet corn genome assembly (Hu et al., 2021). Canu assembles PacBio or Oxford Nanopore sequences in three phases: correction, trimming, and assembly. The recommended coverage for eukaryotic genomes is between 30 x and 60 x. Here, we will use traditional PacBio long reads to show how to perform the genome assembly using Canu. If the users have Oxford Nanopore or PacBio HiFi reads, we suggest referring to the software’s manual of HiCanu for further information and troubleshooting (Nurk et al., 2020).
Canu is a very user-friendly tool for genome assembly. First, the users do not need to worry about abnormal termination of their Canu jobs. Canu can detect where it stops, and resume the incomplete jobs automatically. For example, some jobs in the cormhap step (generating correction overlaps in the correction phase) may be killed due to job timeout. If that happens, the user can manually increase the walltime, and rerun the original Canu command. Canu will find those incomplete jobs and resubmit them automatically. Secondly, Canu does not require the upfront definition of computational resource allocation. If the users are unsure how much to allocate to the job, the software will detect the available memory and processors, and request resources based on the genome size of their assembly. If there are not enough resources to do the assembly, Canu will not start. The threads parameters using maxMemory and maxThreads can also be used to limit the amount of memory and threads used. Finally, Canu can automatically submit it to the grid, for execution in a grid environment by default. If no grid is detected, or if the user sets useGrid=false, Canu will run on a single local machine.
Canu supports sequence inputs in FASTA or FASTQ format, as well as the compressed (.gz, .bz2, or .xz) version of these formats. It can automatically perform correction, trimming, and assembly in series by default. However, the users can also run these three phases separately, if they want to test different parameters of each phase, or if they only want to run trimming and assembly phases, using corrected reads generated from other software. In this protocol, we will show how to run each phase of Canu separately, and what kind of parameters of each phase can be adjusted. If the users want to run those three phases automatically by default, please refer to the software’s manual for further information.
Correct the raw reads
In this phase, Canu will do multiple rounds of overlapping and correction. To run the correction phase specifically, the users need to use the -pacbio-raw option, to provide raw PacBio reads as input data, and use the -correct option, to let Canu only correct the raw reads. If the users have more than 4,096 input files, they must consolidate them into fewer files. The output of the correction phase will be one compressed fasta file with all corrected reads (maize.correctedReads.fasta.gz, in our example).
$ canu -correct \
-p maize -d maize \
genomeSize=2.3g \
-pacbio-raw raw_PacBio_1.fastq \
raw_PacBio_2.fastq \
raw_PacBio_3.fastq \
raw_PacBio_4.fastq \
raw_PacBio_5.fastq \
raw_PacBio_6.fastq \
raw_PacBio_7.fastq \
raw_PacBio_8.fastq \
raw_PacBio_9.fastq
The -p <string> option is mandatory to set the file name prefix of intermediate and output files. The -d <assembly directory> is optional. If it is not provided, Canu will run in the current directory. The genomeSize parameter is required by Canu, which will be used to determine coverage in the input reads. The users can provide the estimated genome size in bases, or with common SI prefixes.
[Tip 1] If the raw PacBio coverage is low (less than 30 x), one option is to increase the parameter correctedErrorRate (the allowed difference in an overlap between two corrected reads, expressed as fraction error) to 0.105 (the default value is 0.045). The parameter corMinCoverage (limits read correction to regions with at least this minimum coverage) will be automatically set up as 0 x. If the raw PacBio coverage is high (more than 60 x), a better correction will be observed if the parameter correctedErrorRate is reduced to 0.040. The parameter corMinCoverage will be automatically set up as 4 x.
[Tip 2] If the users have high raw PacBio coverage, they can consider increasing the parameters minReadLength (reads shorter than this are not loaded into the assembler), and minOverlapLength (overlaps shorter than this will not be discovered), to discard the short reads, and reads with short overlaps, to improve the assembly quality.
[Tip 3] If the users’ genome is very heterozygous, they can increase the parameter corOutCoverage (only corrects the longest reads up to this coverage) higher than the raw PacBio coverage. In that case, they will correct all the raw reads. However, when we test this parameter in our maize genome assembly, it does not improve the assembly a lot and also increases running time. Therefore, if the genome is not very heterozygous, we do not recommend changing the default value of corOutCoverage.
[Tip 4] Canu runs in two modes: locally, using just the local machine, or grid-supported, using multiple hosts managed by a grid engine, such as the Portable Batch System (PBS Pro) by default. The grid engine works as a job scheduler. After the users submit the initial job, the grid engine will queue and run them, based on the resources and genome size they are assembling. By default, Canu will automatically detect the users’ system for grid support, and submit itself to the grid for execution. If they want to specify their grid options, they can use parameter gridOptions ="<your options list>", to provide memory and time limits, and account information. For example, gridOptions="--mem=100gb --time=168:00:00 --qos=account_name" is asking memory for 100gb, time limits for 168 hours, and specify account information to every job submitted by Canu. However, we do not recommend the users to define memory and time limits because Canu will always reserve their defined memory resources and time limits for every job. Each step of the three phases requires different memory and time to be finished. If the users request too much memory in gridOptions, most of their jobs are not using that much, so their assembly will spend more time waiting to run than actually running. That being said, to disable grid support, users must specify useGrid=false to run Canu on the local machine.
Trim the corrected reads
The trim phase will decide the high-quality regions using overlapping reads, and remove the remaining SMRTbell adapter sequences. The input data should be the output of the correction phase. The users need to use the -pacbio-corrected option, to provide the corrected PacBio reads as input data, and use the -trim option, to let Canu only trim the corrected reads. The output of the trimming phase will be one compressed fasta file with all corrected and trimmed reads (maize.trimmedReads.fasta.gz, in our example).
$ canu -trim \
-p maize -d maize \
genomeSize=2.3g \
-pacbio-corrected maize/maize.correctedReads.fasta.gz
[Tip 5] If the users have high PacBio coverage (>50 x), they could speed up the trimming phase, by increasing the minimum coverage and overlaps, to perform more stringent overlap-based trimming. The users can add the parameter (trimReadsCoverage=2 trimReadsOverlap=500) if they have >50 x coverage. The parameter trimReadsCoverage and trimReadsOverlap are used to define minimum depth of evidence, to retain bases and minimum overlap between evidence to make a contiguous trim.
Assemble the corrected and trimmed reads into unitigs
The assembly phase will identify the consistent overlaps, order and orient reads into contigs, and generate a consensus sequence for the unitig. The output of the trimming phase will be used for unitig construction. The users need the -pacbio-corrected option, to provide corrected and trimmed PacBio reads as input data, and use the -assemble option, to let Canu only assemble the corrected and trimmed reads. Canu will generate three assembled sequences, including maize.contigs.fasta, maize.unitigs.fasta, and maize.unassembled.fasta, wherein the maize.contigs.fasta is the primary output.
$ canu -assemble \
-p maize -d maize \
genomeSize=2.3g \
-pacbio-corrected maize/maize.trimmedReads.fasta.gz
[Tip 6] There are several parameters that may need tweaking to get the best genome assembly. First, the users can use different correctedErrorRate, to test the effect of different stringency on overlaps to be used on the assembly quality. We recommend setting up correctedErroRate as 0.035 for low coverage data (<30 x), and 0.055 for high coverage data (>50 x). Second, utgOvlErrorRate (overlaps generated for assembling reads above this error rate are not computed) is another parameter that needs tweaking. If set too high, it will result in errors in genome assembly and increase the running time, but, if set too low, real overlaps between low-quality reads will be missed, resulting in truncated genome assembly. We recommend setting up utgOvlErroRate as 0.035 for low coverage data (<30 x), and 0.055 for high coverage data (>50 x).
Assembly polishing
To improve the accuracy of the genome assembly, Arrow will be used to polish the contigs assembled from the Sequel System data, by mapping a set of raw PacBio raw reads to the contigs, and building a consensus of this read mapping. The variantCaller provided by GenomicConsensus package is the command line tool to call Arrow algorithm, to get consensus and variant calling on the mapped reads.
First, align the raw PacBio reads (*.subreads.bam files) to the assembled genome sequence, using pbalign with the following command:
$ pbalign raw_PacBio_1.subreads.bam maize.contigs.fasta raw_PacBio_1.subreads_aligned.bam
Optionally, the number of CPU threads (--nproc <int>) can be set.
If the users have multiple bam files, they can use sambamba to merge those aligned bam files into one. For instance, merge nine aligned bam files into one, as follows:
$ sambamba merge raw_PacBio.subreads_aligned_merged.bam \
raw_PacBio_1.subreads_aligned.bam \
raw_PacBio_2.subreads_aligned.bam \
raw_PacBio_3.subreads_aligned.bam \
raw_PacBio_4.subreads_aligned.bam \
raw_PacBio_5.subreads_aligned.bam \
raw_PacBio_6.subreads_aligned.bam \
raw_PacBio_7.subreads_aligned.bam \
raw_PacBio_8.subreads_aligned.bam \
raw_PacBio_9.subreads_aligned.bam
Before polishing the assembled genome sequence, the reference genome should be indexed with samtools faidx.
$ samtools faidx maize.contigs.fasta
Run the variantCaller command line tool to call Arrow on the merged and aligned bam files, if the users have multiple bam files, or on a single aligned bam file, if the users have only one bam file. The following command is used for call Arrow on merged and aligned bam files.
$ variantCaller --algorithm=arrow raw_PacBio.subreads_aligned_merged.bam \
--referenceFilename maize.contigs.fasta \
-j 32 \
-o Maize.contigs.polished.arrow.fastq \
-o Maize.contigs.polished.arrow.fasta \
-o Maize.contigs.polished.arrow.gff
where --algorithm sets the algorithm as Arrow, --referenceFilename provides the file name of the assembled genome FASTA file, -j is optional to set the number of threads, and -o sets the output files. The users can generate multiple outputs with different formats, including FASTA, FASTQ, GFF, and VCF.
It is highly recommended to use high-quality Illumina short-read data, to further polish the assembled genome sequence. Pilon is a commonly used pipeline to perform sequence error correction (Walker et al., 2014). In this protocol, we will use another pipeline called ntEdit to polish the assembled genome sequence. It is a bloom filter k-mer based approach that significantly reduces the running time, and makes fewer mistakes compared to Pilon (Warren et al., 2019).
First, run the tool ntHits to split the Illumina short reads into kmers. The kmers that pass the coverage thresholds will be used to build a bloom filter (BF).
$ nthits -c 2 --outbloom -p maize -b 36 -k 25 -t 8 \
maize.R1.pair.fq maize.R2.pair.fq
where -c sets the maximum coverage threshold for reporting kmer. We recommend setting -c as 1 for low coverage Illumina short-read data (<20 x), 2 for coverage (20–30 x), or running with the --solid with high coverage data (>30 x), to report non-error kmers. The option --outbloom will output the coverage-thresholded kmers in a bloom filter, and option -p will set the prefix for the output file name (the name of output of ntHits is maize_k25.bf based on the above settings). The bloom filter bit size is defined by the option -b [-b 36: keeps the Bloom filter false positive rate low (~0.0005)], and the kmer size can be adjusted using the option -k. Optionally, the number of CPUs can be set (-t <int>). The input file can be two pair-end fastq files, or a file listing the path to all pair-end fastq files.
Then, ntEdit will polish the Arrow-polished contigs from the assembled genome sequence, based on BF data.
$ ntedit -f Maize.contigs.polished.arrow.fasta \
-r maize_k25.bf -k 25 -b Maize.contigs.polished.arrow.ntedit -t 24
where -f is the users’ assembled genome input, -r sets the bloom filter file generated from ntHits, -k sets the length of the kmer, and -b sets the output file prefix (the name of output of ntHits is Maize.contigs.polished.arrow.ntedit_edited.fa based on the above settings). Optionally, the number of CPUs can be set (-t <int>).
Quality assessment
After genome assembly and genome polishing, it is necessary to check the completeness and duplication of the assembly. BUSCO is a commonly used tool to assess the completeness of the genome assembly (Simão et al., 2015). Check the newest version at https://busco.ezlab.org/. The users can run BUSCO by using the following command line:
$ run_BUSCO.py -i Maize.contigs.polished.arrow.ntedit_edited.fa \
-o PacBio_assembly.BUSCO -m geno -sp maize -l embryophyta_odb9
where -i is the assembled fasta sequence, -o is the output file name, -m sets the mode for BUSCO (geno or genome for genome assemblies, tran or transcriptome for transcriptome assemblies, or prot or proteins for annotated gene sets), and -l is the dataset used as reference for comparison [the lineage data (embryophyta_odb9) is related to maize]. The lineage data can be downloaded from the BUSCO website.
BUSCO assesses the completeness of the assembled genome, by quantitatively checking evolutionarily-informed expectations of gene content of near-universal single-copy orthologs. BUSCO will report the expected BUSCO genes in different categories: C:complete [S:single-copy, D:duplicated], F:fragmented, and M:missing. The results are reported as absolute numbers, as well as the percentage of the total BUSCO genes. In the above example, BUSCO analyzed the completeness of the assembled maize genome in terms of complete single-copy, complete duplicated, fragmented, and missing BUSCOs, using a plant-specific database (embryophyte_odb9) that consisted of 1440 total BUSCO groups from 30 species. For model species, the good assembled genome should have BUSCO score above 95% complete. The complete duplicated BUSCOs will reflect the duplications of the users’ assembly. If the users have a large amount of fragmented and missing BUSCOs, that means the users’ assembly is fragmented, and does not cover the entire genome.
Example of the protocol application – sweet corn genome assembly
The dataset provided in our original publication (Hu et al., 2021) will be used to describe this protocol. In summary, the sweet corn (Zea mays L.) inbred line Ia453 with sh2-R allele (Ia453-sh2) was sequenced. DNA from 1-week-old etiolated seedlings was extracted, using a modified CTAB method for PacBio sequencing. Large insert (20 kb) SMRTbell libraries were sequenced, using a PacBio Sequel system. DNA extracted from the same sample was used to build standard 300-bp Illumina libraries. All Illumina libraries were sequenced with 150 bp paired-end reads.
Genome assembly
For sweet corn genome assembly (Hu et al., 2021), around 19.9 million PacBio SMRT subreads were error-corrected, and assembled using Canu version 1.8. The correction phase of Canu was run with default parameters, except for the minimum read length (-minReadLength) set to 5000, to only correct reads longer than 5 kb, and the coverage in corrected reads (-corOutCoverage) set to 60, to get more corrected reads. With the read length cutoff as 5 kb, and read coverage as 60 x, around 12.3 million reads with 134 Gb (58.26 x coverage) were used for Canu correction. After correction, 9.8 million reads with 102.5 Gb remained. The trim and assembly phase of Canu were run using the default parameters: rawErrorRate=0.300, correctedErrorRate=0.045, corMhapSensitivity=normal, corMinCoverage=4, corOutCoverage=40, minOverlapLength=500, and minReadLength=1000. After trimming, around 1.08 million reads kept the same (no trimming), 8.64 million reads were trimmed, and 30,678 and 62,457 reads were deleted, due to no overlaps or short trimmed length. The remaining 9.7 million reads with 98.6 Gb (42.86 x coverage) were used for unitig construction. Finally, the assembly phase of Canu generated a consensus sequence for the unitig. The general statistics is shown in Table 1.
Table 1. The summary statistics of the sweet corn Ia453-sh2 assembly.
Genomic feature Assembly
Length of genome assembly (bp) 2,258,407,602
Max length (bp) 2,583,225
Contig N50 (bp) 385,558
Contig N90 (bp) 62,492
Number of contigs 15,550
Genome polishing
To improve the accuracy of the genome assembly, Arrow was used to correct the sequencing errors with default parameters. A total of 1,573,052 bases, including 999,948 bases of insertions, 57,359 bases of deletions, and 515,745 bases of substitutions were corrected.
Then, we ran ntEdit to further polish the genome assembly using ~23 x coverage of paired-end Illumina whole genome sequencing data. The ntHits was first ran with parameters “-k 25 -c 2” to build a bloom filter, which was read by ntEdit to polish the assembly with default parameters. A total of 832,323 changes were corrected, including 31.29% SNPs, and 68.7% small indels (2–25 bps).
Quality assessment
The genome completeness of the assembled genome sequence was assessed using the benchmarking universal single-copy orthologs (BUSCO) v3.02. The assembly was tested against the Plantae BUSCO “Embryophyta_odb9” database, which contained 1440 protein sequences and orthogroup annotations for major clades. BUSCO analysis showed that 94.6 % (1,363), 1.11 % (18), and 4.09 % (59) of the Plantae BUSCO genes are present in the Canu assembled Ia453-sh2 genome as complete, fragmented, and missing genes, respectively. Out of the 94.6% complete genes, 88.05% were single-copy genes, and 6.59% were duplicated genes.
Result interpretation
In order to assemble the Ia453-sh2 genome, 150.5 Gb (~70-fold coverage, 19.9 million reads) of PacBio single-molecule long reads were self-corrected and assembled with Canu, generating 15,550 contigs with an N50 of 0.39 Mb (Table 1). The quality and completeness of the Ia453-sh2 genome was evaluated through BUSCO. The BUSCO results are similar to what was obtained for field corn reference genomes, such as B73 v4 (Jiao et al., 2017), W22 (Springer et al., 2018), and Mo17 (Sun et al., 2018), indicating similar continuity and completeness of our assembly.
Discussion
This protocol is focusing on introducing how to assemble a maize genome with traditional PacBio long reads, using Canu version 1.8. However, for large and complex plant genomes, the assembly produced by Canu is usually fragmented, and requires additional scaffolding methods to improve genome assembly. In our recent sweet corn genome assembly study (Hu et al., 2021), other two data sources, including BioNano optical maps, and Dovetail Hi–C mapping, were used to generate high-quality and complete genome assembly. BioNano optical maps dramatically improved the genome assembly, by anchoring 15,550 PacBio contigs into 29 super scaffolds and 8486 unscaffolded contigs, and increased N50 from 0.39 Mb to 120.9 Mb. To further anchor and orient the super scaffolds and unscaffolded contigs into pseudochromosomes, Dovetail Hi–C mapping was used for scaffolding through a hierarchical clustering strategy. The final assembly has a genome length of 2.29 Gb, and contains 10 pseudochromosomes, with a total length of 2.11 Gb, as well as 8440 unassigned contigs, with a total length of 177.23 Mb. Therefore, single-molecule real-time (SMRT) long-read sequencing, combined with BioNano optical mapping and Dovetail Hi–C mapping technologies, helped us assemble a high-quality reference genome of sweet corn. For a detailed description of the method and parameters of BioNano optical mapping and Dovetail Hi-C, the users are referred to our sweet corn study (Hu et al., 2021).
Acknowledgments
This work was supported by the National Institute of Food and Agriculture (SCRI 2018-51181-28419 to M.F.R.R.).
Competing interests
The authors declare no conflicts of interest.
References
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Chin, C. S., Peluso, P., Sedlazeck, F. J., Nattestad, M., Concepcion, G. T., Clum, A., Dunn, C., O'Malley, R., Figueroa-Balderas, R., Morales-Cruz, A., et al. (2016). Phased diploid genome assembly with single-molecule real-time sequencing. Nat Methods 13(12): 1050-1054.
Haberer, G., Kamal, N., Bauer, E., Gundlach, H., Fischer, I., Seidel, M. A., Spannagl, M., Marcon, C., Ruban, A., Urbany, C., et al. (2020). European maize genomes highlight intraspecies variation in repeat and gene content. Nat Genet 52(9): 950-957.
Hufnagel, D. E., Hufford, M. B. and Seetharam, A. S. (2020). SequelTools: a suite of tools for working with PacBio Sequel raw sequence data. BMC Bioinformatics 21(1): 429.
Hufford, M. B., Seetharam, A. S., Woodhouse, M. R., Chougule, K. M., Ou, S., Liu, J., Ricci, W. A., Guo, T., Olson, A., Qiu, Y., et al. (2021). De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science 373(6555): 655-662.
Hu, Y., Colantonio, V., Muller, B. S. F., Leach, K. A., Nanni, A., Finegan, C., Wang, B., Baseggio, M., Newton, C. J., Juhl, E. M., et al. (2021). Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn. Nat Commun 12(1): 1227.
Jiao, Y., Peluso, P., Shi, J., Liang, T., Stitzer, M. C., Wang, B., Campbell, M. S., Stein, J. C., Wei, X., Chin, C. S., et al. (2017). Improved maize reference genome with single-molecule technologies. Nature 546(7659): 524-527.
Korlach, J., Officer, C. S. and Biosciences, P. (2013). Understanding Accuracy in SMRT® Sequencing. Technical Report.
Koren, S., Walenz, B. P., Berlin, K., Miller, J. R., Bergman, N. H. and Phillippy, A. M. (2017). Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 27(5): 722-736.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G. and Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16): 2078-2079.
Lin, G., He, C., Zheng, J., Koo, D. H., Le, H., Zheng, H., Tamang, T. M., Lin, J., Liu, Y., Zhao, M., et al. (2021). Chromosome-level genome assembly of a regenerable maize inbred line A188. Genome Biol 22(1): 175.
Nurk, S., Walenz, B. P., Rhie, A., Vollger, M. R., Logsdon, G. A., Grothe, R., Miga, K. H., Eichler, E. E., Phillippy, A. M. and Koren, S. (2020). HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. Genome Res 30(9): 1291-1305.
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Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. and Zdobnov, E. M. (2015). BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19): 3210-3212.
Sun, S., Zhou, Y., Chen, J., Shi, J., Zhao, H., Zhao, H., et al. (2018). Extensive intraspecific gene order and gene structural variations between Mo17 and other maize genomes. Nat Genet 50(9): 1289-1295.
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Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/Maize_Genome_Assembly_With_PacBio_Reads.
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4,457 | https://bio-protocol.org/en/bpdetail?id=4457&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Whole-mount Senescence-Associated Beta-Galactosidase (SA-β-GAL) Activity Detection Protocol for Adult Zebrafish
MM Marta Marzullo
MM Mounir El Maï
MF Miguel Godinho Ferreira
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4457 Views: 3414
Reviewed by: Pilar Villacampa Alcubierre Anonymous reviewer(s)
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Bio-protocol journal peer-reviewed
Jul 05, 2022 | This version
Preprint
Mar 07, 2022
Original Research Article:
The authors used this protocol in eLIFE May 2020
Abstract
Senescence-associated beta-galactosidase (SA-β-GAL) is an enzyme that accumulates in the lysosomes of senescent cells, where it hydrolyses β-galactosides. With p16, it represents a well-recognized biomarker used to assess senescence both in vivo and in cell culture. The use of a chromogenic substrate, such as 5-bromo-4-chloro-3-indoyl-β-d-galactopyranoside (X-Gal), allows the detection of SA-β-GAL activity at pH 6.0 by the release of a visible blue product. Senescence occurs during aging and is part of the aging process itself. We have shown that prematurely aged zebrafish accumulate senescent cells detectable by SA-β-GAL staining in different tissues, including testis and gut. Here, we report a detailed protocol to perform an SA-β-GAL assay to detect senescent cell accumulation across the entire adult zebrafish organism (Danio rerio). We also identify previously unreported organs that show increased cell senescence in telomerase mutants, including the liver and the spinal cord.
Keywords: SA-β-GAL Senescence Aging Whole organism Zebrafish
Background
Cellular senescence is defined as a permanent cell cycle arrest driven by different mechanisms (including telomere shortening, DNA damage, genotoxic stress, and inflammatory cytokines release) that culminate in the activation of p53 and the cyclin-dependent kinase inhibitor p16 (Collins and Sedivy, 2003; Coppé et al., 2008; Li et al., 2016). Alongside the activation of p53 and p16, senescent cells possess a panel of features, detected both in cell culture and in animal models, that can be used as biomarkers for cellular senescence (Gorgoulis et al., 2019). One of the most widely used markers for detecting senescent cells is the Senescence-associated beta-galactosidase (SA-β-GAL; Dimri et al., 1995), an enzyme that cleaves β-D-galactose residues in β-D-galactosides. This enzyme accumulates in the lysosomal compartment of senescent cells, where its activity is detectable at pH 6.0 (Dimri et al., 1995). The number and size of lysosomes increase in senescent cells; therefore, SA-β-GAL activity increase is also related to increased lysosome content (Lee et al., 2006).
Accordingly, a method has been developed to detect senescence cells based on the use of 5-bromo-4-chloro-3-indoyl-β-d-galactopyranoside (X-Gal), a colorless, soluble compound consisting of galactose linked to an indole. At pH 6.0, the SA-β-GAL enzyme hydrolyses the X-Gal, releasing a deep blue, insoluble product on the cell culture or in the tissue, allowing the detection of senescent cells (Dimri et al., 1995).
Previous studies revealed how senescent cells accumulate with aging (Biran et al., 2017). Consequently, SA-β-GAL activity increases with aging in different tissues. Using a zebrafish telomerase mutant (tert-/-), we previously showed that SA-β-GAL positive cells accumulate in the gut, testis, and kidney (Henriques et al., 2013; El Maï et al., 2020). We also discovered that progressive telomere shortening is associated with a cell fate transition from apoptosis to senescence during aging of telomerase deficient zebrafish. In young telomerase mutants, proliferative tissues exhibit DNA damage and p53-dependent apoptosis, but no senescence. However, the same tissues in older animals display loss of cellularity, increased pro-proliferation signaling, and cell senescence becomes predominant. We showed that prematurely aged fish accumulate senescent cells, detectable by SA-β-GAL staining, and correlate with increase in number of senescence-associated p16 positive cells (El Maï et al., 2020).
Common protocols designed to identify senescent cells in aged tissues are performed on isolated organs. One of the advantages of zebrafish is its small size. This peculiarity allows us to observe, in the same longitudinal histological section, several organs from the same individual. Here, we report a whole-mount SA-β-GAL assay to detect the accumulation of cell senescence in the entire adult zebrafish (Danio rerio). Fixed and stained fish can be sectioned and the slides analyzed under bright-field microscopy, or a slide scanner, for blue staining evaluation in the organs of interest.
Materials and reagents
Animals
Adult zebrafish (Danio rerio) 9-month-old
Materials
Polypropylene centrifuge tube 15 mL (Corning, catalog number: 352096)
Glass microscope Superfrost plus slides 25 × 75 × 1 mm (Menzel Gläser, catalog number: J1800AMNZ)
Cover Glass 24 × 36 mm (Labelians, catalog number: LCO2436)
Reagents
Tricaine/MS-222 (Pharmaq)
Tris base (Sigma-Aldrich, catalog number: T-1503)
PFA 16% (Thermo ScientificTM, catalog number: 28908)
Potassium hexacyanoferrate(II) trihydrate (Sigma-Aldrich, catalog number: P9387)
Potassium hexacyanoferrate(III) (Sigma-Aldrich, catalog number: 244023)
X-Gal (5-Bromo-4-Chloro-3-Indolyl-B-D-Galactopyranoside) (Sigma-Aldrich, catalog number: B4252)
N,N-Diméthylformamide (DMF) (Sigma-Aldrich, catalog number: 227056)
Magnesium Chloride Hexahydrate (MgCl2·6H2O, Sigma-Aldrich, catalog number: 7791-18-6)
Sodium Chloride (NaCl, Sigma-Aldrich, catalog number: S7653)
Potassium Chloride (KCl, Sigma-Aldrich, catalog number: 7447-40-7)
Sodium phosphate dibasic (Na2HPO4, Sigma-Aldrich, catalog number: 71505)
Potassium phosphate dibasic (KH2PO4, Sigma-Aldrich, catalog number: 1.05104)
Ethylenediaminetetraacetic acid (EDTA, VWR, catalog number: A10713.0I)
Nuclear Fast red (Sigma-Aldrich, catalog number: 1001210500)
Histology cassettes (Simport, catalog number: M505)
Embedding Molds (Sakura Finetek, catalog number: 4133)
10% buffered Formalin (VWR, catalog number: 9713.9010)
Xylene (VWR, catalog number: 28973.363)
Ethanol 100% (EtOH, VWR, catalog number: VWRC20821.330)
Paraffin (Merck Millipore, catalog number: 1.11609.9025)
1 M Tris pH 9 (see Recipes)
Tricaine/MS-222 400 mg/L solution (see Recipes)
Tricaine/MS-222 200 mg/L solution (see Recipes)
4% Paraformaldehyde (see Recipes)
10× Phosphate Buffered Saline (PBS, pH 7.4) (see Recipes)
1× Phosphate Buffered Saline (PBS, pH 7.4) (see Recipes)
1× Phosphate Buffered Saline (PBS, pH 6) (see Recipes)
Ethylenediaminetetraacetic acid (EDTA, 0.5 M, pH 8) (see Recipes)
X-Gal stock solution (25 mg/mL) (see Recipes)
X-Gal staining solution (see Recipes)
Potassium hexacyanoferrate (II) trihydrate (0.5 M) (see Recipes)
Potassium hexacyanoferrate (III) (0.5 M) (see Recipes)
Magnesium Chloride (MgCl2 0.5 M) (see Recipes)
X-Gal staining solution (see Recipes)
Ethanol 70% (see Recipes)
Ethanol 95% (see Recipes)
Equipment
Roller mixer (CAT Ingenieurbuero, catalog number RM5)
Dry incubator at 37°C (Memmert, catalog number: UNB 100)
NanoZoomer Digital slide scanner (Hamamatsu, catalog number: C13140-01)
Tissue processor (Leica Biosystems, catalog number: HistoCore PEARL)
Tissue Embedding Console System (Sakura Finetek, catalog number: Tissue-Tek® TECTM 5)
Automated Rotary Microtome (Leica Biosystems, catalog number: RM2255)
Software
NDP.view2 Image viewing software (U12388-01 Hamamatsu) to open and analyze NanoZoomer scans. Free download from https://www.hamamatsu.com/eu/en/product/life-science-and-medical-systems/digital-slide-scanner/U12388-01.html
Procedure
SA-β-GAL Staining procedure
Day 0
Starve the fish overnight for at least 17 h, leaving them in their aquarium.
Day 1
Sacrifice fish by placing them in a container with 50 mL of 200 mg/L Tricaine MS-222 for 30 min.
Note: Death can be determined by checking cessation of breath and gill movements.
Proceed with fixation by individually incubating fish in 15 mL centrifugation tubes containing at least 10 mL of 4% PFA for 3 days, at 4°C on the roller mixer.
Notes:
Differences in PFA quality might affect fixation of the entire fish and, therefore, the quality of β-galactosidase detection. It is then important to prepare fresh 4% PFA solution for each experiment.
Incubation with gentle agitation helps the penetration of PFA and improves fixation of inner organs.
Day 4
Wash each sample three times for 1 h in at least 10 mL of PBS pH 7.4, at 4°C on the roller mixer.
Wash each sample 1 h in at least 10 mL of PBS pH 6.0, at 4°C on the roller mixer.
Note: Pre-incubating fish at pH 6.0 is crucial to ensure an optimal SA-β-GAL reaction in the next step of the protocol.
Incubate each fish with at least 10 mL of X-Gal staining solution for 24 h at 37°C in the dark.
Note: It is crucial to ensure that SA-β-GAL activity detection is performed at pH 6.0. Lowering the pH below pH 5.9 results in false positives, while increasing the pH above pH 6.1 produces false negatives.
Day 5
Wash each sample three times for 5 min in at least 10 mL of PBS pH 7.4 at room temperature on the roller mixer.
Proceed with de-calcification for 48 h in 10 mL of 0.5 M EDTA pH 8 at room temperature.
Note: To avoid loss of SA-β-GAL staining, fish should not be incubated for more than 48 h in EDTA.
Embedding procedure
After de-calcification, remove EDTA by incubating fish in water for at least 30 min at room temperature.
Insert each sample into a histology cassette.
Proceed with the embedding of the samples in a tissue processor using the following program:
10% buffered formalin for 1 h
Distilled water for 2 min
Ethanol 70% for 2 h
Ethanol 95% for 1 h
Ethanol 100% for 1 h
Ethanol 100% for 1 h
Ethanol 100% for 2 h
Ethanol 100% for 1 h
Xylene for 30 min
Xylene for 1 h
Xylene for 1 h
Paraffin for 30 min at 62°C
Paraffin for 1 h at 62°C
Paraffin for 1 h at 62°C
Using the Tissue Embedding Console System, insert each sample into an embedding mold and pour paraffin into the mold. Allow for solidification of the paraffin block by placing the mold containing each sample and paraffin onto the cryomodule plate of the Tissue Embedding Console.
Counterstaining procedure
Prepare 5 µm section slides from each paraffin-embedded sample using a microtome.
Counterstain the slides with Nuclear fast red, following the manufacturer’s protocol. Briefly, after conventional deparaffinization and rehydration, wash slides for 1 min at room temperature in distilled water and stain them by incubating for 10 min at room temperature in Nuclear fast red-aluminum sulfate solution 0.1%. After 1 min, wash in distilled water and proceed with conventional dehydration and xylene incubation prior to slide mounting.
Image acquisition
Acquire images using a bright-field microscope or slide scanner.
Note: The images of the different tissues shown in Figure 1 have been selected from a scan of a whole-body fish section. The slide scans were acquired with a NanoZoomer Digital slide scanner with a 40× source lens and analyzed with the NDPi software.
Figure 1. SA-β-GAL staining allows the detection of cell senescence in prematurely aged zebrafish tissues. A) Representative images of fish assayed for SA-β-GAL activity. Blue staining shows the presence of SA-β-GAL in different tissues of prematurely aged fish (tert-/-) compared to age-matched controls (wild type, WT). Corresponding scale bar represented in each panel B) Zoom-in of gut villi in A, allowing to precisely distinguish the cells stained in blue. Scale bar 50 μm.
Note: A significant increase in SA-β-gal positive cells is seen by 9 months of age in tert-/- tissues and by 24 months in WT tissues.
Concluding Note:
We analyzed different tissues of adult zebrafish for presence of SA-β-GAL blue staining. Intensity and localization may change due to biological or technical issues (i.e., age of the fish, health status, penetration of the fixative, longitudinal sections, etc.). Thus, it is crucial to have the proper number of technical and biological replicates for effective result interpretation. In our experiments, we performed a minimum of three biological replicates for each genotype and age.
Recipes
1 M Tris pH 9
Dilute 121.4 g tris base in 850 mL of Milli-Q water.
Adjust pH to 9.
Bring volume to 1 L.
Tricaine/MS-222 400 mg/L solution
Dissolve 2 g of tricaine/MS-222 in 489.5 mL of Milli-Q water.
Add 10.5 mL of 1 M Tris (pH 9).
Adjust pH to 7.
Tricaine/MS-222 200 mg/L solution
Add 50 mL of tricaine/MS-222 to 50 mL of fish system water.
4% Paraformaldehyde
Make fresh solution by adding 10 mL PFA 16% to 30 mL of PBS.
10× Phosphate Buffered Saline (PBS, pH 7.4)
Add 80 g of NaCl, 2.0 g of KCl, 14.4g of Na2HPO4, and 2.4 g of KH2PO4 to 800 mL of Milli-Q water.
Adjust pH to 7.4.
Bring volume to 1 L.
Autoclave and store at room temperature.
1× Phosphate Buffered Saline (PBS, pH 7.4)
Dilute 100 mL of 10× PBS pH 7.4 in 900 mL of Milli-Q water and keep at 4°C.
1× Phosphate Buffered Saline (PBS, pH 6)
Dilute 100 mL of 10× PBS pH 7.4 in 800 mL of Milli-Q water.
Adjust the pH to 6.0.
Bring up the volume to 1 L and keep at 4°C.
Ethylenediaminetetraacetic acid (EDTA, 0.5 M, pH 8)
Add 146.12 g of EDTA to 850 mL of Milli-Q water.
Adjust the pH to 8.0.
Bring up the volume to 1 L.
Filter and store at room temperature.
X-Gal stock solution (25 mg/mL)
Dissolve 150 mg of X-Gal in 5mL of DMF.
Potassium hexacyanoferrate (II) trihydrate (0.5 M)
Dissolve 2.11 g of Potassium hexacyanoferrate (II) in 10 mL of Milli-Q water.
Store at 4°C in the dark.
Potassium hexacyanoferrate (III) (0.5 M)
Dissolve 1.646 g of Potassium hexacyanoferrate (III) in 10 mL of Milli-Q water.
Store at 4°C in the dark.
Magnesium Chloride (MgCl2 0.5 M)
Dissolve 5.1 g of Magnesium Chloride Hexahydrate in 50 mL of Milli-Q water.
X-Gal staining solution
To prepare the SA-β-GAL staining solution (1 mg/mL X-Gal, 5 mM potassium ferrocyanide, 5 mM potassium ferricyanide, 2 mM Magnesium chloride in PBS pH 6), add 1 mL of 0.5 M Potassium hexacyanoferrate (II) trihydrate, 1 mL of 0.5 M Potassium hexacyanoferrate (III), 400 µL of 0.5 M MgCl2 and 4 mL of 25mg/mL X-Gal to 93.6 mL of 1× PBS pH 6.0.
Make a fresh solution for each experiment and keep it in the dark until use.
Note: X-Gal concentration can be adjusted up to 1.5% to increase the staining.
Ethanol 70%
Add 300 mL of Milli-Q water to 700 mL of ethanol 100%.
Ethanol 95%
Add 50 mL of Milli-Q water to 950 mL of ethanol 100%.
Acknowledgments
The protocol described has been previously used and described in El Maï et al. (2020).
We thank the Instituto Gulbenkian de Ciência histology unit for assistance with experimental planning, sample processing, and data collection, and the IGC Fish Facility for excellent animal care. IGC Fish Facility is financed by Congento LISBOA-01–0145-FEDER-022170, co-financed by FCT (Portugal) and Lisboa2020, under the PORTUGAL2020 agreement (European Regional Development Fund). MEM is a recipient of a postdoctoral fellowship from the Ville de Nice. This work was supported by the Fondation pour la Recherche Médicale FRM (EQU201903007804) and the Agence Nationale de la Recherche (ANR-21-CE14-0054) grants received by MGF.
Ethics
Animal experimentation: All Zebrafish work was conducted in Portugal according to National Guidelines and approved by the Ethical Committee of the Instituto Gulbenkian de Ciência and the Direção Geral de Alimentação e Veterinária (DGAV, Approval number: 010294) and in France by the Animal Care Committee of the IRCAN, the regional (CIEPAL Cote d’Azur 531 #697) and national (French Ministry of Research #27673-2020092817202619) authorities.
Competing interests
The authors declare that no competing interests exist.
References
Biran, A., Zada, L., Abou Karam, P., Vadai, E., Roitman, L., Ovadya, Y., Porat, Z. and Krizhanovsky, V. (2017). Quantitative identification of senescent cells in aging and disease. Aging Cell 16(4): 661-671.
Collins, C. J. and Sedivy, J. M. (2003). Involvement of the INK4a/Arf gene locus in senescence. Aging Cell 2(3): 145-150.
Coppé, J. P., Patil, C. K., Rodier, F., Sun, Y., Munoz, D. P., Goldstein, J., Nelson, P. S., Desprez, P. Y. and Campisi, J. (2008). Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol 6(12): 2853-2868.
Dimri, G. P., Lee, X., Basile, G., Acosta, M., Scott, G., Roskelley, C., Medrano, E. E., Linskens, M., Rubelj, I., Pereira-Smith, O., et al. (1995). A biomarker that identifies senescent human cells in culture and in aging skin in vivo. Proc Natl Acad Sci U S A 92(20): 9363-9367.
El Maï, M., Marzullo, M., de Castro, I. P. and Ferreira, M. G. (2020). Opposing p53 and mTOR/AKT promote an in vivo switch from apoptosis to senescence upon telomere shortening in zebrafish. Elife 9: e54935.
Gorgoulis, V., Adams, P. D., Alimonti, A., Bennett, D. C., Bischof, O., Bishop, C., Campisi, J., Collado, M., Evangelou, K., Ferbeyre, G. et al., (2019). Cellular Senescence: Defining a Path Forward. Cell 179(4): 813-827.
Henriques, C. M., Carneiro, M. C., Tenente, I. M., Jacinto, A. and Ferreira, M. G. (2013). Telomerase is required for zebrafish lifespan. PLoS Genet 9(1): e1003214.
Lee, B. Y., Han, J. A., Im, J. S., Morrone, A., Johung, K., Goodwin, E. C., Kleijer, W. J., DiMaio, D. and Hwang, E. S. (2006). Senescence-associated beta-galactosidase is lysosomal beta-galactosidase. Aging Cell 5(2): 187-195.
Li, T., Liu, X., Jiang, L., Manfredi, J., Zha, S. and Gu, W. (2016). Loss of p53-mediated cell-cycle arrest, senescence and apoptosis promotes genomic instability and premature aging. Oncotarget 7(11): 11838-11849.
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In vivo Characterization of Endogenous Protein Interactomes in Drosophila Larval Brain, Using a CRISPR/Cas9-based Strategy and BioID-based Proximity Labeling
EU Ezgi Uçkun
GW Georg Wolfstetter
JF Johannes Fuchs
RP Ruth H. Palmer
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4458 Views: 2540
Reviewed by: David PaulRajesh RanjanSonya Nassari
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Original Research Article:
The authors used this protocol in Journal of Molecular Biology Nov 2021
Abstract
Understanding protein-protein interactions (PPIs) and interactome networks is essential to reveal molecular mechanisms mediating various cellular processes. The most common method to study PPIs in vivo is affinity purification combined with mass spectrometry (AP–MS). Although AP–MS is a powerful method, loss of weak and transient interactions is still a major limitation. Proximity labeling (PL) techniques have been developed as alternatives to overcome these limitations. Proximity-dependent biotin identification (BioID) is one such widely used PL method. The first-generation BioID enzyme BirA*, a promiscuous bacterial biotin ligase, has been effectively used in cultured mammalian cells; however, relatively slow enzyme kinetics make it less effective for temporal analysis of protein interactions. In addition, BirA* exhibits reduced activity at temperatures below 37°C, further restricting its use in intact organisms cultured at lower optimal growth temperatures (e.g., Drosophila melanogaster). TurboID, miniTurbo, and BirA*-G3 are next generation BirA* variants with improved catalytic activity, allowing investigators to use this powerful tool in model systems such as flies. Here, we describe a detailed experimental workflow to efficiently identify the proximal proteome (proximitome) of a protein of interest (POI) in the Drosophila brain using CRISPR/Cas9-induced homology-directed repair (HDR) strategies to endogenously tag the POI with next generation BioID enzymes.
Keywords: BirA MiniTurbo TurboID Proximitome Proteomics
Background
There are numerous approaches to identify protein-protein interactions (PPI)s, including yeast two-hybrid (Y2H), affinity purification combined with mass spectrometry (AP–MS), and proximity labeling (PL). Conventional methods such as Y2H and AP–MS are commonly used to identify interacting protein partners. However, these methods rely on high affinity and stable protein interactions and are less effective at identifying weakly and/or transiently interacting partners (Rees et al., 2015). In the past decade, PL methods coupled to MS have been developed as a powerful complementary approach and utilized to reveal PPI networks in spatial and temporal detail (Bosch et al., 2021; Qin et al., 2021). In general, PL enzymes are fused to a protein of interest (POI), where they convert a small molecule substrate to a reactive intermediate that, upon release, covalently labels proteins in close proximity (Xu et al., 2021).
Proximity-dependent biotin identification (BioID) is one of the commonly employed PL techniques based on BirA, a 35 kDa biotin protein ligase from Escherichia coli. Wild-type BirA converts biotin to reactive biotinoyl-5’-AMP in the presence of ATP and labels exposed lysine residues of substrates with biotin. BioID-based PL utilizes a mutant form of BirA (BirA[R118G], referred to as BirA*), which has lower affinity for reactive biotinoyl-5’-AMP compared to wild-type BirA and thereby prematurely releases reactive biotin resulting in promiscuous biotinylation of neighboring proteins (Roux et al., 2012; Sears et al., 2019). Biotinylated proteins are then pulled down with affinity reagents and analyzed by MS to map the protein interactome. BirA* enzymes derived from Aquifex aeolicus (BioID2) and Bacillus subtilis (BASU) as well as engineered forms of E. coli BirA* (miniTurbo, TurboID, and BirA*G3) offer the advantage of increased enzymatic activity and/or smaller size, and have been successfully used for PL-strategies (Kim et al., 2016; Branon et al., 2018; Ramanathan et al., 2018; Samavarchi-Tehrani et al., 2020; Droujinine et al., 2021).
One important consideration when using PL enzymes is the expression level, as it has been shown to have significant effects on the obtained interactome maps, especially in systems where expression cannot be tightly controlled, like endogenous protein expression (Shiraiwa et al., 2020; Xu et al., 2021). Overexpression alters the spatio-temporal occurrence of a POI and might interfere with its localization and/or physiological function, eventually resulting in biotin-labeling artifacts. As an alternative, CRISPR/Cas9-mediated HDR strategies allow modifying endogenous gene loci to express in-frame chimeras of the POI and a next generation PL enzyme under the control of endogenous regulatory elements.
Here, we provide a detailed protocol to generate endogenous BioID fusions in Drosophila and perform in vivo PL in larval brains of these flies, followed by liquid chromatography–tandem mass spectrometry cubed (LC–MS3) analysis.
Materials and Reagents
1.5 mL microcentrifuge tube (Biotix, catalog number: MTL-0150-BC)
2.0 mL microcentrifuge tube (Biotix, catalog number: MT-0200-BC)
Acetonitrile hypergrade (Merck, catalog number: 75-05-08)
Apple juice (any brand)
Bacto-agar (Sigma, catalog number: A5306)
cOmpleteTM, Mini, EDTA-free protease inhibitor cocktail (Roche, catalog number: 11836170001)
D-(+)-Biotin, 98+% (Alfa Aesar, catalog number: A14207)
Dithiothreitol (DTT) (Roche, catalog number: 11583786001)
Drosophila sorting brush (any brand)
DynabeadsTM MyOneTM Streptavidin C1 (Thermo Fisher Scientific, catalog number: 65002)
Embryo collection cages (Genesee Scientific, catalog number: 59-100)
Ethanol 96% vol (VWR Chemicals, catalog number: 83804.360)
Fly food (Nutri-Fly Bloomington formula (BF), Genesee Scientific, catalog number: 66-113)
Fly food vials (VWR, catalog number: 734-2264)
Formic acid (VWR Chemicals, HiPerSolv CHROMANORM for LC–MS, catalog number: 84865.290)
Goat anti-biotin HRP (Cell Signaling Technology, catalog number: 7075)
Methyl methanethiosulfonate (Sigma-Aldrich, catalog number: 64306-10mL)
Methyl-4-hydroxybenzoate (Sigma-Aldrich, catalog number: H5501-500G)
Petri dishes (VWR, catalog number: 390-1373)
Phosphate-buffered saline (PBS) tablets (Medicago, catalog number: 09-9400-100)
phosSTOPTM phosphatase inhibitor tablet (Roche, catalog number: 4906837001)
PierceTM High pH Reversed-Phase Peptide Fractionation Kit (Pierce, catalog number: 84868)
PierceTM BCA Protein Assay Kit (Thermo Fisher Scientific, catalog number: 23225)
Rabbit 11H10 anti-α-tubulin (Cell Signaling Technology, catalog number: 2125)
rLys-C (Promega, catalog number: V1671)
Sucrose (Sigma, catalog number: S0389)
Tissue grinding pestles (Kisker Biotech, catalog number: 033522)
TMTproTM 16plex Label Reagent Set (Thermo Fisher Scientific, catalog number: A44521)
Triethylammonium bicarbonate (Honeywell Fluka, catalog number: 17902-100mL)
Trifluoroacetic acid (Sigma-Aldrich, catalog number: 299537-50g)
Tris (2-carboxyethyl) phosphine (Thermo Scientific, catalog number: 77720)
Tris-Cl pH 7.4 (Alfa Aesar, catalog number: J60202.K2)
PierceTM Trypsin protease (Pierce, catalog number: 90057)
Yeast paste (baker’s yeast in tab water) (Kisker Biotech, catalog number: 789093)
Apple-juice agar plates (see Recipes)
25% ethanolic Methyl-4-hydroxybenzoate (see Recipes)
4× Laemmli Buffer (see Recipes)
RIPA buffer (see Recipes)
Wash buffer 1 (see Recipes)
Wash buffer 2 (see Recipes)
Wash buffer 3 (see Recipes)
Equipment
Acclaim TM PepMap TM 100 C18 HPLC Column (Thermo Fisher Scientific, catalog number: 164199)
Easy-nLC TM 1200 (Thermo Fisher Scientific, catalog number: LC140)
Heating block (Grant, model: QBD2)
Incubator (Termaks, catalog number: TS 8056)
In-house packed analytical column (ESI Source Solutions, catalog number: PTC3-75-50-SP)
Magnetic stand (Thermo Fisher Scientific, model: DynaMag-2)
Microcentrifuge (Thermo Fisher Scientific, model: Fresco 21)
Microcentrifuge (VWR, model: CT15RE)
Orbitrap FusionTM LumosTM TribridTM mass spectrometer interfaced with an Easy-nLC1200 liquid chromatography system (Thermo Fisher Scientific, catalog number: IQLAAEGAAPFADBMBHQ)
Reprosil-Pur C18 (Dr. Maisch, catalog number: R13.AQ.0001)
Rotator (Thermo Fisher Scientific, Labquake, catalog number: 13-687-12Q)
Ultrapure water system (Elga LabWater, Purelab)
Vacuum centrifuge (Genevac, miVac, catalog number: DUC-23050-B00)
Software
Mascot (Matrix Science, Version 2.5.1)
Proteome DiscovererTM (Thermo Fisher Scientific, Version 2.4, catalog number: OPTON-30945)
Procedure
A CRISPR-Cas9-mediated HDR strategy to endogenously tag a POI with BioID-enzymes
A detailed protocol for the generation of CRISPR components and screening strategies in Drosophila can be found in Housden et al. (2014).
Guide RNA design and cloning
Select one or two suitable CRISPR target sites using the flyCRISPR Target Finder tool (http://targetfinder.flycrispr.neuro.brown.edu/) (Gratz et al., 2014). The target site should ideally be located in close proximity (≤100 bp) to the intended hinge region between the endogenous coding DNA sequence (CDS) of the POI and the BioID-encoding insert. Guide sequences with estimated off-targets (annotated in the flyCRISPR Target Finder tool) should be avoided. We followed the flyCRISPR protocol for cloning guide plasmids (available at https://flycrispr.org/protocols/grna/).
Note: If not possible otherwise, one off-target sequence on a different chromosome can be tolerated since the affected chromosome can be removed later during the screening process. A CRISPR off-target site might nonetheless decrease the number of positive candidates obtained.
dsDNA donor design and cloning
Small, commonly used bacterial plasmids (e.g., puc57, pBlueScript II, or pCRII Topo) can be efficiently employed as vector backbone. Gene-specific homology arms (from 0.5-1kb length; longer and shorter sequences can also be chosen but might affect HDR efficiency) are cloned from a genomic DNA source by standard procedures. Codon-optimized CDS of BioID-enzymes should be used for optimal codon usage in the targeted species. Plasmids for expression of next-generation BioID enzymes, miniTurbo (number 116905), and TurboID (number 116904) can be obtained from Addgene and used as template for amplification. Short and flexible amino acid linker sequences such as 1-4x[Glycine-Glycine-Serine-Glycine] or 1-4x[Glycine-Serine-Alanine-Threonine] between the POI and the BioID enzyme can be introduced to minimize potential effects on POI function caused by steric hindrance (http://parts.igem.org/Protein_domains/Linker, available @ igem.org, 22 April 2022). However, it should be considered that linker sequences likely increase the BioID labeling radius. Small protein tags, e.g., HA (amino acid sequence Tyr-Pro-Tyr-Asp-Val-Pro-Asp-Tyr-Ala) or OLLAS: Ser-Gly-Phe-Ala-Asn-Glu-Leu-Gly-Pro-Arg-Leu-Met-Gly-Lys) can also be added to analyze expression and localization of the chimeric protein. Several strategies can be used to mask the CRISPR target site for Cas9 recognition in the donor vector: (1) changing Guanine(s) within the NGG PAM sequence, thereby introducing a silent mutation in the POI’s CDS; (2) if changing the NGG sequence is not feasible, several nucleotides in the target sequence can be altered, introducing silent point mutations in the POI’s CDS; (3) placing the CRISPR target site over the intended hinge region so that the recognized sequence will be split and separated by the BioID-encoding insert. The last approach is recommended if the NGG PAM following the target sequence is located in a non-protein-coding region where base-pair alterations could affect gene expression.
Notes:
Sequence information of the miniTurbo and TurboID next generation BioID enzymes (Branon et al., 2018) can be obtained from plasmids deposited at Addgene #116905 and #116904, respectively. These can be employed as templates for amplification.
Scarless gene editing provides a donor vector system that simplifies the candidate screening process (https://flycrispr.org/scarless-gene-editing/).
AviTagTM (Schatz, 1993; Cognet et al., 2005) can be used to incorporate artificial biotinylation sites in the POI or possible proximitome candidates. In case of no or few accessible lysine residues, this can serve as a BioID positive control (adding AviTag to the POI) or to enable detection of a proximitome candidate by MS.
Plasmid injection into Drosophila embryos
Injection of guide RNA and dsDNA donor plasmids in Drosophila embryos that express Cas9 in their germ line can either be done by following flyCRISPR injection protocols (https://flycrispr.org/protocols/injection/) or using a Drosophila microinjection facility or commercial injection service.
Note: Several transgenic Drosophila stocks expressing Cas9 in their germ line (e.g., M{vas-Cas9}ZH-2A) are available for injection. It should be taken into account that the genetic background of the injection stock should a) be identical to the genetic background that was used to select the CRISPR/Cas9 guide RNA target sites, and b) not distort the following experimental analysis (certain traits, e.g., sleep and life span are highly impacted by genetic background). Furthermore, the source of the Cas9-transgene should be located on a different chromosome than the targeting region.
Screening for CRISPR-mediated HDR events
Parental (P) male flies derived from the injected embryos are crossed individually to female virgin flies from a suitable balancer stock. P female flies are crossed “en masse” to suitable balancer males. After 2–3 days, egg-laying females can be identified and isolated in fresh culture vials. Isolation of fertile females can be continued on every other day. Excluding non-fertile females at this point significantly reduces consumables and work spent during the screening process. Two to five F1 males from each parental cross are isolated and crossed individually to balancer females. When larval progeny is visible in the F1 cross, the F1 males can be sacrificed for genomic DNA isolation and further genotyping using single fly PCR screening.
Note: We follow a standard single fly DNA preparation protocol (available, e.g., fromhttp://francois.schweisguth.free.fr/protocols/Single_fly_DNA_prep.pdf) with the following modifications: Proteinase K digestion is done in a PCR-cycler for 30 min at 50°C, followed by enzyme inactivation for 10 min at 85°C. We typically prepare 25 µL PCR mixes with 2.5 µL from the crude DNA preparation as template solution. Positive candidates should be analyzed by Sanger sequencing before further experiments are conducted.
In vivo labeling of the POI interactome in Drosophila
Place an apple-agar plate with a smear of yeast paste in an embryo collection cage.
Transfer 40–50 young (<7 days) female and male flies expressing the chimeric BioID-POIs to the embryo cages and allow egg laying for 2–8 h. If sufficient eggs are laid, remove plates from the cage and age at 25°C. If not, replace with a new apple-agar plate for another egg laying period.
Note: As a background control, use an appropriate reference fly stock that closely matches the genetic background of your genetically engineered flies (e.g., w1118 or Canton-S).
After 22–23 h, remove hatched larvae from the plate using a Drosophila sorting brush and check again every hour for freshly hatched first instar L1 larvae. Transfer 50 L1 larvae from the same collection point into a Drosophila culture vial containing a sufficient amount of Bloomington formula (BF) fly food supplemented with 100 µM biotin. For each genotype/condition/replicate, prepare at least five vials.
Notes:
Biotin stock is prepared with water and incorporated into fly food after cooking before pouring into the vials to make 100 µM final concentration.
Synchronizing developmental timing at this step is important obtain the proximitome from a homogeneous population of age-matched third instar larvae.
Higher concentrations of supplemented biotin resulted in lethality of control larvae that did not express any BioID-fusion protein (Uçkun et al., 2021).
Collect 150 biotin-fed third instar larvae (72–120 h after egg laying; 48–96 h after hatching) for each genotype/condition/replicate.
Protein extraction from Drosophila larval brains
Dissect 150 larval brains (Hafer and Schedl, 2006) in ice-cold PBS and transfer to a microcentrifuge tube containing 300–400 µL PBS on ice.
Notes:
Dissection is ideally performed by multiple persons to avoid sample decay and de-synchronizing of developmental timing. If the dissection is performed by only one person, several rounds of dissection for one genotype/condition/replicate are required.
Dissected brains can be snap-frozen in liquid nitrogen and stored at -80°C until the required sample size is collected.
After dissection is complete, remove the PBS and lyse dissected third instar larval brains directly in 700 µL of RIPA buffer supplemented with 1× cOmpleteTM Mini EDTA-free protease inhibitor cocktail, 1× phosSTOPTM phosphatase inhibitor, and 1 mM DTT using a tissue grinding pestle.
Centrifuge samples at 21,500 × g at 4°C for 20 min and transfer supernatant to a new microcentrifuge tube.
Perform BCA assays to determine protein concentration for each sample.
Notes:
Equal or greater than 1 mg of total protein for each sample/replicate/condition is desirable.
BCA assay is performed according to the PierceTM BCA Protein Assay Kit user guide.
Normalization of protein quantity is required prior to pull-down if different numbers of brains are lysed, and protein concentration varies between samples. This can be done by diluting more concentrated samples with RIPA buffer.
Transfer 50 µL of lysate to a separate microcentrifuge tube for western blot analysis and validation of protein biotinylation; 50 µg protein is sufficient for western blot analysis of biotinylated proteins. Use specific antibodies to detect your POI or an optional protein tag as well as anti-Biotin-HRP/Streptavidin-HRP to confirm increased protein biotinylation. Use antibodies against housekeeping proteins (such as anti α-tubulin) as loading control.
Note: Protocols for western blotting of biotinylated proteins with some examples are available in Roux et al. (2013).
Pull-down of biotinylated proteins
This pull-down protocol is adapted from Roux et al. (2013).
Prepare 1.5 mL microcentrifuge tubes for each sample/replicate and place on a magnetic stand.
Note: The following steps are performed at room temperature.
Add 500 µL of RIPA buffer and 500 µL of 50 mM Tris-Cl pH 7.4 to each tube.
Homogenize DynabeadsTM MyOneTM Streptavidin C1 stock solution by gently tapping and add 300 µL to each tube. Place tubes in the magnetic stand and wait 3 min.
Note: The quantity of streptavidin beads used will depend on the amount of protein in the sample; 300 µL of beads are sufficient for 1–1.5 mg of total protein. Use more beads for higher protein amounts.
Gently remove supernatant and add 700 µL of protein lysate corresponding to at least 1 mg of total protein from step C3.
Resuspend the lysate with beads and incubate on a rotator at 4°C overnight.
Place tubes in the magnetic stand and wait 3 min.
Transfer the supernatant to a new 1.5 mL microcentrifuge tube labeled as flow-through.
Note: Flow-through labeled supernatant allows assessment of pull-down efficiency in western blotting, when compared to samples from step C5.
Resuspend beads with1.5 mL of wash buffer 1.
Place tubes on rotator at room temperature for 8 min.
Place tubes in magnetic stand and wait 3 min.
Remove supernatant and repeat steps D8–D10.
Resuspend beads with 1.5 mL of wash buffer 2 and repeat steps D9–D10.
Resuspend beads with 1.5 mL of wash buffer 3 and repeat steps D9–D10.
To remove detergent, wash beads four times with 1.5 mL 50 mM Tris-Cl pH 7.4 following the procedure described in steps D8–D10.
Remove 150 µL of resuspended beads to a new tube for western blot analysis and keep the remaining 1.35 mL of resuspended beads for MS analysis.
Spin both 150 µL and 1.35 mL aliquots of resuspended beads at 2,000 × g at room temperature for 5 min.
For western blot samples prepared in steps D15–D16, remove supernatant and add 100 µL of 1× LaemmLi buffer. Heat samples at 95°C for 5 min and centrifuge at 18,700 × g, 4°C for 10 min. The supernatant can be stored at -20°C for further western blot analysis.
For MS analysis, remove the supernatant from 1.35 mL samples and resuspend beads with 200 µL Tris-Cl pH 7.4.
Elution, reduction, alkylation, and tryptic digestion of biotinylated proteins
Pellet beads for 1 min using a magnetic stand and remove supernatant.
Wash beads twice with 1 mL of 50 mM triethylammonium bicarbonate (TEAB).
Add 100 µL of 50 mM TEAB to beads. Flip tubes gently five times so that all beads are in motion.
For proteolytic bead-elution, add 10 µL of 0.05 µg/µL rLys-C dissolved in the resuspension buffer provided with the enzyme directly to the sample.
Incubate for 3 h at 37°C in an incubator. Mix the beads every 30 min by flicking the sample tubes gently with one finger so that all beads are in motion. Do the same for each of the following steps. Do not mix beads by vortexing.
Reduction: Add 1 µL of 500 mM Tris (2-carboxyethyl) phosphine (TCEP) for a final concentration of 5 mM TCEP. Flip samples and incubate for 30 min at 37°C in an incubator.
Alkylation: Add 5 µL of 200 mM methyl methanethiosulfonate (MMTS) for a final concentration of 10 mM MMTS. Flip samples and incubate for 30 min at room temperature.
For further digestion of the samples, add 6 µL of 0.05 µg/µL trypsin (suspension in 50 mM TEAB). Flip sample tubes to ensure mixing of the samples and incubate at 37°C incubator overnight.
Note: It is not necessary to use 50 mM TEAB. Water can be used. Buffers containing primary amines (e.g., Tris, ammonium bicarbonate), which inhibit TMT-labeling, should be avoided.
Pellet beads using the magnetic rack and transfer supernatant to new sample tubes.
Tandem mass tag (TMT) labeling with TMTproTM 16plex
Allow TMT-reagents to equilibrate to room temperature.
Dissolve TMT-reagents in 130 µL of acetonitrile, vortex shortly, and dissolve for 5 min at room temperature.
Spin down TMT-reagents briefly and transfer 42 µL reagent to the respective sample, e.g., 42 µL TMT-reagent 126 to control 1.
Mix sample on vortex, spin down briefly, and incubate for 1 h at room temperature.
Add 8 µL of 5% hydroxylamine (dilute 1:10 from 50% hydroxylamine provided in the TMT labeling kit) to each sample and incubate at room temperature for 15 min.
Pool all labeled samples. Wash each vial with 50 µL of 50% acetonitrile to recover remaining sample and add to the pool.
Dry samples in a vacuum centrifuge at 40°C. It might take several hours until sample is completely dry. Check occasionally.
High pH reversed phase fractionation
Note: Digested and labeled peptides are fractionated into 10 fractions in this step using a High pH Reversed-Phase Peptide Fractionation Kit. Analyzing fractions will result in more detected peptides via LC–MS, compared to injecting the pooled TMT-sample directly. Each column has a recommended capacity of 10–100 µg peptides.
Dissolve sample in 600 µL of 0.1% trifluoroacetic acid (TFA) and let stand at room temperature until step G7.
Prepare washing and elution buffers containing 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 25%, and 50% acetonitrile in 0.1% triethylamine (supplied in the high pH fractionation kit), according to the Table 1.
Table 1. Volumes of Acetonitrile and Triethylamine for preparation of washing and elution buffers.
Fraction No. Acetonitrile (%) Acetonitrile (µL) Triethylamine (0.1%) (µL)
Wash buffer 3% 30 970
1 8% 80 920
2 10% 100 900
3 12% 120 880
4 14% 140 860
5 16% 160 840
6 18% 180 820
7 20% 200 800
8 22% 220 780
9 25% 250 750
10 50.0% 500 500
Use two columns and remove the protective white tip from the bottom of the fractionation column. Place each column into a 2.0 mL tube.
Centrifuge at 5,000 × g for 2 min to remove storage buffer and pack the resin material.
Remove the red screw cap and add 300 µL of acetonitrile to the columns. Spin at 5,000 × g for 2 min; repeat this step once and discard flow through.
Add 300 µL of 0.1% TFA to the columns. Spin at 5,000 × g for 2 min; repeat this step once and discard flow through.
Transfer 300 µL sample to each of the two columns. Spin at 3,000 × g for 2 min for following steps. Reapply sample on column and spin again.
Place column into a new 1.5 mL tube and add 300 µL water. Spin at 3,000 × g for 2 min for all washing and elution steps.
Wash the column with 300 µL 3% acetonitrile in 0.1% triethylamine to remove unreacted TMT-reagent.
Place column into a new 1.5 mL tube and elute with 300 µL elution buffer containing 8% acetonitrile.
Repeat step 11 using a new tube for each elution buffer.
Dry samples in a vacuum centrifuge and dissolve sample in 3% acetonitrile, 0.1% formic acid for LC–MS3 analysis.
LC–MS3 analysis
Analyze each fraction on an Orbitrap FusionTM LumosTM TribridTM mass spectrometer interfaced with an Easy-nLCTM 1200 liquid chromatography system. The LC-system should be equipped with an Acclaim TM Pepmap TM 100 C18 trap column (100 μm × 2 cm, particle size 5 μm) and an in-house packed analytical column i.d. 75 μm, particle size 3 μm, Reprosil-Pur C18, Dr. Maisch, length 35 cm.
Separate peptides using a linear gradient from 5% to 33% B over 77 min followed by an increase to 100% solvent B for 3 min, and 100% B for 10 min at a flow of 300 nL/min. Solvent A is 0.2% formic acid, and solvent B is 80% acetonitrile, 0.2% formic acid.
Run the Orbitrap FusionTM LumosTM TribridTM mass spectrometer using SPS-MS3. The precursor ion mass spectra are acquired at 120,000 resolution, and MS/MS analysis is performed in a data-dependent multinotch mode where CID spectra of the most intense precursor ions are recorded in the ion trap with collision energy setting of 30 for 3 s (‘top speed’ setting). Precursors are isolated in the quadrupole with a 0.7 m/z isolation window, charge states 2 to 7 are selected for fragmentation, dynamic exclusion is set to 45 s and 10 ppm. MS3 spectra for reporter ion quantitation are recorded at 50,000 resolution with HCD fragmentation at collision energy 55 using synchronous precursor selection.
Proteomic Data Analysis
All data files are merged for identification and relative quantification using Proteome DiscovererTM 2.4 (Thermo Fisher Scientific). Data matching is performed against the Drosophila melanogaster database from Uniprot (Swissprot+TrEMBL) using Mascot version 2.5.1 (Matrix Science) as a search engine. The precursor mass tolerance is set to 5 ppm and fragment mass tolerance to 0.6 Da. Tryptic peptides were accepted with one missed cleavage, variable modifications of methionine oxidation and fixed cysteine alkylation, TMTpro-label modifications of N-terminal and lysine are selected. Percolator is used for the validation of Peptide-Spectrum-Matches (confidence threshold medium (<5%) and high (<1%)). TMT reporter ions are identified in the MS3 HCD spectra with 3 mmu mass tolerance. Only unique peptides for a given protein are considered for quantification of the proteins.
Recipes
Apple-juice agar plates
Add 18 g of Bacto-agar to 800 mL of cold tap water and boil in a microwave oven. Add 20 g of sucrose and 200 mL of apple juice. Mix thoroughly and allow to cool to ~55°C. Add 5 mL of 25% ethanolic Methyl-4-hydroxybenzoate (Nipagin) stock solution, mix thoroughly, and pour into Petri dishes.
25% ethanolic Methyl-4-hydroxybenzoate
Prepare 25% weight/volume (w/v) stock solution of Methyl-4-hydroxybenzoate in 96% ethanol
4× Laemmli Buffer
200 mM Tris-Cl pH 6.8, 8% SDS, 40% glycerol, 0.4% bromophenol blue, and 50 mM DTT
RIPA buffer
50 mM Tris-Cl, pH 7.4, 250 mM NaCl, 1 mM EDTA, 1 mM EGTA, and 0.5% Triton X-100
Wash buffer 1
2% (w/v) SDS
Wash buffer 2
0.1% (w/v) deoxycholic acid, 1% Triton X-100, 1 mM EDTA, 500 mM NaCl, 50 mM HEPES pH 7.5
Wash buffer 3
0.5% (w/v) deoxycholic acid, 0.5% NP-40, 1 mM EDTA, 250 mM LiCl, 10 mM Tris-Cl pH 7.4
Acknowledgments
This work has been supported by grants from the Swedish Cancer Society (RHP CAN18/729 and CAN18/834), the Swedish Childhood Cancer Foundation (RHP PR2019-0078), the Swedish Research Council (RHP 2019-03914), the Göran Gustafsson Foundation (RHP2016), Åke Wiberg Foundation (GW M19-0561), and the Knut and Alice Wallenberg Foundation (KAW 2018.0057). Graphical abstract was created with BioRender (BioRender.com).
The pull-down section of this protocol was adapted from Roux et al. (2013).
Competing interests
The authors declare that they have no competing interests.
References
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Cognet, I., Guilhot, F., Gabriac, M., Chevalier, S., Chouikh, Y., Herman-Bert, A., Guay-Giroux, A., Corneau, S., Magistrelli, G., Elson, G. C., et al. (2005). Cardiotrophin-like cytokine labelling using Bir A biotin ligase: a sensitive tool to study receptor expression by immune and non-immune cells. J Immunol Methods 301(1-2): 53-65.
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Gratz, S. J., Ukken, F. P., Rubinstein, C. D., Thiede, G., Donohue, L. K., Cummings, A. M. and O'Connor-Giles, K. M. (2014). Highly specific and efficient CRISPR/Cas9-catalyzed homology-directed repair in Drosophila. Genetics 196(4): 961-971.
Hafer, N. and Schedl, P. (2006). Dissection of larval CNS in Drosophila melanogaster. J Vis Exp(1): 85.
Housden, B. E., Lin, S. and Perrimon, N. (2014). Chapter Nineteen - Cas9-Based Genome Editing in Drosophila. In: Doudna, J. A. and Sontheimer, E. J. (Eds.). Methods in Enzymology. Academic Press, 415-439.
Kim, D. I., Jensen, S. C., Noble, K. A., Kc, B., Roux, K. H., Motamedchaboki, K. and Roux, K. J. (2016). An improved smaller biotin ligase for BioID proximity labeling. Mol Biol Cell 27(8): 1188-1196.
Qin, W., Cho, K. F., Cavanagh, P. E. and Ting, A. Y. (2021). Deciphering molecular interactions by proximity labeling. Nat Methods 18(2): 133-143.
Ramanathan, M., Majzoub, K., Rao, D. S., Neela, P. H., Zarnegar, B. J., Mondal, S., Roth, J. G., Gai, H., Kovalski, J. R., Siprashvili, Z., et al. (2018). RNA-protein interaction detection in living cells. Nat Methods 15(3): 207-212.
Rees, J. S., Li, X. W., Perrett, S., Lilley, K. S. and Jackson, A. P. (2015). Protein Neighbors and Proximity Proteomics. Mol Cell Proteomics 14(11): 2848-2856.
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4,459 | https://bio-protocol.org/en/bpdetail?id=4459&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Automated Quantification of Multiple Cell Types in Fluorescently Labeled Whole Mouse Brain Sections Using QuPath
JC Jo-Maree Courtney
GM Gary P. Morris
EC Elise M. Cleary
DH David W. Howells
BS Brad A. Sutherland
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4459 Views: 3209
Reviewed by: Pilar Villacampa AlcubierreCaitlin FinneySamuel Gonçalves Ribeiro
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Original Research Article:
The authors used this protocol in eNeuro Nov 2021
Abstract
The quantification of labeled cells in tissue sections is crucial to the advancement of biological knowledge. Traditionally, this was a tedious process, requiring hours of careful manual counting in small portions of a larger tissue section. To overcome this, many automated methods for cell analysis have been developed. Recent advances in whole slide scanning technologies have provided the means to image cells in entire tissue sections. However, common automated analysis tools do not have the capacity to deal with the large image files produced. Herein, we present a protocol for the quantification of two fluorescently labeled cell populations, namely pericytes and microglia, in whole brain tissue sections. This protocol uses custom-made scripts within the open source software QuPath to provide a framework for the careful optimization and validation of automated cell detection parameters. Images obtained from a whole-slide scanner are first loaded into a QuPath project. Manual counts are performed on small sample regions to optimize cell detection parameters prior to automated quantification of cells across entire brain regions. Even though we have quantified pericytes and microglia, any fluorescently labeled cell with clear labeling in and around the nucleus can be analyzed using these methods. This protocol provides a user-friendly and cost-effective framework for the automated analysis of whole tissue sections.
Keywords: Image analysis Cell counting QuPath Brain Pericyte Microglia Slide scanning microscope
Background
Since the invention of the microscope, quantification of specific cell types in tissue sections has played a crucial role in biological discovery. Advances in cell labeling, including immunohistochemistry, in situ hybridization, and the use of genetically encoded fluorescent labels, have enabled cells to be identified and distinguished with increasing specificity. However, the quantification of labeled cells has largely remained a tedious manual or semi-automated process. The time-consuming nature of this process means it has only been practical to quantify small sample areas of tissue, leaving the majority of tissue uncounted. Even when an entire brain can be imaged, computer-based semi-automated image analysis tools available in programs such as ImageJ are not able to handle the large files produced; therefore, analysis has largely remained limited to small sub-regions. In a complex and heterogeneous organ, such as the brain, these restricted processes can lead to experimenter bias, due to the subjective nature of manual counting and sampling bias, if a selected subset of tissue is not an accurate representation of a whole region.
Recent advances in computational image analysis and whole slide scanning technology have made it possible to quantify every single cell in a whole tissue section on a regular desktop computer. It is now practicable to quantify and further analyze the characteristics of hundreds of thousands of cells in a few minutes—a process that would take days or weeks to do manually. However, this process is not perfect. Software programs that examine digitized images to determine what is, and is not, a cell, are only as good as their underlying algorithms (which are hard-coded by the engineers of the software) and the validity of any user-determined input parameters. It remains important to carefully assess the validity of automated detection algorithms manually, as small differences in tissue processing, staining, and imaging can have significant impacts on the performance of automated algorithms when they are applied across whole projects. Despite this, many studies using automated cell counting approaches do not present evidence of optimization, or justification for the selection of specific parameters.
Here, we present a semi-automated method for counting and classifying two fluorescently labeled cell types—pericytes and microglia—in whole mouse brain tissue sections using the open source software QuPath (Bankhead et al., 2017) as used in Courtney et al. (2021). Our method uses extensive optimization to objectively determine the specific automated cell detection parameters required for each different brain region.
Although this method is written specifically for quantifying pericytes labeled with the fluorophore DsRed and microglia labeled with the fluorophore GFP in mouse brain tissue, it could easily be adapted to quantify any type of cell in any type of tissue, so long as the stain is localized within or immediately around the nucleus. In addition, we present the optimization of just one specific parameter important for automated cell detection, the fluorescence intensity threshold. However, we provide the framework for adding optimization steps for additional cell detection parameters, if desired.
Collectively, the method presented here offers a user-friendly and cost-effective framework for the automated quantification of cell numbers in whole tissue sections, without the need for extensive and time-consuming manual counting.
Equipment
VS120 Slide Scanner (Olympus) or any other microscope capable of scanning and digitizing whole slides
Computer: 64-bit Windows, Linux, or Mac with minimum 16 GB RAM and a fast multicore processor (e.g., Intel Core i7)
Note: This protocol will likely work with a less powerful computer or with lower RAM, but analyses will be slow and may encounter memory errors. For more details, please refer to the QuPath online documentation (https://qupath.readthedocs.io/).
Software
QuPath 0.3.2 open source software (https://qupath.github.io/)
Custom QuPath scripts available at: https://github.com/jo-maree/BioProtocol-2022-Scripts
Notepad or any other simple text editor for making changes to scripts and classifiers
Microsoft Excel or similar
GraphPad Prism (GraphPad Software https://www.graphpad.com/) or similar
Procedure
Stain and scan tissue sections
The specific protocol for staining and scanning sections will depend on the starting material, individual laboratory practices, and slide scanning equipment, so will not be covered here. For details on our tissue processing and imaging, please refer to Courtney et al. (2021). Tissue should be stained with a clear nuclear stain [e.g., DAPI (4’,6-diamidino-2-phenylindole)], which is used to identify nuclei of cells. Cells should be clearly labeled with appropriate fluorophores. In our case, the fluorescent tags were genetically encoded, but a well-optimized immunohistochemical stain should give comparable results.
QuPath uses BioFormats (Linkert et al., 2010) to handle the import of files from most slide scanning platforms. BioFormats currently supports over 150 different file formats including .vsi, .svs, .czi, and .tiff. Images should be scanned at high enough resolution to enable clear visual identification of nuclei and other cellular structures—we used the 40× objective of the VS120 Slide Scanner to provide images with a resolution of 160.3nm/pixel; however, with clear staining, this analysis should be possible with lower resolution (e.g., 322nm/pixel from a 20× objective). Images imported into QuPath should contain a single plane (our images were taken in a single plane, but this protocol would also work with a projection from a z-stack image), and each brain section should be saved as an individual file rather than an entire slide with multiple sections.
Note: QuPath can import both z-stack images and single images with multiple sections, so this kind of analysis is possible in such situations; however, the custom scripts written for this analysis will need to be adapted to cope with these scenarios, and describing how to do so is outside the scope of this protocol.
Create a project and prepare images
The first step to any analysis in QuPath is to create a project. This allows the saving of scripts and classifiers that can be used across multiple images. Note that the project will never contain actual image files, just the data pertaining to them and links to the original images. The project folder does not have to be stored in the same place as the images, but if they are separated (e.g., images on a server and the project on an external hard drive), it may be difficult to reinstate the links at a later time; therefore, it is recommended to at least keep them on the same drive.
Create a project and add images
In your file management system, create a new folder (directory) and give it an appropriate name. This folder will house the QuPath project file and all associated data.
Start QuPath and choose ‘Create project’.
Navigate to the folder you just created, double-click to open it, and then click Select Folder.
Choose ‘Add Images’ to open the Import Images dialog box (Figure 1A) and select options as follows:
Choose the files to be analyzed by dragging and dropping them into the box or selecting one of the four buttons below (e.g., Choose Files to select from your file manager).
Image provider: leave as Default (let QuPath decide).
Set image type: Fluorescence.
Rotate image: Depending on the orientation of your scanned images, you may want to rotate them by 90°, 180°, or 270°, or leave with no rotation.
Optional args: Leave this blank.
Auto-generate pyramids: checked.
Import objects: unchecked.
Click the Import button to link the images to your QuPath project.
Open your file manager, and, in the folder you created in step B1b, there should now be two folders, ‘classifiers’ and ‘data’. Add new folders called ‘scripts’ and ‘exports’ to sit alongside them. Your folder should now look like Figure 1B.
Copy all the script (.groovy) files associated with this protocol into the scripts folder (Figure 1C).
Figure 1. Import of images and example folder structure. A) Import Images dialog box showing the import of four fluorescent images that need to be rotated 180 degrees. B) Set up of QuPath project folder structure. C) Groovy script files in the scripts folder.
Set up channel colors, names, and classes
QuPath automatically colors channels in the order red, green, blue, yellow, cyan, and magenta, but, depending on the file format and scanning options, this will likely be incorrect for your images. This can be corrected for all images at once using the following script.
Find the Channels and Colours script in QuPath in the menu Automate > Project Scripts and open it in the Script Editor (Figure 2A).
Our image channels were scanned in the order Blue > Green > Red, so the script is ordered in this way. To check your own settings, open the Brightness & contrast panel in QuPath to see the current order (Figure 2B)—you will need to open an image to do this. Adjust the order of the getColorRGB lines if needed (Figure 2A). Colors are set using RGB values (i.e., 255, 0, 0, = pure red).
Channel names are set in the same order as the colors—change the names or the order as appropriate for your project.
Note: These channel names are referred to in other scripts, so if you use different ones here, you must remember to change them elsewhere.
In the Run menu, choose ‘Run for Project’ to apply this script to all images. The colors and channel names will change and will be reflected in the images (Figure 2C).
Note: If you have an image open while running the script, you will need to File > Reload data (select OK) to see the changes in the open image.
Below the Class list, open the More Options list (⋮) and select ‘Populate from image channels’. When asked whether to keep existing available classes, select ‘No’. The Class List should now reflect the channel names.
Open the More Options list again and create two new classes named ‘Tissue’ and ‘Vessels’.
Figure 2. The QuPath Script Editor and Changing Colours and Channels. A) QuPath’s Script Editor with the Channels and Colours script open. B) Brightness & contrast panel when images are imported showing that the colors do not match the channel names provided by the VS120 Slide Scanner. C) Brightness & contrast panel after running the Channels and Colours script showing appropriate colors and channel names.
Determine optimal parameters
Duplicate project
Close the Project (File > Project… > Close Project).
In your file manager, navigate to the folder that contains the project and duplicate the entire folder. Now you have one project for optimization and one for analysis. Rename the folders appropriately.
In QuPath, open the optimization project.
Create small annotations for manual counting
Determining the optimal parameters for automated cell detection begins with manually counting the DAPI stained nuclei, DsRed labeled pericytes, and GFP labeled microglia in small annotations. These counts are compared to those from a range of automated detection parameters—in this case, differing intensity thresholds. To ensure the chosen thresholds are appropriate for each individual region, we placed test annotations in every brain region of interest and analyzed these regions independently (Figure 3). In brain regions with marked heterogeneity (e.g., the cortex and hippocampus), two test regions were placed to reflect different characteristics of the region. The size of the test regions was set such that each contained ~100 nuclei. If your project contains a large number of images, you may choose to only optimize using a subset of images, in which case the other images may be deleted from the optimization project.
Open the first image.
Objects > Annotations… > Specify annotation.
Check ‘Use µm’ then specify an annotation that is 300 µm wide, 200 µm high, and Name = ‘Upper Cortex’ (Figure 3A). Click Add annotation.
Note: These are the specifications and names of the small annotations that we used, but these can be changed to the size and names relevant to your project.
The Specify Annotation box will remain open, so continue to add another five annotations with the names ‘Lower Cortex’, ‘DG’, ‘CA1/CA3’, ‘Thalamus’, and ‘Hypothalamus’ (Figure 3B, C).
Close the Specify Annotation box. If needed, check View > Show Names.
Move each annotation to the appropriate position on the image. Try to avoid positioning the annotations on holes in the tissue or large blood vessels. Take care when moving annotations that you do not accidentally resize them—make sure you click in the center to move, not near the edges.
In the File menu, select Object data… > Export as GeoJSON. Select All objects and leave default options selected (Figure 3D). This saves a record of the annotations to the project folder as a .geojson file.
For each of the remaining images, drag and drop the .geojson file into the image to copy the annotations, then adjust their positions as appropriate.
Figure 3. Placing and exporting annotations for optimization. A) The Specify Annotation dialog box with the requirements to specify the first counting annotation. B) Left hemisphere of a brain section showing the positioning of the six counting annotations. C) Detail of area enclosed by white box in B. D) Settings for the export of objects.
Manually count cells
Before starting the process of manually counting cells, it is worth spending time examining the images and determining how you will decide which nuclei and which cells should be counted and marked as positive. Having specific criteria for making decisions before starting will ensure your counting is consistent.
Open the first image.
Adjust the zoom and Channels view to clearly see nuclei—usually, it is best to turn off all channels except DAPI and set to greyscale for clarity.
Navigate to the first 300 µm × 200 µm box.
Select the Points annotation tool—the Counting Window will open (Figure 4A).
Click Add three times to create three new points annotations. Double click them each, in turn, to rename them DAPI, GFP, and DsRed and change their colors to blue, green, and red, respectively.
Select the DAPI annotation and start placing points in the center of each nucleus (Figure 4B).
When you have identified all nuclei, change the Channel view so you can see the GFP expressing microglia.
Select the GFP annotation and check each annotated nucleus. If it is positive for GFP expression, add a green point alongside, or overlapping, the blue one (Figure 4C).
Note: Do not label a cell as GFP-positive if there is no nucleus marked. This prevents the accidental counting of fluorescent spots that are not actually cells and also ensures that sampling is consistently restricted to those cells for which the nucleus is in the focal plane. You may find it helpful to keep both the Counting and the Brightness & Contrast Windows open and adjust the view and points as necessary; however, do ensure that any adjustments to the brightness and contrast do not bias results.
Repeat for the DsRed annotation to label the DsRed-positive pericytes.
With the Hierarchy tab visible, choose Object > Annotations…> Resolve Hierarchy. This should insert the three points annotations into the parent Rectangle annotation.
Repeat steps C3e–C3j for each of the small rectangular counting rectangles.
Note: You will end up with multiple annotations called DAPI, GFP, and DsRed in the Counting Window—using the Hierarchy tab and ensuring you insert into hierarchy after completing each set makes it easier to keep track. You can select specific annotations in the Hierarchy tab, and they will be selected in the Counting Window.
Repeat this process for all other images.
Figure 4. Example of manual count annotations and cell detections. A) The Counting Window. B) DAPI-stained nuclei shown in greyscale and marked with blue point annotations. C) GFP (arrow) and DsRed (arrowhead) positive cells marked with green and red points annotations, respectively. D) The same cells following automated cell detection and classification.
Export manual count data
Ensure all images are saved, and then choose Measure > Export Measurements.
Add all images to the selected column. Click Choose and select the exports folder within the optimization project structure and enter an appropriate file name (e.g., manual counts). For Export type, select Annotations, and for Separator, select Tab (tsv).
Click on Populate to populate the Columns to Include list. From this list, select: Image, Name, Parent, Num points.
Click Export.
Open the file with Excel.
Arrange the manual count data into three tables—one for each channel (DAPI, GFP, DsRed)—as in Figure 5.
Note: The layout and coloring shown in Figure 5 is not essential but will assist with the lookup process described in step C6d.
Figure 5. Table of manual counts of DAPI-positive nuclei from small annotations within multiple brain regions.
Test parameters for cell detection
Note: QuPath’s Cell Detection algorithm offers a number of different parameters that can be changed to optimize cell detection. We have found that the most important parameter to optimize is the intensity threshold and, for our tissue, leaving other parameters at their default levels gives good results. Therefore, this protocol and its associated scripts only optimizes the threshold parameter. You may find that you need to further optimize other parameters, including background radius (the size of the rolling ball used to subtract background staining; it may be useful to optimize if there is a high level of background staining) and sigma (a measure of the level of smoothing which is applied; may need to be raised if nuclear staining is uneven or lowered if nuclei are often very close together). If this is the case, then the scripts associated with Courtney et al. (2021) offer the ability to optimize for sigma and background radius, as well as threshold, and could be further adapted for other parameters.
Find the Optimisation of Cell Detection script under Automate > Project Scripts.
Select Run > Run.
You will be presented with a series of input boxes to specify how many different threshold values you want to test for cell detection in the DAPI channel, as well as what the starting (lowest) test value should be and the amount to increment for the remaining values (e.g., if you want to test thresholds of 150, 200, and 250 you should enter ‘3’, ‘150’, and ‘50’, respectively).
When the process is complete, you will see a pop-up notification, and the data file will be saved in a folder called Optimisation Results in the project folder.
Analyze cell detection parameters
To determine the optimal cell detection parameters, the automated counts need to be compared to the manual counts using the formula:
Open the DAPI Results.csv file from the Optimisation Results folder with Excel.
Delete all columns except those headed Image, Annotation, Threshold, and Cells. These should now be columns A, B, C, and D, respectively.
Copy the DAPI Manual Count table created in step C4f into the spreadsheet a few columns to the right of the data (e.g., starting in cell I1).
Add the heading Manual to the first cell in column E, and enter the relevant manual count numbers for each image and annotation using the DAPI Manual Count table as a reference.
Note: As the number of rows is the product of images, regions, and thresholds (and sigmas and radii if you have tested them), the rows can number in the hundreds or thousands. Entering manual count numbers by hand is both tedious and prone to errors, so we suggest you use one of Excel’s various lookup functions to aid this process. There are multiple ways to achieve this, and the one you choose will likely depend on your level of familiarity with Excel, but one way, using INDEX-MATCH, is detailed here:
Ensure that the image and annotation names in the DAPI Manual Count table from step C6c match those in the data table exactly.
Select the cells containing the manual counts (yellow in Figure 5) and name this range “Counts” in the Name Box.
Select the cells containing the image names (orange in Figure 5) and name this range “ImageNames” in the Name Box.
Select the cells containing the regions (blue in Figure 5) and name this range “Regions” in the Name Box.
In cell E2 enter the formula =INDEX(Counts, MATCH(A2, ImageNames, 0), MATCH(B2, Regions, 0))
Copy this formula down the entire column.
Create a new column (F) formatted as Percentage and calculate the percentage difference using the formula =(D2-E2)/E2. Copy this formula down the entire column.
For each region, use GraphPad Prism or similar software to graph the percentage difference at each threshold. Identify which threshold most reliably gives a percentage difference close to 0. This will be the optimal DAPI threshold for this region (Figure 6A).
For additional confirmation that the chosen threshold is appropriate, the correlation between manual counts and automated counts in each image for that threshold can be calculated (Figure 6B).
Figure 6. An example of graphs to determine the optimal DAPI threshold. A) The mean (with standard deviation) percentage difference between manual and automated counts in one brain region is plotted against the fluorescence thresholds tested. The point at which the mean is closest to 0 (arrow) represents the optimal threshold. B) Correlation plot of manual against automated counts for the optimal threshold in a single brain region in multiple images. A Pearson Correlation Coefficient (r) approaching 1 suggests that the chosen threshold is appropriate.
Test parameters for cell classification
Find the Optimisation of Cell Detection script under Automate > Project Scripts.
Before running the script, you will need to adjust two lines of code as follows:
Line 16:
def regions = ['Upper Cortex', 'Lower Cortex', 'DG', 'CA1/CA3', 'Thalamus', 'Hypothalamus']
Adjust the region names to match your annotations (Note: this is why correct and consistent spelling and capitalization are crucial).
Line 17:
def DAPIthresholds = [150, 150, 75, 75, 150, 150]
Adjust the DAPI thresholds to match the ones determined previously as optimal for each region. Ensure the order is the same as in Line 16.
Select Run > Run.
When prompted, choose to optimize the GFP channel and set the required number, start and increment for thresholds.
The results will be saved in the Optimisation Results folder.
Repeat steps C7c–C7e for the DsRed channel.
Close the Optimization Project.
Analyze cell classification parameters
Open the GFP Results.csv file from the Optimisation Results folder with Excel.
Copy the GFP Manual Count table created in step C4f into the spreadsheet.
Create a new column and enter the relevant manual count numbers for each image and region. The same lookup strategy described in step C6d can be used here.
Create a new column formatted as Percentage and calculate the percentage difference:
(Cell Count – Manual Count)/Manual Count
For each region, use GraphPad Prism or similar software to graph the percentage difference at each threshold. Identify which threshold most reliably gives a percentage difference close to 0. This will be the optimal GFP threshold for this region.
Repeat steps C8a–C8e for DsRed.
Detect tissue and define regions of interest
Define regions of interest
Open the Analysis Project in QuPath. Open the first image.
Select the Brush tool.
Note: The diameter of the brush tool scales with image magnification—this setting and the starting diameter can be changed in Edit > Preferences > Drawing Tools. This tool allows you to click and drag to “paint” a region of interest. Regions can be further defined by clicking inside and pushing the boundaries out, or Alt-clicking outside and pushing the boundaries in.
Using the Allen Brain Atlas as a guide, draw regions corresponding to the cortex, hippocampus, thalamus, and hypothalamus on both left and right hemispheres.
Note: The regions may overlap the edges of the brain, and any holes in the tissue as these will be removed later (Figure 7A).
Merge the pairs of left and right hemispheres into a single annotation for each region.
Name each region (Cortex, Hippocampus, Thalamus, and Hypothalamus—be careful to use this exact spelling and capitalization) by right-clicking and choosing Set Properties.
Once the four regions have been defined in the first image, save the annotations using File > Object data… > Export as GeoJSON. Select All objects and leave default options selected. This saves a record of the annotations to the project folder as a .geojson file.
For each of the remaining images, drag and drop the .geojson file into the image to copy the annotations, then use the Brush tool to make minor adjustments to the annotations as needed.
Detect tissue and remove vessels
Note: The parameters for tissue detection used in our scripts may need to be adjusted for different tissues and scans. We recommend testing the script on a single image before running for all images, particularly as this script can take some time to run.
Open the script Tissue Detection.groovy (Automate > Project Scripts > Tissue Detection).
Run for Project with all images moved to the Selected list.
Intersect regions of interest with tissue
Open the script Intersect ROIs.groovy (Automate > Project Scripts > Intersect ROIs).
Run for Project with all images moved to the Selected list. Regions should now fit the edges of the tissue and have large DsRed positive vessels removed (Figure 7B).
Visual check
Visually check the tissue detection for each image and, if needed, use the brush tool to remove any areas with staining or scanning artifacts (e.g., a fold in the tissue or a region that is out of focus; see Figure 7C–F for examples) or large vessels that were missed by the automated process and would interfere with the optimized cell detection/classification.
Figure 7. Region Annotations and Tissue Detection. A) Brain region annotations following definition with the Brush Tool. B) Brain region annotations following tissue detection and intersection of ROIs. C–F) Lower panels show examples of artifacts that should be removed from the region annotations, including: C) an area where the automatic focusing has failed in the DAPI channel; D) a bubble in the mounting medium; E) a bright fluorescent patch of unknown origin; and F) a piece of debris.
Apply optimal parameters
Create classifiers
As different regions are likely to require different detection thresholds, you will need to create a separate classifier file incorporating the optimal DsRed and GFP thresholds for each region.
Within the classifiers directory of the Analysis project, create a new folder called ‘object_classifiers’.
Open the file DsRed-GFP Cortex.json with Notepad (or similar).
Change the Threshold values to those determined in step C8 above and save the file with ‘Cortex’ replaced with the relevant region name in the object_classifiers directory.
Repeat for each region.
Insert optimal parameters into the analysis script
With the Analysis project open in QuPath, Automate > Project Scripts > Cell Classification
Adjust lines 16 and 17 of the code as in step C7b above.
Adjust line 18 of the code to correctly reference the classifiers you created in step E1.
Run analysis for project
In line 20 of the code, make sure the regionNum = 1.
Run for Project with all images moved to the Selected list.
Following automated cell detection and classification, detected cells should appear as in Figure 4D.
Export Annotation data for all images:
Measure > Export measurements.
Move all images to the Selected pane.
Choose a save location (we suggest creating an ‘outputs’ folder within the Project directory) and a filename with the appropriate region name.
Set Export to Annotations and Separator to .csv.
Click Populate, then tick all columns to be included and click Export.
Open the .csv file in Excel and remove the rows for all annotations except the one you currently have chosen.
Repeat steps E3a–E3d for each region, changing the regionNum to 2, then 3, etc.
Note: Each region needs to be analyzed separately, and the data from that region needs to be saved and extracted after each analysis to make sure the appropriate cell detection parameters are used.
Data analysis
The specifics of data analysis will depend on the questions being asked. For details of our analysis, refer to Courtney et al. (2021) Figure 5.
Acknowledgments
This work was supported by the National Health and Medical Research Council for Australia grants APP1137776 and APP1163384 (BAS) and the University of Tasmania (DWH).
This protocol is based on that described in Courtney et al. (2021).
Competing interests
The authors declare no competing financial or non-financial interests.
Ethics
All animal procedures were approved by the Animal Ethics Committee, University of Tasmania (A0018608) and conformed with the Australian NHMRC Code of Practice for the Care and Use of Animals for Scientific Purposes – 2013 (8th Edition).
References
Bankhead, P., Loughrey, M. B., Fernandez, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., McQuaid, S., Gray, R. T., Murray, L. J., Coleman, H. G., et al. (2017). QuPath: Open source software for digital pathology image analysis. Sci Rep 7(1): 16878.
Courtney, J. M., Morris, G. P., Cleary, E. M., Howells, D. W. and Sutherland, B. A. (2021). An automated approach to improve the quantification of pericytes and microglia in whole mouse brain sections. eNeuro 8(6): ENEURO.0177-21.2021.
Linkert, M., Rueden, C. T., Allan, C., Burel, J. M., Moore, W., Patterson, A., Loranger, B., Moore, J., Neves, C., Macdonald, D., et al. (2010). Metadata matters: access to image data in the real world. J Cell Biol 189(5): 777-782.
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Neuroscience > Cellular mechanisms
Computational Biology and Bioinformatics
Cell Biology > Cell imaging > Fixed-tissue imaging
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446 | https://bio-protocol.org/en/bpdetail?id=446&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Fusarium Virulence Assay on Wheat and Barley Seedlings
LC Lorenzo Covarelli
DG Donald Gardiner
GB Giovanni Beccari
PN Paul Nicholson
Published: Vol 3, Iss 7, Apr 5, 2013
DOI: 10.21769/BioProtoc.446 Views: 13229
Reviewed by: Fanglian He Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in PLOS Pathogens Sep 2012
Abstract
Fusarium root and crown rot is a very important complex disease of small grain cereals worldwide which may lead to very high yield losses. Traditional virulence assays are time consuming and often require plants to be grown in greenhouses or climatic chambers in soil. We describe a rapid laboratory assay for assessing such a disease in wheat and barley seedlings. The method could be successfully used for testing fungal virulence as well as to assess plant resistance.
Materials and Reagents
Fungal strains
25% Campbell`s V8 juice (pH 6.5 with NaOH)
1.2% agar plates (9 cm diameter)
Wheat and barley seeds
Sterilizing solution (0.64% sodium hypochlorite - 10% ethanol)
Sterile deionized water
Equipment
Petri dishes (9 and 14 cm diameter)
Filter paper (Whatman No.3, 8 and 12.5 cm diameter)
Pipette tip or cork borer
Sealing film (Phyto Technology Laboratories) or parafilm
Ruler
Razor blades
Laminar flowhood
Illuminated incubator at 21 ± 1 °C, light intensity > 90 μmols
Fungal growth cabinet with white (one 18 W lamp) and black fluorescent (one 18 W lamp) lights on 12/12 h day/night cycle at 20-22 °C
Incubator
Procedure
Day 1
Grow fungal colonies on V8 agar plates for 7 days at 20-22 °C under white and black fluorescent light on a 12/12 h day/night cycle, starting from stored fungal cultures or colonies from plates.
Day 3 (wheat) or 4 (barley)
For each fungal isolate or plant genotype 16 germinated seeds are required. If testing fungal isolate virulence, a mock treatment is also required. Barley is more vigorous in the early stages of growth and seeds are allowed to germinate for 2 days whereas wheat is allowed to germinate for 3 days prior to inoculation.
Disinfect wheat or barley seeds in sterilizing solution for 5 min and wash 3 times with sterile deionized water.
Imbibe disinfected seeds in 9 cm Petri dishes containing one 8 cm filter paper soaked with sterile deionized water at 4 °C for 1 day. Keep in dark by wrapping plates in aluminium foil.
Day 4 (wheat) or 5 (barley)
Transfer plates to plant growth chamber but maintain in darkness (wrapped in foil).
Day 6
Place three 12.5 cm diameter filter paper layers into 14 cm Petri dishes.
Add sterile deionized water to filter paper until completely soaked.
Remove excess water from plates.
Place 16 pre-germinated wheat or barley seeds on filter paper in rows of 3-5-5-3 seeds.
Seal plates with film and place plates to plant growth chamber in dark overnight.
Day 7
Make mycelial plugs of approximately 5-6 mm diameter by using the reverse of a pipette tip or a cork borer from the edge of the growing colony (Figure 1).
Figure 1. Mycelial plugs obtained from the edge of a growing Fusarium colony.
Place mycelial plugs upside down on the main root of each germinated seed when about 3 cm long, at approximately 1 cm from the seed, with the mycelium in direct contact with the root (Figure 2).
Figure 2. Mycelial plugs on a wheat rootle.
Seal plates with sealing film or Parafilm.
Put plates in incubator at 21 ± 1 °C for 4 to 6 days with 12 h of light.
Day 11-13 as required
Determination of root-rot: observation of root necrosis at 4 days post-inoculation by measuring symptom extension (SE) (cm) and visually observing the browning index (BI, 0 = symptomless; 1 = slightly necrotic; 2 moderately necrotic; 3 = severely necrotic; 4 = completely necrotic).
Determination of crown-rot: Visual observation of crown necrosis at 6 days post-inoculation by a 0-4 scale (0 = symptomless; 1 = slightly necrotic; 2 moderately necrotic; 3 = severely necrotic; 4 = completely necrotic), measuring of shoot length with a ruler (cm) and weighing the shoots after their dissection with a razor blade.
Please see Figure 1 of Beccari et al. (2011) and Figures 6 and 8 of Gardiner et al. (2012).
Acknowledgments
The present protocol here described in detail was adopted in experiments reported in the following publications: Beccari et al. (2011) and Gardiner et al. (2012). Work was supported by the Australian Grains Research and Development Corporation, an Australian statutory authority.
References
Beccari, G., Covarelli, L. and Nicholson, P. (2011). Infection processes and soft wheat response to root rot and crown rot caused by Fusarium culmorum. Plant Pathol 60(4): 671-684.
Gardiner, D. M., McDonald, M. C., Covarelli, L., Solomon, P. S., Rusu, A. G., Marshall, M., Kazan, K., Chakraborty, S., McDonald, B. A. and Manners, J. M. (2012). Comparative pathogenomics reveals horizontally acquired novel virulence genes in fungi infecting cereal hosts. PLoS Pathog 8(9): e1002952.
Article Information
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© 2013 The Authors; exclusive licensee Bio-protocol LLC.
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Category
Microbiology > Microbe-host interactions > In vivo model
Plant Science > Plant immunity > Disease bioassay
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4,460 | https://bio-protocol.org/en/bpdetail?id=4460&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
HaloChIP-seq for Antibody-Independent Mapping of Mouse Transcription Factor Cistromes in vivo
AH Ann Louise Hunter
AA Antony D. Adamson
TP Toryn M. Poolman
MG Magdalena Grudzien
AL Andrew S. I. Loudon
DR David W. Ray
DB David A. Bechtold
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4460 Views: 2137
Reviewed by: Chiara Ambrogio Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in eLIFE Aug 2021
Abstract
Chromatin immunoprecipitation (ChIP) maps, on a genome-wide scale, transcription factor binding sites, and the distribution of other chromatin-associated proteins and their modifications. As such, it provides valuable insights into mechanisms of gene regulation. However, successful ChIP experiments are dependent on the availability of a high-quality antibody against the target of interest. Using antibodies with poor sensitivity and specificity can yield misleading results. This can be partly circumvented by using epitope-tagged systems (e.g., HA, Myc, His), but these approaches are still antibody-dependent. HaloTag® is a modified dehalogenase enzyme, which covalently binds synthetic ligands. This system can be used for imaging and purification of HaloTag® fusion proteins, and has been used for ChIP in vitro. Here, we present a protocol for using the HaloTag® system for ChIP in vivo, to map, with sensitivity and specificity, the cistrome of a dynamic mouse transcription factor expressed at its endogenous locus.
Graphical abstract:
Keywords: HaloTag® ChIP Nuclear receptor Tag Fusion protein NR1D1
Background
Transcription factors (TFs), such as nuclear receptors, are critical regulators of gene expression. They can be highly dynamic, low abundance proteins. By mapping the locations of TF binding genome-wide (the cistrome), mechanisms of gene regulation, and how these vary by cell type and state, can be examined. Chromatin immunoprecipitation (ChIP) makes use of reversible formaldehyde cross-linking, to capture DNA-protein interactions (Jackson, 1978). The protein-DNA complex can then be immunoprecipitated with an antibody against the protein of interest, and an antibody-binding protein (e.g., Protein A, Protein G) coupled to agarose beads. DNA not bound by the protein of interest, i.e., non-specific signal, is removed by washing. Cross-links are reversed by heat, proteins are digested (e.g., with Proteinase K), and the released DNA is purified for analysis by quantitative polymerase chain reaction (qPCR) (Orlando, 2000), microarray (Ren and Dynlacht, 2003), or next generation sequencing (ChIP-seq) (Wei et al., 2006).
Antibody-based ChIP is dependent upon a highly sensitive and highly specific antibody against the target protein of interest. Recent work in our group has focused on the action of circadian clock protein and nuclear receptor NR1D1 (REVERBα) in mouse adipose tissue and liver. Unfortunately, high-quality NR1D1 antibodies are lacking, and overlap between published NR1D1 cistromes in mouse liver is limited (Hunter et al., 2020). Epitope-tagging, in which a recombinant version of the protein of interest carries a small peptide tag (against which antibodies are available), can partly circumvent this. Indeed, this approach has been taken successfully by another group in the study of NR1D1, using haemagglutinin (HA)-tagged NR1D1 (Adlanmerini et al., 2019). However, epitope tag ChIP remains dependent on antibody binding affinity (Encell et al., 2012), and this may limit yield when the protein of interest is expressed at low levels. We chose to use the HaloTag® system to map the NR1D1 cistrome (Hunter et al., 2020, 2021). This approach is distinct, as it relies on covalent and irreversible binding between the 34-kDa HaloTag®, which is a modified haloalkane dehalogenase (Los et al., 2008; Encell et al., 2012), and synthetic haloalkane ligands. A ligand can be attached to a resin, allowing highly specific pull-down of HaloTag® proteins. The binding is sufficiently stable to permit the stringent wash steps needed to remove unbound DNA from the ChIP reaction. HaloChIPTM (Daniels and Urh, 2013) has been used in vitro to examine TF binding in transfected cell lines (Du et al., 2009; Hartzell et al., 2009; Deplus et al., 2013). Here, we describe our method for HaloChIP-seq, to map the cistrome of an endogenously expressed mouse TF in vivo. The method, as presented, was developed for studying NR1D1 in mouse adipose tissue and liver. However, with careful adaptation and optimisation, the method should be adaptable to other TFs in other tissues.
Central to performing in vivo HaloChIP is a system for expressing the HaloTag® fusion protein of interest in a model organism. This requires gene editing expertise. Here, we provide a detailed description of the approach taken to generate the HaloTag®-Nr1d1 mouse, but this is intended as a guide for a gene editing team with CRISPR-Cas9 experience. Thereafter follows a detailed protocol for the HaloChIP wet lab process, which is intended for use by readers with some general molecular biology experience.
Materials and Reagents
*0.5 M EDTA (e.g., Thermo ScientificTM, catalog number: J15694-AE), store at room temperature (RT)
*Nonidet® P40 (Substitute) (e.g., PanReac AppliChem, catalog number: A1694,0250), store at RT
*Note: Only needed for making adipose tissue lysis buffer.
Ultra-High Recovery 1.5 mL microcentrifuge tubes (e.g., Star Lab, catalog number: E1415-2600), store at RT
15 mL centrifuge tubes (e.g., Corning, catalog number: 430791), store at RT
Phase Lock Light 2 mL gel tubes (5 PRIME, catalog number: 2302820), store at RT
Surgical scalpel blade No.22, sterile (Swann-Morton, catalog number: 0308), store at RT
Sterile 10 cm dishes (e.g., Corning, catalog number: 430167), store at RT
**Glass Pasteur pipettes (e.g., 230 mm, Fisher Scientific, catalog number: 1156-6963), store at RT
**Note: Only needed for working with adipose tissue, or other tissue likely to float on water.
Dimethylsulfoxide (DMSO) (e.g., Thermo ScientificTM, catalog number: 20688)
Disuccinimidyl glutarate (DSG) (e.g., Thermo ScientificTM, catalog number: 20593)
Prepare a 0.5 M DSG solution, by adding 306 μL of DMSO to 50 mg DSG. Invert several times to mix, and store 40-μL aliquots at -20°C.
Formaldehyde solution for molecular biology 36.5–38% in H2O (Sigma-Aldrich, catalog number: F8775), store at RT.
$RNase A 10 mg/mL (e.g., Thermo ScientificTM, catalog number: EN0531), store at -20°C.
$Proteinase K 20 mg/mL (e.g., Thermo ScientificTM, catalog number: 26160), store at -20°C.
$Molecular biology grade glycogen 20 mg/mL (e.g., Thermo ScientificTM, catalog number: R0561), store at -20°C.
$Glycine, ≥99%, Molecular Biology Grade, Ultrapure (e.g., Thermo ScientificTM, catalog number: 15815158), store at RT
$PBS, 10× solution, molecular biology grade (e.g., Thermo ScientificTM, catalog number: 15825418), store at RT
$NaCl (5 M), RNase-free (e.g., InvitrogenTM, catalog number: AM9760G), store at RT
$Note: Alternatively, the High Sensitivity Chromatin Prep Kit (Active Motif, catalog number: 53046) includes the equivalent of these reagents (note that the Proteinase K supplied in the Active Motif kit is 10 μg/μL). Purchasing reagents as a kit has the advantages of avoiding reagent contamination and degradation, and can be more convenient. Cost-effectiveness may depend on your sample numbers.
A lysis buffer in which you will homogenise your tissue. For liver tissue, we use the Chromatin Prep Buffer in the Active Motif High Sensitivity Chromatin Prep Kit (see above). An alternative is the Mammalian Lysis Buffer in the Promega HaloCHIPTM System. For adipose tissue, we use a homemade lysis buffer (see Recipes), store at 4°C.
HaloCHIPTM System (Promega, catalog number: G9410). Mixed storage—see manufacturer’s instructions.
Comprises HaloLinkTM Resin, Mammalian Lysis Buffer, High Salt Wash Buffer, Reversal Buffer, HaloCHIPTM Blocking Ligand, nuclease-free water, TE buffer 1× molecular biology grade.
Protease Inhibitor Cocktail, 50× (Promega, catalog number: G6521)
Reconstitute protease inhibitor cocktail (PIC) by adding 1 mL of 100% ethanol to the vial. Store reconstituted PIC at 4°C.
#Universal tracrRNA (IDT, Coralville, USA, catalog number: 1072533)
#EnGen Cas9 protein (New England Biolabs, catalog number: M0646M)
#KOD Hot start DNA polymerase (Merck, catalog number: 71086)
#Zero Blunt PCR cloning kit (ThermoFisher, catalog number: K270020)
#REDExtract-N-AmpTM Tissue PCR Kit (Sigma-Aldrich, catalog number: XNAT)
#Note: Only needed in the mouse generation process.
ChIP DNA Clean & Concentrator kit (Zymo Research, catalog number: D5205); an alternative is the MinElute PCR Purification Kit (Qiagen, catalog number: 28004), store at RT
Water for molecular biology (e.g., Lonza AccuGene, catalog number: BE51200), store at RT
Phenol–chloroform–isoamyl alcohol mixture, BioUltra for molecular biology, 25:24:1 (Sigma-Aldrich, catalog number: 77617), store at 4°C
IGEPAL® CA-630 (e.g., Sigma-Aldrich, catalog number: 18896), store at RT
1 M Tris-HCl (pH 8.0) (e.g., Sigma-Aldrich, catalog number: T3038), store at RT
Lithium chloride (anhydrous) (e.g., Scientific Laboratory Supplies Ltd., catalog number: CHE2356), store at RT
Sodium deoxycholate 10% (e.g., BioWORLD, catalog number: 40430018-1), store at RT
Wet ice
Ethanol absolute (100%), store at RT
1× PBS (see Recipes)
1% formaldehyde-PBS solution (see Recipes)
2.5 M glycine solution (see Recipes)
Adipose tissue lysis buffer (see Recipes)
1 M lithium chloride (LiCl) solution (see Recipes)
Lithium chloride wash buffer (Promega recipe) (make fresh) (see Recipes)
Equipment
Specialist equipment:
Handheld tissue homogeniser (e.g., Qiagen TissueRuptor 220V)
15 mL glass dounce homogeniser (e.g., Active Motif, catalog number: 40415)
Sonicator with cooling system (e.g., Active Motif EpiShearTM Probe Sonicator 230V, catalog number: 53052). See ChIP protocol section D.
System for accurate quantification of ChIP DNA mass. We use QubitTM dsDNA HS and BR Assay Kits (InvitrogenTM, catalog number: 10616763) with the QubitTM fluorometer.
Electrophoresis system for assessment of DNA shearing quality. We use the Agilent TapeStation 2200 system; it is also possible to perform traditional agarose gel electrophoresis, but this does not offer as good a resolution as the TapeStation, Bioanalyzer, and equivalents.
General equipment:
You will also need temperature-controlled benchtop centrifuges capable of holding 15-mL and 1.5-mL tubes, a benchtop tube rotator, a benchtop vortexer, a thermocycler or heat block, Parafilm or similar, micropipettes (e.g., Gilson) and tips, and a pipette boy and stripettes. You will need access to a fume hood to work safely with formaldehyde and phenol. Access to a phase-contrast microscope is useful for checking nuclei release after douncing.
Procedure
Description of mouse generation
We routinely use CRISPR-Cas9 to tag endogenous genes with genetically encoded tags, for a range of downstream applications. Here, the intention was to fuse the HaloTag® to the endogenous Nr1d1 gene. The process involves the following steps: (i) in silico design of the gene editing, (ii) generation of the gene editing reagents, (iii) manipulation of mouse embryos and embryo transfer to pseudopregnant mothers, and (iv) screening of pups for correct gene integration. The following protocol describes the process for this particular allele, but can serve as a blueprint for similar tagging strategies for other genes.
Note: Why CRISPR-Cas9? CRISPR-Cas9 is a gene editing tool that allows us to make changes to a genome. By designing a single guide RNA (sgRNA) specific for the genomic target, and coupling it with Cas9, we can generate a double strand break (DSB) at that site, and exploit the natural DNA repair mechanisms of the cell to direct a desired change. By altering the endogenous genes in this way, we avoid many of the issues associated with random integration of exogenous constructs.
Design of the gene editing
Where to tag
When tagging genes with functional fusions, we take into account a number of factors, to ensure both preservation of endogenous function, and the functionality of the tag itself. With respect to the Nr1d1 gene, evidence from the literature suggests that tagging at the N-terminus with fluorescent genes, and expression from exogenous vectors results in functional, visible proteins (Ka et al., 2017). However, CRISPR-Cas9 results in the manipulation of endogenous sequences, and one must consider collateral genomic disruption that may have unintended consequences and effects. The mouse Nr1d1 gene is found on chromosome 11, and the 3’ sequences of this gene overlap with the 3’ sequences of the Thra (thyroid hormone receptor alpha) gene on the antisense strand (Figure 1). Thus, integration of the HaloTag® fusion gene directed at the C-terminus would result in perturbation of the Thra gene. As a result, we targeted the HaloTag® integration at the N-terminus of Nr1d1. These considerations should be taken when integrating tags on endogenous genes.
Figure 1. Targeting Nr1d1. Region of mouse chromosome 11 where Nr1d1 is situated. Blue shaded boxes correspond to the N- and C-terminus coding sequences. For CRISPR-mediated HaloTag® knock in, we targeted exon 1 of Nr1d1 (corresponding to the N-terminus) (Hunter et al., 2020). Note the overlap of the C-terminus with the Thra gene, negating C-terminal tagging as an option. lncRNA = long non-coding RNA.
Design of sgRNA
When designing guide RNAs for CRISPR, we modify our design rules according to the desired outcome. For gene knock out or disruption via InDel (insertion and deletion) formation, following repair of the Cas9-induced DSB by non-homologous end joining (NHEJ), we can target different exons of the target gene to achieve the same result. Thus, one usually has a number of potential sgRNA to choose from, and can stratify the selection according to low off-targeting potential, and perhaps factor in predicted on-target efficiency (Doench et al., 2016). With respect to precise genetic changes mediated by homology directed repair (HDR), the breadth of sgRNA choice is more limited; one must design sgRNA for the DSB to be induced proximally to the insertion site (usually, 10–15 bp, or so). Thus, one may have to compromise on using sgRNA with a less than ideal off-targeting score. In such circumstances, it may be advisable to screen for off-target editing in positive founders. Should undesirable co-edits be identified, if they are located on a different chromosome, then they can be segregated through breeding and screening the following generations.
Note: What are off-target effects? Partial sgRNA recognition may occur elsewhere in the genome. On these sites, it is possible, though less likely, that the sgRNA:Cas9 complex can generate DSB, and result in unwanted collateral DNA editing.
Off-target effects are probably not as great an issue as first feared, especially in non-transformed cells, and can be largely mitigated through improved sgRNA design (Thomas et al., 2019; Haeussler, 2020), and transient delivery of the sgRNA and Cas9 (Kim et al., 2014). In gene-edited animals, it is also possible to segregate unwanted edits through breeding. Nevertheless, we factor in off-targeting potential in our design.
A number of webtools have been developed that will predict guide RNA target sites, searching by either genes, chromosomal positions, or inputting a sequence for targeting. Here, we used the Sanger WTSI site, http://www.sanger.ac.uk/htgt/wge/ (Hodgkins et al., 2015), and selected the sgRNA sequences shown in Table 1, positioned close to the ATG start site of the Nr1d1 gene. Both of these sgRNA have low off-targeting potential.
Design of the Homology Flanked Donor
For fusion tags, the aim is to integrate the coding sequence of the tag plus linker to be produced in frame with the endogenous gene, and homology arms are designed to achieve this precisely. We use a long single strand DNA (lssDNA) donor strategy, which requires far shorter homology arms (here, 96 nt and 101 nt) than classic double stranded DNA (dsDNA) donors (~800 bp), and has been demonstrated to be more effective than dsDNA donors (Quadros et al., 2017). We also integrated synonymous changes into these homology arms, intended to ensure the same amino acid is produced by the altered codon, but the genetic sequence of the sgRNA PAM site (protospacer adjacent motif) is disrupted. These so-called ‘shield mutations’ insulate the correctly repaired gene sequence from further binding of the sgRNA:Cas9 complex, and undesired editing.
The seamless insertion of the donor at the ATG site will ensure the preservation of all critical endogenous regulatory regions and sequences, which is vital for a dynamically regulated gene, such as Nr1d1.
Generation of editing reagents and embryo injection mixture
In addition to the description below, we refer the reader to our recent publication (Bennett et al., 2021) for this step.
The sgRNA and Cas9 complex
We inject mouse embryos with CRISPR RiboNucleoProtein (RNP) complexes, using commercially sourced reagents. For the sgRNA in this study, we used dual oligos supplied by Sigma (part of Merck KGaA Darmstadt), which require the crRNA (crispr RNA) with the specific targeting sequence to be annealed with a universal tracrRNA (trans-activating crispr RNA). The simple protocol for this is provided below, but it should be noted that many suppliers now offer the synthesis of full length sgRNA for Cas9-related applications. We routinely use these full sgRNA (supplied by either Sigma or Integrated DNA Technologies), as it streamlines the process of making the embryo injection mix.
Resuspend universal tracrRNA in sterile RNase-free injection buffer (1 mM Tris-HCl, pH 7.5, 0.1 mM EDTA) to a concentration of 1 μg/μL. Prepare aliquots of 5-μL volume, and freeze at -80°C for long term storage.
Resuspend the crRNA oligo in sterile RNase-free injection buffer, to a concentration of 1 μg/μL. We typically hope to generate the desired mouse model at the first attempt, but the resuspended crRNA can be aliquoted and stored at -20°C for future use, should a re-attempt be required.
Combine 2.5 μg crRNA with 5 μg universal tracrRNA (IDT, Coralville, USA, 1072533), and heat to 95°C in a thermal cycler, before allowing to cool slowly to RT.
Combine the annealed sgRNA with EnGen Cas9 protein (New England Biolabs, M0646M), by adding 1 μg sgRNA to 0.3 μL (equivalent to 1 μg, or 0.24 μM) Cas9 diluted to 5 μL in injection buffer, and incubating at room temperature for 10 min.
Note: There are many commercial suppliers of Cas9 protein. We have used Sigma, IDT, and Synthego Cas9, as well as NEB EnGen Cas9, and have been satisfied with all. We recommend screening batch activity of Cas9 in blastocyst assays (Scavizzi et al., 2015).
The lssDNA donor purification
The workflow consists of (i) Gibson assembly (Gibson et al., 2009) of a Homology-HaloTag®-Homology donor vector, (ii) use of this vector as a template for Biotinylated PCR, (iii) on column denaturation and purification of the lssDNA. We have recently published our method for generating ultra-pure lssDNA templates for mouse embryo injection (Bennett et al., 2021). We have applied this method successfully on >20 mouse knock in alleles, and the detailed protocol is available in the above reference. The lssDNA sequence for the HaloTag®-Nr1d1 mouse is provided in Table 1.
Generation and screening of mice
The injection mix developed in section B is microinjected in single cell mouse zygotes, according to standard protocols (Nagy et al., 2006; Pu et al., 2019). Once pups are born, we follow a standard genotyping strategy, detailed in Bennett et al. (2021) for gene tags, that involves a series of PCR reactions (Figure 2), followed by Sanger sequencing. Reaction 1 uses primers (here, AL04 Cut Test F, and AL04 Cut Test R—see Table 1) that amplify over the sgRNA target site, from outside the homology arms, and produce a product of ~200–400 bp on WT sequences, and can also detect size changes as a result of NHEJ and InDel formation (a useful quality control, to confirm sgRNA were active), and at times can detect the integration of the full transgene.
Notes:
We currently use microinjection, but others have demonstrated electroporation to be a viable delivery method of lssDNA and RNP complexes into mouse embryoshttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5930688/.
NHEJ and InDel formation when tagging a gene at the N terminus can result in coding frameshifts and potential gene KO. This has some implications for reducing and refining animal use: 1. We regularly ask if a KO mouse allele would be of any use to the research group, and can genotype by sequencing if desired, to prevent animal wastage. 2. It should also be noted that some gene KO can be detrimental to animal health, and this should be carefully considered from the outset of the project. If gene KO is predicted to be detrimental, then pup health should be monitored as appropriate.
This is followed by two targeted integration PCRs, where the above AL04 Cut Test F primer from outside the 5’ homology arm is used in combination with an internal Reverse HaloTag primer (AL04 Geno HaloR1b), and, similarly, an internal Forward HaloTag primer (AL04 Geno Halo F1b) is used with the Cut Test R primer designed outside the 3’ homology arm. Primer sequences can be found in Table 1. Mice that are positive for these assays can have their amplicons sequenced, to confirm precise integration of the tag.
Genomic DNA (gDNA) extraction, PCR amplification, and sequencing
There are several commercially available kits to extract mouse genomic DNA from tissues, such as ear punches. We use the Sigma Aldrich REDExtract-N-AmpTM Tissue PCR Kit as detailed in Bennett et al. (2021). From the master stock of gDNA, we set up 96 well PCR plates with 1/10 dilutions (in ddH2O) ready for assay. The above array of PCR reactions, using the RedEx polymerase provided with the kit, are performed and run on either an agarose gel or automated gel system (e.g., Qiaxcel Advanced system Qiagen, #9002123). As we described in Hunter et al. (2020), three HaloTag®-Nr1d1 mice were candidates for further analysis from these assays.
Sequencing of the edited gDNA
Focusing on potential positive pups from the initial PCR screen, use High Fidelity polymerase, such as KOD Hot start DNA polymerase (Merck, #71086) (Bennett et al., 2021), to re-amplify the products using the flanking primer pair, and gel extract the larger band, which corresponds to the insert. This product can be sequenced directly using primers giving full coverage of the product. For higher quality sequencing, one can blunt clone the amplicon using Zero Blunt PCR cloning kit (ThermoFisher, K270020), transform, and miniprep colonies to instead sequence purified plasmid DNA, using the M13F and M13R primers.
Align the sequencing data against the predicted post-CRISPR genomic DNA sequence in an appropriate software (e.g., Snapgene, GSL Biotech). This sequencing step is necessary to ensure sequence fidelity, especially when using lssDNA, as imperfect or illegitimate repairs can give false conclusions from the PCR (Codner et al., 2018) (Figure 2).
Figure 2. Genotyping and screening. Genotyping primer design (upper panel) and alignment (filled red bars) of Sanger sequences from 3 pups with predicted knock in sequence (middle panel). Note the small non-filled section of Pup 3, which corresponds to a 6 bp loss of sequence (lower panel). lncRNA = long non-coding RNA; ssDNA = single stranded DNA; 5’H = 5’ homology arm; 3’H = 3’ homology arm; TEV site = Tobacco etch virus (TEV) protease cleavage site.
Table 1. Nucleotide sequences used in HaloTag®-Nr1d1 mouse generation
HaloChIP
Our HaloChIP protocol is an adaptation of the Promega HaloCHIPTM manufacturer’s instructions (indeed, for some steps, we recommend that the manufacturer’s instructions are followed unchanged), the Active Motif High Sensitivity Chromatin Prep kit protocol (notably, the tissue fixation and chromatin preparation steps), and is indebted (for adipose tissue work) to the published methods of other groups (Haim et al., 2013; Castellano-Castillo et al., 2018). Reagent volumes are given for a single sample. We recommend that, if working alone, you do not try to process large numbers of samples simultaneously, as many steps are time- and temperature-sensitive. Processing 4–8 samples simultaneously is usually manageable. Also, bear in mind that ChIP DNA yields are in the picogram-nanogram range; thus, it is imperative to minimise reagent and sample contamination as much as possible. We strongly recommend using low binding plasticware to minimise sample loss (we use 1.5 mL ultra-high recovery tubes throughout the protocol).
Tissue collection
We have applied this protocol to both fresh and flash-frozen tissue. We have found fresh tissue to yield superior results, but have still produced sequencing-quality data from flash-frozen samples. No adjustments to the protocol are needed. We recommend that you test the protocol in both fresh and flash-frozen tissue, if possible. The starting mass required will vary between tissues. We find 100 mg of liver tissue yields sufficient chromatin for HaloChIP-seq, whilst we have needed >1,000 mg of white adipose tissue. As NR1D1 is a highly rhythmic clock protein, we collected tissue at the peak [zeitgeber time (ZT) 8 (8 hours after lights on)] and trough (ZT20) of NR1D1 recruitment to the genome, using the ZT20 samples as negative controls.
Fixation
We adopt a dual cross-linking approach (Papachristou et al., 2018), using both disuccinimidyl glutarate (DSG) and formaldehyde fixation, to maximise yield. Before starting, ensure that you have chilled your benchtop centrifuges down to 4°C, and have made and chilled the buffers needed for washing and tissue lysis. Ensure your dounce homogeniser is cold (store at 4°C, or chill on wet ice).
Add 40 μL of 0.5 M DSG to 10 mL 1× PBS (to make a 2 mM DSG solution). The PBS should be at room temperature (RT) to avoid DSG precipitation. Mix well, and warm a little between your hands if precipitate appears.
With two No.22 scalpel blades, finely mince the tissue on a 10 cm dish kept cold on wet ice, in 10 mL of 2 mM DSG, aiming for <1 mm pieces (Figure 3A).
Using a 1-mL pipette tip (with the end of the tip cut off), or a stripette, transfer the tissue and DSG solution to a clean 15-mL tube.
Rotate at 10 rpm and RT for 15 min.
Note: During this step, freshly prepare a 1% formaldehyde-PBS solution (see Recipes below).
Centrifuge the minced tissue suspension at 1,000 × g and 4°C for 3 min.
For most tissues, the tissue pieces will collect at the bottom of the tube. Remove the liquid layer above. For lipid-rich tissues (e.g., white adipose), the tissue pieces will float on top (Figure 3B). In this case, we use fine glass Pasteur pipettes (to which the tissue pieces do not stick) to remove the liquid from beneath the tissue.
Resuspend the tissue pieces in 10 mL of 1% formaldehyde-PBS, and rotate at 10 rpm and RT for 15 min.
Quench the formaldehyde by adding glycine to a final concentration of 0.125 M (e.g., add 0.5 mL of 2.5 M glycine solution, recipe below), or by using Stop Solution as directed in Section C of the Active Motif High Sensitivity Chromatin Prep kit manual, and rotate at 10 rpm and RT for 5 min.
Remove the liquid, and add 10 mL of ice-cold 1× PBS. Invert 2–3 times to mix. Centrifuge the tissue suspension at 1,000 × g and 4°C for 3 min. Repeat this wash step once more. Remove the liquid.
Figure 3. Tissue processing and chromatin preparation. A. Tissue should be minced very finely, so pieces are <1 mm in size. B. Before homogenisation, adipose tissue pieces float on fixation/wash buffer. C. After homogenisation, the suspension should have a uniform appearance (this image shows liver tissue). D. Before sonication, the nuclei suspension is milky in appearance. E. After sonication, the chromatin suspension clears. F. After centrifugation, the suspension clears further, with a black and white pellet of debris (arrow) visible at the bottom of the tube.
Preparing the chromatin suspension
CRITICAL STEP! Chromatin preparation must be optimised for your tissue type, using the sonicator available to you. The sonication step of HaloChIP must be adjusted, so that the chromatin is adequately sheared, but the suspension does not reach too high a temperature (so risking denaturation of the HaloTag®).
Resuspend the tissue pellet in 5 mL of ice-cold lysis buffer (Active Motif Chromatin Prep Buffer, Promega Mammalian Lysis Buffer, or adipose tissue lysis buffer), with 50 μL of proteinase inhibitor cocktail (PIC) (Promega) added.
On ice, disrupt the tissue with a handheld homogeniser, to produce a uniform suspension (Figure 3C), whilst avoiding foaming and overheating.
Note: You will need to optimise this step for your tissue type. For adipose tissue, we homogenise for 15 s with the Qiagen TissueRuptor, on setting 6 (medium-high). For liver tissue, we homogenise for 45 s.
Incubate on wet ice for 10 min.
Nuclei release is performed mechanically, using a chilled dounce homogenizer. Using a stripette, transfer your sample to the douncer, and homogenise with the tight pestle until nuclei release is evident on microscopy (free nuclei are visible as small dense bodies, separate from cell debris).
Note: In our experience, this typically requires 30–70 strokes of the pestle, depending on tissue type. Be sure to optimise this for your samples. If you are processing multiple samples, use the same homogenisation conditions for each sample.
Transfer the sample to a clean 15-mL tube. Centrifuge at 4°C for 3 min to pellet nuclei. For adipose tissue, we centrifuge at 2,780 × g; for liver, at 1,000 × g. Again, this may require adjustment depending on your sample type.
Carefully remove the supernatant (and overlying lipid layer, if adipose). Removing the lipid layer cleanly requires practice. We recommend using a 1 mL pipette tip with the end of the tip cut off, to produce a wide bore.
Resuspend the nuclei pellet in 650 μL of Mammalian Lysis Buffer (Promega HaloCHIPTM System), and transfer to a clean 1.5-mL tube.
Ensure the nuclei pellet is fully resuspended by pipetting (Figure 3D), and add 13 μL of PIC (Promega).
Incubate on wet ice for 15 min.
Proceed to sonication.
The aim is to shear chromatin to 200–1200 bp fragments, without introducing excessive heat or foaming (Figure 3E). See the Active Motif High Sensitivity Chromatin Prep Kit manual for useful advice. We use a 3.5 mm probe sonicator with cooling blocks, keeping samples on wet ice between sonication rounds. We have previously found eight rounds of sonication (30 s on, and 30 s off, for a total of 2 min ‘on’ time per round), at 37% amplitude, to produce optimal chromatin shearing in liver and adipose tissue (Figure 4A). However, when tested on HEK293 cells overexpressing HaloTag®-Nr1d1, we found that these sonication conditions rendered the tag undetectable (SDS-PAGE analysis of cell lysate incubated with HaloTag® fluorescent ligand). The tag remains detectable when samples are sonicated at 20% amplitude, with some sacrifice of shearing quality (Figure 4B).
Centrifuge at top speed (e.g., 17,000 × g) and 4°C for 3 min. The black and white pellet at the bottom of the tube represents debris (Figure 3F).
Reserve a 25-μL aliquot of the supernatant (chromatin suspension), for quantification of DNA concentration, and analysis of shearing quality (section D). Transfer the remainder of the chromatin suspension to a clean 1.5-mL tube (or divide between two or more tubes, if concentrated), and store at -80°C until the pull-down reaction.
**PAUSE POINT** Prepared chromatin suspension can be stored at -80°C.
Figure 4. Chromatin shearing. A. TapeStation image showing optimal shearing of liver chromatin following eight rounds of sonication at 37% amplitude (1 round = 30 s on, 30 s off, cycling for 2 min). B. TapeStation image showing chromatin shearing at 20% amplitude, after increasing rounds of sonication. Purple and green bands indicate upper and lower markers, respectively; arrowheads indicate peaks of fragment distribution.
Input quantification and analysis
Before proceeding to the Halo pull-down, it is necessary to quantify your chromatin and assess shearing quality, using the 25-μL aliquot of chromatin suspension reserved in the previous step.
Add 175 μL of TE buffer and 20 μg RNase A to the 25 μL of chromatin. Mix. Using a heat block or thermocycler, incubate at 37°C for 30 min.
Add 50 μg Proteinase K, and 10 μL of 5 M NaCl. Incubate at 65°C for 6 h, or overnight.
Add 375 μL of phenol–chloroform–isoamyl alcohol. Vortex to mix.
Prepare the Phase Lock tubes by centrifuging at top speed (e.g., 17,000 × g) and RT for 1 min.
Transfer each sample to a Phase Lock tube, on top of the gel layer.
Centrifuge at top speed and RT for 2 min. Remove the aqueous (top) layer, and transfer to a clean 1.5-mL tube. Add 40 μg glycogen and 900 μL of 100% ethanol. Vortex vigorously and leave at -80°C for at least 30 min.
Centrifuge at top speed and 4°C for 15 min. A small white/translucent pellet should be visible at the base of the tube. Pipetting slowly, carefully remove the supernatant from the pellet. Discard the supernatant.
Add 500 μL of 70% ethanol, and centrifuge at top speed and 4°C for 5 min.
Again, carefully remove and discard the supernatant, leaving just the pellet.
Allow residual ethanol to evaporate from the tube for 10–15 min.
Resuspend the pellet in 25 μL of water for molecular biology (at room temperature).
Quantify DNA, by fluorometric (e.g., QubitTM), or spectrophotometric (e.g., Nanodrop) methods, following the manufacturer’s instructions.
Check shearing quality, by analysing an aliquot of DNA by electrophoresis (e.g., TapeStation). Adequately sheared DNA will appear as a smear of fragments 200–1,200 bp in length (Figure 4). If DNA fragments are under- or over-sheared (majority of fragments >1,200 bp or <200 bp in length), your sonication conditions will require adjustment.
HaloLinkTM resin preparation
This step exactly follows the manufacturer protocol (HaloCHIPTM System Technical Manual) (section 5.A. Phase 1. Resin Equilibration). Take care when removing the supernatant from the resin, to avoid removing any of the resin (Figure 5A–5C). Pipette slowly, lowering your tip down the tube as the supernatant is removed.
Figure 5. Handling the HaloLink resin. A. Resin in suspension, dispersed throughout buffer. B. After centrifugation, resin collects at the bottom of the tube. C. The supernatant is removed carefully to avoid loss of resin.
Pull-down
If frozen, gently thaw your chromatin suspension on ice. Centrifuge at top speed and 4°C for 3 min.
We recommend that you use the same mass of chromatin across all your samples. For liver tissue, we have found a single pull-down with 100 μg chromatin to yield sufficient DNA for sequencing; for adipose tissue (where chromatin yield is much less), we have performed multiple (e.g., 3–5) pull-down reactions of 30–50 μg, and pooled DNA at the elution stage. Prepare chromatin suspension with your desired mass of chromatin, making up a total volume of 600 μL with Mammalian Lysis Buffer (Promega).
Add 600 μL of prepared chromatin suspension to the prepared HaloLink Resin.
Rotate at RT for 3 h.
Centrifuge at 800 × g and RT for 2 min, then carefully discard the supernatant.
Wash steps and de-crosslinking
Following the HaloCHIPTM System Technical Manual, wash the resin in the order described in section 5.A. Phase 3. Capture and Release of DNA, steps 6–12, including the Lithium Chloride Wash Buffer step (see recipes below), to reduce non-specific DNA binding. For each wash, mix well, spin down (800 × g at RT for 2 min), and then remove the supernatant. Take care to avoid pipetting up any of the resin. Note that, as the detergent is washed away in the final water steps, the resin will stick to the sides of the tube.
Following the next step of the HaloCHIPTM System Technical Manual, add 300 μL of Reversal Buffer, and mix as directed. If you have resin on the sides of the tube, carefully pipette the Reversal Buffer down the side,s to ensure all the resin is mixed with the buffer.
Incubate at 65°C for 6–16 h (this is the cross-link reversal step—the heat and the high salt content of the Reversal Buffer serve to reverse the protein-DNA cross-links).
DNA elution
Centrifuge resin and Reversal Buffer at 800 × g and RT for 2 min.
Carefully remove the supernatant and split between two clean 1.5-mL tubes (i.e., 150 μL in each) (Figure 6A).
Clean up the DNA with the Zymo ChIP DNA Clean & Concentrator kit, following the manufacturer’s instructions. As the ChIP DNA Binding Buffer is added to the sample in a volume ratio of 5:1 (i.e., 750 μL added to 150 μL supernatant), the sample is split between two 1.5-mL tubes, but can be recombined at the column step (i.e., running each aliquot successively through one column) (Figure 6B). At the elution step, perform two successive elutions, with 11 μL of buffer each time (final volume ~20 μL).
You now have your purified ChIP DNA, which can be taken forward for further analysis. Use 1 μL for quantification (see section K), and set aside an aliquot of 1–2 μL for the PCR enrichment check.
**PAUSE POINT** Purified ChIP DNA can be stored at -20°C.
Figure 6. DNA elution. A. The de-crosslinked supernatant (containing the ChIP DNA) is removed from the resin, and divided between two clean tubes (1 and 2). B. After adding Binding Buffer, the contents of tubes 1 and 2 can be run through the DNA column successively, so that all the ChIP DNA is collected with one column.
Quality control—PCR enrichment check
CRITICAL STEP! To avoid sequencing poor quality samples, we strongly recommend that you check that each sample shows expected enrichment of one or more known TF binding sites, compared to one or more unbound regions. We use droplet digital PCR (ddPCR) to do this, because of its high sensitivity (Hunter et al., 2019); qPCR is an alternative.
Dilute a small volume (e.g., 1–2 μL) ChIP DNA 1:10 in nuclease-free water.
Perform ddPCR or qPCR with primer sets directed to one or more known (or expected) sites of TF binding, and one or more sites where the TF is not expected to bind (e.g., a gene desert). Use 2 μL of diluted ChIP DNA per PCR reaction. ‘Positive control’ and ‘Negative control’ ChIP primer sets are commercially available (e.g., from Active Motif). Signal from the unbound site(s) reflects non-specific DNA signal (‘background’) in your ChIP DNA. Primer efficiency can be compared, by quantifying signal in input DNA (diluted at least 1:10) (Figure 7A).
Calculate enrichment of the positive over negative signal(s), by simply dividing the positive signal by the negative signal. For sequencing, we typically take forward samples where enrichment is at least 5-fold (for a robust TF binding site, much higher enrichment can be seen in good quality samples).
Poor enrichment may be seen in samples where the HaloTag® protein is not expressed (e.g., wildtype or negative controls) (Figure 7B), or in instances where the ChIP has failed.
Figure 7. HaloChIP results. A. ddPCR quantification (copies per 20 μL well) of a positive control region (Arntl promoter) and a negative control region (gene desert) in two HaloChIP samples (IP1, and IP2), and in input DNA. Enrichment of the positive region over the negative region is calculated by dividing the positive signal by the negative signal. Positive and negative signals should be comparable in the input DNA. B. Visualised ChIP-seq signal at the Arntl promoter in mouse adipose tissue in animals homozygous (Hom) wildtype (WT) for HaloTag®-Nr1d1 at zeitgeber time (ZT) 8, the zenith of NR1D1 recruitment to the genome, or ZT20, the nadir.
Quality control – DNA quantification
Measure the concentration of your ChIP DNA, using 1 μL of your sample, following the manufacturer’s instructions [e.g., for the QubitTM dsDNA HS (high sensitivity) kit].
Calculate the total mass of ChIP DNA. Our sequencing core uses the Illumina TruSeq ChIP Libary Preparation Kit, which is designed for 5–10 ng ChIP DNA in a 50-μL volume.
ChIP-seq—library preparation and sequencing
Liaise with your sequencing core or service provider regarding library preparation and sequencing. We recommend that this is done prior to starting any experiment. They will also be able to advise on expected number of reads that their sequencing platform should produce, and make recommendations about read depth. The ENCODE (Encyclopedia of DNA Elements) guidelines (https://www.encodeproject.org/chip-seq/transcription_factor/) are also helpful here.
Data analysis
A detailed overview of ChIP-seq data analysis is beyond the scope of this protocol, but broadly speaking, ChIP-seq data is processed and analysed along the following lines:
Raw reads are trimmed, filtered, and aligned to a reference genome. Duplicate reads are marked and (usually) removed.
The genomic locations of transcription factor binding sites are called by identifying peaks of signal in the aligned reads. A negative control sample may be used as the ‘background’ against which peaks in the experimental sample(s) are called. Alternatively, sites where transcription factor binding differs between conditions may be identified by comparing ChIP-seq data from two or more conditions (differential binding analysis).
The properties of transcription factor binding sites are examined. For example, the underlying DNA sequences may be studied to look for enrichment of certain transcription factor binding motifs, or the proximity of sites to other genomic features may be examined.
A comprehensive overview of ChIP-seq data analysis has been published recently (Nakato and Sakata, 2021); readers may find Figure 1 of this review useful for illustrating the data analysis process. We outline our approach in the Methods sections of our publications (Hunter et al., 2020, 2021).
Recipes
1× PBS
Reagent Final concentration Amount
10× PBS 1× 10 mL
Water for molecular biology n/a 90 mL
Total n/a 100 mL
1% formaldehyde-PBS solution
Reagent Final concentration Amount
10× PBS 1× 5 mL
Formaldehyde solution 36.5–38% in H2O 1% 1.37 mL
Water for molecular biology n/a 43.63 mL
Total n/a 50 mL
2.5 M glycine solution
Reagent Final concentration Amount
Glycine 2.5 M 9.38 g
Water for molecular biology n/a 50 mL
Total n/a 50 mL
Adipose tissue lysis buffer (make fresh)
Reagent Final concentration Amount
1 M Tris-HCl (pH 8.0) 10 mM 1 mL
5 M NaCl 140 mM 2.8 mL
0.5M EDTA 5 mM 1 mL
10% Nonidet® P40 (Substitute)* 1% 10 mL
Water for molecular biology n/a 85.2 mL
Total n/a 100 mL
*Like most detergents, NP-40 is viscous. Make a fresh 10% solution first, to allow for more accurate pipetting, especially when working with small volumes.
1 M lithium chloride (LiCl) solution
Reagent Final concentration Amount
Lithium chloride, anhydrous 1 M 4.239 g
Water for molecular biology n/a 100 mL
Total n/a 100 mL
Lithium chloride wash buffer (Promega recipe) (make fresh)
Reagent Final concentration Amount
1 M Tris-HCl (pH 8.0) 100 mM 1 mL
1 M LiCl 500 mM 5 mL
10% IGEPAL® CA-630* 1% 1 mL
10% sodium deoxycholate 1% 1 mL
Water for molecular biology n/a 2 mL
Total n/a 10 mL
*As above, we recommend that you make a fresh 10% solution first, to allow for more accurate pipetting, especially when working with small volumes.
Acknowledgments
This research was funded by the Biotechnology and Biological Sciences Research Council (BB/I018654/1 to D.A.B.), the Medical Research Council (Clinical Research Training Fellowship MR/N021479/1 to A.L.H.; MR/P00279X/1 to D.A.B.; MR/P011853/1 and MR/P023576/1 to D.W.R.), National Institute for Health Research Oxford Biomedical Research Centre, and the Wellcome Trust (107849/Z/15/Z, 107851/Z/15/Z). For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
This protocol was derived from two original research papers (Hunter et al., 2020, 2021), the Promega HaloCHIPTM manufacturer’s instructions, and the Active Motif High Sensitivity Chromatin Prep kit protocol, with adaptations for adipose tissue work informed by the publications of other groups (Haim et al., 2013; Castellano-Castillo et al., 2018).
We acknowledge the core facilities at the University of Manchester: the Genome Editing Unit, the Genomic Technologies Core Facility, and the Biological Services Unit.
Competing interests
ALH and TMP have received free merchandise from Active Motif. The other authors have no competing interests to declare.
Ethics
All animal procedures described in this protocol were approved by the University of Manchester Animal Welfare and Ethical Review Body and carried out under licence, according to the UK Animals (Scientific Procedures) Act 1986.
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Experimental Models for Cold Exposure of Muscle in vitro and in vivo
TS Tiril Schjølberg *
LA Lucia Asoawe *
SK Solveig Krapf
AR Arild C. Rustan
GT G. Hege Thoresen
FH Fred Haugen
(*contributed equally to this work)
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4461 Views: 1533
Reviewed by: Alessandro Didonna Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Journal of Thermal Biology May 2021
Abstract
Work in cold environments may have a significant impact on occupational health. In these and similar situations, cold exposure localized to the extremities may reduce the temperature of underlying tissues. To investigate the molecular effects of cold exposure in muscle, and since adequate methods were missing, we established two experimental cold exposure models: 1) In vitro exposure to cold (18°C) or control temperature (37°C) of cultured human skeletal muscle cells (myotubes); and 2) unilateral cold exposure of hind limb skeletal muscle in anesthetized rats (intramuscular temperature 18°C), with contralateral control (37°C). This methodology enables studies of muscle responses to local cold exposures at the level of gene expression, but also other molecular outcomes.
Graphical abstract:
Keywords: Cold exposure Skeletal muscle Myotubes In vitro mRNA Protein expression
Background
Occupational cold exposure is reported by 14% in surveys of Norwegian employees/workers (SSB LKU-A, 2019). Technically, cold working conditions are defined by ambient temperatures lower than +10°C (ISO15743:2008, 2008). The impact of a cold working environment at the level of workers’ tissues and cells is largely influenced by physical properties like air movement and humidity, but also behavioral factors like clothing and posture (Makinen and Hassi, 2009).
Exposure to cold temperatures has been associated with chronic pain in some studies (Vale et al., 2017; Farbu et al., 2019), while shorter durations of cold exposure may alleviate pain and inflammation (Bouzigon et al., 2016). Cold exposure localized to the extremities may reduce the temperature of underlying tissues (Saltin et al., 1968). The molecular changes and mechanisms occurring in muscle under cold conditions are currently unknown. To our knowledge, methods for cold exposure of cultured muscle cells and local cold exposure of muscles in anesthetized rats have not been established earlier, although it has been documented that cold exposure of short duration affects muscle gene expression (Egecioglu et al., 2018; Jaworska et al., 2018).
The current protocol may be used to elucidate the molecular effects of cold exposure in the short term. For example, gene expression in muscle, and muscle cell metabolism and secretion. The method could also be extended to study longer-lasting cold exposures, as well as other tissues and cell models.
Materials and Reagents
In vitro materials and reagents
Corning® CELLBIND® 6-well Plate (Corning Inc., catalog number: 734-1210)
Dulbecco’s Phosphate Buffered Saline (DPBS wo/Ca2+ and Mg2+) (Gibco®, Invitrogen, Gibco Life Technologies, catalog number: 14190169)
DMEM, low glucose, GlutaMAX (Gibco®, catalog number: 21885025)
Insulin, Actrapid penfil 100 IU (Novo Nordisk A/S, catalog number: 014398)
Fungizone® (250 µg/mL amphotericin B) (Gibco®, Invitrogen, Gibco Life Technologies, catalog number: 15290026)
Penicillin/Streptomycin (1,0000 U/mL, 10 mg/mL) (Gibco®, Invitrogen, Gibco Life Technologies, catalog number: 15140122)
Fetal bovine serum (FBS) (Gibco®, Invitrogen, Gibco Life Technologies, catalog number: 10500064)
HBSS wo/Ca2+ and Mg2+ (HycloneTM, GE Healthcare, catalog number: SH30588.01)
Trypanblue 0.4 % solution (Sigma-AldrichTM, catalog number: T10282)
Bovine serum albumin (BSA) (Sigma-AldrichTM, catalog number: A8412)
Dimethyl sulfoxide (DMSO) (Sigma-AldrichTM, catalog number: D2650)
Biopsies, musculus vastus lateralis, from four male donors (age 24–29)
Proliferation medium (see Recipes)
Differentiation medium (see Recipes)
In vivo materials and reagents
Female Lewis rats, 20 weeks old (150–200 g) (LEW/OrlRj, Janvier Labs, France)
Isoflurane (ESDG9623C, Baxter International Inc., US)
Ethanol (Kemetyl AS, catalog number: 600068)
Heparin 5000 IE/mL (LEO Pharma AS, catalog number: 009165-07)
MicroporeTM Surgical tape (3M Health Care, catalog number: 1535-1)
RNA-Solv® Reagent (Omega Bio-Tek, catalog number: R6830)
Equipment
In vitro equipment
CountessTM automated cell counter, counting chamber slides (Gibco®, InvitrogenTM, Gibco Life Technologies, catalog number: C10227/C10228)
Water bath (Hetofrig, catalog number: CB11)
CO2 Water-Jacketed incubator (Nuaire, model: NU-4500)
Microscope and cellSens Entry Software (Olympus, model: CKX41)
Cell scraper 24 cm (Sarstedt Inc., catalog number: 83.3951)
Thermal block: Aluminum block strung with perfusion tubes of copper, HI-CONTACTTM 6-PASS COLD PLATE (part No 416101u00000g, Aavid Thermoalloy SRL, Italy)
Stainless steel insulated flexible thermocouple temperature probe (Type-K 228-7445; RS Components AS, Norway)
USB TC-08 data logger (Pico Technology, catalog number: PP222) connected to a portable PC using the PicoLog software
Swip Shaker (Edmund Bühler GmbH, model: SM25-B)
In vivo equipment
Miniplus® 3 Peristaltic Pump (Gilson Inc., catalog number: GFAM00051)
Homeothermic blanket control unit (Harvard Apparatus Ltd., catalog number: 50-7137)
Rat Blanket Only, 15 × 20 cm (Harvard Apparatus Ltd., catalog number: 50-7214)
Harvard Apparatus Vaporizer (Baxter International Inc., catalog number: 34-0387)
Cooling plate EchoTherm (Torrey Pines, catalog number: IC25XR)
Surgical tools:
Spring scissors (Fine Science Tools, catalog number: 15000-08)
Fine scissors (Fine Science Tools, catalog number: 14058.09)
Forceps (Fine Science Tools, catalog number: 11252-00)
Forceps (Fine Science Tools, catalog number: 11006-12)
HaldenwangerTM Porcelain Spouted Mortar (Fisher Scientific, catalog number: 12373328)
Analysis equipment
2100 BioAnalyzer (Agilent Technologies, model: G2938C)
StepOnePlusTM Real-Time PCR Systems (Applied Biosystems, model: 4376592)
Mastercycler® nexus (Eppendorf® AG, model: 6333)
NanoDropTM 8000 Spectrophotometer (Thermo ScientificTM, model: ND-8000-GL)
Software
PicoLog software (PicoLog 6.2.4, Pico Technology, UK)
Procedure
Culturing of human skeletal muscle cells
Harvesting of biopsies of m. vastus lateralis from healthy volunteers, satellite cell isolation, and passaging have been described earlier (Lund et al., 2017).
Store isolated satellite cells from biopsies in cryo vials at -196°C (1 × 106–2 × 106 cells/vial).
Seed myoblasts in 6-well Corning® CELLBIND® plates (passages 3 and 4). Use 2.0 mL of proliferation medium per well and a cell concentration of 50,000 cells per mL, Incubate at 37°C and 5% CO2.
At 80–90% confluency (after one week), replace medium with 2.0 mL differentiation medium to facilitate myotube formation. Incubate for 6–7 days.
Incubator setup
Set up a parallel incubator system with both cooling (18°C) and regular (37°C) conditions in the same incubator. An overview is shown in Figure 1.
Figure 1. Setup of in vitro exposure of myotubes in CO2 incubator with parallel exposure of cells to either warm or cold temperature. Thermal block (highlighted with dashed lines, either blue indicating cold exposure or red indicating control conditions of 37°C) temperatures are controlled via connected water circulators (Control = red tubing; cold = blue tubing). Culturing conditions (the actual exposure temperature) are monitored with a thermocouple probe and PicoLog software. Styrofoam insulation is not shown but should be mounted around both tubing and thermos blocks. Figure created in BioRender (biorender.com).
Use a regular CO2-incubator with openings for connecting tubes. Set at 37°C and 5% CO2.
Set up water circulators holding respective temperatures. The temperature of the cold circulator must be considerably lower than the desired exposure temperature, as the returning water heats up through the incubator. An outline of how to establish the correct temperature is described under section B.2, Method validation.
Install two temperature regulated blocks in the incubator. To ensure sufficient temperature regulation of the thermo block, an aluminum block strung with perfusion tubes of copper (Figure 2) was mounted on the shelves of the incubator. Allow tight connection between surface of the culture wells and the thermo block by milling grooves into the aluminum thermo block (Figure 2A).
Figure 2. Thermo block. A) Back and front sides of the aluminum thermo block (light blue), strung with serpentine copper tubes (brown) and with grooves milled into it (dark blue), allowing a tight contact to form between the thermo block and the culture plate wells. B) The copper tubing and its dimensions (mm) in the thermo block.
Cool or heat the thermo block by perfusion with either cold or hot water from water circulators (outside the incubator). Connect water circulators with thermo block through silicon tubing.
Use styrofoam for insulation of thermo block, culture plates, and tubes.
Method validation
Add 2.0 mL of medium to each well in three 6-well culture plates. Place the 6-well plates onto the thermo block.
Perforate the plate lid and place a thermocouple temperature probe immersed in the well medium of each well.
Monitor the temperature in the culture wells.
Connect thermocouple temperature probe to a USB TC-08 data logger, and monitor temperature data on a portable PC using the PicoLog software. Verify the temperature needed in the circulators for desired conditions.
Measure the culture well temperature every 5th minute for 60 min to establish the required time for temperature stabilization after adjustment of the circulator temperature.
Measure the culture well and thermo block temperature every 30 min (time to reach temperature stabilization in our lab). Set water circulator at 8°C with temperature increment of 5°C, resulting in a curve of six measurements.
Adjust the temperature of the water circulator according to the acquired equation, to obtain the desired temperature in the cell medium before exposure of cells.
In vitro Cold exposure of cells
Incubate cells established in section A.7 at 18°C well temperature or 37°C (control) for 18 h.
Let cells recover at 37°C for 3 h.
Harvest cells by careful aspiration of medium followed by (for the purpose of gene expression analysis) addition of 500 µL Isol-RNA Lysis Reagent to each well. If other products than RNA are desired, use a suitable lysis reagent.
Detach cells with a cell scraper and shake the plate for 5 min to ensure complete lysis. Transfer the suspension to appropriate tubes and store at -80°C.
Continue with RNA isolation according to the procedure recommendations of the lysis manufacturer, or for other preferred downstream analyses.
In vivo cold exposure of muscle
Anesthesia
Anesthetize the rat by placing it in an anesthetizing box. Close the lid and initiate sedation with Harvard Apparatus Vaporizer with 2.0 L (O2)/min and 5% Isoflurane flow. Monitor to ensure complete sedation, 2–3 min.
Place the rat on a table, in supine position. Redirect the anesthesia to an inhalation mask and adjust flow to 0.5 L/min and 3% Isoflurane.
Regularly (every 15 min) inspect the absence of withdrawal reflexes to ensure complete sedation during the entire experiment. Reflexes are inspected by pinching the paws with a tweezer.
Insert a rectal probe with feedback to a heating pad (Homeothermic blanket control unit), which maintains the core temperature at 36–37°C.
Cold exposure of muscle
Shave the posterior legs of the rat
Place the hind limb on the heating pad, at 37°C. Fixate limbs with surgical tape, with the left hind limb on a cooling plate holding 10°C, as shown in Figure 3. Keep limb on the cooling plate for 1 h. After thermal exposure, reheat the muscle by placing it on the heating pad for an additional 2 h.
Figure 3. Setup of in vivo cold exposure. Isoflurane anesthetized (mask) rat placed in supine position on a heating pad (red), with left hind limb fixed with surgical tape to a cooling plate (blue); the right hind limb serves as a contralateral control. Rectal probe and vaporizer are not shown. Figure created in BioRender (biorender.com).
Perform transcardial perfusion by a surgical thoracotomy.
Spray the chest and abdomen with 70% ethanol.
With a surgical scissor and tweezer, make a 5–7 cm transverse incision through the skin and abdominal wall, at the abdominal center.
Make a horizontal incision through the diaphragm to fully identify the heart.
Inject 0.1 mL (50 mg) of heparin into the left ventricle.
Use a scissor to cut the rib cage laterally on both sides, starting from the lower ribs and up toward the clavicle. Use an artery clamp on the xiphoid processus and tilt the anterior rib cage surface up away from the heart.
Perform a small incision in the pericardium to uncover the heart muscle
Make a small incision on the apex, approximately 2–3 mm, into the left ventricle. Insert a perfusion needle through the left ventricle, 5–10 mm into the aorta. Fix the needle position with a clamp.
Make an incision in the right atrium to secure drainage and initiate the perfusion. Use Hank´s balanced salt solution (HBSS) without Ca2+ and Mg2+. Perform perfusion with Gilson Miniplus® 3 Pump at 20 mL/min. Terminate prefusion when the liver changes color from red to light brown.
Harvest m. gastrocnemius and snap-freeze in N2(ℓ). Store at -80°C for further analysis.
Homogenize tissue with a mortar and pestle in N2(l).
Continue, for example, with RNA or protein isolation.
Data analysis
The in vitro temperatures in respective parts of the incubator were validated by assessing the time to reach a stable temperature, compliance between culture wells and thermo block, and the relation between culture well, thermo block, and water circulator temperature. In our specific setup, a stable temperature was observed after 30 min. Thereafter, the relation between thermo block and culture wells was examined at six different temperatures of the water circulators (Figure 4).
Figure 4. Temperature in thermo block and culture wells after 30 min at six different water circulator temperatures. Mean + SEM values are shown for 18 culture wells in three 6-well plates (N = 18).
In our specific setup, the relation between the temperature in the water circulator and culture well (Figure 5) gave the following equation: y = 0.75x + 9.01
The equation was used to determine the water circulator temperature to obtain a culture well temperature of 18°C.
Figure 5. Linear relation (R2 = 0.99) between culture well and water circulator temperature. Mean + SEM values are shown for 18 culture wells in three 6-well plates (N = 18).
Our previous results (Krapf et al., 2021) indicate that these novel methods can be used to study cold exposure in skeletal muscle. To this end, we have shown that myokine production is regulated by intramuscular temperature in vivo and in vitro. Down-stream analyses included gene expression at the mRNA level as well as protein secretion into the culture media. Furthermore, we have studied effects of direct cold exposure and rewarming on glucose and fatty acid metabolism in cultured human myotubes (manuscript in review). This was achieved using labeling with isotope tracers and measuring CO2 production. The current protocol may be utilized to gather new insight into the biological impact of direct cold exposure and temperature changes to tissues and cells.
Recipes
Proliferation medium
Reagent Amount
Dulbecco’s modified Eagle’s medium (DMEM) w/Glutamax (w/1.0 g glucose) 500 mL
FBS 50 mL
Penicillin/Streptomycin, 10,000 units/mL 2.5 mL
Fungizone (250 µg/mL amphotericin B) 2.5 mL
Total 555 mL
Differentiation medium
Reagent Amount
Dulbecco’s modified Eagle’s medium (DMEM) w/Glutamax (w/1.0 g glucose) 500 mL
FBS 10 mL
Penicillin/Streptomycin, 10,000 units/mL 2.5 mL
Fungizone (250 µg/mL Amphotericin B) 2.5 mL
Insulin (25 pmol/L) 21.5 µL
Total 536.5 mL
Acknowledgments
This protocol was derived from our previously published paper (Krapf et al., 2021).
Competing interests
The authors have no financial and non-financial competing interests.
Ethics
The animal studies were executed in accordance with regulations and approved by the Norwegian Food Safety Authority (FOTS, ID9483). Human muscle biopsies were obtained with informed consent from all participants, and all research was performed in accordance with all relevant guidelines and regulations with approval from the National Committee for Research Ethics, Norway (ref. no. 2011/2007 REK sør-øst B).
References
Bouzigon, R., Grappe, F., Ravier, G. and Dugue, B. (2016). Whole- and partial-body cryostimulation/cryotherapy: Current technologies and practical applications. J Therm Biol 61: 67-81.
Egecioglu, E., Anesten, F., Schéle, E. and Palsdottir, V. (2018). Interleukin-6 is important for regulation of core body temperature during long-term cold exposure in mice. Biomed Rep 9(3): 206–212.
Farbu, E. H.,Skandfer, M.,Nielsen, C.,Brenn, T., Stubhaug, A. and Hoper, A. C. (2019) Working in a cold environment, feeling cold at work and chronic pain: a cross-sectional analysis of the Tromso Study. BMJ Open 9: e031248.
ISO15743:2008. (2008). Ergonomics of the thermal environment — Cold workplaces — Risk assessment and management. https://www.iso.org/standard/38895.html.
Jaworska, J., Micielska, K., Kozlowska, M., Wnorowski, K., Skrobecki, J., Radziminski, L., Babinska, A., Rodziewicz, E., Lombardi, G. and Ziemann, E. (2018). A 2-Week Specific Volleyball Training Supported by the Whole Body Cryostimulation Protocol Induced an Increase of Growth Factors and Counteracted Deterioration of Physical Performance. Front Physiol 9: 1711.
Krapf, S., Schjolberg, T., Asoawe, L., Honkanen, S. K., Kase, E. T., Thoresen, G. H. and Haugen, F. (2021). Novel methods for cold exposure of skeletal muscle in vivo and in vitro show temperature-dependent myokine production. J Therm Biol 98: 102930.
Lund, J., Rustan, A. C., Lovsletten, N. G., Mudry, J. M., Langleite, T. M., Feng, Y. Z., Stensrud, C., Brubak, M. G., Drevon, C. A., Birkeland, K. I., et al. (2017). Exercise in vivo marks human myotubes in vitro: Training-induced increase in lipid metabolism. PLoS One 12(4): e0175441.
Makinen, T. M. and Hassi, J. (2009). Health problems in cold work.Ind Health 47: 207-220.
Saltin, B., Gagge, A. P. and Stolwijk, J. A. (1968). Muscle temperature during submaximal exercise in man. J Appl Physiol 25(6): 679-688.
SSB LKU-A. (2019). Working environment, survey on living conditions. Statistics Norway (SSB).
Vale, T. A., Symmonds, M., Polydefkis, M., Byrnes, K., Rice, A. S. C., Themistocleous, A. C. and Bennett, D. L. H. (2017). Chronic non-freezing cold injury results in neuropathic pain due to a sensory neuropathy. Brain 140(10): 2557-2569.
Article Information
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Abstract
In bulk RNA-seq analysis, normalization and batch effect removal are two procedures necessary to scale the read counts and reduce technical errors. Many differential expression analysis tools require a raw count matrix as input and embed the normalization and batch effect removal procedures in the analysis pipeline. However, researchers need to perform these two procedures independently when they build up their own bulk RNA profile analysis models. This protocol includes detailed codes and explanations for normalization and batch effect removal, helping users to more conveniently understand and perform these procedures. In this case study, we use the easily obtainable Arabidopsis thaliana bulk RNA-seq dataset, so that researchers interested in this topic can use this protocol to learn and apply.
Keywords: Transcriptome Normalization Batch effect removal Bioinformatics Bulk RNA-seq analysis
Background
RNA-seq is a widely used sequencing technique that reveals the quantity of gene expression. Based on RNA-seq reads, we can perform quality control and alignment, getting a raw count matrix that notes expression counts for each gene, in each sample. In practice, technical errors in the raw count matrix may affect the downstream analysis. Therefore, we should apply normalization and batch effect removal procedures to correct this technical bias.
RNA-seq measures gene expression based on the number of reads aligned to the gene. The number of reads aligned to the reference is considered as a random variable, but experimental errors, such as ununified fragment amplification and different coverage, can affect the read count. Additionally, gene length can affect the alignment—long genes have a higher probability to get reads align, while short genes have the opposite issue. Therefore, a normalization procedure is necessary in RNA-seq analysis, to make the read counts comparable across samples. The standard normalization methods include library size normalization and gene length normalization. The former focuses on making the library sizes comparable by scaling raw read counts in each sample by a single sample-specific factor, reflecting its library size. Gene length normalization corrects the impact of gene length on the estimation of gene abundances. Accounting for gene length is necessary when comparing expression between different genes within the same sample.
While normalization focuses on correcting the bias generated in each sequencing experiment, batch effect removal helps to reduce the bias generated across batches. Batches may include the dates of sequencing, people who performed the sequencing, the protocol, the type of sequencing machine, etc. When sequencing is performed in different batches, the systematic technical differences can cause a non-biological bias that should be considered in RNA-seq analysis. When removing batch effects, two situations may occur: (i) the batch information is known, or (ii) the batch information is unknown. Different batch effect removal procedures should be used under each situation.
Both normalization and batch effect removal procedures aim to reduce technical bias, but they work on different aspects. This protocol shows readers how to perform different normalization and batch effect removal methods in the case study section, using two R packages: edgeR (Robinson et al., 2010; McCarthy et al., 2012) and sva (Leek et al., 2014) with limma (Ritchie et al., 2015), respectively.
Software
All the software can be downloaded/used from the following locations:
R (Version 4.1) https://www.r-project.org/
Package edgeR (Version 3.34.0) https://bioconductor.org/packages/release/bioc/html/edgeR.html
Package sva (Version 3.40.0) https://bioconductor.org/packages/release/bioc/html/sva.html
Package limma (Version 3.48.0) https://bioconductor.org/packages/release/bioc/html/limma.html
Input data
To demonstrate different normalization and batch effect removal methods, we use the Arabidopsis thaliana RNA count data published by Cumbie et al. ( 2011) as an example. Summarized count data is available as an R dataset, and readers can download the data using the link http://bioinf.wehi.edu.au/edgeR/UserGuideData/arab.rds. In Cumbie’s experiment, they inoculated six-week-old Arabidopsis plants with the ΔhrcC mutant of P. syringae. Control plants were inoculated with a mock pathogen. Each treatment was done as biological triplicates, with each pair of replicates at separate times and derived from independently grown plants and bacteria.
We can use the following script to download and import the input dataset in R (or R studio) environment:
# Specify URL where the file is stored
url <- "http://bioinf.wehi.edu.au/edgeR/UserGuideData/arab.rds"
# Specify destination where file should be saved
destfile <- "path/to/folder/arab.rds"
# Apply download.file function in R
download.file(url,destfile)
# Import the input r dataset
raw_counts_matrix <- readRDS(destfile)
# Check out the import raw counts matrix
head(raw_counts_matrix)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 35 77 40 46 64 60
AT1G01020 43 45 32 43 39 49
AT1G01030 16 24 26 27 35 20
AT1G01040 72 43 64 66 25 90
AT1G01050 49 78 90 67 45 60
AT1G01060 0 15 2 0 21 8
Case study
Normalization
# Load library
library(edgeR)
# Create group vector that indicate each sample’s group type
group <- c('mock','mock','mock','hrcc','hrcc','hrcc')
# Create DEGList object
DEGL <- DGEList(counts=raw_counts_matrix, group=group)
# Checkt out DEGList object
DEGL
> DEGL
An object of class "DGEList"
$counts
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 35 77 40 46 64 60
AT1G01020 43 45 32 43 39 49
AT1G01030 16 24 26 27 35 20
AT1G01040 72 43 64 66 25 90
AT1G01050 49 78 90 67 45 60
26217 more rows ...
$samples
group lib.size norm.factors
mock1 mock 1902162 1
mock2 mock 1934131 1
mock3 mock 3259861 1
hrcc1 hrcc 2130030 1
hrcc2 hrcc 1295377 1
hrcc3 hrcc 3526743 1
Based on the input raw count matrix, we can perform different normalization methods. The most commonly used methods include library size normalization and gene length normalization (Abbas-Aghababazadeh and Li, 2018). Library size normalization divides each column of the raw count matrix by a normalization factor estimated by other samples. Recently proposed library size normalization methods are the trimmed mean of M-values (TMM), relative log estimate (RLE), and upper quartile (UQ). Gene length normalization methods include reads/fragments per kilobase of exon per million reads/fragments mapped (RPKM/FPKM), and transcripts per kilobase million (TPM). In the edgeR package, the first step is to create a DEGList object, which includes the count matrix and group information.
Counts per million (CPM)
The simplest way to normalize the data is to convert raw counts to counts per million (CPM). It divides every count in a sample by the total number of counts for that sample multiplied by 106.
For each sample,
Where i is the ith feature (gene), ri represents the count number, and n is the total number of genes. Note that CPM normalization keeps the raw library size for each sample and does not scale library size. In the edgeR package, the function calcNormFactors() performs library normalization on the input DEGList object. If we set parameter method = "none", the function will not scale the library size, and will directly use each sample’s total read counts as library size. We can get the cpm matrix via function cpm(). Additionally, we can set log = TRUE in the cpm() function, to calculate the log2(CPM).
# Keep the raw library size
DEGL_cpm <- calcNormFactors(DEGL, method = "none")
# Calculate the cpm
cpm <- cpm(DEGL_cpm, log = FALSE, normalized.lib.sizes=TRUE)
# Calculate the log cpm
log_cpm <- cpm(DEGL_cpm, log = TRUE, normalized.lib.sizes=TRUE)
#Check out the cpm normalized matrix and log cpm normalized matrix
head(cpm)
head(log_cpm)
> head(cpm)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 18.400115 39.811161 12.2704618 21.59594 49.40647 17.012864
AT1G01020 22.605856 23.266263 9.8163695 20.18751 30.10707 13.893839
AT1G01030 8.411481 12.408673 7.9758002 12.67588 27.01916 5.670955
AT1G01040 37.851666 22.232207 19.6327389 30.98548 19.29940 25.519296
AT1G01050 25.760161 40.328189 27.6085391 31.45496 34.73892 17.012864
AT1G01060 0.000000 7.755421 0.6135231 0.00000 16.21150 2.268382
> head(log_cpm)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 4.267107 5.345726 3.7142054 4.488650 5.651355 4.159228
AT1G01020 4.552132 4.592183 3.4155622 4.395177 4.952390 3.882448
AT1G01030 3.211894 3.729319 3.1424103 3.758095 4.800812 2.706009
AT1G01040 5.274478 4.528969 4.3566298 4.992751 4.332963 4.721014
AT1G01050 4.734130 5.363953 4.8309999 5.013869 5.153524 4.159228
AT1G01060 -0.227364 3.105947 0.5535731 -0.227364 4.093025 1.642735
Trimmed mean of M-values (TMM) normalization
TMM is a weighted trimmed mean of M-values (to the reference) library size normalization method, which was proposed by Robinson and Oshlack (2010). This method assumes that most genes are not differentially expressed, accounting for library size variation between samples. We set parameter method = "TMM" in calcNormFactors() function, to calculate the library size normalization factor for each sample. Then, we can calculate the CPM based on TMM scaled library size.
# Calculate normalization factors using TMM method to align columns of a count matrix
DEGL_TMM <- calcNormFactors(DEGL, method="TMM")
# Calculate the cpm with the TMM normalized library
TMM <- cpm(DEGL_TMM, log = FALSE, normalized.lib.sizes=TRUE
# Check out the cpm of TMM normalization
head(TMM)
> head(TMM)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 17.69333 37.512585 13.8788097 21.03330 43.29289 19.451664
AT1G01020 21.73752 21.922939 11.1030477 19.66157 26.38160 15.885526
AT1G01030 8.08838 11.692234 9.0212263 12.34563 23.67580 6.483888
AT1G01040 36.39771 20.948586 22.2060955 30.17822 16.91128 29.177496
AT1G01050 24.77066 37.999761 31.2273218 30.63546 30.44031 19.451664
AT1G01060 0.00000 7.307646 0.6939405 0.00000 14.20548 2.593555
Relative log expression (RLE) normalization
The RLE normalization method was proposed by Anders and Huber (2010). A median library is calculated from the geometric mean of all columns, and the median ratio of each sample to the median library is taken as the scale factor. This is the default normalization method in R package DESeq (Love et al., 2014), adapted for use with edgeR. In the calNormFactors() function, we can set method = "RLE" to calculate the scale factor, and then get the CPM based on the RLE normalized library size.
# Calculate normalization factors using RLE method to align columns of a count matrix
DEGL_RLE <- calcNormFactors(DEGL, method="RLE")
# Calculate the cpm with the RLE normalized library
RLE <- cpm(DEGL_RLE, log = FALSE, normalized.lib.sizes=TRUE)
# Check out the TMM normalized result
head(RLE)
> head(RLE)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 18.610636 38.777094 13.3567455 20.48292 45.59497 18.124818
AT1G01020 22.864495 22.661938 10.6853964 19.14708 27.78443 14.801935
AT1G01030 8.507719 12.086367 8.6818846 12.02259 24.93475 6.041606
AT1G01040 38.284736 21.654741 21.3707928 29.38854 17.81053 27.187227
AT1G01050 26.054890 39.280692 30.0526773 29.83383 32.05896 18.124818
AT1G01060 0.000000 7.553979 0.6678373 0.00000 14.96085 2.416642
Upper Quartile (UQ) normalization
The UQ normalization, proposed by Bullard et al. (2010), calculates the scale factors from the 75% quantile of the counts for each library. Like TMM and RLE normalization, we can set the method = “upperquartile” to perform UQ normalization, and then get the CPM counts.
# Calculate normalization factors using UQ method to align columns of a count matrix
DEGL_UQ <- calcNormFactors(DEGL, method="upperquartile")
# Calculate the cpm with the UQ normalized library
UQ <- cpm(DEGL_UQ, log = FALSE, normalized.lib.sizes=TRUE)
# Check out the UQ normalized result
head(UQ)
> head(UQ)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 19.012345 39.266313 13.506840 20.16548 44.42250 18.063364
AT1G01020 23.358024 22.947845 10.805472 18.85034 27.06996 14.751748
AT1G01030 8.691358 12.238851 8.779446 11.83626 24.29355 6.021121
AT1G01040 39.111111 21.927941 21.610944 28.93307 17.35254 27.095046
AT1G01050 26.617284 39.776265 30.390390 29.37145 31.23457 18.063364
AT1G01060 0.000000 7.649282 0.675342 0.00000 14.57613 2.408449
Reads per kilobase of exon per million reads mapped, and fragments per kilobase of exon per million mapped fragments normalization (RPKM and FPKM)
RKPM is a within-sample normalization method, and it is used to compare gene expression levels within a single sample. FPKM is analogous to RKPM, but it is explicitly used in paired-end RNA-seq experiments (Trapnell et al., 2010).
For each sample,
where i is the ith feature (gene) counts, ri represents the count’s number, n is the total number of features, and li is the length of the gene i.
RPKM/FPKM normalization needs the length for each feature, so we should download the dataset of each gene’s length first, and then add it into the DEGList object for the following steps. Here, we use the TxDb.Athaliana.BioMart.plantsmart28 database, to calculate each gene’s length, and then use the function rpkm() to perform RPKM normalization.
# Download the TxDb and import the database into R
BiocManager::install("TxDb.Athaliana.BioMart.plantsmart28")
# Import the database into R environment and create a database variable
library(TxDb.Athaliana.BioMart.plantsmart28)
TxDb <- TxDb.Athaliana.BioMart.plantsmart28
# Subtract the gene length information from TxDb.Athaliana.BioMart.plantsmart28
ref_gene_length <- as.data.frame(genes(TxDb))["width"]
# Delete the genes that in raw counts matrix without length information in reference
raw_counts_matrix <- raw_counts_matrix[intersect(rownames(raw_counts_matrix), rownames(ref_gene_length)),]gene_length <- ref_gene_length[rownames(raw_counts_matrix),]
# Create a DEGList with the gene length information
DEGL_with_gene_length <- DGEList(counts=raw_counts_matrix, group=group, genes=data.frame(Length=gene_length))
# Check out the DEGList with gene length information
DEGL_with_gene_length
# Calculate normalization factors to align columns of a count matrix
DEGL_with_gene_length_rpkm <- calcNormFactors(DEGL_with_gene_length)
# Calculate RPKM normalization
RPKM <- rpkm(DEGL_with_gene_length_rpkm)
# Check out the RPKM normalized matrix
head(RPKM)
> head(RPKM)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 7.801623 16.550845 6.1202305 9.281576 19.050395 8.5746344
AT1G01020 7.739512 7.810344 3.9535383 7.005845 9.373824 5.6544272
AT1G01030 3.916887 5.665586 4.3690329 5.983177 11.441850 3.1390522
AT1G01040 4.505729 2.594858 2.7491815 3.738725 2.089198 3.6109587
AT1G01050 12.491248 19.174183 15.7486426 15.460784 15.318963 9.8063737
AT1G01060 0.000000 1.628241 0.1545382 0.000000 3.156759 0.5773676
Transcripts per kilobase million (TPM) normalization
TPM, introduced by Li et al. (2010), is closely correlated with RPKM/FPKM normalization. To better demonstrate their correlation, we show their expressions as below:
Where i is the ith feature, ri represents the count's number, li represents the length of the gene, and is the total number of read counts. We can convert the RPKM values to TPM by the following equation:
To perform the TPM normalization, we need to create a self-defined function rpkm_to_tpm().
# Calculate TPM from RPKM
# Input: RPKM normalized matrix
# Output: TPM normalizaed matrix
rpkm_to_tpm <- function(x) {
rpkm.sum <- colSums(x)
return(t(t(x) / (1e-06 * rpkm.sum)))
}
Then, apply rpkm_to_tpm() to perform TPM normalization, based on RPKM normalization results.
# Use the constructed function perform tpm normalization based on the result of RPKM normalization
TPM <- rpkm_to_tpm(RPKM)
# Check out the TPM normalization result
head(TPM)
> head(TPM)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 12.583074 27.187909 8.6959745 15.640215 35.142449 12.684487
AT1G01020 12.482896 12.829974 5.6174138 11.805422 17.291984 8.364614
AT1G01030 6.317465 9.306803 6.2077725 10.082142 21.106891 4.643611
AT1G01040 7.267196 4.262547 3.9061947 6.300057 3.853965 5.341704
AT1G01050 20.146872 31.497241 22.3765744 26.052687 28.259039 14.506603
AT1G01060 0.000000 2.674696 0.2195767 0.000000 5.823303 0.854102
Batch effect removal
RNA-seq experiments are often produced in multiple batches because of logistical or practical restrictions, which cause technical variation and differences across batches. We call the bias caused by the non-biological factor from different batches as batch effects (Leek et al., 2010). Proposed batch effect removal methods include ComBat (Johnson et al., 2007) with known sources effects, and SVA seq (Leek, 2014) or RUV seq (Risso et al., 2014) for heterogeneity from unknown sources. Meanwhile, commonly used R packages, such as edgeR and DESeq2, include batch variables in the linear model, to perform differential gene expression analysis.
Here, we use R package sva in the case study. This package, which includes the functions ComBat, ComBat-seq, and sva, can remove batch effects in two ways: (i) directly removing known batch effects, and (ii) identifying and estimating surrogate variables from unknown sources in RNA-seq experiments.
Remove batch effects with known batches based on ComBat function
ComBat removes the batch effect in datasets where the batch covariate is known. Users can choose parametric or non-parametric empirical Bayes frameworks for adjusting data for batch effects. Function ComBat() returns the adjusted RNA expression data based on a cleaned and normalized input counts matrix. Here, we use the TMM-CPM normalized expression profile (a result from section 1.2) as an input dataset for ComBat.
# Import the sva package
library(sva)
# Create batch vector
batch <- c(1,2,3,1,2,3)
# Apply parametric empirical Bayes frameworks adjustment to remove the batch effects
combat_edate_par = ComBat(dat=TMM, batch=batch, mod=NULL, par.prior=TRUE, prior.plots=TRUE)
# Apply non-parametric empirical Bayes frameworks adjustment to remove the batch effects
combat_edata_non_par = ComBat(dat= TMM, batch=batch, mod=NULL, par.prior=FALSE, mean.only=TRUE)
# Check out the adjusted expression profiles
head(combat_edate_par)
head(combat_edate_non_par)
> head(combat_edate_par)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 23.32251 25.051220 22.3741482 26.00493 28.79416 26.943792
AT1G01020 20.57127 18.369262 16.9645376 18.85090 21.38939 20.798486
AT1G01030 10.02911 8.658437 12.7601412 13.54820 16.20375 10.275468
AT1G01040 29.55215 26.740817 23.0471627 24.93558 23.85726 28.751158
AT1G01050 26.66558 32.188893 33.2713853 31.45122 26.86053 24.073241
AT1G01060 0.00000 7.307646 0.6939405 0.00000 14.20548 2.593555
> head(combat_edata_non_par)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 22.477138 23.049996 21.5636368 25.81711 28.83030 27.136491
AT1G01020 21.106413 18.092070 16.0590482 19.03046 22.55073 20.841526
AT1G01030 9.348134 7.539353 11.9653553 13.60539 19.52292 9.428017
AT1G01040 30.843475 26.446379 22.5551441 24.62398 22.40908 29.526545
AT1G01050 25.910028 34.560019 33.9462917 31.77483 27.00057 22.170634
AT1G01060 0.000000 7.307646 0.6939405 0.00000 14.20548 2.593555
Remove batch effects with known batches based on ComBat_seq function
ComBat_seq (Zhang et al., 2020) is an improved model from ComBat that uses negative binomial regression, being explicitly designed for RNA-seq studies. Similarly to ComBat, ComBat_seq requires known batches information, but it uses a raw count matrix as input, instead of normalized data. ComBat_seq returns the adjusted integer counts matrix.
# Include group condition
combat_seq_with_group <- ComBat_seq(raw_counts_matrix, batch=batch, group=group, full_mod=TRUE)
# Without group condition
combat_seq_without_group <- ComBat_seq(raw_counts_matrix, batch=batch, group=NULL, full_mod=FALSE)
# Check out the adjusted expression profiles
head(combat_seq_with_group)
head(combat_seq_without_group)
> head(combat_seq_with_group)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 42 41 64 55 35 97
AT1G01020 38 33 51 38 28 79
AT1G01030 18 15 43 29 21 31
AT1G01040 54 52 70 49 31 103
AT1G01050 50 61 120 67 35 76
AT1G01060 0 15 2 0 21 8
> head(combat_seq_without_group)
mock1 mock2 mock3 hrcc1 hrcc2 hrcc3
AT1G01010 41 40 68 55 36 93
AT1G01020 39 32 54 38 29 75
AT1G01030 16 17 45 30 20 30
AT1G01040 55 52 75 48 30 100
AT1G01050 46 62 110 71 32 88
AT1G01060 0 15 2 0 21 8
Both ComBat and ComBat_seq functions can remove the batch effects when we know the batch information. When this is not the case, we can use the sva method to remove unknown batch effects in the count matrix.
Remove batch effects with unknown batches based on sva function
For the Arabidopsis thaliana RNA-seq study, we assume there is no batch information or adjustment information, so we need to use the sva method to correct the gene expression profile. First, the complete model matrix needs to be created, including the adjustment variables and the variable of interest (treatment). In this case, we do not have adjustment variables, and the variable of interest is binary (mock or hrcc). Therefore, we treat the variables of interest as factor variables, and create the full model matrix mod:
# Create the group variable in data frame format
df_group <- as.data.frame(group)
rownames(df_group) <- c("mock1","mock2","mock3","hrcc1","hrcc2","hrcc3")
colnames(df_group) <- "Treatment"
# Create the full model matrix mod
mod = model.matrix(~as.factor(Treatment), data=df_group)
The null model matrix should only contain the adjustment variables. We assume there are no adjustment variables, so the null model matrix should be an all-ones vector.
# Create the null model matrix
mod0 = model.matrix(~1,data=df_group)# Create the null model matrixmod0 = model.matrix(~1,data=df_group)
Now that the full model matrix and null model matrix are created, we can apply the sva function, to estimate the batch and get the sv object. The sva function can identify the number of latent factors that need to be estimated, and then return the sv object.
# Calculate the sv object
sva_result <- sva(TMM,mod,mod0)
names(sva_result)
> names(sva_result)
[1] "sv" "pprob.gam" "pprob.b" "n.sv"
The sva function returns a list composed by four variables—sv, pprob.gam, pprob.b, and n.sv—where sv is a matrix whose columns correspond to the estimate surrogate variables, pprob.gam is the posterior probability that each gene is associated with one or more latent variables, pprob.b is the posterior probability that each gene is associated with the variable of interest, and n.sv is the number of surrogate variables estimated by the sva. Each of the return variables has a specific usage in the downstream analysis. In this case study, we are only focusing on removing the batch effects, and we can use the removeBatchEffect() function from limma to achieve this goal.
Result interpretation
In Figure 1 we created the log2(CPM) violin plot of raw counts and used five normalization methods (RLE, RPKM, TMM, TPM, and UQ). The values of log2(CPM) obtained from library size normalization methods that are similar to each other (i.e., RLE, TMM, and UQ) showed s between them. However, the outcomes of RPKM and TPM were significant smaller. Here, we need to note that RPKM is within-sample normalization, but RLE, TMM, UQ, and TPM are across-sample normalization methods
Note that the input raw library size of samples directly decided the outcomes of different normalization methods. The results based on the example dataset cannot represent all cases, so readers should select the appropriate normalization method based on the outcomes from their own input datasets.
Figure 1. Box plot of normalization methods and raw expression log2 (CPM) outcomes.
We perform a PCA analysis to explore the performance of different batch effect removal methods (Figure 2). From the PCA analysis, we see that the clustering of samples is not ideal, as mock3 and hrcc3 are far from the other four samples, so we infer this is caused by batch effects. Figure 2C, D, E, and F show the PCA clustering results based on four batch effect removal methods (parametric ComBat, non-parametric ComBat, ComBat_seq, and SVA, respectively). In Figure 2C and D, the PC1 percentage shows a significant improvement, as two clusters clearly separate from each other (control group on the left, and hrcc group on the right). Therefore, the batch effect removal procedure can reduce bias, and we suggest that researchers add it to their own research pipeline.
Figure 2. The plot of PC1 and PC2 based on different batch removal methods (C, D, E, and F) compared to raw CPM (A) and TMM normalized CPM (B).
Discussion
Normalization and batch effect removal are two necessary procedures in the analysis of gene expression. This protocol provides codes of commonly used R packages to perform normalization (TMM, UQ, RLE, RPKM, and TPM) and batch effect removal procedures (parametric ComBat, non-parametric ComBat, ComBat_seq, and SVA), based on raw count data. Readers can use the code in the protocol to learn the normalization and batch effect removal steps in detail. The output results, based on the example dataset, are also provided, so that readers can check their results against the given outputs. Due to space limitation, this paper only shows how to perform normalization and batch effect removal procedures based on R packages edgeR and sva, but we should note that many other packages can implement normalization (such as DESeq2 and limma) and batch effect removal (e.g., bapred). This paper does not include the comparison between different normalization and batch effect removal methods, because results are determined by input raw count datasets, and the experimental design continuously changes. Therefore, we suggest that researchers try different normalization and batch effect removal methods, and choose the most suitable ones.
Acknowledgments
This protocol was derived from the research in Dr. Zhenyu Jia’s lab, UC Riverside. The authors thank Dr. Zhenyu Jia for his review of the manuscript and helpful comments.
Competing interests
The authors declare that there are no conflicts of interest or competing interests.
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Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/Normalization-and-Batch-Effect-Removal.git.
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Serological Measurement of Poly-IgA Immune Complex Levels in IgA Nephropathy and IgA Vasculitis
XZ Xue Zhang
JL Jicheng Lv
PL Pan Liu
XX Xinfang Xie
XL Xinyan Li
HZ Hong Zhang
JJ Jing Jin
Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4463 Views: 2047
Reviewed by: Xiaoyi Zheng Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Clinical Journal of the American Society of Nephrology Nov 2021
Abstract
Both IgA nephropathy and IgA vasculitis, formerly known as Henoch-Schӧnlein purpura, are immune deposition diseases. IgA nephropathy is caused by the deposition of aberrantly formed poly-IgA complexes from blood circulation to the kidney glomerulus; IgA vasculitis is characterized by IgA-dominant immune deposits to small vessels of the skin and other organs, including the kidney. Therefore, measuring the disease-causing poly-IgA contents in the plasma is needed to study these conditions. However, while clinical tests for the level of total plasma IgA are routinely performed, methods for specific detection of poly-IgA contents are unavailable in clinical medicine. In this protocol, we describe a practical solution for measuring poly-IgA in patient samples. The new method is based on the biological selectivity of IgA Fcα receptor I (FcαRI/CD89) toward poly-IgA species, in contrast to its relatively low affinity for normal monomeric IgA. By devising recombinant CD89 ectodomain as the “capturing” probe, we validated the feasibility of the assay for measuring plasma poly-IgA levels in a 96-well format. The methodology was able to differentiate plasma samples of IgA nephropathy, or related IgA vasculitis, from those of other autoimmune kidney disease types or from healthy controls. Moreover, the measured poly-IgA indices not only correlated with the severity of IgA nephropathy, but the levels also trended lower following corticosteroid or immunosuppressant treatments of patients. Therefore, we anticipate the new assay will provide useful measurements of the IgA nephropathy disease activity index for stratifying disease severity or for evaluating treatment response.
Graphical abstract:
Keywords: Poly-IgA immune complex CD89/IgA Fc receptor IgA nephropathy IgA vasculitis/Henoch-Schӧnlein purpura Circulating IgA immune activity index ELISA method
Background
IgA nephropathy is the most common form of primary glomerulonephritis worldwide (Lai et al., 2016). The diagnosis requires renal biopsy and there are no validated diagnostic serum or urine biomarkers for IgA nephropathy. Among recognized risk factors, high levels of galactose-deficient IgA1 (Gd-IgA1) and excessive formation of poly-IgA immune complexes in circulation are associated with kidney glomerular deposition (Magistroni et al., 2015). The observations of recurrent IgA deposition in kidney grafts in transplant recipients with IgA nephropathy strongly suggest the extrarenal origin of IgA as the source of the renal deposits (Moroni et al., 2019). This notion is further supported by evidence of circulating immune complexes in patients sharing the same immunoglobulin classes with IgA extracted from the kidney (Kanatsu et al., 1983). Local immune reactivities to the IgA deposits in the glomerulus stimulate proliferation of mesangial cells, synthesis of extracellular matrix, and infiltration of inflammatory cells (Magistroni et al., 2015).
Meanwhile, circulating IgA immune complexes are catabolized primarily by the mononuclear phagocyte system via IgA Fcα receptor I (FcαRI/CD89) (Chen et al., 2018). CD89 is a type I transmembrane glycoprotein broadly expressed on the surface of myeloid cells, including monocytes/macrophages, dendritic cells, Kupffer cells, neutrophils, and eosinophils (Maliszewski et al., 1990; Monteiro and Van De Winkel, 2003; Bakema and van Egmond, 2011). This IgA-specific receptor binds both IgA1 and IgA2 through its N-terminus Ig domain, which interacts with the Cα2/Cα3 junction of IgA (Herr et al., 2003). Previously, we and others demonstrated that CD89 exhibits higher affinities to polymeric IgA than to monomeric IgA, allowing phagocytes to selectively capture poly-IgA complexes (Reterink et al., 1997; Zhang et al., 2021).
To this end, we constructed a recombinant (r) CD89-based affinity probe for serological detection of poly-IgA immune complexes in clinical samples, namely from patients with IgA nephropathy and IgA vasculitis, formerly known as Henoch-Schӧnlein purpura (HSP) (Zhang et al., 2020). In our study, we demonstrated that rCD89 can distinctively capture poly-IgA in the plasma samples, making this rCD89 probe suitable for measuring only the disease-causing poly-IgA contents without the interference of background signals from normal IgA species. The probe was mounted on ELISA plates and the tests were performed directly with diluted plasma samples. Using this high-throughput test, we demonstrated significantly elevated levels of poly-IgA complexes in IgA nephropathy and HSP samples, as compared to either healthy controls or samples from other kidney disease types (Figure 1). The results outperformed those obtained from measurements of either total IgA or Gd-IgA1 levels regarding disease correlation. It is important to note that despite the recognition of circulating poly-IgA complexes being prone to deposition in the kidney and elsewhere, clinical tests for their levels are unavailable. Research labs have been using size-exclusion chromatography (SEC) to isolate and characterize high-molecular weight IgA complexes. However, the procedures are cumbersome and the quality of poly-IgA separation from their monomeric and dimeric counterparts by SEC is poor (Reterink et al., 1997; Novak et al., 2005, 2011). In addition, chromatography requires pre-extraction of IgA and these additional steps have the tendency to introduce experimental artifacts of IgA self-aggregation (Hui et al., 2015). In contrast, our recombinant CD89-directed ELISA is a robust assay that can be easily automated and further adapted to clinical applications. Here we describe the experimental workflow in a research lab setting.
Figure 1. Comparison of plasma poly-IgA levels among different kidney diseases. The rCD89-directed ELISA kit detects higher poly-IgA levels in plasma samples of IgAN patients, as compared to samples of healthy controls or non-IgAN kidney disease types, including membranous nephropathy (MN), lupus nephritis (LN), ANCA nephritis, Focal Segmental glomerulosclerosis (FSGS), tubulointerstitial nephritis (TIN), diabetic nephropathy (DN), and minimum change disease (MCD). (Note that the figure was adapted from Zhang et al., 2021)
Materials and Reagents
Disposable tips
10 μL capacity (Thermo Fisher Scientific, QSP, catalog number: 104-Q, Rockford, US)
200 μL capacity (Thermo Fisher Scientific, QSP, catalog number: TF140-200-Q, Rockford, US)
1 mL capacity (Thermo Fisher Scientific, QSP, catalog number: 112NXL-Q, Rockford, US)
1.5 mL Microcentrifuge tube (Thermo Fisher Scientific, Invitrogen, catalog number: AM12400, Carlsbad, US)
100 mm culture dish (Corning, Falcon, catalog number: 353003, Glendale, US)
Amicon Ultra-15 centrifugal filter units, 10 kDa MWCO (Sigma, Millipore, catalog number: UFC901024, Darmstadt, Germany)
Carbonate bi-carbonate coating buffer (Medicago, catalog number: 09-8922-100, Uppsala, Sweden)
Bovine serum albumin (Sigma, catalog number: 90604-29-8, Saint Louis, US)
Tween-20 (Thermo Fisher Scientific, catalog number: BP337500, Carlsbad, US)
pcDNA3 expression vector (Thermo Fisher Scientific, Invitrogen™, catalog number: V79020, Carlsbad, US)
HEK293 cells (ATCC, catalog number: CRL-1573, Manassas, US)
Lipofectamine 2000 transfection reagent (Thermo Fisher Scientific, Invitrogen, catalog number: 11668027, Carlsbad, US)
Geneticin/G418 (Thermo Fisher Scientific, Gibco, catalog number: 11811023, Carlsbad, US)
Dulbecco’s Modified Eagle’s Medium (Life Sciences, Corning, catalog number: 10-017-CV, Glendale, US)
Fetal bovine serum (Thermo Fisher Scientific, Gibco, catalog number: 10099141, Carlsbad, US)
Commercial CD89 protein, human, recombinant (Sino Biological, catalog number: 10414-H08H, Beijing, China)
Human IgA1 standard, myeloma (Sigma, catalog number: 400109, Saint Louis, US)
PBS powder (Sigma, catalog number: P3813, Saint Louis, US)
3×FLAG peptide (Sigma, catalog number: F4799, Saint Louis, US)
ANTI-FLAG M2 affinity gel (Sigma, catalog number: A2220, Saint Louis, US)
Slide-A-Lyzer Dialysis Cassettes (Thermo Scientific, catalog number: 66380, Carlsbad, US)
Bio-Rad Protein Assay Dye Reagent (Bio-Rad, catalog number: #5000006, Hercules, US)
Primary antibodies and secondary antibodies
HRP-conjugated anti-DDDDK tag antibody [M2] (Abcam, catalog number: ab49763, Waltham, US)
HRP-conjugated anti-human IgA antibody [1H9] (Abcam, catalog number: ab7383, Waltham, US)
Recombinant anti-CD89 antibody (Abcam, catalog number: ab124717, Waltham, US)
ECL Western Blotting Substrate (Thermo Scientific, catalog number: 32209, Carlsbad, US)
Nunc MaxiSorp 96-Well plates (Thermo Fisher Scientific, catalog number: 44-2404-21, Glendale, US)
Immuno Clear Standard Modules (Thermo Scientific, catalog number: 468667, Carlsbad, US)
3,3′,5,5′-Tetramethylbenzidine (TMB) substrate set (BD, catalog number: 555214, Franklin Lakes, US)
Sulfuric acid (Thermo Scientific, catalog number: N600, Carlsbad, US)
Penicillin and streptomycin (Thermo Scientific, catalog number: 15140122, Carlsbad, US)
Cell culture mediums (see Recipes)
Growth medium
Selection medium
Cryopreservation medium
0.05 M carbonate sodium buffer (pH 9.6) (see Recipes)
0.01 M Phosphate Buffered Saline (PBS) buffer (see Recipes)
ELISA washing buffer (0.1% PBST buffer, pH 7.4) (see Recipes)
ELISA blocking buffer (1% BSA/PBST buffer) (see Recipes)
ELISA stop solution (1 M H2SO4) (see Recipes)
Equipment
-80°C freezer (e.g., Thermo Scientific Forma 900 Series)
Fixed volume single-channel pipettes (e.g., Thermo Fisher Scientific, catalog number: 4651140)
Refrigerated tabletop centrifuge (e.g., Thermo Sorvall Legend XTR refrigerated centrifuge)
Microplate absorbance reader (e.g.,Bio-Rad, catalog number: 1681130XTU)
CO2 incubators (e.g., Thermo Fisher Scientific, catalog number: 51032875)
Liquid nitrogen tank (e.g., Thermo Scientific)
Gel imaging system (e.g., Biorad Gel Doc XRS+ Imaging System, catalog number: 1708265)
Procedure
Generation of stable cell lines for the expression of recombinant CD89
If using commercial CD89 from Sino Biological, skip sections A and B, and go directly to section C.
To generate recombinant soluble CD89 protein (rCD89), synthesize DNA that encodes human FcαRI/CD89 ectodomain (Met1-Asn227 based on RefSeq accession: NP_001991.1) fused to a C-terminus 3×Flag of DYKDHD-G-DYKDHD-I-DYKDDDDK sequence.
Clone the cDNA fragment into pcDNA3 vector for expression using mammalian cells.
Transfect pcDNA3-rCD89-Flag plasmid into HEK293 cells cultured in growth medium using Lipofectamine 2000 in 6-well plates following the standard transfection protocol. The plasmid (2.5 μg, diluted in 100 μL of Opti-MEM medium) and Lipofectamine 2000 (7.5 μL, diluted in 100 μL of Opti-MEM medium) are mixed and incubated at room temperature for 15 min, then added to the well and mixed with the culture medium by gently pipetting.
After one day, dissociate the transfected cells by trypsin digestion and transfer the cells to 100 mm cell culture dishes with five-fold serial dilutions (five 100 mm dishes are used, with dilution ranges from 1:5 to 1:3125). Maintain the cells in 15 mL of selection medium.
Replace the selection medium every 3 days for 14 days until distinct cell clones are formed with an average of 100–500 cells per clone.
Isolate well-formed individual stable cell colonies under a microscope using a 20 μL pipette (by gently scratching and then catching the detached cell clones) and seed them in 96-well plates.
Maintain the cells in the selection medium for 5–7 days without changing the medium. Test the medium in each well for recombinant expression of rCD89-Flag by dot-blotting using HRP-conjugated anti-DDDDK tag antibody.
Prepare a strip of nitrocellulose membrane and draw grids (1 cm × 1 cm) on it with a pencil.
Spot 5 µL of medium samples onto the nitrocellulose membrane at the center of the grids. Minimize the area that the samples penetrate (usually less than 4 mm in diameter) by applying it slowly. Wait until the membrane is dry.
Block the membrane with 5% dry milk in TBST and incubate for 1 h at room temperature.
Pour off the block buffer, and keep the membrane always wet for the remainder of the procedure.
Incubate the membrane with HRP-conjugated anti-DDDDK tag antibody (dilute at the ratio of 1:1,000 with 2% non-fat milk in TBST) for 1 h at room temperature.
Wash the membrane three times with TBST.
Incubate the membrane with ECL reagent and image with a chemiluminescence imaging system. The ECL reagent detects protein at the picogram level.
Select 2–3 stable cell clones with the highest recombinant protein expression and expend these individual clones to culture in 100 mm dishes.
Freeze down stable cell clones with cryopreservation medium (2 × 107 cells/mL) using a cell freezing container (e.g., Nalgene 5100-0036), and then store the cell bank in a liquid nitrogen tank.
Expression and purification of recombinant CD89-Flag
Culture a high-yielding stable cell clone in 100 mm dishes with DMEM supplemented with 10% FBS and 500 μg/mL G418.
When the cells grow to ~90% confluency, change the medium to serum-free DMEM and culture for another 5 days to allow the production of rCD89-Flag protein in the culture medium.
Harvest the medium (~100 mL) and then concentrate the medium with Amicon Ultra-15 filters with a molecular weight cut-off of 10,000 Da. Spin the filters at 4,000 × g at room temperature until the sample was concentrated to less than 5 mL.
Assemble a 5 mL gravity column packed with 2 mL of anti-flag M2 antibody-conjugated affinity gel. Load the concentrated medium into the column.
Wash the gravity column three times with PBS (30 mL each time). Then elute the recombinant protein with 5 mL of 3× Flag peptides at 150 μg/mL in PBS.
Collect the elution buffer containing the rCD89 protein, and dialyze the purified protein against PBS buffer overnight at 4°C by using Slide-A-Lyzer Dialysis Cassettes with a molecular weight cut-off of 10,000 Da.
Measure the total protein concentration using Bio-Rad protein assay reagent, following the manufacturer’s instruction.
Store the recombinant protein at -80°C.
Detection of poly-IgA complexes in plasma by performing rCD89-directed ELISA
Plate Preparation
Dilute rCD89 protein in carbonate sodium buffer (pH = 9.6) to a final concentration of 10 μg/mL. Immediately coat a 96-well ELISA microplate or strips with 100 μL of rCD89 protein per well. Seal the plate and incubate the reactions overnight at 4°C.
Aspirate each well and then wash the wells with 300 μL of washing buffer. Repeat the process two more times for a total of three rounds of washes. After the last wash, remove any remaining wash buffer by aspiration, and then by inverting the plate to be patted against a stack of clean paper towels.
Block the plate by adding 300 μL of blocking buffer to each well. Incubate the blocking reactions at 37°C for 1 h.
Repeat aspirating and washing cycles as described in step C1b. The plates are now ready for measuring samples. However, avoid letting the empty wells to get air dried for a long time.
Prepare plasma samples and IgA standard
Dilute the plasma samples 1:1,000 in blocking buffer (Plasma can be from freshly harvested samples, or from frozen stocks retrieved from -80°C storage. Based on our test results, 2–3 rounds of freeze-thaw cycles with storage at -80°C do not significantly change the reading of poly-IgA contents using the assay. If there is any precipitation from the freeze-thaw process, plasma samples should be centrifuged to remove the precipitates at 3000 x g at 4°C for 15 min).
Dilute purified human IgA1 standard in blocking buffer in a concentration series ranging from 500 μg/mL to 7.8125 μg/mL.
Assay procedure
Add 100 μL of diluted plasma samples or IgA1 standards in blocking buffer to each well. Cover the plate with an adhesive strip and incubate the reactions for 3 h at 37°C.
Perform aspiration/washing cycles as described in step C1b above.
Dilute the detection antibody (HRP-conjugated anti-human IgA antibody) 1:1,000 in blocking buffer. Add 100 μL of detection antibody solution to each well. Cover the plate with a new adhesive strip and incubate the reactions for 1 h at 37°C.
Wash the wells three times as described in step C1b.
Add 100 μL of TMB substrate solution to each well. Incubate the reactions for 25 min at room temperature. Avoid placing the plate under direct light.
Add 100 μL of stop solution to each well.
Measure the optical density of each well using a microplate reader under dual-wavelength set at 450/570 nm.
Data analysis
For testing plate-to-plate variability, in addition to the human IgA1 standard series, a sample standard is also included on each plate as the quality control. Only when the coefficient of variation of the quality control between different test plates is less than 10% the test optical density value is considered stable and reliable.
Concentrations of measured poly-IgA complexes in plasma for each sample are estimated by four-parameter logistic equation:
[y = (A - D) / [1 + (x/C) ^ B] + D
where y = optical density value, x = concentration, A = minimum asymptote, B = slope factor, C = concentration corresponding to the response midway between A and D, and D = maximum asymptote] (Figure 2) (Zhang et al., 2021)].
Figure 2. The standard curve for determining the plasma concentration of poly-IgA complex as measured by rCD89-directed ELISA. The y-axis values are readings of the optical density of the TMB reactions at 450 nm. The x-axis values are marked as the corresponding concentrations of the human IgA1 standards (μg/mL). The data series (the red dots) is obtained from measurements of the human IgA1 standards between 7.8125 and 500 μg/mL. The fitting curve is derived from the four-parameter logistic regression model, which is subsequently used to calculate the unit concentration of poly-IgA complex in patient samples.
In this protocol, the concentration unit of poly-IgA complex is indexed as U/mL that is equally converted from the μg/mL value of measured IgA. The reason for using U/mL here instead of μg/mL is to clarify the measured content being poly-IgA, as opposed to total IgA.
Recipes
Growth medium
Dulbecco’s Modified Eagle’s Medium (DMEM)
10% fetal bovine serum (FBS)
100 U/mL penicillin and streptomycin
Selection medium
Growth medium supplemented with G418 to 1 mg/mL.
Cryopreservation medium
Growth medium supplemented with DMSO to a final concentration of 10%.
0.05 M carbonate sodium buffer (pH 9.6)
Deposit one tablet in a beaker placed on a magnetic stirrer.
Add 50 mL of deionized water and stir the solution for a few min.
Adjust the water up to 100 mL, stir until full dissolution, and the buffer is ready to use.
0.01 M Phosphate Buffered Saline (PBS) buffer
Dissolve a 1 L bag of PBS powder in 500 mL of deionized water.
Adjust the water up to 1,000 mL, stir until full dissolution, and the buffer is ready to use.
ELISA washing buffer (0.1% PBST buffer, pH 7.4)
Reagent Final concentration Amount
0.01 M PBS buffer 0.01M 999 mL
Tween-20 n/a 1 mL
Total n/a 1,000 mL
ELISA blocking buffer (1% BSA/PBST buffer)
Reagent Final concentration Amount
Bovine serum albumin 1% 1g
0.1%PBST buffer 0.1% 100 mL
Total n/a 100 mL
* Dissolve BSA in PBST buffer by gently rocking the capped container.
ELISA stop solution (1 M H2SO4)
Reagent Final concentration Amount
98% concentrated sulfuric acid 1 M 27.8 mL
ddH2O 0.1% 472.2 mL
Total n/a 500 mL
Acknowledgments
This study was supported by National Natural Science Foundation of China grants 81670649 and 81925006, the Capital Health Development Research Project of China grant 2018-2-4073, Beijing Science and Technology Plan Project of China grant D181100000118003, and CAMS Innovation Fund for Medical Sciences grant 2019-I2M-5-046 (to J. Lv). This protocol was adapted from procedures published in Zhang et al. (2021).
Competing interests
J. Jin reports having an ownership interest in Accubit Inc.; being an advisor to Shenzhen Lujing Biotechnology Corporation, Limited, which is developing this technology toward clinical application in diagnosis; having consultancy agreements with Alebund Pharmaceuticals, Mannin Research Inc., and Qbio Med, Inc.; and serving as a scientific advisor for, or member of, Scientific Reports. J. Jin, J. Lv, and H. Zhang report applying for a patent related to the methodology described in this protocol for measuring the level of poly-IgA complex in clinical samples. H. Zhang reports serving as a vice-director of the nephrology committee in the Beijing Society of Medicine, board committee member of nephrology in the Chinese Medical Doctor Association, board committee member of the Chinese Society of Nephrology, member of the International Society of Nephrology (ISN)–Advancing Clinical Trials committee and member of ISN Sister Renal Centers Global Outreach committee and having consultancy agreements with Calliditas, Janssen, Novartis, and OMEROS. X. Li is an employee of Shenzhen Lujing Biotechnology Corporation, Limited. All remaining authors have nothing to disclose.
Ethics
The research was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the local ethics committees.
References
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Chen, A., Yang, S. S., Lin, T. J. and Ka, S. M. (2018). IgA nephropathy: clearance kinetics of IgA-containing immune complexes. Semin Immunopathol 40(6): 539-543.
Herr, A. B., Ballister, E. R. and Bjorkman, P. J. (2003). Insights into IgA-mediated immune responses from the crystal structures of human FcalphaRI and its complex with IgA1-Fc. Nature 423(6940): 614-620.
Hui, G. K., Wright, D. W., Vennard, O. L., Rayner, L. E., Pang, M., Yeo, S. C., Gor, J., Molyneux, K., Barratt, J. and Perkins, S. J. (2015). The solution structures of native and patient monomeric human IgA1 reveal asymmetric extended structures: implications for function and IgAN disease. Biochem J 471(2): 167-185.
Kanatsu, K., Doi, T., Sekita, K., Yoshida, H., Nagai, H. and Hamashima, Y. (1983). A comparative immunologic study of IgA nephropathy. Am J Kidney Dis 2(6): 618-625.
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Article Information
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Biological Engineering > Biomedical engineering
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Improve Research Reproducibility
A Bio-protocol resource
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Published: Vol 12, Iss 13, Jul 5, 2022
DOI: 10.21769/BioProtoc.4464 Views: 5411
Reviewed by: Longping Victor TseSuresh PantheeRita Marie Celine Meganck
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Original Research Article:
The authors used this protocol in Science Nov 2020
Abstract
Profiling the specificities of antibodies can reveal a wealth of information about humoral immune responses and the antigens they target. Here, we present a protocol for VirScan, an application of the phage immunoprecipitation sequencing (PhIP-Seq) method for profiling the specificities of human antiviral antibodies. Accompanying this protocol is a video of the experimental procedure. VirScan and, more generally, PhIP-Seq are techniques that enable high-throughput antibody profiling by combining high-throughput DNA oligo synthesis and bacteriophage display with next-generation sequencing. In the VirScan method, human sera samples are screened against a library of peptides spanning the entire human viral proteome. Bound phage are immunoprecipitated and sequenced, identifying the viral peptides recognized by the antibodies. VirScan Is a powerful tool for uncovering individual viral exposure histories, mapping the epitope landscape of viruses of interest, and studying fundamental mechanisms of viral immunity.
Graphical abstract:
Keywords: VirScan PhIP-Seq Bacteriophage display Synthetic biology High-throughput screening Serology Antibody Epitope Virus Immunology
Background
VirScan (Xu et al., 2015) is based on a general technology called phage immunoprecipitation sequencing (PhIP-Seq) (Larman et al., 2011; Mohan et al., 2018; Mandel-Brehm et al., 2019, Garrett et al., 2020). In PhIP-Seq, a proteome-scale library of peptides is designed, and DNA oligos encoding these peptides are synthesized and cloned into a T7 bacteriophage display system. Each phage encodes the sequence of one peptide in its genome and displays the same peptide on its surface, thus linking genotype with phenotype (Smith and Petrenko, 1997; Kosuri et al., 2010). For each PhIP-Seq reaction, the phage display library is mixed with a sample containing human antibodies, and the antibodies bind to their cognate epitopes on the phage surface. Then the phage-antibody complexes are immunoprecipitated and unbound phage are washed away. PCR amplification and high-throughput sequencing of the insert DNA from bound phage reveal the peptides targeted by antibodies in the sample. Whereas the original PhIP-Seq assays were performed using a phage display library of peptides derived from the human proteome to detect autoantibodies, VirScan employs a library of peptides derived from the human virome to identify the specificities of antibodies targeting viral antigens.
A comparison of the advantages and disadvantages of PhIP-Seq relative to peptide or protein microarrays for high-throughput epitope profiling is provided inMohan et al. (2018). In brief, PhIP-Seq enables higher throughput, less expensive, and more highly programmable assays relative to peptide and whole protein microarrays. A disadvantage of PhIP-Seq compared with protein microarrays is that the experimental procedure takes longer to perform since its readout involves next-generation sequencing. As with all peptide-based epitope profiling methods, PhIP-Seq generally does not enable detection of discontinuous epitopes or epitopes that involve post-translational modifications.
A comprehensive article describing the PhIP-Seq protocol has been published (Mohan et al., 2018) and is a valuable resource to those interested in using VirScan technology. The present article serves to supplement that resource by presenting videos of the experimental protocol (Videos 1–5) and including information relevant for VirScan-specific data analysis (Supplementary materials). This protocol does not contain information related to the design and generation of the VirScan phage display library, as these methods have been covered in depth byMohan et al. (2018) and Xu et al. (2015). This article assumes that the researcher has access to the VirScan library and focuses on the downstream experimental procedures, namely, phage-antibody complex formation, immunoprecipitation, and preparation of DNA libraries for next-generation sequencing, which are also depicted in the videos (Videos 1–5). Further, this protocol covers VirScan-specific data analysis steps, including hits by virus calculation, virus score calculation, and determination of virus seropositivity.
The VirScan protocol may be modified with supplemental libraries, alternative immunoprecipitation reagents, and input samples other than human serum to address a broader set of scientific questions. Alanine scanning and saturation mutagenesis libraries may be designed to enable high-resolution mapping of antibody epitopes, as performed in Shrock et al. (2020) and Chen et al. (2021). The standard immunoprecipitation reagents, Protein A and Protein G, may be replaced with isotype-specific secondary antibodies to profile antibody isotypes other than IgG, such as IgA or IgE, as performed in Shrock et al. (2020) and Chen et al. (2021). The protocol may be used with serum samples from several mammalian species other than humans, including mice and non-human primates, since the Protein A and Protein G bind to mouse and non-human primate IgG as well as human IgG (Borriello et al., 2022). Finally, antibody-containing samples other than serum, including saliva, breast milk, and supernatant from cultured B cells, may be used as input samples for VirScan.
VirScan has been used successfully in many applications, including to estimate the number of viral species to which individuals have been exposed (Xu et al., 2015); to show that infection by measles virus diminishes the preexisting antibody repertoire, leaving individuals vulnerable to reinfection to pathogens (Mina et al., 2019); to study the maternally derived antibody repertoire in human infants (Pou et al., 2019); to investigate the effects of CART therapy directed against CD19 on the antiviral antibody repertoire (Hill et al., 2019); to uncover a putative viral etiology of the rare neurological condition Acute Flaccid Myelitis (Schubert et al., 2019), to map SARS-CoV-2 linear epitopes with high resolution and determine humoral immune correlates of COVID-19 severity (Shrock et al., 2020; Zamecnik et al., 2020), and to provide evidence that Epstein-Barr virus infection increases risk for subsequent development of multiple sclerosis (Bjornevik et al., 2022).
Materials and Reagents
Pipette Tips SR LTS 20 µL F 960A/5 (Rainin, catalog number: 17005860), storage temperature: room temperature
Pipette Tips SR LTS 200 µL F 960A/5 (Rainin, catalog number: 17005859), storage temperature: room temperature
Pipette Tips SR LTS 1,200 µL F 768A/4 (Rainin, catalog number: 17007084), storage temperature: room temperature
Disposable Serological Pipets, Polystyrene, Sterile, Plugged, 5 mL (e.g., VWR, catalog number: 89130-896), storage temperature: room temperature
Disposable Serological Pipets, Polystyrene, Sterile, Plugged, 10 mL (e.g., VWR, catalog number: 89130-898), storage temperature: room temperature
Disposable Serological Pipets, Polystyrene, Sterile, Plugged, 25 mL (e.g., VWR, catalog number: 89130-900), storage temperature: room temperature
Disposable Serological Pipets, Polystyrene, Sterile, Plugged, 50 mL (e.g., VWR, catalog number: 89130-902), storage temperature: room temperature
Reagent Reservoirs, Sterile (e.g., Corning, Costar, catalog number: 4870), storage temperature: room temperature
Sterile Filter Storage Bottles/Receivers (e.g., Thermo Fisher, Nalgene, catalog number: 455-0500), storage temperature: room temperature
Deep Well Plate, 96-well, PP, 1.1 mL, Standard, U-Bottom (Cole-Parmer, BrandTech, catalog number: EW-07904-04), storage temperature: room temperature
Kimtech Science Kimwipes Delicate Task Wipes (Kimberly-Clark, catalog number: 34155), storage temperature: room temperature
Sealing paddle (USA Scientific, catalog number: 2928-7355), storage temperature: room temperature
MicroAmp Optical Adhesive Film (Thermo Fisher, Applied Biosystems, catalog number: 4311971), storage temperature: room temperature
Colored Labeling Tape, Rainbow Pack (Fisher Scientific, Fisherbrand, catalog number: 15-901-10R), storage temperature: room temperature
PCR Plate, 96-well (e.g., VWR, catalog number: 82006-704), storage temperature: room temperature
Bravo Lab Disposable Pipette Tips (Agilent, catalog number: 19477-022), storage temperature: room temperature
Note: These are necessary if performing magnetic bead washes using the Agilent Bravo.
Nunc 96-Well Polypropylene DeepWell Storage Plates, sterile (Thermo Fisher, Thermo Scientific, catalog number: 260251), storage temperature: room temperature
Nalgene Disposable Polypropylene Robotic Reservoirs, sterile (Thermo Fisher, Thermo Scientific, catalog number: 1200-1301), storage temperature: room temperature
Note: These are necessary if performing magnetic bead washes using the Agilent Bravo.
Corning 96-well Clear V-Bottom 2 mL Polypropylene Deep Well Plate, sterile (Corning, catalog number: 3960), storage temperature: room temperature
Note: These are necessary if performing magnetic bead washes using the Agilent Bravo.
MicroAmp Fast Optical 96-Well Reaction Plate with Barcode, 0.1 mL (Thermo Fisher, Applied Biosystems, catalog number: 4346906), storage temperature: room temperature
Note: These are necessary if performing qPCR using the Applied Biosystems Fast 7500 system.
Qubit Assay Tubes (Thermo Fisher, Invitrogen, catalog number: Q32856), storage temperature: room temperature
(Optional) IgG (Total) Human ELISA Kit (e.g., Thermo Fisher, Invitrogen, catalog number: BMS2091), storage temperature: 4°C
Tris Buffered Saline with Tween 20 (TBST-10X) (Cell Signaling, catalog number: 9997), storage temperature: room temperature
Bovine Serum Albumin (BSA) (VWR, catalog number: 0332-500G), storage temperature: 4°C
PBS, pH 7.4 (e.g., Thermo Fisher, catalog number: 10010023), storage temperature: room temperature
VirScan T7 phage display library (Available upon request, storage temperature: -80°C)
Note: Based on T7Select Packaging Kit (Millipore-Sigma, catalog number: 70014) storage temperature: -80°C.
UltraPure 1M Tris-HCI, pH 8.0 (Thermo Fisher, Invitrogen, catalog number: 15568025), storage temperature: 4°C
NaCl (5 M), RNase-free (Thermo Fisher, Invitrogen, catalog number: AM9759), storage temperature: room temperature
Magnesium sulfate solution (Millipore Sigma, catalog number: M3409-100ML), storage temperature: room temperature
Chloramphenicol (Millipore Sigma, catalog number: C0378-100G), storage temperature: room temperature for powder or -20°C for reconstituted solution
Kanamycin B sulfate salt (Millipore Sigma, catalog number: B5264-250MG), storage temperature: -20°C for powder and for reconstituted solution
NP-40 Surfact-Amps Detergent Solution (Thermo Fisher, catalog number: 85124), storage temperature: room temperature
Dynabeads Protein A for Immunoprecipitation (Thermo Fisher, Invitrogen, catalog number: 10008D), storage temperature: 4°C
Dynabeads Protein G for Immunoprecipitation (Thermo Fisher, Invitrogen, catalog number: 10009D), storage temperature: 4°C
UltraPure 1 M Tris-HCI Buffer, pH 7.5 (Thermo Fisher, Invitrogen, catalog number: 15567027), storage temperature: 4°C
UltraPure DNase/RNase-Free Distilled Water (Thermo Fisher, Invitrogen, catalog number: 10977023), storage temperature: room temperature
Q5 Hot Start High-Fidelity DNA Polymerase (New England Biolabs, catalog number: M0493L) storage temperature: -20°C
dNTP Set (100 mM) (Thermo Fisher, Invitrogen, catalog number: 10297018), storage temperature: -20°C
TaqMan Gene Expression Master Mix (Thermo Fisher, Applied Biosystems, catalog number: 4369016), storage temperature: 4°C
UltraPure Agarose (Thermo Fisher, Invitrogen, catalog number: 16500100), storage temperature: room temperature
UltraPure DNA Typing Grade 50× TAE Buffer (Thermo Fisher, Invitrogen, catalog number: 24710030), storage temperature: room temperature
QIAquick Gel Extraction Kit (250) (QIAGEN, catalog number: 28706), storage temperature: room temperature
QIAquick PCR Purification Kit (250) (QIAGEN, catalog number: 28106), storage temperature: room temperature
Qubit dsDNA HS Assay Kit (Thermo Fisher, Invitrogen, catalog number: Q32851), storage temperature: mixed, room temperature and 4°C
HPLC-purified primers (IDT, storage temperature: -20°C)
Primer name Primer sequence (5’ – 3’)
IS7 ACACTCTTTCCCTACACGACTCCAGTCAGGTGTGATGCTC
IS8 GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCCGAGCTTATCGTCGTCATCC
IS4 AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACTCCAGT
Index primer CAAGCAGAAGACGGCATACGAGATNNNNNNNGTGACTGGAGTTCAGACGTGT
5’NEST-qPCR TCGGGGATCCAGGAATTC
3’NEST-qPCR CGTCGTCATCCTTGTAATCG
NEST_probe /56-FAM/TAATCGCGG/ZEN/CCGCAAGCTTGTC/3IABkFQ/
T7-Illumina-READ1-A TGCTCGGGGATCCAGGAATTCCGCTGCGT
Note: Orthogonal 7 nt barcodes for the Index primer are available upon request.
Phage extraction buffer (Recipe listed below), storage temperature: 4°C
PhIP-Seq Wash Buffer (Recipe listed below), storage temperature: 4°C
Equipment
Pipet-Lite Multi Pipette L12-20XLS+ (Rainin, catalog number: 17013808)
Pipet-Lite Multi Pipette L12-200XLS+ (Rainin, catalog number: 17013810)
E4 Pipette Multi E12-1200XLS+ (Rainin, catalog number: 17014499)
Portable Pipet-Aid XP Pipette Controller (Drummond, catalog number: 4-000-101)
Rotator (e.g., Barnstead/Thermolyne, model: 415110)
Benchtop Centrifuge with swinging-bucket rotor assembly and microplate carrier (e.g., Beckman Coulter, model: Allegra X-15R or Avanti J-15R, swinging-bucket rotor assembly: SX4750A or JS-4.750 , microplate carrier: SX4750)
Bravo NGS Automated Liquid Handling Platform (Agilent, catalog number: G5573AA)
96-Well Microtiter Plate Magnetic Separation Rack (NEB, catalog number: S1511S)
Note: This is necessary if performing magnetic bead washes manually.
Thermal cycler (e.g., Bio-Rad, model: C1000 Touch with 96-well Fast Reaction Module, catalog number: 1851196)
96-well Aluminum Block For 0.2 mL Tubes (Universal Medical, catalog number: 81001)
7500 Fast Dx Real-Time PCR Instrument, with laptop computer (Thermo Fisher, Applied Biosystems, catalog number: 4406984)
Qubit 4 Fluorometer (Thermo Fisher, Invitrogen, catalog number: Q33238)
Software
bowtie (Langmead et al., 2009)
samtools (Li et al., 2009)
python (Python Software Foundation. Python Language Reference, version 2.7. Available at http://www.python.org)
gcc (GNU Compiler Collection, version 6.2.0. Documentation at https://gcc.gnu.org/onlinedocs/gcc.pdf)
R (R Core Team, 2017)
Procedure
Video 1. Introduction
Block plates (Video 2)
Video 2. Blocking plates
Prepare 100 mL of TBST 3% BSA for every 96-well deep well plate (Cole-Parmer) to be blocked. Transfer to reagent reservoir.
Add 1 mL of TBST 3% BSA to each well of 96-well deep well plate.
Blot top of plate with kimwipes to remove excess liquid.
Seal plate well with MicroAmp optical adhesive film.
Note: Plate may be sealed by pressing outward from the center of plate to eliminate large air bubbles, then by using a sealing paddle to eliminate all remaining air pockets.
Invert plate several times to ensure the liquid is moving throughout the plate.
Tape 96-well deep well plate to the plate rotator at 4°C and rotate end-over-end overnight.
Phage-antibody complex formation (Video 3)
Video 3. Phage-antibody complex formation
Thaw VirScan T7 phage library on ice. Characteristics of the library are shown in Table 1.
Prepare 110 mL of diluted T7 phage library for each 96-well deep well plate. See Table 2 for information on how to prepare the diluted phage library.
Mix very well.
Table 1. VirScan T7 phage library characteristics
Complexity (version Vir3) 115,753 members
Desired final concentration 2 × 105 pfu/mL per member of the library, or approximately 2 × 1010 pfu/mL
Table 2. Preparing diluted phage library
Component Stock concentration Final concentration 110 rxns
VirScan phage library 9.9 × 1010 pfu/mL (this may vary by batch) 2 × 1010 pfu/mL 22.2 mL
chloramphenicol 50 mg/mL (1,000×) 50 μg/mL (1×) 110 μL
kanamycin 50 mg/mL (1,000×) 50 μg/mL (1×) 110 μL
Phage extraction buffer To 110 mL
Make aliquots of serum diluted to 0.2 μg/μL in PBS in 96-well PCR plates.
Notes:
Concentration of IgG in human serum is generally 5–10 μg/μL. Dilute 2 μL of serum in 98 μL of PBS (1:50 dilution) to reach a concentration of approximately 0.2 μg/μL human IgG. Mix well.
If needed, the concentration of IgG in a sample can be measured by IgG ELISA.
Serum samples are typically run in duplicate.
Eight no-serum controls are typically included for each run.
Pour out blocking solution from 96-well deep well plates into sink. Flick plates several times to remove all blocking solution.
Blot the surface of the plate with a kimwipe to remove liquid.
Add 1 mL of diluted phage library to each well.
Blot the surface of the plate with a kimwipe to remove excess liquid.
Add sera containing 2 μg of IgG to each well, or 10 μL of the 0.2 μg/μL plate previously prepared.
Blot the surface of the plate with a kimwipe to remove excess liquid.
Seal plates extremely well with a new MicroAmp optical adhesive film, using a paddle. Make sure no air bubbles remain between wells.
Invert plate several times to ensure that liquid is moving throughout the plate. Secure plates on rotator at 4°C and rotate with end-over-end mixing for 20 h or overnight.
Seal plate with diluted serum samples and store at -80°C.
Immunoprecipitation (Video 4)
Video 4. Immunoprecipitation
Centrifuge 96-well deep well plate at 500× g for 3 min to collect liquid away from seal.
Tightly hold down plate while removing seal. Avoid splashing and cross-contamination between wells.
Resuspend Protein A and Protein G Dynabeads by shaking bottles until there are no remaining beads settled at the bottom.
For each 96-well deep well plate, add 2 mL of Protein A and 2 mL of Protein G Dynabeads to a reagent reservoir and mix with a serological pipette.
Add 40 μL of Protein A/G to each well of the 96-well deep well plate.
Blot the surface of the plate with a kimwipe to remove excess liquid.
Seal plate with a new MicroAmp optical adhesive seals and tape plate to a rotator. Rotate for 4 h at room temperature or overnight at 4°C.
Take one plate off at a time for washes. Centrifuge the 96-well deep well plate at 500 × g for 3 min to collect liquid away from the seal.
Perform three washes using a liquid handling robot, as shown in Video 4, washing with 170 μL of PhIP-Seq Wash Buffer each time. At one point during the washes, transfer beads to a new 96-well deep well plate (Thermo Fisher) to avoid phage that may have bound non-specifically to the wells of the original plate. The Bravo protocol file is available in the Supplementary materials.
Alternatively, perform washes manually.
Place the plate on a magnetic separation rack.
Let plate sit for 2 min to allow beads to collect. You should be able to see the solution become clear.
Aspirate the liquid from each well. Switch tips after each well to avoid cross-contamination.
When aspirating, make sure to hold the plate flush against the magnetic rods to avoid aspirating the beads.
Note: Adjust the direction depending on where the magnetic rod sits relative to the wells.
After aspirating the liquid from each row of wells, add 400 μL of PhIP-Seq Wash Buffer to the empty wells to prevent the beads from drying out.
Remove the plate from the magnetic separation rack and use a multichannel pipettor to resuspend the beads in all the wells by pipetting up and down 10 times.
Repeat steps i-iv for a total of three washes. During the first wash, transfer the beads to the new 96-well deep well plate.
Cover the plate with a new MicroAmp optical adhesive seal and centrifuge the beads at 500 × g for 1 min. Aspirate any remaining liquid.
Resuspend the beads in each well in 40 μL of sterile water and transfer to PCR plate. Seal plate.
Spin PCR plate with resuspended beads in centrifuge for ~10 s, until centrifuge reaches 50 × g, to collect beads off the sides of the wells.
Heat plate to 95°C for 10 min to lyse T7 phage.
Store plate at -80°C for up to a week or proceed directly to library preparation for next-generation sequencing.
Library preparation for next-generation sequencing (Video 5)
Note: When setting up PCRs, keep PCR plate on aluminum block on ice at all times. Keep all reagents on ice at all times.
Video 5. Library preparation for next-generation sequencing
Thaw frozen beads on ice, then centrifuge at 1,000 × g for 2 min.
Make PCR1 master mix, mix well, and transfer to a reservoir on ice.
Component Stock concentration Final concentration 1 rxn (μL) 110 rxns (μL)
Sterile water 2.68 294.8
Reaction Buffer 5× 1× 6.0 660
dNTPs 10 mM 0.3 mM 0.90 99
Primer IS7 100 μM 0.2 μM 0.06 6.6
Primer IS8 100 μM 0.2 μM 0.06 6.6
Q5 2 U/μL 0.02 U/μL 0.30 33
Template 2× 1× 20
Total 30 μL
Aliquot 10 μL of PCR1 master mix to each well of a new 96-well PCR plate. Keep plate on aluminum block on ice at all times.
Resuspend beads by pipetting and add 20 μL of beads to corresponding wells. Mix well by pipetting.
Note: If sequencing input library, mix 5 μL of input library and 15 μL of sterile water and use this as the template for the PCR1 instead of 20 μL of resuspended beads.
Spin PCR1 plate in centrifuge for ~10 s, until centrifuge reaches 50 × g, then immediately remove plate and return to aluminum block on ice.
Run PCR1.
STEP TEMP TIME
Initial Denaturation 98°C 30 s
28 Cycles total 98°C 5 s
66°C 10 s
72°C 30 s
Final Extension 72°C 2 min
Hold 4–10°C
Make PCR2 master mix, mix well, and transfer to reagent reservoir.
Notes:
Sample multiplexing is achieved using barcoded PCR2 RV primers (Index primers).
Index primers are diluted to 2.5 μM and kept in a 96-well plate.
Component Stock concentration Final concentration 1 rxn (μL) 110 rxns (μL)
Sterile water 4.55 500.5
Reaction Buffer 5× 1× 2.0 220
dNTPs 10 mM 0.3 mM 0.3 33
Primer IS4 100 μM 0.5 μM 0.05 5.5
Index primer 2.5 μM 0.5 μM 2.0
Q5 2 U/μL 0.02 U/μL 0.1 11
Template 2× 1× 1.0
Total 10 μL
Distribute 7 μLof PCR2 master mix to each well of a new 96-well PCR plate.
Add 2 μL of appropriate index primers (diluted to 2.5 μM) to corresponding wells.
Add 1 μL of appropriate PCR1 product to corresponding wells as template.
Mix PCR reactions by running the paddle rapidly across the bottom of PCR plate a few times, thus agitating the wells. Spin PCR plate in centrifuge for ~10 s until centrifuge reaches 50 × g, then immediately return plate to aluminum block on ice.
Run PCR2.
STEP TEMP TIME
Initial Denaturation 98°C 30 s
Eight cycles total 98°C 5 s
68°C 10 s
72°C 30 s
Final Extension 72°C 2 min
Hold 4–10°C
Note: Steps 13–19 are quality control steps to verify that there is an amplicon in all appropriate wells.
Dilute PCR2 product 1:40,000 in sterile water.
Serially dilute 2 μL of PCR2 product in 398 μL of sterile water (1:200 dilution) twice.
Make qPCR master mix, mix well, and transfer to reservoir.
Component Stock concentration Final concentration 1 rxn (μL) 110 rxns (μL)
Sterile water 8.75 962.5
Universal Mix 2× 1× 10 1100
3’ NEST qPCR primer 100 μM 0.5 μM 0.1 11
5’ NEST qPCR primer 100 μM 0.5 μM 0.1 11
NEST qPCR probe 100 μM 0.25 μM 0.05 5.5
PCR2 template, diluted 1:40,000 1.0
Total 20 μL
Distribute 19 μL of qPCR master mix to each well of a 96-well qPCR plate.
Add 1 μL of appropriate PCR2 product, diluted 1:40,000, to corresponding wells as template.
Mix qPCR reactions by running paddle rapidly across bottom of PCR plate a few times, thus agitating the wells. Spin in centrifuge for ~10 s, until centrifuge reaches 50 × g.
Run qPCR.
STEP TEMP TIME
1 Cycle 50°C 2 min
95°C 10 min
40 Cycles 95°C 15 s
60°C 2 min
If a well fails to amplify by qPCR, run out the corresponding PCR1 and PCR2 products to diagnose the problem. If necessary, redo PCR1 and/or PCR2.
Pool 2 μL of each sample of PCR2 in a reservoir, mix, and transfer to 1.5 mL microfuge tube.
Notes:
Pool samples from individual plates separately.
If sequencing input library, add 10× the volume of any given sample into the final pool, i.e., if pooling 2 μL of each sample, add 20 μL of the input library to the pool.
Run 40 μL of pooled PCR2 products from each plate on a 2% agarose TAE gel.
Gel extract correct size band using QIAgen Gel Extraction Kit.
Notes:
The expected amplicon size for the T7 VirScan library is 376 bp.
There may be a faint band directly below the correct-size band. Do not extract this faint lower band, as it contains products with truncated or missing Primer IS4 or Index Primer sequences.
PCR purify gel-extracted samples using QIAquick PCR Purification kit.
Note: PCR purification is performed after gel extraction to ensure greater purity of the sample prior to next-generation sequencing.
Quantitate DNA using dsDNA HS Qubit assay, then pool equal amounts (ng) of each plate.
Next-generation sequencing
Submit the pooled library for sequencing. The following sequencing parameters are required:
Note: We generally sequence pooled libraries of 192 samples at a core facility with an Illumina NextSeq 500 instrument and the NextSeq 500/550 High Output Kit v2.5 (75 Cycles), which yields ~400M reads. We order single-read, single-index sequencing, detailed below.
Read 1: 75 cycles
Note: Only 50 cycles are required, but we typically order 75 cycles and truncate the reads during the Data Analysis steps.
Index I7: 7 cycles
Sequencing depth: 1M reads/sample.
Custom sequencing primer for Read 1: T7-Illumina-READ1-A
Data analysis
Notes:
In the instructions below, lines of code are bolded. These instructions are for use on a computing cluster using SLURM.
Example VirScan data for two serum samples and their technical replicates are provided (Supplementary materials). Data files include a sample legend, fastq files, BAM files, alignment report files, indexed BAM files, counts files, count.combined files (counts summed across four lanes of a Nextseq 500 flow cell), a counts table (count.combined data presented in a table format; summed counts for no-serum controls are provided in the column “input”), a Z-score table (again, summed counts for no-serum controls are present in the column ‘input’), a hits_combined table, and virus scores files.
Align sequencing reads to a reference file
Use the reference fasta file for the VirScan library (“vir3.fasta”) (Supplementary materials) and generate index files with the .ebwt extension. Run the following commands:
module load gcc/6.2.0
module load bowtie/1.2.2
bowtie-build vir3.fasta vir3
Align sequencing reads to the reference file. See “script.align.sh” and edit as needed (Supplementary materials). The output file is a file that ends in “.bam”
Notes:
Sequencing reads are typically distributed as fastq files. These fastq files are stored in a subdirectory called “raw.data”.
In “script.align.sh”, “bowtie -3 25” trims 25 nucleotides off the 3’ end of each sequencing read. This is done if sequencing reads are 75 nucleotides in length. The reference file only includes the first 50 nucleotides of each member of the library, so the sequencing reads must be trimmed down to 50 nucleotides to align correctly to the reference.
In “script.align.sh”, replace “path_to_vir3_reference_fasta_and_index_files” with the appropriate path.
./ script.align.sh
Check the alignment report file that ends in “.out”
Note: Typically, >85% of the reads align to the reference file.
Index files with the following commands. The output file is a file that ends in “.bai”
module load gcc/6.2.0
module load samtools/1.3.1
for i in raw.data/*.bam; do samtools index $i; done
Count indexes with the following commands. The output is a file that ends in “.count.csv”
module load gcc/6.2.0
module load samtools/1.3.1
for i in raw.data/*.bam; do samtools idxstats $i | cut -f 1,3 | sed -e '/^\*\t/d' -e '1 i id\tSAMPLE_ID' | tr "\\t" "," >${i%.bam}.count.csv; done
Gzip the counts files with the following command.
for i in raw.data/*.csv; do gzip $i; done
Create a directory called “log_directory” with the following command.
mkdir log_directory
If the same sample is run on two or more lanes of a flow cell and separate files are provided for each flow cell, combine the counts files from the different lanes using the following commands. These commands require the python script “combine_two_lanes.py” to be copied to the folder where you are running the commands (Supplementary materials).
Note: In the code below, the samples were run on four lanes of an Illumina Nextseq 500 flow cell. The suffix of each count file is “L001_R1_001.count.csv.gz” if the count file was from the first lane of the flow cell, “L002_R1_001.count.csv.gz” if the count was from the second lane of the flow cell, etc.
module load gcc/6.2.0
module load python
for i in raw.data/*L001_R1_001.count.csv.gz; do python combine_two_lanes.py $i ${i%1_R1_001.count.csv.gz}2_R1_001.count.csv.gz ${i%1_R1_001.count.csv.gz}1_2_R1_001.count.csv; done
for i in raw.data/*L003_R1_001.count.csv.gz; do python combine_two_lanes.py $i ${i%3_R1_001.count.csv.gz}4_R1_001.count.csv.gz ${i%3_R1_001.count.csv.gz}3_4_R1_001.count.csv; done
for i in raw.data/*L001_2_R1_001.count.csv; do python combine_two_lanes.py $i ${i%1_2_R1_001.count.csv}3_4_R1_001.count.csv ${i%1_2_R1_001.count.csv}1_2_3_4_R1_001.count.combined.csv; done
Gzip the count.combined files with the following command.
for i in raw.data/*1_2_3_4_R1.count.combined.csv; do gzip $i; done
Calculate Z-scores
Note: To perform the Z-score analysis, count.combined files are merged into a table, and columns corresponding with no-serum controls are summed in a column called “input”.
Edit the R script “Zscore_analysis.R” to include the path to the count.combined table file and the desired path to the output file, then run the script (Supplementary materials). The packages “mmR_0.1.0” and “virScanR_0.1.0.9000” are required (Supplementary materials).
Note: The file “Zscores_vir3” contains the results after this step (Supplementary materials).
A Z-score of at least 3.5 in both technical replicates of a sample is required to call a peptide a “hit”.
Note: The file “hits_combined_vir3_3.5_cutoff” contains the results after this step (Supplementary materials).
Calculate virus scores
Create a directory called “hits”. In this directory should be .csv files for each sample with “True” or “False” values for each peptide ID, depending on whether the peptide scored as a hit (Z-score > 3.5) in both technical replicates of a sample or not. These files may be created by splitting each column of the “hits_combined_vir3_3.5_cutoff” file into a separate files (Supplementary materials).
Generate virus scores files using the following code:
Note: The “VIR3_clean” file provides the annotations for the oligos” (Supplementary materials). There are 115,753 oligos in the Vir3 library. Some protein fragments are identical in different viruses, and in these case there are multiple rows in the “VIR3_clean” file that correspond to a single oligo. To identify the viral source of a given peptide, look for the row(s) in the VIR3_clean file with the "id" value of the given peptide.
for i in hits/*.csv.gz; do python calc_scores_nofilter.py $i VIR3_clean.csv.gz Species 7 >virus_scores_$i; done
Determining virus seropositivity
A sample is determined to be seropositive for a virus if the virus_score > VirScan_viral_threshold and if at least one public epitope from that virus scores as a hit. The file “VirScan_viral_thresholds” contains the thresholds for each virus (Supplementary materials).
Note: Public epitope annotations are available upon request.
Recipes
Phage extraction buffer
20 mM Tris-HCl, pH 8.0
100 mM NaCl
6 mM MgSO4
Store at 4°C
PhIP-Seq Wash Buffer
50 mM Tris-HCl, pH 7.5
150 mM NaCl
0.1% NP-40
Store at 4°C
Acknowledgments
Funding: E.L.S. was supported by the NSF Graduate Research Fellowship Program. S.J.E. is an Investigator with the Howard Hughes Medical Institute.
Original research papers from which this protocol was derived: Larman et al. (2011), Xu et al. (2015), and Mina et al. (2019).
We thank A. Kohlgruber for designing the schematic in the graphical abstract.
Competing interests
S.J.E. is a founder of TSCAN Therapeutics, MAZE Therapeutics, Mirimus, and ImmuneID. S.J.E. serves on the scientific advisory board of Homology Medicines, TSCAN Therapeutics, MAZE Therapeutics, XChem, and is an advisor for MPM, none of which impact this work. E.L.S. was a consultant for ImmuneID. S.J.E. is an inventor on a patent application filed by the Brigham and Women's Hospital (US20160320406A) that covers the use of the VirScan library to identify pathogen antibodies in blood.
Ethics
Human specimens were collected in accordance with the local protocol governing human research after obtaining informed written consent from the donors. Secondary use of all human samples for the purposes of this work was exempted by the Brigham and Women’s Hospital Institutional Review Board (protocol number 2013P001337).
References
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Borriello, F., Poli, V., Shrock, E., Spreafico, R., Liu, X., Pishesha, N., Carpenet, C., Chou, J., Di Gioia, M., McGrath, M. E., et al. (2022). An adjuvant strategy enabled by modulation of the physical properties of microbial ligands expands antigen immunogenicity. Cell 185(4): 614-629 e621.
Chen, G., Shrock, E. L., Li, M. Z., Spergel, J. M., Nadeau, K. C., Pongracic, J. A., Umetsu, D. T., Rachid, R., MacGinnitie, A. J., Phipatanakul, W., et al. (2021). High-resolution epitope mapping by AllerScan reveals relationships between IgE and IgG repertoires during peanut oral immunotherapy. Cell Rep Med 2(10): 100410.
Garrett, M. E., Itell, H. L., Crawford, K. H. D., Basom, R., Bloom, J. D. and Overbaugh, J. (2020). Phage-DMS: A Comprehensive Method for Fine Mapping of Antibody Epitopes. iScience 23(10): 101622.
Hill, J. A., Krantz, E. M., Hay, K. A., Dasgupta, S., Stevens-Ayers, T., Bender Ignacio, R. A., Bar, M., Maalouf, J., Cherian, S., Chen, X. et al. (2019). Durable preservation of antiviral antibodies after CD19-directed chimeric antigen receptor T-cell immunotherapy. Blood Adv 3(22): 3590-3601.
Kosuri, S., Eroshenko, N., Leproust, E. M., Super, M., Way, J., Li, J. B. and Church, G. M. (2010). Scalable gene synthesis by selective amplification of DNA pools from high-fidelity microchips. Nat Biotechnol 28(12): 1295-1299.
Langmead, B., Trapnell, C., Pop, M. and Salzberg, S. L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3): R25.
Larman, H. B., Zhao, Z., Laserson, U., Li, M. Z., Ciccia, A., Gakidis, M. A., Church, G. M., Kesari, S., Leproust, E. M., Solimini, N. L. et al. (2011). Autoantigen discovery with a synthetic human peptidome. Nat Biotechnol 29(6): 535-541.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16): 2078-2079.
Mandel-Brehm, C., Dubey, D., Kryzer, T. J., O'Donovan, B. D., Tran, B., Vazquez, S. E., Sample, H. A., Zorn, K. C., Khan, L. M., Bledsoe, I. O., et al. (2019). Kelch-like Protein 11 Antibodies in Seminoma-Associated Paraneoplastic Encephalitis. N Engl J Med 381(1): 47-54.
Mina, M. J., Kula, T., Leng, Y., Li, M., de Vries, R. D., Knip, M., Siljander, H., Rewers, M., Choy, D. F., Wilson, M. S., et al. (2019). Measles virus infection diminishes preexisting antibodies that offer protection from other pathogens. Science 366(6465): 599-606.
Mohan, D., Wansley, D. L., Sie, B. M., Noon, M. S., Baer, A. N., Laserson, U. and Larman, H. B. (2018). PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes. Nat Protoc 13(9): 1958-1978.
Pou, C., Nkulikiyimfura, D., Henckel, E., Olin, A., Lakshmikanth, T., Mikes, J., Wang, J., Chen, Y., Bernhardsson, A. K., Gustafsson, A., et al. (2019). The repertoire of maternal anti-viral antibodies in human newborns. Nat Med 25(4): 591-596.
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Schubert, R. D., Hawes, I. A., Ramachandran, P. S., Ramesh, A., Crawford, E. D., Pak, J. E., Wu, W., Cheung, C. K., O'Donovan, B. D., Tato, C. M., et al. (2019). Pan-viral serology implicates enteroviruses in acute flaccid myelitis. Nat Med 25(11): 1748-1752.
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4,465 | https://bio-protocol.org/en/bpdetail?id=4465&type=0 | # Bio-Protocol Content
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Generation of a Human Conditionally Immortalized Cell-based Multicellular Spheroidal Blood-Brain Barrier Model for Permeability Evaluation of Macromolecules
RI Ryuto Isogai
HM Hanae Morio
AO Ayaka Okamoto
KK Keita Kitamura
TF Tomomi Furihata
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4465 Views: 1890
Reviewed by: Pilar Villacampa AlcubierreAchira RoyXuecai Ge
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Original Research Article:
The authors used this protocol in Biological and Pharmaceutical Bulletin Jul 2021
Abstract
There is an urgent need for the development of brain drug delivery carriers based on middle-sized or macromolecules, to which in vitro blood-brain barrier (BBB) models are expected to contribute significantly through evaluation of BBB permeability. As part of efforts to develop such models, we have been working on human conditionally immortalized cell-based multicellular spheroidal BBB models (hiMCS-BBB models), and we herein introduce the model development protocol. Briefly, astrocytes are first seeded in an ultra-low attachment 3D cell culture plate, to make the central core (Day 0). Next, pericytes are added over the core, to form an outer layer (Day 1). Then, brain microvascular endothelial cells are further added to each well, to create the outmost monolayer serving as the BBB (Day 2). Finally, the spheroids cultured for two days (on Day 4) can be used for assays of interest (e.g., antibody permeability assays). Neither special equipment nor techniques are required to produce hiMCS-BBB models. Therefore, the protocol presented here will not only facilitate the model sharing among the BBB community but also provide some technical clues contributing to the development of similar MCS-BBB models using other cell sources, such as primary or iPS-derived BBB cells.
Graphical abstract:
Keywords: Blood-brain barrier In vitro model Spheroid Receptor-mediated transcytosis Immortalized cell Central nervous system Drug development Microphysiological systems
Background
The blood-brain barrier (BBB) forms a nearly impregnable wall preventing the distribution of numerous blood-borne middle-sized and macromolecules (middle/macromolecules) and low-molecular-weight drugs into the human brain (Sanchez-Cano et al., 2021; Segarra et al., 2021). As such, it often imposes a frustrating barrier to brain drug delivery efforts, thus rendering central nervous system (CNS) diseases among the most difficult to treat pharmaceutically. Brain microvascular endothelial cells (BMECs), which work with the support of pericytes and astrocytes, make up the critical components of the BBB. The pericytes are located in the immediate vicinity of the BMECs, while the astrocytes wrap them through their endfeet. This structural integrity is essential for BBB functions (Ballabh et al., 2004; Abbott et al., 2006; Daneman et al., 2015). The two primary functional characteristics of the BBB are tight/adherens junctions and efflux transporters. The former tightly seals BMEC plasma membranes to limit paracellular transport of various substances, including middle/macromolecules, while the latter are localized on the vascular side of BMECs and actively pump out their substrates into circulation (Ballabh et al., 2004; Abbott et al., 2010). Therefore, as part of efforts to create effective therapeutic approaches to CNS diseases, it is necessary to develop BBB-permeable drug delivery system (DDS) carriers that can overcome this barrier.
From that point of view, receptor-mediated transcytosis (RMT) occurring at the BBB has gained significant attention (Lajoie et al., 2015; Fang et al., 2017). Physiologically, after binding to their middle/macromolecule ligands at the blood side of BMECs, RMT receptors undergo endosomal vesicle formation to travel to the brain side, where they eventually release their cargo into the brain via exocytosis (Freskgård et al., 2017; Kouhi et al., 2021; Zhou et al., 2021). One intriguing idea for facilitating the development of brain DDS carriers involves taking advantage of those RMT processes, as exemplified by antibodies targeting transferrin or insulin receptors expressed in BMECs (Boado et al., 2016; Sonoda et al., 2018), resulting in an ongoing urgent need for effective and high-throughput evaluations of their BBB permeabilities. To this end, there have been a variety of next-generation in vitro BBB models based on microphysiological systems (MPSs), including BBB-on-a-chip, organoids, and spheroids (Cho et al., 2017; Wevers et al., 2018; Simonneau et al., 2021). These models feature high functionality derived based on their reproduction of the structure and surrounding microenvironment of the BBB in vivo (specifically, MPSs).
As part of efforts to facilitate the development of such models, we have been working on human conditionally immortalized cell-based multicellular spheroidal BBB models (hiMCS-BBB models) consisting of human conditionally immortalized BMECs (HBMEC/ci18 cells) (Kamiichi et al., 2012; Ito et al., 2019), astrocytes (HASTR/ci35 cells) (Furihata et al., 2016; Kitamura et al., 2018), and brain pericytes (HBPC/ci37 cells) (Umehara et al., 2018). These cells carry immortalization genes that enable them to extensively proliferate, while their status can be changed simply by varying the cell culture temperature (33 °C for growth and 37 °C for differentiation — for details, please refer to our above-cited previous papers).
In hiMCS-BBB models, HASTR/ci35 cells shape the central core, which is covered by an HBPC/ci37 cell layer. That layer is further surrounded by an HBMEC/ci18 cell monolayer serving as the BBB (Kitamura et al., 2021, 2022). This structural feature allows us to perform several BBB functional analyses, such as transporter activity assessments, and immune cell recruitments (Kitamura et al., 2021, 2022). In particular, the models exhibit RMT functions that are sufficiently high for use in evaluating the BBB permeability of antibodies and peptides (Kitamura et al., 2022). Additionally, the immortalized cells used are both scalable and easy to handle, and neither special equipment nor techniques are required to produce the models (as described herein). Owing to all these advantages, hiMCS-BBB models are expected to have great potential for use in developing novel middle/macromolecule-based DDS carriers.
In this paper, we describe the method used for constructing hiMCS-BBB models together with the culture methods for the human immortalized BBB cells. In alignment with that, we will also introduce an example of a middle/macromolecule permeability assay performed using hiMCS-BBB models. Through this publication, we aim not only to share hiMCS-BBB models among the BBB community but also to provide some technical clues that may contribute to the development of MCS-BBB models using other cell sources, such as primary or iPS-derived BBB cells, although some modifications may be necessary.
Materials and Reagents
Note: Most products can be replaced by those from other suppliers, but it is uncertain whether this is also true for the marked products (*) since we have not tested other materials.
Low binding 200 µL tips (TreffLab, catalog number: 96.11179.4.01)
Normal tips (Nacalai Tesque, catalog numbers: 19166-54 [10 µL], 19167-44 [200 µL], 19168-34 [1,000 µL])
Violamo Disposable Pipette II (VIOLAMO, catalog numbers: 2-5237-12 [2 mL], 2-5237-03 [5 mL], 2-5237-04 [10 mL], 2-5237-05 [25 mL])
Cryotubes (Thermo Fisher Scientific, catalog number: 363401PK)
15-mL centrifuge tubes (Thermo Fisher Scientific, catalog number: 339650)
50-mL centrifuge tubes (Thermo Fisher Scientific, catalog number: 339652)
1.5 mL tubes (WATSON, catalog number: 131-715C)
Protein LoBind 1.5 mL tubes (Eppendorf, catalog number: 22431081)
Collagen I-coated 60-mm dishes (IWAKI, catalog number: 4010-010)
Collagen I-coated 100-mm dishes (IWAKI, catalog number: 4020-010)
Note: Other collagen type I-coated products may be used.
PrimeSurface 96V plates (96-well V-bottom plates)* (Sumitomo Bakelite, catalog number: MS-9096V)
Cell counting slides (Logos Biosystems, catalog number: L12001)
Slide glass 76 × 26 mm (slide glass) (Matsunami-glass, catalog number: MAS-01)
Cover glass 24 × 60 mm (cover glass) (Matsunami-glass, catalog number: C024601)
100-mL flask (IWAKI, catalog number: 4980FK100)
Parafilm
Nail polish
Human astrocytes/conditionally immortalized clone 35 (HASTR/ci35 cells)* (Furihata et al., 2016; Kitamura et al., 2018)
Human brain pericytes/conditionally immortalized clone 37 (HBPC/ci37 cells)* (Umehara et al., 2018)
Human brain microvascular endothelial cells/conditionally immortalized clone 18 (HBMEC/ci18 cells)* (Kamiichi et al., 2012; Ito et al., 2019)
Blasticidin S (InvivoGen, catalog number: ant-bl-1)
Astrocyte Medium kit (consisting of the basal medium and culture supplements)* (Thermo Fisher Scientific, catalog number: A1261301)
Pericyte Medium kit (consisting of the basal medium and culture supplements)* (ScienCell, catalog number: 1201)
VascuLife VEGF Comp kit (consisting of VascuLife BM and culture supplements) (Lifeline Cell Technology, catalog number: LEC-LL0003)
Note: EBM-2 (Lonza, catalog number: CC-3162) can be used instead.
Penicillin-streptomycin (Nacalai Tesque, catalog number: 26253-84)
Bambanker (NIPPON Genetics, catalog number: CS-02-001)
Dulbecco’s phosphate buffered saline Ca, Mg free (D-PBS(-)) (Nacalai Tesque, catalog number: 14249-24)
D-PBS(+) preparation reagent (Ca, Mg solution) (Nacalai Tesque, catalog number: 02492-94)
Hanks’ balanced salt solution (HBSS(+)) (Nacalai Tesque, catalog number: 09735-75)
2.5 g/L-trypsin/1 mmol/L-EDTA (trypsin) (Nacalai Tesque, catalog number: 32777-15)
Trypan blue (Wako, catalog number: 207-17081)
4% paraformaldehyde (PFA) (Nacalai Tesque, catalog number: 09154-85)
Fluoro-KEEPER Antifade Reagent, Non-Hardening Type (antifade reagent) (Nacalai Tesque, catalog number: 12593-64)
Methyl cellulose-viscosity: 4,000 cP (methyl cellulose)* (Sigma-Aldrich, catalog number: M0512-100G)
MEM189 [Alexa Fluor 647] (Novus Biologicals, catalog number: NB500-493AF647)
CellTracker Orange CMTMR Dye (Invitrogen, catalog number: C2927)
Red-fluorescent Cytoplasmic Membrane Staining Kit (PromoKine, catalog number: PK-CA707-30023)
CellTracker Green CMFDA Dye (Invitrogen, catalog number: C2925)
AM (astrocyte medium) (see Recipes)
PM (pericyte medium) (see Recipes)
VascuLife medium (see Recipes)
Spheroid medium (see Recipes)
D-PBS(+) (see Recipes)
Equipment
Clean bench (or safety cabinet)
Water bath set at 37 °C
Water bath set at 60 °C
Centrifuge (e.g., Kokusan, catalog number: H-19Rα)
Aspirator
Phase contrast microscope (e.g., Nikon, ECLIPSE Ts2)
Confocal laser scanning microscope (e.g., OLYMPUS, FLUOVIEW FV3000)
Humidified incubator set at 33 °C with 5% CO2/95% air
Humidified incubator set at 37 °C with 5% CO2/95% air
Automated cell counter (e.g., Logos Biosystems, catalog number: L10001SS)
Fridge (4 °C) and freezers (-20 °C and -80 °C)
Liquid nitrogen storage
Electric pipettor (e.g., Greiner Bio-One, catalog number: J847050)
Pipettes (e.g., HTL LAB SOLUTIONS, catalog number: 7904)
Stirring bar (e.g., AS ONE Corporation, catalog number: 1-4206-27)
Magnetic stirrer
Autoclave (e.g., HIRAYAMA, HV-2LB)
Procedure
The HASTR/ci35, HBPC/ci37, and HBMEC/ci18 cell lines carry two immortalization genes: the temperature-sensitive simian virus 40 large tumor antigen (tsSV40T) and the human telomerase reverse transcriptase catalytic subunit (hTERT) genes. The tsSV40T promotes proliferation at 33 °C, while becoming unstable to lose its function at 37 °C. Therefore, for maintenance and differentiation purposes, the cells should be cultured at 33 °C and 37 °C, respectively. Please see our previous reports for the details (Kamiichi et al., 2012; Furihata et al., 2016; Kitamura et al., 2018; Umehara et al., 2018; Ito et al., 2019).
Thawing cells
Notes:
Blasticidin S (final concentration (f.c.) 4 µg/mL) should always be added to each culture medium to maintain the expression of the immortalization genes.
The cell handling procedure should always be performed inside a clean bench.
HASTR/ci35 cells
Warm the astrocyte medium (AM, see Recipe 1) in a water bath set at 37°C.
Add 1 mL of AM into a 15-mL centrifuge tube.
Remove the cryotube containing the frozen cells from the liquid nitrogen and immediately place it in a water bath set at 37°C.
Note: Cells (0.5 × 106–1.0 × 106) at the logarithmic growth phase (70%–80% confluency) are recommended for frozen storage with 1 mL of Bambanker.
Immediately begin thawing the frozen cells by gently shaking the cryotube in the water bath. However, remove the cryotube from the water bath before the frozen cells are completely thawed.
Transfer the cells into a 15-mL centrifuge tube containing 1 mL of AM, and then perform centrifugation (120 × g) at room temperature for 3 min.
Remove the supernatant using an aspirator and resuspend the cells with 5 mL of AM.
Seed the cells into a collagen I-coated 60-mm dish and then gently shake the dish back and forth and from side to side, to ensure the cells disperse evenly.
Check the cells in the dish under a microscope.
Culture the cells in a humidified incubator at 33 °C with 5% CO2/95% air.
HBPC/ci37 cells
The handling procedure for HBPC/ci37 cells is essentially the same as that employed for HASTR/ci35 cells, except for the use of the pericyte medium (PM, see Recipe 2) instead of AM.
Note: For frozen storage, we recommend the cell number of 0.7 × 106–1.0 × 106 in a cryotube with 1 mL of Bambanker.
HBMEC/ci18 cells
The handling procedure for HBMEC/ci18 cells is essentially the same as that employed for HASTR/ci35 cells, except for the use of VascuLife medium (see Recipe 3) instead of AM.
Note: For frozen storage, we recommend the cell number of 0.8 × 106–1.0 × 106 in a cryotube with 1 mL of Bambanker.
Passaging cells
Figure 1. Cell confluency of the human immortalized BBB cells before and after the passaging. Upon reaching appropriate cell confluency (>90%) in a collagen I-coated 100-mm dish, as represented in (A), (B), and (C), HASTR/ci35, HBPC/ci37, and HBMEC/ci18 cells can be passaged with 6.0 × 105, 5.5 × 105, and 5.5 × 105 cells, respectively. The representative cell culture images captured one day after passaging are shown in (D), (E), and (F). The images were taken under a phase-contrast microscope (ECLIPSE Ts2, NIKON, Tokyo, Japan).
Notes:
* Avoid culturing at low cell density levels (you should always maintain confluency at more than 50%).
* Avoid rough pipetting to prevent cell degeneration or loss of cell traits.
* Blasticidin S (f.c. 4 µg/mL) should always be added to each culture medium to maintain the expression of the immortalization genes.
All the above notes (marked with *) are critically important.
The cell handling procedure should always be performed inside a clean bench.
As an example, the procedure shown in this section is used for passaging cells from a collagen I-coated 100-mm dish into a new one.
HASTR/ci35 cells
Warm AM and D-PBS(-) in a water bath set at 37 °C.
Prepare the cells in a collagen I-coated dish, as shown in Figure 1A.
Remove the AM from the dish using an aspirator.
Wash the cells once with 4–8 mL of D-PBS(-).
After completely removing the D-PBS(-) using an aspirator, add 1 mL of trypsin (one-tenth of the medium volume) to the cells, and then incubate them at 37 °C for 5 min.
Check the cells under a microscope to ensure they have detached from the dish.
Add 1 mL of AM (the same amount of trypsin) to the cells to stop the trypsinization process while loosening any adhering cell lumps via gentle pipetting.
Notes:
Use of a 1,000 µL tip is recommended for cell pipetting. Take at least 3 s for each suction/discharge operation to avoid imparting excess stress on the cells.
Alternatively, centrifugation can be used to remove the trypsin.
Transfer an appropriate number of cells to a new collagen I-coated 100-mm dish, and then add fresh AM up to 10 mL.
Note: Do NOT subculture the cells at densities of less than 6.0 × 105 cells in a 100-mm dish.
Gently shake the dish back and forth and from side to side, to ensure the cells disperse evenly.
Culture the cells in a humidified incubator at 33 °C with 5% CO2/5% air.
Note: Passaging can be performed every three days when using a density of 6.0 × 105 cells in a 100-mm dish (Figure 1D).
HBPC/ci37 cells
Prepare the cells in a collagen I-coated dish as shown in Figure 1B. The handling procedure for HBPC/ci37 cells is essentially the same as that employed for HASTR/ci35 cells, except for the use of PM and 6 min trypsinization time instead of AM and 5 min, respectively.
Notes:
Passaging can be performed every four days when using a density of 5.5 × 105 cells in a 100-mm dish (Figure 1E). Do NOT subculture the cells at densities of less than this concentration.
HBPC/ci37 cells are sometimes difficult to detach from collagen I-coated dishes even when following the trypsin treatment method described here. In such cases, try one of the following actions:
1) Extend the trypsin treatment period up to 9 min.
2) After 6 min of the first trypsin treatment, collect and transfer the detached cells from the dish into a 15-mL centrifuge tube. Immediately, add another 1 mL of trypsin solution to the dish, and allow it to stand for another 3 min. Then, collect the remaining cells and combine them with those removed earlier.
HBMEC/ci18 cells
Prepare the cells in a collagen I-coated dish as shown in Figure 1C. The handling procedure for HBMEC/ci18 cells is essentially the same as that employed for HASTR/ci35 cells, except for the use of VascuLife medium and 6 min trypsinization time instead of AM and 5 min, respectively.
Notes:
Passaging can be performed every four days when using a density of 5.5 × 105 cells in a 100-mm dish (Figure 1F). Do NOT subculture the cells at densities of less than this concentration.
HBMEC/ci18 cells are often difficult to detach from collagen I-coated dishes even when following the trypsin treatment method described here. In such cases, follow the instructions provided in the Note for HBPC/ci37 cells.
Construction of hiMCS-BBB models in a 96-well V-bottom plate
Figure 2. A diagram of the hiMCS-BBB model construction process. This figure shows HASTR/ci35 cells seeded in a PrimeSurface 96V plate (Sumitomo Bakelite, Tokyo, Japan) at 1,750 (cells/well) on Day 0. On Day 1, HBPC/ci37 cells (500/well) are added over the HASTR/ci35 spheroid core. On Day 2, HBMEC/ci18 cells (750/well) are further added to each well. Finally, the spheroids cultured on Day 4 can be used for assays of interest.
Notes:
The cell handling procedure should always be performed inside a clean bench.
Blasticidin S is not necessary in the Spheroid medium (see Recipe 4).
All medium and D-PBS(-) should be pre-warmed in a water bath set at 37 °C.
Only one spheroid should be formed in each well of a 96-well V-bottom plate.
The spheroid development protocol described here is related to our report in 2022 (Kitamura et al., 2022).
Day 0: HASTR/ci35 cell seeding
Collect the HASTR/ci35 cells from the dish using the same procedure shown in steps B1c–B1g, and transfer them into a 15-mL centrifuge tube.
Centrifuge (500 × g) the tube at room temperature for 3 min.
Remove the supernatant using an aspirator and resuspend the cells with 1 mL of D-PBS(-).
Repeat step 2.
Remove the supernatant using an aspirator and resuspend the cells with 1 mL of the Spheroid medium.
Mix 20 µL of the cell suspension with 20 µL of trypan blue in a 1.5 mL tube.
Apply 10 µL of the trypan blue-mixed cell suspension to a cell counting slide, and count the cell number using an automated cell counter.
Prepare 3.5 × 104 cells/mL (for use at 1,750 cells/50 µL/well) of the cell suspension with the Spheroid medium. (The preparation volume should be calculated based on the number of wells needed.)
Seed 50 µL of the cell suspension to each well of a 96-well V-bottom plate.
Note: Do not use the outermost wells because the medium in these wells is susceptible to evaporation.
Add 100–200 µL of D-PBS(-) to each of the outermost wells of the 96-well V-bottom plate.
Note: This step is important to prevent evaporation of the medium.
Place the 96-well V-bottom plate in a humidified incubator set at 37 °C with 5% CO2/95% air.
Note: A single spheroid will appear.
Day 1: HBPC/ci37 cell seeding
The seeding procedure for HBPC/ci37 cells is essentially the same as the above-described steps 1–9 and 11, except that the cell concentration for seeding should be set at 1.0 × 104 cells/mL (500 cells/50 µL/well).
Note: The cell suspension can be added directly to the wells where HASTR/ci35 cells exist. The medium change is not always necessary.
Day 2: HBMEC/ci18 cell seeding
The seeding procedure for HBMEC/ci18 cells is essentially the same as the above-described steps 1–9, except that the cell concentration for seeding should be set at 1.5 × 104 cells/mL (750 cells/50 µL/well).
Note: The cell suspension can be added directly to the wells where HASTR/ci35 and HBPC/ci37 cells exist. The medium change is not always necessary.
Place the 96-well V-bottom plate in a humidified incubator set at 37 °C with 5% CO2/95% air, and incubate it for 48 h.
Note: Spheroids can be kept in culture at least for 48–72 h after HBMEC/ci18 cells are seeded. The medium change is not always necessary during the culture period but may be carried out depending on your assays of interest.
Note: When conducting a cell localization assay, HASTR/ci35, HBPC/ci37, and HBMEC/ci18 cells can be dyed with something appropriate [e.g., CellTracker Orange CMTMR Dye (541/565 nm), Red-fluorescent Cytoplasmic Membrane Staining Kit (644/665 nm), and CellTracker Green CMFDA Dye (492/517 nm), respectively, as shown in Figure 3]. In each case, follow the original protocol provided for each product.
Figure 3. Localization of the human immortalized BBB cells in the hiMCS-BBB models. These images, which were captured under a confocal laser scanning microscope (FLUOVIEW FV3000, OLYMPUS, Tokyo, Japan), show localization of HASTR/ci35, HBPC/ci37, and HBMEC/ci18 cells in the hiMCS-BBB models. HASTR/ci35 cells are accumulated at the internal core of the model, over which HBPC/ci37 cells form a layer. At the outmost side of the spheroid, HBMEC/ci18 cells create a layer that functions as the BBB. The scale bar indicates 100 µm.
Permeability assay
Notes:
The series of assay procedures should be performed without stopping.
The procedure for permeability assays using Alexa Fluor 647-labeled MEM189 antibodies (MEM189) is shown below as an example. The underlined parts can be changed appropriately depending on the substance of interest (see Table 1).
Whenever transferring the spheroids, gently place the tip vertically into the bottom of the well or the tube to suck up the spheroids. Always use tips that have been cut at approximately 7 mm from the top of the thinner side so that the entrance hole has a diameter of around 1 mm, to prevent damage to the spheroids.
Table 1. A summary of experimental conditions used in our permeability assays
Substrate Final concentration Incubation
MEM189/13E4 10 µg/mL 180 min
Lucifer Yellow 5 µM 90 min
2-NBDG 100 µM 90 min
Rhodamine123 1 µM 90 min
Insulin 100 nM 120 min
Transferrin 100 nM 120 min
SLS peptide/DNP peptide 10 µM 60 min
For details, please refer to our previous papers (Kitamura et al., 2021, 2022).
Using a low binding 200 µL tip, transfer 10–20 spheroids from the 96-well V-bottom plate to a Protein LoBind 1.5 mL tube.
Carefully remove the excess supernatant using a pipette until a medium volume of approximately 15 µL remains. Then, allow the tube to stand before the spheroids sink completely to the bottom (Figure 4A).
Wash the spheroids with 500 µL of HBSS(+).
Carefully remove the supernatant using a pipette. Then add HBSS(+) containing MEM189 (f.c. 10 µg/mL) into the tube, until a final total volume of approximately 100 µL is reached.
After placing the tube horizontally to disperse the spheroids, incubate for 180 min at 37 °C or refrigerate at 4 °C (Figure 4B).
Wash the spheroids twice with 500 µL of ice-cold D-PBS(+) (see Recipe 5) as described in steps 2 and 3.
After carefully removing the supernatant using a pipette, incubate the spheroids with 500 µL of 4% PFA at room temperature for 10 min (fixation treatment).
Wash the spheroids twice with 500 µL of ice-cold D-PBS(+), as described in steps 2 and 3.
Using a low binding 200 µL tip, suck the spheroids together with the remaining D-PBS(+) (approximately 10–20 µL) from the tube.
Place a piece of parafilm (from which a square of 6–8 mm on a side has been removed) on a slide glass. The empty area is to provide a protected space for the spheroids to minimize damage (Figure 4C).
Figure 4. Reference images for the section “D. Permeability assay”. Image (A) indicates the amount (approximately 15 µL) of supernatant remaining in a Protein LoBind 1.5 mL tube after step 2. Image (B) shows the position of a Protein LoBind 1.5 mL tube placed horizontally on a table to disperse the spheroids as in step 5. Image (C) shows an example of a slide glass topped by a piece of parafilm with square windows cut out for holding antifade–spheroid mixture, as in steps 10 and 11.
After placing a drop of antifade reagent at the center of the empty square in the glass slide-mounted parafilm sheet, mix the spheroids with the antifade reagent and disperse them into the opening via gentle pipetting.
Place a cover glass on top of the slide and seal it with nail polish.
Note: To prevent damage to the spheroids, avoid pressing down on the cover glass too firmly.
Immediately detect the fluorescence by observing the spheroids under a confocal microscope (650/665 nm in case with Alexa Fluor 647-labeled MEM189) (Figure 5).
Figure 5. Permeability assay of anti-transferrin receptor antibody MEM189. These images show the representative results of the permeability assays performed using Alexa Fluor 647-labeled MEM189 (MEM189, 10 µg/mL) and its isotype control IgG (CTRL IgG, 10 µg/mL) conducted at 37 °C (RMT-active condition) or 4 °C (RMT-inactive condition). The blank views show spheroids incubated without any antibodies. The scale bar indicates 100 µm. An overview of MEM189 entering the spheroids is also shown.
Recipes
Note: All the complete medium prepared here should be stored at 4 °C before use. Please follow the storage guideline provided by each supplier.
AM (astrocyte medium)
Add N-2 supplement and FBS, which are included in the Astrocyte Medium kit, to the basal astrocyte medium.
Add penicillin-streptomycin at 1% (v/v) (e.g., Nacalai Tesque, as shown at No. 25 in the material section) to the above-prepared medium.
PM (pericyte medium)
Add FBS, PGS, and P/S solution, which are included in the Pericyte Medium kit, to the basal pericyte medium.
VascuLife medium
Add rh FGF-b, ascorbic acid, hydrocortisone, FBS, L-glutamine, rh IGF-1, rh EGF, rh VEGF, and heparin, all of which are included in the VascuLife VEGF Comp kit, to the VascuLife basal medium.
Add penicillin-streptomycin at 1% (v/v) (e.g., Nacalai Tesque, as shown in the material section at No. 25) to the above-prepared medium.
Note: Although we do not routinely use, gentamicin-amphotericin provided by the medium supplier may be alternatively used.
Spheroid medium
After adding 1.2 g of methyl cellulose (viscosity: 4,000 cP) and a stirring bar to a 100-mL flask, sterilize the flask in an autoclave.
Add 100 mL of VascuLife medium to the above-sterilized 100-mL flask.
Incubate the flask in a water bath set at 60 °C for 20 min.
Completely dissolve the methyl cellulose by rotating the stirring bar in the flask for an hour.
Aliquot 100 mL of the methyl cellulose solution into two 50-mL centrifuge tubes.
Centrifuge (2,500 × g) the two tubes at room temperature for 30 min.
Transfer the supernatant into a sterilized container. This solution is referred to as the methyl cellulose stock solution.
Prepare the Spheroid medium containing 0.48 mg/mL of methyl cellulose by mixing the methyl cellulose stock solution together with the VascuLife medium at a ratio of 1:24.
Note: To ensure spheroids with good reproducibility, use a freshly-prepared Spheroid medium whenever possible. The Spheroid medium should not be used if it is more than three weeks old. To create an additional supply of Spheroid medium, follow the procedure above starting from step h.
D-PBS(+)
Add D-PBS(+) preparation reagent (Ca, Mg solution) [1%(v/v)] to D-PBS(-).
Acknowledgments
This work was supported by grants from JSPS KAKENHI (19K07214, 22Kxxxxx), Eisai (Tokyo, Japan), Ono Pharmaceuticals (Osaka, Japan), the Mochida Memorial Foundation for Medical and Pharmaceutical Research (Tokyo, Japan), and partly by AMED under grant no. JP17be0304322h0001. The authors would like to express our sincere appreciation to Dr. Takafumi Komori (Eisai), Dr. Saki Izumi (Eisai), Dr. Yoshiyuki Yamaura (Ono Pharmaceuticals), and Dr. Ryo Ito (Ono Pharmaceuticals) for their kind supports. This protocol is essentially derived from Kitamura et al. (2022).
Competing interests
Conflict of interest statements related to research funds are provided in the acknowledgments section, and the model development method herein has been applied for a patent (No. 2020-007041). There is another related patent application (No. 2020-065670). The authors declare that they do not have any other conflicts of interest.
References
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4,466 | https://bio-protocol.org/en/bpdetail?id=4466&type=0 | # Bio-Protocol Content
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Evaluation of Urine Proteins by Capillary Electrophoresis
PN Paula F. Navarro *
LG Laura Gil *
SF Salceda Fernández-Barredo *
(*contributed equally to this work)
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4466 Views: 1128
Reviewed by: Manjula MummadisettiSaptashati Biswas Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Journal of veterinary diagnostic investigation 2021
Abstract
Capillary electrophoresis (CE) is a laboratory method usually used to separate proteins in body fluids such as serum, cerebrospinal fluid, or urine. Separation of proteins in urine can have clinical applications for evaluating samples from healthy dogs and dogs with proteinuria in a qualitative way, which would not be possible with gel electrophoresis. Other advantages of CE over gel electrophoresis in serum include the reduced separation time (2 min vs. 20 min in a gel), reduction of waste harmful to humans and the environment, and ability to obtain a curve without the need for additional staining. This protocol is divided into four steps. Firstly, urine needs to be prepared prior to dialysis. Secondly, urine needs to undergo dialysis to eliminate compounds that could interfere with separation, and to concentrate the urine. The third step is CE using specific equipment. The last step is to separate the fractions of the phoretograms obtained in the previous step. This method is mostly an automatized process, easily reproducible, and that can be performed in any laboratory, as a part of the diagnostic or follow-up of patients with renal disease.
Graphical abstract:
Keywords: Canine Capillary Electrophoresis Minicap Proteins Renal Sebia Urine
Background
Serum protein analysis by capillary electrophoresis (CE) is a well-established laboratory method used for the diagnosis and follow up of infectious, inflammatory, immune-mediated, and neoplastic conditions in human and veterinary medicine (Jenkins, 2009; Giordano and Paltrinieri, 2010). CE is one of the most frequent techniques used to separate serum proteins, as it is a simple, adaptable, and quick technique, and does not require a large sample amount. The CE laboratory technique is based on the separation of charged molecules by their electrophoretic mobility in an alkaline buffer at a specific pH. The separation occurs according to the electrolyte pH and electroosmotic flow, yielding different electrophoretic fractions (Osatinsky, 2007). In serum, the phoretogram is commonly divided into five different fractions, from low to high molecular weight and charge: albumin, alpha1 globulin, alpha2 globulin, beta globulin, and gamma globulin (Gay-Bellile et al., 2003; Tappin et al., 2011).
Recently, the analysis of proteins in urine by CE has proven to be a suitable method in human medicine to detect the presence of characteristic electrophoretic patterns in renal and extrarenal disorders, such as myelomas (Jenkins, 1997; Theodorescu et al., 2005; Mischak et al., 2010). Although quantitative proteinuria can only be assessed by calculation of the urine protein/creatinine ratio (UPC), electrophoretic techniques can be used as a qualitative method to assess the loss of proteins through the urine, as different patterns can be identified (Lees et al., 2005). CE associated with mass spectrophotometry techniques is also useful to identify peptide biomarkers associated with chronic kidney disease (Pelander et al., 2019). The use of urine to identify such abnormalities represents a great advantage over the use of blood, because urine can be collected in quantity, does not require trained staff for its collection, and urinary proteins remain stable for at least 3 days at 4ºC or 3 months at -20°C (Théron et al., 2017). They can provide information about kidney functionality earlier than blood biomarkers, such as SDMA or Cystatin C (Yalçin and Çetin, 2004; Pelander et al., 2019).
Comparison with other electrophoretic techniques that evaluate proteinuria could be challenging because the principle of migration is different. In sodium dodecyl sulfate agarose/polyacrylamide gel (SDS-AGE or SDS-PAGE) electrophoretic techniques, particle migration is only based on their molecular weight. Initially, it might be easier to identify proteins that migrate in the different phoretogram fractions (Yalçin and Çetin, 2004; Zini et al., 2004; Giori et al., 2011; Lavoue et al., 2015; Chacar et al., 2017; Hokamp et al., 2017). Nevertheless, the result of the technique presented in this manuscript is a profile, where abnormalities associated with protein excretions can be easily detected when compared against curves from healthy dogs and any other mammals.
The aim of this study is to establish a standardized protocol to prepare urine adequately, to evaluate the proteins in dog urine by CE on an instrument normally used for serum samples. It can be a useful tool to assess pathological proteinuria in dogs, alongside quantitative methods such as UPC.
Materials and Reagents
Ultrafiltration column 4 mL Vivaspin Turbo 4 10000 MWCO (Sartorius, Vivaspin Turbo 4, catalog number: VS04T02)
Eppendorfs 1.5 mL (Lambda, Eppendorf, catalog number: 1003/G)
Polystyrene tube for urine 12 mL (Lambda, catalog number: 301402)
10–200 μL tips (Lambda, catalog number: 18260)
Kit Minicap Protein (Sebia Hispania S. A., Sebia, catalog number: 2203). Storage temperature between 2 °C and 30 °C
Kit Urine Dialysis Capillarys (Sebia Hispania S.A., Sebia, catalog number: 2013). Storage temperature between 2 °C and 30 °C
Capiclean (Sebia Hispania S.A., Sebia, catalog number: 2058). Storage temperature between 2 °C and 30 °C
Reconstituted buffer for 4 samples (see Recipes)
Equipment
Minicap + Phoresis system (Sebia Hispania, S.A., catalog number Minicap: 1232; Phoresis. Software version 8.6.3)
Centrifuge Nahita 2650 (Nahita, Nahita 2650, catalog number: 200352650000)
Software
Minicap computer program (Sebia Hispania S.A. www.sebia.com)
Procedure
Preparation of the urine prior to dialysis
Centrifuge 10 mL of urine in a rounded bottom tube at 1,342 × g for 10 min. Identify the tube.
Label the Eppendorf tubes. Transfer and aliquot supernatants obtained in 1.5 mL Eppendorf tubes with a Pasteur pipette. Aliquot a minimum of 4 mL, at 1 mL per Eppendorf. Freeze samples at -20 °C until dialysis.
Note: As many supernatants as possible should be frozen, in case the dialysis process needs to be repeated. Additionally, 8 mL would be ideal, in case electrophoresis needs to be repeated.
Dialysis and concentration of the samples prior to capillary electrophoresis
Note: Urine is dialyzed and concentrated using 10 kDa molecular weight cut-off ultrafiltration columns, which are double membranous. This step is necessary not only to concentrate proteins, but also to avoid artifacts from contaminants (Figure 1).
Figure 1. Different parts of an ultrafiltration colums tube 4 mL capacity. The concentration membrane where proteins are retained, and waste deposit where disposals are collected.
Thaw 4 mL of urine supernatant from each individual to study at room temperature, and centrifuge the Eppendorf tubes at 1,609 × g for 10 min.
Transfer this sample to a 4-mL ultrafiltration column. Identify the ultrafiltration columns.
Note: Columns with 15 mL of capacity are available. In this work, due to the difficulty obtaining a large amount of urine, 4-mL columns are preferred.
Centrifuge the ultrafiltration column with the urine at 1,878 × g for 25 min, or until a maximum volume of 500 μL is left in the column.
Simultaneously, prepare a solution containing 50% distilled water and 50% dialysis buffer (see table of materials) in a sterile container. Use two 10-mL syringes to prepare the solution. Mix this solution prior to its use.
Discard the urine that emerges at the bottom of the column (waste deposit, Figure 1). With a Pasteur pipette, add the washing solution prepared in point 4 to the ultrafiltration column (concentration membrane, Figure 1) with the urine, up to the 4 mL mark.
Centrifuge the column with the urine and the buffer solution at 1,878 × g for 20 min, or until a maximum of 400–500 μL are left in the column.
Homogenize the dialyzed urine with a fine tip micropipette (maximum capacity: 200 mL), and transfer the dialyzed urine to an Eppendorf.
Note: The capillary electrophoresis equipment (see table of materials) requires a minimum of 100 μL.
Capillary electrophoresis of dialyzed samples
Start the electrophoretic computer program provided by the equipment manufacturer (Phoresis software version 8.6.3). Make sure that the analytical equipment is on too. Enter the program password: a pop-up window will appear and ask to continue with the current technique (protein) or change it to urine. You must change the work mode to urine. Make sure to check reagents and waste deposit before running the samples. A notification will appear on screen when the equipment is ready to process the samples.
Note: This can be done during the dialysis and concentration of the samples, since the start-up process of the analytical equipment takes 15 min.
Once the equipment is ready, insert the Eppendorf tubes with the dialyzed and concentrated urine into the electrophoresis instrument. Insert samples in pairs to reduce reagent wastage. As soon as the samples are inside, the electrophoretic instrument starts automatically. Do not open the instrument’s door until the CE process is finished.
Note: The analytical instrument can process 26 samples at the same time, and takes 10 min per sample.
Fraction separation
Phoretograms appear on the screen once the CE process is complete. Identify each phoretogram in the program with the patient’s number. Manually divide the phoretogram into five fractions—although the program establishes predetermined divisions, they are not designed for dog urine (Figure 2).
Note: The computer program allows manipulations of the profile, such as changing the size or superposition of curves, to be done manually on the phoretograms obtained (Video 1).
Figure 2. Final result of capillary electrophoresis in urine. Phoretogram with the five divisions indicated, from a healthy 2 year entire female Border Collie. Health check was assessed by hematology, biochemistry, serum phoretogram, and complete urinalysis.
Video 1. Video of how a phoretogram can be divided and how quality control serum (yellow) is superimposed to the study curve (pink).
Recipes
Reconstituted buffer for 4 samples
Reagent Final concentration Amount
Dialysis Buffer n/a 8 mL
Distilled H2O n/a 2 mL
Total 16 mL
Data analysis
The final result of CE in urine is a profile that represents the different protein fractions contained in dog urine, which varies depending on the amount of protein excreted.
The phoretogram was divided into five fractions based on serum CE. The different fractions that are obtained in each profile are F1—corresponding to albumin, F2—corresponding to alpha1 globulin, F3—corresponding to alpha2 globulin, F4—corresponding to beta globulin, and F5—corresponding to gamma globulin. These fractions were determined by superimposing a normal canine serum sample, diluted 1:49, and used as quality control, over the electrophoretic urine samples (Figure 3). Protein fractions were verified and, if necessary, corrected by visual inspection of the electrophoretogram.
Figure 3. Normal canine diluted serum (yellow) superimposed on the study curve (blue). The phoretogram is divided into five fractions (F1–F5) according to the diluted canine serum.
Notes
As quality control material, frozen aliquoted serum from a healthy dog was included, diluted 1:49 in running buffer, and migrated prior to any run and in each batch. Internal verification experiments were also performed; within-run and between-run experiments were performed, using urine from a healthy dog. This urine was stored at 4°C during the entire experiment, and dialyzed and concentrated for every run following the manufacturer’s protocol. Three migrations per sample and day (repeatability) were made for five consecutive days (reproducibility), with the objective of calculating the CV for each of the fractions of the urinary proteinogram (Table 1). The CV results were 3.38%, 3.84%, 7.25%, 4.43%, and 7.31% for F1, F2, F3, F4, and F5, respectively. In the between-run experiment, the CV results were 4.78%, 5.17%, 10.0%, 6.09%, and 9.66% for F1, F2, F3, F4, and F5, respectively (Figure 4).
Table 1. Daily coefficient of variation and total coefficient of variation obtained from repeatability (R1, R2, and R3) and reproducibility (Days 1–5) experiments from each fraction (F1–F5).
F1 R1(%) R2(%) R3(%) CVD(%) CVT(%)
Day 1 54 53.2 54 0.86 4.77
Day 2 45.3 49.8 55 9.70
Day 3 54.2 52.1 53.5 2.00
Day 4 53.5 53.4 51.3 2.35
Day 5 54.8 53.2 55.3 2.01
F2 R1(%) R2(%) R3(%) CVD(%) CVT(%)
Día 1 9.6 9.6 9.7 0.60 5.72
Día 2 11.2 11.2 9.6 8.66
Día 3 10.5 9.9 9.4 5.54
Día 4 10.9 10.4 10.1 3.86
Día 5 10.1 10 10.1 0.57
F3 R1(%) R2(%) R3(%) CVD(%) CVT(%)
Día 1 5.8 5.7 5.2 5.77 10
Día 2 6.8 5.7 5.8 9.97
Día 3 5.2 5.6 4.9 6.71
Día 4 5.1 5 5.2 1.96
Día 5 6.6 5.9 5.2 11.86
F4 R1(%) R2(%) R3(%) CVD(%) CVT(%)
Día 1 20.6 21 21 1.10 6.09
Día 2 23.3 22.2 20 7.69
Día 3 20.3 22.2 22.1 4.96
Día 4 19.5 21.2 21.2 4.75
Día 5 18.6 20 19.3 3.62
F5 R1(%) R2(%) R3(%) CVD(%) CVT(%)
Día 1 10 10.5 10.1 2.59 9.66
Día 2 13.4 11.1 9.6 16.83
Día 3 9.8 10.2 10.1 2.07
Día 4 11 10 12.2 9.95
Día 5 9.9 10.9 10.1 5.13
CVD= Daily Coeficient of Variation; CVT= Total Coeficient of Variation; R= Repetition
The limit of detection (LOD) was determined with the urine sample of the same healthy dog. Briefly, 1:2, 1:4, 1:8, and 1:16 dilutions of the dialyzed urine in running buffer were run. The LOD was selected as the last dilution with an electrophoretic pattern equal to the undiluted urine, which was 1:8. The sensitivity obtained in the LOD experiment was 2.1 mg/L, and the initial sample protein concentration was 17.5 mg/L.
Figure 4. Reproducibility and repeatability experiment using a urine from a healthy dog during five consecutive days. Urine from a healthy dog should be stored at 4 °C, to be dialyzed and concentrated prior to every run.
Acknowledgments
This work was supported by Universidad Católica de Valencia San Vicente Mártir grant (UCV 2016-226-001) (to LG).
This work has been adapted from previous work (Navarro et al., 2021).
Competing interests
The authors have no competing interests to disclose.
Ethics
All experimental procedures have been approved by the research and ethics committee of the Universidad Católica de Valencia San Vicente Mártir (Valencia, Spain; UCV 2017-2018-33).
References
Chacar, F., Kogika, M., Sanches, T. R., Caragelasco, D., Martorelli, C., Rodrigues, C., Capcha, J. M. C., Chew, D. and Andrade, L. (2017). Urinary Tamm-Horsfall protein, albumin, vitamin D-binding protein, and retinol-binding protein as early biomarkers of chronic kidney disease in dogs. Physiol Rep 5(11): e13262.
Gay-Bellile, C., Bengoufa, D., Houze, P., Le Carrer, D., Benlakehal, M., Bousquet, B., Gourmel, B. and Le Bricon, T. (2003). Automated multicapillary electrophoresis for analysis of human serum proteins. Clin Chem 49(11): 1909-1915.
Giordano, A. and Paltrinieri, S. (2010). Interpretation of capillary zone electrophoresis compared with cellulose acetate and agarose gel electrophoresis: reference intervals and diagnostic efficiency in dogs and cats. Vet Clin Pathol 39(4): 464-473.
Giori, L., Tricomi, F. M., Zatelli, A., Roura, X. and Paltrinieri, S. (2011). High-resolution gel electrophoresis and sodium dodecyl sulphate-agarose gel electrophoresis on urine samples for qualitative analysis of proteinuria in dogs. J Vet Diagn Invest 23(4): 682-690.
Hokamp, J. A., Leidy, S. A., Gaynanova, I., Cianciolo, R. E. and Nabity, M. B. (2018). Correlation of electrophoretic urine protein banding patterns with severity of renal damage in dogs with proteinuric chronic kidney disease. Vet Clin Pathol 47(3): 425-434.
Jenkins, M. A. (1997). Clinical application of capillary electrophoresis to unconcentrated human urine proteins. Electrophoresis 18(10): 1842-1846.
Jenkins, M. A. (2009). Serum and urine electrophoresis for detection and identification of monoclonal proteins. Clin Biochem Rev 30(3): 119-122.
Lavoue, R., Trumel, C., Smets, P. M., Braun, J. P., Aresu, L., Daminet, S., Concordet, D., Palanche, F. and Peeters, D. (2015). Characterization of Proteinuria in Dogue de Bordeaux Dogs, a Breed Predisposed to a Familial Glomerulonephropathy: A Retrospective Study. PLoS One 10(7): e0133311.
Lees, G. E., Brown, S. A., Elliott, J., Grauer, G. E., Vaden, S. L. and American College of Veterinary Internal, M. (2005). Assessment and management of proteinuria in dogs and cats: 2004 ACVIM Forum Consensus Statement (small animal). J Vet Intern Med 19(3): 377-385.
Mischak, H., Delles, C., Klein, J. and Schanstra, J. P. (2010). Urinary proteomics based on capillary electrophoresis-coupled mass spectrometry in kidney disease: discovery and validation of biomarkers, and clinical application. Adv Chronic Kidney Dis 17(6): 493-506.
Navarro, P. F., Gil, L., Martin, G. and Fernandez-Barredo, S. (2021). Reference intervals for electrophoretograms obtained by capillary electrophoresis of dialyzed urine from healthy dogs. J Vet Diagn Invest 33(4): 632-639.
Osatinsky, R. (2007). ¿Qué es la electrophoresis capilar? [What is capillary electrophoresis?] Bioquímica y patología clínica. 71: 60-66 Spanish.
Pelander, L., Brunchault, V., Buffin-Meyer, B., Klein, J., Breuil, B., Zurbig, P., Magalhaes, P., Mullen, W., Elliott, J., Syme, H., et al. (2019). Urinary peptidome analyses for the diagnosis of chronic kidney disease in dogs. Vet J 249: 73-79.
Tappin, S. W., Taylor, S. S., Tasker, S., Dodkin, S. J., Papasouliotis, K. and Murphy, K. F. (2011). Serum protein electrophoresis in 147 dogs. Vet Rec 168(17): 456.
Theodorescu, D., Fliser, D., Wittke, S., Mischak, H., Krebs, R., Walden, M., Ross, M., Eltze, E., Bettendorf, O., Wulfing, C., et al. (2005). Pilot study of capillary electrophoresis coupled to mass spectrometry as a tool to define potential prostate cancer biomarkers in urine. Electrophoresis 26(14): 2797-2808.
Théron, M. L., Piane, L., Lucarelli, L., Henrion, R., Layssol-Lamour, C., Palanche, F., Concordet, D., Braun, J. D., Trumel, C. and Lavoue, R. (2017). Effects of storage conditions on results for quantitative and qualitative evaluation of proteins in canine urine. Am J Vet Res 78(8): 990-999.
Yalcin, A. and Çetin, M. (2004). Electrophoretic separation of urine proteins of healthy dogs and dogs with nephropathy and detection of some urine proteins of dogs using immunoblotting. Revue de Medecine Veterinaire 155: 104-112.
Zini, E., Bonfanti, U. and Zatelli, A. (2004). Diagnostic relevance of qualitative proteinuria evaluated by use of sodium dodecyl sulfate-agarose gel electrophoresis and comparison with renal histologic findings in dogs. Am J Vet Res 65(7): 964-971.
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Purification and Immunostaining of Mouse Ependymal Ciliary Shafts
KH Kai Hao
XZ Xueliang Zhu
Xiumin Yan
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4467 Views: 1803
Reviewed by: David PaulYoko BekkuNona Farbehi
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Original Research Article:
The authors used this protocol in Nature Communications Nov 2021
Abstract
Cilia and flagella are microtubule-based hair-like organelles protruding from the surface of most eukaryotic cells, and play essential roles in cell locomotion, left-right asymmetry, embryo development, and tissue homeostasis. With isolated cilia and flagella, great progress has been made in understanding the composition, structure, and function of cilia. However, the current cilia/flagella isolation methods are deficient in the integrity or productivity of purified cilia when applied to mammalian motile cilia. Here, we describe a new protocol that isolates cilia shafts from mouse ependymal cells, by horizontal shear force and mild detergent. This method enables the production of virtually integral cilia with high yields and less cell body contamination. It is suitable for immunostaining, puromycin labeling assay, and proximity ligation assay of mammalian motile cilia.
Graphical abstract:
Keywords: Ependymal cells Motile cilia Ciliary shaft purification Immunostaining Mammalian
Background
Multiple cilia/flagella isolation methods, including pH-shock, calcium-shock, dibucaine treatment, and mechanical procedures (e.g., peel-off, and slide-pull), have been developed in various organisms (Witman et al., 1972, 1978, 1986; Adoutte et al., 1980; Mitchell et al., 2009). The pH- and calcium-shock methods were first created to purify cilia from Euglena and Tetrahymena, respectively (Gibbons, 1965; Rosenbaum and Child, 1967). Later, the two methods became the most used cilia/flagella purification methods in protozoa. In mammals, mechanical peel-off or slide-pull approaches have been used to isolate primary cilia from cultured cells, such as MDCK (Madin-Darby canine kidney) cells, normal mouse cholangiocytes (NMCs), and normal rat cholangiocytes (NRCs) (Huang et al., 2006; Kiesel et al., 2020). The calcium-shock method combined with mechanical agitation is used to separate motile cilia from rabbit oviduct, pig trachea, and primary cultured mouse ependymal cells (mEPCs) (Anderson, 1974; Hastie et al., 1986; Zheng et al., 2019). It is also used to isolate primary cilia from rat olfactory cilia and inner medullary collecting duct (IMCD3) cells (Mayer et al., 2008; Ishikawa et al., 2012). The ciliary protein composition and high-resolution ciliary ultrastructure have been well studied using these methods in purified cilia/flagella. However, these procedures usually cause cilia membrane damage and ignore the physiological activity of isolated cilia, thus hindering further exploration of cilia biology.
Here, we report a protocol of cilia isolation, which is improved from the calcium-shock combined mechanical agitation method. To maintain the integrity of isolated cilia and reduce cytoplasmic contamination, we decreased the detergent concentration in the deciliation buffer and replaced the vortex with horizontal shear force. With this method, we obtained a sufficient yield of motile cilia for immunostaining, puromycin labeling, and proximity ligation assays. As an example of its application, we applied this procedure to purify mouse ependymal cilia to verify ciliary RNA local translation. In addition, this method can also be used to purify motile cilia from mouse brain lateral ventricle.
Materials and Reagents
0.22 μm filter (Millipore, catalog number: SLGPR33RB)
75 cm2 Flask (Corning, catalog number: 430641)
15 mL tube (Falcon, catalog number: 352095)
12 mm diameter circle coverslips (Marienfeld, catalog number: MAR0111520)
Glass slides (Premiere, catalog number: 9308W)
24-well plate (Costar, catalog number: 3524)
15 cm Petri dish (Corning, catalog number: 430599)
Filter paper (GE, catalog number: 10311611)
Parafilm (Bemis, catalog number: PM-996)
Milli-Q water
Fibronectin (1 mg/mL) (Sigma-Aldrich, catalog number: FC010), store at 4°C
Papain (Worthington Biochemical Corporation, LS003126), store at 4°C
DMEM (ThermoFisher Scientific, GibcoTM, catalog number:12430054), store at 4°C
Primocin (50 mg/mL) (InvivoGen, ant-pm-2), store at -20°C
Fetal bovine serum (Ausbian, VS500T), store at -20°C
Poly-L-lysine hydrobromide (Sigma-Aldrich, catalog number: P1399), store the powder at -20°C.
Note: Sterilize the stock solution (100 mg/mL Poly-L-lysine in Milli-Q water) with a 0.22 μm filter, and store it in aliquots at -20°C.
Trition X-100 (Sangon Biotech, catalog number: A110694)
Tween 20 (Sangon Biotech, catalog number: A100777)
Paraformaldehyde (PFA) (Sigma-Aldrich, catalog number: P6148), store the powder at 4°C
Bovine Serum Albumin (BSA) (Sigma-Aldrich, catalog number: A3912), store the powder at 4°C
Mouse anti-Acetylated Tubulin (Sigma-Aldrich, catalog number: T6793), store at 4°C
Rabbit anti-Cep290 (home-made) (Zhao et al., 2021), store at -20°C
Guinea pig anti-Odf2 (home-made) (Zhao et al., 2019), store at -20°C
Donkey anti-mouse IgG conjugated with Alexa Fluor 488 (ThermoFisher Scientific, catalog number: A-21202), long-term storage at -80°C, short-term storage at 4°C
Donkey anti-rabbit IgG conjugated with Cy3 (Jackson ImmunoResearch, catalog number: 711-165-152), long-term storage at -80°C, short-term storage at 4°C
Donkey anti-guinea pig IgG conjugated with Alexa Fluor 647 (Jackson ImmunoResearch, catalog number: 706-605-148), long-term storage at -80°C, short-term storage at 4°C
ProLong Diamond Antifade Mountant (ThermoFisher Scientific, catalog number: P36970), store at 4°C
Immersion oil (Lecia microsystem, catalog number: 12847995)
PBS (see Recipes), store at 4°C
Dissection buffer (see Recipes), store at 4°C
Enzymatic digestion buffer (see Recipes), freshly prepared
mEPC culture medium (see Recipes), store at 4°C
Starvation culture medium (see Recipes), store at 4°C
Deciliation buffer (see Recipes), store at 4°C
4% PFA (see Recipes)
TBST (10×) (see Recipes)
Blocking buffer (see Recipes), stored in aliquots at -20°C
Equipment
Milli-Q (Millipore, model: Advantage A10)
Sharp tweezer (Dumont, catalog number: 0208-5/45-PO)
Tweezer (Dumont, catalog number: 0203-5/15-PO)
Horizontal shaker (Zhichu, model: ZQZY-AS9)
Superspeed centrifuge (ThermoFisher Scientific, model: Sorvall LYNX 6000, catalog number:75006590)
Swinging bucket rotor (ThermoFisher Scientific, model: BIOFlexTM HC, catalog number: 75003000)
Confocal microscopy (Leica, model: TCS SP8 WLL system equipped with a 63×/1.4 oil immersion objective)
Procedure
Preparation before ciliary shaft purification
Grow and maintain mouse ependymal cells (mEPCs) in a 75 cm2 flask (Hao et al., 2021).
Add 6 mL of fibronectin (10 μg/mL in PBS) to a 75 cm2 flask, and incubate at 37°C for 24 h to coat the flask the day before culture.
Dissect the telencephala from five C57BL/6 mouse pups at postnatal day 0 to 1 (P0–P1) in ice-cold dissection buffer, and remove the hippocampus, the cerebellum, the choroid plexus, the olfactory bulb, and meninges with sharp tweezers.
Transfer the dissected telencephala into a 15-mL tube, and digest them with 10 mL of freshly prepared enzymatic digestion buffer at 37°C for 30 min.
Dissociate cells carefully by pipetting ten times with a 5-mL pipette, and collect cells by centrifugation at 400 × g at room temperature for 5 min.
Resuspend cells with mEPC culture medium, and seed them into a 75-cm2 fibronectin-coated flask.
Shake off and remove neurons one day after seeding.
When cells are confluent, rinse the cells with PBS, and add 10 mL of starvation culture medium to induce differentiation.
Harvest cells after culturing for ten days in starvation culture medium.
Note: The ratio of multiciliated cells should be approximately 50%, when harvested on day 10 of serum starvation (Figure 1).
Figure 1. Primary cultured mouse ependymal cells. Acetylated tubulin (Ac-tub) decorates ciliary axonemes. Zo-1 and DAPI label tight junctions and nuclei, respectively. Scale bar, 25 μm.
Coat coverslips with poly-L-lysine, one day before ciliary shaft purification.
Place 12 sterilized coverslips in a 24-well plate, with one coverslip per well.
Rinse coverslips three times, with 500 μL of PBS per well.
Add 500 μL of poly-L-lysine in PBS (100 ng/μL) to each well, and incubate at 37°C for 24 h.
Ciliary shaft purification
Wash mEPCs twice with 6 mL of ice-cold PBS, and twice with 6 mL of ice-cold deciliation buffer quickly.
Into the flask, add 9 mL of ice-cold deciliation buffer containing 0.01% Triton X-100.
Fix the flask on a horizontal shaker with a sticky green rubber base (Figure 2).
Figure 2. Representative image of an adhered flask on a horizontal shaker.
Immediately shake at 300 rpm and 37°C for 15 min, to detach cilia from the base of the transition zone (Video 1).
Video 1. Ciliary shaft purification using shear force.
Transfer the supernatant containing ciliary shafts into a 15-mL tube.
Centrifuge horizontally in a swinging bucket rotor (BIOFlexTM HC) at 600 × g and 4°C for 10 min to remove cell debris.
Rinse the poly-L-lysine coated coverslips three times with 500 μL of PBS per well.
Aliquot the supernatant into 12 wells with poly-L-lysine coated coverslips in equal amounts (720 μL of supernatant per well).
Place the 24-well plate in a swinging bucket rotor (BIOFlexTM HC).
Centrifuge horizontally at 4,200 × g and 4°C for 10 min.
Wash the coverslips once with 500 μL of PBS per well.
Now, the purified ciliary shafts are ready for immunostaining, puromycin labeling, and proximity ligation assays.
Note: It is recommended to use immunofluorescence staining to examine the quality and integrity of cilia. The antibodies against Arl13b (a ciliary membrane protein) and acetylated tubulin are for the quality and integrity of ciliary membrane and axonemes, respectively. The antibodies against Cep290 (a transition zone protein) and Odf2 (a basal body protein) are used to check if the purified ciliary shafts contain the transition and lack the basal body.
Immunostaining of purified ciliary shafts
Fix the ciliary shafts with 500 μL of 4% PFA per well at room temperature for 15 min.
Briefly wash with 500 μL of PBS per well.
Permeabilize with 500 μL of 0.5% Triton X-100 in PBS per well for 15 min.
Briefly wash with 500 μL of PBS per well.
Incubate with 500 μL of blocking buffer (4% BSA in TBST) per well at room temperature for 1 h.
Make a humidity chamber (Figure 3).
Wrap the outer surface of a 15 cm Petri dish with tin foil, to protect the sample from light. Place the shiny side of the tinfoil facing out of the humidity chamber.
Place a water-soaked filter paper into the Petri dish.
Place a piece of parafilm on the filter paper.
Figure 3. Representative image of a humidity chamber. Tinfoil, filter paper, parafilm, and coverslip are noted. Filter paper and parafilm are outlined by purple and blue dashed lines, respectively.
Using a tweezer, transfer the coverslips onto the parafilm. Place the side with ciliary shafts upward.
Incubate each coverslip with 90 μL of primary antibodies diluted in blocking buffer at 4°C overnight.
Wash with 200 μL of blocking buffer three times for 5 min each.
Incubate each coverslip with 90 μL of secondary antibodies diluted in blocking buffer at room temperature for 1 h.
Wash with 200 μL of blocking buffer three times for 5 min each.
Briefly wash with 200 μL of Milli-Q water per coverslip.
Drop 10 μL of mounting medium (ProLong Diamond Antifade Mountant) per slide.
Remove excess Milli-Q water from coverslips with a filter paper.
Mount the coverslips onto the slides immediately (Cao et al., 2014).
Dry the sample at room temperature for at least 2 h in the dark, and store it at 4°C.
Imaging of purified ciliary shafts by confocal microscope
Confocal microscopy images were taken on a Leica TCS SP8 WLL system with a 63×/1.4 oil immersion objective. Immersion oil with a refractive index of 1.518 was used to minimize spherical aberrations. Scan speed was 400 Hz, line average was 3, and optical sections were captured at 0.5-μm intervals along the z-axis. A typical image is shown in Figure 4. For extra fluorescence images, please refer to the supplementary Figure 2C of the original research article (Hao et al., 2021).
Measurement parameters for confocal imaging are in Table 1, and proper ciliary shaft density for fluorescence imaging is shown in Figure 4.
Table 1. Filters and measurements parameters
Filter Excitation Emission
Laser (nm) Intensity Detector Wavelength (nm) Gain
Alexa Fluor 488 498 1.5% HyD standard mode 508–542 81%
Cy3 550 7% HyD standard mode 560–620 100%
Alexa Fluor 647 650 2% HyD standard mode 660–720 80%
Figure 4. Typical images of isolated ciliary shafts. Purified ciliary shafts from one 75 cm2 flask of mPECs were equally spun onto 12 pieces of 12-mm coverslips. Ac-tub decorates ciliary axonemes. Cep290 marks the transition zone. Scale bar, 25 μm.
Recipes
PBS, pH 7.4
Reagent Final concentration Amount
NaCl 137 mM 8 g
KCl 2.7 mM 0.2 g
KH2PO4 2 mM 0.24 g
Na2HPO4 10 mM 1.44 g
Milli-Q water n/a 1,000 mL
Total n/a 1,000 mL
mEPC culture medium
Reagent Final concentration Amount
Primocin 50 μg/mL 500 μL
DMEM n/a 500 mL
FBS 10% 50 mL
Total n/a 500 mL
Starvation culture medium
Reagent Final concentration Amount
Primocin 50 μg/mL 500 μL
DMEM n/a 500 mL
Total n/a 500 mL
Dissection buffer, pH 7.4
Reagent Final concentration Amount
NaCl 161 mM 9.4 g
KCl 5 mM 0.37 g
MgSO4 1 mM 0.12 g
CaCl2 4.7 mM 0.41 g
HEPES 5 mM 1.2 g
Glucose 5.5 mM 0.99 g
Milli-Q water
n/a 1,000 mL
T0tal
n/a 1,000 mL
Enzymatic digestion buffer
Reagent Final concentration Amount
EDTA (50mM stock) 0.5 mM 100 μL
CaCl2 (100mM stock) 1 mM 100 μL
NaOH (1M stock) 1.5 mM 15 μL
Papain 10 U/mL 100 U
Dissection buffer
n/a 10 mL
Total
n/a 10 mL
Deciliation buffer, pH 5.5
Reagent Final concentration Amount
Sucrose 250 mM 85.575 g
CaCl2 20 mM 2.22 g
Pipes 20 mM 6.047 g
Milli-Q water n/a 1,000 mL
Total n/a 1,000 mL
Adjust the pH with saturated HCl. Filter-sterilize with a 0.22 μm filter, and store at 4°C.
4% PFA
Reagent Final concentration Amount
Paraformaldehyde 4% 4 g
PBS n/a 100 mL
Total n/a 100 mL
Heat the solution to 60°C with stirring, to accelerate the dissolution of PFA.
Freshly prepare, and filter-sterilize with a 0.22 μm filter before use.
TBST (10×), pH 7.5
Reagent Final concentration Amount
NaCl 1.5 M 88 g
Tris base 0.5 M 60 g
Tween 20 0.5% 5 mL
Milli-Q water n/a 1,000 mL
Total n/a 1,000 mL
Heat the solution to 60°C with stirring, to accelerate the dissolution of solutes.
Blocking buffer
Reagent Final concentration Amount
BSA 4% 4 g
TBST (10×) 1× 10 mL
Milli-Q wate n/a 90 mL
Total n/a 100 mL
Filter-sterilize with a 0.22 μm filter, and store at -20°C.
Acknowledgments
Thanks to the financial support from National Natural Science Foundation of China (31991192 for X.Z. and 31970652 for X.Y.), National Key R&D Program of China (2017YFA0503500 for X.Z. and X.Y.), and Chinese Academy of Sciences (XDB19020102 for X.Z.). Thanks to the work of Dr. Anderson (University of Texas Southwestern Medical School) for the original buffer recipe for this ciliary shaft purification method. Thanks to the work of Dr. Yawen Chen (Shanghai Institute of Biochemistry and Cell Biology), which adapted Anderson’s method to primary cultured mEPCs.
Competing interests
The authors declare no competing interests.
Ethics
Experiments involving mouse tissues were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of CAS Center for Excellence in molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese academy of Sciences. The approval ID is SIBCB-S302-2110-037, and the validity period is from Aug 2nd 2021 to Aug 1st 2023.
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Category
Cell Biology > Organelle isolation
Molecular Biology > RNA > mRNA translation
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4,468 | https://bio-protocol.org/en/bpdetail?id=4468&type=0 | # Bio-Protocol Content
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Peer-reviewed
Immunohistochemistry of Immune Cells and Cells Bound to in vivo Administered Antibodies in Liver, Lung, Pancreas, and Colon of B6/lpr Mice
KA Kieran Adam
AM Adam Mor
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4468 Views: 2202
Reviewed by: Xiaoyi ZhengXiaoyu LiuEmilie Besnard
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Original Research Article:
The authors used this protocol in PLOS ONE Feb 2021
Abstract
Employing a novel mouse model of immune related adverse events (irAEs) induced by combination of anti-PD1 and anti-CTLA-4 antibodies, we visualized immune infiltration into the liver, lung, pancreas, and colon. Here, we describe the avidin-biotin conjugate (ABC) method used to stain T cells (CD4 and CD8), B cells (CD19), macrophages (F4/80), and cells bound by the in vivo administered rat anti-mouse antibodies for chromogenic immunohistochemistry (IHC). Using a biotinylated goat anti-rat antibody, we detected the localization of cells bound to the in vivo antibodies for PD-1 and CTLA-4. IHC has advantages over other techniques, namely antibody availability, resistance to photobleaching, and greater sensitivity. Additionally, detection and localization of in vivo antibodies can be used in mice models to infer their therapeutic efficacy, stability, and function.
Graphical abstract:
Keywords: Immune checkpoint blockade Immunohistochemistry Mice models Immune related Adverse Events (irAEs) Programmed cell Death protein 1 (PD-1) Cytotoxic T Lymphocyte Associated protein 4 (CTLA-4) T cells Antibody
Background
The last decade has seen the approval of several immune checkpoint blockade (ICB) antibodies in various cancers, which has improved patient survival. However, patients that respond to these ICB develop toxicities known as irAEs. We have previously developed a novel mouse model of irAEs in B6/lpr mice, that developed multiorgan toxicities with immune infiltration, when given a combination of anti-PD-1 and anti-CTLA-4 (Adam et al., 2021). Mice were injected with 200 μg of anti-PD1 (BioXCell BE0146), and 100 μg of CTLA-4 (BioXcell BE0131) antibodies intraperitoneally twice a week for 6 weeks. Mice were sacrificed at endpoint, and tissue collected for IHC, to assess the cellular landscape. The injected ICB antibodies derived from rat were visualized in the tissue using a goat anti-rat that recognized the fragment crystallizable (Fc) portion of the IgG rat antibody. This method of detection could be used to evaluate ICB antibodies for toxicity in mice models. Although there are numerous other techniques for visualization or detection of antibodies (de Boer et al., 2015; Mestel, 2017; Knight et al., 2019; Wen et al., 2021), the limitations are the access to large and expensive microscopes, CT scanner, or MRI, which may be inaccessible to many laboratories. Our method is advantageous due to a relatively low expense, accessible selection of conjugated antibodies, and flexibility with IHC kits.
Materials and Reagents
Tissue Tek Slide Staining Dish (Fisher, catalog number: NC0731403)
Slide Holder (Fisher, catalog number: NC9697666
10 mL pre-filled flush syringe saline (NaCl 0.9%) (BD, catalog number: 306575)
25G × ¾’’ blood collection set (BD, catalog number: 367285)
FisherbrandTM ColorFrostTM Plus Microscope Slides (Fisher, catalog number: 12-550-17)
FisherbrandTM Standard Disposable Transfer Pipettes, Nongraduated (Fisher, catalog number: 13-711-7M)
Goat anti-rat IgG antibody (H+L), biotinylated (Vector, catalog number: BA-9400)
Goat anti-rabbit IgG antibody (H+L), biotinylated (Vector, catalog number: BA-1000)
VECTASTAIN(r) Elite ABC-HRP Kit, peroxidase (Standard) (Vector, catalog number: PK-6100)
Dako liquid 3,3'-diaminobenzidine (DAB) and substrate (DAKO, catalog number: K3468)
CD4 (D7D2Z) (CST, catalog number: 25229)
CD8a (D4W2Z) (CST, catalog number: 98941)
CD19 (D4V4B) (CST, catalog number: 90176)
F4/80 (BM8) (Invitrogen, catalog number: 144801)
Xylene (Sigma, catalog number: 534056)
10× Citrate buffer pH 6.0 (Novus Biologicals, catalog number: NB900-62075)
Triton X-100 (Sigma, catalog number: X100)
Ethanol (Fisher Bioreagents, catalog number: BP2818100)
Hydrogen peroxide (BioRad, catalog number: BUF017B)
Hematoxylin counterstain (Vector, catalog number: H-3401-500)
Proteinase K (abcam, catalog number: ab64220)
10× PBS (Phosphate Buffered Saline) (Thermo Scientific, catalog number: AAJ75889K8)
Normal goat serum blocking solution (Vector, catalog number: S-1000-20)
FisherbrandTM SuperfrostTM ExcellTM Microscope Slides (Fisher, catalog number: 22-037-247)
Fisher ChemicalTM PermountTM Mounting Medium (Fisher, catalog number: SP15-100)
Dako Antibody Diluent (Agilent, catalog number: S0809)
Deionized water
B6/lpr (Jackson Laboratory, catalog number: 000482)
10% Neutral Buffered Formalin (Fisher, catalog number: 22-110-869)
Globe Scientific Rectangular Cover Glass size 24 × 50 mm, No.1 (Fisher, catalog number: 22-170-388)
Tween 20 (Sigma, catalog number: P1379)
PBS (Phosphate Buffered Saline) and PBS-T (Tween) (see Recipes)
10 mM Sodium Citrate (see Recipes)
Bluing solution (see Recipes)
Equipment
Forceps
Microtome (any supplier)
Microwave (any supplier)
Pressure cooker (any supplier)
Leica SCN400 scanner
Fume hood (any supplier)
Light microscope with 20× and 40× lenses
Water bath (ISOtemp205)
Fisher Scientific Isotemp 650D incubator oven
Software
AperioImage Scope (Leica, https://www.leicabiosystems.com/us/digital-pathology/manage/aperio-imagescope)
Procedure
Tissue processing (liver, lung, pancreas, and colon)
Collect tissue
Euthanize mice with CO2 and cervical dislocation.
Incise the skin from chin to thorax.
Cut away the sternum.
Using a 25G butterfly needle attached to a 10 mL syringe with 0.9% saline, insert this into the left ventricle, near the apex of the heart.
Cut the right atrium, and perfuse with saline.
Collect liver, lung, pancreas, and colon.
Fix tissue
Use 10 mL of 10% formalin for colon and pancreas, and 20 mL of 10% formalin for liver and lung.
Fix at room temperature for 48 h.
Dehydrate tissue
Immerse tissue in 70% ethanol at room temperature for 15 min.
Immerse tissue in 90% ethanol at room temperature for 15 min.
Immerse tissue in 100% ethanol at room temperature three times for 30 min each.
Immerse tissue in xylene at room temperature three times for 20 min each.
Heat paraffin in Isotemp incubator oven.
Embed tissue in paraffin at 58°C. As the paraffin will take several minutes to harden, this can be a pause point in the procedure.
Cut 5 μm-thick sections using a microtome.
Place each section in a water bath, so that it floats, and scoop with a slide to mount the section.
Dry slides at room temperature overnight.
Deparaffinization, and hydration
Immerse slides through the following solutions:
Xylene (pure), three washes of 3 min each.
100% Ethanol, two washes of 1 min each.
95% Ethanol, two washes of 1 min each.
70% Ethanol, one wash of 1 min.
Wash with deionized water two times for 3 min each.
Heat-induced antigen retrieval
Add 10 mM Sodium Citrate buffer (pH 6.0) to a staining dish with slides, and place into a pressure cooker or in microwave to bring to the boil for 10 min, using full power. Then, maintain at half power for 10 min (total of 20 min). For proteinase K retrieval, add 200 μL onto the section, incubate at room temperature for 5 min, and follow step C.4.
Allow to cool down at room temperature for 30 min.
Wash slides in distilled water for 5 min.
Wash slides in PBS-T three times for 5 min each.
Peroxidase quenching
To block endogenous peroxidase activity:
Quench section in 3.0% hydrogen peroxide in PBS-T for 10 min.
Wash slides in PBS-T three times for 5 min each.
Permeabilization and blocking of non-specific binding
Permeabilization
Wash sections in 0.1% Triton X-100 in PBS once for 10 min.
Wash slides in PBS-T three times for 5 min each.
Blocking
Block non-specific binding, by incubating the tissue section in 10% goat serum in PBS-T at room temperature for 25 min.
Antibody incubation
Primary antibody staining in Dako antibody diluent, as per dilutions in notes below.
Incubate at room temperature for 1.5 h.
Wash in PBS-T three times for 5 min each.
Secondary antibody staining.
Add biotinylated secondary antibody (1:200) and incubate at room temperature for 30 min.
Wash in PBS-T three times for 5 min each.
Detection
ABC (avidin/biotinylated enzyme complex) method:
Prepare working solutions of reagent A (avidin) and B (biotinylated HRP) in PBS at 1:50 dilution, 30 min prior. To prepare 1:50 dilution, add 100 μL of each reagent into 5 mL of PBS.
Incubate tissue sections at room temperature for 30 min.
Wash in PBS three times for 5 min each.
Prepare DAB (3,3'Diaminobenzidine)
Determine the volume of DAB needed (100 μL per section). Following the manufacturer’s instructions, add one drop of DAB per milliliter of substrate buffer.
Warning: Wear gloves, and work in the fume hood.
Add 100 μL of DAB working solution to each section. The biotinylated antibody with HRP will oxidize DAB and produce a brown precipitate at the site of the antigen. Monitor the slide every 5 min to visualize the brown color.
When the desired staining develops brown color, wash slides with deionized water.
Counterstaining
Counterstain using hematoxylin.
Immerse slides in hematoxylin to cover the tissue sections.
Incubate for 16 s.
Rinse section with tap water, until water is colorless.
Dip slides ten times in acid rinse solution, followed by ten dips in tap water.
Incubate slides in bluing solution.
Note: Hematoxylin is filtered once a week.
Slide dehydration, and mounting
Dehydrate slides by passing through the following solutions twice for 1 min each:
95% Ethanol
100% Ethanol
Xylene (pure)
Mount coverslips
Using a transfer pipette, add one drop of mounting media per slide and place the coverslip. Allow to dry for 1–2 h.
Slide visualization
Scan slides with a Leica SCN400, or use a microscope to visualize the tissue sections (Figure 1).
Figure 1. Immunohistochemistry of murine liver.
Notes
Antibody name Company Cat # Antigen retrieval Antibody Dilution
CD19 Cell Signaling 90176 citrate buffer 1:1,000 (1 μL antibody + 999 μL diluent)
CD8a Cell Signaling 98941 citrate buffer 1:100
CD4 Cell Signaling 25229 citrate buffer 1:80
F4/80 eBioscience 14-4801 proteinase K 1:200 (5 μL antibody + 995 μL diluent)
Biotinylated goat anti rat Vector BA-9400 citrate buffer 1:200
Recipes
PBS (Phosphate Buffered Saline) and PBS-T (Tween)
1× PBS (900 mL of water + 100 mL of 10× PBS)
0.05% Tween 20 (add 0.5 mL of Tween 20 to 1 L of 1× PBS)
0.1% Triton (add 1 mL of Triton to 1 L of 1× PBS)
10 mM Sodium Citrate
10 mL of 10× Citrate + 90 mL of water
Bluing solution
1.5 mL of NH4OH (30% stock)
98.5 mL of 70% Ethanol
Acknowledgments
We would like to thank Shalom Lerrer, Sean Chen, Hongyan Tang, Tao Su, and Sun Dajiang for their support and expertise. This work was supported by grants from the NIH (AI125640, CA231277, AI150597) and the Cancer Research Institute. The method described here was used in the publication (Adam et al., 2021).
Competing interests
The author reports no competing interests.
Ethics
Animals used in accordance with NIH guidelines and approved by Columbia University’s Institutional Animal Use and Care Committee. Graphic was from BioRender stock IHC image. This protocol was adapted from: https://www.rndsystems.com/resources/protocols/protocol-preparation-and-chromogenic-ihc-staining-paraffin-embedded-tissue.
References
Adam, K., Iuga, A., Tocheva, A. S. and Mor, A. (2021). A novel mouse model for checkpoint inhibitor-induced adverse events. PLoS One 16(2): e0246168.
de Boer, E., Warram, J. M., Tucker, M. D., Hartman, Y. E., Moore, L. S., de Jong, J. S., Chung, T. K., Korb, M. L., Zinn, K. R., van Dam, G. M., et al. (2015). In Vivo Fluorescence Immunohistochemistry: Localization of Fluorescently Labeled Cetuximab in Squamous Cell Carcinomas. Sci Rep 5: 10169.
Mestel, R. (2017). Cancer: Imaging with antibodies. Nature 543(7647): 743-746.
Knight, J. C., Mosley, M. J., Kersemans, V., Dias, G. M., Allen, P. D., Smart, S. and Cornelissen, B. (2019). Dual-isotope imaging allows in vivo immunohistochemistry using radiolabelled antibodies in tumours. Nucl Med Biol 70: 14-22.
Wen, L., Xia, L., Guo, X., Huang, H. F., Wang, F., Yang, X. T., Yang, Z. and Zhu, H. (2021). Multimodal Imaging Technology Effectively Monitors HER2 Expression in Tumors Using Trastuzumab-Coupled Organic Nanoparticles in Patient-Derived Xenograft Mice Models. Front Oncol 11: 778728.
Article Information
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Immunology > Animal model > Mouse
Immunology > Immune cell staining > Immunodetection
Cell Biology > Cell staining > Protein
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4,469 | https://bio-protocol.org/en/bpdetail?id=4469&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
Fluorescence Imaging of 3D Cell Models with Subcellular Resolution
IZ Indra Van Zundert
NM Nina Maenhoudt
SV Silke De Vriendt
HV Hugo Vankelecom
BF Beatrice Fortuni
SR Susana Rocha
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4469 Views: 3493
Reviewed by: Gal HaimovichPradeep Kumar BhaskarSarajo Mohanta
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Original Research Article:
The authors used this protocol in Nature Cell Biology Aug 2019
Abstract
Over the past years, research has made impressive breakthroughs towards the development and implementation of 3D cell models for a wide range of applications, such as drug development and testing, organogenesis, cancer biology, and personalized medicine. Opposed to 2D cell monolayer culture systems, advanced 3D cell models better represent the in vivo physiology. However, for these models to deliver scientific insights, appropriate investigation techniques are required. Despite the potential of fluorescence microscopy to visualize these models with high spatial resolution, sample preparation and imaging assays are not straightforward. Here, we provide different protocols of sample preparation for fluorescence imaging, for both matrix-embedded and matrix-free models (e.g., organoids and spheroids, respectively). Additionally, we provide detailed guidelines for imaging 3D cell models via confocal multi-photon fluorescence microscopy. We show that using these protocols, images of 3D cell culture systems can be obtained with sub-cellular resolution.
Graphical abstract:
Keywords: 3D cell culture systems Organoids Spheroids Fluorescence Microscopy Multi-Photon Fluorescence Microscopy
Background
In recent years, 3D cell models have gained increasing attention in a wide variety of research areas. By mimicking physiological conditions, 3D cell models enabled obtaining more detailed information on several biological processes, from general human biology to disease progression and drug delivery. One of the most popular 3D cell models is spheroids, which are usually formed from small cell aggregates that proliferate further into dense cell clusters (Lazzari et al., 2017; Van Zundert et al., 2020). The spheroids primarily used in cancer research are obtained from cancer cells lines and are often referred to as multicellular tumor spheroids. These models have been proven to be more physiologically relevant than 2D monolayer culture systems, as they present key features of solid tumor tissue (Pinto et al., 2020).
The formation of spheroids is relatively straightforward as they require standard growth medium, and several well-established methods are available (Souza et al., 2010; Foty, 2011; Velasco et al., 2020). The growth of organoids, on the other hand, requires special growth factors and the support of a hydrogel scaffold. Organoids are grown from stem cells that are encapsulated in a supporting matrix, usually Matrigel®, and represent a more complex 3D model. When provided with a specific conditioned medium, stem cells encapsulated in biomimetic hydrogels self-organize into miniature organ-like structures (Boretto et al., 2017; Schutgens and Clevers, 2020).
Both organoids and spheroids are relatively large three-dimensional structures (ranging from 200 to 1,000 μm in diameter), which hampers direct imaging of (sub-)cellular organization, especially in optical microscopy, where the mismatch of the refractive indices between the different cellular compartments, causes a high level of scattering in dense multicellular structures. Together with the light absorption by living matter, this implies a limited penetration of the excitation light and reduced signal from the inside the 3D cell models (Edwards et al., 2020). Although optical clearing methods (DISCO, CUBIC, CLARITY, etc.) can significantly enhance the fluorescence signal obtained from thick samples by improving light penetration, they are usually performed under harsh conditions, which often result in loss of cell morphology or sample damage (Ertürk et al., 2012; Tomer et al., 2014; Dekkers et al., 2019). Alternatively, thick samples can be physically sectioned, and the images acquired from each consecutive section can be used to reconstruct the 3D model. However, this method is time-consuming, and artifacts are easily introduced upon sample cutting (Erickson et al., 2011; Bolduan et al., 2020).
Here, we propose a method for performing fluorescence microscopy on 3D cell culture samples without invasive sample processing. Although samples are prepared without optical clearing or sectioning, fluorescence images with sub-cellular resolution can still be achieved by using multi-photon microscopy. We illustrate both an immunofluorescence staining and a staining with small organic molecules, and provide optimized staining protocols for both scaffold-free and scaffold embedded 3D models. The 3D cell culture systems maintain their native morphology and cellular composition, thereby avoiding biased observations. While in these protocols the samples are imaged using two-photon microscopy, the same sample preparation can also be used for single-photon excitation (albeit with reduced light penetration). After performing the 3D reconstruction of the collected images, a detailed three-dimensional view of the whole spheroid or organoid model can be achieved.
Materials and Reagents
Common for both protocols
1.5 mL microcentrifuge tubes (Eppendorf, catalog number: 0030125150)
Aluminum foil
Dulbecco’s phosphate-buffered saline (DPBS) 1× (ThermoFisher Scientific, GibcoTM, catalog number: 14190144)
Formaldehyde (w/v) 16%, methanol-free (ThermoFisher Scientific, Pierce, catalog number: 28908)
Triton X-100 (Sigma-Aldrich, catalog number: T8787)
Bovine serum albumin (BSA; Sigma-Aldrich, catalog number: A2058)
Fixation buffer (see Recipes)
Permeabilization buffer (see Recipes)
Blocking buffer (see Recipes)
Primary antibodies:
Mouse Anti-E-cadherin (Biosciences, catalog number: 610182)
Rabbit Anti-FOXA2 (Abcam, catalog number: ab108422)
Primary antibody solution (see Recipes)
Secondary antibodies:
Donkey anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor 555 (ThermoFisher Scientific, catalog number: A31572)
Donkey anti-Mouse IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor 488 (ThermoFisher Scientific, catalog number: A21202)
Secondary antibody solution (see Recipes)
Fluorescent probes:
Nuclear staining: Hoechst33342 (Sigma-Aldrich, catalog number: 14533)
Cytoskeleton staining: Phalloidin CruzFluorTM 647 Conjugate (Santa Cruz, catalog number: sc363797)
Nuclear staining solution (see Recipes)
Cytoskeleton staining solution (see Recipes)
Specific for Matrix-embedded 3D model
8-well chambers, #1.5 coverglass (e.g., Cellvis, catalog number: C8-1.5H-N; Ibidi, catalog number: 80807; or NuncTM Lab-TekTM II, Thermo Fisher Scientific, catalog number: 155360)
48-well culture plate (e.g., VWR®, catalog number: 10062-898)
Matrigel® Growth Factor Reduced (GFR) Basement Membrane Matrix, Phenol Red-free, LDEV-free, 10 mL, (Corning, catalog number: 356231) or other suitable, thermo-responsive hydrogels
For endometrial organoids:
Dulbecco’s Modified Eagle Medium-F12 mixture (DMEM/F12) with L-glutamine, HEPES, and Phenol Red (GibcoTM, catalog number: 11320032)
TrypLE express (GibcoTM, catalog number: 12604013)
Rock Inhibitor, Y-27632 (Tocris, catalog number: 1254)
Recombinant Human R-Spondin-1 (RSPO-1) (PreproTech, catalog number: 120-38)
Recombinant Human Noggin (NOG) (PreproTech, catalog number: 120-10C)
B27 supplement (50×), minus vitamin A (Life Technologies, catalog number: 12587010)
N-2 supplement (100×) (Life Technologies, catalog number: 17502048)
Insulin Transferrin Selenium (Life Technologies, catalog number: 41400045)
Penicillin/Streptomycin (Life Technologies, catalog number: 15140122)
Nicotinamide (Sigma-Aldrich, catalog number: 73240-100G)
A83-01 (Sigma-Aldrich, catalog number: SML0788-5MG)
N-Acetyl-L-Cystein (Sigma-Aldrich, catalog number: A7250-50G)EGF (R&D Systems, catalog number: 236-EG-01M)
Basic Fibroblast Growth Factor (bFGF) (R&D Systems, catalog number: 233-FB-025)
Fibroblast Growth Factor 10 (FGF-10) (PreproTech, catalog number: 100-26)
P38 Mitogen Activated Protein Kinase inhibitor, SB 202190 (Sigma-Aldrich, catalog number: S7067-5MG)
β Estradiol (Sigma-Aldrich, catalog number: E8750-100MG)
Organoid medium (for endometrial organoids) (see Recipes)
Organoid dissociation solution (see Recipes)
Specific for Matrix-free 3D model
Grace Bio-Labs CoverWellTM perfusion chambers, chamber diam. × thickness: 9 mm × 1.7 mm (Grace Bio-Labs, distributed by Sigma-Aldrich, Merck, catalog number: GBL622205)
Culture plate (e.g., 6-well Sarstedt® cell culture plate, catalog number: 83.3920.500)
Glass coverslips #1.5, 24 × 50 mm (e.g., ThorLabs, catalog number: CG15KH)
Transparent scotch tape
BIOFLOATTM FLEX coating solution for 3D cell culture (faCellitate, catalog number: F202005)
Trypsin/EDTA solution (ThermoFisher Scientific, Invitrogen, catalog number: 15400054)
3D Petri Dish® micro-mold (MicroTissues, Inc., catalog number: 12-256)
Ultra-pure agarose powder (ThermoFisher Scientific, Invitrogen, catalog number: 16500100)
NaCl (Sigma-Aldrich, catalog number: S9888)
Agarose solution (see Recipes)
For A549 spheroids
T25 culture flask (e.g., Sigma-Aldrich, Corning®, catalog number: CLS430639)
Dulbecco’s Modified Eagle Medium (DMEM) (GibcoTM, catalog number: 31053028)
Fetal Bovine Serum (GibcoTM, catalog number: 11533387)
Glutamax (GibcoTM, catalog number: 35050061)
Culture medium (for A549 cells) (see Recipes)
Equipment
Humidified CO2 incubator (ThermoFisher Scientific)
Fridge and freezer (4°C and -20°C)
Table-top centrifuge (ThermoFisher Scientific, Fisher Scientific, catalog number: 12-006-901)
Micropipettes
Leica TCS SP8 dive microscope (Leica microsystems) or other confocal microscope setup with multiphoton excitation
Sterile flow cabinet
Software
Leica application suite (LAS X, Leica microsystems)
LAS X 3D viewer or other image analysis tool such as Fiji/ImageJ (Schindelin et al., 2012)
Procedure
PART I: SAMPLE PREPARATION OF MATRIX-EMBEDDED 3D MODELS
Preparation of matrix-embedded 3D models (e.g., Organoids)
Important points
In this protocol, endometrial organoids (derived from patient biopsies), cultured and embedded in Matrigel are used as an example. However, the following protocol can be applied to any cell model embedded in thermo-responsive hydrogels that gelate between 20 and 30°C. If other organoids are used, the recipe for the organoid medium will be different. The endometrial organoid culture was performed as previously described by Vankelecom et al. (Boretto et al., 2019).
The preparation of the imaging sample starts from already mature organoids or from single cells (during the passage of organoids).
Keep the Matrigel on ice for at least 2 h before use.
During the entire protocol, it is important to respect the indicated temperatures.
This procedure should be carried out under a sterile flow cabinet.
All the centrifugation steps are performed for 5 min at 200 × g.
When organoids are grown immediately on a glass bottom substrate, suitable for fluorescence imaging, the last section can be skipped (Organoid transfer to glass bottom dishes).
Step-by-step protocol
Dissociation of organoids into single cells
Remove the organoid medium from the wells with matrix-embedded organoids.
Add 400 µL of ice-cold DMEM/F12 and pipet up and down multiple times to release the organoids from the Matrigel.
Transfer the solution into a 1.5 mL microcentrifuge tube and place it on ice.
Wash the wells once with 400 µL of ice-cold DMEM/F12 to collect the remaining organoids.
Transfer the solution into another 1.5 mL microcentrifuge tube and place it on ice.
Centrifuge at 4°C and discard the supernatant.
Add 500 µL of pre-warmed (37°C) organoid dissociation solution (see Recipe 2) to each 1.5 mL microcentrifuge tube containing the organoid pellet.
Mix by pipetting up and down multiple times.
Incubate in a 37°C water bath for 5 min.
Add 500 µL of ice-cold DMEM/F12 to inactivate the TrypLE Express.
Centrifuge at 4°C and discard the supernatant.
Resuspend the pellet in 700 µL of ice-cold DMEM/F12.
Put a P200 tip (no filter) over a P1000 tip (with filter) and pipet up and down 25–30 times to mechanically dissociate the organoids into single cells.
Centrifuge at 4°C and discard the supernatant until ~30 μL (30%) of dissociated organoids/DMEM/F12 is left in the 1.5 mL tube. The volume of 30 μL can be measured by comparing it with another 1.5 mL tube with 30 μL of water.
Resuspend the 30 μL (30%) of pellet with 70 μL (70%) of ice-cold Matrigel.
Note: The volumes of the organoid pellet and the added Matrigel should always be adjusted to have a ratio of 30%/70%.
Organoid seeding
Dispense 25 µL droplets in a pre-warmed 48-well culture plate or 8-well glass bottom dish.
Incubate the plate/dish upside down in a humidified CO2 incubator at 37°C for 2030 min.
Organoid growth
Pre-warm organoid medium in a 37°C water bath.
Add 250 µL of pre-warmed organoid medium to each well.
Keep in culture at 37°C in a 5% CO2 incubator until the organoids reach the desired size or morphology.
Note: The medium should be refreshed every 2 to 3 days.
Organoid transfer to glass bottom dishes (only if the organoids are grown in a 48-well culture plate)
Remove the medium from the well (48-well culture plate) containing the organoids to be imaged.
Add 400 μL of ice-cold DMEM/F12 and pipette up and down multiple times to release the organoids from the Matrigel.
Centrifuge and remove the supernatant until ~30 μL (30%) of organoids/DMEM/F12 is left in the 1.5 mL tube. The volume of 30 μL can be measured by comparing with another 1.5 mL tube with 30 μL of water.
Resuspend the 30 μL (30%) of pellet with 70 μL (70%) of ice-cold Matrigel.
Note: The volumes of the organoid pellet and the added Matrigel should always be adjusted to have a ratio of 30%/70%.
Dispense 25 μL of droplets in the middle of the well of an 8-well glass bottom dish.
Note: Other glass bottom dishes can be used.
Incubate the glass bottom dish upside down in the humidified CO2 incubator for 20–30 min.
Add 250 μL pre-warmed DPBS (1×) around the Matrigel drop.
Note: It is important that solutions are always added and removed with the pipet tip placed at a corner of the well to avoid touching the Matrigel drop (Figure 1).
Figure 1. Handling of Organoids in Matrigel. (A) Organoid droplets (25 μL) in solid Matrigel are added to the center of each well. (B) Solutions are added or retrieved carefully by placing the pipet tip at the corner of the well.
Fixation and permeabilization
Important points
Both the fixation and permeabilization buffers should be pre-warmed at 37°C.
When organoids were grown immediately on a glass bottom substrate, carefully remove the organoid medium and wash three times with 250 μL of pre-warmed DPBS (1×).
Step-by-step protocol
Discard the DPBS solution.
Add 250 μL of pre-warmed fixation buffer to each well.
Incubate for 1 h at 37°C in a humidified CO2 incubator.
Wash the fixed organoids three times with pre-warmed DPBS (1×) and discard the solution.
Add 250 μL of pre-warmed permeabilization buffer to the Matrigel embedded organoids and incubate for 30 min at 3°C.
Wash the Matrigel embedded organoids three times with 250 μL of pre-warmed DPBS (1×).
Immunofluorescence staining
Important points
During the entire protocol, it is important to respect the indicated temperatures of the solutions. Solutions are pre-warmed to 37°C.
Here, a combined immunofluorescence staining is performed using a FOXA2 and E-Cadherin antibody (see Recipe 7). However, the protocol is easily adapted to other antibodies.
When staining is performed using small organic molecules, proceed directly to section D.
Samples are kept in the dark by covering them with aluminum foil.
Step-by-step protocol
Discard the DPBS solution.
Add 250 μL of pre-warmed blocking buffer to the Matrigel embedded organoids (see Recipe 6).
Incubate with blocking buffer for 2 h at 37°C.
Remove the blocking buffer.
Add 250 μL of primary antibody solution (see Recipe 7).
Incubate with primary antibody overnight at room temperature.
Remove the primary antibody solution.
Wash three times with pre-warmed DPBS (1×) and discard the solution.
Add 250 μL of secondary antibody solution (see Recipe 8).
Incubate for 2 h at room temperature (22–25°C), in the dark.
Add 250 µL of pre-warmed DPBS (1×) and incubate for 10 min at 37°C.
Remove the solution.
Repeat steps 11) and 12) two times.
Add 250 µL of pre-warmed DPBS and store the sample at 37°C until the next staining or imaging.
Fluorescence staining with small organic molecules
Important points
Here, a staining of the cytoskeleton and nucleus is performed, using Phalloidin CruzFluor647 and Hoechst33342, respectively. The incubation with the two fluorophores is performed consecutively, to obtain an optimal fluorescence staining.
Samples are kept in the dark by covering them with aluminum foil.
Step-by-step protocol
Discard the DPBS solution.
Add 250 μL of pre-warmed nuclear staining solution (see Recipe 9).
Incubate the sample for 4 h at 37°C.
Add 250 µL of pre-warmed DPBS (1×) and incubate for 10 min at 37°C.
Discard the solution.
Repeat steps 4) and 5) two times.
Add 250 μL of pre-warmed cytoskeleton staining solution (see Recipe 10).
Incubate the organoids with the cytoskeleton staining solution overnight at room temperature (22–25°C), in the dark.
Add 250 µL of pre-warmed DPBS (1×) and incubate for 10 min at 37°C.
Discard the solution.
Repeat steps 9) and 10) two times.
Add 250 µL of pre-warmed DPBS and store the sample at 37°C until the next staining or imaging.
PART II: SAMPLE PREPARATION OF MATRIX-FREE 3D MODELS
Preparation of matrix-free 3D models (e.g., Spheroids)
Important points
The cells used in this protocol are grown in T25 cell culture flasks and are confluent at the start of the protocol. We used A549 cells, but any other adherent cell line can be used.
Here, we use Trypsin/EDTA solution, but any other method to resuspend the cells can be used.
Although in this protocol, spheroids are prepared by the liquid overlay method (using 3D Petri Dishes® micro-molds, see Materials), other spheroid preparation methods can also be used.
The procedure described here for the preparation of the spheroids is adapted from the protocol of the microtissue supplier (MicroTissues Inc., https://www.microtissues.com/protocols).
This procedure should be carried out under a sterile flow cabinet.
Step-by-step protocol
Casting of the agarose microtissues
Rinse the 3D Petri Dishes® micro-molds with MilliQ water.
Place the micro-molds under UV light for 20 min for sterilization.
When sterile, rinse the micro-molds with DPBS (1×) and subsequently remove all the DPBS (1×).
Microwave the agarose at 900 W and swirl it around each 10 s until the solution is completely liquid (see Recipe 11).
Add 500 μL of agarose solution into the micro-mold (Figure 2A).
Let the agarose solidify for 20 min.
After the agarose has solidified, carefully bend the micro-molds to remove the formed agarose microtissue. Do not bend it too much to avoid rupture of the agarose microtissue. A sterile pipet tip can be used to help remove the microtissue (Figure 2B).
Transfer the microtissue into a culture dish (e.g., a 6-well culture plate, Figure 2C).
Figure 2. Preparation of agarose microtissues. (A) Add 500 μL of liquid agarose into the micro-mold. (B) After solidification, carefully remove the agarose microtissue from the micro-mold (a tip can be used). (C) Transfer the microtissue into a cell culture dish.
Equilibration of the agarose microtissue
Completely submerge the agarose microtissue in culture medium (see Recipe 3).
Incubate the microtissue in culture medium for 15 min.
Remove the culture medium.
Repeat steps 10) to 11) two more times.
Resuspend cells
Remove the medium from the T25 cell culture flask.
Wash the adherent cells three times with 4 mL of DPBS (1×) and discard the solution.
Add 50 µL of Trypsin/EDTA solution plus 450 μL of DPBS (1×).
Incubate for 5 min at 37°C in the humidified CO2 incubators.
Add 3.5 mL of culture medium to inactivate the Trypsin/EDTA and pipette up and down multiple times to resuspend the cells.
Count the cells.
Seeding of the agarose microtissue
Remove all the medium in and around the microtissue.
Seed 190 μL of cell suspension with the appropriate cell concentration in a dropwise manner inside the microtissue (here, 500,000 cells per microtissue were seeded to obtain spheroids with a diameter of around 250 μm).
Note: The number of cells used will depend on the cell type and the desired spheroid diameter.
Allow the cells to sink into the wells of the microtissue for 10 min.
Add culture medium around the microtissue.
Keep in culture at 37°C in a 5% CO2 humidified incubator until the spheroids reach the desired size or morphology.
Note: The culture medium should be refreshed every 2 to 3 days; the incubation time will depend on the cell type.
Spheroid harvesting (once the spheroids reach the desired morphology)
Remove the medium surrounding and inside the microtissue.
Vigorously pipet 1 mL of DPBS (1×) on the wells of the microtissue to release the spheroids from the wells. Repeat this multiple times (until all spheroids are free from the wells).
Transfer the spheroid-containing solution into a 1.5 mL microcentrifuge tube.
Fixation and permeabilization
Important points
All the centrifugation steps are performed for 5 s at 2,000 × g.
During the incubation steps the microcentrifuge tube should be placed horizontally on a shaking plate. In this way, the area where the spheroids will sink is increased, allowing the spheroids to be less dense (more distributed) and, therefore, avoiding incomplete fixation or permeabilization. If no shaking plate is available, place the 1.5 mL microcentrifuge tube horizontally on the bench (or in the fridge).
Step-by-step protocol
Centrifuge the harvested spheroids and discard the supernatant.
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to resuspend the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 2) and 3) two more times.
Add 500 μL of fixation buffer (see Recipe 4) and mix gently by flicking the 1.5 mL microcentrifuge tube.
Incubate for 20 min at room temperature.
Centrifuge and discard the supernatant (fixation buffer).
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 8) and 9) two more times.
Add 500 μL of permeabilization buffer (see Recipe 5) and mix gently by flicking the 1.5 mL microcentrifuge tube.
Incubate for 20 min at room temperature.
Centrifuge and remove the supernatant (permeabilization buffer).
Add 1 mL DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 14) and 15) two more times.
Immunofluorescence staining
Important points
During the incubation steps the microcentrifuge tube should be placed horizontally on a shaking plate. In this way, the area where the spheroids will sink is increased, allowing the spheroids to be less dense (more distributed), and, therefore, better staining will be achieved. If no shaking plate is available, place the 1.5 mL microcentrifuge tube horizontally on the bench (or in the fridge).
When staining is performed using small organic molecules, proceed directly to section D.
Samples are kept in the dark by covering them with aluminum foil.
All the centrifugation steps are performed for 5 s at 2,000 × g.
Step-by-step protocol
Add 200 μL of blocking buffer (see Recipe 6) to the spheroid pellet and mix gently by flicking the 1.5 mL microcentrifuge tube.
Incubate for 2 h at room temperature.
Centrifuge and discard the supernatant (blocking buffer).
Add 200 μL of primary antibody solution (see Recipe 7).
Incubate overnight at 4°C.
Centrifuge and remove the supernatant (primary antibody solution).
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 7) and 8) two more times.
Add 200 µL of secondary antibody solution (see Recipe 8).
Incubate for 2 h at room temperature, in the dark.
Centrifuge and discard the supernatant (secondary antibody solution).
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 13) and 14) two more times.
Optional: If no other staining will be performed, add 100 µL of DPBS (1×) and mix gently by flicking the tube.
Fluorescence staining using small organic molecules
Important points
During the incubation steps, the microcentrifuge tube should be placed horizontally on a shaking plate. In this way, the area where the spheroids will sink is increased, allowing the spheroids to be less dense (more distributed), and, therefore, better staining will be achieved. If no shaking plate is available, place the 1.5 mL microcentrifuge tube horizontally on the bench (or in the fridge).
Here, a staining of the cytoskeleton and nucleus is performed, using Phalloidin CruzFluor647 and Hoechst33342, respectively. The incubation with the two fluorophores is performed consecutively to obtain an optimal fluorescence staining.
Samples are kept in the dark by covering them with aluminum folium.
All the centrifugation steps are performed for 5 s at 2,000 × g.
Step-by-step protocol
Add 200 μL of nuclear staining solution (see Recipe 9).
Incubate for 4 h at room temperature, in the dark covered with aluminum foil.
Centrifuge and discard the supernatant (nuclear staining solution).
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 4) and 5) two more times.
Add 200 μL of cytoskeleton staining solution (see Recipe 10).
Incubate overnight at room temperature in the dark.
Centrifuge and discard the supernatant (cytoskeleton staining solution).
Add 1 mL of DPBS (1×) and mix gently by flicking the tube to wash the spheroids.
Centrifuge and discard the supernatant.
Repeat steps 10) and 11) two more times.
Add 100 µL of DPBS (1×) and mix gently by flicking the tube.
Mounting of stained spheroids
Important points
Here, we used a 24 ×50 mm #1.5 glass coverslip but other formats can be used.
Spheroids are prone to sticking to the pipette tip. If this is a problem, before transferring the spheroids to the perfusion chamber, draw 200 μL of BIOFLOATTM FLEX coating solution into a P200 pipette, leave it in the pipette tip for 10 s and discard. Use this pipette tip to transfer the spheroid-containing solution into the perfusion chamber.
Note: Alternatively, ice-cold 1% BSA in DPBS (1×) solution can be used for coating the tip.
Step-by-step protocol
Glue a CoverWell perfusion chamber onto a glass coverslip.
Take 50 μL of stained spheroids and pipet the necessary volume into the perfusion chamber until full; the remaining spheroids can be transferred again to the 1.5 mL microcentrifuge tube (Figure 3A).
Cover the two openings of the perfusion chamber with transparent scotch tape to avoid sample evaporation during imaging (Figure 3B).
Figure 3. Mounting spheroid sample for imaging. (A) Take 50 μL of stained spheroids and pipet the necessary volume into the perfusion chamber until full. (B) Cover the two openings of the perfusion chamber with transparent scotch tape to prevent sample evaporation.
PART III: IMAGING OF MATRIX-EMBEDDED AND MATRIX-FREE 3D MODELS
Data acquisition and 3D reconstruction
Important points
The Leica TCS SP8 dive microscope used for the visualization of the samples prepared in PART I and PART II is equipped with a multi-photon Insight X3 laser (range 680–1,300 nm), a FLUOTAR VISIR 25× water objective (NA 0.95), a HC PL IRAPO 40× water objective (NA 1.1), and two HyD hybrid detectors.
To capture a complete spheroid/organoid, the objectives used to image 3D cell models need to have a long working distance (WD), preferentially longer than 0.6 mm. The FLUOTAR VISIR 25× objective used has a WD of 2.4 mm and is therefore used for larger spheroid/organoid diameters, while the HC PL IRAPO 40× objective has a WD of 0.65 mm and can be used for smaller spheroids/organoids.
Here, two-photon excitation is used to visualize the spheroids/organoids. Two-photon excitation requires simultaneous excitation by two photons with longer wavelength than the emission light. This longer wavelength (usually near-infrared) is less scattered by cellular compartments, thereby enhancing light penetration. Standard single-photon excitation can also be used to visualize the samples but will imply reduced light penetration into the spheroid/organoid, resulting in a reduced fluorescence signal.
When in live mode (fast-scanning), scanning speed is set at 600 Hz and the image format at 512 × 512 pixels. During data acquisition the speed is set at 400 Hz and the image format at 1,024 × 1,024 pixels format, to enhance image quality.
The step size for the acquisition of a z-stack is typically set to 1 μm.
In this protocol, image reconstruction is carried out using the LASX 3D viewer. However, other image analysis programs, such as ImageJ or Fiji, can also be used.
Often, the light penetration, thus fluorescent signal, decreases when moving the z-position up. This effect can be reduced by using the z-compensation tool (incorporated in the LASX software). With this tool, the power of the excitation light and/or the excitation gain can be increased in a linear fashion during the z-stack (adjusted for each xy plane).
Step-by-step protocol
After starting up the microscope, place the sample onto the sample holding stage of the microscope.
Adjust the microscope parameters depending on the fluorescent dyes used to stain the sample (Table 1). When multiple dyes are used in one sample, a sequential scan is carried out. Here, we performed a sequential scan between stacks; accordingly, the complete stack is acquired for 1st channel, and next, the complete stack is acquired for the 2nd channel.
Table 1. Excitation wavelength and detector parameters used for the fluorescence stainings.
Phalloidin Cruzfluor647 Hoechst33342 Foxa2 (AF488) E-Cadherin(AF555)
single photon excitation (nm) 647 350 488 555
two-photon excitation (nm) 1,294 700 976 1,110
hyD detector range (nm) 650–750 400–450 500–550 570–650
Bring the spheroid or organoid in focus via the eyepiece using the transmission light.
Center the spheroid/organoid in the field of view using the sample stage.
Start the live mode to check the fluorescence signal in the spheroid/organoid.
Z-stack acquisition
Move the z-position all the way to the bottom of the spheroid/organoid.
Define this location as the beginning of the stack.
Move the z-position to the top of the spheroid/organoid.
Define this location as the end position of the stack.
Start the acquisition of the stack.
Stack reconstruction
Open the stack in the LASX 3D viewer software.
Adjust the colors, brightness, contrast, and gamma as desired for each channel.
Set the background to black by checking the box “black” instead of “grey”.
Optional: Change the orientation of the spheroid/organoid as desired by holding and dragging the left mouse button.
Optional: Using the clipping tool, the spheroid/organoid can be sectioned into planes. Parts can be cut out to have a better view inside the spheroid/organoid (Figures 4–6).
Add the scale bar and orientation inset to the 3D reconstruction by checking the boxes “scale bar” and “draw frame”.
Figure 4. 3D reconstruction of an endometrial organoid stack stained with antibodies against E-Cadherin and FOXA2. (A) Immunofluorescence of FOXA2 (cyan) and E-Cadherin (red) in an endometrial organoid; different frames in various positions in the stack are displayed. (B) 3D reconstruction of the complete z-stack. (C) 3D view with the bottom half clipped, exposing the inside of the organoid.
Figure 5. 3D reconstruction of an endometrial organoid stack with labeled nucleus and actin filaments. (A) Staining with Hoechst (nucleus, green) and Phalloidin647 (cytoskeleton, magenta), different frames in various positions in the stack are displayed. (B) 3D reconstruction of the complete zstack. (C) 3D view with the bottom half clipped, exposing the inside of the organoid.
Figure 6. 3D reconstruction of a spheroid stack stained with labeled actin filaments. (A) Different sections in various positions of the stack. (B) 3D reconstruction of the complete z-stack. (C) 3D view with the bottom half clipped, exposing the inside of the spheroid.
Troubleshooting
Table 2.Troubleshooting
Problem Potential reason(s) Solution (s)
Loss of spheroids 1. Spheroids are not fully pelleted during centrifugation cycles
2. Spheroids stick to the pipet tip
1. Pre-coat the tip with a BIOFLOATTM FLEX coating solution or with ice cold 1% BSA in DPBS
Matrigel collapsed 1. Solution was not pre-heated to 37°C 1. Keep all solutions in a warm water bath for at least 20 min
Spheroids disintegrate/fall apart during protocol
1. Spheroids were not fully formed when harvested
2. Too fast centrifugation
3. Severe mixing during washing steps
1. Before harvesting the spheroids, check under an optical microscope that dense coherent spheroids are formed.
2. When spheroids are prone to disintegration (weaker cell-cell interactions, instead of centrifugation to pellet the spheroids, leave them in the microcentrifuge tube until they sink to the bottom.
3. Do not pipet into the spheroid solution, but mix the spheroids by flicking the tube.
No fluorescent signal in the middle of the spheroids/organoids
1. Antibodies/dyes did not penetrate into the organoid/spheroid core
2. Necrosis in the spheroid/organoid core.
3. Excitation light is not able to penetrate the middle of the spheroid/organoid.
1. Prolong the permeabilization and/or antibody incubation times.
2. Avoid growing spheroids too long without changing the medium before harvesting.
3. Use red/far-red dyes as the excitation light for these dyes have better penetration into larger samples
Recipes
Organoid medium (for endometrial organoids)
DMEM/F12 (with L-glutamine and HEPES), supplemented with 10% (v/v) RSPO1, 10% (v/v) NOG), 2 % (v/v) B27, 1% (v/v) N2, 1% (v/v) Glutamax, 1% (v/v) Insulin Transferrin Selenium, 1% (v/v) Penicilin/Streptomycin, 2 mM Nicotinamide, 0.5 µM A83-01, 1.25 mM N-acetyl L-cysteine, 50 ng/mL EGF 50 ng/mL, 2 ng/mL bFGF, 10 ng/mL FGF-10, 10 µM SB202190, 1 nM β Estradiol, and 10 µM Rock Inhibitor (Y-27632b)
Organoid dissociation solution
TrypLE Express with 10 μM Rock Inhibitor (Y-27632b)
Culture medium (for A549 cells)
DMEM with 10% (v/v) Fetal Bovine Serum, 5% (v/v) Glutamax, and 0.1% (v/v) Gentamycin
Fixation buffer
4% Formaldehyde in DPBS (1×)
Permeabilization buffer
0.1% Triton X-100 in DPBS (1×)
Blocking buffer
3% BSA in DPBS (1×)
Primary antibody solution
Mouse Anti-E-cadherin (1:200, 1.25 μg/mL) and Rabbit Anti-FOXA2 (1:150, 13.5 μg/mL) in blocking buffer (3% BSA in DPBS 1×)
Secondary antibody solution
Anti-Rabbit IgG AF555 (1:500, 4 μg/mL) and Anti-Mouse IgG AF488 (1:500, 4 μg/mL) in blocking buffer (3% BSA in DPBS 1×)
Nuclear staining solution
Hoechst 33342 (1:1,000, 5 μg/mL) in DPBS 1×
Cytoskeleton staining solution
Phalloidin CruzFluor647 (1:1,000 of stock solution in DMSO) in blocking buffer (3% BSA in DPBS 1×)
Agarose solution
2% (w/v) Ultra-pure agarose powder dissolved in 0.9% (w/v) NaCl in Milli-Q water. Autoclave before use.
Acknowledgments
This work was supported by the Research Foundation—Flanders (FWO, projects G0A5817N, G0D4519N, 1529418N, G081916N, and G094717N), by KU Leuven (C14/16/053, C14/18/061, and KA/20/026). I.V.Z., N.M., and B.F. acknowledge the support from FWO for their Ph.D. and Postdoctoral fellowships, respectively (11F5419N, 11A1120N, and 12X1419N). The protocol for spheroid preparation was adapted from the protocol provided by the supplier of the microtissues (Microtissues, Inc.).
Competing interests
There are no competing interests.
Ethics
Endometrial biopsies were obtained from patients undergoing laparoscopy for benign gynecological conditions after informed written consent. The study was approved by the Ethics Committee Research UZ/KU Leuven (S59006; S59177).
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The authors used this protocol in eLIFE Nov 2021
Abstract
Microorganisms have evolved adaptive strategies to respond to the autonomous degradation of their environment. Indeed, a growing culture progressively exhausts nutrients from its media and modifies its composition. Yet, how single cells react to these modifications remains difficult to study since it requires population-scale growth experiments to allow cell proliferation to have a collective impact on the environment, while monitoring the same individuals exposed to this environment for days. For this purpose, we have previously described an integrated microfluidic pipeline, based on continuous separation of the cells from the media and subsequent perfusion of the filtered media in an observation chamber containing isolated single cells. Here, we provide a detailed protocol to implement this methodology, including the setting up of the microfluidic system and the processing of timelapse images.
Keywords: Single-cell ecology Cell fate heterogeneities Microfluidic-based time-lapse microscopy Cytosolic pH Quiescence entry Diauxic shift Metabolic state
Background
The proliferation capacity of microorganisms is tightly linked to the nature and availability of nutrients in their habitat. Exponential cell multiplication leads to the rapid exhaustion of resources, or to the secretion of metabolic byproducts in the medium, which can improve long-term population survival (Fabrizio and Longo, 2003; Enriquez-Hesles et al., 2021) or allow subsequent proliferation phases (Allen et al., 2006).
For instance, during its natural life cycle, budding yeast S. cerevisiae undergoes transitions between different metabolic phases due to the progressive consumption of nutrients in the environment. A rapid phase of sugar fermentation during which ethanol is produced is followed by a respiration phase where the cells consume the ethanol. In between these two phases, cells undergo a reversible proliferation arrest called the diauxic shift. Upon complete exhaustion of carbon sources, cells ultimately enter a dormant state, referred to as quiescence, a reversible proliferation arrest that lasts until new nutrient sources arise. Hence, S. cerevisiae’s fate is highly dynamic and tightly coupled to the continuous remodeling of its environment.
In addition, cells in this changing environment experience massive intracellular reorganizations in a very dynamic manner. Moreover, there is a high cell-to-cell variability in the cellular state reached by isogenic S. cerevisiae cells in a nutrient-deprived environment (Allen et al., 2006; De Virgilio, 2012; Sagot and Laporte, 2019). Lastly, the state of quiescence is sensitive to the nature of the nutrient deprivation (Klosinska et al., 2011), to the initial composition of the glucose medium (Fabrizio and Longo, 2003; Burtner et al., 2009; Smith et al., 2009), and also to the rate at which nutrients are consumed over time (Solopova et al., 2014). Therefore, studying quiescence at the population scale ignores cell-to-cell heterogeneities, while observing single cells responding to starvation with classical strategies such as microfluidics, is unable to consider the natural dynamics of a culture media (Li et al., 2013; Miles et al., 2021).
Studying the entry into quiescence requires longitudinal tracking of single cells while allowing cell proliferation to have a collective impact on the environment.
To this end, we have recently proposed a new microfluidic methodology to image single budding yeast cells during an unperturbed life cycle, from the fermentative phase to late quiescence, in an autonomously degrading environment (Jacquel et al., 2021). The cells trapped in an observation microfluidic device are constantly fed with the medium of a growing culture of cells, thus experiencing comparable environmental conditions.
In this protocol, we describe in detail how to run a typical experiment using this microfluidic system and provide a case study with a fluorescence single-cell pH cytosolic sensor during an unperturbed life cycle.
Materials and Reagents
Glass coverslips 0.15 mm in thickness, 24 × 50 mm (e.g., Knittel Glass)
Glass slide, any thickness >0.5 mm, 24 × 75 mm (e.g., Knittel Glass)
Plastic weighing boat
Razor blade (e.g., Swan Morton with n°10 blade)
1 mm biopsy punch (e.g., Kai medical)
Cutting mat (e.g., QIAGEN WB100020, FisherScientific, catalog number: 11323365)
Aluminum foil
Ethanol 70% and 100%
Clear removable tap (e.g., 3M magic tape)
“Spiral”, “Dust filter”, and observation microfluidic molds (see Figure 1). Designs available at https://github.com/TAspert/Continuous_filtration and (Goulev et al., 2017); can be produced by a standard photolithographic process (see details at Jacquel et al., 2021) or sent on demand.
1 m of 1 mm outer diameter Polytetrafluoroethylene (PTFE) tubes (e.g., Adtech Polymer Engineering 1.07 mm outer diameter, Fisher Scientific, catalog number: 11929445)
5 mL Syringe (e.g., Terumo)
23G needles (e.g., Terumo)
Budding yeast strain
Culture media (e.g., Yeast Extract Peptone supplemented with Dextrose, YPD)
Polydimethylsiloxane (PDMS) and cross-linking agent (Sylgard 184 from Dow Chemical) (see Recipes for preparation)
Equipment
Plasma cleaner (e.g., Diener, model: Zepto)
Peristaltic pump (e.g., Ismatec, model: IPC) or any other pump able to generate flow rates between 10 and 100 µL/min
Inverted epifluorescence microscope (e.g., Nikon, model: Ti Eclipse 2)
Oven (heating at 60°C)
Tweezers (e.g., Fine Science Tools, catalog number: 91100-16)
1 Erlenmeyer flask per condition (25 mL)
Vacuum desiccator (e.g., Nalgene, Thermo Fisher, catalog number: 5305-0609)
Vacuum pump (e.g., Millivac-Maxi Vacuum Pump, Merck, catalog number: SD1P014M04)
Orbital shaker (e.g., Solaris 2000, ThermoFischer, catalog number:SK2000)
For pHluorin observation:
Fluorescence emission source of peak excitation wavelengths at 390/18 and 475/28 nm (e.g., Lumencor, model Retra)
Filter cubes for peak excitation wavelengths at 390/18 and 475/28 nm, and collection at 525/50 nm (for both excitation wavelengths) (e.g., Chroma)
Software
To drive the microscope: Micromanager 2.0.0 (https://micro-manager.org) (Edelstein et al., 2014)
For image and data analysis: Matlab, including Matlab Toolbox “Image processing”, “Statistical analysis”, “Signal processing”, and the Matlab modules Phylocell + Autotrack (Goulev et al., 2017), https://github.com/gcharvin/phyloCell, https://github.com/gcharvin/autotrack or DetecDiv (Aspert et al., 2022).
Procedure
The whole protocol describes how to run an experiment with one condition. Details are given at specific points for running multiple conditions in parallel. This procedure works with haploid budding yeast cells but can be adapted by tweaking the dimensions of the devices in order to fit with similar cells.
Fabrication of the microfluidic devices (day -1)
Prepare the PDMS (cf. Recipe section). One spiral (5 g of PDMS required) and one dust filter (5 g required) are required per condition; the observation device can take up to 16 conditions (10 g required) (for description of molds, see Figure 1). Therefore, one condition requires approximately 20 g of PDMS, and an additional 10 g is required per additional condition.
Pour the PDMS into the three microfluidic molds and leave them at room temperature for ~5 min to let any potential bubbles leave the PDMS.
Bake the molds at 60–80°C for a few hours (at least 5 h at 60°C, or at least 2 h at 80°C) in an oven. Molds can be left overnight or over the weekend in the oven without a problem.
Carefully peel the chips off the molds using a razor blade, and cut exceeding sides on the cutting mat.
Turn the chip features up and punch holes using the 1 mm biopsy tool at the inlets of the PDMS devices. Four holes have to be punched on the observation device (per condition), three on the spiral, and two on the dust filter (Figure 1). Perform this operation on the cutting mat to not damage your tool.
Preparation of the devices (day 0)
Take the previously fabricated PDMS devices (cf part A), and carefully clean their surfaces using the cleaning tape.
Prepare one glass coverslip for the observation device and one glass slide per condition.
Put the chips in the chamber of the plasma cleaner, face-up, as well as the glass coverslip and slide(s). Close the chamber.
Vacuum the chamber to approximately 0.2 mbar. Then, inject dioxygen (or air) into it until a pressure of 0.7 mbar is reached (parameters may vary depending on the plasma cleaner).
Set the power to 10% and the timer to 20s, and generate the plasma (parameters may vary depending on the plasma cleaner).
Once the plasma exposure is done, take back the chips and glass cover from the chamber, and seal the chips to their respective glass cover. The spiral and dust filter can be put on the same glass slide for convenience. Do not press the chips too much against the glass (especially for the observation device) as it could collapse the chambers.
Put the assembled devices in a 60°C oven for 20min.
The chips are ready to be primed and loaded. This should be done no later than an hour after the plasma activation to keep the surfaces hydrophilic, to avoid the formation of air bubbles once the channels are filled with media.
Preparation of the cell culture (days -2, -1, and 0)
General note for the two following sections (C and D): All the media manipulations must be done under a sterile hood or close to a flame to prevent contaminations from other microorganisms. Antibiotics can be added to the medium to limit the probability of microbial contamination.
Thaw cells from -70°C on an agar plate and let them at 30°C for 2 or 3 days.
The day before the experiment, inoculate the cells in a culture tube of the same media as the experiment and let the cells grow overnight at 30°C with continuous shaking.
Note: All media used within the following steps need to be recently filtered to avoid dust particles and media crystals.
On the day of the experiment, prepare 25 mL of filtered liquid medium (typically, YPD) into a 50 mL Erlenmeyer, and resuspend cells to low OD (between 0.05 and 0.1). Put a sterile aluminum foil on the top of the Erlenmeyer to prevent microbial contamination while allowing air exchange between the room and the Erlenmeyer. Let the cells grow at room temperature with continuous shaking.
One to two hours before the desired start point of the time-lapse (see Note for details), load ~5 mL of the culture into a 5mL syringe, using a 23 G needle. This syringe will be used to load the microfluidic chambers. Put back the Erlenmeyer flasks containing the rest of the culture (~20 mL) under continuous shaking, during the preparation and the loading of the microfluidic device.
Note: The time at which cells are loaded within the device depends on the growth phase of the yeast life cycle to study. Example: To image the transition from fermentative growth to the diauxic shift, it is recommended to start cell loading 5 h before the end of the fermentative phase (i.e., 5h before the diauxic shift); 1 to 2 h are needed from the cell loading (step B6) to the beginning of the time-lapse, depending on the experimenter.
Priming and loading the microfluidic chip (day 0)
Clean and sterilize the PTFE tubes by running ethanol 70% and then air into them.
Connect the PTFE tubes as described in Figure 1, i.e., per condition, plug:
1) One tube from the pump to the dust filter
2) One tube from the dust filter to the inlet of the spiral (centered hole)
3) One tube from the external outlet of the spiral to the observation device
4) One tube from the internal outlet of the spiral to nothing
5) One tube from the outlet of the observation device to nothing
6) One tube from each of the two cell-inlets of the observation device to nothing
Figure 1. Schematic of the fluidic system. Colored lines represent tubes; the color indicates the concentration in cells (darker means higher). Arrows indicate flow direction at steady-state. The observation device contains 16 independent conditions, only one being used here.
Once the cell culture is at the desired growth stage, remove it from the shaker.
Wipe the other end of the pump tube with a tissue and ethanol 100%, let it dry for a few seconds, and plug it into the Erlenmeyer through the aluminum foil. This inlet has to be in contact with the culture medium since it has to aspirate the culture medium into the pump and the whole microfluidic system. Seal the hole made into the aluminum using paper tape, to maintain sterility.
Switch the pump on with a flow rate of 50–100µL/min to prime the microfluidic system. The four tube ends of this system (the outlet of the spiral, two cell-inlets of the observation device, and the outlet tube of the observation device) can be momentarily put into an empty beaker (Figure 2, left). Let the medium flow for a few minutes to remove all the air from the fluidic system.
Figure 2
Figure 2. Picture of the fluidic system during (left) and after (right) the cell injection step.
Wipe the outlet tube from the observation device with a tissue and ethanol 100%, let it dry for a few seconds, and plug it into the Erlenmeyer through the aluminum foil. This tube does not need to be in contact with the culture medium. At this time, only two tubes, the lateral tubes from the observation device, should remain unplugged.
Stop the pump. Take the syringe prepared in step C4 and connect it (via a 23 G needle) to one of the two lateral tubes (it does not matter which one) (Figure 2, left). Gently inject cells within the microfluidics device. It is recommended to check cell injection in real-time with a bench microscope to adjust the number of cells within microfluidics sub-chambers. The number of initial cells must be adjusted depending on the life-cycle phase of interest. To study cells from fermentation to quiescence, it is recommended to start with approximately 3–10 cells per chamber (Figure 3).
Figure 3. Typical field of view of a chamber of the observation device after cell injection.
Disconnect the syringe from the PTFE tube. Wipe the lateral tubes with a tissue and ethanol 100%, let them dry for a few seconds, and plug them into the Erlenmeyer through the aluminum foil. At this time, the fluidic system should be in a closed loop (Figure 2, right).
Set up and start of the timelapse (day 0)
Bring the fluidic system (devices, tubes, Erlenmeyer, and pump) close to the microscope.
Install the observation device onto the sample holder of the microscope.
Place the Erlenmeyer onto an orbital shaker and the rest of the devices in a relevant place. The tubes can be secured using paper tape.
Figure 4. Picture of a typical fluidic and microscopy setup during the timelapse experiment.
Switch the pump back on and set it to a flow rate of 80-120 µL/min (flow rate for optimal spiral filtration). The setup should be similar to the one in Figure 4.
Check that the media is properly flowing in all the tubes by checking for droplets at the outlets. If not, check for potential bubbles all along the tubes.
Set up the positions for the timelapse (typical position displayed in Figure 3), as well as the imaging conditions (channels, exposure, etc.). This can be done using Micromanager or any microscope controlling software. To image the pHluorin sensor, the fluorescence is acquired at two different excitation wavelengths (Peak excitation wavelengths at 390/18 and 475/28 nm) and collected for both excitation wavelengths at 525/50 nm (emission wavelength). Adjust excitation and emission wavelengths depending on the fluorescent protein.
Monitor the experiment throughout the days. In particular, check for potential leaking or clogging of the devices (notably from the dust filter device, which serves as a fluidic fuse), for potential loss of focus from the microscope, or potential contamination in the chamber.
Data analysis
As a case study, a data analysis workflow is described below, using the single-cell analysis of cytosolic pH using the ratiometric fluorescent sensor pHluorin (Mouton et al., 2020; Jacquel et al., 2021) as an example. This processing can be done in multiple ways using different software tools. Here, we use the custom Matlab addons Phylocell and Autotrack (https://github.com/gcharvin/phyloCell, https://github.com/gcharvin/autotrack). Tutorials for these software tools are available in their respective folders.
At the end of the timelapse experiment, load the data into PhyloCell.
Visualize the images series, and check that the cells grew following the expected different growth phases and that no apparent problem has occurred (contamination, loss of focus, air bubbles…).
Segment and track cells using the automatic batch segmentation workflow from Autotrack. Segmentation and cell tracking can then be corrected manually using PhyloCell if needed. Although segmentation is usually robust, a few tracking errors might require manual correction.
Note: Cell segmentation means determining cell contours on an image. Cell tracking means attributing a cell contour to a cell throughout the timepoints (to recapitulate the whole “life trajectory”.)
Once cells are correctly segmented and tracked, it is possible to measure the fluorescence of each cell segmented area, for each excitation wavelength, and for each timepoint. Subtract the background value from each wavelength (estimated from an area on the image depleted of cells).
Calculate the fluorescence ratio I390/I475, and convert it into pH using the pH calibration, for each timepoint. You now have access to the cytosolic pH of each cell throughout the timepoints.
Notes:
The pHluorin probe works as a ratiometric fluorescent cytosolic pH sensor. Depending on the cytosolic pH, the intensity of the light collected at the two different excitation wavelengths is modified, resulting in a modification of the light intensity ratio. To transform the fluorescence ratio into an absolute cytosolic pH value, a calibration must be done using the same system as the experiment [See supplementary section of Mouton et al. (2020); Jacquel et al. (2021) for details].
The fluorescent ratio within the vacuole is slightly different from the rest of the cytosol. However, excluding the vacuole from the analysis does not dramatically change the estimated value of the cytosolic pH.
Recipes
PDMS
Pour approximately 30 g of PDMS into a plastic weighing boat (for one condition).
Add curing agent in a 1:10 proportion (3 g in this case).
Thoroughly mix (for example, using a bent 1 mL tip) and degas the solution under a vacuum desiccator for approximately 30 min.
Acknowledgments
This work was supported by the Fondation pour la Recherche Médicale (FRM, B.J, and G.C.), the Agence Nationale pour la Recherche (T.A. and G.C.), the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
This protocol is a related to our previous study published in eLife [Jacquel et al. (2021)], doi: 10.7554/eLife.73186.)
Competing interests
The authors declare no competing interests.
References
Allen, C., Buttner, S., Aragon, A. D., Thomas, J. A., Meirelles, O., Jaetao, J. E., Benn, D., Ruby, S. W., Veenhuis, M., Madeo, F., et al. (2006). Isolation of quiescent and nonquiescent cells from yeast stationary-phase cultures. J Cell Biol 174(1): 89-100.
Aspert, T., Hentsch, D. and Charvin, G. (2022). DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis. bioRxiv: 2021.2010.2005.463175.
Burtner, C. R., Murakami, C. J., Kennedy, B. K. and Kaeberlein, M. (2009). A molecular mechanism of chronological aging in yeast. Cell Cycle 8(8): 1256-1270.
De Virgilio, C. (2012). The essence of yeast quiescence. FEMS Microbiol Rev 36(2): 306-339.
Edelstein, A. D., Tsuchida, M. A., Amodaj, N., Pinkard, H., Vale, R. D. and Stuurman, N. (2014). Advanced methods of microscope control using muManager software. J Biol Methods 1(2).
Enriquez-Hesles, E., Smith, D. L., Jr., Maqani, N., Wierman, M. B., Sutcliffe, M. D., Fine, R. D., Kalita, A., Santos, S. M., Muehlbauer, M. J., Bain, J. R., et al. (2021). A cell-nonautonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism. J Biol Chem 296: 100125.
Fabrizio, P. and Longo, V. D. (2003). The chronological life span of Saccharomyces cerevisiae. Aging Cell 2(2): 73-81.
Goulev, Y., Morlot, S., Matifas, A., Huang, B., Molin, M., Toledano, M. B. and Charvin, G. (2017). Nonlinear feedback drives homeostatic plasticity in H2O2 stress response. Elife 6: e23971.
Jacquel, B., Aspert, T., Laporte, D., Sagot, I. and Charvin, G. (2021). Monitoring single-cell dynamics of entry into quiescence during an unperturbed life cycle. Elife 10:e73186
Klosinska, M. M., Crutchfield, C. A., Bradley, P. H., Rabinowitz, J. D. and Broach, J. R. (2011). Yeast cells can access distinct quiescent states. Genes Dev 25(4): 336-349.
Li, L., Miles, S., Melville, Z., Prasad, A., Bradley, G. and Breeden, L. L. (2013). Key events during the transition from rapid growth to quiescence in budding yeast require posttranscriptional regulators. Mol Biol Cell 24(23): 3697-3709.
Miles, S., Bradley, G. T. and Breeden, L. L. (2021). The budding yeast transition to quiescence. Yeast 38(1): 30-38.
Mouton, S. N., Thaller, D. J., Crane, M. M., Rempel, I. L., Terpstra, O. T., Steen, A., Kaeberlein, M., Lusk, C. P., Boersma, A. J. and Veenhoff, L. M. (2020). A physicochemical perspective of aging from single-cell analysis of pH, macromolecular and organellar crowding in yeast. Elife 9: e54707.
Sagot, I. and Laporte, D. (2019). The cell biology of quiescent yeast - a diversity of individual scenarios. J Cell Sci 132(1): jcs213025.
Smith, D. L., Jr., Li, C., Matecic, M., Maqani, N., Bryk, M. and Smith, J. S. (2009). Calorie restriction effects on silencing and recombination at the yeast rDNA. Aging Cell 8(6): 633-642.
Solopova, A., van Gestel, J., Weissing, F. J., Bachmann, H., Teusink, B., Kok, J. and Kuipers, O. P. (2014). Bet-hedging during bacterial diauxic shift. Proc Natl Acad Sci U S A 111(20): 7427-7432.
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Isolation and ex vivo Expansion of Limbal Mesenchymal Stromal Cells
Naresh Polisetti
LS Lyne Sharaf
TR Thomas Reinhard
GS Günther Schlunck
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4471 Views: 1447
Reviewed by: Vivien Jane Coulson-ThomasMingxia SunIsabel Moreno
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Original Research Article:
The authors used this protocol in International Journal of Molecular Sciences Mar 2022
Abstract
Limbal mesenchymal stromal cells (LMSC), a cellular component of the limbal stem cell niche, have the capability of determining the fate of limbal epithelial progenitor cells (LEPC), which are responsible for the homeostasis of corneal epithelium. However, the isolation of these LMSC has proven to be difficult due to the small fraction of LMSC in the total limbal population, and primary cultures are always hampered by contamination with other cell types. We recently published the efficient isolation and functional characterization of LMSC from the human corneal limbus using CD90 as a selective marker. We observed that flow sorting yielded a pure population of LMSC with superior self-renewal capacity and transdifferentiation potential, and supported the maintenance of the LEPC phenotype. Here, we describe an optimized protocol for the isolation of LMSC from cadaveric corneal limbal tissue by combined collagenase digestion and flow sorting with expansion of LMSC on plastic.
Graphical abstract:
Keywords: Limbal mesenchymal stromal cells Limbal niche cells Limbal stem cells Cornea Isolation Expansion
Background
Homeostasis of the corneal epithelium is regulated by limbal epithelial stem/progenitor cells (LEPC) located at a specific anatomic location referred to as the limbal stem cell niche (Gonzalez et al., 2018). It is characterized by limbal vasculature, a specific extracellular matrix composition (ECM), and surrounding non-epithelial limbal niche cells (LNCs) (Shortt et al., 2007; Ordonez et al., 2012; Polisetti et al., 2016) (Figure 1). Limbal mesenchymal stromal cells (LMSC), a cellular component of the limbal stem cell niche, have been shown to support corneal epithelial regeneration during wound healing, and the maintenance of the LEPC phenotype, both in vitro and in vivo (Dziasko et al., 2014; Nakatsu et al., 2014; Li et al., 2018; Polisetti et al., 2016). In addition, LMSC were shown to have potent immunomodulatory, anti-inflammatory, and anti-angiogenic properties, making them potentially attractive tools for clinical use (Funderburgh et al., 2016; Veréb et al., 2016; Al-Jaibaji et al., 2019; Polisetti et al., 2021). Thus, the co-cultivation of LEPC with LMSC might represent an improved strategy to generate cell transplants for patients suffering from limbal stem cell deficiency (Rama et al., 2017; Ghareeb et al., 2020). Previously, LMSC have been isolated either by enzymatic digestion of limbal tissue (dispase, collagenase, or in combination) or by explant culture of limbal tissue followed by enrichment using cell type-specific media (Chen et al., 2011; Xie et al., 2012; Li et al.,2012; Li et al., 2014; Chen et al., 2015; González et al., 2013; Polisetty et al., 2008; Xiao et al., 2020). The main disadvantage of these methods is the contamination by other cell types (Polisetty et al., 2008; Li et al., 2012). Collagenase digestion of limbal tissue results in cell clusters consisting of 80% epithelial cells and 20% LMSC, whereas a combination of dispase and collagenase yields clusters composed of approximately 95% LMSC (Li et al., 2012). Thus, current protocols for LMSC purification require culturing of at least one passage to eliminate contaminating cells. Thus, research on freshly isolated LMSC has been hampered by the lack of a good protocol for isolating this cell type.
Here, we present an optimized protocol for the isolation of LMSC from organ-cultured corneal samples by means of fluorescence-activated cell sorting (FACS), using CD90 as a selective marker (Polisetti et al., 2022).
Figure 1. Localization of limbal niche cells in situ. A. Triple immunostaining analysis of limbal tissue sections showing melanocytes [melan-A+ (red) vimentin+ (cyan) cells, arrow heads] in close contact with clusters of cytokeratin (CK)15+, CK14+, CK19+ (green) limbal epithelial progenitor cells (LEPC), whereas sub-epithelial stromal cells [vimentin+ cells (cyan), arrows] were in close association with basal limbal epithelial cells, and not with more superficial CK3+ cells (green). Dashed line represents the basement membrane (BM), and nuclear counterstaining was done with 4′,6-diamidino-2-phenylindole (DAPI, blue). B. Double immunostaining of limbal sections showing the co-localization of CD90 (green) and vimentin (cyan) in the sub-epithelial stromal cells (white arrows), which were in close association with basal layers of limbal epithelium (dotted line represents the BM), as well as blood vessels of the limbal stroma (yellow arrows). The limbal sections also show the co-localization of CD117 (green) and melan A (red) in the melanocytes (arrow heads) at the basal layer of the limbal epithelium. Nuclear counterstaining with DAPI (blue). C. Immunofluorescence analysis of cultured limbal clusters showing the expression of keratins (PCK, green) and vimentin (cyan) in epithelial cells, melan-A (red) and vimentin (cyan) expression in melanocytes (arrow heads), and only vimentin expression in stromal cells (arrows). Double immunostaining of cultured limbal clusters showing the CD90+ stromal cells (green, arrow) at the edge of clusters and also in between E-cadherin+ epithelial cells (red, dashed line represents the edge of the cluster), whereas melan-A+ melanocytes were located between the cells (red, arrow heads). Nuclear counterstaining with DAPI (blue). Reprinted from Polisetti et al. (2022), licensed under a CC BY 4.0.
Materials and Reagents
12-well plate (Corning, Costar®, catalog number:3513)
Micropipette tips (0.5–20 µL, 100–200 µL, 1,000 µL) (Greiner Bio-One)
60 mm cell culture dish (Corning, Falcon®, catalog number: 353004)
100 mm cell culture dish (Corning, Falcon®, catalog number: 353003)
Syringe filter 0.2 μm (VWR, catalog number: 28145-501)
Disposable Scalpel blades No. 10 (pfm Medical ag, Feather®, catalog number: 201000010)
Serological pipettes (5 mL, 10 mL) (Corning, StripetteTM)
15 mL conical tubes (Greiner Bio-One, catalog number:188271)
50 mL conical tubes (Greiner Bio-One, catalog number:227261)
T75 flasks (Corning, catalog number: CLS430641)
Reversible cell strainers (Stem Cell Technologies, catalog number:27215)
Cell filter 20 µm (Cell TricsTM, Sysmex Partec GmbH, catalog number:04-004-2325)
FACS tubes (5 mL polystyrene round-bottom tube, Falcon, catalog number: 352058)
Collagenase A (Sigma-Aldrich, Roche Diagnostics, catalog number: 10103578001)
Dulbecco’s Phosphate Buffered Saline (DPBS) (no calcium, no magnesium) (Thermo Fisher Scientific, GibcoTM, catalog number: 14190094)
0.25% Trypsin-EDTA (Thermo Fisher Scientific, Gibco®, catalog number: 25200056)
Dulbecco’s Modified Eagle Medium (DMEM) high glucose (Thermo Fisher Scientific, GibcoTM, catalog number: 11960044)
Fetal Bovine Serum (FBS) (Thermo Scientific, GibcoTM, catalog number: 10082147)
Penicillin-Streptomycin (Sigma-Aldrich, catalog number: P4333)
MesenCultTM MSC Basal Medium (Human) (Stemcell Technologies, catalog number: 05401)
MesenCultTM MSC Stimulatory Supplement (Human) (Stemcell Technologies, catalog number: 05402)
70% Ethanol
0.5 M EDTA (Invitrogen, catalog number: AM9260G)
CD11c-PE (Biolegend, catalog number: 337205)
CD14-PE (Biolegend, catalog number: 301805)
CD19-PE (Biolegend, catalog number: 302207)
CD44-PE (Biolegend, catalog number: 397503)
CD45-PE (Biolegend, catalog number: 304007)
CD73-PE (Biolegend, catalog number: 344003)
CD90-PE (Abcam, catalog number: 328109)
CD90-APC (BD biosciences, catalog number: 559869)
CD105-PE (Biolegend, catalog number: 323205)
Mouse IgG2a, k Isotype-APC (eBioscience, catalog number: 17-4724-81)
Mouse IgG2a, k Isotype-PE (Biolegend, catalog number: 400212)
Cytokeratin AE1/AE3 (DAKO, catalog number:M3515)
Melan-A (Abcam, catalog number: EPR20380)
Vimentin (R&D Systems, catalog number: MAB2105)
4′,6-diamidino-2-phenylindole (DAPI, Sigma-Aldrich, catalog number: MBD0015)
Collagenase solution (see Recipes)
Mesencult complete medium (see Recipes)
FACS Buffer (see Recipes)
Equipment
Pipette aid (BRAND, accu-jet® pro)
Micropipette (Eppendorf Research plus, P20, P200, P1000)
Forceps (Dumont, 5-Dumoxel®-H)
Hemocytometer (MARIENFELD, Neubauer, catalog number: 0640130)
Biosafety cabinet (Thermo ScientificTM, Type S2020 1.2)
CO2 incubator (Thermo ScientificTM, HeracellTM 240i)
Centrifuge (Thermo ScientificTM, Heraeus Multifuge 1S-R)
Phase contrast inverted microscope with a camera (ZEISS, Objectives 4×, 10×, 20×)
Freezer -20°C (Liebherr)
Refrigerator 2–8°C (Siemens)
FACS Aria II sorter (BD Biosciences)
Water bath (GFL®, catalog number: 1013)
Software
CapturePro 2.10.0.1 (JENOPTIC Optical systems GmbH)
FACSDiva software (BD Pharmingen, BD Biosciences)
FlowJo software (Tree Star)
Procedure
The dissection of limbus and preparation of limbal clusters is similar to the previously published procedure (Polisetti et al., 2019).
Dissection of limbus
Organ-cultured corneoscleral tissues, which are not suitable for transplantation due to low corneal endothelial cell density (<2,200 cells/mm2), or the presence of neurological disorders or malignancies in the donor, were obtained from the cornea bank with appropriate research consent and ethical approval. Donor cornea remnants after corneal endothelial transplant preparation are also a valuable source, if appropriate research consent has been obtained.
Place the organ-cultured corneoscleral tissue in a 60 mm culture dish, and wash twice with DPBS. Cut the tissue into four equal quarters, using a scalpel blade and forceps (see Video 1).
Note: For single preparation, use 4–6 corneoscleral tissues to get enough LMSC for downstream applications. Organ-cultured corneoscleral tissue used in this study was light pigmented donor limbal tissue obtained from donors with a mean age of 69.8 ± 10.7 years, and the culture duration was 24.0 ± 4.9 days, after the postmortem time of 33.54 ± 17.4 h.
Make incisions at 1 mm before and beyond the anatomical limbus to get limbal segments (see Video 1). The limbal segments are further dissected into 2–3 segments, as shown in the video.
Video 1. Limbal cell isolation
Isolation of limbal mesenchymal stromal cells
Place the limbal segments in a 60-mm dish containing 5 mL of collagenase A (2 mg/mL), and cut the limbal segments into smaller pieces (2–3 pieces) with a scalpel blade. Incubate at 37°C with 5% CO2 overnight, to digest the stromal collagen and obtain limbal cell clusters.
After incubation, triturate the suspension inside the dish with an up and down motion using a 1-mL pipette (P1000), and observe for the presence of cell clusters and single cells in the microscope (Figure 2B). The cell clusters are supposed to consist of limbal epithelial cells, stromal, and melanocyte niche cells (as shown in Figure 1C).
Note: In case of incomplete digestion of limbal segments after overnight incubation and trituration, re-incubate in the same solution at 37°C with 5% CO2 for an additional 2 h to achieve complete digestion. On the contrary, over-digestion of tissue (more than 20 h) might adversely affect cell viability and the quality of cells.
Figure 2. Isolation of limbal cluster cells. A. The corneal scleral rim (left) was cut into sectors, and each sector was trimmed off 1 mm before and after the limbal region (right). Reprinted from Polisetti et al. (2019), licensed under a CC BY 4.0. B. Different sizes of limbal clusters and single cells (left) formed after overnight incubation of limbal segments in collagenase solution (x40 magnification). C. Limbal clusters separated from single cells after filtration. D. Single cell suspension of limbal cells after digestion of limbal clusters with trypsin-EDTA (x40 magnification).
Separate limbal cell clusters from single cells using cell filters with a pore size of 20 µm that enable single cells to pass through the cell filter and the clusters to be retained. Wash the filters twice with DPBS, to remove any remaining single cells. Reverse the strainer and place it on a 60 mm dish. Add 0.25% trypsin-EDTA (5 mL) to flush clusters (Figure 2C) into a petri dish, and incubate at 37°C for 10–15 min, to dissociate the clusters into single cells.
Note: In place of 20 µm cell filters, 37 µm reversible cell strainers can be used. The single cell suspension obtained after filtration can either be discarded or used for other purposes, such as to obtain limbal fibroblasts.
After incubation, triturate the cell suspension with an up and down motion with a 1-mL pipette. Observe the cell suspension under the microscope (Figure 2D). Inhibit trypsin digestion by adding 5 mL of pre-warmed DMEM (37°C in water bath) containing 10% FBS. Transfer the cell suspension into a 15-mL Falcon tube, and centrifuge at 200 × g for 5 min.
Note: In case of incomplete dissociation of clusters after 15 min incubation and trituration, re-incubate in the same solution at 37°C with 5% CO2 for an additional 5 min to achieve complete dissociation. On the contrary, prolonged dissociation of clusters might adversely affect cell viability and the quality of cells.
After centrifugation, resuspend the cell pellet by pipetting up and down using a P200 pipette in 200 µL of FACS buffer (see Recipe 3).
Fluorescence Activated Cell Sorting (FACS)
Transfer the cell suspension to FACS tubes (100 µL/tube) and add a mouse APC-conjugated anti-human CD90 antibody (5 µL/106 cells) to one tube, and an IgG2a-Isotype APC to another tube at 4°C. Gently vortex the samples, and incubate on ice for 45 min, tapping at 15 min intervals.
Note: If the cell number is high, i.e., more than 106 cells, adjust the volumes and concentration of antibody accordingly.
After incubation, add 1 mL of FACS buffer to each FACS tube, and centrifuge the cells at 400 × g for 5 min. Repeat the washing twice.
After washing, add 500 µL of FACS buffer containing DAPI (1:5000), to exclude dead cells, and proceed to flow sorting using a FACS Aria II sorter (Polisetti et al., 2022).
The gating strategy is shown below (Figure 3).
Figure 3. Fluorescence activated cells sorting (FACS) images demonstrating the gating strategy used to isolate limbal mesenchymal stromal cells. Forward scatter (FSC-A) vs. side scatter (SSC-A) graph showing the cells of interest selected on the basis of size and granularity (i). Side scatter area vs. width graph showing the selection of single cells by excluding doublets or clumps, (ii) followed by dead cell exclusion using 4′,6-diamidino-2-phenylindole DAPI (iii). The isotype control graph shows the set of gates (iv) used to select the CD90+ cells (iv). Percentages (%) of positive cells are expressed as the means ± SEM.
Expansion of limbal mesenchymal stromal cells
Seed the sorted CD90+ LMSC onto a well of a 12-well plate.
Note: The number of CD90+ cells per limbus (150–900) varies from sample to sample. The CD90- populations mainly contain LEPC, and can be used to enrich LEPC, using cell type-specific media (Polisetti et al., 2020).
Cultivate the LMSC at 37°C with 5% CO2 in Mesencult complete medium to expand LMSC. Change media every 2 days.
Visualize the morphology of LMSC by phase-contrast microscopy. LMSC appear as spindle-shaped, elongated cells with prominent nucleoli (Figure 4).
Figure 4. Phase contrast images showing the spindle shaped, elongated with prominent nucleolus of CD90+ cells after day 3, 5, and 10 of seeding [×40 magnification (upper row); ×100 magnification (bottom row)].
Sub-cultivation of limbal mesenchymal stromal cells
Remove the media from the culture vessel at 70 to 80% confluency.
Wash the cells using DPBS, and add 1 mL of trypsin-EDTA (0.25%; pre-warmed at 37°C in a water bath). Incubate at 37°C with 5% CO2 for 5 min.
After incubation, add 2 mL of DMEM containing 10% FBS to inhibit trypsin action, and mix well.
Transfer the cell suspension to a 15-mL tube, and centrifuge at 200 × g for 5 min. Resuspend the cell pellet in Mesencult medium, and count the total cell number using a hemocytometer.
Use cells for the application of choice or for subculturing.
Note: Over-confluence (more than 80%) and prolonged trypsin digestion (more than 5 min) adversely affect cell viability and the quality of cells during sub-culturing. Always passage cells at 70 to 80% confluence. Avoid prolonged incubations in trypsin.
To evaluate the LMSC characteristics, phenotypic profile, colony forming efficiency, growth characteristics and differentiation potential have been tested (Figure 5). Please refer to the published article for the detail protocols (Polisetti et al., 2022).
Data analysis
The conditions provided in this protocol have been optimized to isolate and expand LMSCs. A detailed analysis of the isolation and expansion of the LMSCs can be found in Polisetti et al. (2022).
Figure 5. Phenotypic profile and functional characterization of CD90+ (LMSC) cells. A. Flow cytometry analysis showing the expression of CD markers. Percentage of cells expressed as mean ± SEM of four individual experiments. B. Graphs showing the population doublings [log10(y/x)/log102, where y is the final density of the cells, and x is the initial seeding density of the cells], population doubling time [(t − t0)log2/(logy – logx), where t, t0 represents the time at cell counting, y equals the number of cells at time t, and x equals the number of cells at time t0], growth rate [ln(Nt/No)/t, where Nt represents final cell number, No represents the initial cell number, and t equals the number of days in culture], and proliferation potential of LMSC over the passages. Data are expressed as means of five individual experiments. C. Phase contrast micrograph showing the LMSC colony (i), and T75 flask showing crystal violet stained colonies of LMSC (ii). The graph represents the colony forming efficiency of LMSC over the passages. Percentage of colonies expressed as means ± standard deviation (n = 5). D. Immunostaining analysis showing the expression of fatty acid binding protein 4 (FABP4), osteocalcin, and aggrecan in adipogenic, osteogenic, and chondrogenic induced cells, respectively. No staining has been seen for FABP4 in undifferentiated (UD) controls, but weak staining was observed for osteocalcin and aggrecan in UD controls. Nuclear counterstaining with DAPI (blue).
Reprinted from Polisetti et al. (2022), licensed under a CC BY 4.0.
Recipes
Collagenase solution (2 mg/mL)
Reagent Collagenase A
Components and Preparation 500 mg Collagenase A
220 mL of DMEM High Glucose
25 mL of fetal calf serum
5 mL of Penicillin-Streptomycin
Mix well by inverting
Method of Sterilization Sterile Filter (0.2 µm)
Note Prepare 10 mL aliquots
Storage -20°C
MesenCult Medium
Medium MesenCultTM medium complete
Components and Preparation 450 mL of MesenCultTM MSC Basal Medium
0 mL of MesenCultTM MSC Stimulatory Supplement
5 mL of Penicillin-Streptomycin
Mix well by inverting
Method of Sterilization None
Note Prepare aliquots if needed
Storage 1 month at 2–8°C
FACS buffer (2% FBS and 0.5mM EDTA in DPBS)
Components and Preparation 1 mL of FBS
25 µL of 0.5 M EDTA
24 mL of DPBS
Mix well by inverting
Method of Sterilizaton None
Note Always use fresh
Acknowledgments
This protocol was adapted from previous work (Polisetti et al., 2022).
Competing interests
The authors declare that they have no competing interests.
References
Al-Jaibaji, O., Swioklo, S. and Connon, C. J. (2019). Mesenchymal stromal cells for ocular surface repair. Expert Opin Biol Ther 19(7): 643-653.
Chen, S. Y., Hayashida, Y., Chen, M. Y., Xie, H. T. and Tseng, S. C. (2011). A new isolation method of human limbal progenitor cells by maintaining close association with their niche cells. Tissue Eng Part C Methods 17(5): 537-548.
Chen, S. Y., Han, B., Zhu, Y. T., Mahabole, M., Huang, J., Beebe, D. C. and Tseng, S. C. (2015). HC-HA/PTX3 Purified From Amniotic Membrane Promotes BMP Signaling in Limbal Niche Cells to Maintain Quiescence of Limbal Epithelial Progenitor/Stem Cells. Stem Cells 33(11): 3341-3355.
Dziasko, M. A., Armer, H. E., Levis, H. J., Shortt, A. J., Tuft, S. and Daniels, J. T. (2014). Localisation of epithelial cells capable of holoclone formation in vitro and direct interaction with stromal cells in the native human limbal crypt. PLoS One 9(4): e94283.
Funderburgh, J. L., Funderburgh, M. L. and Du, Y. (2016). Stem Cells in the Limbal Stroma. Ocul Surf 14(2): 113-120.
Ghareeb, A. E., Lako, M. and Figueiredo, F. C. (2020). Recent Advances in Stem Cell Therapy for Limbal Stem Cell Deficiency: A Narrative Review. Ophthalmol Ther 9(4): 809-831.
Gonzalez, G., Sasamoto, Y., Ksander, B. R., Frank, M. H. and Frank, N. Y. (2018). Limbal stem cells: identity, developmental origin, and therapeutic potential. Wiley Interdiscip Rev Dev Biol 7(2).
González, S. and Deng, S. X. (2013). Presence of native limbal stromal cells increases the expansion efficiency of limbal stem/progenitor cells in culture. Exp Eye Res 116: 169-176.
Li, G. G., Zhu, Y. T., Xie, H. T., Chen, S. Y. and Tseng, S. C. (2012). Mesenchymal stem cells derived from human limbal niche cells. Invest Ophthalmol Vis Sci 53(9): 5686-5697.
Li, G., Zhang, Y., Cai, S., Sun, M., Wang, J., Li, S., Li, X., Tighe, S., Chen, S., Xie, H. and Zhu, Y. (2018). Human limbal niche cells are a powerful regenerative source for the prevention of limbal stem cell deficiency in a rabbit model. Sci Rep 8(1): 6566.
Li, Y., Inoue, T., Takamatsu, F., Kobayashi, T., Shiraishi, A., Maeda, N., Ohashi, Y. and Nishida, K. (2014). Differences between niche cells and limbal stromal cells in maintenance of corneal limbal stem cells. Invest Ophthalmol Vis Sci 55(3): 1453-1462.
Nakatsu, M. N., Gonzalez, S., Mei, H. and Deng, S. X. (2014). Human limbal mesenchymal cells support the growth of human corneal epithelial stem/progenitor cells. Invest Ophthalmol Vis Sci 55(10): 6953-6959.
Ordonez, P. and Di Girolamo, N. (2012). Limbal epithelial stem cells: role of the niche microenvironment. Stem Cells 30(2): 100-107.
Polisetti, N., Giessl, A., Zenkel, M., Heger, L., Dudziak, D., Naschberger, E., Stich, L., Steinkasserer, A., Kruse, F. E. and Schlotzer-Schrehardt, U. (2021). Melanocytes as emerging key players in niche regulation of limbal epithelial stem cells. Ocul Surf 22: 172-189.
Polisetti, N., Schlunck, G., Reinhard, T., Kruse, F. E. and Schlotzer-Schrehardt, U. (2020). Isolation and ex vivo Expansion of Human Limbal Epithelial Progenitor Cells. Bio-protocol 10(18): e3754.
Polisetti, N., Sharaf, L., Schlotzer-Schrehardt, U., Schlunck, G. and Reinhard, T. (2022). Efficient Isolation and Functional Characterization of Niche Cells from Human Corneal Limbus. Int J Mol Sci 23(5).
Polisetti, N., Zenkel, M., Menzel-Severing, J., Kruse, F. E. and Schlotzer-Schrehardt, U. (2016). Cell Adhesion Molecules and Stem Cell-Niche-Interactions in the Limbal Stem Cell Niche. Stem Cells 34(1): 203-219.
Polisetty, N., Fatima, A., Madhira, S. L., Sangwan, V. S. and Vemuganti, G. K. (2008). Mesenchymal cells from limbal stroma of human eye. Mol Vis 14: 431-442.
Rama, P., Ferrari, G. and Pellegrini, G. (2017). Cultivated limbal epithelial transplantation. Curr Opin Ophthalmol 28(4): 387-389.
Shortt, A. J., Secker, G. A., Munro, P. M., Khaw, P. T., Tuft, S. J. and Daniels, J. T. (2007). Characterization of the limbal epithelial stem cell niche: novel imaging techniques permit in vivo observation and targeted biopsy of limbal epithelial stem cells. Stem Cells 25(6): 1402-1409.
Veréb, Z., Póliska, S., Albert, R., Olstad, O. K., Boratkó, A., Csortos, C., Moe, M. C., Facskó, A. and Petrovski, G. (2016). Role of Human Corneal Stroma-Derived Mesenchymal-Like Stem Cells in Corneal Immunity and Wound Healing. Sci Rep 6: 26227.
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Peer-reviewed
Binding Affinity Quantifications of the Bacteriophage Mu DNA Modification Protein Mom Using Microscale Thermophoresis (MST)
SU Shubha Udupa
VN Valakunja Nagaraja
SK Shweta Karambelkar
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4472 Views: 2027
Reviewed by: ASWAD KHADILKARMarc-Antoine Sani Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Nucleic Acids Research Jun 2020
Abstract
Epigenetic modifications play diverse roles in biological systems. Nucleic acid modifications control gene expression, protein synthesis, and sensitivity to nucleic acid-cleaving enzymes. However, the mechanisms underlying the biosynthesis of nucleic acid modifications can be challenging to identify. Studying protein-ligand interactions helps decipher biosynthetic and regulatory pathways underlying biological reactions. Here, we describe a fluorescence labeling-based quantitative method for unraveling the biomolecular interactions of bacteriophage Mu DNA modification protein Mom with its ligands, using microscale thermophoresis (MST). Compared to traditional methods for studying protein-biomolecular interactions, MST requires significantly lower sample amounts, volumes, and analysis time, thus allowing screening of a large number of candidates for interaction with a protein of interest. Another distinguishing feature of the method is that it obviates the need for protein purification, often a time- and resource-consuming step, and works well with whole or partially purified cell extracts. Importantly, the method is sensitive over a broad range of molecular affinities while offering great specificity and can be used to interrogate ligands ranging from metal ions to macromolecules. Although we established this method for a DNA modification protein, it can easily be adapted to study a variety of molecular interactions engaged by proteins.
Keywords: Microscale thermophoresis (MST) Kd-dissociation constant Bacteriophage Mu mom DNA modification GNAT fold Fe2+/3+-binding Acetyl coenzyme A (acetyl CoA) Anti-restriction
Background
[Background] Biological background: Biological entities have evolved a plethora of epigenetic modifications in their nucleic acids, ranging from simple methylation to complex moieties derived from sugars, amino acids, polyamines, and other cellular metabolites (Boccaletto et al., 2018; Sood et al., 2019). Epigenetic modifications regulate gene expression, mRNA translation, and cellular stress responses, and protect bacteriophages from DNA-damaging immune systems of bacterial hosts (Kahmann, 1983; Hattman, 1999; Choi et al., 2014; Gu et al., 2014; Reynolds et al., 2014; Bryson et al., 2015; Hutinet et al., 2019). The ability to target nucleic acid modifications has broad applications in designing antibiotics and antifungal strategies through the impairment of modification pathways unique and essential to pathogens (Koh and Sarin, 2018). Similarly, the fields of phage therapy and microbiome engineering stand to benefit from the discovery of DNA modification pathways that can protect the DNA payload from a wide range of host immune systems. Novel DNA modifications are constantly being discovered in phages, presenting new puzzles surrounding their biosynthesis and function (Lee and Weigele, 2021; Lee et al., 2022). Studying molecular interactions opens a window into the inner workings of macromolecules, cells, and underlying mechanistic and regulatory pathways (Corbeski et al., 2018; Karambelkar et al., 2020). Here, we describe interaction studies of the DNA modification protein Mom in the context of its metal ion and small molecule cofactor interactions (Karambelkar et al., 2020) using the technique of microscale thermophoresis (MST).
Technical background: MST offers a simple method to quantitatively investigate protein-ligand interactions, and is based on thermophoresis, the movement of molecules across thermal gradients (Jerabek-Willemsen et al., 2011). Ligand-induced changes in size, charge, hydration shell, or conformation of a macromolecule alter its thermophoretic movement (Jerabek-Willemsen et al., 2011). Using a titration approach, MST enables the measurement of affinity constants of a wide variety of interactions in the binding equilibrium (Karambelkar et al., 2020; Osuna et al., 2020a, 2020b). MST requires extremely small sample amounts compared to conventional methods like isothermal calorimetry (ITC) or surface plasmon resonance (SPR), obviates ligand immobilization, and works over a broad range of binding affinities.
Another notable strength of MST over conventional approaches is its compatibility with complex mixtures and cell extracts (Lippok et al., 2012; Khavrutskii et al., 2013; Bartoschik et al., 2018). The ability to fluorescently tag a specific his-tagged protein of interest in a complex mixture of proteins, as highlighted in this protocol, not only obviates protein purification, often a rate limiting and cumbersome step, but also provides high sensitivity for detecting interactions in a near-native environment (Bartoschik et al., 2018).
Although MST measurements can be performed using intrinsic fluorescence of proteins (Seidel et al., 2012), labeling of the target proteins with a suitable fluorophore is required when using complex samples (Bartoschik et al., 2018). In routine labeling techniques for MST, fluorophores are covalently attached to lysine residues using NHS- or to cysteine residues using maleimide chemistry. However, these labeling methods require purified proteins and cannot be applied to a mixture of proteins. Moreover, it is not possible to predict where the fluorophore will bind to the protein—inhomogeneous protein-dye conjugates might even display destabilization, loss of functionality, or steric hindrance at the ligand binding site (Lindhoud et al., 2012). The above limitations are overcome by the selective and site-specific labeling of a protein of interest in a complex mixture. This can be achieved in various ways, such as by expressing in vivo a fusion of the protein of interest with a fluorescent protein like GFP (Khavrutskii et al., 2013; Magnez et al., 2017; Gao et al., 2021). However, such relatively large tags are not always desired for quantitative interaction analysis and also require the cloning of a suitable linker and fluorescence tag. Various other site-specific labeling strategies have been demonstrated, such as co-translational introduction of unnatural or modified amino acids, or labeling via specific amino acid sequences, including His-tags and tetracysteine motifs (Griffin et al., 1998; Krishnan et al., 2007; Nienberg et al., 2016). Among these, the His-tag is the most convenient, popular, and widely used affinity tag for purification, immobilization, or detection of proteins.
The tris-NTA/His-tag system comprises one of the smallest high-affinity recognition elements known to date (Braner et al., 2016). Fast, stoichiometric binding of tris-NTA conjugates enables in situ protein labeling of His-tagged proteins, making the system suitable for quantitative protein interaction analysis by MST (Lata et al., 2005). Because the tris-NTA/His-tag labeling is based on non-covalent coordinate bonds with the transition metal ion Ni(II), it is sensitive to reagents that compete or interfere with the labeling (Table 1).
Materials and Reagents
Protein Purification
15 mL Bioruptor TPX tubes (Diagenode, catalog number: NC1463349)
10 kDa dialysis membrane (Sigma-Aldrich, catalog number: 0530-100FT)
Isopropyl-β-D-thiogalactoside (Sigma-Aldrich, catalog number: 11411446001)
Lysozyme (Sigma-Aldrich, catalog number: L6876)
Phenylmethanesulfonyl fluoride (PMSF) (Sigma-Aldrich, catalog number: P7626)
Poly(ethyleneimine) (Sigma-Aldrich, catalog number: P3143)
NaCl (Sigma-Aldrich, catalog number: 746398)
Sodium phosphate dibasic (Sigma-Aldrich, catalog number: S5136)
Sodium phosphate monobasic (Sigma-Aldrich, catalog number: S3139)
EDTA (Sigma-Aldrich, catalog number: E5134)
2-Mercaptoethanol (Sigma-Aldrich, catalog number: M3148)
HEPES (Affymetrix USB, catalog number:16928)
Ammonium sulfate (Sigma-Aldrich, catalog number: A4418)
Cellulose phosphate (Sigma-Aldrich, catalog number: C3145)
Trizma base or Tris base (Sigma-Aldrich, catalog number: T6066)
NaOH (SDFCL, catalog number: 20252KO5)
HCl (Qualigens, catalog number: Q29147)
Amicon Ultra-15 centricon10 kDa NMWCO (Millipore, catalog number: UFC901008)
Bovine serum albumin (BSA), analytical standard (Millipore Sigma, catalog number: P5619)
Lysis buffer (see Recipes)
Phosphocellulose binding buffer (see Recipes)
Wash buffer 1 (see Recipes)
Wash buffer 2 (see Recipes)
Elution buffer (see Recipes)
Storage buffer (see Recipes)
MST Experiment
PCR plates (Axygen, catalog number: 14-222-320)
Ammonium Iron(II) sulfate (Sigma-Aldrich, catalog number: 09719)
Acetyl Coenzyme A (Sigma-Aldrich, catalog number: A2056)
MonolithTM NT.115 Series, Premium Capillaries (NanoTemper Technologies GmbH, catalog number: MO-K025–200 Count)
Monolith His-Tag Labeling Kit RED-Tris-NTA (NanoTemper Technologies GmbH, catalog number: MO-L008)
MST buffer (see Recipes)
1× PBS-T (see Recipes)
Equipment
Incubator (New Brunswick Scientific Innova 4230)
Bioruptor® Sonicator (Diagenode UCD 300)
Centrifuge (Kubota 6500)
Ultracentrifuge (Beckman L8-70M)
Magnetic Stirrer (IKA Big Squid)
Peristaltic pump (Pharmacia LKB pump P-1)
Pipettes (GilsonTM PIPETMAN ClassicTM Pipets P2, 20, 200, and 1000) (Gilson, catalog numbers: F144801, F123600G, F123601G, and F123602G)
Monolith NT.115 instrument (NanoTemper Technologies GmbH)
Software
MO.Control 2 from Nanotemper Technologies (https://nanotempertech.com/monolith-mo-control-software/)
MO.Affinity Analysis 3 from Nanotemper Technologies (https://nanotempertech.com/monolith/monolith-nt115/)
GraphPad Prism 5 version 5.03 (https://www.graphpad.com/scientific-software/prism/)
Procedure
Partial purification of His-tagged Mom for MST assays
Cell extract preparation
Note: Perform all steps at 4°C or on ice. Aliquot samples at each step for SDS PAGE analysis (Figure 1).
Resuspend 2 g of cell pellet (Escherichia coli C41 expressing Mom, Figure 1, lanes 1–2) in 12 mL of lysis buffer (see Recipe 1). Add PMSF to a final concentration of 1 mM.
Pre-cool the Diagenode Bioruptor. Distribute 2 mL of the cell suspension into six 15 mL TPX tubes and sonicate using at a high power setting for 20 cycles (30 s on, 45 s off).
Centrifuge the sonicated extract for 2 h at 4°C at 100,000 × g in the ultracentrifuge. The supernatant and pellet obtained after the spin are referred to as S100 supernatant and S100 pellet, respectively (Figure 1, lanes 3–4).
Figure 1. Partial purification of his-tagged wild-type (WT) and mutant Mom proteins for microscale thermophoresis (MST). His-tagged WT Mom (Upper panel), R101A Mom (middle panel), and Y149A Mom (lower panel) were overexpressed in E. coli C41 pNC1 cells and partially purified as follows. Crude cell extracts of uninduced (lane 1) and IPTG-induced (lane 2) cultures were subjected to ultracentrifugation at 100,000 × g, and the supernatant (lane 3) and pellet fractions (lane 4) analyzed. Nucleic acids were removed from the S100 supernatant using PEI precipitation (lanes 5–6), and cellular proteins were fractionated using 0–35% and 35–65% ammonium sulfate cuts (lanes 7–8). His-tagged Mom protein in various stages of purification is indicated using red arrowheads, and purified non-his-tagged Mom protein was loaded in lane 9. Buffer exchange was carried out to remove ammonium sulfate from the Mom-containing ammonium sulfate fraction (35–65%, lane 10), and the dialyzed fraction was loaded on PC column. Flowthrough fraction (lane 11) was collected, and the column washed to remove weakly bound protein (lanes 12–13). Elution was carried out with a high salt buffer (lanes 14–16). For protein quantitation using densitometry, PC elutions were dialyzed and concentrated; 1 μL, 2 μL, 4 μL, 8 μL, and 10 μL (lanes 17–21) of the concentrated protein were loaded alongside known amounts (100, 200, 400, and 800 ng) of BSA standard (lanes 22–25) and Genetix 3 color prestained protein marker (Lane 26). Samples were analyzed on 15% SDS PAGE gels.
Removal of nucleic acids
Add polyethyleneimine (PEI) pH 7.4 dropwise to the S100 supernatant from the above step to a final concentration of 1% while continuously stirring on a magnetic stirrer.
Centrifuge the resulting suspension at 20,000 × g for 10 min in Kubota centrifuge to precipitate PEI-nucleic acid complexes (Figure 1, lane 6).
Decant the supernatant (referred to as the PEI supernatant, Figure 1, lane 5) into a fresh tube.
Fractionation of cellular proteins
Ammonium sulfate precipitation is a technique used for fractionation of cellular proteins. It is based on an effect termed salting-out, wherein at higher salt concentrations, protein solubility usually decreases, leading to precipitation (Green and Hughes, 1995). Because precipitation is due to reduced solubility and not denaturation, pelleted protein can be readily resolubilized using standard buffers. After removal of ammonium sulfate using dialysis, the protein is well suited for further chromatographic fractionation or purification procedures.
Fractionate the PEI supernatant from the above step using two ammonium sulfate saturation cuts, 0–35% and 35–65% (Wingfield, 2001), as follows.
For 0–35% saturation, weigh the required amount of ammonium sulfate crystals and slowly, grain by grain, add it to the PEI supernatant while stirring it constantly on a magnetic stirrer, allowing the salt to dissolve completely.
After the appearance of a precipitate, incubate the suspension on ice for 10 min and centrifuge for 20,000 × g for 15 min at 4°C.
Collect the supernatant and subject it to 35–65% ammonium sulfate saturation as above. The pellets obtained after the ammonium sulfate precipitation (Figure 1, lanes 7–8) can be stored on ice overnight at 4°C.
Phosphocellulose activation/equilibration
Add 1 g of cellulose phosphate P1 swells to 3–4 mL resin. Wash approximately 25 g of phosphocellulose powder with 25 volumes of MilliQ water.
For all the washing steps, gently stir the resin by swirling it in a 1 L beaker and allowing it to stand for 10 min, followed by decanting the liquid. Wash volumes are calculated with respect to the dry weight of phosphocellulose processed, such that volume here is 25 × 25 = 625 mL.
Wash the resin with 10 volumes each of 95% and 50% distilled ethanol.
Subsequently, wash the resin with 25 volumes of 0.5 N NaOH.
Thereafter, wash the resin with 75–100 volumes of Milli Q water, until the pH of the decanted liquid is less than 10.
Add 25 volumes of 0.5 N HCl to resin and stir well. Allow the resin to settle for exactly the same time as in step 4.
Next, wash the resin with 75 volumes of MilliQ water.
Phosphocellulose chromatography
Resuspend the 35–65% ammonium sulfate pellet, which is enriched in Mom protein, in phosphocellulose binding buffer (see Recipe 2), and dialyze against 1 L phosphocellulose binding buffer, with two changes of the dialysis buffer over 3 h.
Centrifuge the dialyzed suspension at 20,000 × g for 10 min at 4°C.
Apply the supernatant (Figure 1, lane 10) onto a 50 mL pre-equilibrated phosphocellulose column using a peristaltic pump at a flow rate of 2.5–5.0 mL/min. Collect the flow-through (Figure 1, lane 11) and load it back on the column. Repeat this step two more times to ensure complete binding of Mom to resin.
Wash the resin with 3 column volumes each of wash buffers 1 and 2 (see Recipes 3 and 4) (Figure 1, lanes 12–13).
Elute Mom with 0.5 column volumes of high salt elution buffer (see Recipe 5) (Figure 1, lanes 14–16).
Dialyze the eluted protein against storage buffer (see Recipe 6) and concentrate using Amicon Ultra-15 with a 10 kDa MWCO membrane.
Aliquot the concentrated protein, snap freeze in liquid nitrogen, and store at -80°C.
Protein quantitation
Purified proteins were quantitated using SDS-PAGE densitometry. SDS PAGE-based protein quantitation, unlike spectrophotometric methods like the Bradford assay, carries the advantage of quantitating a specific protein of interest in a complex mixture of proteins and hence is more reliable for estimating protein concentrations for MST. A 2 mg/mL stock of BSA standard prepared in water was further diluted to 10 ng/μL, 20 ng/μL, 40 ng/μL, and 80 ng/μL; 10 μL of each of the dilutions was loaded in the gel (Figure 1, lanes 22–25) alongside a series of two-fold increasing volumes (1 μL, 2 μL, 4 μL, 8 μL,10 μL) of test sample (Figure 1, lanes 17–21). Concentration of the protein of interest within the test sample was estimated by comparing densities of the specific band of interest with those of the BSA standards.
MST Protocol
Labeling the protein with fluorescent dye
The instructions for this step are based on using the Red-Tris-NTA dye and consumables from NanoTemper Technologies. The Monolith NT His-tag Labeling Kit facilitates site-specific, purification-free labeling of small amounts of His-tagged proteins with the NT647 fluorescent dye. The kit can be used for the labeling of any protein or peptide carrying a polyhistidine tag (at least six histidines), and labeling can be completed within 30 min. The dye binds efficiently (subnanomolar affinity) to His-tags, and near-complete binding of the dye to His-tagged proteins obviates further purification steps or excess dye removal. Moreover, the specificity for His-tags allows for the method to work well with impure or partially purified protein preparations. An alternate approach to using the Tris-NTA dye is to tag the protein of interest with a fluorescent tag, e.g., GFP, in which case no further labeling should be required. Note that the dye (or tag) must be compatible with the filters installed in the Monolith instrument and that the dye or tag should not block any potential ligand-binding sites.
Some buffer components–e.g., imidazole, poly-His-tagged ligands, histidine, ATP, reducing agents like TCEP, DTT, and 2-Mercaptoethanol–might interfere with the labeling reaction, and their concentrations should not exceed the limits specified by Nanotemper (Table 1).
Add 8.0 mL of water to the vials containing 5× PBS-T to obtain 1× PBS-T (see Recipe 8)
Suspend 250 pmol RED-Tris-NTA dye in 50 μL of PBS-T to obtain a 5 μM dye solution.
Prepare a 100 nM dye solution by mixing 2 μL of dye (5 μM) and 98 μl 1× PBS-T.
Adjust the protein concentration to 200 nM in a volume of 100 μL.
Note: Protein concentration should be estimated using band densitometry on a Coomassie blue-stained SDS gel, and is particularly important when quantifying protein of interest in cell extracts or partially purified protein preparations.
Mix 100 μL of protein (200 nM) with 100 μL of dye (100 nM).
Incubate for 30 min at room temperature.
Centrifuge the sample for 10 min at 4°C and 15, 000 × g.
Note: This step is crucial in reducing the noise in the MST data. Noise in the MST data can result from precipitation or aggregation of proteins. Aggregation can occur owing to intrinsic instability of proteins or due to the absence of interacting partners, stabilizing agents, or optimal buffer conditions (unlike in a native cellular environment).
The protein is labeled and ready for the binding assay.
Table 1. Compatibility of Tris-NTA dye with commonly used buffer components (as recommended by Nanotemper Technologies).
Compound Maximum allowed concentration
Histidine 1 mM
Imidazole 1 mM
EDTA 0.5 mM
TCEP* 0.5 mM
DTT 5 mM
β-mercapto-ethanol** 1 mM
GSH 10 mM
GTP, GDP 1 mM
AMP, ADP, ATP 5 mM
Glycerol 10 %
Zn2+, Co2+, Cu2+ preloaded protein only***
Polyhistidine-tagged ligand None
* NanoTemper Technologies recommends avoiding the use of TCEP with red dyes in general.
**We found that 7 mM β-mercapto-ethanol was compatible with our microscale thermophoresis (MST) assays
*** Zn2+, Co2+, and Cu2+ ions compete for the binding with RED-tris-NTA. Because of that, only low nanomolar concentrations of listed ions are tolerated.
Binding assay
Prepare serial dilutions of ligand in PCR tubes or plates
Prepare 25 μL of the ligand at 2× concentration (e.g., for a final concentration of 5 mM, prepare the ligand at a concentration of 10 mM).
Note: The highest ligand concentration in the binding reaction should be at least 20× the Kd to cover enough data points in the saturation as well as in the baseline of the binding curve. For instance, the measured binding affinities of Mom for Fe2+/3+ and acetyl coenzyme A were in the 10–100 μm range, and to have a satisfactory binding curve, the ligands were prepared at concentrations of 1 mM and 10 mM, respectively, in MST buffer. In cases where the binding affinity is completely unknown, a few ligand concentration ranges can be empirically tested based on assumed Kd values. Refer to the NanoTemper Technologies Concentration Finder tool for the ligand concentration range estimation.
Add 10 μL of PBS-T into the PCR tubes 2–16.
Transfer 20 μL of the ligand into PCR-tube 1.
Transfer 10 μL of the ligand from PCR-tube 1 to PCR-tube 2 with a pipette and mix by pipetting up and down multiple times. Transfer 10 μL to PCR-tube 3 and mix. Repeat the procedure for PCR-tube 4–16. Discard the extra 10 μL from PCR-tube 16.
Add 10 μL of labeled protein to each well (1–16) and mix by pipetting. The final target protein concentration is 50 nM. This concentration should be used for the calculation of the Kd value. Incubate the samples at room temperature for 5 min.
Note: Inclusion of 2-Mercaptoethanol at a final concentration of 7 mM in the binding buffer reduced noise in the data. Also, the use of premium coated capillaries instead of standard capillaries solved the problem of protein sticking to the capillary glass surface. Spinning the samples at 15,000 × g for 10 min after the labeling also reduced data noise.
Load the capillaries and start sample measurement at 25°C using 40% LED power and medium MST power. For each measurement, repeat experiments three times and carry out data analysis using NanoTemper MO analysis software.
Notes:
Recommended settings are 40% LED and a medium MST power. At the final dye concentration of 25 nM, the expected fluorescence intensity at LED 40% is around 300 counts on a Monolith NT.115.
The concentration of the labeled protein should be lower than your expected Kd. The labeled protein can be diluted to 10 nM. With an LED power of 100%, fluorescence intensities of 200–250 counts are typically achieved. Nanotemper Technologies does not recommend working with fluorescent intensities < 200 counts for MST measurements.
Data analysis
The MO control software first performs a capillary scan to ensure that the concentration is within the detection limits and if the protein is sticking to the capillary walls, as evidenced by shoulders or double peaks in the capillary scan traces instead of a smooth, symmetrical curve (Figure 2).
Note: If the protein is sticking to the capillaries, optimize the binding conditions by adding detergents or additives such as Tween-20, 2-Mercaptoethanol, BSA, or changing the pH or ionic strength of your buffer, changing to a different buffer, or using the premium coated capillaries. For all Mom-ligand interaction measurements, premium coated capillaries were used, and the binding buffer included 2-Mercaptoethanol at a final concentration of 7 mM.
Figure 2. Capillary scan, microscale thermophoresis (MST) traces, and dose response of a representative experiment. Typical output of a representative MST experiment run using the MO control software is shown. A typical acquisition runs for 10 min.
Data analysis was carried out using the MO.Affinity Analysis program (NanoTemper). Three replicates were merged to form one dataset.
Select the appropriate binding model. The Kd model is suitable for the vast majority of investigated interactions, while the Hill model is useful when the investigated interaction is known to be cooperative. We selected the Kd model, which is the standard fitting model derived from the law of mass action.
Tick the ‘TargetConc’ box to fix the concentration of the fluorescently labeled to 50 nM or other if diluted.
The program will compute the Kd value and the associated confidence. Within a confidence of 68%, Kd is within the given range. The lower this number, the more confident one can be about the given Kd.
MST evaluation strategy can be selected to default or manual to evaluate data along with either default or custom time points along the MST trace.
Inspect the binding curve. A signal-to-noise ratio of more than 5 is desirable, while more than 12 indicates an excellent assay. Free dye in the solution might impair the signal-to-noise ratio. In case the concentration of the protein prior to labeling has been overestimated, excess dye is present. Nanotemper Technologies recommends re-checking the concentration of the protein or increasing the ratio between the protein and the dye to, e.g., 4:1. Changing the laser power, which gives a better signal-to-noise ratio for the analysis, can also be helpful.
For comparing multiple datasets, such as for various Mom mutants, baseline-corrected normalized fluorescence, normalized for amplitude of each dataset was plotted by selecting the ‘Fraction bound’ option in the MO.Affinity Analysis program.
Data was exported to GraphPad Prism software, and the curves were re-plotted (Figure 3).
Figure 3. Microscale thermophoresis (MST) analysis of interactions of Mom with acetyl CoA and Fe2+/3+. His-tagged wild-type Mom (WT) and mutants were fluorescently labeled and titrated against indicated concentrations of ligands acetyl CoA (A) and Fe2+/3+(B). Normalized fluorescence is plotted for analysis of thermophoresis. Data shown are representative of three independent experiments. Error bars represent standard deviations of n = 3 measurements (adapted from Karambelkar et al., 2020).
Recipes
Lysis buffer
10 mM HEPES-NaOH pH 7.4
1 mM 2-Mercaptoethanol
1 M NaCl
1 mM PMSF
1 mg/mL lysozyme
Phosphocellulose binding buffer
10 mM HEPES-NaOH (pH 7.4)
1 mM 2-Mercaptoethanol
400 mM NaCl
Wash buffer 1
10 mM HEPES-NaOH (pH 7.4)
1 mM 2-Mercaptoethanol
400 mM NaCl
Wash buffer 2
10 mM HEPES-NaOH (pH 7.4)
1 mM 2-Mercaptoethanol
600 mM NaCl
Elution buffer
10 mM HEPES-NaOH (pH 7.4)
1 mM 2-Mercaptoethanol
1.5 M NaCl
Storage buffer
10 mM HEPES-NaOH (pH 7.4)
1 mM 2-Mercaptoethanol
300 mM NaCl
MST buffer
10 mM HEPES–NaOH (pH 7.4)
300 mM NaCl
7 mM 2-Mercaptoethanol
1× PBS-T (Phosphate buffered saline-Tween)
137 mM NaCl
2.7 mM KCl
10 mM Na2HPO4
1.8 mM KH2PO4
0.05% Tween 20
Acknowledgments
Dedicated to the memory of Stanley Hattman (1938-2020), whose pioneering work laid the foundation for many exciting discoveries in the field of bacteriophage Mu DNA modification. This protocol reports in detail the sample preparation and quantitative analysis of biomolecular interactions of the bacteriophage Mu DNA modification protein Mom using MST and is derived from our work published earlier (Karambelkar et al., 2020). The work was funded by various grants to V.N. from the Department of Science and Technology, Department of Biotechnology, Government of India. VN is a J.C. Bose Fellow of Department of Science and Technology, Government of India. S.K. was supported by fellowship from the Council of Scientific and Industrial Research, India. We thank Ujjwal Rathore for assisting with data analysis and are grateful to Saji Menon and Sivaramaiah Nallapeta of Nanotemper technologies for providing technical assistance with microscale thermophoresis.
Competing interests
The authors declare no conflict of interest or competing interest.
References
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Analysis of Caenorhabditis elegans Aging-related Neurodegeneration in Chemosensory Neurons
CC Cira Crespo
Roberto Grau
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4473 Views: 1441
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Original Research Article:
The authors used this protocol in Journal of Alzheimer's Disease 2020
Abstract
Aging and neuronal deterioration constitute important risk factors for the development of neuronal-related diseases, such as different dementia. The nematode Caenorhabditis elegans has emerged as a popular model system for studying neurodegeneration diseases, due to its complete neuronal connectivity map. DiI is a red fluorescent dye that can fill the worm amphid neurons and enables the visualization of their neurodegeneration over time. This protocol provides an efficient, fast, and safe method to stain worm amphid neurons to highlight the chemosensory structures of live nematodes.
Keywords: DiI Aging Caenorhabditis elegans Neurons Neurodegeneration
Background
Neurodegenerative diseases share a common predisposing factor, the aging of the brain. So, a greater understanding of the normal aging brain may be necessary before we can fully understand the causes of pathological aging and cognitive decline (Yankner et al., 2008).
The existence of a complete neuronal connectivity map and genetic tractability of C. elegans make this animal model useful for studying human neurological diseases. Analysis of multiple genetic databases shows that a considerable number of human genes associated with different diseases have a significant homology to C. elegans genes, and the genetic tools available for this nematode have allowed the construction of predictive models for studying the molecular mechanism of these diseases (Alexander et al., 2014; Griffin et al., 2017).
In the aging C. elegans nervous system, synapses appear physically less robust than in younger animals. The average synapse in an elderly animal is smaller in its presynaptic density and includes fewer synaptic vesicles compared to young adults; this is similar to what occurs in the human brain, where loss of synaptic integrity contributes to its deterioration and dysfunction. Away from the synapse, typical changes in aging neurons include reduced axon caliber, poor axonal transport, smaller nuclei, and reduced cytoplasmic volume. In addition, part of the loss of mobility has an origin in defects of the nervous system (Toth et al., 2012). In recent years, numerous protocols have emerged to facilitate the visualization of C. elegans neurons, taking advantage of the transparent nature of this nematode. DiI is a long-chain dialkylcarbocyanine dye that uniformly labels neurons via lateral diffusion in the plasma membrane (Godement et al., 1987; Hofmann and Bleckmann, 1999). Neurons can be labeled either retrogradely or during dissociation. Some of the labeled membrane gradually becomes internalized and retains its fluorescence, allowing identification of cells for several weeks. DiI specifically labels amphid (ADL, ASH, ASI, ASJ, ASK, and AWB), and phasmid (PHA and PHB) IL1 and IL2 neurons, as well as IL sheath and socket cells to highlight the chemosensory structures of live nematodes (Wormatlas.org [Reference 12]). These dyes do not appear to affect the survival, development, or basic physiological properties of neurons, and do not spread detectably from labeled to unlabeled neurons. It seems likely that cells become retrogradely labeled mainly by lateral diffusion of dye in the plane of the membrane (Honig and Hume, 1986). Labeling with carbocyanine dyes has already allowed several exciting advances in developmental neurobiology (Honig and Hume, 1989). The aim of this protocol is to provide a modified technique for Dil staining, to allow the study of neurodegeneration in dementia disease models of C. elegans.
Materials and Reagents
Petri dishes 60 × 15 mm 500/cs (Fisher Scientific, catalog number: FB0875713A)
Pipette tips 2–200 µL Eppendorf® epT.I.P.S. (Eppendorf, catalog number: 022492039)
Pipette tips 50–1,000 µL Eppendorf® epT.I.P.S. (Eppendorf, catalog number: 022492055)
Eppendorf® Safe-Lock 1.5 mL microcentrifuge tubes (Eppendorf, catalog number: 022363204)
Corning® 15 mL centrifuge tubes (Corning, catalog number: 430791)
Glass media bottles 200 mL (Fisher Scientific, catalog number: FB800250)
Glass slide (25 × 75 × 0.9mm) and coverslip (22 × 22mm) (Sigma-Aldrich, catalog number: CLS294875X25-72EA; C9802-1PAK)
C. elegans strains (Caenorhabditis Genetics Center: N2 Bristol)
Escherichia coli strain OP50-1 (University of Minnesota, C. elegans Genetics Center, MN)
Bacillus subtilis strain NCIB3610 (Bacillus Genetic Stock Center, catalog numbers: 3A1 and 1A96)
1,1’-dioctadecyl-3,3,3’,3’,-tetramethylindocarbocyanine perchlorate (DiI, Sigma-Aldrich, catalog number: 468495)
Magnesium sulfate heptahydrate (MgSO4·7H2O) (Sigma-Aldrich, catalog number: M1880)
Potassium phosphate monobasic (KH2PO4) (Sigma-Aldrich, catalog number: P5655)
Potassium phosphate dibasic (K2HPO4) (Sigma-Aldrich, catalog number: P2222)
Sodium chloride (NaCl) (Sigma-Aldrich, catalog number: S7653)
Sodium azide (Sigma-Aldrich, catalog number: S8032)
NaClO Hypochlorite (Sigma-Aldrich, catalog number: 13440)
Sodium hydroxide (NaOH) (Sigma-Aldrich, catalog number: S8045)
Bacto peptone (BD, BactoTM, catalog number: 211677)
Agar (Sigma-Aldrich, catalog number: A1296)
Cholesterol in absolute ethanol Cholesterol (Sigma-Aldrich, catalog number: C8667)
100% ethanol (Sigma-Aldrich, catalog number: E7023)
Calcium chloride dihydrate (CaCl2·2H2O) (Sigma-Aldrich, catalog number: C3881)
Luria broth (Sigma-Aldrich, catalog number: L3522)
M9 buffer (see Recipes)
Nematode growth medium (NGM) agar (see Recipes)
Potassium phosphate buffer (see Recipes)
1 M MgSO4 (see Recipes) 5 mg/mL cholesterol (see Recipes)
1 M CaCl2 (see Recipes)
LB media (see Recipes)
Phosphate buffer (see Recipes)
1 N NaOH (see Recipes)
Bleaching solution (see Recipes)
DiI stock solution (see Recipes)
Equipment
Fluorescence microscope Zeiss (Carl Zeiss, Serial number: 3108012846)
Shaker (Axyos Technologies, catalog number: S04036.tu)
Autoclave (Tuttnauerusa, model: 6690)
Worm pick. Worm picks can either be purchased (Genesee Scientific, catalog number: 59-AWP) or made in the lab as described in Wollenberg et al. (2013)
Centrifuge (Eppendorf, model: 5430)
Tabletop centrifuge (Eppendorf, model: 5424)
Bunsen burner (Humbolt, catalog number: H-5870)
Procedure
C. elegans maintenance
Inoculate an E. coli OP50 colony into 50 mL of LB broth in a 200 mL flask, and incubate with gentle agitation at 37°C overnight (1 × 108 UFC/mL; OD: 1–1.2).
Apply approximately 200 μL of OP50 liquid culture to a 60 mm NGM plate. Incubate seeded plates at 37°C overnight before use.
Worms can be chunked (transfer agar pieces carrying worms from an old plate to a new one every 3–4 days).
Keep worms at 20°C.
C. elegans synchronization by bleaching
Allow previously synchronized worms to grow until L4 larval stage (approximately 48 h, see Figure 1), and then adult stage (~8 more hours).
Recover gravid adults in 15-mL tubes by washing plates with M9 buffer (see Recipe 1).
Pellet worms by centrifuging at 400 × g (~1,500 rpm on a standard table centrifuge) and room temperature for 2 min, and discard supernatant.
Perform 1–3 washes until the buffer appears clear of bacteria.
Add 5 mL of bleaching solution (see Recipe 8) into the tube, and shake vigorously at room temperature for up to 5 min. Bleaching longer than 5 min will kill the eggs. We followed destruction of worm bodies under the dissecting microscope, and the reaction is stopped when traces of adults are still visible, which typically takes between 3 and 5 min.
Stop reaction by adding M9 buffer until the 15-mL mark of the conical tube.
Quickly centrifuge (since treatment may still be active) at 400 × g for 1 min, and discard the supernatant.
Wash the pellet three more times, by filling the tube with M9 buffer.
Add 1 mL of M9 buffer to the pellet, or place the eggs to unseeded NGM plates, and incubate at the desired temperature with gentle agitation. Proper aeration should be provided to obtain all animals in stage L1. We check all worms are in larval stage 1 before proceeding further.
Transfer the L1 population to NGM agar plates previously seeded with the corresponding bacterial food, and incubate until they reach the young adult stage, approximately 48 h later (see Figure 1). Most of the C. elegans strains are maintained at 20°C on NGM media seeded with E. coli OP50 or B. subtilis NCIB3610.
Figure 1. C. elegans life cycle from egg-laying to adult worms. A. C. elegans viewed through the dissecting microscope. B. Life Cycle of C. elegans. Animals increase in size throughout the four larval stages. Photographs were taken on Petri dishes (note the bacterial lawns in all but the dauer images). Scale bar: 0.1 mm.
DiI staining of worms
Adult worms (approximately 100 worms per condition) fed with E. coli OP50- and B. subtilis NCIB3610- strain fed adult worms are collected, washed, and resuspend in 1 mL of M9 buffer, and then mixed with 5 µL of a 1:200 dilution of DiI solution (prepared from stock solution, see Recipe 10).
Incubate on a shaker (20 × g, ~75 rpm) at room temperature for 2–3 h.
Wash worms with M9 (1–3 washes) and transfer the labeled worms onto agar pads.
Figure 2. DiI-stained C. elegans neurons. Neuronal morphological changes of aging worms colonized by OP50 or NCIB3610 bacteria. Aging wild-type worms, colonized by OP50 or NCIB3610 bacterial cells (right and bottom rectangles for A and C; and B, respectively) at different ages, were labeled with fluorescent DiI to highlight amphid neuron morphology: A, normal morphology or no neuronal loss; B, partial neuronal alterations or partial neuronal loss; and C, total neuronal deterioration or total neuronal loss. The top and bottom micrographs (phase contrast and fluorescence microscopy, respectively) in A–C are representative of 10 independent worm images analyzed for each age. Arrows in A indicate the location of the chemosensory worm neurons (i.e., ASK, ADL, ASI, ASH, ASJ, and AWB), and arrows in B indicate some of the age-associated neuronal alterations. D. Semi-quantification of age-related neurodegeneration. Ten N2 worms colonized with OP50 or NCIB3610 bacteria, cultured on NGM plates at 20°C, were taken at the indicated times, processed, and labeled with DiI to determine the degree of age-related neuronal deterioration (not loss, partial loss, or loss). Results are expressed as a percentage of the initial population of worms (n = 100) ± S.E.M. Images from Cogliati et al. (2020) with permission.
Obtain the images of the worms
Mount the labeled worms onto a 2% agar pad on a glass slide using 0.1 M sodium azide (the azide acts as an anesthetic for the worms) and enclose with a coverslip.
Use the 40× objective to visualize the labeled worms.
Neuron degeneration can be examined over time with an Olympus FV1000 laser confocal scanning microscope using the Zen program, and a semi-quantitative analysis can be performed.
Data analysis
The worms are analyzed for the absence of amphid neuron architecture (complete loss), the presence of a complete and intact set of amphid neurons (no loss), or the presence of at least one single structural abnormality, such as wavy, branched, or interrupted dendrites (partial loss) (see Figure 2). All assays are performed at least three times in duplicate. Mean survival days, standard error of the mean (S.E.M.), intervals of mean survival days with 95% confidence, and equality p values to compare averages are calculated by log-rank and Kaplan-Meier tests, using the OASIS program. The S.E.M. values are used in the figures; p < 0.05 was considered statistically significant.
Notes
When worms are old adults, instead of centrifuging, let them settle on their own, since centrifugation can damage them as they are very weak.
When mounting the worms on slices, cut off the end of the pipette tips approximately 0.5 cm to create a broader opening, which will help avoid breaking the worms while transferring them.
For a better appreciation of the staining with DiI, turn off the light when observing the worms under a microscope.
Recipes
M9 buffer
3 g KH2PO4
6 g Na2HPO4·7H2O
5 g NaCl
Water up to 1 L Autoclave, then add 1 mL of 1 M MgSO4
Nematode growth medium (NGM) agar for 1 L medium
3.0 g NaCl
20 g Bacto agar
2.5 g Bacteriological peptone
Autoclave to sterilize the agar, cool to 55°C, then add:
1 mL of 1 M MgSO4
1 mL of 1 M CaCl2
1 mL of 5 mg/mL cholesterol in absolute ethanol
25 mL of 1 M Potassium phosphate buffer (see Recipe 6)
1 M MgSO4·7H2O
Dissolve 6 g MgSO4 heptahydrate in 50 mL of dH2O
Autoclave (121°C for 20 min)
Store at room temperature
5 mg/ml cholesterol
Dissolve 0.25 g of cholesterol in 50 mL of 100% ethanol
Do not autoclave
1 M CaCl2
Dissolve 5.55 g CaCl2 dihydrate in 50 mL of dH2O
Autoclave (121°C for 20 min)
Store at room temperature
Potassium phosphate buffer (1 M KPO4, pH 6.0)
108.3 g KH2PO4
35.6 g K2HPO4
Water up to 1 L
Autoclave (121°C for 20 min)
Store at room temperature
LB media
20 g LB broth dissolve in 1 L ddH2O
Autoclave (121°C for 20 min)
Bleaching solution
1 mL of 3% hypochlorite solution
2.5 mL of 1 N NaOH
0.5 mL of dH2O
1 N NaOH
Dissolve 2 g NaOH in 50 mL of dH2O
DiI stock solution
Stock solution is 2 mg/mL in dimethyl formamide
Store at -20°C in a foil-wrapped tube
Dilute the stock solution 1:200 in M9. Some dye will precipitate when you do this.
Acknowledgments
This work was supported by CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas) and FONCyT (Fondo para la Investigación Científica y Tecnológica) with the aid of the Pew Latin-American Program in Biological Sciences (Philadelphia, USA), the Fulbright Committee (Washington, DC, USA) and former Fundación Antorchas (Buenos Aires, Argentina). We modified the media and NGM plate’s preparation from Stiernagle T. Maintenance of C. elegans. WormBook. 2006 11:1-11. We modified C. elegans synchronization from Montserrat Porta-de-la-Riva et al. (2012). Basic Caenorhabditis elegans Methods: Synchronization and Observation. Journal of Visualized Experiments; 64, e4019, 1-9. The protocol is based on “Dil and diO: versatile fluorescent dyes for neuronal labelling and pathway tracing” (Honig and Hume, 1989).
Competing interests
There are no conflicts of interest or competing interests.
References
Alexander, A., Marfil, V. and Li, C. (2014). Use of Caenorhabditis elegans as a model to study Alzheimer’s disease and other neurodegenerative diseases. Front Genet 5: 279.
Cogliati, S., Clementi, V., Francisco, M., Crespo, C., Arganaraz, F. and Grau, R. (2020). Bacillus subtilis Delays Neurodegeneration and Behavioral Impairment in the Alzheimer's Disease Model Caenorhabditis elegans. J Alzheimers Dis 73(3): 1035-1052.
Godement, P., Vanselow, J., Thanos, S. and Bonhoeffer, F. (1987). A study in developing visual systems with a new method of staining neurones and their processes in fixed tissue. Development 101(4): 697-713.
Griffin, E., Caldwell, K. and Caldwell, G. (2017). Genetic and pharmacological discovery for Alzheimer’s disease using Caenorhabditis elegans. ACS Chem Neurosci 8: 2596-2606.
Hofmann, M. H. and Bleckmann, H. (1999). Effect of temperature and calcium on transneuronal diffusion of DiI in fixed brain preparations. J Neurosci Methods 88(1): 27-31.
Honig, M. G. and Hume, R. I. (1986). Fluorescent carbocyanine dyes allow living neurons of identified origin to be studied in long-term cultures. J Cell Biol 103(1): 171-87.
Honig, M. G. and Hume, R. I. (1989). Dil and diO: versatile fluorescent dyes for neuronal labelling and pathway tracing. Trends Neurosci 12(9): 333-335, 340-331.
Porta-de-la-Riva, M., Fontrodona, L., Villanueva, A. and Ceron, J. (2012). Basic Caenorhabditis elegans methods: synchronization and observation. J Vis Exp(64): e4019.
Stiernagle, T. (2006). Maintenance of C. elegans. WormBook. 1-11. Doi: 10.1895/wormbook.1.101.1.
Toth, M. L., Melentijevic, I., Shah, L., Bhatia, A., Lu, K., Talwar, A., Naji, H., Ibanez-Ventoso, C., Ghose, P., Jevince, A., et al. (2012). Neurite sprouting and synapse deterioration in the aging Caenorhabditis elegans nervous system. J Neurosci 32(26): 8778-8790.
Wollenberg, A. C., Visvikis, O., Alves, A. F. and Irazoqui, J. E. (2013). Staphylococcus aureus killing assay of Caenorhabditis elegans. Bio-protocol 3(19): e916.
Wormatlas.org (DiI and DiO Staining in C. elegans).
Yankner, B. A., Lu, T. and Loerch, P. (2008). The aging brain. Annu Rev Pathol 3:41-66.
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4,474 | https://bio-protocol.org/en/bpdetail?id=4474&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Maximizing the Rod Outer Segment Yield in Retinas Extracted from Cattle Eyes
IP Isabella Panfoli
DC Daniela Calzia
SR Silvia Ravera
PB Paolo Bianchini
AD Alberto Diaspro
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4474 Views: 1105
Reviewed by: Gal HaimovichSrinidhi Rao Sripathy Rao Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Biochimie Sep 2011
Abstract
The retina is a thin neuronal multilayer responsible for the detection of visual information. The first step in visual transduction occurs in the photoreceptor outer segment. The studies on photoreception and visual biochemistry have often utilized rod outer segments (OS) or OS disks purified from mammalian eyes. Literature reports several OS and disk purification procedures that rarely specify the procedure utilized to collect the retina from the eye. Some reports suggest the use of scissors, while others do not mention the issue as they declare to utilize frozen retinas. Because the OS are deeply embedded in the retinal pigmented epithelium (RPE), the detachment of the retina by a harsh pull-out can cause the fracture of the photoreceptor cilium. Here, we present a protocol maximizing OS yield. Eye semi-cups, obtained by hemisecting the eyeball and discarding the anterior chamber structures and the vitreous, are filled with Mammalian Ringer. After 10–15 min of incubation, the retinas spontaneously detach with their wealth of OS almost intact. The impressive ability of the present protocol to minimize the number of OS stuck inside the RPE, and therefore lost, compared with the classic procedure, is shown by confocal laser scanning microscopy analysis of samples stained ex vivo with a dye (MitoTracker deep red) that stains both retinal mitochondria and OS. Total protein assay of OS disks purified by either procedure also shows a 300% total protein yield improvement. The advantage of the protocol presented is its higher yield of photoreceptor OS for subsequent purification procedures, while maintaining the physiological features of the retina.
Keywords: Bovine Confocal laser scanning microscopy Disks Imaging Retina Rod outer segment
Background
The vertebrate eye is a photoreceptive sense organ (Stenkamp, 2015). Its laminar structure comprises three main layers: the fibrous tunic, consisting of the cornea and sclera; the vascular tunic (uvea), including the iris, ciliary body, and choroid; and the nervous tunic, including the retina and the retinal pigmented epithelium (RPE) (Netter, 2018). The eye can also be divided into an anterior and a posterior segment. The former includes the cornea, iris, ciliary body, and lens, while the latter encompasses the vitreous, retina, RPE, and choroid. The RPE faces the sensory retina and separates the subretinal space from the choroid, forming the outer blood–retinal barrier. Aqueous humor fills the anterior segment. The mammalian retina, a part of the central nervous system, consists of five classes of neurons (retinal ganglion cells, amacrine cells, bipolar cells, horizontal cells, and the cone and rod photoreceptors), arranged into three nuclear and two synaptic layers (Masland, 2012). The input for visual signaling (Palczewski, 2014) comes from photoreceptor cells, distinct in cones, responsible for the chromatic vision, and rods, high-sensitive receptors responsible for scotopic vision, that consist of a specialized inner and outer segment. Most mammalian retinas express one short wavelength-sensitive and one long wavelength type of cone, while a few express three (Masland, 2012). A cilium connects the OS to the inner segment (IS) (Gilliam et al., 2012); in fact, rod and cone OS are structurally homologous to non-motile cilia. The OS captures photons, initiating the visual transduction (Palczewski, 2014). In particular, the rod OS consists of a stack of approximately 2,000 membranous disks surrounded by a plasma membrane, which express the proteins devoted to phototransduction (Molday and Moritz, 2015). Recently, it was reported that the proteins of the mitochondrial redox chain are also functionally expressed in the rod OS (Bruschi et al., 2020). Disks are synthesized at the base of the OS (Young, 1967) and are shed at the apical tip, where the RPE phagocytizes exhausted disks (Campbell et al., 2018). Since the 1970s, studies on photoreception and on the biochemistry of vision have typically utilized rod outer segments (OS) or OS disks from cattle eyes, as these allow to obtain a large quantity of sample. Literature reports several rod OS purification procedures (de Grip et al., 1972; Raubach et al., 1974; McDowell and Kühn, 1977; Papermaster, 1982; Zimmerman and Godchaux, 1982; Molday et al., 1987; Uhl et al., 1987; Bubis, 1998), and one isolation procedure for disks (Smith et al., 1975, 1982). However, these seldom specify the procedure utilized to collect the retina from the eye. Some reports suggest the use of scissors; others do not include this passage, as they utilize frozen retinas. Because the OS are deeply embedded in the RPE, the detachment of the retina from the RPE by a harsh procedure can cause the fracture of the photoreceptor cilium. The goal of this protocol is to describe a gentle procedure for the extraction of living retinas from bovine eyeballs, maximizing the yield of rod OS, and avoiding the fracture of the rod at the cilium level inside the RPE and their eventual loss when the eye semi-cup is discarded.
The best yield of rod OS or disks is obtained when retina is let to spontaneously detach from the RPE by filling the eye semi-cup with sterile filtered mammalian ringer (MR) for at least 15 min. In the first step of the protocol, cattle eyes, freed from periocular muscle and connective tissue, are cut at the level of the ora serrata on a section plane below the pupil, as shown in Figure 1, and the anterior portion of the eye is discarded. In this way, it is possible to eliminate the lens, the aqueous humor, and the vitreous humor, obtaining a semi-cup containing the retina (Figure 1). Then, to facilitate the spontaneous detachment of the retina, the semi-cup is filled with sterile filtered MR and incubated for at least 10 min: in this way, most of the rod OS remain attached to the free-floating retina that detaches from the RPE. By contrast, if the retina is extracted utilizing a tweezer or a soft brush, the photoreceptors can fracture at the cilium and remain immersed in the RPE. The comparison between the two methods is shown by data obtained from the confocal laser scanning microscope (CLSM) analysis shown in Figures 3 and 4, after staining the retina with MitoTracker Deep Red 633 (ThermoFisher), as previously reported (Calzia et al., 2010; Panfoli et al., 2010; Ravera et al., 2007). Specifically, the retina detached by the MR incubation method presents a homogeneous layer of photoreceptors (Figure 3, Panel A) while, in the remaining semi-cup of the eye, only mitochondria are visible (Figure 3, Panel B). By contrast, when the retina is detached with a soft brush, few recognizable OS are observed (Figure 4, Panel A), which are instead still partially stained inside the eye semi-cup (Figure 4, Panel B).
Figure 1. Scheme for the cut of the eye semi-cup. The drawing shows where the plane of section passes to obtain the eye semi-cup. The panel on the right shows a close-up of an eye semi-cup unscrewed by the crystalline lens, aqueous humor, and vitreous humor, in which the retina lining the bottom of the eye is recognized.
The innovation of the present protocol, with respect to the literature, is the use of a gentle procedure to extract the retinas from the eye semi-cup, maximizing the absolute amount of rod OS still attached to the retina. Confocal laser scanning microscopy (Figures 3 and 4) demonstrated the advantage our protocol for the extraction of the retinas offers, with respect to the conventional extraction of the retina by means of a tweezer or even using a soft brush, and the actual risk of leaving almost all the rod OS inside the RPE of the eye semi-cup (Figure 3).
The significance of the improvement represented by the present protocol is the possibility to maximize the presence of the photoreceptor OS in the retinas extracted from large mammalian eye semi-cups. This is advantageous if retinas are used to purify rod OS or disks, but also for any subsequent procedure requiring the presence of photoreceptors in the isolated retina.
Materials and Reagents
Eppendorf Tube (Eppendorf, catalog number: 0030 102.002)
Glass Pasteur Pipettes (Teklab Limited, UK catalog number: GP225)
Centrifuge tube, conical bottom, 13 mL volume (VWR, catalog number: VWRI525-0179)
Milli-Q® Biocel System water (Millipore, http://www.millipore.com/)
Ampicillin (Millipore, catalog number: 171257), storage at -20°C
Protease inhibitor cocktail (Millipore, catalog number: 539133), storage at -20°C
NaCl (VWR, catalog number: 7647-14-5), room temperature storage
KCl (VWR, catalog number: 7447-40-7), room temperature storage
Na2HPO4 (Millipore, catalog number: 567547), room temperature storage
NaH2PO4 (Millipore, catalog number: 567545), room temperature storage
MgCl2·6H2O (Millipore, catalog number: 442615), room temperature storage
CaCl2·2H2O (Millipore, catalog number: 137101), room temperature storage
Steritop® Bottle-top Filtration Units 0.22 μm (Millipore Express® PLUS)
MitoTrackerTM Deep Red 633 FM Dye (ThermoFischer Scientific, catalog number: M46753)
Mammalian Ringer (MR) (see Recipes)
MitoTrackerTM Deep Red 633 FM Dye stock solution (see Recipes)
Equipment
Pipetting Standard (Gilson, Pipetman®, models: P20, P200, and P1000) (http://www.gilson.com/Products/)
MicroCentrifuge (Eppendorf, model: 5417R)
Dissecting Scalpels and Blades, dissecting Scissors, dissecting dressing Forceps, as in United (ScientificTM Dissecting Set, catalog number: S111010)
Dewar flask
Red light/dark room
Vacuum filtration device
Procedure
A flowchart depicting the whole experimental procedure is shown in Figure 2.
Figure 2. Flowchart of the procedure to detach the retina from the eye semi-cup with the MR incubation.
Prepare the eye semi-cup for incubation
Operations from step A2 on must be carried out at room temperature, in a dark room in dim red light (lower than 10 lux, 620 nm red lighting), to avoid rhodopsin bleaching. This facilitates the detachment of the photoreceptor OS from the RPE.
Obtain freshly enucleated bovine eyes from a slaughterhouse and use them within 2 h of animal death. The age of the cattle from which the eyes can be obtained for scientific purposes may be limited (as is the case in Italy) to 1.5 years, as a cautionary measure for the risk of possible transmission of Bovine Spongiform Encephalopathy (BSE). Eyes must be kept warm, in a light-tight container, possibly a Dewar flask, and handled to minimize the temperature decline.
Remove extraocular tissues with scissors.
Gently separate the anterior segment and vitreous from the eye semi-cup containing the neural retina. Make an incision in the sclera with a scalpel on one side of the eyeball, then hemi-sect the eye using scissors, approximately at the level of the ora serrata. Remove the anterior chamber, the lens, and vitreous carefully and discard them.
Detach the retina with MR incubation (Figure 3)
Fill the eye semi-cup containing the retina still attached to the RPE with 5–7 mL (depending on the size of the eye) of sterile filtered MR containing 2 mM glucose, protease inhibitor cocktail, and Ampicillin (100 μg/mL). All the operations, including incubations, are conducted at room temperature. The surface for dissection is routinely an aluminum foil.
Incubate each eye semi-cup for 10–15 min to allow the retina to detach completely. Eyes should be dissected and incubated with MR in rapid sequence.
Figure 3. CLSM evaluation of OS distribution in the retina and the eye semi-cup after asportation with MR. A) Mitotracker signal in a whole retina spontaneously detached from the eye semi-cup. In this case, a homogeneous layer of photoreceptors is recognizable. B) Mitotracker signal in an eye semi-cup from which the retina was let float to detach spontaneously from RPE. In this case, only mitochondria are visible (white head arrows). MitoTracker Deep Red 633 was used, dissolved in DMSO, and kept at -20°C in dark vials.
Gathering of Retinas (Figure 4)
After 10 min of incubation, rods spontaneously detach from the RPE, and the retina freely floats inside the eye semi-cup, attached to it through the optic nerve fibers; upon shorter incubation time, if it is necessary to remove the retina, gently shake the eye semi-cup by hand for 10 s, avoiding spilling the liquid contained inside, until the retina completely detaches from the RPE.
Rapidly turn the eye semi-cup inside out and discard the MR previously filling the semicup and now dripping out.
Cut each retina free from the optic nerve with scissors, letting the retina drop into a centrifuge 13 mL tube.
Figure 4. CLSM evaluation of OS distribution in the retina and the eye semi-cup after retina asportation with a soft brush. A) Retina detached from the eye semi-cup by a soft brush. In this case, the sample is characterized by a poor OS layer, allowing the visualization of the underlying mitochondria (white head arrow) belonging to inner segments of photoreceptors and the other retinas layers. B) Mitotracker signal in an eye semi-cup from which the retina had been detached with a soft brush. Specifically, it is possible to observe mitochondria (white head arrows) and OS immersed into the RPE (white arrows) since they have been torn from their ellipsoid.
Data analysis
The present method allows an increase of approximately 300% in the yield of total OS disk protein compared with the mechanical removal of the retinas from the eye semi-cup with a tweezer. When OS disks are purified by the method in Smith et al. (1975), the yield is 0.5 mg of rhodopsin/retina, corresponding to 0.58 mg protein/retina and approximately 11 mg total protein from 20 retinas (Smith et al., 1975). We have purified disks from 20 retinas utilizing the method described by Smith et al. (1975), extracting the retinas from the eye semi-cups, both following the present protocol and the mechanical method utilizing tweezers. The total disk protein yield, as assayed according to Bradford (Bradford, 1976), was 30 ± 2 mg of total disk protein in the first case and 10 ± 0.8 mg of total protein when retinas were extracted using tweezers.
Notes
In our experience of more than 10 years using this method, the reproducibility is excellent. Any eye of cattle up to 1.5 years of age (limitation due to BSE precaution rules) can be treated as described with predictable outcomes. On the other hand, if retinas are mechanically detached from the eye semi-cup, either with scissors or a brush, the yield in rod outer segment protein is extremely variable and can be approximately 300% lower. Additionally, our procedure maintains the physiological features of the retinal tissue.
Cautionary points:
(i) To prevent rhodopsin activation, avoid any white light source (McDowell and Kühn, 1977) by performing experiments in a dark/red light room;
(ii) Remove the vitreous humor from the eye semi-cup with special care, i.e., by gentle and rapid manual squeezing to avoid premature detachment of the retina, which would invalidate the present procedure;
(iii) Keep the eyes warm, minimizing the temperature drop, as eye cooling causes disaggregation of the RPE, which can contaminate the retinas, even when extracted with the present procedure;
(iv) As the bacterial dimension is similar to the rod disks (Smith and Litman, 1982), work in sterile conditions, filter sterilize the medium, use an antibiotic, and thoroughly clean the dissection tools with disinfectant soap and warm water.
Recipes
Mammalian Ringer (MR)
7.850 mL of 1 M NaCl
0.250 mL of 1 M KCl
1.750 mL of 200 mM Na2HPO4
2.000 mL of 200 mM NaH2PO4
0.025 mL of 1M MgCl2
Mix 0.025 of 1 M CaCl2 pH 6.9 in Milli-Q® water; add the protease inhibitor cocktail, according to the manufacturer instructions), and 100 μg/mL of Ampicillin.
When MT Deep Red 633 FM Dye is necessary, add it form the stock solution at 500 nM final concentration.
MitoTrackerTM Deep Red 633 FM Dye stock solution
Dissolve the mitochondrial dyes MT Deep Red in dimethylsulfoxide (DMSO) to make a 200 µM stock solutions and keep the solution at −20°C in dark vials.
Acknowledgments
This work was supported by FRA (Fondi per la Ricerca di Ateneo) 2019 from University of Genoa. This protocol was derived from previous original research articles, Calzia et al. (2018) and Ravera et al. (2020).
Competing interests
Authors declare absence of financial and non-financial competing interests.
Ethics
The present protocol utilizes bovine eyes from cattle intended for human consumption, which are killed at local slaughterhouses; therefore, ethic issues can be considered ruled out.
References
Bradford, M. M. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248-254.
Bruschi, M., Bartolucci, M., Petretto, A., Calzia, D., Caicci, F., Manni, L., Traverso, C. E., Candiano, G. and Panfoli, I. (2020). Differential expression of the five redox complexes in the retinal mitochondria or rod outer segment disks is consistent with their different functionality. FASEB Bioadv 2(5): 315-324.
Bubis, J. (1998). Effect of detergents and lipids on transducin photoactivation by rhodopsin. Biol Res 31(1): 59-71.
Calzia, D., Bianchini, P., Ravera, S., Bachi, A., Candiano, G., Diaspro, A. and Panfoli, I. (2010). Imaging of living mammalian retina ex vivo by confocal laser scanning microscopy. Anal Methods 2(11).
Campbell, L. J., West, M. C. and Jensen, A. M. (2018). A high content, small molecule screen identifies candidate molecular pathways that regulate rod photoreceptor outer segment renewal. Sci Rep 8(1): 14017.
de Grip, W. J., Daemen, F. J. and Bonting, S. L. (1972). Enrichment of rhodopsin in rod outer segment membrane preparations. Biochemical aspects of the visual process—XVIII. Vision Res 12(10): 1697-1707.
Gilliam, J. C., Chang, J. T., Sandoval, I. M., Zhang, Y., Li, T., Pittler, S. J., Chiu, W. and Wensel, T. G. (2012). Three-dimensional architecture of the rod sensory cilium and its disruption in retinal neurodegeneration. Cell 151(5): 1029-1041.
Masland, R. H. (2012). The neuronal organization of the retina. Neuron 76(2): 266-280.
McDowell, J. H. and Kuhn, H. (1977). Light-induced phosphorylation of rhodopsin in cattle photoreceptor membranes: substrate activation and inactivation. Biochemistry 16(18): 4054-4060.
Molday, R. S., Hicks, D. and Molday, L. (1987). Peripherin. A rim-specific membrane protein of rod outer segment discs. Invest Ophthalmol Vis Sci 28(1): 50-61.
Molday, R. S. and Moritz, O. L. (2015). Photoreceptors at a glance. J Cell Sci 128(22): 4039-4045.
Netter. (2018). Atlas of Human Anatomy. (Professional Edition). Including Student Consult Interactive Ancillaries and Guides. Elsevier.
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Panfoli, I., Calzia, D., Ravera, S., Bianchini, P. and Diaspro, A. (2010). Immunochemical or fluorescent labeling of vesicular subcellular fractions for microscopy imaging. Microsc Res Tech 73(12): 1086-1090.
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Neuroscience > Sensory and motor systems > Retina
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Cell Biology > Tissue analysis > Tissue imaging
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4,475 | https://bio-protocol.org/en/bpdetail?id=4475&type=1 | # Bio-Protocol Content
Improve Research Reproducibility
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Contigs Scaffolding with Hi-C for Plant Genomes
HA Hong An
QX Qing Xiao
ZJ Zhibo Jia
JP J. Chris Pires
BY Bin Yi
Published: Aug 5, 2022
DOI: 10.21769/BioProtoc.4475 Views: 897
Reviewed by: Liangliang GaoSanzhen Liu Anonymous reviewer(s)
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Abstract
Hi-C is a chromosome conformation capture method originally developed to detect genome-wide chromatin interactions. Nowadays, it is widely applied in scaffolding de novo assembled contigs into chromosome-scale genome sequences. Multiple open-source software has been developed to perform genome scaffolding with Hi-C data. The input data is de novo assembled contigs using long-read or short-read sequencing. Then, Hi-C data is mapped to these contigs, and the interact matrix is computed by software to scaffold contigs into chromosome-scale sequences. Different tools have specific algorithms to calculate the interact matrix and correct misassemblies and misjoins and may require different dependent packages or running environments. Here, we describe a step-by-step protocol for genome scaffolding using Hi-C data with a comprehensive pipeline: compute interact matrix with Juicer, scaffold contigs with 3D-DNA pipeline, and then visualize and modify scaffolding with Juicebox. This is the first detailed protocol showing how to do Hi-C scaffolding using this pipeline in plants. Compared to many other pipelines, this protocol only requires primarily assembled contigs and raw Hi-C data as inputs. Moreover, it is also compatible with multiple enzymes, and provides visualization and the possibility for manual correction. Currently, more and more genomes are sequenced combining Hi-C; this step-by-step protocol may be applied widely in mass large eukaryotic genome scaffolding.
Keywords: Hi-C Scaffolding Genome assembly Bioinformatics Plant Next-generation sequencing
Background
A plant genome provides valuable information to researchers for all kinds of molecular biological studies. In recent years, the development of sequencing technology has allowed faster and more affordable genome sequencing. Nevertheless, chromosome-scale genome sequences are still hard to obtain with only next-generation sequencing (NGS) or long-read sequencing due to some complicated genomic structures, like long interspersed repeats or highly homologous genome blocks. To conquer this, a genetic linkage map or optical map has been applied, to order and orient contigs into chromosome-scale sequences (Yamaguchi et al., 2021). However, the genetic linkage map is labour- and time-consuming in the Plantae kingdom. Meanwhile, the optical map requires a large quantity and high quality of high molecular weight DNA, which makes its production relatively difficult. In contrast, the quickly developed Hi-C scaffolding only requires 100 mg of plant tissue, and short-read sequencing on the NGS platform. This makes the Hi-C scaffolding both tissue- and cost-affordable. However, we need to be aware of the Hi-C library preparation, which will determine the success of the genome scaffolding. Young leaf tissue is commonly used in Hi-C library preparation for plants. Multi-round quality control is recommended during library preparation (Kadota et al., 2020). In particular, small-scale sequencing is highly recommended to evaluate the quality of the library, including the proportion of valid interaction reads, and estimation of the proper read pairs for further deep sequencing. Hi-C scaffolding has become one of the main solutions to obtain chromosome-scale scaffolds, having been widely utilized in recent plant genome sequencing projects. Meanwhile, multiple open-source software have been developed to compute the interact matrix, and order and orient assembled contigs into scaffolds (Table 1). Among these tools, the 3D-DNA pipeline is a widely used software that supports interactively visualizing and manually modifying the scaffolds.
Table 1. Overview of the major Hi-C scaffolding software
Program Input format Other information Literature
3D-DNA Juicer mapper format Compatible with multiple enzymes; results can be visualized and modified by Juicebox (Dudchenko et al., 2017)
LACHESIS Generic bam format No function to correct misjoins; developer’s support discontinued (Burton et al., 2013)
HiRise Generic bam format Used in Dovetail Chicago/Hi-C service; no open-source update available since 2015 (Putnam et al., 2016)
SALSA2 Generic bam (bed) file, assembly graph, unitig, 10× link files Compatible with multiple enzymes; results can be visualized by Juicebox (Ghurye et al., 2019)
ALLHiC
Hi-C reads;
gene annotation or closely related chromosome-scale reference genome
Designed for scaffolding plant polyploid genome (Zhang et al., 2019)
HiCAssembler Hi-C matrix in h5 format created by HiCExplorer Assembly errors can be manually corrected by specifying the position in the software (Renschler et al., 2019)
instaGRAAL Hi-C matrix created by hicstuff or HiC-Box Requires NVIDIA CUDA and GPU environment (Baudry et al., 2020)
Software
Trimmomatic (Bolger et al., 2014) (http://www.usadellab.org/cms/?page=trimmomatic)
Juicer (Durand et al. 2016) (https://github.com/aidenlab/juicer/)
3D-DNA pipeline (Dudchenko et al. 2017) (https://github.com/aidenlab/3d-dna)
Juicebox (version 1.11.08) (https://github.com/aidenlab/Juicebox)
BWA (Li and Durbin, 2009) (http://bio-bwa.sourceforge.net/)
Samtools (Li et al., 2009) (http://www.htslib.org/)
Miniconda (https://docs.conda.io/en/latest/miniconda.html)
BUSCO (Seppey et al., 2019) (https://gitlab.com/ezlab/busco)
Java 1.8 JDK (https://www.oracle.com/java/technologies/downloads/#java8)
Note: We recommend users to use the latest version of each software listed above, except for Juicebox (v. 1.11.08).
Equipment
Linux server or cluster
PC or Mac with at least 16GB RAM for handling big genomes (>1GB)
Input data
De novo assembly contigs file in FASTA format
Raw Hi-C sequencing data in FASTQ format
Procedure
Install and configure Juicer
Juicer is the software that maps Hi-C paired-end reads to assembled contigs and generates the Hi-C interact matrix for downstream analysis.
Download Juicer from the official GitHub repository.
$ mkdir hic; cd hic
$ git clone https://github.com/theaidenlab/juicer.git
Configure Juicer.
$ ln -s juicer/SLURM/scripts/ scripts
$ cd scripts; wget https://hicfiles.tc4ga.com/public/juicer/juicer_tools.1.9.9_jcuda.0.8.jar; ln -s juicer_tools.1.9.9_jcuda.0.8.jar juicer_tools.jar; cd ../
$ mkdir references
$ mkdir restriction_sites
Make sure samtools and bwa are in your $PATH.
$ export PATH=your_samtools/samtools:$PATH
$ export PATH=your_bwa/bwa:$PATH
Note: Juicer can be run on AWS, LSF, Univa Grid Engine (UGER), SLURM, and even a single CPU, but users may need to change the command line “ln -s juicer/SLURM/scripts/ scripts” in the “b. Configure Juicer” section to fit their system. For example, use “ln -s juicer/AWS/scripts/ scripts” for the AWS scheduler. For macOS users, curl https://hicfiles.tc4ga.com/public/juicer/juicer_tools.1.9.9_jcuda.0.8.jar --output ./ can be used instead of wget. The same can also be applied to all the wget in this protocol.
Prepare input data for Juicer
Copy your contigs.fasta file (or make soft link) into reference path, and index it with bwa index.
$ ln -s your_path/your_contigs.fasta ./references
$ cd ./references; bwa index your_contig.fasta; cd ..
Prepare enzyme site file for your_contigs.fasta.
$ cd restriction_sites
$ wget https://raw.githubusercontent.com/aidenlab/juicer/main/misc/generate_site_positions.py
Use vi or vim to edit generate_site_positions.py, insert the following line in line 25:
‘your_contigs’: ‘../references/your_contigs.fasta’,
$ python generate_site_positions.py your_enzyme your_contigs
$ awk 'BEGIN{OFS="\t"}{print $1, $NF}' your_contigs_your_enzyme.txt > your_contigs.chrom.sizes
$ cd ..
Filter and clean raw Hi-C sequencing data.
$ wget https://github.com/usadellab/Trimmomatic/files/5854859/Trimmomatic-0.39.zip
$ unzip Trimmomatic-0.39.zip
$ java -jar ./Trimmomatic-0.39/trimmomatic-0.39.jar PE -threads your_threads -phred33 -trimlog trimmomatic.log your_hic_R1.fastq.gz your_hic_R2.fastq.gz your_hic_pair_R1.fastq.gz your_hic_unpair_R1.fastq.gz your_hic_pair_R2.fastq.gz your_hic_unpair_R2.fastq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36
Note: your_contigs, your_enzyme, and your_threads are variable; users need to name their own contig file, choose the specific enzyme they used, and specify how many threads they would like to use. your_hic_R1.fastq.gz, your_hic_R2.fastq.gz are the sequenced raw Hi-C paired-end data.
Run Juicer to obtain the interact matrix
$ mkdir your_contigs_hic; cd your_contigs_hic
$ mkdir fastq
$ ln -s ../your_hic_pair* ./fastq/
$ sh ../scripts/juicer.sh -D $PWD/hic -g your_contigs -s your_enzyme -p ../restriction_sites/your_contigs.chrom.sizes -y ../restriction_sites/your_contigs_your_enzyme.txt -z ../references/your_contig.fasta -Q 2-00:00 -L 7-00:00 -q your_queue_name -l your_long_queue_name -t your_threads -A your_account –-assembly
$ cd ..
Note: Check juicer.sh, and make sure all the Partition, Account, QOS, and Threads fit your cluster’s scheduler. To be safe, add these parameters to your command line. Juicer will submit jobs to the cluster through the scheduler automatically. After all the jobs are done, the file named merged_nodups.txt in your_contigs_hic/aligned will be used by 3D-DNA pipeline.
Run 3D-DNA pipeline
3D-DNA pipeline is designed to correct misassembles and scaffold contigs based on the Hi-C interact matrix. It will generate the scaffolds fasta file and .hic and .assembly files for visualization in Juicebox.
Download 3D-DNA pipeline and uncompress.
$ wget https://github.com/aidenlab/3d-dna/archive/refs/tags/201008.tar.gz
$ tar -zxf 201008.tar.gz
$ chmod 554 ./3d-dna-201008/*.sh
Run 3D-DNA to scaffold the contigs using the interact matrix information.
$ cd your_contigs_hic
$ ../3d-dna-201008/run-asm-pipeline.sh ../references/your_contigs.fasta ./aligned/merged_nodups.txt
After the job is done, two files named your_contigs.rawchrom.assembly and your_contigs.rawchrom.hic will be used by Juicebox.
Note: If the scaffolding results are not ideal, try different –round (or -r), different edit round, and slightly increase --editor-repeat-coverage misjoin editor threshold repeat coverage. In this case study, we use -r5 --editor-repeat-coverage 3.
Visualize and modify the scaffolding with Juicebox
Based on the system, the corresponding Juicebox 1.11.08 version can be downloaded at https://github.com/aidenlab/Juicebox/wiki/Download.
Download your_contigs.rawchrom.assembly and your_contigs.rawchrom.hic to your PC.
Run Juicebox, then load your_contigs.rawchrom.hic and your_contigs.rawchrom.assembly in turn (Figure 1).
Correct scaffolding manually (Figures 2 and 3).
1) Shift+left-click to choose the region that needs to be edited.
2) Right-click to choose to remove or add chr boundaries.
3) Move the mouse to the upper-right corner of the selected region until a circle appears, and then left-click to rotate the selected region.
Note: A demo video made by the Juicebox developer can be found on the GitHub repository.
Figure 1. Steps to load .hic and .assembly file to Juicebox.
A. load the .hic file; B. load the .assembly file.
Figure 2. Examples of how to edit misjoin and misorientation.
A. edit misjoin via add and remove chr boundaries. B. edit misorientation by rotating selected contigs.
Figure 3. Manually correct the scaffolding with Juicebox.
A. the original scaffolding visualization. B. manually corrected scaffolding. Ex. 1: misjoin, Ex. 2: misorientation.
Run the 3D-DNA pipeline again to update the manual modification
Upload your_contigs.rawchrom.edit.assembly to cluster, and place it in your_contigs_hic.
Run the 3D-DNA pipeline to obtain your edited scaffolds fasta file.
$ ../3d-dna/run-asm-pipeline-post-review.sh -r your_contigs.rawchrom.edit.assembly ../references/your_contigs.fasta aligned/merged_nodups.txt
Primarily estimate the scaffolding with BUSCO
Install BUSCO.
$ conda install -c bioconda busco
Download the dataset for BUSCO.
$ mkdir busco_evalue; cd busco_evalue
$ wget https://busco-data.ezlab.org/v4/data/lineages/embryophyta_odb10.2020-09-10.tar.gz
$ tar -zxf embryophyta_odb10.2020-09-10.tar.gz
Run BUSCO.
$ busco -c your_threads -m genome -i ../your_contigs_hic/your_contigs_arrow_nextpolish_HiC.fasta -o your_contigs_hic_busco -l ./embryophyta_odb10
Check BUSCO value and components (Figure 4).
Figure 4. BUSCO summary information.
Result interpretation
Table 2. Comparison of input contigs and Hi-C scaffolds
Contigs Scaffolds
Count 1,277 1,756
Total 1,021,027,667 1,021,751,667
Max 33,995,119 71,758,703
Min 518 518
N25 16,298,438 62,920,139
L25 12 4
N50 8,776,215 52,692,430
L50 33 9
N75 3,298,835 23,729,965
L75 80 16
Acknowledgments
This project is supported by National Key Research and Development Program of China (2021YFD1600500).
Competing interests
The authors declare no conflict of interest.
References
Baudry, L., Guiglielmoni, N., Marie-Nelly, H., Cormier, A., Marbouty, M., Avia, K., Mie, Y. L., Godfroy, O., Sterck, L., Cock, J. M., et al. (2020). instaGRAAL: chromosome-level quality scaffolding of genomes using a proximity ligation-based scaffolder. Genome Biol 21(1): 148.
Bolger, A. M., Lohse, M. and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15): 2114-2120.
Burton, J. N., Adey, A., Patwardhan, R. P., Qiu, R., Kitzman, J. O. and Shendure, J. (2013). Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat Biotechnol 31(12): 1119-1125.
Dudchenko, O., Batra, S. S., Omer, A. D., Nyquist, S. K., Hoeger, M., Durand, N. C., Shamim, M. S., Machol, I., Lander, E. S., Aiden, A. P., et al. (2017). De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356(6333): 92-95.
Durand, N. C., Shamim, M. S., Machol, I., Rao, S. S., Huntley, M. H., Lander, E. S. and Aiden, E. L. (2016). Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments. Cell Syst 3(1): 95-98.
Ghurye, J., Rhie, A., Walenz, B. P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A. M. and Koren, S. (2019). Integrating Hi-C links with assembly graphs for chromosome-scale assembly. PLoS Comput Biol 15(8): e1007273.
Kadota, M., Nishimura, O., Miura, H., Tanaka, K., Hiratani, I. and Kuraku, S. (2020). Multifaceted Hi-C benchmarking: what makes a difference in chromosome-scale genome scaffolding? Gigascience 9(1): giz158.
Li, H. and Durbin, R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14): 1754-1760.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16): 2078-2079.
Putnam, N. H., O'Connell, B. L., Stites, J. C., Rice, B. J., Blanchette, M., Calef, R., Troll, C. J., Fields, A., Hartley, P. D., Sugnet, C. W., et al. (2016). Chromosome-scale shotgun assembly using an in vitro method for long-range linkage. Genome Res 26(3): 342-350.
Renschler, G., Richard, G., Valsecchi, C. I. K., Toscano, S., Arrigoni, L., Ramirez, F. and Akhtar, A. (2019). Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling. Genes Dev 33(21-22): 1591-1612.
Seppey, M., Manni, M. and Zdobnov, E. M. (2019). BUSCO: Assessing Genome Assembly and Annotation Completeness. Methods Mol Biol 1962: 227-245.
Yamaguchi, K., Kadota, M., Nishimura, O., Ohishi, Y., Naito, Y. and Kuraku, S. (2021). Technical considerations in Hi-C scaffolding and evaluation of chromosome-scale genome assemblies. Mol Ecol 30(23): 5923-5934.
Zhang, X., Zhang, S., Zhao, Q., Ming, R. and Tang, H. (2019). Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nat Plants 5(8): 833-845.
Supplementary information
Data and code availability: All data and code have been deposited to GitHub: https://github.com/Bio-protocol/Plant_genome_Hi-C_scaffolding.git.
Article Information
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Computational Biology and Bioinformatics
Plant Science > Plant molecular biology > Genetic analysis
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4,476 | https://bio-protocol.org/en/bpdetail?id=4476&type=0 | # Bio-Protocol Content
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Gene Expression Analysis in Stem Cell-derived Cortical Neuronal Cultures Using Multi-well SYBR Green Quantitative PCR Arrays
VS Vasavi Nallur Srinivasaraghavan
FZ Faria Zafar
BS Birgitt Schüle
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4476 Views: 1930
Reviewed by: Salma MerchantValerie Uytterhoeven Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Stem Cell Research Apr 2022
Abstract
To optimize differentiation protocols for stem cell-based in vitro modeling applications, it is essential to assess the change in gene expression during the differentiation process. This allows controlling its differentiation efficiency into the target cell types. While RNA transcriptomics provides detail at a larger scale, timing and cost are prohibitive to include such analyses in the optimization process. In contrast, expression analysis of individual genes is cumbersome and lengthy.
Here, we developed a versatile and cost-efficient SYBR Green array of 27 markers along with two housekeeping genes to quickly screen for differentiation efficiency of human induced pluripotent stem cells (iPSCs) into excitatory cortical neurons. We first identified relevant pluripotency, neuroprogenitor, and neuronal markers for the array by literature search, and designed primers with a product size of 80-120 bp length, an annealing temperature of 60°C, and minimal predicted secondary structures. We spotted combined forward and reverse primers on 96-well plates and dried them out overnight. These plates can be prepared in advance in batches and stored at room temperature until use. Next, we added the SYBR Green master mix and complementary DNA (cDNA) to the plate in triplicates, ran quantitative PCR (qPCR) on a Quantstudio 6 Flex, and analyzed results with QuantStudio software.
We compared the expression of genes for pluripotency, neuroprogenitor cells, cortical neurons, and synaptic markers in a 96-well format at four different time points during the cortical differentiation. We found a sharp reduction of pluripotency genes within the first three days of pre-differentiation and a steady increase of neuronal markers and synaptic markers over time. In summary, we built a gene expression array that is customizable, fast, medium-throughput, and cost-efficient, ideally suited for optimization of differentiation protocols for stem cell-based in vitro modeling.
Keywords: Human iPSCs Induced pluripotent stem cells Cortical neurons Neuronal differentiation SYBR Green Quantitative PCR Multi-well qPCR Primer design
Background
The real-time quantitative PCR (qPCR) technique detects amplification of target nucleic acid sequences, and it is considered sensitive, reproducible, and specific (Arya et al., 2005).
Here, we use multi-well qPCR assays to amplify multiple genes with SYBR Green technology (Arikawa et al., 2011). SYBR Green is a DNA binding dye that binds non-specifically to double-stranded DNA (dsDNA) (Boone et al., 2015).
Based on the RT2 ProfilerTM array (Arikawa et al., 2011), we designed a multi-well SYBR Green qPCR panel to analyze the expression of genes involved in the differentiation of cortical neurons from the human iPSCs by forced expression of Neurogenin 2 (Ngn2), which is a neuronal transcription factor supporting neuronal differentiation of human embryonic stem cells or iPSCs into cortical-like neurons (Zhang et al., 2013). Here, we used a human iPSC line with a doxycycline-inducible mouse Ngn2 transgene engineered into a safe harbor locus (Wang et al., 2017). We collected cells at different time points (iPSCs, Day 0 pre-neurons, Day 15, and Day 30 cortical neurons) and analyzed genes that mark pluripotent stem cells, intermediate neuroprogenitors, and mature cortical neurons on a single 96-well plate. The amplicons/ primers were designed in the range of 80-120 bp, and the Tm was between 63°C and 66°C. The in-house preparation of the multi-well SYBR Green qPCR assay allows tailoring primers to specific experiments and assay modification as needed. This multi-well SYBR Green qPCR assay can be used for the quantitative analysis of any set of genes of interest. Different RT2 profiler arrays for pathway analysis are commercially available; however, none of them are optimized to follow the maturation of cortical neurons derived from iPSCs. We show that the multi-well SYBR Green qPCR is easily adaptable for customization in the laboratory. It is an economic platform and ideally suited for the optimization of differentiation protocols for in vitro stem cell modeling.
Materials and Reagents
RNA extraction
Homogenizer spin column (Thermo Fisher Scientific, Life Technologies, catalog number: 12183-026)
2-mercaptoethanol (Sigma-Aldrich, Aldrich Chemistry, catalog number: M2650)
DNase I, amplification grade (Thermo Fisher Scientific, Invitrogen, catalog number: 18068015)
Ethanol, molecular grade (Thermo Fisher Scientific, catalog number: BP2818500)
PureLinkR RNA mini kit (Thermo Fisher Scientific, Life Technologies, catalog number: 12183025)
RNase away (Thermo Fisher Scientific, Life Technologies, catalog number: 10328011)
cDNA Reverse Transcription
MicroAmp 8-tube strip (Thermo Fisher Scientific, Applied Biosciences, catalog number: A30589)
High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, Invitrogen, catalog number: 4368814)
Multi-well PCR reaction
MicroAmp Optical 96-well reaction plate (Thermo Fisher Scientific, Applied Biosystems, catalog number: N8010560)
MicroAmp Optical adhesive film (Thermo Fisher Scientific, Applied Biosystems, catalog number: 4311971)
Nuclease-free water (US Biological LifeSciences, catalog number: W0900)
PowerUpTM SYBRTM Green master mix (Thermo Fisher Scientific, Applied Biosystems, catalog number: A25780)
Consumables
1.5 mL and 0.6 mL RNase-free microcentrifuge tubes
RNase-free filter pipette tips (P1000, P200, P20, and P2)
Others
10× PBS, molecular grade (Fisher Scientific, catalog number: J75889K2
Accutase (Thermo Fisher Scientific, catalog number: NC9464543)
Bucket with wet ice
Personal protective equipment (gloves, lab coat, goggles)
Equipment
Revco Ultima II ultra low temperature -86°C freezer (Thermo Scientific, catalog number: ULT2586-9)
Microcentrifuge 5415C (Eppendorf, catalog number: M7282)
Refrigerated centrifuge (Beckman Coulter, catalog number: GS6 Allegra)
Mini centrifuge (Fisher Scientific, catalog number: 05-090-100)
Water bath (Thermo Fisher Scientific, Cole Parmer, catalog number: TSGP20)
MiniAmpTM thermal cycler (Applied Biosystems, Thermo Fisher Scientific, catalog number: A37834)
NanoDrop spectrophotometer (Thermo Fisher Scientific, catalog number: 13-400-525)
QuantStudio 6 Flex (Applied Biosystems, Thermo Fisher Scientific, catalog number: 4485691)
Optional: PlateR visual pipetting aid tablet (Biosistemika, catalog number: P-10)
Software
Beacon Designer (Premier Biosoft, http://www.premierbiosoft.com/qOligo/Oligo.jsp?PID=1)
In silico PCR prediction (UCSC Genome Browser, https://genome.ucsc.edu/cgi-bin/hgPcr)
Primer3 software (Whitehead Institute for Biomedical Research, Steve Rozen, Maido Remm, Triinu Koressaar, and Helen Skaletsky, https://bioinfo.ut.ee/primer3-0.4.0/)
QuantStudio Flex 6-v1.7.1 (Applied Biosystems, ThermoFisher Scientific, https://www.thermofisher.com/us/en/home/global/forms/life-science/quantstudio-6-7-flex-software.html)
UNAFold (Integrated DNA technology, https://www.idtdna.com/UNAFold). Create an account to use the software
Procedure
Ngn2-guided cortical neuron sample collection
The iPSCs seeded at 1.5 × 105 cells, were differentiated in a 12-well plate (~40,000 cells per cm2) according to the protocol of Wang et al. (2017) using an Ngn2-inducible cell line. The media was changed every other day. As shown in Figure 1, cells were collected at day -3 (3 days before doxycycline induction), day 0, day 15, and day 30 for iPSCs, pre-neurons, day 15, and day 30 cortical neurons, respectively, for the illustration of this SYBR Green multi-well array. A confluent well of a 12-well plate of iPSCs yields 3 × 106–4 × 106 cells, and the RNA yield will be approximately 8–10 μg total RNA. For pre-neurons, the RNA yield ranges between 5-6 μg from 2 × 106–3 × 106 cells, and for neurons (days 15 and 30), RNA yield ranges between 1–3 μg from 1 × 106–2 × 106 cells.
Figure 1. Timeline for the Ngn2-guided cortical neuronal differentiation and collection of samples for RNA extraction. Scale bar: 100 μm.
To dissociate the cells for sample collection, aspirate the old media, directly add 400 μL of Accutase per well of a 12-well plate, and incubate the cells at 37°C for 3–5 min to lift them off.
Add 400 μL of 1× cold PBS to Accutase, pipette the cell solution up and down to dissociate, and transfer the cell suspension to a 1.5 mL Eppendorf tube. Wash the well with additional 400 μL of 1× cold PBS to collect the remaining cells and add to the same Eppendorf tube.
Centrifuge the cell suspension at 15,000 × g at 4°C for 5 min.
Aspirate and discard the supernatant.
Wash the cell pellet with 1 mL of 1× cold PBS by pipetting up and down several times, and centrifuge again at 15,000 × g at 4°C for 5 min.
Aspirate the supernatant while keeping it on wet ice.
Continue with RNA extraction or store the cell pellet at -80°C.
RNA extraction and purification (PureLinkR RNA Mini Kit, Thermo Fisher, Life Technologies, 12183025)
Preparation:
Clean the bench with 70% ethanol and RNase Away.
Use RNase-free barrier filter tips for RNA extraction.
Before using Wash Buffer II for the first time:
Add 60 mL of 96-100% ethanol directly to the Wash buffer bottle.
Check the box on the Wash Buffer II label to indicate that ethanol was added.
Store Wash Buffer II with ethanol at room temperature.
Prepare fresh Lysis Buffer containing 1% 2-mercaptoethanol for each purification. Under the chemical hood, add 3 μL of 2-mercaptoethanol per 300 μL of Lysis Buffer.
Procedure:
Take the cell pellet from the -80°C freezer and place it on ice (perform subsequent steps at room temperature).
Add 300 μL of Lysis Buffer to the cell pellet.
Vortex for 10 s at high speed until the cell pellet is thoroughly mixed.
Transfer the lysate to a homogenizer spin column inserted in an RNase-free Eppendorf tube and centrifuge at 12,000 × g for 2 min. Remove and discard the homogenizer cartridge after centrifugation.
Add 300 μL of 70% ethanol to the cell homogenate.
Vortex to mix thoroughly and to disperse any visible precipitate that may form after adding ethanol.
Transfer up to 700 μL of the sample to a spin cartridge (with a collection tube).
Centrifuge at 12,000 × g for 15 s at room temperature. Discard the flow-through and reinsert the spin cartridge into the same collection tube.
Add 700 μL of Wash Buffer I to the spin cartridge. Centrifuge at 12,000 × g for 15 s at room temperature. Discard the flow-through and the collection tube. Place the spin cartridge into a new collection tube.
Add 500 μL of Wash Buffer II (supplemented with ethanol) to the spin cartridge.
Centrifuge at 12,000 × g for 15 s at room temperature. Discard the flow-through and reinsert the spin cartridge into the same collection tube.
Repeat steps 10-11 once.
Centrifuge the spin cartridge at 12,000 × g for 2 min to dry the membrane containing the RNA.
Discard the collection tube and insert the spin cartridge into a new recovery tube.
Add 30 μL of RNase-free water to the center of the spin cartridge.
Incubate at room temperature for 1 min.
Centrifuge the spin cartridge for 2 min at ≥12,000 × g at room temperature to elute the RNA from the membrane into the recovery tube.
Add the eluted RNA sample to the same spin cartridge again and repeat steps 16–17 to increase the yield of the RNA sample.
The concentration of the eluted RNA is determined using a NanoDrop spectrophotometer.
The concentration of RNA varies between cell types as mentioned in Figure 2.
Critical step! Aliquot the RNA into RNase-free tubes, each having 1 μg of RNA, to avoid freeze-thaw cycles and degradation of RNA. The aliquot volume for 1 μg of RNA is directly used for the DNase I treatment.
Note: The aliquots are treated with DNase I before storage.
Proceed with DNase I treatment directly after RNA purification or freeze aliquots at -80°C.
It is absolutely critical to aliquot RNA and cDNA samples to avoid freeze-thaw cycles and avoid degradation of the sample.
Figure 2. Workflow and calculations for the different cell types through the cortical neuron differentiation with stopping points and storage.
DNase I Treatment (Thermo Fisher Scientific, Invitrogen, catalog number: 18068015)
Combine the items shown in Table 1 in RNase-free tubes:
Table 1. Reaction mix for DNase I treatment of eluted RNA
Component Volume
RNA (1 μg) up to 8 μL
10× DNase I Buffer 1 μL
RNase-free Water add up to 8 μL
DNase I, Amplification Grade 1 μL
Final Volume 10 μL
Mix and incubate for 15 min at room temperature.
Heat-inactivate the DNase I by adding 1 μL of 25mM EDTA to the DNase I treated RNA sample and place it in a water bath at 65°C for 3 min.
Once the RNA samples are DNase I heat-inactivated, place them on ice.
Proceed with the reverse transcription or store aliquots at -80°C.
cDNA Reverse Transcription (High-Capacity cDNA Reverse Transcription Kit, Thermo Fisher, Invitrogen, catalog number: 4368814)
The extracted RNA is converted to cDNA for qPCR amplification. As a control, prepare a reverse transcription control with no addition of the reverse transcriptase in the reaction mix.
The reaction mixture (RT mix) is prepared according to Table 2. The 1 μg RNA (10 μL volume) from the previous step is mixed with the reaction mix (Table 2) for a final volume of 20 μL for the cDNA reaction.
Table 2. Reaction mix for the cDNA reverse transcription reaction.
Component Volume/reaction (μL)
10× RT Buffer 2.0
25× dNTP Mix (100mM) 0.8
10× RT Random Primers 2.0
MultiscribeTM Reverse Transcriptase 1.0
RNase Inhibitor 1.0
Nuclease-free water 3.2
Total volume per reaction mix (RT mix) 10.0
Preparation of cDNA RT reaction:
The RT mix is prepared, mixed gently, and placed on ice.
Pipette 10 µL RT master mix into MicroAmp 8-tube strip.
Add 10 µL of DNase I treated RNA sample (1 μg) to the reaction mix and mix by pipetting up and down several times.
Notes:
One tube has to be prepared containing the RNA input but not the MultiscribeTM Reverse Transcriptase. This is used as reverse transcriptase control (RTC), which can confirm that no genomic DNA is amplified.
Do not introduce bubbles while pipetting.
The tubes are sealed and centrifuged to spin down the contents and eliminate air bubbles.
Place the tubes on ice and load them into the MiniAmpTM Thermal Cycler.
Reverse transcription thermal cycling conditions (Table 3):
The reaction volume is set to 20 µL.
Load the reaction tubes into the thermal cycler.
The thermal cycler program is set to RUN.
Once the cycle is complete, add 80 μL of nuclease-free water to the 20 μL cDNA for a working concentration of 10 ng/μL, store the cDNA at -80°C.
Critical step! Aliquot the sample to avoid freeze-thaw cycles and degradation of cDNA.
Table 3. Thermal cycler conditions of cDNA reaction.
Step 1 Step 2 Step 3 Step 4
Temperature (°C) 25 37 85 4
Time (min) 10 120 5 ∞
Primer Design
We designed SYBR Green primers using an established protocol (Thornton and Basu, 2011). The primer parameters of this section are: Product size: 80–120 bp, product melting temperature (Tm): 63–66°C, secondary structure ΔG: not more than -3.5 and the GC percentage: 35–80%, with optimal at 65%. The primers were designed in an intron-spanning fashion, so that the forward and the reverse primer were not placed in the same exon. This can avoid contamination from genomic DNA.
Step 1: To obtain the sequence of the gene of interest in FASTA format from the National Center for Biotechnology Information (NCBI) website: http://www.ncbi.nlm.nih.gov.
Select the Nucleotide option from the dropdown menu in search “All Databases”.
Enter the gene name or the sequence ID of interest in the search box and click on Search.
Since the cortical neurons are differentiated from the human iPSCs, either mention homo sapiens along with the gene name in the search bar, or select homo sapiens from the species filter on the top left of the webpage after clicking on search.
Click on the RefSeq transcripts and select the FASTA option, then click apply.
Step 2: After obtaining the FASTA sequence for the selected gene, design the primers using Primer3 software: https://bioinfo.ut.ee/primer3-0.4.0/ (SantaLucia, 1998), Figure 3.
Note: The explanation for the default values is given in the webpage: https://bioinfo.ut.ee/primer3-0.4.0/input-help.htm.
Figure 3. Screenshot of Primer3 webpage indicating the parameters and conditions for designing primers of the SYNAPSIN1 (SYN1) gene.
Copy and paste the FASTA format sequence of the gene interest into the box provided on the Primer3 primer design page.
Pick left primer: This option was left blank for the software to pick the primers.
Pick hybridization probe: This option was left blank (not required with this experiment).
Pick right primer: If this option is left blank, the Primer3 program will choose the right primer.
Sequence Id (Name of the gene): This is to identify the primers for the sequence. A proper name is set corresponding to the sequence.
Targets (region of the sequence of the gene of interest): After looking into the CDS and exon regions (shown in Figure 4) the specific nucleotide position in the sequence is entered against the target, following with the number of nucleotides along to be flanked for the primers to design surrounding that particular region. An example, on how to enter the target regionis is shown in Figure 4.
Figure 4. Image of NCBI webpage indicating the position of exons
Primer Tm: This is the temperature at which 50% of the primer is hybridized to the DNA template. For this experiment, all primers are designed in the range of 63–66°C Tm.
Maximum Tm difference: Enter the value as 2.
Table of Thermodynamic parameters: Primer3 uses these formulas to calculate the melting temperature. Set the method to SantaLucia (1998).
Product Tm: This is the temperature at which 50% of the amplicon is ssDNA. Set the optimal value to 50.
Primer GC: This is the minimum and maximum percentage of guanine and cytosine (GC) allowed. The GC content of primers is used to determine the melting temperature of the primer, which can be used to predict the annealing temperature. Set the values to Minimum: 35, Optimum: 65, Maximum: 80.
Max Self-complementary: Primers should not be self-complementary or complementary to each other. Primers that are self-complementary form self-dimers or hairpin structures. Enter the value as 4.
Max 3’ Self-complementary: As polymerases add bases at the 3’ end of the oligonucleotide, the 3’ ends of primers should not be complementary to each other, as primer dimers will occur. Enter the value as 3.
Max #N: This is the maximum number of unknown bases which Primer3 could consider for designing primers. Set value at 0.
Max Poly-X: The maximum number of mononucleotides repeats to allow in the primer. Long mononucleotide repeats can promote mispriming. Enter the value as 3.
Inside target penalty and outside target penalty: Used if the primer needs to be designed to overlap a region. Leave as default.
First Base Index: This parameter tells Primer3 which programming index type the first base in the input sequence is. Leave as default.
GC Clamp: Defines the specific numbers of Gs and Cs at the 3’ end of both the left and right primers. Leave the value as 0.
Conc. of monovalent cations: This is the millimolar concentration of KCl salt in the PCR. Enter the value as 50 µM.
Note: According to the SantaLucia (1998), the concentration for monovalent cations is assumed at 50 μM and at 3.5 mM for divalent cations. Other literature suggests a range for monovalent cations between 20 to 100 μM and divalent cations between 1.5 to 5 mM.
Salt correction formula: Factors such as ΔG and Tm affect PCR performance and alter the efficiency of primer pairs. The SantaLucia (1998) salt formula is preferred by Primer3. This formula is designed to accommodate the salt correction independent of sequence but dependent on oligonucleotide length.
Conc. of divalent cations: This is the concentration of divalent salts present in the PCR mix. Set value at 3.5 mM.
Conc. of dNTPs: A dNTP concentration of 200 µM is usually recommended for Taq polymerase to function efficiently in a conventional PCR. Some SYBR Green master mixes come with Taq, KCl, MgCl2, and dNTP. These mixes tested in laboratories give maximum performance. Enter the value as 0.20 mM
Annealing Oligo Concentration: Used to calculate the oligo melting temperature, this is the nanomolar concentration of annealing oligos in the PCR. Leave at default.
Objective function penalty weights for Primers: The penalty weights section allows Primer3 users to modify the criteria that Primer3 uses to select the best sets of primers.
Objective Function Penalty Weights for Primers:
• Tm Lt = 1; Gt = 1
• Size Lt = 1; Gt =1
• Self complementary = 3
• 3’ Self complementary = 3
• #N’s = 2
• All other values = 0
Objective Function Penalty Weights for Primer Pairs:
• Product Tm: Lt = 1; Gt = 1
• Tm difference = 2
• Any complementary = 3
• 3’ complementary = 3
• Primer Penalty weight = 1
• All other values = 0
Analyzing primers: Once all the Primer3 parameters are set as mentioned above, Primer3 will design primer pair options.
Once all options are entered, press ‘Pick Primers’.
The sequence will be displayed under the primers with the details on the primers generated, and the location of the primers within the sequence is indicated by >>>>>>> for the forward primer and <<<<<< for the reverse primer. The first primer that has the correct product length and Tm is analyzed for the secondary structure using Beacon DesignerTM free edition. Select the primer pair based on the 3′ value, which should not be more than 3.00. The 3′ value is the measurement of primer dimers formed within the primer pair (Figure 5).
Figure 5. Image of Primer3 output indicating the 3′ value, for the primer dimers in SYN1
Use Beacon DesignerTM free edition to check for primer secondary structures. The acceptable ΔG value for the primers should not be more than -3.5.
Go to http://free.premierbiosoft.com. Click on Beacon Designer [Free Edition]. Then click on launch Beacon DesignerTM Free Edition.
Click the SYBR Green option and enter the left primer sequence in the box for ‘Sense primer.’ Enter the right primer sequence in the box for ‘Anti-sense primer.’ Click ‘Analyze.’
Beacon Designer free edition allows you to visualize secondary structures that can form between primers or primer pairs. An example of the secondary structure analysis is shown in Figure 6.
Note: If self-dimers or cross dimers cannot be avoided, choose primers with the highest -ΔG (meaning the least negative number, the one closest to zero). Redesign primers with ΔGs more negative than -3.5 kcal/mol. If hairpins cannot be avoided, steer clear of hairpins that involve a 3’ end, and use UNAFold software to determine the melting temperature of the structure.
Figure 6. Images of Beacon Designer webpage for analyzing the secondary structure of SYN1 primer.
Use UNAFold software to check amplicon secondary structures.
Once the primers have been checked for secondary structures, an additional QC step is needed to verify the amplicon’s secondary structures using UNAFold software by Integrated DNA Technologies (IDT).
Go to: https://www.idtdna.com/UNAFold. Copy the amplicon (include both forward and reverse primers) into the sequence box. Change the annealing temperature to 60°C and the magnesium concentration to 3 mM. Click submit.
Evaluate the structures that are displayed for the amplicon by checking for the ΔG values, which should not be -3.5.
In-silico PCR (https://genome.ucsc.edu/cgi-bin/hgPcr): This is a QC step for verification of the exon spanning of the designed forward and reverse primers and also to cross verify the Tm and product length of the primer sets (Figure 7).
Insert the forward and the reverse primer for each gene into the blank spaces.
It is also important to set the target to GENCODE, which shows cDNA sequence, whereas genome assembly shows genomic DNA and allows to verify of intron spanning primer sequences. https://genome.ucsc.edu/FAQ/FAQgenes.html#ens.
Select submit, to study results of in-silico PCR.
Figure 7. In-Silico PCR analysis and result for SYN1 in UCSC browser.
All the primers are designed and ordered at a 40 nmol scale. Primer stocks are re-constituted at 100 µM in nuclease-free water and dilutions at 10 µM are the working concentration.
Test primer efficiency
It is important to test primer efficiency for each primer pair by creating a standard curve with five serial dilutions of your cDNA template, e.g., 1:5 dilution. The primer efficiency should lie between 90-110%. The standard curve should cover the Ct value of the experimental value (Figure 8).
The primer (forward and reverse) concentrations are 300 nM and the cDNA concentration is set for a 5-fold serial dilution (12.5 ng, 2.5 ng, 0.5 ng, 0.1 ng, 0.02 ng) for a 5 µL reaction volume as triplicates in a 384-well plate.
The primer efficiency is calculated using the Excel template available at https://toptipbio.com/calculate-primer-efficiencies/.
Figure 8. Primer efficiency calculation of genes involved in different timepoints of Ngn2 cortical neuron differentiation. OCT4 is tested for its efficiency with iPS cells.
Plating of primers for multi-well SYBR Green qPCR array for cortical neuron differentiation
For this array, we designed SYBR Green primers for 27 genes with two housekeeping genes. We wanted to capture pluripotency genes, neuro-precursor genes, and genes that are upregulated in cortical neurons. We also looked for synaptic markers and astrocyte gene expression. We used triplicates for each gene in a 96-well optical plate to study the expression (ΔΔCt) for each gene along with negative control (NC) and reverse transcriptase control (RTC). The working concentration of the primers diluted in nuclease-free water was 10 μM.
Prepare the arrays for the PCR run at least a day in advance for the primers to dry out overnight.
Plate primers according to the design of the 96-well, in triplicates (Figure 9). Pre-mix the forward and reverse primer for each gene and add to the corresponding well. The calculation for the amount of primer to be added to each well is shown in Step 3.
Figure 9. 96-well plate template design for the multi-well qPCR reaction.
Primer volume:
Primer concentration in 20 μL qPCR reaction volume.
Total reaction volume of qPCR reaction per well of 96 well plates: 20 µL.
Primer volume (from 10 µM working solution): 0.6 µL (forward primer) + 0.6 µL (reverse primer) to reach 300 nM per reaction.
Total: 1.2 µL of pre-mixed primers per gene per well.
The primer mix is prepared in triplicates per gene. The amount of primer mix is (0.6 μL + 0.6 μL) × 4 times (includes 1 extra reaction for pipetting error). Prepare mix depending on the number of plates that are prepared.
Optional: For plating of 96- or 384-well plates, pipetting can be facilitated by using PlateR (Biosistemika), a tablet-based visual support to pipette samples into wells.
CRITICAL. Dispense the primer mix at the bottom of the well and spin down the plate for the primer mix to settle at the bottom of the well.
Let the primer-coated plates dry overnight at room temperature in a Tupperware container to reduce the contamination.
Time consideration: Coating of primers for a single 96-well plate takes about 20–30 min.
Note: Do the primer coating for the array design after optimization in large batches. Plates can be stored at room temperature for several months, e.g., in sealed plastic bags.
The concentration of primers and cDNA was determined as 300 nM and 2 ng (calculated for 96-well) based on the primer efficiency experiments (done in a 384-well plate) for each gene primer pair.
qPCR Analysis (PowerUpTM SYBRTM Green Master Mix [Thermo Fisher, catalog number: A25780])
PCR reaction mix:
Since the primers are already pre-coated onto the plates, only the SYBR Green master mix, cDNA template, and nuclease-free water are combined as a master mix and added to each well. Since the pre-coated primers dry out, the master mix is made only with reagents shown in Table 4, which would be total volume of 20 μL.
Before adding to the plate, the reaction mix is mixed thoroughly and spun down to avoid air bubbles. The plate should be kept on ice while adding the reaction mix. Calculate 1–2 extra reactions to account for pipetting errors. For a 96-well plate reaction, e.g., prepare a 98× reaction mix (Table 4).
Table 4. Reaction mix for the multi-well Qpcr.
Components Volume (each well)
SYBR Green master mix 10 µl
cDNA template 2 ng
Nuclease free water variable
Total reaction mix 20 µl
Once the reaction mix is added, tightly seal the 96-well plate with the MicroAmp Optical adhesive film and centrifuge them briefly to remove any air bubbles and to bring all of the reaction mix to the bottom of the well.
Plate set-up in QuantStudio 6 Flex and link to the software
Once the plate is ready for the qPCR run, open the QuantStudio software v1.7.1 (link mentioned in the software section).
PCR reaction set-up (for Tm of Primers more than 60°C):
Spin down the plate after adding the reaction mix and then place it in the QuantStudio 6 Flex.
The thermal cycling settings are set according to the Table 5 below for the Tm of primers between 63–66°C. Annealing temperature should be approximately 3°C lower than Tm.
Table 5. Thermal cycling settings for the PCR reaction.
Step Temperature Duration Cycles
UDG activation 50°C 2 min Hold
Dual-LockTM Taq DNA polymerase 95°C 2 min Hold
Denature 95°C 15 s 40
Anneal/ extend 60°C 1 min
The instrument should be set for the default dissociation step as shown in Table 6.
Table 6. Setting for the dissociation step.
Step Ramp rate Temperature Time
Denature 1.6°C/s 95°C 15 s
Anneal 1.6°C/s 60°C 1 min
Dissociation 0.15°C/s 95°C 15 s
Once the run is complete the Ct data can be analyzed by clicking on analyze and the data can be exported as an excel file by clicking on the excel sheet.
The plate setup in Quantstudio 6 is illustrated in Figure 10. For detailed plate set up, run parameters, and analysis, follow the User Guide for the QuantStudio software attached: https://tools.thermofisher.com/content/sfs/manuals/4489822.pdf.
Figure 10. Workflow representation of setting up the plate in a QuantStudio 6 Flex software.
Data analysis
For the data analysis, we used the QuantStudio software to analyze the Ct values of each gene and the variability of replicates. The acceptable cycle difference should not be more than 0.5 cycles. The housekeeping genes B-ACTIN or GAPDH are used as the loading controls for ΔΔCt calculation (Livak and Schmittgen, 2001) of genes comparing the Day 0, Day 15, and Day 30 cortical neurons Ct values to the iPSCs Ct value. The negative template control should not show amplification (The link for the calculation of ΔΔCt in Excel is https://1drv.ms/x/s!AgUabBW4Y2yQgZEon-ZKuwMJ4PhaLQ).
As shown in Table 7, to calculate the average of 2-ΔΔCt fold change of genes, we initially compared the Ct of the gene of interest with the house-keeping gene (control), B-ACTIN, and the difference between them is the ΔCt. Next, to calculate the ΔΔCt, take an average of the ΔCt values of the iPSCs. When we subtract the ΔCt values of each sample from the average (ΔCt)iPSCs, we get the ΔΔCt. With the ΔΔCt values, we calculate the 2-ΔΔCt and the average of 2-ΔΔCt. This shows the fold change in the expression of genes in each sample relative to their expression in iPSCs. To visually illustrate the changes in gene expression, we plotted a heatmap for samples at different time points using GraphPad Prism. The pluripotency markers OCT4 and NANOG are highly expressed in the iPSCs (Figure 10) and expression is drastically reduced and, in some instances, undetectable with the assay at Day 15 and 30 of the cortical neuronal differentiation. Markers for early mature cortical, neuronal, and synaptic proteins show an increase in their expression on day 15 and 30 samples compared to the iPSCs (Figure 11). Both housekeeping genes B-ACTIN and GAPDH showed comparable results.
Table 7. ΔΔCt calculation of NANOG gene.
Figure 11. Fold change of gene expression using β-Actin as housekeeping gene comparing iPSCs with Day 0, Day 15, and Day 30 cortical neurons for pluripotency markers (OCT4 and NANOG), early neuronal markers (SOX2 and NESTIN), mature cortical neuronal markers (POU3F2 and TBR1) and synaptic markers (BASSOON and SYNAPSIN).
Summary:
In summary, we describe a comprehensive and economical protocol for a versatile multi-well SYBR Green qPCR protocol. Single-tube SYBR Green qPCR is a standard procedure in many labs to assess gene expression and there are also commercial platforms available for SYBR Green arrays. However, our protocol focusses on an efficient way to analyze multiple genes by building a multi-well qPCR array that can be customized and stored for several months at room temperature. These arrays are ideally suited to monitor iPSC differentiation protocols into various cell types and these arrays can be easily customized.
Acknowledgments
The study was supported by the California Institute for Regenerative Medicine (CIRM) Bridges program (TB1-01195).
Competing interests
Nothing to disclose.
Ethics
The work was approved under Stem Cell Research Oversight protocol SCRO-754 to use the WTC11 human-induced pluripotent stem cell for the Ngn2 differentiation.
References
Arya, M., Shergill, I. S., Williamson, M., Gommersall, L., Arya, N. and Patel, H. R. (2005). Basic principles of real-time quantitative PCR. Expert Rev Mol Diagn 5(2): 209-219.
Arikawa, E., Quellhorst, G., Ying, H., Pan, H. and Yang, J. (2011). RT2 ProfilerTM PCR arrays: Pathway-focused gene expression profiling with qRT-PCR. BioTechniques 43(5).
Boone, D. R., Micci, M. A., Taglialatela, I. G., Hellmich, J. L., Weisz, H. A., Bi, M., Prough, D. S., DeWitt, D. S. and Hellmich, H. L. (2015). Pathway-focused PCR array profiling of enriched populations of laser capture microdissected hippocampal cells after traumatic brain injury. PLoS One 10(5): e0127287.
Livak, K. J. and Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCt Method. Methods 25(4): 402-408.
SantaLucia, J., Jr. (1998). A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics.Proc Natl Acad Sci U S A 95(4): 1460-1465.
Thornton, B. and Basu, C. (2011). Real-time PCR (qPCR) primer design using free online software.Biochem Mol Biol Educ 39(2): 145-154.
Wang, C., Ward, M. E., Chen, R., Liu, K., Tracy, T. E., Chen, X., Xie, M., Sohn, P. D., Ludwig, C., Meyer-Franke, A., et al. (2017). Scalable Production of iPSC-Derived Human Neurons to Identify Tau-Lowering Compounds by High-Content Screening. Stem Cell Reports 9(4): 1221-1233.
Zhang, Y., Pak, C., Han, Y., Ahlenius, H., Zhang, Z., Chanda, S., Marro, S., Patzke, C., Acuna, C., Covy, J., Xu, W., Yang, N., Danko, T., Chen, L., Wernig, M. and Sudhof, T. C. (2013). Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 78(5): 785-798.
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Neuroscience > Nervous system disorders > Cellular mechanisms
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Genome-assisted Identification, Purification, and Characterization of Bacteriocins
KO Kirill V. Ovchinnikov *
TO Thomas F. Oftedal *
SR Sebastian J. Reich
NB Nadav S. Bar
HH Helge Holo
MS Morten Skaugen
CR Christian U. Riedel
DD Dzung B. Diep
(*contributed equally to this work)
Published: Vol 12, Iss 14, Jul 20, 2022
DOI: 10.21769/BioProtoc.4477 Views: 2202
Reviewed by: Alba BlesaValentine V TrotterXuhui Zheng
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Original Research Article:
The authors used this protocol in Microbiology Spectrum Oct 2021
Abstract
Bacteriocins are antimicrobial peptides with activity against antibiotic resistant bacterial pathogens. Here, we describe a set of methods aimed at purifying, identifying, and characterizing new bacteriocins. The purification consists of ammonium sulphate precipitation, cation-exchange chromatography, and reversed-phase chromatography. The yield of the bacteriocin is quantified by bacteriocin antimicrobial activity in a microtiter plate assay after each purification step. The mass of the purified bacteriocin is assessed by MALDI TOF MS analysis of the active fractions after reversed-phase chromatography. The mass is compared with the theoretical mass based on genetic information from the whole genome sequencing of the bacteriocin producer strain. Physicochemical characterization is performed by assessing antimicrobial activity following heat and protease treatments. Fluorescent techniques are used to examine the capacity of the bacteriocin to disrupt membrane integrity. Herein a set of protocols for purification and characterization of the bacteriocin nisin Z is used as a typical example in this paper.
Keywords: Bacteriocin Purification Peptides Antimicrobial peptide Antibiotic resistance Chromatography MALDI MALDI TOF Biosensor pHluorin Propidium iodide Pore formation
Background
Antibiotics used to treat bacterial infections are becoming increasingly less efficacious due to the emergence of antibiotic-resistant pathogens (Högberg et al., 2010). In addition, such pathogens are often resistant to two or more antibiotics. As a consequence, first line therapies often involve the administration of either multiple or broad-spectrum antibiotics (Hagihara et al., 2012; Khameneh et al., 2016; Frieri et al., 2017). The overuse of antibiotics is thought to be the primary selection pressure driving the dissemination of resistance (World Health Organization, 2018). In addition, broad-spectrum treatments are known to cause long lasting alterations to the healthy gut microbiota, which is likely to have unforeseen health consequences (Willing et al., 2011). For these reasons, there is a need for alternative antimicrobials, such as bacteriocins, that could be used therapeutically.
Bacteriocins are ribosomally synthesized antimicrobial peptides produced by bacteria to kill or inhibit other closely related bacteria for nutrients and/or niche competition (Eijsink et al., 2002). Bacteriocins comprise a very diverse group of peptides, from extensively post-translationally modified molecules (class I) to small unmodified peptides (class II) (Alvarez-Sieiro et al., 2016; Acedo et al., 2018). Most bacteriocins produced by Gram-positive bacteria are cationic (pI > 7) and hydrophobic/amphiphilic peptides (Diep and Nes, 2002). They are often of small size ranging from 40 to 70 amino acids, heat-stable, and do not lose activity after storage in organic solvents (2-propanol, acetonitrile, etc.). Most bacteriocins are protease-sensitive (especially unmodified peptides) and have narrow inhibitory spectra, targeting species or genera closely related to the producer (Nissen-Meyer and Nes, 1997), but some have wide inhibitory spectra (Field et al., 2015; Ovchinnikov et al., 2016). Unlike most antibiotics, bacteriocins normally exploit membrane proteins as receptors and disrupt the membrane integrity of sensitive cells upon binding, causing leakage of intracellular solutes and eventually cell death (Nes et al., 2007). Thus, due to different modes of action, bacteriocins are most often equally active against both antibiotic-sensitive pathogens and their antibiotic-resistant counterparts. Bacteriocins have many desirable properties for clinical use, such as high potency, low toxicity, specific inhibition spectrum, and the potential probiotic use of producer organisms (Cotter et al., 2013). However, bacteriocins have not been used in human clinical settings so far. There are a few challenges to the clinical use of bacteriocins, such as their sensitivity towards proteases and low solubility under physiological conditions. Another major factor is likely the insufficient investment spent on the discovery and characterization of new bacteriocins to find candidates more suitable for medical applications.
Here, we describe a set of methods for bacteriocin purification, identification, and characterization. The methods have been used to characterize several bacteriocins in our laboratory (Holo et al., 1991; Ovchinnikov et al., 2016; Desiderato et al., 2021; Goldbeck et al., 2021; Oftedal et al., 2021; Weixler et al., 2022). We believe that this scheme is a good starting point for most bacteriocins and could easily be optimized for special cases, such as multi-peptide bacteriocins, circular bacteriocins, or bacteriocins with relatively low isoelectric points.
Materials and Reagents
0.2 µm syringe filter, Filtropur S, PES (Sarstedt, catalog number: 83.1826.001)
Eppendorf Safe-Lock microcentrifuge tubes (Sigma-Aldrich, catalog number: EP0030123611)
1.5 mL microcentrifuge tubes (Eppendorf Safe-Lock, catalog number: EP0030123611)
Micro test plate, 96-well, transparent (Sarstedt, catalog number: 82.1581.001)
NalgeneTM PPCO Centrifuge Bottles (Thermo Scientific, catalog number: 3141-0250PK)
Glass laboratory bottles (VWR, catalog numbers: 215-1514, 215-1515, 215-1517, 215-1518)
15 mL reaction tubes (Sarstedt, catalog number 62.554.002)
Black microtiter plates (Sarstedt, catalog number: 82.1581.120)
D-(+)-Glucose monohydrate (Sigma-Aldrich, catalog number: 49159)
M17 broth (Oxoid, catalog number: CM0817)
Bacteriological agar (Oxoid, catalog number: LP0011T)
Ammonium sulphate (Sigma-Aldrich, catalog number: 7783-20-2)
Na2HPO4·2H2O (Sigma-Aldrich, catalog number: 71643)
NaH2PO4 (Sigma-Aldrich, catalog number: S0751)
NaCl (Sigma-Aldrich, catalog number: S7653).
Proteinase K (Sigma-Aldrich, catalog number: P2308)
2-Propanol ≥99.0%, GPR RECTAPUR® (VWR Chemicals, catalog number: 20839.366)
Hydrochloric acid (Sigma-Aldrich, catalog number: 320331)
Trifluoroacetic acid, suitable for HPLC, ≥99.0% (Sigma-Aldrich, catalog number: 302031)
Acetonitrile, LiChrosolv® Reag. Ph Eur. (Merck Millipore, catalog number: 1000302500)
α-cyano-4-hydroxycinnamic acid (Bruker, catalog number: 8201344)
Bruker MTP 384 Target Plate Ground Steel BC (Bruker, catalog number: 8280784)
Peptide Calibration Standard II (Bruker LabScape Daltonics, catalog number: 8222570)
Propidium Iodide (Fisher Scientific, Invitrogen, catalog number: P1304MP)
Brain Heart Infusion Broth (Dehydrated) (Thermo Scientific, Oxoid, catalog number: CM1135B)
GenEluteTM Bacterial Genomic DNA Kits (Sigma-Aldrich, catalog number: NA2120-1KT)
Chloramphenicol (Sigma-Aldrich, catalog number: C0378)
KH2PO4 (Sigma-Aldrich, catalog number: 795488)
MgSO4 (Sigma-Aldrich, catalog number: M7506)
(NH4)2SO4 (Sigma-Aldrich, catalog number: A4418)
Nisin (Sigma-Aldrich, catalog number: N5764-5G)
Micrococcin P1 (Cayman Chemical, catalog number: 17093)
MOPS (3-Morpholino-propanesulfonic acid) (Sigma-Aldrich, catalog number: 69947)
Solution A (see Recipes)
Solution B (see Recipes)
Sodium phosphate wash buffer (see Recipes)
PBS (Phosphate-buffered saline) (see Recipes)
HCCA matrix solution (see Recipes)
Listeria minimal buffer (LMB) (see Recipes)
Equipment
ÄKTA purifier w/ Box-900, pH/C-900, UV-900, P-900, Frac-900 (Pharmacia Biotech)
HiPrep SP XL 16/10 (GE Healthcare, catalog number: 28936540)
RESOURCE RPC 1 mL (Cytiva, catalog number: 17118101)
TS-100 Thermo-Shaker (Biosan, catalog number: BS-010120-AAI)
-86°C ULT Chest Freezer (Thermo Scientific, model: 8708)
Incubator (Termaks, model: KBP6395LL)
Microfuge 16 (Beckman Coulter)
FinnpipetteTM F2 GLP Kits (Thermo Scientific, catalog number: 4700880)
FinnpipetteTM F2 Multichannel Pipette (Thermo Scientific, catalog number: 4662030)
pH meter (Mettler Toledo® F20)
SPECTROstarNano (BMG LABTECH, Germany)
High-speed centrifuge Avanti J-26 XP w/ JA-14 rotor (Beckman Coulter)
Merck Milli-Q Integral 10 (Merck Millipore)
Ultrasonic bath (VWR, model: USC100T)
NanoDrop 2000/2000c (Thermo Scientific, catalog number: ND-2000C)
Hidex Sense Multi-Mode Microplate Reader
Rotary shaking incubator (I26, New Brunswick Scientific)
Infinite M200 fluorescence microplate reader (Tecan)
IKA RCT magnetic stirrer (IKA, catalog number: 0003810000)
Software
Unicorn 5.11 to support ÄKTA (Cytiva, https://www.cytivalifesciences.com/en/us/shop/unicorn-5-11-p-03388)
Procedure
Bacteriocin purification
Take the vial of bacteriocin producing culture Lactococcus lactis LMGT 4215 (nisin Z producer) from deep freezer (-80°C) and place it on ice or in a cold block.
Aseptically transfer culture to M17 agar plates supplemented with 0.5% wt/vol glucose (GM17) with sterile loop and streak out to obtain single colonies.
Incubate at 30°C for 24 h.
Take a single colony from the plate with a sterile loop and transfer it to a sterile culture tube containing 10 mL of the GM17 broth. Leave the tube O/N (overnight) at 30°C without shaking.
The following day, inoculate 1 L of GM17 with the culture prepared earlier (1% inoculum, v/v). Leave the bottle for 20–24 h without shaking at 30°C.
Note: Bacteriocin production usually peaks at the early stationary growth phase, but this can vary from strain to strain. Therefore, this has to be monitored for each new bacteriocin producer if yield is important. If the culture is incubated for a prolonged period of time, bacterial proteases can digest the bacteriocin of interest and reduce or even abolish antimicrobial activity. It is important to optimize the incubation time for each individual bacteriocin producer. Also, bacteriocin production can depend on the growth medium, temperature, and aeration—all those parameters should also be optimized for a particular bacteriocin producer (Telke et al., 2019).
Transfer the culture (1 L) of the bacteriocin producer to centrifuge bottles (floor centrifuge) at room temperature. Spin down the cells (10,000 × g, 20 min, 4°C). Distribute the supernatant (SN) carefully into a new 1.5–2 L bottle. Discard the cell pellet.
Note: Continue immediately to the next step to avoid bacterial growth in the supernatant.
Take an aliquot of the SN (1–2 mL) to analyze the initial bacteriocin concentration in the SN. Immediately heat the SN aliquot for 5 min at 100°C to sterilize and inactivate proteases. Store at -20°C until use.
Add ammonium sulphate dry salt to the cold cell-free SN (at 4°C) to reach 50% (w/v) saturation; mix well using a magnetic stirrer until all salt is dissolved. Leave the SN with ammonium sulphate O/N at 4°C for protein precipitation.
Notes:
Use an ammonium sulphate saturation calculator (such as: http://www.encorbio.com/protocols/AM-SO4.htm). Increasing the ammonium sulphate concentration up to 70% saturation can increase yield as more of the bacteriocin will precipitate.
Bacteriocins are unstructured in water, meaning that there is no need for careful and gradual addition of ammonium sulphate. In our laboratory, the procedure takes only a few min. After adding the ammonium sulphate, the solution can be left at 4°C for a few days without loss of bacteriocin activity, as proteases are unlikely to be active at high concentrations of ammonium sulphate. However, some bacteriocins lose activity due to oxidation, such as pediocin PA-1 (Fimland et al., 2000); in this case, prolonged storage in ammonium sulphate is not recommended.
Centrifuge the ammonium sulphate solution (12,000 × g, 45 min, and 4°C), and carefully discard the SN from the centrifuge bottles to avoid resuspension of the protein pellet because loss of the protein pellet will reduce yield.
Gently resuspend all protein pellets in Milli-Q water to a total volume of 150 mL (100–150 mL/L of starting volume of supernatant). Use a 5 mL pipet to dislodge and resuspend the pellets. Transfer the total volume to a new bottle or beaker. Adjust the pH of the protein solution to 4 by the addition of 1 M HCl.
Note: Reducing the pH ensures that bacteriocin peptides are positively charged, which improves binding to the cation-exchange column.
Connect the cation exchange column HiPrep 16/10 SP-XL column to the ÄKTA purifier system equipped with the fraction collector. Set the maximum pressure limit to 0.5 MPa (highest pressure limit for that column) to avoid potentially damaging the column.
Wash pump A with Milli-Q water with a pH of 4 and pump B with 1 M NaCl (unbuffered).
Equilibrate the column with 5 CV (column volumes; 100 mL) of Milli-Q water adjusted to pH 4.
Place pump A inlet into the protein solution and apply it to the column at a flow rate of 1–7 mL/min. Collect the flow-through in a new bottle.
Wash the column again with 5 CV of Milli-Q pure water at pH 4 (this step can be omitted).
Place pump A inlet in 20 mM phosphate buffer (pH 7) and wash the column with 5 CV (100 mL). Collect the flow-through in a new bottle.
Elute the bacteriocin with a linear gradient from 0 M to 1 M NaCl (unbuffered) at a flow rate of 5 mL/min over 20 min. Set the fraction collector to collect 20 fractions of 5 mL each. Each fraction, as well as the initial heat-treated SN, the cation-exchange flow-through, and the “wash” fractions, are checked for antimicrobial activity using the microtiter plate assay (see below). The active fractions eluted with NaCl are pooled for the reversed-phase chromatography (RPC) purification.
Note: To prevent bacteriocin aggregation, it is recommended to reduce the pH of the pooled active fractions to 2 with 1 M HCl. This is especially important if the cation-exchange eluate will be stored for a long time and/or the purified bacteriocin molecules are large (>40 residues) and hydrophobic. The recommended temperature to store bacteriocins is -20°C.
RPC purification is performed with a resource RPC column (1 mL) connected to ÄKTA purifier system. First, prepare 200 mL Milli-Q water with 0.1% (v/v) trifluoroacetic acid (TFA; solution A) and 200 mL 2-propanol with 0.1% (v/v) TFA (solution B). Wash pump A and pump B with solution A and B, respectively. Set the maximum pressure limit to 4 MPa (highest pressure limit for that RPC column) to avoid potentially damaging the column. Equilibrate the RPC column with at least 10 mL of solution A.
Change pump A inlet from solution A to the pooled active fractions from cation-exchange chromatography (eluate). Apply the eluate to the column at 3–5 mL/min flow rate.
Use a linear gradient (0–100%) of solution B at the flow rate of 1.0 mL/min for elution of the bacteriocin.
Note: Normally, bacteriocins are eluted at 25–50% solution B.
Set the fraction collector to collect 1 mL per fraction from the RPC column. Collect a total of 30–40 fractions.
Take a 10 µL aliquot from each fraction for antimicrobial activity test in a microtiter plate assay (see microtiter plate protocol below).
Microtiter plate assay
Add 100 µL of GM17 broth medium to the wells A1 to A11 of a microtiter plate. Add 200 µL to well A12 as a control; this well should have no growth.
Add 100 µL of the heat-treated supernatant or cation-exchange fractions (flow-through, wash flow-through, elution fraction) to A1 to a total volume of 200 µL.
Notes:
For reversed-phase fractions, use 10 µL of each reversed-phase fraction plus 90 µL of growth medium, so that the total added volume is 100 µL to each well.
If the purified bacteriocin is predicted (BAGEL4, AntiSMASH, see below) to consist of two or more different peptides, the individual peptides can be eluted into different fractions, thereby resulting in low or no antimicrobial activity. In this case, we recommend pooling the fractions corresponding to the peaks and seeing if the antimicrobial activity is restored. A checkboard assay can then be performed to determine which two fractions the peptides are in.
The growth of mutants resistant to the bacteriocin can supersede the growth of the wild-type strain during incubations longer than 5–6 h; hence, avoid overnight incubations.
Mix the liquid in A1 by pipetting up and down 4–5 times.
Take 100 µL from A1 and transfer to A2, and pipet up and down 4–5 times to mix. Move 100 µL from A2 to A3 and so on until A10.
After mixing in A10, discard the tip containing 100 µL of liquid.
Make 25 times diluted O/N culture of indicator (known to be sensitive towards your bacteriocin, such as Lactococcus lactis IL1403 or Listeria innocua LMGT 2785 for nisin), e.g., 1 mL O/N culture into 24 mL of BHI broth.
Add 100 µL of the diluted culture to well A11. Now there is 200 µL in A11 with no bacteriocin; this is a positive control for normal cell growth.
Continue adding 100 µL of diluted indicator culture to A10, then A9, and so on, up to A1 without changing the tip(s). Now there is 200 µL of liquid in all A1–A12. A12 will always be transparent (pure broth), and A11 will become turbid (only bacteria).
Note: Other fractions can be tested using the rest of the microtiter plate (B1-H1). After application of the test samples into the wells, use a multichannel pipette.
Incubate the plate at 30°C for 5–6 h.
Measure growth at A600 using a spectrophotometer such as the SPECTROstar Nano. One bacteriocin unit (BU) is defined as the amount of bacteriocin that inhibits the growth of the indicator strain by at least 50% in 200 µL culture (i.e., ≤ 50% of the turbidity of the control culture without bacteriocin). The amount of antimicrobial in column 5 of Figure 1 is then 1 BU or 5 BU/mL. The RPC fraction then has an activity of 3,200 BU/mL if 10 µL of the RPC fraction was added to well No. 1 at the beginning.
Note: Using the bacteriocin purification protocol presented here, we typically achieve 60–70% yield starting from 320 BU/mL in the cell-free supernatant.
Figure 1. An example of the microtiter plate assay. Eight aliquots of nisin Z (10 µL each) from the same RPC fraction were tested for antimicrobial activity against L. lactis IL1403. The plate was incubated for 5 h at 30°C before optical density was read at 600 nm. Wells with clear inhibition (more than 50% compared to the OD in wells of column 11) are shown in yellow (columns 1–5), cultures without bacteriocin in brown (positive control; column 11), cultures with no or less than 50% inhibition in white, and GM17 broth control in blue (negative control; column 12).
Protease-sensitivity
Reconstitute proteinase K in Milli-Q water to 20 mg/mL.
Dilute indicator strain L. lactis IL1403 (for nisin Z) in GM17 soft agar (0.8% agarose) cooled to 45°C; pour evenly over a GM17 agar plate. Leave the soft-agar to solidify for 3–5 min with the lid partly off.
Drop 2–3 µL of the bacteriocin producing O/N culture (or a bacteriocin containing solution). Drop 2 µL of proteinase K solution 4–5 mm near the bacteriocin-producing culture (make sure the drops do not mix). Let the plate dry for 5–10 min before incubation O/N at appropriate temperature. Next day a “crescent moon” shape will appear on the plate if the antimicrobial is susceptible to proteinase K, see Figure 2.
Note: Circular and highly modified bacteriocins can be resilient to proteinase K.
Figure 2. Proteinase K drop (indicated with the black dot) degrades nisin Z produced by L. lactis LMGT 4215 (A), making it inactive against indicator culture L. lactis IL1403 (B).
Heat-stability
Spin down the O/N culture of the bacteriocin producer using a centrifuge (10,000 × g, 3 min). It is also possible to further sterilize the SN by filtration using a 0.2 µm filter.
Take 1 mL of the cell-free SN and distribute it equally into two centrifuge tubes. Leave one tube at room temperature, and place the other in a heating block (or water bath) at 100°C for 5 min. Compare antimicrobial activity in the two tubes (heated and non-heated) using a microtiter plate assay as described above.
Note: Bacteriocins are heat-stable molecules and do not lose their activity after heating. If the antimicrobial activity is lost after heating, it is most likely to be due to antimicrobial enzymes/proteins (of high molecular weight).
MALDI TOF MS
Prepare the MALDI matrix solution as described in the recipes section. Thoroughly dissolve the α-cyano-4-hydroxycinnamic acid (HCCA) by vortexing, followed by sonication (5 min).
Note: Although a number of alternative matrices, such as 2,5-didroxybenzoic acid (DHB), could work well, we find that HCCA is particularly useful for bacteriocin analysis.
Prepare the calibration standard by dissolving the Peptide Calibration Standard II in 0.1% TFA according to the manufacturer’s instructions. Store the peptide calibration standard as 4–5 µL aliquots at -20°C until use.
Note: For optimal results, it is recommended to calibrate the mass axis frequently. This is achieved by acquiring spectra from calibration standards covering the useful mass range, which may be obtained from several vendors.
To 1–2 µL of RPC purified bacteriocin sample, add an equal volume of matrix solution in, e.g., a 0.2 mL PCR tube, and mix thoroughly by pipetting up and down several times. Apply a small drop (0.5–1 µL) to a spot on the MALDI target plate and let the droplet air dry.
Note: For best mass accuracy results, always apply your sample next to a calibration spot, which is prepared the same way as the sample spot.
Mount the target plate in the target frame, insert the frame into the instrument, and wait for the complete evacuation of the ion source. Load an appropriate (positive reflectron mode) acquisition method. Set the instrument to an acceleration voltage (ion source 1) of 20 kV, ion source 2 of approximately 18 kV, reflectron voltage 1 and 2 of approximately 21 kV and 11 kV, respectively, and a PIE (delayed extraction) setting of approximately 140 ns. To suppress low mass (mainly matrix) signals, use a deflection setting of 400–600.
Note: The procedure described applies to analysis performed using the Bruker Daltonics Ultraflex and Ultraflextreme MALDI-TOF/TOF instruments. For other systems, adjustments to sample preparation as well as to instrument settings may be required.
Position the cursor on the appropriate spot and start firing the laser. Adjust the laser intensity to achieve maximum resolution. Achieve the required peak intensity and signal/noise ratio by accumulating several shots; increasing the laser intensity instead may lead to poor resolution and mass accuracy. Once an acceptable spectrum has been accumulated, calibrate the instrument by assigning the peaks to a list of theoretical monoisotopic m/z values, using a cubic enhanced function. A calibration with <5 ppm error is acceptable; normally, <2 ppm is achieved. Once the calibration spectrum has been accepted, the instrument’s mass axis is calibrated, proceed to acquire data from your sample spot(s). A representative example for nisin is shown in Figure 3.
Figure 3. MALDI TOF MS spectrum obtained from the most active RPC fraction. The mass of 3329.6 m/z corresponds well with the predicted mass for nisin Z (containing one unmodified Ser/Thr).
Whole genome sequencing and analysis
Prepare genomic DNA from the bacteriocin producer from 1.5 mL of overnight culture using the GenElute Bacterial Genomic DNA kit according to the manufacturer’s instructions.
Ensure that the sample meets the minimum requirements set by the sequencing laboratory. For microbial genome sequencing by Novogene, the sample concentration should be ≥ 10 ng/µL by Qubit with a minimum volume of 20 µL. The total amount of DNA should be ≥ 200 ng. The DNA should migrate on an agarose gel as a single band at approximately 20–25 kb, and OD260/280 should be 1.8–2.0 by NanoDrop.
Ship the sample to your sequencing provider (e.g., Novogene) for bacterial whole genome sequencing (100× coverage, paired-end 150 bp).
Download the sequencing results using the web interface from your sequencing provider. Two files should be associated with the sample and have a suffix _R1/_1 for forward reads and _R2/_2 for reverse reads.
Create an account with https://www.patricbrc.org, which provides free bioinformatic analyses such as assembly.
Note: Most assembly software is freely distributed and can be executed on your personal computer (such as SPAdes, MEGAHIT, ALLPATHS-LG, IDBA-UD, MIRA, and Velvet). However, these tools are inaccessible to most researchers because they require familiarity with the command-line interface and GNU/Linux (or Windows Subsystem for Linux).
In the web interface, go to WORKSPACES and “Genome Groups”. Go to “Upload”, then “Select Files”. Select both sequencing files. Then “Start Upload”.
Select the first file, then “Edit type” and select “reads” in the drop-down menu. Do this for both files.
Go to “Services” then “Assembly”. In the “Paired read library” box, select read file 1 as the file named _R1 or _1. For read file 2, select the file named _R2 or _2.
In the box “Parameters” select SPAdes under “Assembly strategy”, set the output folder to “/home/Assemblies”. Give the assembly an output name.
Click the right arrow in the “Paired read library” box, then click “Assemble” at the bottom.
When the assembly is finished, go to “Workspaces” and select “home”. Double-click on the “Assemblies” directory, then on the directory with the assembly name chosen previously.
Select the file named *contigs.fasta, then download the file by clicking “DWNLD” in the green bar to the right.
Submit the file to http://bagel4.molgenrug.nl and https://antismash.secondarymetabolites.org to identify bacteriocin genes, see Figure 4A.
Analyze the identified genes and compare the theoretical monoisotopic mass with that obtained by MALDI TOF MS. The mass can be calculated using a tool such as PeptideMass (https://web.expasy.org/peptide_mass/), see Figure 4B.
Figure 4. AntiSMASH search result. AntiSMASH correctly identifies a lanthipeptide cluster in the assembled contigs from the nisin Z producer (A). Theoretical monoisotopic mass of the predicted core peptides is provided in a panel located at the lower right of the AntiSMASH window (B). The mass measured by MALDI TOF MS is correctly predicted in the alternative weights assuming 1 unmodified Ser/Thr (3331.0 Da).
Propidium iodide pore formation assay
Dilute RPC purified antimicrobial in PBS containing 40 µM propidium iodide to total volume of 100 µL in the well of a black 96-well plate. Include three controls, one containing no antimicrobial, one containing an antimicrobial that does not form pores such as micrococcin P1, and one containing a known pore-former such as commercially obtained nisin A.
Prepare 20–50 mL overnight culture of your indicator, such as L. lactis IL1403 in GM17. Wash the cells once in PBS and resuspend to an OD600 of 1.
Add 100 µL of cell suspension to the wells containing diluted antimicrobial and the negative controls.
Immediately place the 96-well plate in the Hidex Sense plate reader and measure the fluorescence every 10 min (kinetic) for 3 h with excitation at 535/20 nm (515–555 nm) and emission at 630/40 nm (590–670 nm); see Figure 5 for a representative result and Figure 6 for the principle of the Propidium iodide assay.
Note: Many fluorometers can produce very large values depending on the settings and dynamic range of the instrument. Here, we are only interested in the difference between samples; relative fluorescence values are obtained by dividing readings from all samples by the same constant (e.g., the first reading from the well containing micrococcin P1, making this value equal to 1).
Figure 5. Propidium iodide pore formation assay. An increase in fluorescence indicative of pore formation is observed for commercial nisin A (green) as well as for the purified fraction of nisin Z (grey). Wells with micrococcin P1 (yellow), which does not form pores but kills cells by inhibiting protein synthesis, or the control with no added antimicrobial (NC; blue), show no increase in fluorescence.
Figure 6. Principle of the propidium iodide-based pore formation assay. Intact bacterial membranes are impermeable to propidium iodide molecules (left). Membrane disruption allows PI to diffuse into bacteria and interact with DNA, causing an increase in the fluorescence intensity (right). The triangle represents the fluorescence emission from PI in solution (small triangle, left) and when interacting with dsDNA (larger triangle; right).
Assessment of pore formation using pHlourin biosensors
Inoculate 5–10 mL of BHI containing 10 µg/mL chloramphenicol from a single bacterial colony of the biosensor bacteria, e.g., Listeria innocua/pNZ-pHin2Lm (biosafety level 1) or Listeria monocytogenes/pNZ-pHin2Lm (BSL 2) (Reich et al., 2022), and incubate overnight at 37°C under shaking conditions (130 rpm).
Next morning, harvest the bacteria by centrifugation at 4,500 × g for 10 min, wash with an equal volume of PBS, and measure the OD600 (typically between 3–4). Centrifuge again and resuspend bacteria at an OD600 of 3 in Listeria minimal buffer (LMB) (Crauwels et al., 2018).
Prepare your samples in a black 96-well microtiter plate as follows:
For general analysis of activity in multiple samples, distribute 100 µL per sample to the wells of the microtiter plate. Include controls of 100 µL LMB (no pore formation) and 100 µL LMB containing 10 µg/mL of a commercial nisin A preparation (maximum pore formation).
For closer analysis of activity in up to eight samples, fill as many rows of the plate as samples to be analyzed with 100 µL of LMB per well. Add 100 µL of sample to the first well of a row and mix by pipetting. Prepare horizontal dilution rows by transferring 100 µL to the next well using a multichannel pipette, ensuring always to mix well. Repeat until column 11, then discard 100 µL from the wells in column 11. Use wells in column 12 for positive and negative controls as described in step 3a.
Note: Column 12 is used for both negative and positive controls, e.g., by using wells A12/B12/C12 for negative and D12/E12/F12 for positive controls.
Using a multichannel pipette, add 100 µL of LMB-suspended sensor bacteria to all wells. Mix carefully by shuffling the plate on the lab bench.
Incubate at RT in the dark for 30 min.
Measure fluorescence emission at 520 nm of each well using an infinite M200 multiplate reader (Tecan) with excitation at 400 and 480 nm.
In the results file, divide the emission value for excitation at 400 nm by the emission value for excitation at 480 nm. Compare ratio values by plotting, e.g., as bar chart (Figure 7). Pore formation leads to collapse of intracellular pH, leading to a decrease in fluorescence ratio.
Figure 7. Principle of assessing membrane integrity via pHluorin2 fluorescence. Biosensor bacteria constitutively express the pH-sensitive fluorescent protein pHluorin2, which shows a bimodal excitation spectrum with maxima at 400 and 480 nm. In intact cells, the ratio of fluorescence intensities at the two excitation peaks is defined by the intracellular pH (left). If pH homoeostasis is disrupted by membrane-damaging compounds, intracellular pH drops to the pH of the assay buffer (pH 6.2), and this leads to a ratiometric change in the fluorescence intensity of pHLuorin2 at the two excitation peaks right). Calculation of fluorescence intensity ratios at the two excitation maxima (400 and 480 nm) allows discrimination between intact and disrupted cells (middle).
Recipes
Solution A
Reagent Final concentration Amount
Trifluoroacetic acid (99%) 0.1% 0.1 mL
H2O n/a 99.1 mL
Total n/a 100 mL
Solution B
Reagent Final concentration Amount
2-Propanol (≥99.0%) n/a 99.9 mL
Trifluoroacetic acid (99%) 0.1% 0.1 mL
Total n/a 100 mL
Sodium phosphate wash buffer
Reagent Final concentration Amount
NaH2PO4 (1 M) 650 µL
Na2HPO4 (0.5 M) 2670 µL
H2O n/a 96.68 mL
Total n/a 100 mL
PBS (Phosphate-buffered saline)
Reagent Final concentration Amount
NaCl 137 mM 8 g
KCl 2.7 mM 0.2 g
Na2HPO4 10 mM 1.44 g
KH2PO4 1.8 mM 0.24 g
H2O n/a Up to 1,000 mL
Total n/a 1,000 mL
HCCA matrix solution
Reagent Final concentration Amount
HCCA 15 mg/mL 15 mg
TFA (10%) 0.1% 10 µL
Ethanol 50% 500 µL
Acetonitrile 49.9% 490 µL
Total n/a 1 mL
Listeria minimal buffer (LMB)
Reagent Final concentration Amount
MOPS 100 mM 2.09 g
KH2PO4 4.82 mM 65.6 mg
Na2HPO4 11.55 mM 206 mg
MgSO4 1.7 mM 20.5 mg
(NH4)2SO4 0.6 mg/mL 60 mg
Glucose 55 mM 1.09 g
NaOH (1 M) NA to pH 6.5
Total n/a 100 mL
Acknowledgments
This project has received funding from the Bio Based Industries Joint Undertaking under the European Union’s Horizon 2020 research and innovation program under grant agreement No 790507, and by Norway Grants 2014–2021 via the National Centre for Research and Development (grant number NOR/POLNOR/PrevEco/0021/2019-00). TFO acknowledges funding by the Research Council of Norway (project no 275190).
The propidium iodide pore formation assay has been adapted from Chehimi et al. (2010), Wang et al. (2014), and Boix-Lemonche et al. (2020). The Norway grants 2014–2021 via the National Centre for Research and Development; NOR/POLNOR/PrevEco/0021/2019-00.
Competing interests
The authors declare no competing interests.
References
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DSP-crosslinking and Immunoprecipitation to Isolate Weak Protein Complex
KA Kotaro Akaki
TM Takashi Mino
OT Osamu Takeuchi
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4478 Views: 5698
Reviewed by: Chiara AmbrogioSoumya MoonjelyAdriano Bolondi
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Original Research Article:
The authors used this protocol in eLIFE Oct 2021
Abstract
Detecting protein-protein interactions (PPIs) is one of the most used approaches to reveal the molecular regulation of protein of interests (POIs). Immunoprecipitation of POIs followed by mass spectrometry or western blot analysis enables us to detect co-precipitated POI-binding proteins. However, some binding proteins are lost during cell lysis or immunoprecipitation if the protein binding affinity is weak. Crosslinking POI and its binding proteins stabilizes the PPI and increases the chance of detecting the interacting proteins. Here, we introduce the method of DSP (dithiobis(succinimidyl propionate))-mediated crosslinking, followed by tandem immunoprecipitation (FLAG and HA tags). The eluted proteins interacting with POI can be analyzed by mass spectrometry or western blotting. This method has the potential to be applied to various cytoplasmic proteins.
Graphical abstract:
Keywords: Immunoprecipitation (IP) Tandem affinity purification Dithiobis(succinimidyl propionate) (DSP) crosslinking Protein-protein interaction (PPI) FLAG-tag Hemagglutinin (HA)-tag HeLa cells
Background
Detection of proteins interacting with POIs is one of the effective ways to explore how the POIs are regulated by other proteins in the cells. Immunoprecipitation of the POI is a widely used method to co-precipitate the associating proteins, which can be detected by following mass spectrometry or western blot analysis. When the interaction between a protein and the POI is stable and strong enough, crosslinking is not necessary to isolate the binding protein. However, the simple immunoprecipitation method may not be suitable for the detection of binding proteins that bind to the POI weakly or transiently. DSP is a cell-permeable chemical crosslinker that reacts with amino groups such as lysine residue. Therefore, treatment of cells with DSP can strengthen the PPI in the cells (Lomant and Fairbanks, 1976; Zlatic et al., 2010) (Figure 1). Furthermore, since DSP has a disulfide bond in its spacer arm, this crosslinker can be cleaved by a reducing agent after the isolation of the protein complex to obtain linear proteins.
By performing DSP crosslinking and following immunoprecipitation and mass spectrometry analysis, we have previously investigated IL-1β-dependent PPI of Regnase-1, an RNase which degrades mRNAs coding inflammatory genes. We discovered that SKP1, CUL1, F-box (SCF) proteins, and 14-3-3 proteins bind to Regnase-1 in an IL-1β stimulation-dependent manner (Akaki et al., 2021).
Here, we describe the method of DSP crosslinking and immunoprecipitation using HeLa cells expressing POIs. Whereas previous methods of DSP-crosslinking and protein purification were performed with single immunoprecipitation (Zlatic et al., 2010; Wang et al., 2019), we precipitated FLAG- and HA-tagged POI by tandem affinity purification after crosslinking to isolate binding proteins with low background. As the lysis buffer used in this method is sufficient to dissolve Regnase-1, which predominantly localizes in the cytoplasm, this method is suggested to be applicable to investigate PPIs of other cytoplasmic proteins.
Figure 1. Schematic illustration of the DSP reaction. One DSP molecule reacts with two proximal amino groups. After the purification of the crosslinked POI and proteins, the linkers can be cleaved by reducing agents such as 2-mercaptoethanol or dithiothreitol (DTT).
Materials and Reagents
1.5 mL tube (Eppendorf, Eppendorf Safe-Lock Tubes, 1.5 mL, Eppendorf QualityTM, catalog number: 0030120086)
50 mL tube (Thermo Scientific, 50 mL Conical Sterile Polypropylene Centrifuge Tubes, catalog number: 339652)
10 cm dish (Corning, Falcon® 100 mm TC-treated Cell Culture Dish, catalog number: 353003)
Scraper (VIOLAMO, Violamo Cell Lifter, catalog number: 1-2249-01)
20–200 μL pipette tips (Labcon, catalog number: 1093-260-000-9)
1,000 μL pipette tips (Labcon, catalog number: 1045-260-000-9)
5 mL pipettes (Thermo Scientific, NuncTM 5 mL Serological Pipette, catalog number: 170355N)
10 mL pipettes (Thermo Scientific, NuncTM 10 mL Serological Pipette, catalog number: 170356N)
25 mL pipettes (Thermo Scientific, NuncTM 25 mL Serological Pipette, catalog number: 170357N)
50 mL pipettes (Thermo Scientific, NuncTM 50 mL Serological Pipette, catalog number: 170358N)
HeLa cells
DSP (dithiobis(succinimidyl propionate)) (Tokyo Chemical Industry Co., Di(N-succinimidyl) 3,3'-Dithiodipropionate [Cross-linking Reagent], catalog number: D2473)
Dynabeads Protein G (Invitrogen, DynabeadsTM Protein G for Immunoprecipitation, catalog number: 10004D)
FLAG Peptide (Millipore, FLAG® Peptide, catalog number: F3290, Dissolve in TBS as described in “FLAG peptide stock solution”. Aliquot the solution in 20 μL and store at -30 °C.)
Anti-FLAG antibody (Merck, Monoclonal ANTI-FLAG® M2 antibody produced in mouse, catalog number: F3165)
Anti-HA antibody (Merck, Anti-HA antibody Mouse monoclonal, catalog number: H3663)
Lipofectamine 2000 (Invitrogen, Lipofectamine® 2000, catalog number: 11668500; any transfection reagent can be used if it works)
1 M Tris HCl pH7 (Invitrogen, Tris (1 M), pH 7.0, RNase-free, catalog number: AM9850G)
1 M Tris HCl pH8 (Invitrogen, Tris (1 M), pH 8.0, RNase-free, catalog number: AM9855G)
5 M NaCl (Invitrogen, NaCl (5 M), RNase-free, catalog number: AM9760G)
NP-40 (Nacalai Tesque, Nonidet(R) P-40, catalog number: 23640-94)
cOmplete Mini EDTA-free (Roche, cOmpleteTM, Mini, EDTA-free Protease Inhibitor Cocktail, catalog number: 11836170001)
PhosSTOP (Roche, PhosSTOPTM, catalog number: 4906837001)
H2O (Invitrogen, UltraPureTM DNase/RNase-Free Distilled Water, catalog number: 10977-023)
DMSO (Merck, Dimethyl sulfoxide, catalog number: D2650)
Urea (Nacalai Tesque, catalog number: 35940-65)
Tris (Nacalai Tesque, Tris(hydroxymethyl)aminomethane, catalog number: 35434-21)
HCl (Nacalai Tesque, Hydrochloric Acid(35%), catalog number: 18321-05)
SDS (Nacalai Tesque, Sodium Lauryl Sulfate, catalog number: 08933-05)
Glycerol (Nacalai Tesque, catalog number: 17045-65)
Bromophenol blue (Nacalai Tesque, catalog number: 05808-61)
DMEM (Nacalai Tesque, DMEM (4.5 g/L Glucose) with L-Gln, without Sodium Pyruvate, liquid, catalog number: 08459-64)
FBS (Gibco, catalog number: 10270-106, LOT: 42G9391K)
PBS (Nacalai Tesque, D-PBS(-) without Ca and Mg, liquid, catalog number: 14249-24)
Penicillin/Streptomycin (Nacalai Tesque, catalog number: 09367-34)
100 mM DSP (see Recipes)
Tris-HCl (1 M, pH 7.4) (see Recipes)
STOP solution (see Recipes)
Wash buffer (see Recipes)
IP buffer (see Recipes)
TBS (Tris Buffered Saline) (see Recipes)
FLAG peptide stock solution (see Recipes)
FLAG-elution buffer (see Recipes)
Urea elution buffer (see Recipes)
3× SDS sample buffer (see Recipes)
1× SDS elution buffer (see Recipes)
Equipment
CO2 incubator (SANYO, model: MCO-19AIC)
Cell counter (Beckman Coulter, model: Z1 Coulter Particle Counter)
Water bath (TAITEC, model: 0068750-000)
Magnetic stand (Invitrogen, DynaMagTM-2 Magnet, model: 12321D)
Rotating incubator (TAITEC, model: RT-50)
Centrifuge (TOMY, model: MX-307)
Heat block (astec, Block Incubator, model: BI-516S)
Micropipette (up to 20 μL) (Gilson, PIPETMAN P20)
Micropipette (up to 200 μL) (Gilson, PIPETMAN P200)
Micropipette (up to 1,000 μL) (Gilson, PIPETMAN P1000)
Pipette controller (Drummond Scientific Company, Pipet-Aid XPress, model: 4-040-135)
Procedure
Preparing cells expressing POI
Notes:
Before the transfection, we culture HeLa cells in DMEM with 10% (FBS), 1% Penicillin/Streptomycin, and 100 µM 2-Mercaptoethanol. Do not use Penicillin/Streptomycin-containing media at the time of transfection.
As a negative control, always prepare sample(s) not expressing FLAG-HA tagged POI.
Alternatively, one can utilize the doxycycline-inducible system. In this case, one should establish a cell line expressing POI in a doxycycline-dependent manner. For the negative control, prepare sample(s) not treated with doxycycline.
Plate 8.0 × 105 HeLa cells in 10 cm dish per sample (10 mL of DMEM containing 10% FBS per dish).
Note: The number of cells can be scaled up or down depending on the purpose of the experiment. The size of dishes and how much plasmid DNA, buffers, beads, antibodies, etc., used should also be scaled up or down along with the amount of the cells.
Incubate the cells at 37 °C, 5% CO2 for 24 h.
Transfect plasmids for FLAG-HA-tagged POI expression using Lipofectamine 2000 according to manufacturer's instructions.
Note: We transfected HeLa cells in 10 cm dish with 4.0 μg of plasmids using 12 μL of Lipofectamine 2000 (each of them is diluted in 200 μL of serum-free DMEM). As too much overexpression of Regnase-1 (our POI) causes cell toxicity, we adjusted the amount of plasmid DNA used to avoid this. In addition, since the efficient amount of POI for IP and following analysis varies depending on POI, one might have to optimize the amount of plasmid DNA used for the transfection.
Incubate the cells at 37 °C, 5% CO2 overnight.
Preparing Wash buffer and IP buffer
On the day of DSP-crosslinking and immunoprecipitation, prepare Wash buffer and IP buffer (see Recipes) before the crosslinking. Keep them on ice.
DSP-crosslinking
Prepare 100 mM DSP just prior to DSP-crosslinking.
Dilute 100 mM DSP to 0.1 mM DSP in pre-warmed (37 °C) PBS.
Rinse the dishes twice with 5 mL of pre-warmed (37 °C) PBS/dish.
Discard the PBS from the dishes.
Add 5 mL of 0.1 mM DSP (prepared in step C2) in each dish.
Note: The higher the concentration of DSP is, the larger the crosslinked protein complex becomes. The concentration of DSP can be optimized depending on the PPI you aim to detect (Figure 2). Note that too much crosslinking makes the protein complex too large, which may result in non-specific crosslinking of non-relevant proteins.
Incubate the dishes at 37 °C for 30 min in a CO2 incubator.
Note: Alternatively, dishes can be incubated at 4 °C for ~2 h. In this case, crystals may appear on the dishes, and it is difficult to remove them. We found that these crystals do not interrupt immunoprecipitation, but we do not know the exact effect of these crystals on the result.
Figure 2. Optimization of DSP concentration. HeLa cells transiently expressing FLAG-HA-Regnase-1 (POI) were crosslinked with different concentrations of DSP (37 °C for 30 min), and the cell lysates were analyzed by western blotting. The smear band in 0.1 mM-DSP-treated sample indicates Regnase-1 crosslinked with other proteins; 1 mM DSP crosslinking resulted in huge protein complexes that could not migrate into the polyacrylamide gel. The effect of crosslinking can be abolished by reducing agents such as 2-mercaptoethanol.
Preparing beads for the first IP
During the DSP-crosslinking (step C6), prepare 40 μL of Dynabeads Protein G/sample in one 1.5 mL tube (e.g., 40 μL × 5* = 200 μL in one 1.5 mL tube for 4 samples; *5 = 4 + 1 for dead volume. This ratio should be used hereafter.)
Wash the Dynabeads Protein G with the same amount of Wash buffer three times.
Set the tube containing Dynabeads Protein G on a magnetic stand and let the beads accumulate onto the magnet.
Discard the supernatant with a pipette.
Add ice-cold Wash buffer (e.g., 40 μL × 5 = 200 μL for 4 samples).
Remove the tube from the magnetic stand.
Resuspend the beads by pipetting up and down.
Repeat step D2 twice more.
Set the tube containing the washed beads on a magnetic stand and discard the supernatant.
Resuspend the beads with ice-cold IP buffer (e.g., 40 μL × 5 = 200 μL for 4 samples).
Add 1 μL of anti-FLAG antibody per one sample (e.g., 1 μL × 5 = 5 μL of the antibody into 200 μL of the washed beads).
Incubate the beads on a rotating incubator at 4 °C for 1 h. (The speed of the rotator is set around the middle between the lowest and the fastest speed. This setting should be used hereafter.)
Note: We usually rotate samples at the middle speed (approximately 24 rotations/min; the radius of the rotating incubator is approximately 10 cm).
Stopping DSP-crosslinking
After the 30-min incubation at step C6, discard the 0.1 mM DSP and rinse the dishes once with 5 mL of pre-warmed (37 °C) PBS/dish.
Discard the PBS and add 5 mL of STOP solution (room temperature)/dish.
Incubate the dishes at room temperature for 15 min.
First IP
Discard the STOP solution from the dishes.
Rinse the dishes twice with 5 mL of ice-cold PBS/dish.
Discard the PBS from the dishes.
Add 500 μL of ice-cold IP buffer/dish.
Scrape off the cells with a scraper and transfer them with all the IP buffer on the dish into a 1.5 mL tube (one tube for one sample).
Note: Collect the cells as much as possible. We usually scrape all the edges of a dish first and then scrape together the cells and IP buffer to one side of the dish. Tilt the dish to the side of the gathered cells and collect them using a pipette.
Resuspend the cells by pipetting up and down.
Incubate the tubes on ice for 10 min to complete cell lysis.
Centrifuge the tubes containing the lysates at 20,000 × g at 4 °C for 5 min.
Transfer 500 μL of the supernatant to a new 1.5 mL tube for IP. (The remaining supernatant can be used as an input sample to check the expression of POI by western blotting.)
Add 40 μL of anti-FLAG-antibody-bound beads (prepared at step D6) into the tube containing the supernatant.
Incubate the tubes on a rotating incubator at 4 °C for 2 h.
Preparing beads for the second IP
Approximately 30 min before finishing the 2-h incubation at step F11, prepare and wash new Dynabeads Protein G, as in steps D1 to D4.
Add 1 μL of anti-HA antibody per one sample (e.g., 1 μL × 5 = 5 μL of the antibody into 200 μL of the washed beads).
Incubate the beads on a rotating incubator at 4 °C for 1 h.
Protein elution with FLAG peptides
Prepare FLAG-elution buffer by diluting FLAG peptide stock solution with TBS and keep it on ice.
After the 2-h incubation at step F11, wash the beads with ice-cold 700 μL of Wash buffer three times. (Discard the supernatant first. See step D2 for the way of beads washing.)
Discard the Wash buffer from the beads.
Resuspend the beads with 100 μL of FLAG-elution buffer (prepared at step H1) gently by pipetting up and down.
Incubate the beads with FLAG-elution buffer on a rotating incubator at 4 °C for 10 min.
Set the tubes on a magnetic stand and transfer the supernatant (containing POI and POI-bound proteins) to new 1.5 mL tubes.
Repeat steps H4 to H5 once more.
Set the tubes on a magnetic stand and transfer the supernatant to the tubes containing first eluted proteins at step H6. (The total volume is 200 μL/sample.)
Add 300 μL of ice-cold IP buffer to the collected supernatant. (The final volume is 500 μL/sample.)
Second IP
Mix the 500 μL of supernatant at step H9 with 40 μL of anti-HA-antibody-bound beads (prepared at step G3).
Incubate the beads on a rotating incubator at 4 °C for 2 h.
Final elution
After the 2-h incubation at step I2, wash the beads with 700 μL of ice-cold Wash buffer three times. (Discard the supernatant first. See step D2 for the way of beads washing.)
Elute the proteins by desired methods.
For western blotting
Add 75 μL of 1× SDS elution buffer and mix by pipetting up and down.
Note: If desired, add 2-mercaptoethanol (IP buffer:3× SDS sample buffer:2-mercaptoethanol = 40:17:3) to cleave the disulfide bond in DSP (Figure 2).
Incubate the samples at 95 °C for 5 min on a heat block.
Cool down the samples on ice.
Note: It takes approximately 5 minutes to cool down. The cooled samples can be stored at -80 °C.
Centrifuge the tubes at 20,000 × g at room temperature for 1 min.
Use the supernatant for western blotting (Figure 3).
Figure 3. A result of western blotting after protein elution. FLAG-HA-Regnase-1 (POI) transiently expressed in HeLa cells was crosslinked, immunoprecipitated, and eluted as above.
For mass spectrometry analysis
Note: Depending on efficiency or specificity of the elution of POI, optimization of elution method might be needed.
Add 100 μL of Urea elution buffer and mix by pipetting up and down.
Incubate the samples on ice for 5 min.
Set the tubes on a magnetic stand and collect the supernatant into new 1.5 mL tubes.
Some of the supernatant can be used for western blotting to check successful crosslinking and IP before mass spectrometry analysis. Mix 10 μL of the supernatant with 5 μL of 3× SDS sample buffer and follow the steps J2a-ii to J2a-iii.
Store the rest of the supernatant at -80 °C until sample preparation for mass spectrometry analysis.
Recipes
100 mM DSP
Reagent Final concentration Amount
DSP 100 mM 10 mg
DMSO n/a 247 μL
Total n/a n/a
Tris-HCl (1 M, pH 7.4)
Reagent Final concentration Amount
Tris-HCl (1 M, pH 7) n/a 16 mL
Tris-HCl (1 M, pH 8) n/a 4 mL
Total n/a 20 mL
STOP solution
Reagent Final concentration Amount
Tris-HCl (1 M, pH 7.4) 20 mM 600 μL
PBS n/a 29.4 mL
Total n/a 30 mL
Wash buffer
Reagent Final concentration Amount
Tris-HCl (1 M, pH 7.4) 20 mM 800 μL
NaCl (5 M) 150 mM 1.2 mL
NP-40 (10%) 0.5% 2 mL
H2O n/a 36 mL
Total n/a 40 mL
IP buffer
Reagent Final concentration Amount
Wash buffer n/a 10 mL
cOmplete Mini EDTA-free n/a 1 tablet
PhosSTOP n/a 1 tablet
Total n/a 10 mL
TBS (Tris Buffered Saline)
Reagent Final concentration Amount
Tris-HCl (1 M, pH 7.4) 50 mM 500 μL
NaCl (5 M) 150 mM 300 μL
H2O n/a 9.2 mL
Total n/a 10 mL
FLAG peptide stock solution
Reagent Final concentration Amount
FLAG peptide 5 mg/mL 4 mg
TBS n/a 800 μL
Total n/a 800 μL
FLAG-elution buffer
Reagent Final concentration Amount
FLAG peptide stock solution 100 μg/mL 20 μL
TBS n/a 980 μL
Total n/a 1 mL
Urea elution buffer
Reagent Final concentration Amount
Urea 8 M 4.8 g
Tris-HCl (1 M, pH 8.0) 50 mM 500 μL
H2O n/a Up to 10 mL
Total n/a 10 mL
3× SDS sample buffer
Reagent Final concentration Amount
Tris-HCl (1 M, pH 6.8) 150 mM 7.5 mL
SDS 6% 3 g
Glycerol 30% 15 mL
Bromophenol blue 0.25% 125 mg
H2O n/a Up to 50 mL
Total n/a 50 mL
1× SDS elution buffer
Reagent Final concentration Amount
3× SDS sample buffer 1/3 200 μL
IP buffer 2/3 400 μL
Total n/a 600 μL
Acknowledgments
We thank Y Ishihama and K Ogata at Kyoto university for the great advice about optimizing the method suitable for mass spectrometry analysis. This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI [18H05278] to OT and [19H03488] to TM; Japan Agency for Medical Research and Development (AMED) [JP20gm4010002, JP21ae0121030 and JP20fk0108454] to OT. KA was supported by ‘Kibou Projects’ Scholarship for doctoral Students in Immunology.
The original research paper for this protocol was published in eLife, DOI: 10.7554/eLife.71966.
Competing interests
We have no competing interests to declare.
References
Akaki, K., Ogata, K., Yamauchi, Y., Iwai, N., Tse, K. M., Hia, F., Mochizuki, A., Ishihama, Y., Mino, T. and Takeuchi, O. (2021). IRAK1-dependent Regnase-1-14-3-3 complex formation controls Regnase-1-mediated mRNA decay. Elife 10: e71966.
Lomant, A. J. and Fairbanks, G. (1976). Chemical probes of extended biological structures: synthesis and properties of the cleavable protein cross-linking reagent [35S]dithiobis(succinimidyl propionate). J Mol Biol 104(1): 243-261.
Zlatic, S. A., Ryder, P. V., Salazar, G. and Faundez, V. (2010). Isolation of labile multi-protein complexes by in vivo controlled cellular cross-linking and immuno-magnetic affinity chromatography. J Vis Exp (37): 1855.
Wang, H., He, M., Willard, B. and Wu, Q. (2019). Cross-linking, immunoprecipitation and proteomic analysis to identify interacting proteins in cultured cells. Bio-protocol 9(11): 3258.
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Akaki et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
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this is great, but i found after crosslinking, the binding between flag tag and beads are much weaker. is this normal, how to avoid this
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TRACES: a Freely Accessible, Semi-automated Pipeline for Detection, Tracking, and Quantification of Fluorescently Labeled Cellular Structures
XJ Xueer Jiang
LJ Linhao Jiang
LJ Li-En Jao
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4479 Views: 1013
Reviewed by: Giusy TornilloVinay Panwar Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Journal of Cell Science Jul 2021
Abstract
Subcellular structures exhibit diverse behaviors in different cellular processes, including changes in morphology, abundance, and relative spatial distribution. Faithfully tracking and quantifying these changes are essential to understand their functions. However, most freely accessible methods lack integrated features for tracking multiple objects in different spectral channels simultaneously. To overcome these limitations, we have developed TRACES (Tracking of Active Cellular Structures), a customizable and open-source pipeline capable of detecting, tracking, and quantifying fluorescently labeled cellular structures in up to three spectral channels simultaneously at single-cell level. Here, we detail step-by-step instructions for performing the TRACES pipeline, including image acquisition and segmentation, object identification and tracking, and data quantification and visualization. We believe that TRACES will be a valuable tool for cell biologists, enabling them to track and measure the spatiotemporal dynamics of subcellular structures in a robust and semi-automated manner.
Keywords: Particle tracking Quantitative image analysis Subcellular structures Live-cell imaging Python Phase separation Condensate Centrosome
Background
Deciphering how subcellular structures change in space and time is often key to understanding biological functions (Kholodenko et al., 2010). Thus, developing approaches to visualize, track, and measure these spatiotemporal changes has been a critical area of research in cell biology. In the past decades, advances in fluorescent protein engineering (Lippincott-Schwartz and Patterson, 2003; Giepmans et al., 2006) and optical microscopy (Tanaami et al., 2002; Stephens and Allan, 2003; Hell, 2007; Chen et al., 2014; Oreopoulos et al., 2014) have allowed scientists to observe subcellular structures with unprecedented spatiotemporal resolution. Post-imaging processing and analysis are then applied to quantify and interpret the data. For example, a popular Fiji plugin, TrackMate, can be used to visualize and analyze the motion of objects (Tinevez et al., 2017; Ershov et al., 2021), including the tracking of hundreds of centrosomes in the same spectral channel simultaneously (Aydogan et al., 2018, 2020, 2022; Alvarez-Rodrigo et al., 2019). CellProfiler (Lamprecht et al., 2007; Stirling et al., 2021), another open-source software tool, can be used to quantify data from biological images, particularly in a modular and high-throughput manner. However, TrackMate cannot track on multiple spectral channels simultaneously and is not optimal for tracking objects that are not perfectly circular. CellProfiler, while versatile and packed with extensive features, is not usually used for analyzing subcellular structures. Imaris (Bitplane, Belfast, UK) is a popular software capable of tracking objects in three dimensions with a user-friendly interface, but this and other commercially available image processing software (e.g., NIS Elements by Nikon, Tokyo, Japan) are not free to users, especially for the advanced features such as particle tracking. To overcome these limitations, we have developed TRACES (Tracking of Active Cellular Structures), a customizable and semi-automated quantification pipeline capable of simultaneously detecting, tracking, and quantifying up to three fluorescently labeled object types at single-cell resolution. TRACES is built on open-source platforms and freely accessible to users. The use of intensity- and size-based thresholding to segment objects in TRACES also makes it possible to identify and track objects that are not circular (an advantage over TrackMate). In addition, as the tracking and quantification algorithm of TRACES is written in Python and implemented using Jupyter Notebook, it can be easily modified or improved to fit users’ needs. While several available tools are optimized for tracking entire cells, TRACES is developed specifically for tracking subcellular structures at single-cell resolution, including tracking micron-sized objects, such as the centrosome. In this protocol, we use the analysis of condensation of pericentrin (PCNT) proteins and the movement of the resulting “condensates” toward the centrosome (Jiang et al., 2021) as an example, hereby demonstrating the TRACES workflow. This workflow involves image acquisition and segmentation, object identification and tracking, and data quantification and visualization.
One limitation of TRACES is its inability to track dividing cells, as the current tracking algorithm assumes one nucleus object per cell. We hope to implement object tracking features for dividing cells in the future. Moreover, while the Python algorithm is capable of tracking on multiple spectral channels simultaneously, the objects of interest in each channel need to be identified manually in the initial image segmentation step in Fiji. We hope to integrate an automated workflow of image segmentation into our future pipeline.
In sum, our TRACES method is a free and semi-automated pipeline for detecting, tracking, and measuring multiple fluorescently labeled cellular structures in up to three spectral channels simultaneously at single-cell level. If these cellular objects can be segmented and distinguished from one another, their relationships and properties (e.g., distance, size) can then be quantified using the TRACES method. Therefore, we envision that TRACES is not limited to analyzing centrosomes, their related structures, and nuclei, the three objects exemplified in this protocol. TRACES can be applied to analyzing any distinct fluorescent objects in up to three spectral channels in the cell, and will thus be a useful tool for the cell biology community, facilitating quantitative image analysis in other biological contexts.
Materials and Reagents
4-chamber 35-mm glass bottom dishes with 20-mm microwell, #1.5 cover glass (Cellvis, catalog number: D35C4-20-1.5-N)
hTERT immortalized retinal pigment epithelial (RPE-1) cells (A gift from Irina Kaverina, Vanderbilt University, Nashville, TN, catalog number: CRL-4000, RRID: CVCL_4388)
RPE-1 cells constitutively expressing mScarlet-i-H2A and miRFP670-CETN2 with stably integrated GFP-PCNT (854-1960) constructs under the control of a Doxycycline-inducible promoter (Jiang et al., 2021)
Doxycycline hyclate (MilliporeSigma, catalog number: D9891)
Dulbecco’s modified Eagle’s medium/Hams F-12 50/50 Mix (DMEM/F-12) (Corning, catalog number: 10-092-CV)
Penicillin-Streptomycin solution, 100× (Corning, catalog number: 30-002-CI)
Tetracycline negative fetal bovine serum (tet-negative FBS) (Gemini Bio, catalog number: 100-800)
Equipment
Spinning disk confocal microscope system (Dragonfly, Andor Technology, Belfast, UK)
The spinning disk confocal module is the Dragonfly 503 multimodal imaging system (Andor) with dual color TIRF, two camera ports, and 25 µm and 40 µm pinholes. It has four lines of laser launches (405 nm/100 mW, 488 nm/50 mW, 561 nm/50 mW, and 643 nm/100 mW). The base of the system is a Leica DMi8 inverted microscope (Leica, Wetzlar, Germany) with objectives spanning the range from 10× to 100× [10×/0.40 (magnification/numerical aperture) air HCX PL APO, 25×/0.95 water HC PL FLUOTAR, 40×/1.10 water HC PL APO, 63×/1.40 oil HC PL APO, 100×/1.40 oil HC PL APO, and 100×/1.47 oil HC PL APO CORR TIRF]. The images shown in this protocol were all acquired by the 63×/1.40 oil HC PL APO objective. The laser lines used in this study are 488 nm, 561 nm, and 643 nm, with the corresponding bandpass emission filters of 525–550 nm, 600–650 nm, and 725–740 nm, respectively.
iXon Ultra 888 EMCCD camera (Andor Technology)
Environmental incubator (Okolab, Pozzuoli, Italy)
Software
Anaconda (Anaconda, Inc., New York, NY)
Fiji (ImageJ) (Johannes Schindelin, Albert Cardona, Pavel Tomancak, RRID: SCR_002285)
Jupyter Notebook (Project Jupyter, RRID:SCR_018315)
Python Programming Language (Python Software Foundation, RRID: SCR_008394)
Procedure
Cell culturing and induction of protein expression
Seed approximately 6 × 104–9 × 104 cells to each chamber of a 35-mm glass bottom dish. Allow cells to attach onto the dish. Maintain cells with appropriate media in a humidified incubator supplied with 5% CO2 at 37 °C.
Note: Tet-ON-GFP-PCNT (854–1960) cells, an RPE-1 derived cell line that expresses GFP-tagged PCNT (residues 854–1960) through doxycycline induction, are used in our study (Jiang et al., 2021). Tet-ON-GFP-PCNT (854–1960) cells also stably and constitutively express mScarlet-i-H2A and miRFP670-CETN2, which label the nucleus and centrosome, respectively. Cells are maintained in DMEM/F12 media supplemented with 10% tet-negative FBS and 1× penicillin-streptomycin solution.
Allow cells to reach 40–60% confluency (12–18 h post seeding for most cultured human cells) before imaging.
Note: For best object tracking results, seed cells at a low density and distribute them evenly on the coverslip to minimize overlapping of cells.
Optional: for doxycycline-inducible cell lines, incubate cells with 1 µg/mL doxycycline hyclate (Dox) to induce transgene expression before the start of time-lapse microscopy (e.g., 3–4 h in our case).
Time-lapse image acquisition
Note: When performing live cell imaging with multiple fluorophores, it is important to select appropriate wavelength ranges, emission filters, and dichroic mirrors to minimize spectral bleed-through artifacts. Appropriate laser power, exposure time, and acquisition intervals should also be empirically determined to maximize the signal-to-noise ratio while minimizing photobleaching, especially over a long period of time-lapse imaging. We also recommend centering the cell(s) of interest in the field of view to prevent them from moving out of the field during imaging. Below are the time-lapse image acquisition settings we use in our system (Andor Dragonfly spinning disk confocal system). Using our current algorithm, TRACES can track up to three fluorescently labeled object types simultaneously, if one of the objects can be used to define the location of the cell over time (e.g., a fluorescently labeled nucleus such as mScarlet-i-H2A in Figure 1; other markers that label the cell membrane or other organelles can also be used). We use a series of images captured during the formation and movement of PCNT condensates as an example to demonstrate the TRACES workflow in this protocol (Figure 1).
Figure 1. Examples of live-cell image acquisition. Time-lapse micrographs of Tet-ON-GFP-PCNT (854–1960) cells. Imaging started around 4 h post Dox induction. The time when the first condensates formed is marked as time 0. Note that GFP-PCNT (854–1960) forms phase-separated condensates that coalesce and move toward the centrosome (denoted by the magenta arrowheads and enlarged in insets). Scale bars: 20 µm and 2 µm (insets).
Environmental control: Mount cells in a humidified chamber supplied with 5% CO2 inside a wrap-around environmental incubator with temperature set at 37 °C (for most cultured mammalian cells).
Note: Allow the microscope system to reach the desired temperature equilibrium before imaging.
Camera: iXon Ultra 888 EMCCD
Note: To minimize phototoxicity over long-term live imaging, we recommend empirically determining the lowest laser power and exposure time that can generate images with at least 2–3 signal-to-noise ratios for objects of interest. Using a highly sensitive camera, such as the one equipped with electron multiplying charge coupled device (EMCCD), is also desirable.
Objective: 63×/1.40 (magnification/numerical aperture) coupled with a 1× motorized magnification changer
Laser power: 1–10% of 50–100 mW lasers
Exposure time: 100–200 ms
Gain: 200
Pinhole size: 40 µm
Z-stack interval: 0.6 µm
For assessing colocalization or analyzing relative spatial distribution between fluorescently labeled structures, acquire all channels for each z-stack from the longest to the shortest wavelength.
Note: We also recommend setting a wide enough z-range, to account for the possibility that cells may drift out of focus during long-term imaging.
Acquisition time interval: 2–4 min
Note: Users need to optimize imaging parameters according to their specific imaging system, experimental design, and structure(s) of interest.
Data analysis
Object segmentation and identification using Fiji
Note: See Notes section A for instructions of Fiji installation.
Image import and Z-projection
Load a time-lapse image in Fiji by selecting “File” > “Open…”.
Note: Our image files are 16-bit in OME TIFF format and can be read using the Bio-Formats package (Linkert et al., 2010) that is integrated in Fiji by default. For other image formats, it might be necessary to convert the file into TIFF format or to directly activate the Bio-Formats Importer plugin to read data.
For “Bio-Formats Import options”, select “Hyperstack” for stack viewing, and “Use virtual stack” (Figure 2A).
Note: Hyperstack view displays images as multi-dimensional stacks (time, channel, Z-slice slider).
To open images with channels displayed separately, select “Default” as color mode, and “Split channel” (Figure 2A).
To perform Z-projection, select “Image” > “Stacks” > “Z Project …”. Determine the stack range by indicating the start and stop slices that will be included in the projection. Choose the appropriate projection type and select “All time frames” (Figure 2B).
Note: Maximum intensity Z-projection is used in our image analysis to select pixels from the maximum intensity of each slice to construct a 2D time-lapse image series. Users may choose other projection types that better represent the raw data.
Save the projected images as TIFF format by going to “File” > “Save As” > “Tiff…” (Figure 2C). Make sure all projected images have the same image type (e.g., 16-bit, 32-bit).
Repeat Steps A1d and 1e to process other spectral channels, if there are any.
Figure 2. Image import and Z-projection. (A) Read image files using Bio-Formats. (B) Set up Z-projection parameters. (C) Save projected images as TIFF format.
Image segmentation by intensity-based thresholding
Open the projected image of a given channel in Fiji (Figure 3A). Adjust the lower and upper limits of the display range through “Image” > “Adjust” > “Brightness/Contrast…” so that objects of interest, not background signals, are clearly displayed (Figure 3B).
Note: Figures 3A and 3B show examples of before and after display adjustment of the signals for GFP-PCNT (854–1960) condensates in the +24 min time frame shown in Figure 1. The same example is also shown in Figure 5. This adjustment step only changes displayed values, not raw pixel intensity values (Ferreira and Rasband, 2012).
To apply thresholding for image segmentation, first convert image type to 8-bit through “Image” > “Type” > “8-bit”. Then, select “Image” > “Adjust” > “Threshold…”. Adjust the minimum and maximum threshold values, so that only objects of interest, not background signals, are segmented. Choose “Red” overlay, and then select “Apply” (Figure 3C). For example, threshold values of 80/255 (minimum/maximum) are used here for segmenting GFP-PCNT (854–1960) condensates.
The “Convert Stack to Binary” window will appear after selecting “Apply” from the previous step (Figure 3C). In this window, select “Default” method and “List thresholds”. Then, select “OK” (Figure 3D).
Note: Execution of Steps A2b and A2c generates a binary stack image that displays the pixels of segmented objects (or foreground) and background (e.g., Figure 5, third column). While we use the default thresholding method based on IsoData algorithm, users may choose other methods Fiji provides (e.g., Intermodes, MaxEntropy) that best segment their objects of interest. Make sure to unselect “Calculate threshold for each image”, if users want to apply the same defined threshold values across all time frames of a given time-lapse image series.
Save the resulting binary stack image with segmented objects as a TIFF file (i.e., using the same step shown in Figure 2C).
Repeat the above steps to segment other objects, if multiple objects have been acquired in different spectral channels.
Figure 3. Examples of image segmentation by intensity-based thresholding. Using the GFP channel of the +24 min time frame in Figure 1 as an example, a step-by-step procedure to segment GFP-PCNT (854–1960) condensates is shown here, including opening the confocal z-projected image (A), adjusting display ranges (B), and applying intensity-based thresholding steps (C, D). Scale bar: 20 µm and 2 µm (insets).
Object identification and measurement
Note: This step assigns each identified object in each channel with a unique ID number and extracts measurement data, which will be used for object tracking.
Open each segmented stack image in Fiji.
Define the image scale through “Analyze” > “Set Scale…”. Then select “OK” (Figure 4A).
Figure 4. Object identification and measurement. (A) Define image scales. (B) Define image coordinates. (C) Specify object measurement and statistical parameters. (D) Execute the “Analyze Particles” function.
Define image coordinates through “Image” > “Adjust” > “Coordinates…”. Then select “OK” (Figure 4B).
Note: It is important to set the correct image scale and coordinates prior to object measurement.
Go to “Analyze” > “Set measurement” to specify measurements and statistics to be extracted (Figure 4C).
Note: We choose to extract area and center-of-mass for our analysis. Users may select other measurements that best fit their quantification purposes. To use the Python tracking program in this pipeline, make sure to include the center-of-mass measurement, as TRACES uses (x,y) object coordinates for tracking.
Activate the “Analyze Particles” function through “Analyze” > “Analyze Particles…”. Set appropriate size thresholds to mask objects of interest and extract measurements. Check “Display results”, “Summarize”, and “Add to manager”, and then select “OK” (Figure 4D).
Note: The size thresholding in this step helps further filter out background signals that are misclassified as segmented objects from the previous intensity-based thresholding step (Figure 3). Circularity thresholding—ranging from 0.00 (elongated polygon) to 1.00 (perfect circle) (Ferreira and Rasband, 2012)—may also be applied to segment objects of interest. We set our circularity threshold as 0.00–1.00 (Figure 4D), meaning that we do not set circularity thresholds and accept all objects regardless of their circularity. “Display results” and “Summarize” options are selected so that the measurement data will be displayed and can be saved for object tracking. The “Add to manager” option is selected so that a unique ID number is automatically assigned to each identified and measured object across all time frames (e.g., Figure 5, fourth column). Because ID numbers are unique, the same object will be represented by different ID numbers across time frames.
Select “yes” to process all time frames of a time-lapse image series.
Save the resulting segmented images with objects labeled by unique ID numbers (e.g., Figure 5, fourth column).
Figure 5. Examples of display adjustment, image segmentation, and object identification for three fluorescently labeled object types. Using the +24 min time frame shown in Figure 1 as an example, z-projected confocal images with the original display settings (first column), adjusted display settings (second column), image segmentation by thresholding (third column), and object identification by executing the “Analyze Particles” function (fourth column) are shown. Note that for each object type, a unique ID number (e.g., insets, fourth column) is automatically assigned to each identified object across all time frames of the time-lapse image series. Scale bars: 20 µm and 2 µm (insets).
Save the object measurement result (Figure 6A) and frame count (Figure 6B) data as .csv format for each object type.
Note: Fiji refers to each “time frame” of a time-lapse image series as “slice” (Figure 6B). To avoid confusion between “time frames” in a time series and “slices” within a z-stack, “slice” and “slice count” (initially defined by Fiji shown in Figure 6B) are subsequently re-defined as “frame” and “frame number”, respectively, in the pipeline.
Repeat the above steps for other objects if multiple objects have been acquired in different spectral channels. Figure 5 demonstrates a complete process of display adjustment, image segmentation, and object identification of three fluorescently labeled object types from a single time frame of a time-lapse image series (i.e., +24 min time frame shown in Figure 1).
Figure 6. Examples of Fiji-exported datasets and their integration using the Python-based df_converter function. (A) Examples of the measurement results of PCNT condensate objects exported from Fiji (from the same time-lapse series shown in Figure 1). XM and YM, x and y coordinates of the object, are based on the center of mass. (B) Examples of the slice/frame count data of PCNT condensate objects exported from Fiji. “Slice” represents each time frame in a time-lapse image series. “Count” represents the number of identified condensate objects in the corresponding “slice”/time frame. (C) Examples of dataframe output of PCNT condensate objects after the execution of df_converter function. Here, “frame” indicates the frame number where each object (with a unique object ID) is located.
Object tracking using a Python-based program
Note: The TRACES object tracking program is written in Python and implemented in Jupyter Notebook. See Notes section B for installation instructions of Anaconda distribution, which conveniently includes the installation of Python, Jupyter Notebook, and packages to run TRACES. TRACES object tracking workflow includes 6 steps (Section I to VI), as detailed below (Figure 7A).
Figure 7. Object tracking, quantification, and data visualization in the TRACES pipeline. (A) Workflow for object tracking. (B) Quantification and data visualization. The highlight of TRACES script lines in each section is shown. See TRACES.ipynb for the complete script. Example plots of condensate object numbers, average condensate distances to the centrosome, and average condensate areas in a single cell are shown. See Figure 4 in Jiang et al., 2021, for examples of the final plots.
Import packages and define working directory (Figure 7A, section I)
Open “TRACES.ipynb” in Jupyter Notebook.
Note: See Notes section C for instructions on launching the Jupyter Notebook application.
Import packages and define working directory.
Load files (Figure 7A, section II)
Load data files with measurement results (e.g., Figure 6A) and frame counts (e.g., Figure 6B) for each object type.
Note: For example, the filename of measurement results for the centrosome object is “centrosome_results.csv”. We thus load the file as “pd.read_csv(‘centrosome_results.csv’)” (Figure 7A, II, line 1). The data files for the measurement results and frame counts are loaded for three object types—centrosome, condensate, and nucleus—whose dataframe variables are named as “cen”, “con”, and “h2a” in the script, respectively. (Figure 7A, II). As variable names are arbitrary, users may choose their own variable names freely.
Combine datasets using the df_converter function
Note: df_converter function combines the object measurement results (e.g., Figure 6A) and frame counts (e.g., Figure 6B) from Fiji into a dataframe with specified variable orders for each object type (e.g., Figure 6C); this information will be used for object tracking.
Note: Two general steps are involved in applying a function: (a) define function and (b) specify parameters and execute function, followed by (c) data output (i.e., a dataframe is generated), as exemplified below.
In section III of the TRACES script, run scripts in the first cell to define “df_converter(df1, df2)” function.
In the second cell, specify parameters and execute function for each object type. “df1” and “df2” are the dataframe variables for the measurement results and frame counts, respectively, specified in section II of the script.
Note: For example, “cen_r” and “cen_sc” are the dataframe variables for the measurement results and frame counts of centrosome objects defined in section II, respectively. We thus specify function parameters as “df_converter(cen_r, cen_sc)” for centrosome object type (Figure 7A, III, line 2).
After execution of the function in the previous step (Step B3b), a dataframe for each object type will be generated with the following variables (from left to right): “Object_ID” (object ID number), “XM” (object x coordinate), “YM” (object y coordinate), “frame” (frame number where each object is located), and other customized measurements (e.g., “Area”) (Figure 6C).
Note: Make sure to create a unique variable name for each dataframe. For example, object dataframe variables are named “centrosome_df”, “condensate_df”, and “h2a_df” for centrosome, condensate, and nucleus object types, respectively. As variable names are arbitrary, users may choose their own variable names freely.
Group objects within cells using the object_grouping function
Note: The position of the nucleus serves as the proxy for the location of the cell. To track subcellular objects over time at single-cell resolution, we first group each object to its own cell by assigning each object to its nearest nucleus using the object_grouping function. This function first measures the distance of each object to all nuclei per time frame and then assigns each object to its nearest nucleus across time frames based on the minimal Euclidean distance.
Note: If users’ cell line of interest does not include a nucleus marker, Hoechst or other fluorescent dyes can be used to label the nucleus. Alternatively, other cytoplasmic markers that generally reflect the cell position may also be used as the reference point for grouping.
In section IV of the TRACES script, run scripts in the first cell to define the “object_grouping(channel_df, h2a_df)” function.
In the second cell, specify parameters and execute function for each object type. “channel_df” and “h2a_df” are the dataframe variables of the grouping and nucleus objects, respectively, specified in section III of the script.
Note: For example, “condensate_df” and “h2a_df” are the dataframe variables for the condensate and nucleus objects defined in section III. To group condensate objects within cells, specify function parameters as “object_grouping(condensate_df, h2a_df)” (Figure 7A, IV, line 2). After execution, both condensate and centrosome object types are then grouped within cells; the resulting dataframe variables after grouping are named “con_h2a_group” and “cen_h2a_group”, respectively.
Integrate spatiotemporal information of different objects using the dist_between_channels function
Note: The dist_between_channels function integrates measurements (e.g., distance, area) between specified object types (e.g., condensate and centrosome) within each cell across time frames. The previous object grouping step only yields a pairwise relationship of the specified two objects (e.g., condensate to nucleus, or centrosome to nucleus). This step is to integrate these two separate pairwise datasets into a single dataset. Therefore, a three-object relationship can be obtained (e.g., the relationship among condensate, nucleus, and centrosome objects).
In section V of the TRACES script, run scripts in the first cell to define the “dist_between_channels(channel1_h2a_df, channel2_h2a_df)” function.
In the second cell, specify parameters and execute function. “channel1_h2a_df” and “channel2_h2a_df” are the dataframe variables of the object grouping specified in section IV of the script.
Note: For example, “con_h2a_group” and “cen_h2a_group” are the dataframe variables for object grouping of condensates and centrosomes specified in section IV, respectively. To integrate different measured values between condensate and centrosome objects within each cell, we specify function parameters as “dist_between_channels(con_h2a_group, cen_h2a_group)” (Figure 7A, V, line 2). After execution, an integrated object dataframe variable, “con_cen_df”, is generated (Figure 7A, V, line 2), in which the relationship among condensates, centrosomes, and nuclei is defined. We will use this dataframe for object tracking in the next step.
Track objects in a target cell using the object_tracker function
Note: The object_tracker function simultaneously tracks all three object types (e.g., centrosome, condensate, and nucleus) of a cell specified by the user. To use this function, users need to specify a target cell for tracking. We use the nucleus object ID to define a target cell. Users may find the nucleus object ID information by viewing the binary segmented image with objects labeled by unique ID numbers generated from the object identification and measurement step in Fiji (e.g., Figure 5, fourth column).
Note: The current TRACES tracking algorithm only tracks objects in non-dividing cells, as the program assumes one nucleus object per cell. We hope to implement object tracking features for dividing cells in the future.
In section VI of the TRACES script, run scripts in the first cell to define the “object_tracker(start_index, end_frame, dataframe)” function.
In the second cell, specify parameters and execute function. The “start_index” parameter is the nucleus object ID of a target cell at the starting frame. The “end_frame” is the ending frame number for tracking. The “dataframe” is the dataframe variable of the integrated object specified in section V of the script.
Note: For example, we want to track objects in a target cell from frame number 5 to 54. The nucleus object ID of the target cell is “21” at frame number 5, and “con_cen_df” is the integrated object dataframe variable specified in section V. Thus, we specify function parameters as “object_tracker(21, 54, con_cen_df)” (Figure 7A, VI, line 2).
After execution, a dataframe named “track_result” is generated, and automatically exported to the working directory as a .csv file named “track_result.csv” (Figure 7A, VI, line 5). This csv file contains the following columns (from left to right): “frame_num” (frame number), “orig_c1_index” (condensate object ID), “orig_c2_index” (centrosome object ID), “orig_h2a_index” (nucleus object ID), “H2A_X”, “H2A_Y” (x and y coordinates of nucleus objects), “c1_XM”, “c1_YM” (x and y coordinates of condensate objects), “c2_XM”, “c2_YM” (x and y coordinates of centrosome objects), and “distance_c1_to_c2” (distance between condensate to centrosome objects). We will use this dataframe for quantification in the next steps.
Note: If users want to track multiple cells in a time-lapse image series, specify a new target cell and repeat the above steps.
Quantification and data visualization using a Python-based program
Quantify object numbers using the count_by_frame function
Note: The count_by_frame function calculates the number of objects per time frame in the target cell and generates a plot for data visualization (Figure 7B, VII). Users need to specify an object type of interest for quantification.
In section VII of the TRACES script, run scripts in the first cell to define the “count_by_frame(track_table, track_table_object_colname) function.
In the second cell, specify parameters and execute function. The “track_table” parameter is the dataframe variable of tracking results specified in section VI. The “track_table_object_colname” is the object ID column of interest in the tracking result dataframe.
Note: For example, the dataframe variable for tracking results is “track_result”. The object ID column name of condensate objects is “orig_c1_index”. To quantify the condensate object number, we specify function parameters as “count_by_frame(track_result, ‘orig_c1_index’)” (Figure 7B, VII, line 2).
After execution, the quantification data and plot (Figure 7B, VII) are automatically exported to the working directory as .csv and .png files, respectively.
Note: The graph shows condensate object numbers as a function of frame number in a target cell (Figure 7B, VII). Users can also convert the x-axis from frame number to time by specifying the time interval between frames. See Figure 4B in Jiang et al., 2021 for examples of the final plots.
Quantify object distances using the distance_plot function
Note: The distance_plot function calculates the average distance between two object types (e.g., the condensate-to-centrosome distance) per time frame in the target cell and generates a plot for data visualization (Figure 7B, VIII).
In section VIII of the TRACES script, run scripts in the first cell to define the “distance_plot(track_table)” function.
In the second cell, specify parameters and execute function. The “track_table” parameter is defined as above in Step C1b.
Note: For example, the dataframe variable for tracking results is “track_result”. To quantify the average condensate-to-centrosome distance per time frame, we specify function parameters as “distance_plot(track_result)” (Figure 7B, VIII, line 2).
After execution, the quantification data and plot (Figure 7B, VIII) are automatically exported to the working directory as .csv and .png files, respectively.
Note: The graph shows the average condensate-to-centrosome distance as a function of frame number in a target cell (Figure 7B, VIII). Users can also convert the x-axis to time, and combine the quantification result from multiple cells. See Figure 4C in Jiang et al., 2021 for examples of the final plots.
Measure the user-specified object properties using the measurement_plot function
Note: Users may choose to measure other properties of objects (e.g., area) during the object identification and measurement step in Fiji. Users can apply the measurement_plot function to measure user-specified properties. Figure 7B, IX shows an example of measuring the area of condensate objects.
In section IX of the TRACES script, run scripts in the first cell to define the “measurement_plot(track_table, track_table_object_colname, object_df, m_type)” function.
In the second cell, specify parameters and execute function. The “track_table” and “track_table_object_colname” parameters are defined as above in Step C1b. The “object_df” is the dataframe variable for the object of interest specified in section III of the script. The “m_type” is the column name of measurement type of interest in the “object_df” dataframe (Figure 6C).
Note: For example, the dataframe variable for tracking results is “track_result”. The object ID column name of the condensate object is “orig_c1_index”. The condensate object dataframe is “condensate_df”, as specified in section III of the script. “Area” is the column name of the area measurement in “condensate_df” dataframe (Figure 6C). To quantify the average condensate area per time frame, we specify function parameters as “measurement_plot(track_result, ‘orig_c1_index’, condensate_df, ‘Area’)” (Figure 7B, IX, line 2).
After execution, the quantification data and plot (Figure 7B, IX) are automatically exported to the working directory as .csv and .png files, respectively.
Note: The graph shows the average condensate area as a function of frame number in a target cell (Figure 7B, IX). Users can also convert the x-axis to time and combine the quantification result from multiple cells. See Figure 4A in Jiang et al., 2021 for examples of the final plots.
Notes
Installation of Fiji
Follow instructions in https://imagej.net/software/fiji/downloads to install Fiji.
Installation of Anaconda
Anaconda is a distribution platform of Python/R programming languages and data-science packages. Downloaded Anaconda also includes Jupyter Notebook, a convenient web-based application for generating and editing Python/R language scripts.
Follow instructions in https://docs.anaconda.com/anaconda/install/ to install Anaconda.
Launching Jupyter Notebook
Note: For detailed instructions, follow this link to open the Jupyter Notebook application.
Download and save “TRACES.ipynb” in a local folder.
To launch Jupyter Notebook, first open the computer terminal.
For Mac users, type “jupyter notebook” in the terminal, and then press the “Enter” button.
The Jupyter Notebook dashboard will appear in a new browser window.
Select “TRACES.ipynb” to open in Jupyter Notebook.
Line numbers on Jupyter Notebook
If line numbers do not show up on Jupyter Notebook, go to “View” > “Toggle Line Numbers”.
Manual correction of misgrouped objects in the target cell using the manual_correct function
Note: As post-analysis quality control, users should confirm the accuracy of the tracking process, by manually evaluating the behaviors of objects in the original time-lapse images with those of the segmented objects and the exported quantification results. Occasionally, certain background signals might be missegmented as objects during image processing steps, which are then incorrectly grouped into the target cell. To solve this issue, we have developed the manual_correct function for users to remove misgrouped objects from the target cell. This step is optional and should only be applied to remove misgrouped objects prior to the workflow of quantification and data visualization.
In the “Optional step” section of the TRACES script, run scripts in the first cell to define the “manual_correct(track_table, track_table_object_colname, index_list)” function.
In the second cell, specify parameters and execute function (Figure 8). The “track_table” parameter is the dataframe variable of tracking results specified in section VI. The “track_table_object_colname” is the object ID column of interest in the tracking result dataframe. The “index_list” is a list of ID numbers of misgrouped objects to be removed from the target cell.
Note: For example, if we want to remove two misgrouped condensate objects with ID number 366 and 375, first specify the “index_list” as “rm_index_ls = [366,375]” (figure 8, line 2). The dataframe variable for tracking results is “track_result”. The column name of condensate object ID in the dataframe is “orig_c1_index”. Thus, we specify function parameters as “manual_correct(track_result, ‘orig_c1_index’, rm_index_ls)” (Figure 8, line 3). The dataframe of the corrected tracking results is automatically exported to the working directory as a .csv file (Figure 8, line 6).
Figure 8. Remove misgrouped objects using the manual_correct function. A highlight of the TRACES script lines. See TRACES.ipynb for the complete script.
Acknowledgments
We thank Dr. Sean R. Collins and Dr. Mark Winey for suggestions on optimizing the TRACES pipeline, and all members of the Jao Lab for discussion. This protocol was adapted from a previous work (Jiang et al., 2021). This work was supported by the National Institutes of Health (1R01GM144435-01 to L.-E.J.) and UC Davis Predoctoral Fellowships (Emmy Werner and Stanley Jacobsen Fellowship and Floyd and Mary Schwall Dissertation Year Fellowship to X.J.).
Competing interests
The authors declare no competing or financial interests.
References
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Cryptococcus neoformans Virulence Assay Using a Galleria mellonella Larvae Model System
PS Piotr R. Stempinski *
DS Daniel F. Q. Smith
AC Arturo Casadevall
(*contributed equally to this work)
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4480 Views: 1728
Reviewed by: Kristin L. ShinglerLoredana ScalschiKrishna Saharan
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Original Research Article:
The authors used this protocol in PLOS Biology May 2021
Abstract
Cryptococcus neoformans is a human pathogenic fungus that can cause pulmonary infections and meningitis in both immunocompromised and otherwise healthy individuals. Limited treatment options and a high mortality rate underlie the necessity for extensive research of the virulence of C. neoformans. Here we describe a detailed protocol for using the Galleria mellonella (Greater Wax Moth) larvae as a model organism for the virulence analysis of the cryptococcal infections. This protocol describes in detail the evaluation of G. mellonella larvae viability and the alternatives for troubleshooting the infection procedure. This protocol can be easily modified to study different inocula or fungal species, or the effects of a drug or antifungal agent on fungal disease within the larvae. We describe modified alternative versions of the protocol that allow using G. mellonella to study fungal diseases with different inocula and at different temperatures.
Keywords: Cryptococcus neoformans Galleria mellonella Larvae Virulence assay Fungal virulence Microbial infection test
Background
Cryptococcus neoformans is a basidiomycetous polysaccharide-encapsulated fungus, pathogenic for multiple species (Kwon-Chung et al., 2014). In humans, C. neoformans can cause serious infections, primarily in immunocompromised patients with clinical manifestations of pneumonia and meningitis (Lui et al., 2006; Kwon-Chung et al., 2014). Due to high mortality, lack of available vaccines, limited treatment options, and increasing resistance to the fluconazole—a drug commonly used for treatment of cryptococcosis—it is estimated that the total number of cryptococcosis-related deaths exceeds 180,000 annually worldwide (Cogliati, 2013; Perfect and Bicanic, 2015). Cryptococcus spp. have several characteristic virulence factors that are essential for establishing infection and providing defense mechanisms against the host immune system. Important cryptococcal virulence factors include the polysaccharide capsule, melanin, and formation of titan cells (Zaragoza, 2019). Researchers have developed several methods to stimulate the production of those virulence factors in culture conditions; while this allows for precise functional analysis, it is not sufficient for a more holistic understanding of virulence (Casadevall et al., 2000; Liu et al., 2008; Crabtree et al., 2012; Almeida et al., 2015).
The study of virulence usually requires the use of an animal model organism. Animal testing plays an essential role in the medical and biomedical field of research. Unfortunately, research performed on mice, rats, and other mammals comes with serious limitations, including medium to high costs, requirement for specialized animal testing facilities, and concerns about the use of vertebrate animals in research. Additionally, mouse and mammalian studies can take several months depending on the virulence of the microbe and disease progression. To avoid those problems, many researchers performed studies, including virulence assays, on invertebrate models like the fruit fly Drosophila melanogaster or the larvae of the Greater wax moth Galleria mellonella. G. mellonella has been shown to be a useful model organism to test pathogenicity of multiple fungal species, including C. neoformans, which was first used in a G. mellonella model by the Mylonakis group in 2005 (Reeves et al., 2004; Mylonakis et al., 2005; Pereira et al., 2018; Maurer et al., 2019). The advantage of G. mellonella as a model host is its flexibility for changes in the infection protocol that allow the study of variables not possible in vertebrate and invertebrate models, such as host temperature. In contrast to other invertebrate model systems, infected larvae of G. mellonella can be incubated at room temperature, 30 °C, and 37 °C (Mylonakis et al., 2005). This temperature range is important because it allows experiments at mammalian temperatures. G. mellonella larvae are between 2–3 cm in length, an easy size to handle and manipulate. In addition, since G. mellonella are relatively easy to infect and store in high numbers, this model enables researchers to perform virulence or survival screens of many different conditions, strains, or mutants, before narrowing those down to use in a resource and time-intensive mouse model (Mylonakis et al., 2005; Firacative et al., 2020).
G. mellonella are used as models for C. neoformans infections, as several of the virulence factors important for C. neoformans infections in mammalian hosts also play comparable roles in G. mellonella. These include laccase, capsule, and the production of titan cells, which allow the fungus to evade immune clearance (Mylonakis et al., 2005; García-Rodas et al., 2011; Eisenman et al., 2014). Additionally, C. neoformans undergoes similar interactions with the immune systems of G. mellonella and mammals (Browne et al., 2013; Trevijano-Contador and Zaragoza, 2018; Stączek et al., 2020; Smith and Casadevall, 2021). C. neoformans is phagocytosed by both insect hemocytes (immune cells) and mammalian macrophages (Browne et al., 2013; Pereira et al., 2018). The fungus is also encapsulated within immune nodules of G. mellonella, which are aggregates of insect immune cells that neutralize the infection, comparable to the granulomas that form around C. neoformans within the mammalian lung. Here we present a standardized protocol for the virulence survival assay of C. neoformans performed in G. mellonella larvae.
Materials and Reagents
Snap-Cap 14 mL culture tubes (Falcon, catalog number: 352059)
Sterile inoculation loop (Fisherbrand, catalog number: 22-363-605)
Pipette tips 200 µL, 1,000 µL (USA Scientific TipOne, catalog numbers: 1111-0006, 1126-7810)
Insulin syringe with 0.400 (27G) needle (BD, catalog number: 329412)
10 cm Petri dish, one per each testing group (Falcon, catalog number:351029)
Nitrile Gloves (Halyard, catalog number: 55082)
1.5 mL Eppendorf tubes (SealRite, catalog number: 1615-5500)
Galleria mellonella larvae (https://www.waxworms.net/, Vanderhorst Wholesale, St. Marys, Ohio, USA)
Cryptococcus neoformans strain H99 (serotype A)
1× DPBS (Gibco, catalog number: 14190-144)
BD Bacto Peptone (Gibco, catalog number: 211677)
BD Bacto Yeast Extract (Gibco, catalog number: 212750)
Difco YPD Broth (Gibco, catalog number: 242820)
Small Polystyrene Weigh Boats (Heathrow Scientific, catalog number: HS1420A)
Glucose (Sigma, catalog number: 1002789701)
YPD liquid media (see Recipes)
Equipment
Hemocytometer (Hausser Scientific, catalog number: 3520)
Pipettes 2–20 µL, 20–200 µL, 100–1,000 µL
Microbiological incubator with a culture tube rotator
Microscope (Olympus, model: BX40)
Autoclave
Syringe stepper (Dymax STEPPER Repetitive Pipette, model: 4001-010)
Benchtop centrifuge (Spectrafuge 24D)
Software
GraphPad Prism software (https://www.graphpad.com/)
Procedure
Selection of larvae with desirable mass
Select and separate G. mellonella larvae and prepare Petri dishes, one for each tested group. Larvae are always handled while wearing nitrile gloves to reduce the risk of contamination.
Use a digital scale to select larvae with a body mass between 100 and 200 mg. Larvae are weighed individually in small polystyrene weigh boats before being transferred into Petri dishes, with up to 15 larvae in each Petri dish.
Note: Larvae should be relatively firm to the touch and not exhibit signs of illness, such as dark melanization throughout the body or reduced movement (Figure 1A). There is normal variability in the cuticle pigmentation in healthy larvae. Ideally, larvae will be sorted at least 16–24 h prior to infection to allow acclimatization at room temperature following arrival.
Figure 1. Evaluation of G. mellonella fitness. (A) Progression of cryptococcal infection in a larva resulting in discoloration and death. (B) Transition of infected larva into the pupa and progression of cryptococcal infection resulting in death. (C) Completed development of the pupa and metamorphosis into moth, which typically occurs at or beyond day 14 under the experimental lab conditions described.
Preparation of fungal cell inoculum
Approximately 48 h prior to the infection, inoculate 5 mL of YPD media with the desired strain of C. neoformans in a 14 mL Snap-Cap culture tube and incubate on the cell culture rotor at 30 °C, 35 rpm. Alternatively, C. neoformans can be grown in 1 mL of YPD media overnight (16–24 h) at 30 °C, 35 rpm.
Transfer 1 mL of stationary-phase culture to 1.5 mL Eppendorf tubes and pellet fungal strain by centrifuging tubes for 4 min at 2,500 × g in the tabletop centrifuge.
Wash your samples twice with DPBS by discarding supernatant and resuspending the pellet in 1 mL of sterile DPBS each time.
Prepare a 1:100 cell dilution and establish cell concentration using a hemocytometer.
According to this protocol, diluting cells to this concentration will result in 105 cells injected per larvae; if a different inoculum is desired, adjust the cell dilution appropriately. To prepare samples for injecting 105 cells per larvae, dilute your washed cells with DPBS to the concentration of 107 cells/mL.
Infection of larvae
Calibrate the stepper device and set to dispense 10 µL of liquid prior to the experiment, unless another volume is needed or desired.
Draw inoculum into a 1 mL tuberculin syringe.
Invert and flick the syringe until air bubbles rise to the top and air can be expelled, leaving only the prepared inoculum.
Load the syringe into the stepper device, making sure the syringe is firmly in place, the syringe’s plunger rests against the stepper’s pusher, and the hilt of the syringe rests on syringe clip to prevent slipping and inaccurate dispensing of inoculum.
Test that the stepper is accurately dispensing the inoculum when the dispense button is pressed.
Pick up a pre-sorted G. mellonella larva with the non-dominant hand. Hold the larva firmly with thumb and index fingers to prevent movement. Fingers should be placed towards the head and thorax to keep the abdomen open. Be careful not to stick the finger with the syringe needle.
Inject the needle into the last left proleg (Figure 2).
It is important to be consistent with which proleg is injected to reduce variability in the infection. The needle should enter midway through the larva.
Remove larvae carefully from the needle and place it into a Petri dish.
If excessive hemolymph (as indicated by yellow fluid) leaks from the injection site, larval death may occur. If problems with hemolymph leaking persist, leaving the needle in the larvae for 15 s before removal may reduce the amount of hemolymph lost. If there are concerns about dried hemolymph on the Petri dish following injection, hemolymph can be cleaned by temporarily removing the larvae, wiping the Petri dish with 70% ethanol, and drying with a paper towel.
Figure 2. Infection of larvae. (A) Illustration of G. mellonella larva model with indication of major anatomical parts. (B) Photo illustrating the injection site of C. neoformans cell suspension into the base of larva’s proleg. (C) Close up photo of the injection site.
Incubation and maintenance of the tested larvae
After finishing the series of injections, transfer Petri dishes with larvae to the location with desired temperature for the analysis (room temperature or 30 °C).
Perform evaluation of larvae variability every day by checking for changes in color of each larva and by gently poking the larva using the pointy end of a pipette tip.
If survival of pupae is also assayed, check pupal survival by gently pressing down on pupae with the base of the pipette tip. Lack of movement following poking indicates death. Change of body color in deceased G. mellonella larvae progress from an initial creamy color to grey, brown, and black (Figure 1A). Healthy pupae start off white and yellow, and naturally become a light to medium brown color, whereas dead pupae show a dark brown to black color (Figure 1B).
Data analysis
To analyze and visualize differences in G. mellonella, upload the data into the Prism GraphPad software using the survival table format. Plot the data as a percentage of survival in relation to the time (days). An example of how the survival data is collected and how tables should be formatted in the Prism GraphPad format is found in Figure 3A and 3B, where 0 represents a censored event, where survival data can no longer be read for the organism (i.e., the organism survives to the endpoint of the experiment or is lost), 1 represents death of an organism, and blank cells indicate no event occurred (no larvae died). Each event (death or censoring) requires a new line. An example output of this data on Prism GraphPad is found in Figure 3C.
Figure 3. Example formatting and graphing of survival data. (A) Survival data of G. mellonella is collected daily and recorded as the number of deaths that occur in each condition. (B) When converting the survival data into the format required by Prism GraphPad, each event is recorded, with only one event being recorded per line. A death event is recorded as a 1, while a censored event, either due to survival by the end point of the experiment or to the loss of an animal, is marked as a 0. In the control data in (B), there are two death events on days 3 and 12, and 13 censored events on day 14; this indicates that 2 larvae died, while 13 survived until the end of the experiment. The example data from (A, B) is plotted in (C) using Prism GraphPad.
Statistical differences between the tested group can be compared via log rank (Kaplan-Meier) test. P-value of <0.05 indicates a significant difference between datasets. Calculated hazard ratios can also be used to compare virulence between conditions.
Alternative protocol: Virulence assay at 37 °C
Development of cryptococcal infection in G. mellonella larvae can be altered with the changes in surrounding temperature. Incubation of infected larvae at 37 °C helps to mimic human body temperature and reduce the length of the experiment, but simultaneously stimulates metamorphosis of G. mellonella.
Selection of larvae with desirable mass
Select and separate G. mellonella larvae and prepare Petri dishes, one for each tested group. Using a digital scale, select bigger larvae with a body mass between 175 and 300 mg.
Eliminate possibility of contamination by using a sterile tissue soaked with 70% ethanol to clean the proleg area of the larvae before its transfer to the Petri dish.
Preparation of fungal cell inoculum
Approximately 48 h prior to the infection, inoculate 5 mL of YPD media with the desired strain of C. neoformans and incubate on the cell culture rotor at 30 °C.
Pellet the 48 h culture of C. neoformans for 4 min at 2,500 × g in the centrifuge, discard supernatant and provide equal amount (5 mL) of YPD media, and incubate culture for another 2–4 h.
This step allows infections to be performed with the cells in the stage of logarithmic growth, if desired. If not, proceed with the next steps without this additional incubation. Different microbial components, including virulence factors, are expressed at logarithmic stages of growth compared to stationary stages. Performing infections with fungi in logarithmic growth would allow researchers to investigate questions specifically related to how those factors affect virulence.
Transfer 1 mL of refreshed culture to Eppendorf tubes and pellet tested fungal strain by centrifuging tubes for 4 min at 2,500 × g in the tabletop centrifuge.
Wash your samples twice with DPBS, prepare a 1:100 cell dilution, and establish cell concentration using a hemocytometer.
Dilute your washed cells with DPBS to the concentration of 107 cells/mL.
Infection of larvae
Follow the steps of Basic Protocol: Infection of larvae.
Incubation and maintenance of the tested larvae
After finishing series of injections, transfer Petri dishes with larvae to the 37°C incubator and perform evaluation of larvae variability every day by checking the changes in color of each larva or by gently poking the larva using the pointy end of a pipette tip.
Data analysis
Follow the steps of Basic Protocol: Data analysis.
Recipes
Yeast peptone dextrose (YPD) liquid medium
1,000 mL of distilled H2O
20 g BD Bacto Peptone
10 g BD Bacto Yeast Extract
20 g Glucose (Sigma, 1002789701)
Alternatively
1,000 mL dH2O
50 g of Difco YPD Broth
To prepare YPD liquid media, mix all the ingredients in a 2 L Erlenmeyer flask using a magnetic stirring bar. Transfer the mixture into the glass bottles and autoclave for 20 min.
Notes
One main consideration when using Galleria mellonella as a model organism is its biological variability, which will depend on source of larvae or rearing protocols. To date, there is no widely available inbred isogenic G. mellonella strain that serves as a wild type. This opens the model up to genetic variation and thus immunological variability between larvae and larvae sources. Additional significant variability occurs due to diet differences during rearing. For this reason, it is important to perform sufficient replicates with different batches/generations of larvae. When measuring pupal survival, consistency is also important. Prior to emergence as a moth, the pupa will also stop responding to stimuli. This will occur after various amounts of time, depending on the environmental temperature, but will usually occur between days 10–14 at 30°C. While these pupae do not respond to stimulus, they will generally have a lighter color than a dead pupa and a lightweight and soft “dry” feeling when poked. Ideally, the experiment will be completed by this timepoint. Adult moths are censored as data points when they emerge, and survival of moths is not recorded.
Critical Parameters & Troubleshooting
To ensure proper quality of data obtained in the G. mellonella survival assay, it is important to include a negative control group of larvae inoculated with DPBS, as well as a positive control with a well-defined virulent cryptococcal strain (H99 or KN99). High mortality in the negative control group indicates problems with the procedure of injection or low viability of used larvae, which could occur for various reasons. For injection practice, food coloring in water or DPBS could be used to make sure the injections are entering the body cavity, indicated by organism-wide coloration. While there may be researcher-to-researcher variations between defining a G. mellonella larva or pupa as alive or dead, it is important that the threshold and determination of survival are consistent from day-to-day and between replicates. Consistency can be improved by making sure one (or as few as possible) researcher records all survival measurements.
To minimize the risk of accidental needlestick injury, keep a firm grip on the larva, avoid recapping the needle, and dispose all used syringes with needles to the appropriate biohazard sharps containers. In case of a needlestick injury, wash the area, follow procedures established at your research institution, notify the appropriate emergency health clinic at your institution, and seek physician expertise (Casadevall et al., 1994) .
Utilization of G. mellonella as a model organism for investigating C. neoformans virulence allows for a relatively quick assessment of different clinical, environmental, or mutant strains. Results of this assay can often be obtained in less than two weeks. Typically, larvae begin dying rapidly in less than a week following infection with C. neoformans. Increased incubation temperature and initial inoculum of fungal cells can shorten the total time of the experiment.
Acknowledgments
Protocol is adapted from Reeves et al. (2004), Mylonakis et al. (2005), García-Rodas et al. (2011), and Smith et al. (2021). Figures were made using BioRender.com.
Competing interests
We declare no conflict of interest.
Ethics
There are no current ethical restrictions or regulations governing the use of Galleria mellonella in laboratory settings due to their status as invertebrates. G. mellonella were euthanized by freezing for at least 1 h at -20°C.
References
Almeida, F., Wolf, J. M. and Casadevall, A. (2015). Virulence-Associated Enzymes of Cryptococcus neoformans. Eukaryot Cell 14(12): 1173-1185.
Browne, N., Heelan, M. and Kavanagh, K. (2013). An analysis of the structural and functional similarities of insect hemocytes and mammalian phagocytes. Virulence 4(7): 597-603.
Casadevall, A., Mukherjee, J., Yuan, R. and Perfect, J. (1994). Management of injuries caused by Cryptococcus neoformans--contaminated needles. Clin Infect Dis 19(5): 951-953.
Casadevall, A., Rosas, A. L. and Nosanchuk, J. D. (2000). Melanin and virulence in Cryptococcus neoformans. Curr Opin Microbiol 3(4): 354-358.
Cogliati, M. (2013). Global Molecular Epidemiology of Cryptococcus neoformans and Cryptococcus gattii: An Atlas of the Molecular Types. Scientifica (Cairo) 2013: 675213.
Crabtree, J. N., Okagaki, L. H., Wiesner, D. L., Strain, A. K., Nielsen, J. N. and Nielsen, K. (2012). Titan cell production enhances the virulence of Cryptococcus neoformans. Infect Immun 80(11): 3776-3785.
Eisenman, H. C., Duong, R., Chan, H., Tsue, R. and McClelland, E. E. (2014). Reduced virulence of melanized Cryptococcus neoformans in Galleria mellonella. Virulence 5(5): 611-618.
Firacative, C., Khan, A., Duan, S., Ferreira-Paim, K., Leemon, D. and Meyer, W. (2020). Rearing and Maintenance of Galleria mellonella and Its Application to Study Fungal Virulence. J Fungi (Basel) 6(3).
García-Rodas, R., Casadevall, A., Rodriguez-Tudela, J. L., Cuenca-Estrella, M. and Zaragoza, O. (2011). Cryptococcus neoformans capsular enlargement and cellular gigantism during Galleria mellonella infection. PLoS One 6(9): e24485.
Kwon-Chung, K. J., Fraser, J. A., Doering, T. L., Wang, Z., Janbon, G., Idnurm, A. and Bahn, Y. S. (2014). Cryptococcus neoformans and Cryptococcus gattii, the etiologic agents of cryptococcosis. Cold Spring Harb Perspect Med 4(7): a019760.
Liu, O. W., Chun, C. D., Chow, E. D., Chen, C., Madhani, H. D. and Noble, S. M. (2008). Systematic genetic analysis of virulence in the human fungal pathogen Cryptococcus neoformans. Cell 135(1): 174-188.
Lui, G., Lee, N., Ip, M., Choi, K. W., Tso, Y. K., Lam, E., Chau, S., Lai, R. and Cockram, C. S. (2006). Cryptococcosis in apparently immunocompetent patients. QJM 99(3): 143-151.
Maurer, E., Hortnagl, C., Lackner, M., Grassle, D., Naschberger, V., Moser, P., Segal, E., Semis, M., Lass-Florl, C. and Binder, U. (2019). Galleria mellonella as a model system to study virulence potential of mucormycetes and evaluation of antifungal treatment. Med Mycol 57(3): 351-362.
Mylonakis, E., Moreno, R., El Khoury, J. B., Idnurm, A., Heitman, J., Calderwood, S. B., Ausubel, F. M. and Diener, A. (2005). Galleria mellonella as a model system to study Cryptococcus neoformans pathogenesis. Infect Immun 73(7): 3842-3850.
Pereira, T. C., de Barros, P. P., Fugisaki, L. R. O., Rossoni, R. D., Ribeiro, F. C., de Menezes, R. T., Junqueira, J. C. and Scorzoni, L. (2018). Recent Advances in the Use of Galleria mellonella Model to Study Immune Responses against Human Pathogens. J Fungi (Basel) 4(4).
Perfect, J. R. and Bicanic, T. (2015). Cryptococcosis diagnosis and treatment: What do we know now. Fungal Genet Biol 78: 49-54.
Reeves, E. P., Messina, C. G., Doyle, S. and Kavanagh, K. (2004). Correlation between gliotoxin production and virulence of Aspergillus fumigatus in Galleria mellonella. Mycopathologia 158(1): 73-79.
Smith, D. F. Q. and Casadevall, A. (2021). Fungal immunity and pathogenesis in mammals versus the invertebrate model organism Galleria mellonella. Pathog Dis 79(3).
Stączek, S., Zdybicka-Barabas, A., Wiater, A., Pleszczynska, M. and Cytrynska, M. (2020). Activation of cellular immune response in insect model host Galleria mellonella by fungal alpha-1,3-glucan. Pathog Dis 78(9).
Trevijano-Contador, N. and Zaragoza, O. (2018). Immune Response of Galleria mellonella against Human Fungal Pathogens. J Fungi (Basel) 5(1).
Zaragoza, O. (2019). Basic principles of the virulence of Cryptococcus. Virulence 10(1): 490-501.
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A Step-by-step Protocol for Obtaining Mature Microglia from Mice
MY Min-Jung Yoo
MK Min-Soo Kwon
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4481 Views: 2106
Reviewed by: Alessandro DidonnaYiqun YuThirupugal Govindarajan
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Original Research Article:
The authors used this protocol in Journal of Neuroinflammation Dec 2021
Abstract
In mice, microglial precursors in the yolk sac migrate to the brain parenchyma through the head neuroepithelial layer between embryonic days 8.5 (E8.5)–E16.5 and acquire their unique identity with a ramified form. Based on the microglial developmental process, we dissected the neuroepithelial layer (NEL) of E13.5 mice, which is composed of microglial progenitor and neuroepithelial cells. The NEL was bankable and expandable. In addition, microglial precursors were matured according to NEL culture duration. The matured microglia (MG; CD11b-positive cells) were easily isolated from the cultured NEL using a magnetic-activated cell sorting system and named NEL-MG. In conclusion, we obtained higher yields of adult-like microglia (mature microglia: NEL-MG) compared to previous in vitro surrogates such as neonatal microglia and microglial cell lines.
Graphical abstract:
Keywords: Microglia Neuroepithelial layer (NEL) Microglial progenitor Expandable cells Banking
Background
So far, microglial cell lines, primary fetal/neonatal microglia, and acute isolated adult microglia have been used in in vitro studies. However, low yields, immature phenotypes, and the use of many experimental animals are barriers to studying microglia. Here, we introduce a new method for obtaining bankable and expandable adult-like microglia. The neuroepithelial layer (NEL) of mice at embryonic day 13.5 (E13.5), which is composed of microglial progenitors and neuroepithelial cells, was dissected and then cultured or banked. Microglia (MG; CD11b-positive cells) were isolated from the cultured NEL using a magnetic-activated cell sorting system and named NEL-MG. This new method contributes to the obtainment of matured forms of microglia (adult-like microglia) with only a small number of experimental animals.
Materials and Reagents
Animals
Timed pregnant (13d; TP13) C57BL/6 mice (female, Daihan-Biolink Co., Chungbuk, Korea)
Culture products
Microtubes (Axygen, catalog number: MCT-150-C)
15 mL conical tubes (Thermo Fisher Scientific, catalog number: 339650)
100 mm dish (Thermo Fisher Scientific, catalog number: 150466)
T-25 Flasks (Thermo Fisher Scientific, catalog number: 156367)
Hanks’ balanced salt solution (HBSS) (Thermo Fisher Scientific, GibcoTM, catalog number: 14170-112)
75% ethyl alcohol anhydrous (Daejung Chemicals & Metals, catalog number: 4023-2304)
Trypsin 2.5% (Thermo Fisher Scientific, GibcoTM, catalog number: 15090-046)
Poly-D-lysine (PDL) (Sigma-Aldrich, catalog number: P7280-5MG)
Dulbecco’s modified Eagle medium (DMEM) (Thermo Fisher Scientific, GibcoTM, catalog number: 11995-065)
Penicillin-Streptomycin (Thermo Fisher Scientific, GibcoTM, catalog number: 15140-122)
Fetal bovine serum (FBS) (Thermo Fisher Scientific, GibcoTM, catalog number: 16000-044)
GlutaMAXTM (Thermo Fisher Scientific, GibcoTM, catalog number: 35050061)
Dulbecco’s phosphate buffered salt (DPBS) (Thermo Fisher Scientific, GibcoTM, catalog number: 14190-144)
Trypan blue stain (0.4%) (Thermo Fisher Scientific, GibcoTM, catalog number: 15250-061)
Dimethyl sulfoxide (DMSO) (Sigma-Aldrich, catalog number: D2650-5X5ML)
Bovine serum albumin fraction V (BSA) (Merck, catalog number: 10735086001)
CD11b (microglia) MicroBeads (Miltenyi Biotec, catalog number: 130-093-634)
MS columns (Miltenyi Biotec, catalog number: 130-042-201)
Culture medium (500 mL) (see Recipes)
70% ethanol (100 mL) (see Recipes)
0.25% trypsin (10 mL) (see Recipes)
PB buffer (50 mL) (see Recipes)
Equipment
Optical microscope (Olympus, model: SZ-ST)
Clean bench (LabTech, model: LCB-1201V)
Dissection tools
Mosquito forceps (KASCO, catalog number: S8-099)
Micro dissecting forceps (KASCO, catalog number: 50-2000-1)
Micro scissors (Medro Instruments, catalog number: 02-027-10)
Electronic forceps (KASCO, catalog number: 11-412-11)
Centrifuge machine (LaboGene, catalog number: 1248R)
Hemocytometer (Marienfeld superior, catalog number: HSU-0650030)
CO2 cell culture incubator (PHCbi, catalog number: MCO-18AC-PK)
37 °C water bath (DAIHAN Scientific, catalog number: DH.WHB00106)
Magnetic cell separator (Miltenyi Biotec, catalog number:130-042-102)
Software
ImageJ (National Institutes of Health, https://imagej.net)
Prism 7 (GraphPad, https://graphpad.com)
Biorender (Biorender, https://biorender.com)
Procedure
Mixed neuroepithelium–microglial progenitor cultures form a confluent layer and help microglial survival and yield. Processing steps for dissection and culture are as follows:
Note: This step should be performed on a clean bench.
Step 1: Isolation and culture of murine microglia
Coat a T-25 culture flask with 5 mL of PDL for 2 h in a humidified incubator (5% CO2, 37 °C). Wash the flask bottom with 5 mL of distilled water three times and dry before use.
Prepare the tools and reagents needed for the culture experiment. Spray the dissection tools and workspace with 70% ethanol. Warm up the culture medium in a 37 °C water bath.
Collect TP13 mice from the breeding cage. For each mouse, inject the pentobarbital at a dose of 0.03 mL using a syringe via the intramuscular (i.m.) route into the leg muscle (100 mg/kg in saline).
Using micro scissors, cut through the abdominal wall. Use micro dissecting forceps to lift up the uterine horns and cut away the uterus with scissors. Transfer the extracted uterus to ice-cold (4 °C) HBSS.
Cut the muscular uterine tissue with micro scissors in a 100 mm dish containing 20 mL of HBSS at room temperature (20–25 °C). Then, grab the muscular uterine tissue with both electronic forceps and pull away to take out the mouse embryos. Separate the embryos by cutting through the uterus in the regions between each embryo. The embryos may pop out spontaneously or come out after pressing gently with the forceps.
Add 20 mL of HBSS at room temperature in a separate 100 mm dish.
Transfer 6–10 embryos to the dish (Figure 1).
With one hand, pick up an embryo with the forceps. Using the other hand, cut off the head skin above the eyes (Figure 2, Video1).
Transfer the dissected tissue to a microtube. Add 1 mL of 0.25% trypsin and chop up the tissue into several pieces using micro scissors. Pipet up and down several times with 1 mL pipet, and then place the tube in the cell culture incubator at 37 °C for 3 min.
Transfer the cell suspension to a 15 mL conical tube. Add 10 mL of DPBS at room temperature and centrifuge the 15 mL conical tubes at 300 × g for 5 min at room temperature.
Aspirate the supernatant and resuspend the pellet with 5 mL of warmed culture media.
Calculate the cell density using a hemocytometer.
Seed the cell suspension into the coated bottom T-25 flask at a density of 200,000 cells/cm2. Add the culture media to reach a final volume of 7 mL in the flasks. Place the flasks into the cell culture incubator at 37 °C with 5% CO2.
Change the fresh culture medium the next day, and then every 2–3 days, to remove cell debris.
After 14–21days of seeding, check the density of cells in the T-25 flask (Figure 3). When the cells reach 90% confluence, split them into two flasks.
Note: If the mixed cells reach confluency, but microglia are not needed immediately, the mixed culture can be stored. Mixed cultures can also be frozen for a long time in freezing media composed of DMEM with 20% FBS and 10% DMSO in liquid nitrogen (about -196 °C).
When thawing the mixed cells, dissolve the stock vials in a water bath at 37 °C for 3 min and dilute with culture medium.
Step 2: Purification of murine microglia from the NEL culture
To collect microglia, add 1 mL of 0.25% trypsin and incubate for 3 min.
Tap the T-25 flasks and collect the floating cells in conditioned culture media in the 15 mL conical tubes.
Add 10 mL of DPBS and centrifuge the tubes at 300 × g for 5 min. Aspirate the supernatant completely.
Resuspend the cell pellet in 90 µL of cold PB buffer per 107 total cells by pipetting up and down.
Add 10 µL of CD11b (microglia) MicroBeads.
Mix well and incubate for 15 min in the dark at 4 °C.
Wash the cells by adding 1 mL of cold PB buffer per 107 cells and centrifuge them at 300 × g for 5 min. Aspirate the supernatant completely.
Resuspend up to 107 cells in 1,500 µL of PB buffer.
Place a column in the magnetic field of a suitable magnetic-activated cell sorting separator (MACS). Prepare the column by rinsing it with 500 µL of PB buffer.
Apply the cell suspension onto the column. Collect the flow-through containing unlabeled cells and perform passing steps by adding the buffer three times, each time after the column reservoir is empty (MS column: 500 µL × 3).
Pipette 1 mL of PB buffer onto the column. Immediately flush out the magnetically labeled cells by firmly pushing the plunger into the column. This is the target cell (microglia) fraction (Figure 4).
Note: To increase the purity of microglia, it is recommended to enrich the positive fraction over a second MS column. Repeat the magnetic separation procedure as described in steps B9 to B11 by using a new column.
Figure 1. Processing of mouse embryos for neuroepithelial layer (NEL) culture. Firstly, separate the mouse embryos by cutting the uterus tissue in the regions between each embryo. Secondly, transfer the embryos to a new dish with cold HBBS—use one dish of fresh HBBS for every 6–10 embryos. Thirdly, use the micro dissecting forceps to dissect the head skin of embryos.
Figure 2. Dissection of mouse embryos for NEL culture. The NEL of mouse embryos was dissected using microsurgical instruments under a microscope.
Figure 3. Expandable microglia from the NEL culture. Arrows point to the microglial progenitors that were supported by NEL. Scale bar = 100 μm.
Figure 4. Isolation and purification of microglia from cultured NEL for 21 days. Cells were stained with microglial markers IBA-1, CX3CR1, and TMEM119. A bright-field microscope image shows the cell morphology. Scale bar = 100 μm.
Video 1. Steps for NEL dissection and culture.
Recipes
Culture medium (500 mL)
Reagent Final concentration Amount
DMEM n/a 450 mL
FBS 10% 50 mL
Pen/Strep
GlutaMAX
1%
0.5×
5 mL
500 µL
Total n/a 505.5 mL
70% ethanol
Reagent Final concentration Amount
Ethanol (absolute) 70% 70 mL
H2O n/a 30 mL
Total n/a 100 mL
Pentobarbital solution, 1 ampule (2 mL)
Reagent Final concentration Amount
100mg pentobarbital 3mg 2 mL
Saline n/a 8 mL
Total n/a 10 mL
0.25% trypsin
Reagent Final concentration Amount
2.5%Trypsin 0.25% 1 mL
DPBS n/a 9 mL
Total n/a 10 mL
PB buffer
Reagent Final concentration Amount
BSA 0.5% 0.25 g
DPBS n/a 50 mL
Total n/a 50 mL
Acknowledgments
This research was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean Government (MIST) (2021M3E5D9025027). The protocol was modified and written referring to our previous paper (You et al., 2021). We appreciate Dahye Kim for providing nice illustration.
Competing interests
There is no conflict of interest.
Ethics
All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of the CHA University (IACUC200116).
References
You, M. J., Rim, C., Kang, Y. J. and Kwon, M. S. (2021). A new method for obtaining bankable and expandable adult-like microglia in mice. J Neuroinflammation 18(1): 294.
Article Information
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Neuroscience > Nervous system disorders
Cell Biology > Cell isolation and culture > Cell differentiation
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4,482 | https://bio-protocol.org/en/bpdetail?id=4482&type=0 | # Bio-Protocol Content
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Visualization, Quantification, and Modeling of Endogenous RNA Polymerase II Phosphorylation at a Single-copy Gene in Living Cells
LF Linda S. Forero-Quintero
WR William Raymond
BM Brian Munsky
TS Timothy J. Stasevich
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4482 Views: 1371
Reviewed by: Zinan ZhouPooja VermaRama Reddy Goluguri
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Original Research Article:
The authors used this protocol in Nature Communications May 2021
Abstract
In eukaryotic cells, RNA Polymerase II (RNAP2) is the enzyme in charge of transcribing mRNA from DNA. RNAP2 possesses an extended carboxy-terminal domain (CTD) that gets dynamically phosphorylated as RNAP2 progresses through the transcription cycle, therefore regulating each step of transcription from recruitment to termination. Although RNAP2 residue-specific phosphorylation has been characterized in fixed cells by immunoprecipitation-based assays, or in live cells by using tandem gene arrays, these assays can mask heterogeneity and limit temporal and spatial resolution. Our protocol employs multi-colored complementary fluorescent antibody-based (Fab) probes to specifically detect the CTD of the RNAP2 (CTD-RNAP2), and its phosphorylated form at the serine 5 residue (Ser5ph-RNAP2) at a single-copy HIV-1 reporter gene. Together with high-resolution fluorescence microscopy, single-molecule tracking analysis, and rigorous computational modeling, our system allows us to visualize, quantify, and predict endogenous RNAP2 phosphorylation dynamics and mRNA synthesis at a single-copy gene, in living cells, and throughout the transcription cycle.
Graphical abstract:
Schematic of the steps for visualizing, quantifying, and predicting RNAP2 phosphorylation at a single-copy gene.
Keywords: Transcription RNA Polymerase II phosphorylation Single-copy gene Fluorescence microscopy Fluorescent antibody-based probes Transcription clusters Computational modelling
Background
Interest in the phosphorylation status of the CTD increased due to recent studies showing its correlation with RNAP2 clustering (Cissé et al., 2013; Cho et al., 2016; Boehning et al., 2018; Pancholi et al., 2021). These findings suggest that RNAP2 clusters form around gene promoters, and early in the transcription cycle, they are enriched in unphosphorylated-RNAP2 and Ser5ph-RNAP2 (Nagashima et al., 2019). RNAP2 phosphorylation distribution along the 1D genome has been extensively studied using immunoprecipitation-based assays (Heidemann et al., 2013; Harlen and Churchman, 2017). However, these techniques are performed using fixed cells and require averaging over a population of cells, limiting temporal resolution and masking heterogeneity (Coulon et al., 2013). Recent advances in fluorescent microscopy and single-molecule tracking (Tokunaga et al., 2008; Chen et al., 2014; Li et al., 2019) have overcome these limitations. Now, it is possible to monitor single RNAP2 dynamics at different locations throughout the genome (Cissé et al., 2013; Steurer et al., 2018) and specific single-copy genes (Cho et al., 2016; Li et al., 2019) pre-marked with MS2 (Tantale et al., 2016; Pichon et al., 2018) or PP7 (Larson et al., 2011; Coulon et al., 2014) RNA stem-loops. When transcribed, MS2 and PP7 tags form hairpin-like secondary structures, which are then bound by their fluorescence-labeled coating proteins, MCP and PCP, respectively. Unfortunately, previous protocols use permanent fluorescent fusion tags to track RNAP2, which cannot distinguish between the crucial RNAP2 phosphorylation states that control transcription.
Fluorescent antibody-based (Fab) probes can detect post-translational modifications to RNAP2 by binding and lighting up specific modifications to the CTD of RNAP2 in vivo (Hayashi-Takanaka et al., 2009; Stasevich et al., 2014; Kimura et al., 2015; Lyon and Stasevich, 2017). However, freely diffusing and unbound Fab probes lead to a high background; hence, this technique was previously limited to large tandem gene arrays (Stasevich et al., 2014) that include multiple copies of the same gene to enhance the signal-to-noise ratio. However, using such a protocol averages over many gene copies, and masks heterogeneity from one gene copy to another. Recently, our lab developed a protocol to measure and predict the spatiotemporal dynamics of RNAP2 phosphorylation and mRNA production throughout the transcription cycle of a single-copy gene. This protocol, which we describe here, combines multicolor single-molecule microscopy, complementary Fabs, and rigorous computational modeling (Forero-Quintero et al., 2021). For our system (Forero-Quintero et al., 2021), we utilized an established HeLa cell line (H-128) expressing a single-copy reporter gene controlled by an HIV-1 promoter, comprising an MS2-tag and its MS2 coating protein tagged with GFP (MCP, blue) (Tantale et al., 2016). Our reporter gene is predominantly active due to persistent stimulation by Tat, leading to a bright MCP-GFP signal, that indicates the location of the transcription site within the nucleus, allowing us to observe fluctuations in mRNA synthesis in real-time (Figure 1a). Our loaded Fabs recognize the CTD of RNAP2 (CTD-RNAP2, conjugated with CF640, red) without or with residue-specific phosphorylation, and specific phosphorylation at the Serine 5 within the CTD of RNAP2 (Ser5ph-RNAP2, conjugated with Cy3, green). This combination of imaging probes makes it possible to observe RNAP2 regions enriched or depleted with Ser5ph within the nucleus (Figure 1a, b). Fab binding and unbinding from their targets occurs rapidly, making it a valuable tool to monitor temporal changes in the phosphorylation status of RNAP2 (Hayashi-Takanaka et al., 2011; Stasevich et al., 2014; Kimura et al., 2015). At the HIV-1 reporter transcription site, we typically observe both Fabs present, but on occasion, the Ser5ph-RNAP2 signal becomes dim or absent despite the presence of CTD-RNAP2 and mRNA signals. Furthermore, all signals occasionally reduce to background levels, evidencing correlated fluctuations of the signals, which are caused by natural bursts and pauses in the transcriptional activity of the reporter gene (Figure 1b). By combining these multicolor elements, we can distinguish three distinct steps of the transcription cycle at the HIV-1 reporter gene: (1) RNAP2 recruitment (marked by Fab targeting CTD-RNAP2), (2) initiation (marked by Fab targeting CTD-RNAP2 and Fab targeting Ser5ph-RNAP2), and (3) elongation (marked by both Fabs and MCP binding to mRNA) (Figure 1a). To add a quantitative interpretation to these observations, we explored many possibilities and identified a simple computational model that matches all data. The optimal model that fits all data, but which avoided overfitting, consists of five basic rate parameters that describe four reactions: (1) the recruitment of RNAP2 in geometrically distributed bursts of average size (β) and frequency (ω), (2) the departure of unsuccessful or lost RNAP2 (kab), (3) promoter escape of RNAP2 (kesc), and (4) a combined rate of transcription completion and RNAP2 release (kc). Our simple mechanistic mathematical model allows us to estimate each of the above rates with excellent precision, as well as to predict the number of unphosphorylated and/or phosphorylated RNAP2 at each state throughout the transcription cycle at the HIV-1 reporter gene, and to simulate additional experimental features, such as RNAP2 positional densities or response to different transcriptional inhibition mechanisms.
Our integrated technique possesses several advantages: (1) Fab binds endogenous RNAP2, so all RNAP2 present in the cell at a given time has a high probability to be labeled; (2) The fluorescence of the Fabs is naturally amplified by the 52 heptad repeats contained in the CTD of RNAP2; (3) Fab continually binds and unbinds RNAP2, reducing the loss of fluorescence due to photobleaching; (4) Our technology can be employed to measure the RNAP2 dynamics and phosphorylation status at other single-copy genes, provided the location of the gene can be identified without (Gu et al., 2018) or with labeling techniques [e.g., using MS2 or PP7 tags (Larson et al., 2011; Coulon et al., 2014; Tantale et al., 2016; Pichon et al., 2018), or other labeling systems such as ROLEX (Ochiai et al., 2015), ANCHOR (Mariamé et al., 2018), DNA FISH (Takei et al., 2017) or CasFISH (Deng et al., 2015)]; and (5) our modeling approach directly considers the temporal and statistical fluctuations of individual transcription sites, and applies information criteria to identify the simplest model that matches all experimental data.
In this protocol, we describe step-by-step how to fragment and fluorescently label antibodies targeting the CTD of RNAP2, how we put them into human cells using bead-loading (McNeil and Warder, 1987; Hayashi-Takanaka et al., 2009; Stasevich et al., 2014; Cialek et al., 2021), the imaging conditions we employed and how to tune them to get a good signal-to-noise ratio based on the experimental needs, how to quantify signal intensities at the transcription site from 3D imaging movies, and how to infer an appropriate mathematical model to reproduce these data without overfitting.
Figure 1. Schematic of our multicolor system to visualize RNAP2 phosphorylation at the transcription site of a reporter gene. A. The reporter gene contains a 128x MS2 insert (blue) that, when transcribed, produces stem-loops which are then recognized and bound by MCP genetically fused to GFP, thus lighting up the location of the gene within the nucleus, as well as the synthesis of nascent and mature mRNAs. Our Fabs are capable of identifying the CTD of RNAP2, as well as its phosphorylation at serine 5, which were fluorescently labeled with CF640 (red) and Cy3 (green), respectively. By combining these three elements, it is possible to visualize the recruitment (by CTD-RNAP2-CF640), initiation (by Ser5ph-RNAP2-Cy3), and elongation (by MS2-MCP-GFP) steps at the transcription site of a reporter gene. B. Crops from an example cell displaying, from top to bottom, the mRNA, Ser5ph-RNAP2, CTD-RNAP2, and merge signals, at three characteristic time points, in which (left) all three signals are present, (middle) mRNA and CTD-RNAP2 are present, but Ser5ph-RNAP2 is dim or absent, and (right) all signals are absent. These data demonstrate transcription fluctuations and the occurrence of multiple transcription cycles (example cell image adapted from Forero-Quintero et al., 2021).
Materials and Reagents
CTD-RNAP2 & Ser5ph-RNAP2 Fab generation and dye-conjugation
15 mL conical collection tubes (Fisher Scientific, catalog number: 14-959-49D)
500 mL Steritop Threaded Bottle Top Filter, 0.22 µm, Polyethersulfone (PES), Sterile, 33 mm fitting, (Millipore Sigma, catalog number: SCGPS05RE)
Amicon Ultracel-4 (10 kDa-cutoff) centrifugal filter unit with cellulose membrane, 4 mL sample volume (Millipore Sigma, catalog number: UFC801024)
Amicon Ultracel-10 (10 kDa-cutoff) 0.5 centrifugal filter unit (Fisher Scientific, catalog number: UFC501024)
0.6 mL and 1.7 mL low retention microcentrifuge tubes (Thomas Scientific, catalog numbers: 1149J99 and 1149K01, respectively)
PD-mini G-25 desalting column (VWR, GE Healthcare, catalog number: 95055-984)
Rack/stand for filtering using 15 mL conical tubes (we use the rack provided with the NucleoBond Xtra Midi Kit, from Macherey-Nagel, catalog number: 740420.50)
Pierce Mouse IgG1 Fab and F(ab’)2 Preparation Kit (Thermo Fisher Scientific, catalog number: PI44980), store at 4 °C
Anti-CTD-RNAP2 and anti-Ser5ph-RNAP2 monoclonal antibodies used were kindly provided by Dr. Hiroshi Kimura, but now they are commercially available (Cosmo Bio USA, catalog numbers: MABI 0601 and MABI 0603, respectively), store at 4 °C
Sodium Azide (Millipore Sigma, catalog Number: 71289-5G), store at RT
Phosphate-buffered saline (10× PBS) (Fisher Scientific, catalog number: BP661-10), store at RT
Sodium Bicarbonate (NaHCO3) (Millipore Sigma, catalog number: S5761-500G), store at RT, and 4 °C when in solution
Dimethyl sulfoxide (DMSO) (Millipore Sigma, catalog number: D8418), stored at RT
Cy3 N-hydroxysuccinimide ester mono-reactive dye pack (VWR, catalog number: 95017-373), store at -20 °C
CF640R Succinimidyl Ester (Biotium, catalog number: 92108), store at -20 °C
Sodium Bicarbonate (NaHCO3) (Millipore Sigma, catalog number: S5761-500G), store at RT, and 4 °C when in solution
1× PBS (see Recipes)
H-128 cell culture
100 mm tissue culture dishes (VWR, CELLSTAR, catalog number: 82050-546)
Serological pipettes Polystyrene 10 mL (VWR, catalog number: 82050-482 (CS))
1 L glass graduated cylinder (Chemistry stock room CSU)
HeLa Flp-in H9 cells (H-128) (Kindly provided by Dr. Edouard Bertrand (Tantale et al., 2016), store at -80 °C, and maintain at 37 °C in culture)
Dulbecco’s modified Eagle medium (DMEM), high glucose, no glutamine (Thermo Fisher Scientific, catalog number: 11960-044), store at 4 °C
L-glutamine (L-glut) (200 mM)-100× (Thermo Fisher Scientific, catalog number: 25030081), store at -20 °C
Penicillin Streptomycin (P/S) (10,000 U/mL) (Thermo Fisher Scientific, catalog number: 15140122), store at -20 °C
Fetal Bovine Serum (FBS), 100% US Origin (Atlas Biologicals, catalog number: F-0050-A), store at -20 °C
Hygromycin B (Gold Biotechnology, catalog number: H-270-1), store at -20 °C
Trypsin-EDTA (0.05%), phenol red (Thermo Fisher Scientific, catalog number: 25300062, store at -20 °C for long term, and at 4 °C when in regular use)
DMEM to maintain H-128 cells (see Recipes)
DMEM to image H-128 cells (see Recipes)
Transcription Inhibitors recipes (see Recipes)
Loading CTD-RNAP2-CF640 & Ser5ph-RNAP2-Cy3 Fabs into living H-128 cells
Glass bottom dishes (35 mm, 14 mm glass) (MatTek Corporation, catalog number: P35G-1.5-14-C).
Dye-conjugated Fabs “CTD-RNAP2-CF640 & Ser5ph-RNAP2-Cy3” (see details in Materials & Procedure sections A), store at 4 °C
Custom-made bead-loader with 106 μm glass beads [see details in our bead-loading protocol (Cialek et al., 2021)].
DMEM medium-high glucose, no glutamine, phenol red-free (Thermo Fisher Scientific, catalog number: 31053-028), store at 4 °C
Imaging
Triptolide, Tripterygium wilfordii (Millipore Sigma, catalog number: 645900), store at -20 °C
Flavopiridol, Alvocidib (Selleck Chemicals, catalog number: S1230), store at -20 °C
THZ1 2HCl, CDK7 Inhibitor (Selleck Chemicals, catalog number: S7549), store at -20 °C
Note: The inhibitors above were reconstituted in DMSO before storage.
Equipment
Rocker/rotator (Thermo Fisher Scientific, model: HulaMixer PRS-5/12, catalog number: 15920D)
Arduino Uno-R3 (SparkFun Electronics, catalog number: DEV-11021), and mini rotor (SparkFun Electronics, Servo-Generic Sub-Micro Size, catalog number: ROB-09065)
Tissue culture CO2 Incubator for cells (Heraeus, model: Heracell 150)
Tabletop centrifuge (Beckman Coulter, model: Microfuge 20)
Tabletop centrifuge capable of cooling (Thermo Fisher Scientific, model: Accusping Micro 17R, and/or Sorvall Legend XFR with F14 6x250LE)
UV-vis Spectrophotometer (Thermo Fisher Scientific, model: NanoDrop OneC, Catalog number: ND-ONE-W)
Biological safety cabinet (Nuaire, model: Class II type A/B3, NU-425-400)
TC20 Automated Cell Counter (Bio-Rad, catalog number: 145-0102)
Pure water filtration (Thermo Fisher Scientific, model: Barnstead NANOpure II)
Digital water bath (Fisher Scientific, model: ISOTEMP 210)
Fluorescence microscope with highly inclined illumination and a stage top incubator [we employed our custom-made microscope (Forero-Quintero et al., 2021)]
Laptop or desktop computer with Mathworks Matlab
Software
Preprocess the images with Fiji ImageJ (Schindelin et al., 2012) (https://fiji.sc/)
Analyze the preprocessed images using custom-made code written in Wolfram Mathematica 11.1.1 (https://www.wolfram.com/mathematica/), and available at https://github.com/MunskyGroup/Forero_2020/tree/master/Bioprotocol_Codes.
Model identification scripts and model-exploration Graphical User Interface (GUI) were created using MATLAB R2019b (https://www.mathworks.com/products/matlab.html), and are available at https://github.com/MunskyGroup/Forero_2020/tree/master/Bioprotocol_Codes.
Procedure
CTD-RNAP2 & Ser5ph-RNAP2 antibodies fragmentation & dye-conjugation (see Figure 2 for visualization of the major steps in this preparation)
Use the Pierce Mouse IgG1 Fab and F(ab’)2 Preparation Kit to fragment the Fabs.
Follow the instructions from the manufacturer available at: https://assets.fishersci.com/TFS-Assets/LSG/manuals/MAN0011653_Pierce_Mouse_IgG1_Fab_Fab2_Prep_UG.pdf.
From the manufacturer’s protocol above, we used the following conditions for the CTD-RNAP2 and/or Ser5ph-RNAP2 antibodies fragmentation process, which resulted in good quality/concentrated Fabs.
Begin with the IgG sample preparation. Repeat the centrifugation step of the Zeba Spin Desalting Column [this column is included in the Pierce Mouse IgG1 Fab and F(ab’)2 Preparation Kit, see details above in step A.1.a.] with 1 mL of Digestion buffer four times.
Add 0.5 mL of CTD-RNAP2 or Ser5ph-RNAP2 full-length antibody in 1× PBS at the maximum concentration recommended by the manufacturer (4 mg).
Important notes:
(1) The preparation of the CTD-RNAP2 and Ser5ph-RNAP2 Fabs should be done on separate days, since the kit only provides a single NAb protein column. This column can be reused up to ten times for different antibodies, as long as it is properly regenerated after each use.
(2) We used highly concentrated CTD-RNAP2 & Ser5ph-RNAP2 antibodies, but if you are purchasing commercial antibodies (usually provided at 1 mg/mL), you should concentrate the antibodies to a higher concentration before generating and purifying Fabs (see details on how to concentrate antibodies at Koch et al., 2021).
After equilibrating the immobilized Ficin in a spin column tube, add the IgG sample obtained in the step above (A.1.b.ii.), and incubate the digestion reaction for four hours (or five hours for better digestion) in constant mixing of the resin at 37 °C.
Note: The manufacturer recommends an end-over-end mixer or tabletop rocker, but sometimes these do not fit in a 37 °C incubator. To be able to keep the resin constantly mixing during the incubation, we used a mini rotor and programmed it to rotate 360° using an Arduino, and place it into our 37 °C tissue culture incubator.
Place the NAb Protein A Column to equilibrate at RT for approximately 30 min before finishing the digestion incubation. Then, perform the purification process as indicated by the manufacturer. This process involves a couple of washing and elution steps, in which the antibody can be lost. Thus, we recommend keeping the flow-throughs resulting from the washing and elution steps separately.
Measure the concentrations of the Fab, as well as the flow-throughs using the absorbance at 280 nm. We use a nanodrop, but any other spectrophotometer or a BCA protein assay would work.
Note: The Fabs generated with this protocol produce 50 kDa Fab, which corresponds to a third of the full-length antibody. Thus, if the starting mass of the antibody is 4 mg, it will produce 2.67 mg Fab. However, during digestion and purification processes, some of the antibodies are lost, resulting in 1–2 mg Fab mass. In many cases mass of Fab above 0.8 mg after digestion and purification could still result in good quality Fab (enough to concentrate, label, and later on, visualize transcriptional processes).
Do not forget to regenerate the NAb protein A column after finishing the purification step to be able to reuse it. Place the column back at 4 °C in 1× PBS with 0.02% sodium azide).
Fabs concentration.
Add the Fab and the flow-through Fab from washes 1 and 2 up to 3 mL into the Amicon Ultracel-4 centrifugal filter unit with a cellulose membrane, and centrifuge at 7,500 × g and 4 °C for 20 min.
Note: Mixing the Fab and flow-through Fab from washes 1 and 2 after the purification process helps to increase the concentration of Fab, if the concentration measured after the purification was between 0.8 and 1.5 mg/mL.
Add the 1 mL left to the filter unit and wash the 15 mL conical tube that contained the Fab using 2 mL of 1× PBS to complete 3 mL in the filter unit. Centrifuge one more time at 7,500 × g and 4 °C for 20 min.
Retrieve the solution retained by the filter unit. This is the concentrated Fab.
Measure the concentration of the concentrated Fab in the Nanodrop.
Another way to concentrate Fab is by using an Amicon Ultracel-10 filter 0.5 centrifugal unit:
Mix the Fab and the flow-through Fab from washes, and spin down 0.5 mL at a time, at 12,000 × g and 4 °C for 5 min, until all the volume (~3 mL) flows through.
Some volume containing the Fab will remain in the filter unit, add the adequate amount of 1x PBS up to 0.5 mL, centrifuge at 12,000 × g and 4 °C for 5 min. Repeat this step once.
Repeat step (A.2.e.ii.) one more time, but now for 20 min.
Carefully, flip the filter unit into a 1.7-mL low binding tube, and centrifuge at 300 × g and 4 °C for 1 min.
Add 30 μL of 1× PBS to wash the filter unit, and centrifuge once again as in step (A.2.E.iv.).
Measure the concentration using a nanodrop.
Purified unconjugated Fab can be stored at 4 °C until use. It can last up to a year or two without degrading, if properly stored.
Fabs dye-conjugation.
Get purified and concentrated Fab protein.
Use one low-binding tube per protein.
In one 0.6-mL low-binding tube, mix: 10 μL of 1 M NaHCO3 (for better results, prepare fresh) with 100 μg of the purified Fab protein, and add 1× PBS to make a total volume of 100 μL.
Note: e.g., if the purified Fab protein concentration is 1.8 mg/mL, 100 μg corresponds to 55.5 μL. Thus, the mixture will consist of 55.5 μL of purified Fab protein, 10 μL of 1 M NaHCO3, and 34.5 μL of 1× PBS, for a total volume of 100 μL.
Add the correct amount of dye. Use 2 μL of 1 μM CF640, and 2.66 μL of 1 μM Cy3 (both dyes were previously diluted in DMSO). After adding the dyes to the respective mixtures (CF640 to CTD-RNAP2, and Cy3 to Ser5ph-RNAP2), pipette up and down, and tap the tube to distribute the mixture evenly. Then, incubate at RT and protected from light for 2 h, while constantly rotating the mixture in a rotator.
Purify dye-conjugated Fabs using a G-25 mini trap desalting column (use one per conjugated Fab protein).
Discard the buffer in the mini trap column and replace it with 1× PBS (repeat this step three times for equilibration).
After equilibrating the column, take the incubated mixture (containing the labeled Fab), and add it to the top of the mini trap column (make sure it is centered and straight). Add 450 μL of 1× PBS for circulation (add it from above, do not touch the sides of the mini trap column).
Note: The Fab protein conjugated with the dye is heavier than the unconjugated one; thus, it would pass through the mini trap column faster. You will be able to see two separate strips forming. The lower one contains your conjugated Fab.
If the desired band is close to the bottom of the mini trap column, add 50 μL of 1× PBS; if further from the bottom, add up to 100 μL of 1× PBS. This will help to bring down the conjugated Fab.
Note: Keep a close look at the mini trap column, since you want to make sure you catch the conjugated Fab.
Start cooling down the centrifuge to 4 °C.
Get one 1.7-mL low-binding tube for each conjugated Fab, place it underneath the respective mini trap column, and add 500 μL of 1× PBS.
Note: Watch carefully, since this step will bring down all the conjugated Fab drop by drop.
Add the conjugated Fab resulting from the step above (A.3.e.v.) to the top of the Amicon Ultracel-10 (10 kDa-cutoff) 0.5 centrifugal filter unit (this filter allows proteins smaller than 10 kDa). Centrifuge at 12,000 × g and 4 °C for 5 min, and discard the flow-through.
Note: Align the filter perpendicularly to the centrifuge, so the protein is not centrifuged directly into the filter.
Add 500 μL of 1× PBS from the top of the filter, centrifuge one more time at 12,000 × g and 4 °C for 5 min, and discard the flow-through.
Repeat the step above (A.3.e.vii.), but now centrifuge for 10 min.
Note: If your flow-through is colored, it means the filter may be defective. The flow-through should be clear, meaning your conjugated Fab remains in the filter, and the flow-through is disposable.
Take the filter containing the conjugated Fab, and tightly place it in a 1.7-mL low-binding tube on top of it, and flip it. Centrifuge at 300 × g and RT for 2 min.
Measure the concentration and absorbance spectrum for each protein to calculate the degree of labeling.
Use a nanodrop or other spectrophotometer that measures the absorbance spectrum. Choose IgG as sample type, and the corresponding dye (CF640 or Cy3). Ideally, you should get a concentration higher than 1 mg/mL for your protein, and a 1.2 for the ratio of the absorbances.
Calculate the degree of labeling (DOL) of the Fab using the following equation:
Where ϵIgG and ϵdye are the extinction coefficients of the Fab protein (IgG) at 280 nm (83,000 M-1cm-1) and the dyes (150,000 M-1cm-1 for Cy3, and 105,000 M-1cm-1 for CF640, respectively). These numbers are provided by the manufacturer. AFab and ADye are the absorbances determined at 280 nm for the IgG protein, and for the dyes at 550 nm for Cy3 and 650 nm for CF640, and CF is the correction factor for the dye at 280 nm (0.08, and 0.37 for Cy3, and CF640, respectively, provided by the manufacturer). Store the labeled Fabs at 4 °C for up to a year or so.
Note: In our study (Forero-Quintero et al., 2021), Fabs with a DOL between 0.75 and 1 were used successfully for live-imaging experiments.
Figure 2. Major steps in fragmenting, labeling, and concentrating antibodies. (Left), Digest the full monoclonal antibody (mAB) against the desired protein modification, and then isolate Fab by using the Pierce Mouse IgG1 Fab and F(ab’)2 Preparation Kit to fragment the Fabs (Procedure A.1). Concentrate the isolated Fab using either an Amicon Ultracel-4 or -10 filter unit, as described in procedure A.2. (Right), Conjugate the purified and concentrated Fab with the desired fluorescent dye by assembling a reaction containing purified Fab, NaHCO3, PBS, and the dye. Purify and concentrate the dye-conjugated Fab, as described in procedure A.3.
H-128 cell culture
Prepare DMEM to maintain H-128 cells (see details in the Recipes section).
Cells are maintained to a confluency not greater than 95% in supplemented DMEM medium (see Recipe 2 below) at 37 °C, 5% CO2 incubator.
Note: The cells were passed a maximum of 25 times before bringing up a new batch of cells. Splitting of the cells was performed twice a week at most, to avoid stressing the cells due to the trypsinization procedure.
The day before performing an imaging experiment, plate the cells into MatTek dishes as follows:
Warm up the 0.05% trypsin stock, and supplemented DMEM to maintain H-128 cells.
Transfer the 100-mm dish from the incubator to the tissue culture hood.
Remove all the medium.
Wash the cells with 5 mL of 1× PBS three times.
Add 4 mL of 0.05% trypsin to cover the surface of the 100-mm dish. Let it stand at RT for approximately 40 s, and remove the trypsin with an aspirator. A thin layer will remain.
Place the cells back in the incubator for 5 min. After incubation, tap the bottom and the edges of the dish, to detach and singularize the cells from the bottom of the dish.
Observe the cells using a light microscope, to confirm the cells are detached and singularized.
Add 10 mL of supplemented DMEM medium to the dish. Using a 10-mL serological pipette, pipette the cells in the suspension up and down, placing the tip of the pipette against an edge of the dish, to break up cell clusters or groups of cells that did not singularize when tapping the cells. To make sure all the cells at the bottom of the dish are in the suspension, tilt the dish, and let the mixture of cells and media run from different angles in the dish while pipetting up and down.
Take a volume of 10 μL of the suspension, and count the cells using a cell counter.
Considering the number of cells measured, plate enough cells on the glass bottom region of the MatTek to reach a final concentration of 1.5 × 105 cells/mL. Let the resuspended cells stand on the glass region for a few seconds, before adding the supplemented DMEM medium. Approximately 0.8 mL of cells in suspension (3 × 105 cells/mL) and 1.2 mL of supplemented DMEM medium are required to maintain H-128 cells. This ratio results in good confluency of cells, to bead-load conjugated Fabs by bead-loading.
Place the cells in the MatTek chambers back in the 37 °C, 5% CO2 incubator, and let them sit for at least 24 h before any further procedure is done.
Loading CTD-RNAP2-CF640 & Ser5ph-RNAP2-Cy3 Fabs into living H-128 cells
Build your own bead loader consisting of 106 μm glass beads, a 100 μm nylon mesh [Spectramesh Woven Filters Polypropylene Opening: 105-µm (Spectrum Labs, catalog number: 148496)], and a MatTek dish with the glass bottom part removed [seeCialek et al. (2021) andKoch et al. (2021) for details on the construction].
On your bench, place a 0.6-mL low-binding tube, and mix:
~0.75 μg of CTD-RNAP2-CF640 protein Fab (~1 μL of the conjugated Fab obtained in procedure step A).
~0.5 μg of Ser5ph-RNAP2-Cy3 protein Fab (~1 μL of the conjugated Fab obtained in procedure step A).
Add 1× PBS to a total volume of 4 μL.
Note: Spin down the tubes containing the conjugated Fabs, and mix well by pipetting up and down before taking the volumes out for the mixture. Depending on the concentration of the conjugated Fabs, you can use up to 10 μL of the mixture described above, as long as the concentrations are maintained.
Mix well by pipetting up and down, but avoid creating bubbles in the mixture. Spin down.
Start warming 50-mL aliquots of the DMEM medium to image H-128 cells (see Recipe 3, below), without (DMEM-) and with (DMEM+) supplementation.
Note: This DMEM is red phenol-free, to facilitate imaging.
Place the following items in the cell culture hood, and perform the following steps in there:
A custom-made bead loader [to see a detailed explanation of the bead loader construction and procedure, see our recent publication (Cialek et al., 2021)].
The mixture of conjugated Fabs (described above).
A 15-mL conical tube per chamber to be bead-loaded.
A MatTek chamber with H-128 cells (plated at least 24 h before).
Load the 4 μL of conjugated Fab in the pipette tip, and set it aside. Remove all the medium (including the remnants around the rim in the glass bottom region, to ensure cells are not scrapped with the pipette tip) from the MatTek chamber, and place it aside in a 15-mL conical tube.
Note: It is important to remove all medium, especially around the glass region, since even the smallest remanent might (1) affect the concentration of conjugated Fabs added, and (2) the beads might float on that medium, and therefore not come in direct contact with the cells.
Add the 4 μL mixture of conjugated Fabs directly on top of the cells, right on the center of the glass bottom area.
Immediately after, place the custom-made bead loader on top of the MatTek chamber and gently sprinkle the glass beads on top of cells, by taping both chambers against the bench once.
Set aside the custom-made bead loader.
Tap the MatTek chamber against the bench 7–10 times, using enough strength for the glass beads to exert force against the cell membranes and let the Fabs in, but gently enough so the cells do not peel off the glass.
Notes:
(1) Similar to electroporation, the bead loading technique induces tiny tears in the cell membranes by a mechanical force, which allows the diffusion of conjugated Fabs into the cells through these tiny tears. This technique does not affect cell viability, and cells recover within hours post-procedure.
(2) Some cell types are more susceptible than others to peeling, especially if they do not attach directly to the glass and require some pre-treatment of the glass, like laminin, or polylysine, in which case bead loading might work, but the strength of tapping must be experimentally determined.
Gently pour the medium removed in step (C.5.) back into cells through a side of the chamber, not directly on top of the cells, ensuring not to disturb the cells.
Place the cells back in the incubator at 37 °C, 5% CO2, and let the cells recover for at least 1 h.
Bring the cells back to the hood and remove the medium. Wash out the glass beads by adding 1 mL of DMEM- at a time and pouring the solution into a liquid waste container. Repeat this as many times as needed, until most of the glass beads are gone. Use a light microscope to visually confirm relatively few beads remain.
Note: Tilting the MatTek chamber will help to bring down the beads, to the rim of the cover glass portion, where they can be aspirated with a pipette tip.
Remove the last addition of DMEM- and add 2 mL of DMEM+. Place the cells back in the incubator at 37 °C, 5% CO2. Let them fully recover for another 4 h before beginning imaging.
Note: In our experience, we observe cells recover fully and display active transcription sites co-localizing with RNAP2 5 h post-bead loading. To see a detailed explanation of the bead loading protocol and its applications, see our recent publication (Cialek et al., 2021).
Imaging
Imaging can be performed on a microscope equipped with 488, 561, and 637 nm lasers with appropriate filters, a stage top incubator to maintain the cells at 37 °C, 5% CO2, and sensitive EM-CCD cameras. We recommend using a widefield fluorescence microscope with highly inclined illumination (HILO) (Tokunaga et al., 2008) for better visualization of active and inactive transcription sites above the background.
Place the cells onto the stage-top incubator (37 °C, 5% CO2).
Define the imaging conditions based on the activation rate (measured or expected) of the gene studied.
Set up the imaging experiment to cover the entire nucleus of the cells. For H-128 (HeLa) cells, 13 z-stacks with 0.5 μm spacing are enough.
Notes:
(1) Capturing the whole volume of the nucleus is important to study transcription dynamics more precisely, and to guarantee that when the transcription sites disappear, this is not caused by it going out of the recorded region, but instead due to inactivation periods.
(2) The Z range we use covers from top to bottom HeLa, U-2 OS, HEK293, RPE1, and fibroblast cells.
Set up the temporal intervals according to the activation rate of the gene of interest and/or the type of event you desire to observe.
To visualize transcription fluctuations, you can set up your imaging experiment on the scale of minutes, depending on your gene of interest. The transcription site of our HIV-1 reporter gene exhibits fluctuations within the minute range. Thus, we did a short live-cell imaging set, in which each cell was imaged every minute, for 30 min. In this type of experiment, we were able to observe that mRNA, CTD-RNAP2, and Ser5ph-RNAP2 transcription fluctuations were nicely correlated; however, we were not able to observe multiple transcription cycles (multiple active and inactive periods) in a single cell record.
To visualize multiple transcriptional active and inactive periods of a gene, you should set up your imaging experiment in the order of hours, and depending on the total length of the measurement, set the scan of each cell every 1 or few minute(s) apart. You can also reduce the laser power if your movie lasts for several hours. Altering these two conditions would help to prevent photobleaching of the fluorescent probes and cell damage over the course of a movie. In our system, we recorded cells for a longer period of time; each cell was imaged every 1 min for 200-time points (~3 h 20 min), covering the entire cell (a representative recording is shown in Video 1). In our HIV-1 reporter gene, the mRNA signal rarely disappeared completely, however, longer movies allowed us to visualize these rare events in some of our cells. In some cases, the mRNA, Ser5ph-RNAP2, and CTD-RNAP2 signals turned on and off up to four times in a single movie, with RNAP2 signals appearing slightly earlier than the mRNA, indicating bursts of transcription and multiple complete transcription cycles.
To determine short time delays between signals, you should set up your experiment to a faster imaging rate. In our system, we observed a time delay between the CTD-RNAP2 and Ser5ph-RNAP2 signals at the HIV-1 transcription site. We expected serine 5 phosphorylation of the CTD tail of RNAP2 to occur in the order of seconds; therefore, we were not able to resolve the time lag between our RNAP2 signals using our 1-min rate movies. Thus, we imaged faster, 1 frame every 150 ms, for a total of 10,000-time points (150 s) in a single plane. Note that faster imaging is limited to a single plane, which is not problematic in this case, since transcription sites do not move much between z planes in the order of seconds.
Add triptolide to test for active transcription.
Set up your imaging experiment to capture the entire cell (13 z-stacks with 0.5 μm spacing), scanning each cell every 1 min for 35 min.
Acquire five time points.
After the first five time points, add triptolide at a final concentration of 5 μM directly to the top of the chamber.
Notes:
(1) For drug experiments, we usually withdraw 1 mL of the DMEM+ medium from the MatTek chamber before mounting it onto the microscope incubator and keep it at 37 °C. A few seconds before adding the stimuli to the cells, add triptolide to the reserved DMEM+, mix well, and add the mixture to cells.
(2) When adding the mixture to cells, make sure not to touch the chamber; otherwise, your field of view will go out of focus and be changed.
Continue to image the cells for 30 time points (30 min) after adding triptolide.
Note: Active transcription sites together with RNAP2 Fab signals disappear within 5–10 min upon addition of triptolide at the transcription site of our HIV-1 reporter gene. Degradation of mature mRNAs occurs in the order of hours. Triptolide experiments are good to determine whether nuclear spots of the right size and brightness are active transcription sites.
Add THZ1 and flavopiridol to inhibit later steps in the transcription cycle (initiation, and elongation, respectively).
Set up your imaging experiment to capture the entire cell (13 z-stacks with 0.5-μm spacing), scanning each cell every 1 min for 35 or 55 min, for flavopiridol and THZ1, respectively.
Note: It takes 20–25 min for THZ1 to completely inhibit transcription initiation, and therefore mRNA synthesis. For this reason, we imaged for an extended time, so we could visualize complete transcriptional initiation inhibition at the transcription site of our HIV-1 reporter gene.
Acquire five time points.
After the first five time points, add THZ1 at a final concentration of 15 μM or flavopiridol at a final concentration of 1 μM directly to the top of the chamber, as described above.
Continue to image the cells for 55 time points (55 min) after adding THZ1, and for 30 time points (30 min) after adding flavopiridol.
Video 1. Representative 3-color movie from a long-time imaging course after processing.
Maximum projection of a 13 z-stack three-color movie, representing an exemplary H-128 cell. The dashed white circle shows the transcription site of the HIV-1 reporter, in which the mRNA, CTD-RNAP2, and Ser5ph-RNAP2 signals are co-localized. The images were acquired every 1 min for a total of 200 min. The field of view is 512 by 512 pixels = 66.56 μm × 66.56 μm. Scale bar, 10 μm.
Data analysis
Image processing and signal quantification:
Correct the 3D images for photobleaching and laser fluctuation in each z-stack, by dividing the movie by the mean intensity of the whole cell or the nucleus in each channel to create a new corrected 3D movie. We used a script in Mathematica to perform this task. The code is available at https://github.com/MunskyGroup/Forero_2020/tree/master/Bioprotocol_Codes, saved as “BleachCorrectionZ_bioprotocol”.
Note: A max of the max image is required to construct a mask in this step (create a maximum projection through z, and then a maximum projection of the z-maximum projection in time). Creating the maximum projections is straight-forward using Fiji ImageJ max-projection (see Figure 3 for further details).
Using Fiji ImageJ, preprocess the corrected 3D movie from step E.1.a. (see Figure 3 for further explanation in how to create the following files), and:
Subtract the background intensity from each channel.
Create a 2D maximum projection through z.
Create a maximum projection in time of the 2D maximum projection in z (from step E.1.b.ii).
Save the 3D image sequences in a folder named with the cell number.
Figure 3. Image pre-processing pipeline. The flow chart displays how to pre-process a 3D movie to generate the files needed to quantify the intensity signals at the transcription site, using our custom-made script in Mathematica.
Note: We performed the tasks described in the following steps (E.1.c–E.1.l) using a custom code written in Mathematica, saved as “TranscriptionSiteTrackingCode_Bioprotocol” and available on Github athttps://github.com/MunskyGroup/Forero_2020/tree/master/Bioprotocol_Codes.
Create a mask delineating the nucleus of the cell.
Note: Use the maximum projection in time of the 2D maximum projection in z (“max of the max image”).
Optional: If the signal-to-noise ratio is poor, it is a good idea to create a running average projection over time (using a few frames, ~3).
Select the thresholds in each channel to visualize spots at the transcription site, and a bandpass filter to highlight just the transcription site in the mRNA channel.
Binarize the image generated in step E.1.e.
Track the transcription site over time. You can use the Trackmate (Tinevez et al., 2017) plugin in Fiji, or create your own tracking routine. We tracked transcription sites over time by using the ComponentMeasurements-IntensityCentroid built-in Mathematica routine, together with our click and track function, which allowed us to find the XY coordinates through time.
Create two masks for each time point: one marking the transcription site (TS) and one marking the background (BG).
Using the 3D image sequences (folder created in step E.1.b.iv.), determine the Z coordinate or z-stack at which the transcription site in XY has its maximum (“best z”).
Note: If the transcription site disappears due to transcription inactivation or inhibition, the Z or Zs where there is no signal remaining are replaced by the Z coordinate of the last visible position.
Calculate a new 2D maximum projection from the XYZ coordinates considering the “best z” in step E.1.i. at each time point.
Calculate the mean intensity values over time for the transcription site and background, using the TS and BG masks created as described in step E.1.h.
Note: We calculated the raw and normalized intensity vectors per channel using a moving average of three points to display the raw intensity as a function of time, and we calculated the normalized intensity by dividing the raw intensity by the average 95% intensity from all transcription sites.
To display the transcription sites over time, generate cropped images of the 3-time point moving average trims from the “best z” in each channel. Center each trim with the intensity centroid of the transcription site in the mRNA channel. We displayed CTD-RNAP2, Ser5ph-RNAP2, mRNA, and a merge.
Notes:
(1) Our Mathematica script “TranscriptionSiteTrackingCode_Bioprotocol” can be tested using the original raw movie (without processing except for the photobleaching and laser fluctuations correction) corresponding to Video 1. The movie is saved as “SupFig3a_PBC_Cell14_woProj_ExemplaryCell.tif”, and available at https://doi.org/10.6084/m9.figshare.14187011 [repository created for our original publication (Forero-Quintero et al., 2021) from which this protocol is derived]. We also provided an image of beads saved as “Beads02.tif” in the same repository, to correct for camera offset.
(2) We calculated the raw mean intensity for each channel at the transcription site over time, including background subtraction for each cell, without running average, and saved a file collecting all the data for all cells analyzed as “Raw_Intensities Analysis-BLC_W_BG_WO_RunAve_Date.XLS”. This file was then used in step E.2.
Biophysical parameters that can be extracted from the data analyzed in the steps above:
XYZ transcription site position through time without generalized maximum projections in Z [see Sup. Figure 3d in the original paper (Forero-Quintero et al., 2021), from which this protocol is derived].
Transcription dynamics throughout the transcription cycle (by CTD-RNAP2, Ser5ph-RNAP2, mRNA intensity signals at the transcription site, Figure 4).
Figure 4. Representative data after signal quantification. Normalized signal intensities over time for the exemplary 3D movie shown in Video 1. The signals co-localize at the transcription site, and represent CTD-RNAP2 (red circles), Ser5ph-RNAP2 (green squares), and mRNA (blue diamonds). Figure adapted fromForero-Quintero et al. (2021).
Analysis of minima signals when transcription is inactive [see Figure 2d in the original paper (Forero-Quintero et al., 2021)].
Analysis of transcription site spatial organization through time and the transcription cycle [see Figure 2e–h, Sup. Figure 3h, and Sup. Figure 4 in the original paper (Forero-Quintero et al., 2021)].
Note: Our “TranscriptionSiteTrackingCode_Bioprotocol” includes a Distance Analysis tab that can be adjusted for this quantification according to your purpose.
Quantification of the number of mRNAs per transcription site [see Figure 3d in the original paper (Forero-Quintero et al., 2021)].
Probability distributions for CTD-RNAP2, Ser5ph-RNAP2 intensity signals, and mRNA counts at the transcription site [see Figure 3d in the original paper (Forero-Quintero et al., 2021)].
Auto- and cross-correlations at the transcription site for CTD-RNAP2, Ser5ph-RNAP2, and mRNA signals [see Figure 3a–b in the original paper (Forero-Quintero et al., 2021)].
Transcription response upon transcriptional inhibition at different steps in the transcription cycle [see Figure 4 in the original paper (Forero-Quintero et al., 2021)].
Please refer to our original paper (Forero-Quintero et al., 2021) for details on criteria for data inclusion/exclusion, details on the number of replicates in each experiment, and statistical tests.
Quantitative model of transcription
Download Forero2020/Bioprotocol_Codes/ from: https://github.com/MunskyGroup/Forero_2020/tree/master/Bioprotocol_Codes.
Load trajectory data from XLS file (named as “Raw_Intensities Analysis-BLC_W_BG_WO_RunAve_Date.XLS” in our example) and normalize intensities and correlations (Section 1 in “ComputationalProtocol.m”).
Intensity data should be formatted such that it contains one column for each channel and (number of time points) × (number of cells) rows, where each subsequent cell is appended vertically,
For example, 3 channels with 20 cells of 200-min trajectories should have a shape of 4000 rows × 3 columns.
Change intensity normalization options if desired:
Default settings are minimum 0, and maximum 1.5, normalization to the 95th percentile of each intensity trajectory.
Change correlation lengths and normalization options:
Default settings linearly interpolate to find the zero-lag autocorrelation G(τ=0) and then average over all cells to find for each signal. This provides an estimate of the variance after removal of shot noise. Cross-correlations are computed separately for each cell, and then divided by the average correlation at zero lag time. By default, correlations are calculated for delays of -10 to +10 min for cross-correlations, and for 0 to 30 min for auto-correlations.
Define the model (Section 2 in “ComputationalProtocol.m”).
Specify the number of states.
Specify the number and initial guess for parameters and noise.
Specify stoichiometry matrix, S, and affine linear propensity functions W = W1*x + W0.
Specify intensity transformation matrix, c.
Additional details on formulating bursting models are found in Methods. Alternative models are described in Forero-Quintero et al. (2021, Sup. Figure 6).
Solve the model to compute steady state means, variances, auto-, and cross- correlations at specified time points (Section 3 in “ComputationalProtocol.m”).
Details for solution methods are provided inForero-Quintero et al. (2021), Section 9, Methods, “A quantitative model of transcription.”
Calculate log-likelihood of the data given the model (Section 4 in “ComputationalProtocol.m”).
Provide measured mean expression values (‘DataMeans’) for each channel, standard error of the mean for the molecules quantified (‘DataSEMs’), and the number of transcription sites (‘Nmolecules’) for each species. These values can be left as zero (0) in the code for channels that are not quantified. In our original paper (Forero-Quintero et al., 2021), we determined the number of nascent mRNAs at the transcription site (‘Ntranscripts’) by counting mature mRNAs and comparing their average intensity to the transcription site intensity for the reporter gene.
Specify which parameters are fixed “par_fixed” and which are allowed to change “par_changed” as needed for parameter searching.
Conduct parameter search to identify maximum likelihood estimate (MLE) (Section 5 in “ComputationalProtocol.m”).
We recommend using 20 or more iterative combinations of genetic algorithm (GA) and fminsearch analyses with multiple initial guesses and then select the best fit over these iterations.
Calculate Bayes Information Criterion (BIC) or Akaike Information Criterion (AIC) for model selection (Section 6 in “ComputationalProtocol.m”).
Specify the number of free parameters (k=5 in our example).
If using BIC, specify an estimated number of degrees of freedom in the data. We recommend a conservative estimate as (e.g., n=8). If using AIC, it is not necessary to estimate the number of degrees of freedom.
Run Metropolis Hastings search for parameter uncertainty quantification (Section 7 in “ComputationalProtocol.m”).
We recommend settings of 5,000 samples over 50 segments with a thinning rate of 20 for at least 20 chains (10 million total samples). For a proposal function, we recommend an N-dimensional Gaussian with variances selected to be 3%–5% of each parameter.
Plot correlation fit (Section 8 in “ComputationalProtocol.m”).
Additional Analyses (Sections 9–12 in “ComputationalProtocol.m”).
Sample model intensities.
Compare model and data intensity histograms.
Predict ChIP from the model.
Predict perturbation analyses.
Recipes
1× PBS
Bring into the cell culture hood:
10× PBS [add the whole content of PBS powder concentrate to 1 L of ultrapure water from a Milli Q, and mix properly. Make sure the pH is ~7.4, and then filter the solution using a Steritop Threaded Bottle Top Filter (0.22 µm)].
Four autoclaved bottles (500 mL).
900 mL of ultrapure water from a Nanopure.
Parafilm.
Steritop Threaded Bottle Top Filter (for 500 mL).
Add 100 mL of 10× PBS to 900 mL of ultrapure water from a Milli Q in a 1-L graduated cylinder, cover with parafilm, and mix it properly. Open a new Steritop Threaded Bottle Top Filter, and place it in the first bottle, add 500 mL of the solution, turn on the vacuum, and plug the hose.
Note: To make good use of the filter, make 3 L of 1× PBS at a time.
Store at RT until use. It lasts several months on the shelf.
DMEM to maintain H-128 cells
Thaw 50 mL of FBS, 5 mL of P/S, and 5 mL of L-glut. Add them to 500 mL of DMEM, high glucose, no glutamine, with red phenol, and mix well. Store at 4°C until use.
Make a 50-mL aliquot of the supplemented medium described above and add 150 μL of hygromycin (previously diluted in ultrapure water from Milli-Q, at a concentration of 50 mg/mL) to obtain a final concentration of 150 μg/mL of hygromycin in the medium.
Note: Hygromycin is necessary to maintain the expression of the HIV-1 reporter in the H-128 stable cell line. When the medium is supplemented with hygromycin, use it within two weeks and store at 4 °C when not in use.
DMEM to image H-128 cells
Follow the same instructions as above (Recipe 2), but now use DMEM, high glucose, no glutamine, without red phenol.
Note: A clear medium is necessary to guarantee crisp fluorescent images. Store at 4 °C. It is stable for several weeks when properly stored.
Transcription Inhibitors
Add 555 μL of DMSO to the whole content of Triptolide (TPL, 1 mg), and mix well, to obtain a stock concentration of 5 mM.
Add 6.2214 mL of DMSO to the whole content of Flavopiridol (Flav, 5 mg), and mix well, to obtain a stock concentration of 2 mM.
Add 3.9125 mL of DMSO to the whole content of THZ1 (5 mg), and mix well, to obtain a stock concentration of 2 mM.
Note: Store all the inhibitor stocks at -20 °C when not in use.
Acknowledgments
We thank all the members of the Stasevich and Munsky labs for their support and helpful discussion and suggestions. T.J.S was supported by the NIH (grant no. R35GM119728) and the NSF (grant no. MCB-1845761). L.S.F.Q., B.M., and W.R. were supported by the NIH (grant no. R35GM124747), and L.S.F.Q. was also supported by the W.M. Keck Foundation. This protocol was derived from the work published in Forero-Quintero et al. (2021).
Competing interests
The authors declare no competing interests.
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The authors used this protocol in PLOS ONE Nov 2021
Abstract
Protein aggregation remains a major challenge in the purification of recombinant proteins in both eukaryotic and prokaryotic expression systems. One such protein is the nucleocapsid protein of Crimean Congo Hemorrhagic fever virus (CCHFV), which has high aggregation tendency and rapidly precipitates upon purification by NiNTA chromatography. Using the detergent gradient purification approach reported here, the freshly purified protein by NiNTA chromatography was mixed with the dilution buffer containing a high detergent concentration, followed by overnight freezing at -80 °C. Thawing the resulting mixture at room temperature triggered the formation of a detergent concentration gradient containing the active protein in the low detergent concentration zone towards the top of the gradient. The inactive aggregates migrated to the high detergent concentration zone towards the bottom of the gradient. The method prevented further aggregation and retained the activity of the native protein despite numerous freeze–thaw cycles. This simple approach creates an appropriate microenvironment towards the top of the gradient for correctly folded proteins, and it prevents aggregation by rapidly separating the preformed early aggregates from the correctly folded protein in the mixture. This unique approach will be of potential importance for the biotechnological industry, as well as other fields of protein biochemistry that routinely purify recombinant proteins and face the challenges of protein aggregation.
Graphical abstract:
Keywords: Protein purification His-tag Bacterial protein expression CCHF nucleocapsid protein Protein aggregation
Background
Expression and purification of recombinant proteins from bacterial, viral, and eukaryotic expression systems is routinely carried out in the biotechnological industry, especially in the areas of development and commercialization of successful protein-based drug products. In addition, the expression and purification of recombinant proteins to study protein-protein, protein-nucleic acid, and protein-drug interactions, is routinely carried out in both academic institutions and the biotechnological industry. The inherent high aggregation tendency of proteins at various stages of expression, purification, and storage has significant impact upon product quality, safety, and efficacy. Unlike eukaryotes, the reduced environment of the bacterial cytosol and the lack of eukaryotic chaperones and post-translational machineries limit the efficient protein folding capability of a bacterial system. Due to these limitations, the huge expression of recombinant proteins in Escherichia coli (E. coli) often results in aggregation in inclusion bodies (Williams et al., 1982; Freedman and Wetzel, 1992; Chrunyk et al., 1993). The expression of the recombinant proteins at high translational rates exhausts the bacterial protein quality control system, resulting in the aggregation of partially folded and misfolded protein molecules to form inclusion bodies (Carrio and Villaverde, 2005). Formation of inclusion bodies poses a great challenge in the production and purification of recombinant proteins using E. coli as host. Purification of native-like proteins from inclusion bodies is extremely difficult. Despite the intensive processing, including the isolation of inclusion bodies from the cell, solubilization using denaturants, followed by refolding, the finally purified proteins tend to re-aggregate and show minimal activity. Protein aggregation in inclusion bodies can be reduced by decreasing the temperature of growing bacterial culture up to 16°C and reducing the inducer concentration. Although these efforts can be helpful for certain proteins, for most others the aggregation is triggered when bacterial cells are lysed during the purification process.
The detergent gradient approach discussed here for the purification of Crimean Congo Hemorrhagic fever virus (CCHFV) nucleocapsid protein (CCHFVNP) separates the early formed inactive protein aggregates from the correctly folded active protein and prevents further aggregation in the native protein sample. The correctly folded protein is retained in the appropriate microenvironment of the gradient, making the protein resistant to aggregation, despite numerous freeze–thaw cycles. The approach can be customized for the purification of any recombinant protein that is prone to aggregation. This native protein purification method produces a significant amount of pure protein without denaturation and refolding steps, commonly used in most protein purification procedures. The yield of the active protein produced by this method depends upon the aggregation tendency of the protein, which varies from protein to protein. If a protein has more aggregation tendency, the aggregates will move towards the bottom of the gradient, and little active protein stays on the top. For our protein (CCHFNP), almost 60% was aggregated, and the remaining 40% was active, which was pooled together and stored for later use. The approach will be of potential significance to the biotechnological industry, which faces challenges of protein aggregation at different stages of development and commercialization of protein-based drug products (Wang and Roberts, 2018).
Materials and Reagents
Toothpicks
Bacterial cultural tubes (MTC BIO, catalog number: T8235)
15 mL tubes (VWR, catalog number: 525-1070)
0.5 mL microtubes, black DNase RNase free (ARGOS, catalog number: T7456-001)
Plasmid pET-30a and Plasmid pET-CCHFNP
Triton X-100 (Fisher Bioreagents, catalog number: BP151-500)
HisTrap FF crude (Cytiva, catalog number: 17528601)
High Precision Streptavidin (SAX) (ForteBio, catalog number: 18-0037)
Rosetta (DE3) Competent Cells (Millipore Sigma, catalog number: 70954)
Kanamycin sulfate (Fisher Scientific, catalog number: BP906-5)
IPTG (IBI Scientific, catalog number: IB02125)
Protein ladder (Fisher Scientific, catalog number: 26616)
HisTrap FF crude (Cytiva, catalog number: 17528601)
Fraction collector F9-R (GE Healthcare, catalog number: 29011362)
T7 RNA polymerase kit (Promega, catalog number: P1300)
Biotin-11-CTP (Perkin Elmer, catalog number: NEL542001EA)
Bradford Protein Assay Kit 4 (Bio Rad, catalog number: 5000204)
1,000× Kanamycin stock (see Recipes)
1,000× IPTG stock (see Recipes)
Lysis buffer (see Recipes)
Elution buffer (see Recipes)
LB Broth (see Recipes)
LB Agar Plates (see Recipes)
5× SDS Loading Dye (see Recipes)
SDS-PAGE (see Recipes)
Coomassie Blue Staining solution (see Recipes)
Coomassie Blue Destaining solution (see Recipes)
Biotinylated RNA (see Recipes)
Dilution buffer (see Recipes)
RNA Binding Buffer (see Recipes)
Equipment
Spectrophotometer (Jenway, model: 6705; absorbance wavelength range 190–1,100 nm)
BLITZ probe (Nemko, forteBIO, model: BLITZ)
HPLC AKTA Pure 25L (GE Healthcare, Cytiva, model: 29018224)
Isotemp Incubator (Fisher Scientific, catalog number: 11-690-637D)
Excella E24 Incubator Shaker Series (New Brunswick Scientific, model: M1352-0000)
Allegra X-14R Centrifuge (Beckman Coulter)
Sonicator-Sonic Dismembrator Model 100 (Fisher Scientific, model: XL2000-350)
Legend Micro 17 Centrifuge (Sorvall, Thermo Scientific)
SDS-PAGE gel running system (Bio-Rad)
Software
Unicorn 7 (Cytiva)
BlitzPro 1.2 (ForteBio)
Procedure
Transformation of the plasmid in Rosetta DE3 E. coli cells
The gene encoding the CCHFV nucleocapsid protein (CCHFVNP) was synthesized by GenScript and cloned between NdeI and XhoI restriction sites in a pET-30a (+) backbone. The resulting plasmid (pET-CCHFNP) was obtained as a lyophilized powder from GenScript, and dissolved in Molecular Biology grade water at a final concentration of 20 ng/µL. This plasmid expresses CCHFVNP containing a C-terminal 6X His-tag. Alternatively, the plasmid can be generated in your own lab. Any inducible vector expressing the His-tagged protein of interest in bacteria can be used.
Thaw a vial of competent Rosetta (DE3) cells (~75 µL) on ice, and add 5 µL of the pET-CCHFNP plasmid (20 ng/µL) to the vial, followed by incubation of the resulting mixture on ice for 30 min.
Transfer the vial to a water bath at 30 °C for 1.5 min, and immediately incubate on ice for 2 min.
Add 700 µL of fresh LB broth to the mixture, and agitate the cells at 250 rpm using a bacterial shaker incubator at 37 °C for 90 min.
Carefully spread 100 µL of the transformed Rosetta cells onto an agar plate containing kanamycin (50 µg/mL). See the Recipes section for pouring agar plates.
Invert the plate and incubate inside a bacterial incubator at 37 °C overnight.
Screening bacterial colonies for protein expression
The next morning, identify five isolated colonies and label them as colonies 1, 2, 3, 4, and 5 on the backside of the agar plate. Lift the five isolated colonies from the agar plate one by one using a sterile toothpick. Drop each toothpick into a culture tube containing 5 mL of LB media with kanamycin (50 µg/mL).
Incubate each tube with constant shaking (250 rpm) inside the shaker incubator at 37 °C overnight.
The next morning, make up two 5-mL tubes of fresh LB media containing kanamycin (50 µg/mL) for each overnight culture tube. You will end up making a total of ten fresh LB tubes for five overnight culture tubes. Add 50 µL of the overnight culture from colony 1 to two tubes and label them properly to represent colony 1. This way, you will generate two secondary cultures for each colony, using the primary overnight culture. Repeat the process for colonies 2, 3, 4, and 5. Save the remaining primary overnight cultures at 4 °C for future inoculations.
Incubate the ten freshly made secondary cultures with constant shaking (250 rpm) at 37 °C for 2–3 h, and periodically keep checking the OD at 600 nm using a spectrophotometer. When the OD600 reaches 0.3–0.5, remove the tubes from the incubator. It usually takes 3–5 h to reach an OD of 0.3–0.5 at 600 nm.
Add 5 µL of IPTG stock solution (1,000×) to one of the two tubes of secondary culture for each colony. Do not add IPTG to the other tube, as this will be used as control later.
Incubate all tubes with constant shaking at 250 rpm at 16 °C overnight.
Transfer the overnight secondary cultures to fresh 15-mL tubes and pellet the cultures down by centrifugation at 4,000 × g and 16 °C for 15 min. Discard the supernatant, and save the bacterial pellets.
Add 80 µL of lysis buffer to each pellet, and vortex until the pellet becomes dispersed. Transfer the lysate into a 1.5-mL Eppendorf tube, and, using a sonicator, sonicate the mixture at 40 kHz (>400W) on ice for 5 min. Add 20 µL of 5× SDS loading dye to each tube. Load 15 µL of the resulting solution into a 12% SDS-PAGE gel. Load 10 µL of protein ladder in one of the lanes. Run the gel at 100 V until the dye front has passed the stacking gel, after which the voltage can be increased up to 200 V, if you want to save time. Stop running the gel when your protein of interest has reached the middle of the resolving gel, determined by looking at the marker lane.
Transfer the gel into a small box containing 200 mL of coomassie blue staining solution and keep on the rocker at room temperature for 1 h. Remove the gel from the staining solution and wash three times with 5–10 mL of water. Transfer the washed gel into 200 mL of destaining solution and keep on the rocker at room temperature for 1 h. If the bands are not visible, then add fresh destaining solution, and incubate the gel again until bands are visible. Compare the intensity of your band of interest between induced and uninduced lanes. The clear difference between induced and uninduced samples will help identify the colony that shows the best expression after induction. For example, a clear difference is noticed in the N protein band intensity, between induced and uninduced cells in Figure 1A (compare the induced lanes 2 and 3 with the corresponding uninduced lanes 9 and 10 in Figure 1A). Select the best expressing colony for large-scale expression.
Once the colony expressing the highest amount of protein has been identified, take 1 mL of the primary culture from that colony, saved at step 9, and add it to 500 mL of LB media containing kanamycin (50 µg/mL). Start this step in the morning.
Incubate the resulting culture with shaking at 37 °C, periodically measuring OD of the culture solution at 600 nm, as mentioned in step 10.
When the OD at 600 nm reaches 0.3–0.5, add 500 µL of the IPTG stock solution (1,000×), followed by incubation with constant shaking at 16 °C overnight, as mentioned in step 12.
The next morning, divide the 500 mL of overnight culture into five tubes, and pellet each tube down by centrifugation at 4,000 × g for 20 min. Discard the supernatant, and save the pellets to be used for protein purification in the next step. Alternatively, the pellets can be stored at -80 °C for later use.
Purification of CCHF-NP using the AKTA pure machine.
Resuspend the pellet from a single tube from step 19 in 20 mL of lysis buffer. Sonicate the lysate six times, for a period of 30 s each, resting the sample on ice for 60 s in between sonication steps. The sonication intensity level is set to ultrasonic frequency -40 kHz (>400W) on the sonicator. However, any other sonicator with ultrasonic frequency >20 kHz can be used for the sonication of cell lysates.
The culture should become noticeably clearer after sonication but will still be somewhat opaque. If the lysate is not clear, you can sonicate at an intensity level of 4 for an additional 30 s, resting the solution on ice for 1 min.
Centrifuge the lysate at 4,300 × g for 20 min to pellet down the cell debris. Store the pellet at -80 °C for later use to confirm that a significant amount of the protein was solubilized into the supernatant. The supernatant will be used in step 23 below. Reserve 100 µL of the supernatant for SDS-PAGE at a later step.
Prepare 500 mL of each lysis buffer and elution buffer in two separate beakers, labeled as beaker A and Beaker B, respectively. Load the supernatant from step 22 into the super loop of the AKTA Pure HPLC protein purification system, and a total of 20 mL of both lysis and elution buffers in equal ratio at the full speed of 20 mL per min. This will clean the pumps and tubing of the AKTA Pure system, and the outflow will go to waste as default.
Attach the HisTrap column to the AKTA Pure protein purification system. Using the Unicorn 7.0 software, equilibrate the column with the lysis buffer by running at least 10 column volumes through the column, at a speed of 4.0 mL per min. Ensure the pressure on the column never exceeds 0.5 Mpa.
While the column equilibrates, prepare the run program on the Unicorn 7.0 software, as follows:
Wash the column with 5 column volumes (5 CV) of lysis buffer.
Reset the UV monitor to zero.
Add the sample to the column at a speed of 1 mL/min. Collect the flowthrough.
Wash the column with 5 CV of lysis buffer. Collect the washes using the fraction collector.
Run the elution gradient from 0% elution buffer to 100% elution buffer over 20 CV. Collect the fractions using the fraction collector.
Wash the column with 10 CV of elution buffer. Let the washes go to waste.
Wash the column with 10 CV of water. For long-term storage, use 20% ethanol in water.
Start the run and pick up the samples from the fraction collector when the run is complete. If your protein has high aggregation tendency, you may see the solution turning turbid at this stage. Under such circumstances, quickly follow steps 27 and 28 below.
Use the elution profile saved on the AKTA purifier to identify the fractions containing the eluted protein. As shown in Figure 1B, the CCHFVNP starts eluting from fraction 1 and peaks in fraction 7. Save 100 µL of sample from each elution at -80 °C for SDS-PAGE analysis to confirm the presence of the protein in the eluted fractions.
Add an equal volume of dilution buffer to each eluted fraction. Gently mix the solution, and freeze the tubes upright at -80 °C overnight.
Figure 1. Purification of CCHFV nucleocapsid protein using a detergent gradient approach. (A) Coomassie-stained 12% SDS-PAGE gel, showing the CCHFV NP expression in different colonies of Rosetta DE3 E. coli cells. Uninduced colonies 1 and 2 are shown as control. (B) The elution profile of CCHFVNP from AKTA pure protein purification system. (C) Coomassie-stained 10% SDS-PAGE gel, showing the CCHFVNP in representative elution fractions from the AKTA pure. (D) The diluted fraction containing a total of 10 mL of solution is thawed at room temperature, after overnight freezing at -80 °C. The numbers on the line show the 1-mL markings on the tube. Pour the 1-mL fractions from the 10-mL tube into 1.5 mL-Eppendorf tubes, without disturbing the concentration gradient, as shown. SDS-PAGE analysis of the 1.5-mL fractions shows the presence of CCHFVNP in each fraction. (E) Fractions 1, 4, 10, and a mixture of fractions 1–4 from panel D were assayed for RNA binding activity using BLI. (F) RNA binding analysis of CCHFVNP using BLI. It should be noted that the CCHFVNP used in panel F was not purified by detergent gradient as shown in panel D. No RNA binding activity was observed. This data has been published in our recent manuscript (Royster et al., 2021).
The next morning, run the saved fractions from step 27 on a 12% SDS-PAGE gel, to identify the fractions that contain the highest concentration of pure protein devoid of any contaminating bacterial protein. Stain the gel with Coomassie blue, followed by destaining, as mentioned in steps 13 and 14. As shown in Figure 1C, the contamination-free CCHFVNP is present in all eluted fractions. However, the concentration is highest in fractions 6–8. It may happen that some elutions still contain contaminant bacterial protein—those fractions should be avoided.
Optional: Running a sample from the original lysate (step 22), flowthrough (step 25c), and pellet (step 22) helps to determine whether the protein is soluble in the lysate, and if the soluble protein can bind the column efficiently. As shown in Figure 1C, the CCHFVNP is soluble in lysis buffer, but a good amount of the protein still remains in the pellet. The protein binds tightly to the column, as a small amount is present in the flowthrough.
Once the fractions containing high concentrations of the protein devoid of contamination are identified in step 29, take out the corresponding diluted fractions from the -80 °C freezer (from step 28). For example, as shown in Figure 1C, the highest concentration of CCHFVNP is present in fractions 6–8, so the diluted fraction 7 is taken out from the -80 °C freezer. The fractions are allowed to thaw undisturbed upright at room temperature. While the solutions thaw, a detergent gradient is formed, with high concentration of the detergent at the bottom of the tube, and low detergent concentration at the top of the tube. The misfolded proteins migrate towards the high detergent concentration, towards the bottom of the tube. The correctly folded proteins remain in the low concentration zone, towards the top of the gradient. Never disturb the thawed tube, as it disturbs gradient formation.
Carefully remove 1-mL fractions from the top of the thawed tube using a pipette, aspirating gently and avoiding expelling air bubbles into the tube. Pour the aspirated 1-mL fraction into a 1.5-mL Eppendorf tube, as shown in Figure 1D. Top fractions will contain correctly folded protein, and misfolded protein will be present in the bottom fractions. Quantify the protein in each fraction using the Bradford Protein Assay Kit. The protein fractions can be stored in the -80 °C freezer. The fractions containing the active protein can be pooled together for long-term use. For our protein (CCHFNP), almost 60% was aggregated, and the remaining 40% was active.
Testing the RNA binding activity of the protein in detergent gradient fractions using Biolayer interferometry (BLI).
Add 5 µL of the biotinylated RNA (1.2 µg/µL) to 300 µL of RNA binding buffer, and save the resulting mixture in a black 0.5-mL Eppendorf tube on ice.
Program the BLITZ PROBE (ForteBio) machine, using the inbuilt BlitzPro 1.2 Software.
Select the initial wash step with RNA binding buffer for 30 s.
Select the binding of biotinylated RNA to the Biosensor for 200 s.
Select the second wash step with RNA binding buffer for 30 s.
Select the association of the protein to the biotinylated RNA for 300 s.
Select the dissociation of protein from the RNA for 500 s.
Hydrate the High Precision Streptavidin biosensor in RNA binding buffer for at least 10 min. Load the hydrated probe into the BLITZ machine.
Dilute the protein from fraction 1 at the required concentration in RNA binding buffer inside a 0.5-mL black tube. Keep the RNA binding buffer ready for wash steps. Do not dilute the protein before, to avoid potential aggregation. Start the run. The software will guide you following the instructions from step 34. As the binding cycle is running, the binding data is consecutively plotted by the inbuilt software, as shown in Figure 1E. After the completion of the first cycle, start another cycle with different concentration of the same protein fraction, but keep the concentration of the RNA same (1.2 µg/µL).
Once the kinetic curves at two or more concentrations of each fraction have been obtained, the kinetic data is analyzed by the BlitzPro 1.2 Software, to calculate the on-rate and off-rate constants, which are then used by the software to calculate the dissociation constant (Kd) that quantifies the binding affinity of the protein-RNA interaction.
Examine all other fractions of the detergent gradient to identify the fractions that contain the active protein, as shown by representative curves in Figure 1E. We plotted the binding curves of CCHFVNP before its purification by the detergent gradient approach, to demonstrate that it did not show activity (Figure 1F).
Data analysis
Generate the kinetic profiles for the protein-RNA interaction, also referred as sensograms, at a fixed concentration of the RNA and two or more concentrations of the protein, as shown in Figure 1E. The kinetic profiles are then analyzed by the inbuilt Blitz Pro 1.2 software in the global mode, in which all the sensograms at different concentrations are processed by the software to generate an on-rate constant (Kass), and an off-rate constant (Kdis). The software then uses these constants to calculate the dissociation constat (Kd). Note that Kd = Kass/Kdis. The sensograms are then individually analyzed by the Blitz Pro1.2 software in the local mode, to calculate these parameters for each sensogram. If the experiment is carried out at three different concentrations of the protein, then three sensograms will generate three Kd values, which are used to calculate the standard deviation (SD), as shown below.
Table 1. Binding parameters for the association of wild-type N protein and its stalk domain with the 5’ UTR of S-segment derived mRNA
Protein Name Kd (nM) Kass (m-1 s-1) Kdis (s-1)
Stalk Fraction 1 54.24 ± 10 1.08 × 105 5.87 × 10-3
Stalk Fraction 4 52.48 ± 16 3.11 × 105 1.82 × 10-2
Stalk Mixture 1–4 36.67 ± 3 1.40 × 105 5.10 × 10-3
Recipes
1,000× kanamycin stock
Reagent Final concentration Amount
Kanamycin 50 mg/mL 0.5 g
H2O n/a 10 mL
Total n/a 10 mL
Before adding the antibiotic to LB agar, first autoclave the LB solutions, and then allow them to cool to ~40 °C before adding the antibiotic.
1,000× IPTG stock
Reagent Final concentration Amount
IPTG 0.5 M 1.2 g
H2O n/a 10 mL
Total n/a 10 mL
Lysis buffer
Reagent Final concentration Amount
NaCl 150 mM 17.5 g
Tris-HCl (pH 7.4) 50 mM 12 g
Triton X-100 1% 20 mL
H2O n/a 1,980 mL
Total n/a 2,000 mL
To maintain ideal binding efficiency with the Ni2+ column, this buffer should have a pH 7.2–8.0.
Elution buffer
Reagent Final concentration Amount
NaCl 500 mM 29 g
Tris-HCl (pH 7.0) 50 mM 6 g
Imidazole 250 mM 17g
Triton X-100 1% 10 mL
H2O n/a 990 mL
Total n/a 1,000 mL
LB Broth
Reagent Final concentration Amount
LB Miller Broth 2.5% 25 g
H2O n/a 1 L
Total n/a 1 L
Autoclave immediately after mixing, and allow to cool to touch before adding any antibiotics.
LB Agar Plates
Reagent Final concentration Amount
LB Miller Agar 4% 40 g
H2O n/a 1 L
Total n/a 1 L
Autoclave immediately after mixing, and allow to cool to touch before adding any antibiotics. Add antibiotics when agar is approximately 60 °C, then mix and pour immediately.
5× SDS Loading Dye
Reagent Final concentration Amount
Tris-HCl 250 mM 4.4 g
SDS 10% 30 g
Glycerol 30% 90 mL
B-Mercaptoethanol 5% 15 mL
Bromophenol blue 0.02% 60 mg
H2O n/a 195 mL
Total n/a 300 mL
β-Mercaptoethanol should be added to aliquots of SDS dye, as it is not stable at room temperature.
SDS-PAGE
Reagent 5% stacking gel Resolving gel 12%
Ultrapure H2O 4.0 mL 3.3 mL
30% bis-Acrylamide 1.0 mL 4.0 mL
1 M Tris-HCl, pH 6.8 0.75 mL NA
1.5 M Tris-HCl, pH 8.8 NA 2.5 mL
10% SDS 60 µL 100 µL
10% APS 60 µL 100 µL
TEMED
Total volume
8 µL
6 mL
8 µL
10 mL
Volumes given are sufficient for making two gels in 1.00 mm plates. Make and pour the resolving gel first. Add 1 mL of either ethanol or isopropanol on top of the resolving gel. After 15–20 min, when the resolving gel has set, pour out the sealing fluid. Make and pour the stacking gel directly on top of the resolving gel and insert the comb.
Coomassie Blue Staining solution
Reagent Final concentration Amount
Methanol 50% 250 mL
Glacial Acetic Acid 10% 50 mL
Coomassie Blue 0.125% 0.625 g
H2O n/a 200 mL
Total n/a 500 mL
Coomassie Blue Destaining solution
Reagent Final concentration Amount
Methanol 40% 200 mL
Glacial Acetic Acid 10% 50 mL
H2O n/a 250 mL
Total n/a 500 mL
Biotinylated RNA
The 40-nucleotide long RNA, corresponding to the 5’ end of viral S-segment genomic RNA, is synthesized by Genscript and labeled at 3’ with biotin. Alternatively, the RNA can be synthesized using T7 RNA polymerase kit, and Biotinylated with CTP. The RNA is dissolved in RNase free water at a concentration of 1.2 μg/μL, and stored in 5-μL aliquots inside the -80 °C freezer.
Dilution buffer
Reagent Final concentration Amount
Tris-HCl (pH 7.4) 50 mM 6 g
L-Arginine 2 mM 0.35 g
L-Glutamine 2 mM 0.30 g
Triton X-100 1% 10 mL
Tween 20 0.4% 4 mL
H2O n/a 986 mL
Total n/a 1,000 mL
RNA Binding Buffer
Reagent Final concentration Amount
NaCl 80 mM 2.3 g
HEPES (pH 7.4) 40 mM g
KCl 20 mM 0.8 g
DTT 1 mM 0.08 g
H2O n/a 500 mL
Total n/a 500 mL
Acknowledgments
We would like to thank Dr. Mohammad Mir for reviewing this protocol. The Data (Figure 1) reported in this protocol has been previously published (Royster et al., 2021).
Competing interests
The authors do not have any financial or non-financial competing interests.
References
Carrio, M. M. and Villaverde, A. (2005). Localization of chaperones DnaK and GroEL in bacterial inclusion bodies.J Bacteriol 187(10): 3599-3601.
Chrunyk, B. A., Evans, J., Lillquist, J., Young, P. and Wetzel, R. (1993). Inclusion body formation and protein stability in sequence variants of interleukin-1 beta. J Biol Chem 268(24): 18053-18061.
Freedman, R. B. and Wetzel, R. (1992). Protein engineering. Curr Opin Biotechnol 3(4): 323-325.
Royster, A., Mir, S. and Mir, M. A. (2021). A novel approach for the purification of aggregation prone proteins.PLoS One 16(11): e0260143.
Wang, W. and Roberts, C. J. (2018). Protein aggregation - Mechanisms, detection, and control. Int J Pharm 550(1-2): 251-268.
Williams, D. C., Van Frank, R. M., Muth, W. L. and Burnett, J. P. (1982). Cytoplasmic inclusion bodies in Escherichia coli producing biosynthetic human insulin proteins. Science 215(4533): 687-689.
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Cost Effective Method for gDNA Isolation from the Cecal Content and High Yield Procedure for RNA Isolation from the Colonic Tissue of Mice
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Original Research Article:
The authors used this protocol in Life Sciences Jan 2022
Abstract
Microbiome studies are quickly gaining momentum. Since most of the resident microbes (consisting of bacteria, fungi, and viruses) are difficult to culture, sequencing the microbial genome is the method of choice to characterize them. It is therefore important to have efficient methodology for gDNA isolation of gut microbes. Mouse models are widely used to understand human disease etiology while avoiding human ethics-related complications. However, the widely used kit-based methods are costly, and sometimes yields (in terms of quality and quantity) are sub-optimal. To overcome this problem, we developed a straightforward, standardized DNA isolation procedure from mouse cecal content for further microbiome-related studies. The reagents we used to standardize the procedure are readily available even in a not-so-well-equipped laboratory, and the reagents are not expensive. The yield and quality of the DNA are also better than those obtained by the readily available kit-based methods.
Additionally, we modified the kit-based method of RNA isolation from the colon tissue sample of the mouse for better yield. Churning the tissue with liquid nitrogen at the beginning of the procedure improves RNA quality and quantity.
Graphical abstract:
Keywords: DNA isolation RNA isolation Cecal DNA Colonic tissue DNA isolation by lysis Cost-effective High yield
Background
Efficient extraction of high-quality (concentration: 800–2,200 ng/μL) and high molecular weight (>50 kb) genomic DNA and tissue RNA from the limited amount of available samples is the key challenge for downstream applications like next-generation DNA sequencing (NGS) or transcriptomics studies, among others. The expanding research on human diseases related to gut microbiota and associated gut health resulted in a plethora of methodologies used to profile the gut microbial composition and associated inflammatory status of the gut tissue.
Each step in the downstream data analysis process is subject to technical variation depending on the protocol or materials used for DNA or RNA isolation. Researchers have found striking differences in the results obtained from different kit-based methods within the same laboratory (Ferrand et al., 2014; Videnska et al., 2019; Gryp et al., 2020). Therefore, standardizing the protocols is of utmost priority for researchers to obtain consistent, good quality, and robust representative data.
The diversity of the gut microbes in gut ecosystems can be categorized based on their morphological, structural, biochemical, and genetic properties. Gut microbes also have notable differences regarding cell wall structure and cell membranes, which enclose their cytoplasm and genomic contents. Harsh sample treatments can affect DNA quality, while a mild process may cause partial lysis of the microbial community (Bag et al., 2016). Moreover, the unknown composition of the lysis buffer of kit-based methods presents different biases, drastically changing the results obtained from the same sample (Brooks et al., 2015). Therefore, it is important to optimize cell lysis methods to obtain genomic DNA from all groups of microbes present in the gut.
We developed a very efficient, cost-effective cell lysis method. Reagents used to standardize the process are readily available, even in a comparatively less equipped laboratory, and the reagents are not too expensive. The yield and quality of the DNA are also better than those obtained by the readily available kit-based methods.
In an RNA isolation procedure from gut tissue, it is essential to standardize the amount of tissue required to obtain good quality RNA. Proper tissue homogenization is another crucial step for a high yield of RNA. To get high quality and quantity of RNA, we standardized the needed amount of colonic tissue and the liquid nitrogen-based homogenization process.
These methodologies were published in a recent article (Pradhan et al., 2022).
Materials and Reagents
For gDNA isolation
Filter MAXIPENSETM, Low retention, clear, sterile tips 1,000 μL (Tarsons, catalog number: 527106), 200 μL (Tarsons, catalog number: 527104), and 10 μL (Tarsons, catalog number: 527100)
SpinwinTM Micro Centrifuge clear, sterile tubes 1.5 mL (Tarsons, catalog number: 500010) and 2 mL (Tarsons, catalog number: 500020)
Dissection box
Spatula
Tissue paper
Kimwipes
Nuclease-free water (Promega, catalog number: P1193)
1× sterile PBS (HiMedia, catalog number: TL1022)
Phenol-chloroform-isoamyl alcohol (24:24:1) (Sigma-Aldrich, catalog number: 516276)
Ice-cold absolute ethanol (Sigma-Aldrich, catalog number: 459836)
RNase A (Sigma-Aldrich, catalog number: R6513)
Tris-base
HCl
EDTA
NaCl
SDS
Milli-Q® ultra-pure water
70% ethanol (1,000 mL) (see Recipes)
Lysis buffer (100 mL), pH 7.2 (see Recipes)
For tissue RNA isolation
Filter MAXIPENSETM, Low retention, clear, sterile tips 1,000 μL (Tarsons, catalog number: 527106), 200 μL (Tarsons, catalog number: 527104), and 10 μL (Tarsons, catalog number: 527100)
SpinwinTM Micro Centrifuge clear, sterile tubes 1.5 mL (Tarsons, catalog number: 500010) and 2 mL (Tarsons, catalog number: 500020)
Dissection box
1 mL syringe
Weighing paper (Fisher Brand, size 4" × 4")
Tissue paper
Kimwipes
Mortar and pestle
RNAlater® (Sigma-Aldrich, catalog number: R0901)
RNaseZAPTM (Sigma-Aldrich, catalog number: R2020)
Nuclease-free water (Promega, catalog number: P1193)
Liquid nitrogen
RNeasy Mini Kit (Qiagen, catalog number: 74104)
DNase I (Qiagen, catalog number: 74106)
RDD buffer (Qiagen, catalog number: 74106)
70% ethanol (1,000 mL) (see Recipes)
Equipment
Pipette (1,000 μL, 200 μL, 20 μL, 2 μL) (Thermo Fisher, Massachusetts, U.S)
-80 °C freezer (Thermo Fisher, Massachusetts, U.S)
CO2 chamber for mice (Thermo Fisher, Massachusetts, U.S)
Vortex (Fisher Biotec, Wembley WA 6904, Australia)
Microcentrifuge (Eppendorf, Hamburg, Germany)
Laminar airflow (Thermo Fisher Scientific, Columbus, OH, USA)
Thermoshaker (Thermo Fisher, Massachusetts, U.S)
Rotospin (Tarsons, Kolkata, India) or any test tube rotator
Nanodrop 2000 machine (Thermo Fisher Scientific, Columbus, OH, USA) or any UV-VIS spectrophotometer (minimum sample volume 0–5 μL)
Qubit4 fluorometer (Invitrogen, California, USA) or any normal fluorometer
Horizontal gel electrophoresis apparatus (California, U.S)
Procedure
Part I: Microbial gDNA isolation from mouse cecal content
Collection of cecal content
Dissect the mouse aseptically and carefully remove the cecum.
Collect the cecal content in a sterile 2 mL microcentrifuge inside the laminar airflow to avoid any kind of environmental contamination. Label the sample properly. Immediately snap freeze the cecal content and store it at -80 °C for further use (Graphical abstract step 1).
Graphical abstract step 1. Collection of cecal content.
Cecal DNA extraction
Take the cecal sample from the -80 °C freezer and keep it on ice. Aseptically transfer 180–220 mg of cecal content into a sterile 2 mL microcentrifuge tube.
Add 1 mL 1× sterile ice-cold PBS to the sample and homogenize it properly by vigorous vortexing and pipetting.
Centrifuge the suspension at 1,500 × g for 5 min at room temperature (Graphical abstract step 2).
Graphical abstract step 2. Centrifugation of the cecal sample.
Carefully remove the supernatant. Add 600 μL of lysis buffer to the pellet and mix it properly by pipetting (Graphical abstract step 3).
Note: Do not use vortex for mixing.
Graphical abstract step 3. Lysis buffer addition.
Keep the mixture at 70 °C for 30 min with intermittent mixing by inverting the microcentrifuge tube several times (Graphical abstract step 4).
Graphical abstract step 4. Heating at 70 °C.
Centrifuge the lysate at 15,700 × g for 15 min at 4 °C and collect the supernatant in a sterile 2 mL microcentrifuge tube.
Add 1 mL of phenol-chloroform-isoamyl alcohol (24:24:1) to the lysate and mix it properly for 2–3 min by inverting the tube approximately 12–15 times.
Centrifuge the mixture at 15,700 × g for 15 min at 4 °C.
Collect the upper aqueous phase in a new sterile 2 mL microcentrifuge tube. Repeat steps 7–9 at least twice, until the lysate is colorless.
Add three volumes of ice-cold absolute ethanol to the colorless lysate and gently mix by simultaneously inverting and rotating in a rotospin instrument for 5–10 min.
Freeze the solution at -80 °C for at least 1 h. For better precipitation of DNA, keep it in the freezer for 4–5 h (Graphical abstract step 5).
Graphical abstract step 5. Precipitation at -80 °C.
Separate the precipitate by centrifugation at 15,700 × g for 15 min at 4 °C.
Wash the pellet once with 700 μL of 70% ethanol and centrifuge at 15,700 × g for 15 min at 4 °C (Graphical abstract step 6).
Graphical abstract step 6. Ethanol wash.
Dry the pellet at room temperature for 20–30 min.
Add 50–100 μL nuclease-free water to the pellet and mix it with gentle tapping.
Add 5 μL of RNase A and keep at room temperature for 15 min.
Repeat steps 10–15 to remove the RNase A and recover the pure microbial gDNA (Graphical abstract step 7).
Graphical abstract step 7. Microbial gDNA.
Immediately check the quality and quantity of the RNA, and store it in a -80 °C freezer.
Part II: RNA extraction from mouse colonic tissue
Collection of the colon tissue sample
Dissect the mouse aseptically and cut the colon portion from the entire gut.
Remove the colonic content by flushing with cold 1× sterile PBS.
Cut the tissue (80–120 mg) into small pieces and store it in RNALater (1,800 μL) at a -20 °C freezer for further use.
RNA extraction
For RNA isolation of the colonic tissue, we use the Qiagen RNeasy Mini Kit with an additional step of churning the tissue with liquid nitrogen for better yield.
Weight 20–30 mg (not more than 30 mg) of colonic tissue. Remove the remaining RNALater from the tissue sample using Kimwipes.
Place the tissue sample in a mortar. Add ample liquid nitrogen and immediately churn the tissue with the pestle. Ensure that all liquid nitrogen evaporates before grinding (Graphical abstract step 8).
Note: After step 2, follow the Qiagen RNeasy Mini Kit protocol.
Graphical abstract step 8. Tissue grinding.
Add 700 μL of RLT buffer to the mortar and mix the churned tissue with the buffer by pipetting.
Transfer the lysate into a 1.5 mL sterile microcentrifuge tube and centrifuge at 14,000 × g for 3 min at room temperature.
Carefully remove the supernatant by pipetting and add 1 volume of 70% ethanol to the lysate. Mix well by pipetting and centrifuge at 14,000 × g for 3 min at room temperature.
Carefully remove the supernatant and transfer up to 700 μL of the sample to an RNeasy Mini spin column placed in a 2 mL collection tube.
Close the lid and centrifuge at 8,000 × g for 15 s at room temperature. After centrifugation, discard the flowthrough.
Add 350 μL of Buffer RW1 to the RNeasy column, close lid, and centrifuge at 8,000 × g for 15 s at room temperature. After centrifugation, discard the flowthrough.
Add 10 μL of DNase I stock solution to 70 μL of Buffer RDD and mix by gently inverting the tube. Give a brief spin.
Add 80 μL of DNase I incubation mix directly to the RNeasy column membrane, and keep it at room temperature for 15 min (Graphical abstract step 9).
Graphical abstract step 9. Column purification.
Add 350 μL of Buffer RW1 to the RNeasy spin column. Close the lid and centrifuge at 8,000 × g for 15 s at room temperature. Discard the flowthrough.
Add 500 μL of Buffer RPE to the RNeasy spin column. Close the lid and centrifuge at 8,000 × g for 15 s at room temperature. Discard the flowthrough.
Add 500 μL of Buffer RPE to the RNeasy spin column. Close the lid and centrifuge at 8,000 × g for 2 min at room temperature. Discard the flowthrough.
Place the RNeasy spin column in a new 2 mL collection tube. Centrifuge at full speed for 1 min to dry the membrane.
Place the RNeasy spin column in a new 1.5 mL collection tube.
Add 30–50 μL of nuclease-free water directly to the spin column membrane. Wait for 2 min.
Close the lid and centrifuge at 8,000 × g for 1 min at room temperature to elute the RNA.
Immediately check the quality and quantity, and store the RNA in a -80 °C freezer (Graphical abstract step 10).
Graphical abstract step 10. Tissue RNA.
Data analysis
The concentration and quality of the obtained DNA (approximate expected yield/concentration: 800–2,200 ng/μL) and RNA (approximate expected yield/concentration: 700–2,000 ng/μL) can be measured by NanoDrop analysis (Graphical abstract step 11). The absorbance ratios at 260 nm/230 nm and 260 nm/280 nm can be determined to evaluate the purity of the extracted DNA and RNA, respectively. DNA and RNA concentration can be validated by the Qubit fluorometer (Graphical abstract step 12). DNA and RNA integrity can be assessed by 0.8% and 2% agarose gel electrophoresis, respectively.
Graphical abstract step 11. Quantity check by Nanodrop.
Graphical abstract step 12. Quality check by Agarose gel.
Notes
It is important to collect cecal samples from all animals within an experimental cohort at the same time of the day, to avoid diurnal oscillations of the gut microbiota (Thaiss et al., 2014). It is also recommended to isolate the DNA from freshly collected samples of a single cohort at the same time to avoid storage artifacts, as freezing of cecal samples was shown to influence the ratio of Firmicutes to Bacteroidetes (Bahl et al., 2012).
Recipes
Lysis buffer for gDNA isolation (100 mL), pH 7.2
Reagent Final concentration Amount
Tris-base n/a 1.211 g
HCl 0.1M 8.940 mL
EDTA 20mM 0.744 g
NaCl 100mM 0.584 g
SDS 4% 4.000 g
Milli-Q® ultra-pure water 100 mL Adjust the volume with water
70% ethanol (1,000 mL)
Reagent Final concentration Amount
Ethanol (absolute) 70% 700 mL
Milli-Q® ultra-pure water n/a 300 mL
Acknowledgments
We acknowledge Dr. Biswaranjan Pradhan for helping us to standardize the DNA isolation protocol.
We also acknowledge the two previous reports from our lab by Pradhan et al. (2019 and 2022), from which we adopted the mentioned DNA isolation protocol.
Competing interests
The authors declare no competing interests.
Ethics
Committee for Control and Supervision of Experiments on Animals, Govt. of India (CPCSEA) approved this study (IAEC, Reg. No- 1634/GO/ReBi/S/12/CPCSEA, protocol number NISER/SBS/IAEC/AH-186). All experiments were performed as per the approved guidelines.
References
Bag, S., Saha, B., Mehta, O., Anbumani, D., Kumar, N., Dayal, M., Pant, A., Kumar, P., Saxena, S., Allin, K. H. et al. (2016). An Improved Method for High Quality Metagenomics DNA Extraction from Human and Environmental Samples. Sci Rep 6: 26775.
Bahl, M. I., Bergstrom, A. and Licht, T. R. (2012). Freezing fecal samples prior to DNA extraction affects the Firmicutes to Bacteroidetes ratio determined by downstream quantitative PCR analysis. FEMS Microbiol Lett 329(2): 193-197.
Brooks, J. P., Edwards, D. J., Harwich, M. D., Jr., Rivera, M. C., Fettweis, J. M., Serrano, M. G., Reris, R. A., Sheth, N. U., Huang, B., Girerd, P., et al. (2015). The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies. BMC Microbiol 15: 66.
Ferrand, J., Patron, K., Legrand-Frossi, C., Frippiat, J. P., Merlin, C., Alauzet, C. and Lozniewski, A. (2014). Comparison of seven methods for extraction of bacterial DNA from fecal and cecal samples of mice. J Microbiol Methods 105: 180-185.
Gryp, T., Glorieux, G., Joossens, M., Vaneechoutte, M. (2020). Comparison of five assays for DNA extraction from bacterial cells in human faecal samples. J Appl Microbiol 129(2): 378-388.
Pradhan, B., Guha, D., Naik, A.K., Banerjee, Tambat, S., Chawla, S., Senapati, S., Aich, P. (2019). Probiotics L. acidophilus and B. clausii Modulate Gut Microbiota in Th1- and Th2-Biased Mice to Ameliorate Salmonella Typhimurium-Induced Diarrhea. Probiotics Antimicrob Proteins 11: 887-904.
Pradhan, S., Ray, P. and Aich, P. (2022). Microbiota transplantation from younger to older mice could restore lost immunity to effectively clear salmonella infection in Th2-biased BALB/c mice. Life Sci 288: 120201.
Thaiss, C. A., Zeevi, D., Levy, M., Zilberman-Schapira, G., Suez, J., Tengeler, A. C., Abramson, L., Katz, M. N., Korem, T., Zmora, N., et al. (2014). Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. Cell 159(3): 514-529.
Videnska, P., Smerkova, K., Zwinsova, B., Popovici, V., Micenkova, L., Sedlar. K., Budinska, E. (2019). Stool sampling and DNA isolation kits affect DNA quality and bacterial composition following 16S rRNA gene sequencing using MiSeq Illumina platform. Sci Rep 9: 13837.
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CRISPR/Cas9-mediated Gene Knockout Followed by Negative Selection Leads to a Complete TCR Depletion in orthoCAR19 T Cells
QZ Qian Zhang
JY Jingyi Yang
EM Eric Nigel Ebenezer Anand Manoharan
AY Alvin B. Yu
MM Michael C. Milone
Published: Vol 12, Iss 15, Aug 5, 2022
DOI: 10.21769/BioProtoc.4485 Views: 2305
Reviewed by: Alak MannaNavnita Dutta Anonymous reviewer(s)
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Cited by
Original Research Article:
The authors used this protocol in Science Translational Medicine Dec 2021
Abstract
Genome-editing technologies, especially CRISPR (clustered regularly interspaced short palindrome repeats)/Cas9 (CRISPR-associated protein 9), endows researchers the ability to make efficient, simple, and precise genomic DNA changes in many eukaryotic cell types. CRISPR/Cas9-mediated efficient gene knockout holds huge potential to improve the efficacy and safety of chimeric antigen receptor (CAR) T cell-based immunotherapies. Here, we describe an optimized approach for a complete loss of endogenous T cell receptor (TCR) protein expression, by CRISPR/Cas9-mediated TCR α constant (TRAC) and TCR β constant (TRBC) gene knockout, followed by subsequent CD3 negative selection in engineered human orthoCAR19 T cells. We believe this method can be expanded beyond CAR T cell application, and target other cell surface receptors.
Graphical abstract:
Schematic overview of the two-step process of endogenous TCR depletion in engineered human orthoCAR19 T cells using (1) CRISPR/Cas9-mediated gene knockout followed by (2) CD3 negative selection.
Keywords: CRISPR-Cas9 TCR knockout CD3 negative selection orthoCAR T cells TRAC/TRBC guide RNA 4D-Nucleofector Lonza Electroporator
Background
CRISPR-Cas9 technology enables gene knockouts (KO) and complete loss of protein translation in human cells, especially in primary cells (Seki and Rutz, 2018). In recently published research, we showed that combining an orthogonal human IL-2 and IL-2Rβ (ortho-hIL-2/ortho-hIL-2Rβ) system with CAR19 T cell therapy markedly enhanced the efficacy of the CAR T cell antitumor activity, in a well-established preclinical model of acute lymphoblastic leukemia (ALL) (Zhang et al., 2021). However, the unexpected deaths observed with high-dose ortho-hIL-2 led us to investigate mechanisms of toxicity. To explore whether T cell-mediated toxicity is related to acute xenogeneic graft-versus-host disease (GVHD) mediated through the T cell receptor (TCR), we knocked out the endogenous TCR of CAR T cells co-expressing ortho-hIL-2Rβ, using a CRISPR-Cas9 gene KO approach. We use guide RNAs (gRNA) targeting the TCR α constant (TRAC) and TCR β constant (TRBC) loci, followed by CD3 negative selection, resulting in TCR negative orthoCAR19 T cells.
Gene silencing is a powerful approach to study gene function and to discern molecular mechanisms underlying complex human diseases. Previous studies have utilized RNA interference (RNAi), small interfering RNA (siRNA), or short hairpin RNA (shRNA) technologies to effectively knock down genes of interest (Berns et al., 2004; O’Keefe, 2013). However, these knockdown approaches do not result in complete loss of gene/protein expression or KO and can often result in off-target effects (Jackson et al., 2006).
The CRISPR-Cas9 genome editing system consists of two components: a “guide” RNA (gRNA) and a Cas9. The Cas9 protein is an endonuclease that uses gRNA to form base pairs with DNA target sequences, enabling Cas9 to introduce a site-specific double-stranded break in the DNA. Through RNA-directed Cas9 nucleases, the CRISPR-Cas9 system can modify DNA with greater precision than existing technologies, such as transcription activator-like endonuclease (TALEN), and zinc-finger nuclease (ZFN) (Conant et al., 2022). While both TALEN and ZFN are artificial structures formed by joining restriction endonucleases with DNA-binding protein domains, CRISPR-Cas9 technology takes advantage of the antiviral defense mechanism of prokaryotes to perform genome editing at the targeted DNA sequence (Khan, 2019). Recent work done by Cui et al. revealed that both TALEN and ZFN inevitably generated massive off-target effects when targeting human papillomavirus 16 (HPV16), while the CRISPR-Cas9 system was shown to be more efficient and specific (Cui et al., 2021). Therefore, CRISPR-Cas9 technology shows better efficiency, feasibility, and practicality in multi-role clinical applications, as compared to TALEN and ZFN. Inference of CRISPR Edits (ICE) was used to analyze CRISPR editing data in this study. ICE is a free and easy-to-use software tool that offers fast and reliable analysis of CRISPR experiments, highly comparable to that of next-generation sequencing (NGS) data. CRISPR editing can be assessed and analyzed by uploading the Sanger sequencing data and specifying a guide sequence(s). A knockout score will be generated, which represents the proportion of cells that have either a frameshift or insertion-deletion mutation (indels). This score is a useful means to quantify the number of contributing indels that are likely to result in a functional KO of the targeted gene.
Our results showed that the CRISPR-Cas9 system is easy to operate, has a short cycle time, low cost, higher accuracy, and is more controllable in targeting TCR α and TCR β genes together than existing technologies such as TALEN and ZFN. The combination of CRISPR/Cas9 with CD3 negative selection leads to a complete TCR depletion in orthoCAR19 T cells.
Materials and Reagents
Tissue culture plates, flasks, and tubes
24 well cell tissue culture plates (Corning, catalog number: 3524)
T25 cell culture flasks (Thermo Fisher, catalog number: 156367)
T75 cell culture flasks (Thermo Fisher, catalog number: 156499)
15 mL centrifuge tubes (Corning, catalog number: 352095)
50 mL centrifuge tubes (Corning, catalog number: 430829)
Phosphate Buffered Saline solution (PBS) (Corning, catalog number: 21-031-CM)
RPMI 1640 medium (Gibco, catalog number: 11875085)
Bovine Calf Serum (Sigma, catalog number: 12306C-500ml)
Penicillin/Streptomycin (Thermo Fisher, catalog number: 10378016)
L-glutamine (Thermo Fisher, catalog number: A2916801)
Recombinant human Interleukin-2 (IL2) (R&D System, catalog number: 202-IL-050)
APC anti-human TCR α/β antibody (Biolegend, catalog number: 306718)
DynabeadsTM CD3 (Thermo Fisher, catalog number:11151D)
TrueCutTM Cas9 Protein v2 (Invitrogen, catalog number: A36497)
EasySet Magnet (Thermo Fisher, catalog number: NC9284020)
DNeasy Blood & Tissue Kit (Qiagen, catalog number: 69504)
Q5 Hot Start High-Fidelity DNA Polymerase Kit (BioLabs, catalog number: E0555S)
Trypan Blue Solution, 0.4% (Thermo Fisher, catalog number: 15250061)
QIAquick PCR Purification Kit (Qiagen, catalog number: 28106)
4D-NucleofectorTM X Kit (Lonza, catalog number: V4XC-2032)
Cell culture media (see Recipes)
Wash buffer for cells (see Recipes)
gRNA (see Recipes)
Equipment
4D-NucleofectorTM X Unit (Lonza, catalog number: AAF-1002X)
Flow Cytometer LSRFortessa (BD Biosciences, catalog number: 647800L6)
EppendorfTM 5424 Microcentrifuges (Fisher, catalog number: 05-400-005)
Cell culture hood HeraSafe KS (Thermo Fisher, catalog number: 10110910)
CO2 incubator HeraCell VIOS 160i (Thermo Fisher, catalog number: 15381075)
VeritiProTM 96-well Thermal Cycler (Applied Biosystems, catalog number: A47394)
Software
Genewiz (Azenta Life Sciences, https://www.genewiz.com/en)
ICE analysis (Synthego, https://ice.synthego.com/#/)
CRISPOR (Tefor, http://crispor.tefor.net/)
FlowJo (Tree Star Inc., version 10.1)
Prism 9 for macOS V.9.3.1(350) (https://www.graphpad.com/scientific-software/prism/)
BioRender (https://biorender.com/)
Procedure
A general workflow for the overall experimental procedures can be found in Figure 1.
Figure 1. General workflow of the overall experimental procedures. CRISPR/Cas9-mediated gene knockout followed by CD3 negative selection results in a complete depletion of TCR in orthoCAR19 T cells.
Preparation of human orthoCAR19 T cells
Primary human total T cells were purchased from the Immunology Core of University of Pennsylvania.
Count cells and adjust to 1 × 106 cells/mL in RPMI 1640 supplemented with 10% FBS, 2 mM L-glutamine, 100-U/mL penicillin, 100-g/mL streptomycin sulfate, and 10-mM HEPES. Assess cell viability using the Trypan Blue solution (0.4%, Thermo Fisher) as a cell stain for the dye exclusion test.
Wash the magnetic beads coated with anti-CD3/anti-CD28 three times with PBS, and once with cell culture media.
Mix T cells with the washed beads at a ratio of 1:3, for 16–24 h.
Transduce activated T cells with viral particles encoding orthoCAR19, as described by our previous work (Zhang et al., 2021). Briefly, both CD19BBz and ortho-hIL-2Rβ sequences were cloned in a p-TRPE lentiviral backbone, in frame with the restriction site XbaI and Sa1I for CD19BBz, ortho-hIL-2Rβ-T2A-mCherry, and CD19-ortho-hIL-2Rβ. Lentivirus was produced by transfecting HEK293T cells with a combination of the above transfer plasmid and three lentiviral package plasmids, pCI VSV-G, pRSV Rev, and pMDL gag/pol.RRE (Addgene).
Culture cells with 100 IU/mL human recombinant IL2, and feed them every day for three days, in preparation for CRISPR/Cas9-mediated TCR KO.
Preparation of the CRISPR-Cas9 complex
TCRα and TCRβ gRNA sequence (TRAC gRNA sequence: TGTGCTAGACATGAGGTCTA; TRBC gRNA sequence: GGAGAATGACGAGTGGACCC) were designed by using CRISPOR, an online program that helps design, evaluate, and clone guide sequences for the CRISPR/Cas9 system. The main considerations regarding potential gRNA candidates are for finding the gRNAs that (1) efficiently KO the gene close to ATG (translation start site) for maximum loss of function, or at the location of functional domain to disrupt the target function; (2) have no or less off-target genes.
The single human genomic sequence used in the TRAC and TRBC gRNA design was CTTCCTTTGTCCCCAATCTGGGCGCGCGCCGGCGCCCCCTGGCGGCCTAAGGACTCGGCGCGCCGGAAGTGGCCAGGGCGGGGGCGACCTCGGCTCACAGCGCGCCCGGCTATTCTCGCAGCTCACCATGGATGATGATATCGCCGCGCTCGTCGTCGACAACGGCTCCGGCATGTGCAAGGCCGGCTTCGCGGGCGACGATGCCCCCCGGGCCGTCTTCCCCTCCATCGTGGGGCGCC, with a protospacer adjacent motif (PAM) sequence of 20bp-NGG-Sp Cas9, SpCas9-HF1, eSpCas9 1.1.
Dissolve TCRα and TCRβ gRNAs (Agilent) in 1× TE buffer (IDT) at 10 μg/μL, and mix them together in equimolar concentrations.
Combine 1 μL of gRNA mixture, including 5 μg TCR α and 5 μg TCR β, with 2 μL (5 μg/μL) of Cas9 (Invitrogen).
Mix the gRNAs-Cas9 complex mixture by gently pipetting up and down twice; avoid creating air bubbles in the tube.
Incubate the complex mix at room temperature (RT: 15–25 °C) for 10 min.
Preparation of T cell suspension for electroporation
For each electroporation condition (including positive and negative controls), prepare 5 mL of cell expansion medium supplemented with 10% FBS, 2 mM L-glutamine, 100-U/mL penicillin, 100-g/mL streptomycin sulfate, 10-mM HEPES, and 100U IL2.
For each condition, add 2 mL of supplemented medium (prepared in Procedure A) to a 12-well plate (for 100-μL tip reactions), and place in a 37°C incubator.
Transfer 1.5 × 106 cells (for 100-μL cuvette reactions) from the orthoCAR19 T cells to a 15-mL tube. Centrifuge at 300 × g and RT for 5 min.
Electroporation of T cells with gRNA-Cas9 complex using the Lonza 4D system
A demonstration of how to perform electroporation using Lonza 4D system can be found in Figure 2.
Figure 2. A demonstration of how to perform electroporation using Lonza 4D system.
Aspirate the supernatant from the cell pellet (prepared in Procedure C). Resuspend cells in 100 μL of P3 buffer from the 4D-Nucleofector X Kit and pipette up and down to mix.
Using sterile 200-μL PCR tubes for each condition, combine the gRNA-Cas9 complex mixture (prepared in Procedure B) with cells in P3 buffer.
Mix gently by pipetting up and down carefully twice; avoid creating bubbles in the tube.
Transfer cells with the gRNA-Cas9 complex mixture into a cuvette from the 4D-Nucleofector X Kit, making sure that there are no air bubbles. Place the cuvette into the electroporation chamber.
Electroporate the cell mixture using the “human stim T-cell” preset program and a pulse code of EH-115.
Post-knockout culture
Immediately add culture media into the cuvette containing the electroporated cells, and incubate at 37 °C for 15 min.
Count cells, and adjust cell density to 0.8 × 106 cells/mL, by adding IL2-supplemented cell culture media.
Incubate at 37 °C for 72 h, for genome editing to occur.
Harvest cells for assessment of genome editing efficiency. Isolate and amplify the genomic DNA using primers that flank the target region. Sequence the PCR product.
PCR kit used: Q5 Hot Start High-Fidelity DNA Polymerase Kit
Harvest cells and check for TCR protein expression with flow cytometry, using APC human anti-TCRα/β.
Isolation of CD3 negative T cells
Negative selection of CD3+ cells is performed using Dynabeads CD3 (Thermo Fisher Scientific).
Wash the Beads
Resuspend the beads in the vial.
Transfer the desired volume of beads to a 5-mL tube.
Add the same volume of Isolation Buffer (PBS supplemented 0.1% BSA).
Place the tube in a magnet for 1 min, and discard the supernatant.
Remove the tube from the magnet and resuspend the washed beads in the same volume of Isolation Buffer as the initial volume of beads.
Prepare Cells
Prepare TCR KO T cells to 1 × 107 cells/mL in Isolation Buffer.
Transfer 1 mL of cells (1 × 107) to a tube, and add 25 µL of pre-washed and resuspended beads.
Incubate with gentle tilting and rotation at 2–8 °C for 30 min (depletion).
Place the tube in a DynabeadsTM magnetic rack for 2 min.
Transfer the supernatant to a new tube for further use, and discard the beads.
Flow cytometry
Wash the CD3 negative T cells twice with PBS, and stain with APC anti-human TCRα/β antibody (1:50, Biolegend) for 30 min, followed by two washes with PBS.
Quantify CD3 negative T cells using a BD LSRFortessa flow cytometer.
Perform analysis of T cell CD3 expression, using FlowJo software (Tree Star Inc., version 10.1).
Data analysis
The expression of CAR19 and orthogonal IL-2Rβ was confirmed by flow cytometry before performing TCR KO (Figure 3). Flow cytometry data were analyzed using the FlowJo software. For direct estimation of the efficiency and the type of mutations introduced by genome editing, genomic DNA was extracted from edited and non-edited T cells. PCR reactions were performed with primers surrounding the guide RNA, and the PCR products were visualized in 1.0% gel (Figure 4), and purified for standard Sanger sequencing (Genewiz). Once Sanger sequencing of the DNA was complete, the sequence traces were analyzed using ICE (Figures 5 and 6A-D). To completely deplete the unedited TCR positive cells, CD3 negative selection was performed using CD3 DynabeadsTM. The purity of the TCRα/β depletion was assessed by flow cytometry (Figure 6E); a demonstration of the flow cytometry gating strategy used in this study can be found in Video 1.
Figure 3. FACS analysis of CAR19 and ortho-IL2Rβ expression in T cells.
Figure 4. Agarose gel electrophoresis results for the analysis of PCR products. (A) TCRα. (B) TCRβ. Lane 1: Control (without TCR gRNA) Lane 2: TCR KO + CD3 negative selection.
Video 1. Demonstration of the flow cytometry gating strategy for the confirmation of complete TCR depletion.
Figure 5. Purification and sequencing of PCR products with a quantitative assessment of genome editing of TCRα/β knockout by using Synthego’s Inference of CRISPR Edits (ICE).
Figure 6. Sequencing results of TCRα/β KO visualized using ICE and flow cytometric assessment of TCRα/β depletion on day 4 after gene editing followed by CD3 negative selection. Samples of TCRα and TCRβ KO were successfully analyzed with multiple parameters shown, including sample label, ICE score, R2 score, knockout score, guide sequence, and PAM sequence. (A–B) The “contributions” tab shows the inferred sequences of TCRα (A) and TCRβ (B) that are present in an edited population, as well as their relative representation in the edited pool. The black vertical dotted line represents the cut site. (C–D) Sequencing chromatograms of TCRα KO vs. TCRα wild type (WT) (C) and TCRβ KO vs. TCRβ WT (D). (E) FACS analysis was used to confirm complete TCRα/β depletion after CD3 negative selection.
Recipes
Cell culture media
RPMI supplemented with 10% heat-inactivated FBS, 1% L-glutamine, 1% HEPES, 1% penicillin, and streptomycin.
Wash buffer for cells
PBS supplemented with 2% BSA
gRNA resuspended in TE buffer at 5 μg/μL
Acknowledgments
We thank the members of the following facilities at the University of Pennsylvania: Flow Cytometry Core for cell sorting, Human Immunology Core for providing T cells from normal donors.
This work was derived from the paper previously published by Zhang et al. (2021), called “A human orthogonal IL-2 and IL-2Rβ system enhances CAR T cell expansion and antitumor activity in a murine model of leukemia” in Sci Transl Med 13(625).
Competing interests
The authors have no financial and/or non-financial competing interests to disclose.
Ethics
T cells were collected under a University Institutional Review Board-approved protocol, and written informed consent was obtained from each healthy donor.
References
Berns, K., Hijmans, E. M., Mullenders, J., Brummelkamp, T. R., Velds, A., Heimerikx, M., Kerkhoven, R. M., Madiredjo, M., Nijkamp, W., Weigelt, B., et al. (2004). A large-scale RNAi screen in human cells identifies new components of the p53 pathway. Nature 428: 431-437.
Conant, D., Hsiau, T., Rossi, N., Oki, J., Maures, T., Waite, K., Yang, J., Joshi, S., Kelso, R., Holden, K., et al. (2022). Inference of CRISPR Edits from Sanger Trace Data. CRISPR J 5(1): 123-130.
Cui, Z., Liu, H., Zhang, H., Huang, Z., Tian, R., Li, L., Fan, W., Chen, Y., Chen, L., Zhang, S., et al. (2021). The comparison of ZFNs, TALENs, and SpCas9 by GUIDE-seq in HPV-targeted gene therapy. Mol Ther Nucleic Acids, 26: 1466-1478.
Gaj, T., Sirk, S. J., Shui, S-I. and Liu, J. (2016). Genome-Editing Technologies: Principles and Applications. Cold Spring Harb Perspect Biol 8(12): a023754.
Jackson, A. L., Burchard, J., Schelter, J., Chau, B. N., Cleary, M., Lim, L. and Linsley, P. S. (2006). Widespread siRNA "off-target" transcript silencing mediated by seed region sequence complementarity. RNA 12(7): 1179-1187.
Khan, S. H. (2019). Genome-Editing Technologies: Concept, Pros, and Cons of Various Genome-Editing Techniques and Bioethical Concerns for Clinical Application. Mol Ther Nucleic Acids, 16: 326-334.
O’Keefe, E. P. (2013). siRNAs and shRNAs: Tools for protein knockdown by gene silencing. Mater Methods 3: 197.
Seki, A. and Rutz, S. (2018). Optimized RNP transfection for highly efficient CRISPR/Cas9-mediated gene knockout in primary T cells. J Exp Med 215(3): 985-997.
Zhang, Q., Hresko, M. E., Picton, L. K., Su, L., Hollander, M. J., Nunez-Cruz, S., Zhang, Z., Assenmacher, C. A., Sockolosky, J. T., Garcia, K. C., et al. (2021). A human orthogonal IL-2 and IL-2Rβ system enhances CAR T cell expansion and antitumor activity in a murine model of leukemia. Sci Transl Med 13(625): eabg6986.
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Immunology > Immune cell function > Antigen-specific response
Molecular Biology > DNA
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Colocalization Assay with Fluorescent-tagged ATG8 Using a Nicotiana benthamiana-based Transient System
JM Jinyan Mai
DS Dandan Shang
FL Faqiang Li
NL Na Luo
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4486 Views: 2029
Reviewed by: Wenrong HeYuan WangYe Xu
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Original Research Article:
The authors used this protocol in bioRxiv Jun 2021
Abstract
Autophagy is an evolutionarily conserved intracellular degradation process. During autophagy, a set of autophagy-related (ATG) proteins orchestrate the formation of double-bound membrane vesicles called autophagosomes to engulf cytoplasmic material and deliver it to the vacuole for breakdown. Among ATG proteins, the ATG8 is the only one decorating mature autophagosomes and therefore is regarded as a bona fide autophagic marker; colocalization assays with ATG8 are wildly used as a reliable method to identify the components of autophagy machinery or autophagic substrates. Here, we describe a colocalization assay with fluorescent-tagged ATG8 using a tobacco (Nicotiana benthamiana)-based transient expression system.
Keywords: Autophagy ATG8 Colocalization assay Transient expression Nicotiana benthamiana
Background
As a highly conserved catabolic process, autophagy is sophisticatedly employed by eukaryotic cells to remove dysfunctional proteins and unwanted or damaged organelles via the vacuole in yeast and plants or the lysosome in animals. During autophagy, a set of ATG proteins, commonly referred to as core autophagic machinery, are recruited to direct the formation of autophagosomes (Marshall and Vierstra, 2018). Among them, ubiquitin-like protein ATG8 (or its mammalian homolog, LC3) is first lipidated through a ubiquitination-like enzymatic cascade and then coats expanding autophagic vesicles to promote the maturation of autophagosomes. Moreover, the lipidated ATG8 on the inner membrane of autophagosomes can serve as a docking platform for autophagy receptors to recruit specific cargoes during selective autophagy. When autophagosomes fuse with the vacuole or lysosome, the lipidated ATG8 lining the outer membrane is released by ATG4 and recycled, whereas the lipidated ATG8 on the inner membrane is degraded together with cargoes into the vacuole. Therefore, ATG8 is regarded as a bona fide marker for autophagosomes, and colocalization assays with ATG8 are wildly used as a reliable method for identification of ATG components or autophagic cargoes (Marshall and Vierstra, 2018).
Colocalization assays with fluorescent-tagged ATG8 have been carried out stably with transgenic plants or transiently with a protoplast expression system (Suttangkakul et al., 2011; Zhuang et al., 2013). Here, we have developed an alternative colocalization assay based on a tobacco (Nicotiana benthamiana) transient expression system. With this system, we have successfully detected the colocalization between ATG8 and multiple proteins of interest (POIs; Luo et al., 2021).
This protocol includes four major steps: 1) Vector construction; 2) Agrobacterium-mediated transient expression; 3) Concanamycin A (ConA) infiltration; 4) Confocal fluorescence microscopy imaging.
Materials and Reagents
1.5 mL microcentrifuge tubes (Biosharp, catalog number: BS-15-M)
50 mL mini bioreactor tubes (NEST, catalog number: 602052)
9 cm Petri dish (Sangon Biotech, catalog number: F611001)
1 mL syringe
Microscope slides, 76 × 26 mm (Sangon Biotech, catalog number: F518101)
Cover slides, 24 × 60 mm (Sangon Biotech, catalog number: F518118)
Marker pen
Single-edge razor blade
Aluminum foil
4-week-old Nicotiana benthamiana seedlings
7-day-old Arabidopsis seedlings
Agrobacterium tumefaciens strain GV3101
E. coli DH5α competent cells (Home-made)
LB (Sangon Biotech, catalog number: A507002)
Sucrose (Sangon Biotech, catalog number: A610498)
MgSO4 (Sangon Biotech, catalog number: A601988)
Agar (Sangon Biotech, catalog number: A505255)
MES (Sangon Biotech, catalog number: A610341)
0.5 M EDTA solution, pH 8.0 (Sangon Biotech, catalog number: B540625)
Acetosyringone (Sangon Biotech, catalog number: A601111)
Dimethyl sulfoxide (DMSO) (Sangon Biotech, catalog number: A100231)
MS basal salt mixture (Caisson, catalog number: 05210003)
Concanamycin A (Adipogen, catalog number: BVT-0237-C100)
Plant RNAout kit (Tiandz Inc., catalog number: 160906-50)
HiScript® II Q RT SuperMix for qPCR Kit (Vazyme Biotech Co., Ltd, catalog number: R222-01)
HiPure Gel DNA Mini Kit (Magen, catalog number: D2111-03)
ClonExpress® II One-Step Cloning Kit (Vazyme Biotech Co., Ltd, catalog number: C112-01)
pEGAD vector (NCBI accession No. AF218816)
FastDigest EcoRI-HF (NEB, catalog number: R3101M)
FastDigest BamHI-HF (NEB, catalog number: R3136M)
Antibiotics (All purchased from Sangon Biotech; Kanamycin sulfate, catalog number: A506636 Rifampicin, catalog number: A600812; Gentamycin sulfate, catalog number: A506614)
Liquid nitrogen
Bacterial suspension buffer (see Recipes)
ConA stock solution (0.5 mM) (see Recipes)
MS-C liquid medium (see Recipes)
Equipment
Centrifuge (Eppendorf, model: 5804 R)
Water bath
Eppendorf Research® plus Pipette (0.5–10 μL pipette, catalog number: 3120000020; 10–100 μL pipette, catalog number: 3120000046; 100–1,000 μL pipette, catalog number: 3120000062)
Nanodrop spectrophotometer (NanoDrop, model: ND-1000)
Incubator
Flow hood
Plant growth chamber (Ningbo Jiangnan Instrument Factory, model: RXZ-500C)
pH meter (Sartorius, model: PB-10)
Thermocycler (Bio-Rad, model: S1000)
Autoclave (HIRAYAMA, model: HVE-50)
Vortexer (Kylin-Bell, model: VORTEX-5)
Procedure
Vector construction
PCR amplification of the Arabidopsis AtATG8a (AT4G21980) gene: Isolate total RNA from 7-day-old seedlings using the Plant RNAout kit (Tiandz Inc.,160906-50), and then convert 1 μg of total RNA to cDNA using the HiScript® II Q RT SuperMix for qPCR Kit (Vazyme Biotech Co., Ltd, R222-01) with oligo(dT)20. Amplify the AtATG8a gene using PCR with the forward primer 5’-CTGCGGCAGCGGCCGAATTCATGGCTAAGAGTTCCTTCAA-3’ and the reverse primer 5’-ATCTAGATCCGGTGGATCCATCCAAAAGTGTTCTCTCCAC-3’ (40 cycles of 95 °C for 15 s, 55 °C for 15 s, and 72 °C for 30 s).
Note: PCR primers should be designed to contain at least 20 bp overlapping sequences (underlined) to a linearized cloning pEGAD vector (see Figure 1A).
Cloning the AtATG8a gene into the pEGAD vector: Linearize the pEGAD vector (NCBI accession No. AF218816) with the restriction enzymes EcoRI and BamHI at 37 °C for 4 h, and then purify with the HiPure Gel DNA Mini Kit (Magen, D2111-03). Assemble the linearized pEGAD vector and the amplified AtATG8a fragment using the ClonExpress® II One-Step Cloning Kit following the manufacturer’s instructions (Vazyme Biotech Co., C112-01). Construct the vector containing protein of interest (POI, pEGAD-POI-mCherry) using a similar method (Figure 1C).
Note: For each POI, two constructs should be designed, with one containing a fluorescent protein at its N−terminus, and the other at the C−terminus. Some general guidelines for creating fluorescent fused protein in plants can be found in Tanz et al. (2013).
E. coli transformation: Mix the 10 μL of the above reaction solution with 100 μL E. coli DH5α competent cells and incubate on ice for 30 min. Heat the cells in a 37 °C water bath for 90 s and incubate on ice for 1–2 min. Add 700 μL of LB to the cells and shake at 37 °C, 200 rpm for 1 h for recovery. Centrifuge at 5,000 rpm for 3 min, then discard 600 μL of supernatant and resuspend the pellet in the remaining supernatant. Spread on an LB plate containing 50 µg/mL of kanamycin and incubate for 12–14 h at 37 °C. Perform colony PCR to identify positive clones and verify by Sanger sequencing with primer: 5’-AATCATCGCAAGACCGGCAACAGGAT-3’.
Agrobacterium transformation: Mix 1 µg of verified plasmid with 200 μL GV3101 competent cells and incubate on ice for 30 min. Freeze the cells with liquid nitrogen for 1–2 min and then thaw by incubating in a 37 °C water bath for 2 min. Add 1 mL of LB to the cells and shake at 28 °C, 200 rpm for 4 h for recovery. Centrifuge at 7,000 rpm for 1 min, discard 1 mL of supernatant, and resuspend the pellet in the remaining supernatant. Spread the cells on LB plates containing appropriate antibiotics and incubate at 28 °C for 2 days for colony formation.
Figure 1. Schematic diagram of the vector constructs used in ATG8 colocalization assay in N. benthamiana leaves. (A) Construction of pEGAD-GFP-ATG8a vector using one-step cloning method. (B) and (C) are the schematic diagrams of pEGAD-GFP-ATG8a and pEGAD-POI-mCherry vectors, respectively. Promoters, terminators, and open reading frames are indicated in the maps. 35S: Cauliflower mosaic virus 35S promoter; BlpR: Basta resistance gene; IS1: insertion sequence; KanR: Kanamycin resistance gene; LB: left border; NOS: NOS terminator; oriV: origin of replication; POI, protein of interest. RB: right border; TetR: repressor of the tetracycline resistance element; trfA: replication initiator protein; traJ: Positive regulator of the F plasmid transfer (tra) operon.
Agrobacterium-mediated transient gene expression in tobacco leaf
Pick up a single A. tumefaciens colony for each construct and inoculate into 15 mL of LB liquid medium containing appropriate antibiotics (50 μg/mL of kanamycin, 50 μg/mL of rifampicin, 10 μg/mL of gentamycin) in a 50 mL mini bioreactor tube. Shake at 200 rpm, 28 °C for 16–24 h until OD600 = 0.8–1.5.
Harvest the cells by centrifugation at 6,000 rpm, 4 °C, for 10 min. Resuspend the cells with fresh suspension buffer (see Recipes) to a final concentration of OD600 = 1.2 and keep at 25 °C for more than 4 h before infiltration (Figure 2A).
Note: As a common practice, acetosyringone is added into bacterial cultures to activate Agrobacterium virulence. The optimal acetosyringone (150 µM) treatment usually requires at least 4 h.
Mix equal volumes of the cells containing the pEGAD-GFP-ATG8a and pEGAD-POI-mCherry or negative control pEGAD-mCherry constructs, and infiltrate on the abaxial side of the tobacco leaf using a 1 mL needleless syringe. Each half of the leaf is infiltrated with about 100 μL of bacterial mixture (Figure 2B), and the infiltrated areas are labeled with a marker pen (Figure 2C).
Note: Infiltrate tobacco leaf carefully to avoid damaging leaf.
Keep the infiltrated tobacco seedlings in a growth chamber at 28 °C under 16/8 h light/dark for 24–36 h.
Concanamycin A (ConA) infiltration
Excise a small leaf disc close to the site of infiltration and examine the expression of GFP or mCherry-tagged proteins in a fluorescence microscope.
Infiltrate diluted ConA solution (1 μM) with 1 mL needleless syringe over the marked leaf areas (Figure 2D). Cut the leaves when ConA solution is almost absorbed (usually takes about 15 min, Figure 2E).
Note: ConA is a specific inhibitor of vacuolar-type ATPases and is often used to stabilize the autophagic bodies (Dröse et al., 1993; Dettmer et al., 2006). The diluted ConA solution must be prepared freshly before use by adding 998 μL fresh suspension buffer to 2 μL ConA stock solution (0.5 mM). Moreover, it is important to use a different injection site for ConA infiltration.
Remove the midvein of detached leaves and place into Petri dishes containing two layers of filter paper pre-wetted with MS liquid medium without sugar (MS-C medium, see Recipes) (Figure 2F). Cover the leaves with one more layer of pre-wetted filter paper and gently press against the leaves to keep them wet (Figure 2G).
Note: Carbon starvation is a common approach for autophagy induction. To do so, MS-C liquid medium is used here, and ConA-infiltrated leaves are cut and placed in the dark. Moreover, add about 1.5 mL of MS-C medium to wet filter paper. Too much water will cause cell death in the leaves.
Cover the Petri dishes with aluminum foil and keep in a growth chamber at 28 °C for 36 h. (Figure 2H).
Figure 2. Illustration of the experimental procedure. (A) Resuspend bacterial solution; (B) Infiltrate bacterial mixture; (C) Mark infiltrated leaf areas; (D) Infiltrate ConA solution; (E) Detach infiltrated leaves; (F) Place detached leaf on pre-wetted filter paper; (G) Cover leaf with one more layer of pre-wetted filter paper; (H) Wrap Petri dish with aluminum foil.
Fluorescence Confocal Microscopy Imaging
Cut four leaf squares (0.5 × 0.5 cm) surrounding the infiltrated sites and mount in ddH2O water.
Examine the adaxial epidermal cells to visualize the subcellular localization of GFP-ATG8a and POI-mCherry with a Zeiss LSM 800 laser scanning confocal microscope (Carl Zeiss, https://www.zeiss.com).
Setup of confocal microscope: for GFP, excitation at 488 nm with an Argon laser and emission detection at 505-550 nm; For mCherry, excitation at 543 nm with an HeNe and emission detection at 585-615 nm. Use a laser strength of 4% and a pinhole of 1 airy unit for both fluorescence proteins.
Data analysis
As shown in Figure 3, numerous puncta decorated by autophagy marker GFP-ATG8a were readily detected in the vacuole when treated with ConA, a specific inhibitor of vacuolar-type ATPases (Dröse et al., 1993; Dettmer et al., 2006). Moreover, POI-mCherry labeled puncta accumulated in the vacuole, colocalizing with GFP-ATG8a upon ConA treatment, indicating the association of POI with autophagic vesicles. In contrast, no mCherry labeled puncta were detected in the vacuole regardless of ConA treatment. The colocalization assay with GFP-ATG8 based on the tobacco transient expression system shown here could be used for the identification of ATG components or autophagic cargoes, together with other approaches such as protein–protein interaction assays and ATG8 lipidation assay.
Figure 3. Representative confocal images showing the subcellular localization of POI-mCherry and GFP-ATG8a. N. benthamiana leaf epidermal cells were co-infiltrated with mCherry (A) or POI-mCherry (B) and GFP-ATG8a, and then analyzed with confocal microscopy 24 h after agroinfiltration followed by a 36-h incubation with 1 μM ConA or DMSO treatment (–ConA). AB: autophagic body; scale bar = 10 μm.
Recipes
Bacterial suspension buffer (must be freshly prepared before use)
10 mM MgCl2
100 µM Acetosyringone
10 mM MES (adjusted with 1 M KOH to pH = 5.8)
In ddH2O
ConA stock solution (0.5 mM)
Prepare stock solution by adding 230.9 μL DMSO to 100 µg ConA. Dispense the solution into 50 μL aliquots and store them at -20 °C or below.
MS-C liquid medium
4.3 g MS basal salt mixture
2 µM MES monohydrate
In 1 L ddH2O (adjusted with 1 M KOH to pH = 5.7)
Acknowledgments
This work was supported by grants from the Natural Science Foundation of Guangdong Province (Grant 2022A1515011483) and South China Agricultural University Students’ Innovation and Entrepreneurship Training program (202110564052) to NL, and the National Natural Science Foundation of China (Grant 31970307) to FL and (Grant 31401906) to NL. The original paper in which this protocol was used is Luo et al. (2021; doi.org/10.1101/2021.06.11.448008).
Competing interests
The authors declare no conflicts of interest.
References
Dettmer, J., Hong-Hermesdorf, A., Stierhof, Y. and Schumacher, K. (2006). Vacuolar H+-ATPase activity is required for endocytic and secretory trafficking in Arabidopsis. Plant Cell 18(3): 715-730.
Dröse, S., Bindseil, K. U., Bowman, E. J., Siebers, A., Zeeck, A. and Altendorf, K. (1993). Inhibitory effect of modified bafilomycins and concanamycins on P- and V-type adenosinetriphosphatases. Biochemistry 32(15): 3902-3906.
Luo, N., Shang, D., Tang, Z., Huang, X., Tao, L.-Z., Liu, L., Gao, C., Qian, Y., Xie, Q. and Li, F. (2021). Engineered Aim-based selective autophagy to degrade proteins and organelles. 2021.2006.2011.448008.
Marshall, R. S. and Vierstra, R. D. (2018). Autophagy: the master of bulk and selective recycling. Annu Rev Plant Biol 29(69): 173-208.
Suttangkakul, A., Li, F., Chung, T. and Vierstra, R. D. (2011). The ATG1/ATG13 protein kinase complex is both a regulator and a target of autophagic recycling in Arabidopsis. Plant Cell 23: 3761-3779.
Tanz, S. K., Castleden, I., Small, I. D. and Millar, A. H. (2013). Fluorescent protein tagging as a tool to define the subcellular distribution of proteins in plants. Front Plant Sci 4: 214.
Zhuang, X., Wang, H., Lam, S. K., Gao, C., Wang, X., Cai, Y. and Jiang, L. (2013). A BAR-domain protein SH3P2, which binds to phosphatidylinositol 3-phosphate and ATG8, regulates autophagosome formation in Arabidopsis. Plant Cell 25(11): 4596-4615.
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
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Plant Science > Plant cell biology > Cell imaging
Cell Biology > Cell imaging > Fluorescence
Molecular Biology > Protein > Protein-protein interaction
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Assay to Study the Phase-transition Behavior of Edc3, a Conserved Processing Body (P-body) Marker Protein
RR Raju Roy
PR Purusharth I. Rajyaguru
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4487 Views: 1729
Reviewed by: Julie WeidnerIndranil MalikAnu P. Minhas
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Original Research Article:
The authors used this protocol in Nature Communications Apr 2022
Abstract
RNA granules are conserved, non-membranous, biphasic structures predominantly composed of RNA and RNA-binding proteins. RNA granules often assemble as a result of cellular responses to a variety of stresses, including infection. Two types of RNA granules are best characterized: stress granules (SGs) and processing bodies (P-bodies). The mechanism of RNA granule assembly and disassembly is still understudied because of its complex composition and dynamic behavior. The assembly of RNA granules is driven by a process known as phase separation of granule components. Edc3 is a conserved decapping activator and an essential P-body component in Saccharomyces cerevisiae. Phase separation of P-body proteins has been poorly explored. This protocol will enable the visualization of the phase transition behavior of Edc3, since it is tagged to mCherry. It further describes using small molecules and other proteins to study P-body dynamics. In addition to the assembly of Edc3, this assay also lays the foundation to study disassembly of phase-separated assemblies in vitro, which was not explored earlier. We have devised the assay to describe the use of one such protein that acts as a disassembly factor. Overall, this protocol is simple to perform and can potentially be combined with analyzing these assemblies using other approaches.
Graphical abstract:
Keywords: Phase separation RNA granule Stress granule P-bodies Messenger ribonucleoprotein RNA binding proteins
Background
RNA granules are mRNA-protein complexes that function as sites of mRNA storage and/or degradation (Anderson and Kedersha, 2006). Cytoplasmic RNA granules are also known as higher-order messenger ribonucleoprotein (mRNP) complexes (Anderson and Kedersha, 2009). RNA granules are dynamic and can exchange mRNP components with their surroundings (Bhattacharyya et al., 2006; Wheeler et al., 2016). RNA granules are also insoluble in lysates, non-membranous cytoplasmic complexes, or foci containing translationally repressed and/or degrading mRNAs. They are found in various cells, including, but not limited to yeast, germ cells, embryos, and neurons, often in response to stress (Thomas et al., 2011; Wheeler et al., 2016). Upon release from RNA granules, the mRNAs can return back to translation. Thus, RNA granules could be mRNA fate-determining sites (Mitchell and Parker, 2014). RNA granules share certain similarities across species (Anderson and Kedersha, 2006), suggesting that they are conserved and share mechanisms of granule formation and regulation of mRNA fate (Zlotorynski, 2015). Stress granules and P-bodies are two important types of cytoplasmic RNA granules that are majorly studied in the field of RNA granule biology. Stress granules (SGs) assemble in the cytoplasm upon stress and are known to harbor translationally repressed mRNAs (Buchan et al., 2011; Rajyaguru et al., 2012). On the other hand, processing bodies (P-bodies) are visible even in the absence of stress but grow in size and intensity in response to stress (Buchan et al., 2011).
Previous reports suggested an important role of intrinsically disordered regions (IDRs) during the assembly of RNA granules (Figure 1A), which has been extensively studied (Jonas and Izaurralde, 2013; Protter et al., 2018). IDRs are specific amino acid sequences or repeats in a protein that do not fold into a secondary structure. The RGG-repeats (arginine-glycine-glycine repeats), a well-studied IDR, play an essential role in RNA granule assembly and translation repression (Rajyaguru et al., 2012; Poornima et al., 2016; Brandariz-Núñez et al., 2018; Ozdilek et al., 2017; Bhatter et al., 2019). Single-stranded nucleic acid-binding protein 1 (Sbp1) contains N-terminal RRM1, C-terminus RRM2, and an RGG-motif sandwiched between the RRM domains (Bhatter et al., 2019). Previous reports suggest the RGG-motif of Sbp1 is essential for binding to the translation initiation factor eIF4G and repressing translation (Rajyaguru et al., 2012; Bhatter et al., 2019). Sbp1 orchestrates P-body disassembly with the help of its RGG-motif (Roy et al., 2022) (Figure 1B).
Several recent reports have found that RNA binding proteins (RBPs), such as G3BP1, PABP1, Tau, FUS, TDP-43, α-synuclein, and hnRNPs, can undergo liquid-liquid phase separation (LLPS). LLPS is a process in which proteins and nucleic acids in cells transition from a liquid phase to a condensed state resembling a liquid droplet (Figure 1A). In neurodegeneration, mutations in RBPs led to aberrant cytoplasmic localization. This mislocalization could result in protein transition to a gel or solid phase (irreversible state) rather than the liquid condensate formation (reversible state) in the cell cytoplasm, promoting aggregation and fibril assembly (Couthouis et al., 2011; Lin et al., 2015; Wheeler et al., 2016). Persistent aggregation and fibril assembly of these RBPs in the cytoplasm can be toxic and lethal for cell survival, as reported in the context of certain neurodegenerative disorders, such as ALS and FTD (Sun et al., 2011; Brunello et al., 2016). Recently, α-synuclein has been found to modulate P-body dynamics by physically binding to decapping factors, disrupting P-body composition, and altering mRNA decay dynamics. Binding of α-synuclein to P-body components alters the dynamics of P-bodies, which act as feedback for α-synuclein aggregates in the cytoplasm (Hallacli et al., 2022).
There are few reports suggesting RBPs undergo phase separation, which is involved in the formation of RNA granules, such as stress granules (Mugler et al., 2016; Riback et al., 2017). Here, we report an extended assay that describes phase separation of Edc3, a conserved P-body marker protein. Unlike stress granules, proteins involved in decapping and degradation of mRNA are found to localize within the P-bodies, therefore believed to be the hub for mRNA decay (Buchan et al., 2011; Mitchell et al., 2013) (Figure 1A). Edc3 is a P-body resident protein and plays an important role in the formation and maintenance of P-bodies. Edc3 contains a C-terminal YjeF-N motif, which can self-interact, thereby contributing to P-body assembly (Decker et al., 2007) (Figure 1A). Deletion of Edc3 leads to poor P-body formation (Decker et al., 2007). Edc3 interacts with RPS28B mRNA, and this interaction has recently been reported to be important for efficient P-body formation (Fernandes and Buchan, 2020). To sum up, Edc3 self-association and interaction with P-body resident proteins and RNAs contribute to higher-order P-body assemblies. Like any conventional RNA granules, P-bodies are very dynamic and shuttle protein-RNA components in and out of the granules (Aizer et al., 2008). This dynamic nature of P-bodies makes them very difficult to study. Therefore, to study the dynamics of P-bodies, we need to develop an in vitro assay system, which must be in accordance with RNA granule studies and can easily be performed in the laboratory. In this protocol, we discuss a multi-component assay system that can be used to study P-body dynamics (assembly and disassembly) in vitro.
Figure 1. Illustrations depicting assembly and disassembly of processing bodies (P-bodies). (A) Self-association of Edc3, recruitment of other P-body resident proteins, along with the association of mRNA and co-factor like NADH, facilitates phase transition of Edc3 leading to P-body assembly. (B) During recovery, Sbp1, with the help of its RGG-motif (IDR), binds to the YjeF-N domain of Edc3, disrupting the self-association and leading to P-body disassembly.
Development of the protocol
This protocol has been developed to understand the phase separation behavior of Edc3-mCherry in vitro (Roy et al., 2022) (Figure 2). Edc3 is a conserved core P-body protein, which is important for forming and maintaining P-bodies. The study of Edc3 assemblies in vitro is key to understanding the process of Edc3 phase separation in vivo and its regulation. Using this protocol, we observe that after 1 h of incubation, purified Edc3-mCherry can form small assemblies in phase separation buffer (PSB) (Figure 3D), which grow in size and intensity in the presence of RNA or NADH (Figure 3E–F), compared to 0 h (Figure 3A–C). We have extended this assay to analyze the impact of a purified disassembly factor on Edc3 assemblies. We found that adding purified Sbp1 to Edc3-mCherry assemblies leads to its dissociation (Figure 4A–B). Overall, this assay provided two important results: a) RNA and NADH promote the formation of Edc3 assemblies, and b) Sbp1 leads to the dissolution of Edc3 assemblies.
Figure 2. Illustration depicting the protocol steps to study the phase separation of Edc3 in vitro. (A) Phase separation behavior of Edc3. (B) Disassembly of phase-separated Edc3.
Applications of the method
This method can be optimized to perform high-throughput screening to identify small molecules that can perturb assembly and/or disassembly of P-bodies. Such small molecules could also be tested for their ability to perturb the aggregates of proteins implicated in neurodegenerative disorders. mRNAs with specific sequences and structures can be tested for their role in promoting Edc3 assembly or disassembly. Furthermore, purified proteins can be added to the assay system to identify factors affecting the assembly and/or disassembly of higher-order Edc3 structures.
Comparison with other methods
Most phase-separation studies use a buffer containing crowding reagents, like BSA, PEG, or glycerol (Lin et al., 2015; Mugler et al., 2016), to reduce the surface area of the reaction in the buffer system. We have standardized this assay such that it does not contain reagents that may directly or indirectly affect protein stability, structure, or function. Also, we wanted an efficient buffer condition for studying both the assembly and disassembly of Edc3 in vitro. We narrowed it down to KCl, HEPES-KOH, and MgCl2, suitable for the Edc3-mCherry assembly and disassembly experiments without compromising protein stability.
Figure 3. Phase separation of Edc3-mCherry in the presence of RNA and NADH. (A) Phase separation of Edc3-mCherry alone at 0 h. (B) Phase separation of Edc3-mCherry in the presence of RNA, (C) or NADH at 0 h. (D) Phase separation of Edc3-mCherry alone after 1 h. (E) Phase separation of Edc3-mCherry in the presence of RNA, (F) or NADH after 1 h at 30 °C. The scale bar represents 5 µm.
Expertise needed to implement the protocol
This protocol has been standardized so that it can be performed by any researcher with a basic knowledge of Biochemistry, protein chemistry, and wide-field fluorescence microscopy.
Limitations
RNA granules contain a variety of RNA binding proteins with different physical properties. Most of the granule residing proteins contain intrinsically disordered regions in different proportions. IDR plays a vital role in the phase separation of granule resident proteins. Therefore, it is unlikely that all IDR-containing proteins will phase-separate under similar conditions. This protocol is designed and standardized for phase separation of Edc3-mCherry in vitro. However, tweaking this protocol may also be useful for studying the phase separation of other RNA-binding proteins.
Figure 4. Disassembly of phase-separated Edc3. (A) Disassembly of phase-separated Edc3+RNA assemblies in the presence of either PSB, Sbp1, Sbp1ΔRGG, or BSA. (B) Disassembly of phase-separated Edc3+NADH assemblies in the presence of either PSB buffer, Sbp1, Sbp1ΔRGG, or BSA. The scale bar represents 5 µm.
Materials and Reagents
1.5 mL microcentrifuge tube (Axygen, catalog number: MCT-150-C)
Frosted microscope slides (Bluestar, 75 mm × 25 mm, 1.35 mm thickness)
Microscope cover glasses (Bluestar, Square 22 mm, 0.13 mm to 0.16 mm thickness)
Microcentrifuge tube holder (VWR, catalog number: 211-0207)
Purified proteins- Edc3-mCherry, Sbp1, Sbp1ΔRGG (Figure 5A) are stored at -80 °C with 10% glycerol in dialysis buffer (Roy et al., 2021). Purified proteins must be kept in aliquots at -20 °C (maximum three days as these proteins are prone to precipitation) or -80 °C (for long-term use, ≥ one week), DO NOT freeze-thaw the proteins more than two times; this might affect protein stability.
Total RNA isolated from Saccharomyces cerevisiae (Figure 5B) using the hot phenol method (store the RNA at -20 °C for short-term and -80 °C for long-term) (Garg et al., 2020).
Bovine Serum Albumin (BSA; Sigma, catalog number: A4503-100G) is stored at 4 °C.
Potassium chloride (KCl; Sigma, catalog number: P9541-1KG) is stored at room temperature.
N-(2-Hydroxyethyl) Piperazine N-(2-Ethane Sulphonic Acid) [HEPES buffer; SRL, catalog number: 16826] is stored at 4 °C.
Magnesium chloride (MgCl2; Sigma, catalog number: M0250-1KG) is stored at room temperature.
Potassium hydroxide (KOH; Sigma, catalog number: V800320-500G) is stored at room temperature.
Diethyl pyrocarbonate (DEPC; SRL, catalog number: 46791) is stored at 4 °C.
Figure 5. Purified proteins and total RNA used in this assay. (A) Purified Edc3-mCherry, only-mCherry, Sbp1, and Sbp1ΔRGG, used for the phase separation and disassembly experiments. * Represents a degradation product of Edc3-mCherry. (B) 0.8% Formamide agarose gel electrophoresis depicting the quality of total RNA isolated from S. cerevisiae cells. Bands represent 25S rRNA, 18S rRNA, and small RNA species, respectively.
β-Nicotinamide adenine dinucleotide, reduced disodium salt hydrate (NADH; Sigma, catalog number: N8129-100MG) is stored at -20 °C.
Immersion oil 1.516 NA (Cargille, catalog number: 20130)
Lint-free tissue paper (Kimwipes, Kimtech, catalog number: 34155)
500 mM KCl (For reagent preparation, see Recipes) should be stored at 4 °C.
150 mM HEPES-KOH, pH 7.4 (For buffer preparation, see Recipes), should be stored at 4 °C.
100 mM MgCl2 (For reagent preparation, see Recipes), should be stored at 4 °C.
0.2 mM NADH (For reagent preparation, see Recipes), aliquot, and store at -80 °C. NADH is prone to degradation; therefore, it is important to aliquot 1mM NADH in nuclease-free water and store it at -80 °C.
DEPC treated H2O/Nuclease-free H2O (For reagent preparation, see Recipes), store at room temperature.
Phase Separation Buffer (PSB; For buffer preparation, see Recipes) must be prepared on ice. All the reaction steps must be done on ice (or 4 °C), and after reaction setup, transfer it to respective temperatures.
Absolute ethanol (EMSURE®, Merck, catalog number: 100983)
70% ethanol (see Recipes)
DEPC treated water (see Recipes)
500 mM Potassium Chloride (KCl) (see Recipes)
150 mM HEPES-KOH buffer, pH 7.4 (see Recipes)
100 mM Magnesium chloride (MgCl2) (see Recipes)
Phase separation buffer (PSB) (see Recipes)
Notes:
Store all the buffers at 4–8 °C. DO NOT store them at room temperature.
Wash the coverslips and glass slides with ethanol and dry them using lint-free tissue paper. Dust can hinder visualizing the phase-separated proteins.
Alternative to DEPC-treated water or solutions, commercially available RNase-free reagents can also be used for the assay.
70% ethanol is used to wash or clean the equipment. Alternatively, decontaminating agents like RNaseZap could also be used.
Equipment
Autoclavable pipettes (1–10 µL, 2–20 µL, 20–200 µL; Finpipette,Thermo Fisher Scientific, catalog number: 4701070). Clean the pipette using 70% ethanol before proceeding with the assay.
Autoclaved DNase, RNase, pyrogen-free micro tips (Axygen, catalog numbers: T-300; T-200-Y)
70% ethanol wiped scissors for cutting tip nose
30 °C incubator/heat block (Shalom, catalog number: SLM-INC-270)
Vortex Mixer (Neuation, catalog number: VM-2110)
Eppendorf® Centrifuge 5424R (Eppendorf, catalog number: EP5404000537)
DeltavisionTM Elite Microscope (GE Healthcare) with 100× objective
Software
softWoRx 6.1.3 software for image acquisition (Applied Precision, LLC)
Fiji ImageJ Version 1.53f51 for image processing (Open source, https://imagej.net/software/fiji/downloads)
Microsoft Excel (Microsoft Corporation, USA)
GraphPad Prism 4 for data analysis (GraphPad Software Inc., https://www.graphpad.com/)
Procedure
Preparation of the phase separation experiment (15–20 min)
Thaw all the proteins and reagents on ice before proceeding with the experiment.
Keep the incubator/dry bath at 30 °C.
Pre-cool the microcentrifuge tubes by embedding them into ice before proceeding with the experiment.
Clean the workbench with 70% ethanol (alternative: use decontaminating agents like RNaseZap) before proceeding, as phase separation requires RNA, which might degrade because of RNase contamination or impurities.
Prepare LLPS buffer for a reaction mixture of 120 µL total volume, as shown in Table 1 (10 min):
Reaction I: Edc3-mCherry + PSB
Reaction II: Edc3-mCherry + 1 µg RNA + PSB
Reaction III: Edc3-mCherry + 0.2 mM NADH + PSB
Table 1. Reactions for phase separation experiment.
Reagent Reaction I
(final conc.)
Reaction I
(final conc.)
Reaction III
(final conc.)
500 mM KCl 150 mM 150 mM 150 mM
150 mM HEPES-KOH, pH 7.4 30 mM 30 mM 30 mM
100 mM MgCl2 2 mM 2 mM 2 mM
1mM NADH n/a n/a 0.2 mM
Total RNA n/a 1µg n/a
Edc3-mCherry 10 µM 10 µM 10 µM
Nuclease free H2O Adjust volume to 120 µL Adjust volume to 120 µL Adjust volume to 120 µL
Phase separation reaction (Figure 3) (1 h 20 min)
Prepare the reaction mixtures as indicated in step A5, and keep them ready on ice.
Incubate the reaction mixtures at 30 °C for 1 h without disturbing the reaction tubes.
Take out the reaction mixtures, and gently vortex (or tap) the microcentrifuge tube to mix the phase-separated proteins.
Aliquot 30 µL ×3 reactions to 1.5-mL microcentrifuge tubes using a 200-µL tip with a cut (at 3–5 mm at the nozzle), and place the reactions on ice. Cutting the tip at the nozzle is critical, as it might affect the size of the phase-separated protein due to suction pressure or size restriction at its nozzle.
Prepare and execute the reactions from step B4 for the disassembly experiment (steps C1–C3).
Immediately carry forward the remaining reaction from step B3 for processing and visualization (steps D1–E6) to confirm the assembly. The processing and visualization of the phase separation reactions are discussed in steps D1–E6.
Reaction for disassembly experiment (Figure 4) (1 h 20 min)
Add 10 µM of purified Sbp1 or Sbp1ΔRGG or Bovine Serum Albumin (Figure 3) to the respective reactions from step B4. Mix the reaction by tapping or gentle vortexing.
Incubate the reaction mixtures at 30 °C for 1 h without perturbing the microcentrifuge stand or the reaction tubes.
Keep the reaction on ice after incubation for post-incubation processing (steps D1–D3).
Post incubation processing of the reactions (5 min)
Spin the reactions at 200 × g for 2 min.
Gently take out 20 µL of the reaction using a 200 µL tip cut at its nozzle to discard as we will not be working with the supernatant.
Keep the remaining reaction from step D2 on ice for visualization under the microscope (steps E1–E6).
Visualizing the phase-separated protein under the microscope (7 min–15 min)
Remove 5 µL of the reaction from the reaction leftover, and place it on a coverslip forming a droplet
Note: Place the coverslip on a lint-free tissue paper to avoid capturing unwanted particles from the bench.
Place the glass slide on the coverslip. Fix the glass slide to the coverslip by gently putting pressure on the glass slide from the top using your thumb. Make sure the reaction gets evenly diffused between the slide and coverslip.
Pipette 2 µL of 1.516 NA immersion oil onto the coverslip.
Mount the slide on the microscope.
Turn the mCherry filter on (excitation: 587 λ; emission: 610 λ) and gently use the fine focusing of the microscope to focus on the assemblies. This step is time-sensitive, as the assemblies from step B6 might grow larger in size when kept at RT for a prolonged period. The imaging time should not exceed more than 7 min. It would take some time to practice focusing on the assemblies, as they are not very clearly visible in white light. We suggest performing a few mock experiments before proceeding with the main experiment. We also recommend setting up initial reactions in a staggered manner, to get enough time for visualizing each reaction.
The assemblies appear as depicted in Figure 3.
Data analysis
Quantitation of the phase-separated assemblies using Fiji ImageJ (Figure 6A–C).
For efficient analysis of phase-separated assembly, capture all images at the same magnification with a similar contrast setting.
Open Fiji ImageJ software, which can be downloaded from https://imagej.net/software/fiji/downloads.
In Fiji, use the menu to open an image (Figure 6D).
Select analyze, then set scale. The scale should be set by default in Fiji using the metadata; if not, enter the distance in pixels using the specifications provided by the microscope or the software. Enter the units (µm or nm). In this case, we used micrometers. Check global so that this measurement is applied to all images with the same magnification (Figure 6E).
Click on the image and duplicate the image by clicking image menu on the toolbar, then duplicate from the option.
Change the image to an 8-bit image by clicking image, then type, 8-bit (Figure 6F).
Under the image menu, select adjust, then threshold (Figure 6G).
Adjust the threshold by sliding the bars so that only the assemblies required to analyze are selected. Then provide the lower threshold and upper threshold value using the set option. Here, we used a lower threshold value of 61 and an upper threshold of 255. Keep it constant throughout the analysis (Figure 6H–I).
Under the analyze tab, select set measurements and check the measurements sufficient for data analysis (Figure 6J).
Then click on analyze and select analyze particles. Check the display results and other settings required for the data analysis. Set a minimum particle size here, so that noise is not included in the data. Then click ok (Figure 6K).
Measurements will show in a chart (Figure 6L). Copy and paste these measurements into excel to analyze the data, then create graphs using GraphPad Prism (Figure 6A–C).
Figure 6. Quantitation of phase-separated assemblies. (A) Quantitation of phase-separated assemblies depicted in Figure 3. (B) Quantitation of disassembly experiment depicted in Figure 4A. (C) Quantitation of disassembly experiment depicted in Figure 4B. (D) Menu bar of Fiji software. (E) Setting up the scale of the acquired image in Fiji. (F) Changing the bit size of the image before proceeding for analysis. (G) Adjusting the threshold for the assemblies. (H–I) Setting the threshold for the assemblies to analyze. (J) Set the kinds of measurements expected from the software. (K) Analyze particle size using the analyze particle option. (L) Copy and paste the data from the results window to the excel sheet for analysis. Data plots in Figure 4A–C represent mean ± SEM from n = 3, where ‘n’ represents the number of independent experiments. A two-tailed paired student t-test was used to calculate P-values.
Notes
Troubleshooting
Use the troubleshooting solutions in Table 2.
Table 2. Troubleshooting table
Problem Possible reason Solution
1 A large aggregation of protein under the microscope The concentration of protein might be high. Before starting the experiment, try out different concentrations of proteins for phase separation.
Protein might be aggregated before incubation in the PSB buffer, while being purified. Centrifuge the purified protein at 15,000 × g for 10 min, collect the supernatant, quantify protein concentration, and use this for the phase separation experiment.
2 No phase-separated proteins were found under the microscope Different RNA binding proteins require a particular substrate, co-factor, etc., for phase separation. Although some proteins phase-separate alone, the presence of RNA/DNA, NADH, or ATP might increase or decrease its ability of phase separation. Try out the phase-separation of protein without any substrate with different concentrations of proteins at different time points.
Try out co-factors like ATP, GTP, etc., or RNA substrates like poly(A) or poly (U), as reported earlier, to help the proteins phase separate.
RNA and NADH might degrade due to some contamination in the reaction mixture. Try setting up the reaction in a clean and RNase-free environment.
Check the pH and concentration of the buffer, as a change in these might lead to less or low phase-separation of proteins.
3 Aggregation of proteins during purification Proteins containing low-complexity regions tend to aggregate during purification. Use the L-arginine-containing lysis buffer to purify proteins (Roy et al., 2022).
4 Presence of air bubbles within the glass slide-coverslip junction Inadequate diffusion of reaction throughout the coverslip or the glass slide was pressed too hard onto the coverslip. Try gently placing the glass slide onto the coverslip and allowing the reaction liquid to diffuse throughout the coverslip first. Then, gently press the glass slide by rolling the thumb from one side to the other.
5 High noise signal while visualizing the phase-separated protein under the microscope. Dust or dirt present in the glass slide or coverslip
Try cleaning the coverslip and the glass slide by first dipping it in 100% ethanol and drying it out using lint-free tissue paper.
Using ordinary tissue paper could be problematic because the free-flowing lint might emit an unwanted signal.
Recipes
70% ethanol
Prepare 100 mL of 70% ethanol by adding 30 mL of autoclaved H2O to 70 mL of absolute ethanol. Store it in a glass reagent bottle at room temperature.
DEPC treated water
Add 2 mL of DEPC (Diethyl pyrocarbonate) to 2 L of MilliQ water in the fume hood. Post addition of DEPC, store the container in a dark area overnight, and then autoclave.
500 mM Potassium Chloride (KCl)
Prepare 500 mM KCl solution by adding 3.73 g of KCl in 100 mL of autoclaved DEPC treated MilliQ water. Stir with a glass rod until all the salt dissolves. Store at 4 °C after preparation.
150 mM HEPES-KOH buffer, pH 7.4
Prepare 150 mM HEPES solution by adding 3.57 g of HEPES salt in 100 mL of autoclaved DEPC treated MilliQ water. Stir with a glass rod until all the salt dissolves. Adjust the pH of the solution to 7.4 by dropwise adding 1 M potassium hydroxide (KOH) solution using a glass pipette. Store at 4 °C after preparation.
100 mM Magnesium chloride (MgCl2)
Prepare 100 mM MgCl2 solution by adding 0.95 g of MgCl2 salt to 100 mL of autoclaved DEPC treated MilliQ water. Stir with a glass rod until all the salt dissolves. Store at 4 °C after preparation.
Phase separation buffer (PSB)
Prepare the phase separation buffer according to the final volume of the reaction mixture. The final concentrations of the component buffers are as follows:
Reagent Final concentration Volume
500 mM KCl 150 mM 36 µL
150 mM HEPES-KOH, pH 7.4 30 mM 24 µL
100 mM MgCl2 2 mM 2.4 µL
Reaction volume n/a 120 µL
After adding PSB components, add the required amount of purified protein or RNA into the reactions separately (Table 1), and make up the volume to 120 µL using autoclaved DEPC treated MilliQ water.
Acknowledgments
We acknowledge support from the DBT/Wellcome Trust India Alliance Fellowship/Grant [IA/I/12/2/500625] and DBT India grant [BT/PR40106/BRB/10/1918/2020]. We also thank the DBT-IISc partnership program and DST-FIST program for infrastructure support. DBT-JRF for fellowship to RR. This protocol was previously used to understand the mechanism of disassembly by Sbp1 in the article titled “Low complexity RGG motif sequence is required for Processing body (P-body) disassembly.” We thank Amrendra Kumar for helping us troubleshoot the purification of Edc3-mCherry protein. We thank Rajyaguru lab members for their constant input, support, and encouragement.
Competing interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Ethics
The authors declare no conflict with respect to ethical grounds.
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Co-differentiation and Co-maturation of Human Cardio-pulmonary Progenitors and Micro-Tissues from Human Induced Pluripotent Stem Cells
WN Wai Hoe Ng
BV Barbie Varghese
XR Xi Ren
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4488 Views: 1972
Reviewed by: Gal HaimovichFarah HaqueSrinidhi Rao Sripathy Rao
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Original Research Article:
The authors used this protocol in eLIFE Jan 2022
Abstract
Currently, there are several in vitro protocols that focus on directing human induced pluripotent stem cell (hiPSC) differentiation into either the cardiac or pulmonary lineage. However, these systemsprotocols are unable to recapitulate the critical exchange of signals and cells between the heart and lungs during early development. To address this gap, here we describe a protocol to co-differentiate cardiac and pulmonary progenitors within a single hiPSC culture by temporal specific modulation of Wnt and Nodal signaling. Subsequently, human cardio-pulmonary micro-tissues (μTs) can be generated by culturing the co-induced cardiac and pulmonary progenitors in 3D suspension culture. Anticipated results include expedited alveolarization in the presence of cardiac cells, and segregation of the cardiac and pulmonary μTs in the absence of exogenous Wnt signaling. This protocol can be used to model cardiac and pulmonary co-development, with potential applications in drug testing, and as a platform for expediting the maturation of pulmonary cells for lung tissue engineering.
Keywords: Cardio-pulmonary Co-differentiation Micro-tissues Alveolarization Segregation
Background
From embryogenesis to adulthood, the heart and lungs are always located in close proximity to each other. This suggests the presence of inter-organ communication that influences their respective developmental programs (Hoffmann et al., 2009; Arora et al., 2012; Peng et al., 2013; Steimle et al., 2018). This idea is well supported by prior work in animal models. For instance, Wnt ligands from the heart field are crucial for foregut endoderm specification (Steimle et al., 2018) and, subsequently, the Hedgehog ligand secreted by the specified lung endoderm is critical for atrial septation (Hoffmann et al., 2009). Additionally, cardio-pulmonary progenitors originating from the second heart field are required for the formation of pulmonary vasculature (Peng et al., 2013). While such work in animal models indicate extensive crosstalk between the developing heart and lungs, the relevance of these findings to human development remains unknown.
Due to limited access to human embryos and ethical concerns, there is a critical lack of platforms that allow for the translation of animal studies into an understanding of the interrelationship between the heart and lungs during human development. Advancements in induced pluripotent stem cell (iPSC) technology have demonstrated the feasibility for direct differentiation of either cardiac (Kattman et al., 2011; Lian et al., 2012, 2015; Mummery et al., 2012; Burridge et al., 2014; Lee et al., 2017) or pulmonary (Wong et al., 2012; Gotoh et al., 2014; Huang et al., 2014; Dye et al., 2015; Chen et al., 2017; Jacob et al., 2017) lineages from human iPSCs (hiPSCs). However, it remains challenging to investigate the mutual interaction between the mesoderm-derived heart and endoderm-derived lung lineages during their specification from hiPSCs. While prior studies have shown that pluripotent stem cells can be differentiated into mesendoderm (Martyn et al., 2019)—the precursor for mesoderm and endoderm, which ultimately can be directed into the cardiac and pulmonary lineages, respectively—we explored and validated the possibility of differentiating hiPSCs into both heart and lung cells within the same culture by modulating the paracrine signaling required for inducing both lineages.
This protocol describes a methodology for simultaneously generating cardiac and pulmonary progenitors from hiPSCs, involving the induction of the primitive streak, definitive endoderm/mesoderm, anterior foregut endoderm/cardiac mesoderm, and finally cardiac and pulmonary progenitors within 15 days of differentiation. In this protocol we used an hiPSC line carrying both NKX2.1-GFP and SFTPC-TdTomato fluorescent reporters to track the emergence of early pulmonary progenitors and alveolar type 2 cells. 3D suspension culture of the co-induced cardiac and pulmonary progenitors led to expedited alveolarization within 3 days. Further, the withdrawal of Wnt agonist (CHIR99021) facilitated cardio-pulmonary tissue segregation, generating pulmonary-only and cardiac-only μTs (Ng et al., 2022). This protocol can be used to generate human cardio-pulmonary progenitors for investigating their co-development and crosstalk in vitro, as well as for drug testing.
Materials and Reagents
For Cell Culture
96-well plate (Corning, catalog number: 3698)
6-well plate (Corning, catalog number: 3516)
Ultra-low adherence 24-well plate (Greiner Bio-One, catalog number: 662970)
Ultra-low adherence 96-well plate (Greiner Bio-One, catalog number: 650979)
hiPSCs BU3-NGST [a gift from Dr. Darrell Kotton’s Laboratory, Boston University; users can request this cell line from Dr. Kotton’s Lab (Jacob et al., 2017)]
mTeSR-Plus (Stem Cell Technologies, catalog number: 05825)
hESC-qualified Matrigel Basement Membrane Matrix (Corning, catalog number: 354234)
ReLeSRTM (Stem Cell Technologies, catalog number: 05873)
StemPro® Accutase® Cell Dissociation Reagent (Thermo Fisher Scientific, catalog number: A1110501)
Dulbecco’s Phosphate-Buffered Saline (DPBS) (Corning, catalog number: 45000-430)
RPMI-1640 (Corning, catalog number: 10-040-CV)
DMEM/F12 (Corning, catalog number: 10-090-CV)
GlutaMAXTM (Thermo Fisher Scientific, catalog number: 35050061)
B27 Supplement (minus insulin) (Thermo Fisher Scientific, catalog number: A1895601)
B27 Supplement (Complete) (Thermo Fisher Scientific, catalog number: 12587-010)
TrypLE Express (Thermo Fisher Scientific, catalog number: 12605028)
HycloneTM Fetal Bovine Serum (FBS) (Cytiva, catalog number: SH30071.03)
Penicillin-Streptomycin (Pen/Strep), 10,000 U/mL (Thermo Fisher Scientific, catalog number: 15140148)
Trypan Blue (VWR, catalog number: K940-100ML)
Media Recipes/Composition (see Recipes)
For immunocytochemistry
Methanol (Fisher Chemical, catalog number: BPA412-1)
Bovine Serum Albumin (BSA) (Fisher BioReagents, catalog number: BP9706-100)
Phosphate Buffer Saline (PBS) 20× (Growcells, catalog number: MRGF-695-010L)
Triton X-100 (Sigma-Aldrich, catalog number: X100-500ML)
Antibodies
Rabbit monoclonal anti-NKX2.1 (Abcam, catalog number: ab76013)
Goat polyclonal anti-NKX2.5 (R&D Systems, catalog number: AF2444)
Donkey anti-rabbit IgG (H+L) Alexa Fluor 488 (Thermo Fisher Scientific, catalog number: A21206)
Donkey anti-goat IgG (H+L) Alexa Fluor 647 (Thermo Fisher Scientific, catalog number A21447)
Growth factors and small molecules
Recombinant human keratinocyte growth factor (KGF) (PeproTech, catalog number: 100-19)
Y27632 (Cayman Chemical, catalog number: 1000558310)
CHIR99021 (Reprocell, catalog number: 04000402)
A83-01 (Sigma-Aldrich, catalog number: SML0788)
IWP4 (Tocris, catalog number: 5214)
All-trans retinoic acid (Cayman, catalog number: 11017)
Dexamethasone (Sigma-Aldrich, catalog number: D4902)
8-bromoadenosine 3’,5’-cyclic monophosphate sodium salt (cAMP) (Sigma-Aldrich, catalog number: B7880)
3-Isobutyl-1-methylxanthine (IBMX) (Sigma-Aldrich, catalog number I5879)
Equipment
EVOS FL Auto 2 Imaging System (Thermo Fisher Scientific, catalog number: AMAFD2000)
Thermo ScientificTM SorvallTM LegendTM X1 Centrifuge (Thermo Fisher Scientific, catalog number: 75-218-382)
Thermo ScientificTM 1300 Series Class II, Type A2 Biological Safety Cabinet (Thermo Fisher Scientific, catalog number: 13-261-306)
CO2 Resistant Shaker (Thermo Fisher Scientific, catalog number: 88881103)
FisherbrandTM IsotempTM CO2 Incubator (Thermo Fisher Scientific, catalog number: 11-676-604)
25 cu. ft. (708 L) Reach-in IR CO2 Incubator (Caron Products, catalog number: 7400-25-1)
Software
ImageJ Version 1.8.0.182 (National Institutes of Health, https://imagej.nih.gov/ij/download.html)
Procedure
Matrigel Coating
Note: All steps are performed under class II biological safety cabinet, unless otherwise stated.
Thaw a -80 °C aliquot of Matrigel (100 µL) by placing it in a 4 °C fridge for 1 h.
Prepare the 1% (v/v) working solution by diluting the thawed Matrigel (100 µL) in 10 mL of DMEM/F12.
Add the Matrigel working solution into each well of the desired multi-well plate: 100 µL for the 96-well plate format, and 1.5 mL for the 6-well plate format.
Incubate the plate at 37 °C for at least 3 h.
Prior to use, aspirate the diluted Matrigel solution and use without washing the well.
BU3-NGST cell maintenance and passaging
Note: All steps are performed under class II biological safety cabinet, unless otherwise stated.
Prior to cell passaging, coat the wells of a 6-well plate with 1% (v/v) Matrigel for at least 3 h at 37 °C.
Remove mTeSR-Plus from Day 5 sub-confluent BU3-NGST cultured on a 6-well tissue culture plate and wash twice with 4 mL of DPBS.
Add 2 mL of ReLeSR and incubate for 15 s. Remove the ReLeSR and incubate the cells at 37 °C for an additional 5 min.
Collect the cells by adding 2 mL of fresh mTeSR-Plus and centrifuge at 300× g for 3 min.
Discard the supernatant and resuspend the cells in 1 mL of fresh mTeSR-Plus.
Passage the cells at ratios of 1:10 to 1:20.
Replenish 2 mL of mTeSR-Plus medium on Day 2, and 4 mL of medium on Day 4.
Normally, cells will be ready to passage again on Day 5.
Plating of BU3-NGST for differentiation
Note: All steps are performed under class II biological safety cabinet, unless otherwise stated. The following steps describe the procedure for obtaining dissociated cells from one well of a 6-well plate.
Prior to cell plating, coat the wells of a 96-well plate with 1% (v/v) Matrigel for at least 3 h at 37 °C.
Remove mTeSR-Plus from Day-5 sub-confluent BU3-NGST (Figure 1A) cultured on a 6-well tissue culture plate and wash twice with 4 mL of DPBS.
To dissociate the hiPSCs into single cells, add 3 mL of pre-warmed Accutase (avoid repeating the freeze-thaw cycle), and incubate for 5 min at 37 °C. Transfer dissociated BU3-NGST into 3 mL of fresh mTeSR-Plus and centrifuge at 300 × g for 3 min.
Discard supernatant and resuspend the cell pellet with 1 mL fresh mTeSR-Plus supplemented with 10 μM Y27632. Gently pipette up and down 10 times to break the cell pellet into single-cell suspension.
Perform cell counting using a hemacytometer by diluting the cells in Trypan Blue at ratio 1:2.
Plate 150,000 cells/cm2 per well in 100 μL of mTeSR-Plus supplemented with 10 μM Y27632 (Figure 1B).
Note: The cells will be ready for differentiation the following day.
Figure 1. Undifferentiated iPSCs in culture. A. Undifferentiated hiPSC colony. B. hiPSCs after one day of single-cell plating (scale bars = 200 μm).
Differentiation from hiPSCs to human cardio-pulmonary progenitors
Note: All steps are performed under class II biological safety cabinet unless otherwise stated. The following steps describe the procedure for differentiating hiPSCs from one well of a 96-well plate.
On the day of induction (Day 0, one day after single-cell plating), remove cell culture medium and add 200 μL of 7 μM CHIR99021 in mTeSR-Plus supplemented with 10 μM Y27632. Refresh the medium on Day 1.
Note: The CHIR99021 concentration required for effective and balanced cardio-pulmonary induction can be cell line dependent. Perform optimization of CHIR99021 concentration as needed.
On Day 2, remove the medium and wash the culture twice with 200 μL pre-warmed RPMI-1640. Add 100 μL pre-warmed medium (composed of RPMI-1640, 1× GlutaMAX, 1× B27 minus insulin, 10 μM Y27632, and 1% Pen/Strep). Refresh the medium on Day 3.
Note: Check for cell viability at this stage. Massive cell death will lead to poor co-differentiation outcome.
On Days 4–7, remove the medium and add 100 μL of pre-warmed medium supplemented with 1 μM A83-01 and 5 μM IWP4. Refresh the medium daily.
On Day 8, remove the medium and wash the culture once with 100 μL pre-warmed RPMI-1640. During Days 8–14, add 100 μL of pre-warmed medium (composed of RPMI-1640, 1× GlutaMAX, 1× B27 complete, and 1% Pen/Strep) supplemented with 3 μM CHIR99021 and 100 nM retinoic acid, and refresh the medium daily.
Note: The appearance of NKX2.1-GFP, which indicates early lung progenitors, can be observed from Day 10 onwards (Figure 2A).
To assess the co-differentiation efficiency, fix the differentiated human cardio-pulmonary progenitors on Day 15, and check for cardiac (NKX2.5) and pulmonary (NKX2.1) markers using immunocytochemistry (Figure 2C–2D) (see section G). Quantify NKX2.1-GFP lung progenitor efficiency on Day 15 by flow cytometry (Figure 2B) (see section H).
Figure 2. Characterization of the co-induced human cardio-pulmonary progenitors. A. GFP expression indicating NKX2.1-expressing pulmonary progenitors (scale bar = 125 μm). B. Quantification of NKX2.1-GFP lung progenitors on Day 15 by flow cytometry. C, D. Immunofluorescence staining of NKX2.1 (pulmonary) and NKX2.5 (cardiac) (scale bars for panel C = 250 μm; scale bars for panel D = 125 μm).
Generation of human cardio-pulmonary microtissues (μTs)
On Day 15, trypsinize at least 3 wells (96-well plate format) of the human cardio-pulmonary progenitors using 100 μL TrypLE Express and incubate at 37 °C for 15 min.
Neutralize the TrypLE Express by adding 200 μL RPMI-1640 supplemented with 10% FBS.
Centrifuge at 300 × g for 3 min.
Resuspend the cell pellet in alveolar maturation medium (comprising RPMI-1640, 1× GlutaMAX, 1% Pen/Strep, 1× B27 complete, 3 μM CHIR99021, 10 ng/mL KGF, 50 nM dexamethasone, 0.1 mM cAMP, 0.1 mM IBMX, and 10 μM Y27632).
Plate 500k cells into one well of an ultra-low adhesion 24-well plate in 500 μL of alveolar maturation medium and incubate on an orbital shaker at 125 rpm to generate μTs.
On Day 16, perform full medium change with alveolar maturation medium without 10 μM Y27632. Tilt the plate at a small angle to collect all μTs at one corner, then carefully aspirate and remove the majority of medium without losing the μTs. Refresh the medium on Day 17.
On Day 18, check for SFTPC-TdTomato using a fluorescence microscope (Figure 3).
Figure 3. Formation of human cardio-pulmonary μTs. Alveolar type 2 cell maturation identified through the emergence of SFTPC-TdTomato fluorescence signal on Day 17; the signal becomes stronger on Day 18 (scale bars = 125 μm).
Segregation of human cardio-pulmonary μTs
On Day 18, transfer one μT from the ultra-low adhesion 24-well plate into each well of an ultra-low adhesion 96-well plate.
Note: The μTs are visible to the naked eye. By inserting a 100 μL pipette tip close enough to the μTs, one can transfer a single μT from the well. Examine under the microscope to confirm.
Replace the medium with alveolar maturation medium without CHIR99021 or Y27632.
On Days 19–23, add 20 μL of cell culture water into each well to compensate medium evaporation and incubate for at least 10 min to allow complete mixture.
Note: Evaporation of the culture medium is inevitable. This step is crucial to prevent salt from accumulating over time in the culture medium following evaporation.
Remove 50 μL of medium and replenish with 50 μL of fresh medium.
On Day 23, look for segregated pulmonary μTs expressing GFP and contracting cardiac μTs (Figure 4).
Figure 4. Segregation of human cardio-pulmonary μTs. μTs before and after segregation (scale bars = 125 μm). Schematic diagram adapted from Ng et al. (2022).
Immunocytochemistry
Note: The following steps describe the staining protocol for cells plated on one well of a 96-well plate.
Fix cells with 100 μL of ice-cold methanol for 20 min.
Discard methanol and air-dry the samples for at least 1 h.
Note: Complete air-dried samples can be rehydrated in PBS and kept at 4 °C for up to a week prior to immunocytochemistry staining. Insufficient air-drying may compromise staining outcome.
Permeabilize cells with 1% (v/v) Triton X-100 in PBS at room temperature for 20 min.
Discard the permeabilization buffer and wash three times with PBS.
Block the cells with 1% BSA diluted in PBS for 30 min at room temperature.
Prepare working stocks of primary antibodies by dilution in 1% BSA (in PBS). See Table 1 for recommended primary antibodies and their working dilutions for each cell type.
Incubate the cells in 30 μL of primary antibodies overnight at 4 °C.
Wash the cells three times with PBS, add 30 μL of secondary antibodies diluted in 1% BSA (in PBS), and incubate at room temperature for 1 h. See Table 1 for recommended secondary antibodies and dilutions.
Wash three times with PBS and leave 300 μL of PBS in the well following the final wash. The cells are then ready for imaging.
Table 1. Antibody dilution
Antibody Dilution
Anti-NKX2.1 (rabbit monoclonal) 1:500
Anti-NKX2.5 (goat polyclonal) 1:500
Donkey anti-rabbit IgG (H+L), Alexa Fluor 488 1:500
Donkey anti-goat IgG (H+L), Alexa Fluor 647 1:500
Flow cytometry
Dissociate Day 15 co-differentiated cells in TrypLE Express for 15 min at 37 °C.
Neutralize TrypLE Express using RPMI-1640 supplemented with 10% FBS and centrifuge at 300 × g for 3 min.
Discard supernatant and resuspend cells in incubation medium (composed of DPBS and 1% FBS).
Analyze the percentage of cells expressing GFP using BD FACSAria II.
Data analysis
Detailed analysis of hiPSC-derived cardio-pulmonary progenitors and their maturation can be found in the open access article recently published by our group (Ng et al., 2022).
Notes
The hiPSC line and initial cell seeding density may affect the outcome of the differentiation efficiency and the sensitivity of cells to CHIR99021 treatment. For different hiPSC lines, it is recommended to explore different cell densities and CHIR99021 concentrations to identify the optimal combination for cardio-pulmonary co-induction. When the differentiation efficiency is compromised, check the quality of the hiPSC maintenance culture. It is important to spot any spontaneous differentiation, over confluency, suspicious cell death, or potential microorganism contamination. It is recommended to thaw a new vial of hiPSCs every 6-12 months to ensure reproducible cellular performance. It is also recommended to wash the cells with basal medium (such as RPMI-1640) at least once prior to switching to a different medium for the next stage of differentiation.
Recipes
Media Recipes/Composition
Note: Differentiation medium can be stored at 4 °C for up to 1 week. Aliquot the needed amount of medium and pre-warm in a 37 °C water bath for 5–10 min before using (beware of any undissolved stock solution).
Media Base Small molecules/Growth Factors Final Concentration
Stage 1: Day 0–1 mTeSR Plus CHIR99021 7 μM
Y27632 10 μM
Stage 1: Days 2–3 RPMI-1640 Y27632 10 μM
B-27 minus insulin (1×)
GlutaMAX (1×)
Stage 2: Days 4–7 RPMI-1640 A83-01 1 μM
B-27 complete (1×) IWP4 5 μM
GlutaMAX (1×) Y27632 10 μM
Stage 3: Days 8–14 RPMI-1640 CHIR99021 3 μM
B27 complete (1×) Retinoic acid 100 nM
GlutaMAX (1×)
Stage 4: Days 15–17 RPMI-1640 CHIR99021 3 μM
B27 complete (1×) KGF 10 ng/mL
GlutaMAX (1×) Dexamethasone 50 nM
cAMP 0.1 mM
IBMX 0.1 mM
Stage 4: Day 18 onwards RPMI-1640 KGF 10 ng/mL
B27 complete (1×) Dexamethasone 50 nM
GlutaMAX (1×) cAMP 0.1 mM
IBMX 0.1 mM
Acknowledgments
This work was supported by Samuel & Emma Winters Foundation A025662 (to X.R.), National Science Foundation CBET2145181 (to X.R.), and the Department of Biomedical Engineering and College of Engineering at Carnegie Mellon University. This protocol was adapted from our previous work (Ng et al., 2022).
Competing interests
W.H.N, and X.R. have a provisional patent application (No. 63/124422; “Methods for simultaneous cardio-pulmonary differentiation and alveolar maturation from human pluripotent stem cells”) related to this study.
References
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4,489 | https://bio-protocol.org/en/bpdetail?id=4489&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
In-Cell Western Protocol for Semi-High-Throughput Screening of Single Clones
AP Arpita S. Pal *
AA Alejandra M. Agredo *
AK Andrea L. Kasinski
(*contributed equally to this work)
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4489 Views: 2195
Reviewed by: Chiara AmbrogioJohn W Peterson Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Cancer Research Apr 2022
Abstract
The in-cell western (ICW) is an immunocytochemical technique that has been used to screen for effects of siRNAs, drugs, and small molecule inhibitors. The reduced time and number of cells required to follow this protocol illustrates its semi-high-throughput nature. Performing a successful ICW protocol requires fixing and permeabilizing adherent cells directly in the plate that specifically exposes the epitope of interest. After blocking of non-specific proteins, the cells are incubated overnight with a primary antibody of interest, which is detected via a host-specific near-infrared fluorescently labeled LI-COR secondary antibody. In the final step, the plate is scanned using an Odyssey LI-COR Imaging System or similar, and each of the wells is quantified. For the first time, this technique has been demonstrated to be reproducibly utilized for semi-high-throughput selection of knockout or overexpression clones.
Graphical abstract:
Keywords: In-cell western Single clone selection Knockout Overexpression Doxycycline High-throughput LI-COR CRISPR-Cas9 Screen validation
Background
Knockout or overexpression screens are efficient methods for identifying the involvement of novel genes that contribute to phenotypes such as drug resistance. Perturbation of gene function is enabled through either loss-of-function studies, using biological tools such as the CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats) (Humphrey and Kasinski, 2015; Szlachta et al., 2018; Li and Kasinski, 2020), or by gain-of-function studies through overexpression of human ORFs (Open Reading Frame) (Arnoldo et al., 2014). Several genes can potentially be identified by such screening methodologies; however, validation is a key step. To validate and dissect the cellular function of the gene(s) of interest, gene modulation has become a prevalent technique in the field. To this end, the candidate gene is either individually knocked out or overexpressed, single clones are isolated, and finally the phenotype observed via the screen is reevaluated. Nevertheless, to confirm that the gene of interest is accurately knocked out or overexpressed in single clones, protein quantification is a usual process.
Differential protein expression of individual clones is conventionally determined by western blot. This and other techniques such as immunofluorescence and immunohistochemistry are indispensable methods for protein analysis; however, these protocols require increased amounts of resources (antibodies, reagents) and often need one or more days to complete. Therefore, a semi-high-throughput screen that allows for rapid identification of differential protein expression post-clonal selection that reduces expenses, labor, and time should be considered. The in-cell western (ICW) is a powerful, simple, and reproducible technique that is underutilized in the field. It is a cost-effective method to quantify intracellular signaling in intact cells. The ICW protocol involves fixation and immunostaining of cells and combines the specificity of a western blot with the reproducibility and throughput of an enzyme-linked immunosorbent assay (ELISA) (Boveia and Schutz-Geschwender, 2015). From previous reports, semi-high-throughput cell-based applications of ICW include: 1) identification of efficient siRNAs from libraries and 2) identification of small molecule inhibitors targeting a particular signaling pathway (Hoffman et al., 2010). Additionally, ICW has been successfully utilized for screening genotoxic drugs by quantifying the expression of γH2AX, a well-known DNA damage and repair marker (Khoury et al., 2013). Another example of the versatility of ICW for throughput experiments is during the screening of chemical libraries for compounds that modulate the intensity and duration of growth factor-induced MAPK activity, an important regulator in cancer progression (Schnaiter et al., 2014).
Here, we describe a semi-high-throughput screening mechanism using the ICW protocol for validation of single knockout or overexpression clones for a protein of interest, initially identified using the CRISPR-Cas9 screening system (Pal et al., 2020, 2022). ICW has proved to be an efficient technique for clonal selection of cells because it allows rapid analysis of numerous samples, conserving the accuracy of the quantifiable output. To the best of our knowledge, the ICW protocol described below is the first reported use of ICW for the selection of multiple single clones simultaneously.
The pros and cons of using ICW versus western blot for efficient clonal selection of cells are enlisted below (Table 1).
Table 1. Pros and cons of using in-cell western over using the more conventional technique of western blot for high-throughput selection of single clones.
Pros Cons
Fewer cells needed
Reliable quantification if unequal cells are plated
Less volume of reagents and buffers needed
Primary antibodies can be reused
Plates can be stored at 4 °C in PBS for processing at a later time
Experimental replicates are easy to obtain
Easier to visualize radical changes in protein expression in multiple samples
Fixation preserves post-translational modifications
Error-prone steps such as cell lysis, gel electrophoresis, and membrane transfer are eliminated
Less time-consuming than western blot (many samples in parallel)
Performed in situ, relevant to cellular context
No molecular weight–based separation step; thus, antibody specificity is critical
Optimization for each antibody may be necessary
More concentrated primary antibodies are required
Slight changes in protein expression may not be detected
A dual-fluorescent imaging system, such as the Odyssey LI-COR Imaging System is required
The protocol described here is validated for one protein; therefore, optimization of various parameters may be necessary to achieve study-specific goals, described in Table 2.
Table 2. Parameters at specific steps of ICW that can be optimized to achieve high-throughput selection of single clones for study-specific goals.
Steps in protocol Parameters to be optimized
Antibody Optimization
Specificity is typically better if antibody is ChIP grade and reported in immunofluorescence studies
Incubation time overnight or >2.5h
Concentration of antibody
Cells
Cell number
Cell type
Choice of plate
Type of plate
Focus for scanning (3.0 mm to 4.0 mm)
Fixation
Type of fixative: methanol, formaldehyde, ethanol, acetone
Use the recommended fixative from primary antibody manufacturer
Incubation time
Incubation temperature
Permeabilization
Type of permeabilizer: methanol, Triton X-100, Saponin
Incubation time
Materials and Reagents
96-well clear flat-bottom polystyrene tissue-culture plates (Corning, catalog number: 3596)
15 mL Falcon tubes (Corning, Falcon®, catalog number: 352097)
Reagent reservoir nonsterile (VWR, catalog number: 89094-684)
100% methanol (Thermo Fisher, catalog number: A412-20), storage: room temperature
Distilled water, storage: room temperature
NaCl (Sigma Aldrich, catalog number: S3014-1KG), storage: room temperature
KCl (Sigma Aldrich, catalog number: P9333-1KG), storage: room temperature
KH2PO4 (Sigma Aldrich, catalog number: P9791-500G), storage: room temperature
Na2HPO4·2H2O (Sigma Aldrich, catalog number: 71643-1KG), storage: room temperature
Triton X (Sigma Aldrich, catalog number: X100), storage: room temperature
Tween-20 (Sigma Aldrich, catalog number: P9416), storage: room temperature
Primary Antibodies (varies), storage: either 4 °C or -20 °C, depending on the antibody
LI-COR Secondary Antibodies (varies), storage: 4 °C
1× PBS (see Recipes)
Permeabilizing buffer (0.2% Triton X in 1× PBS) (see Recipes)
1× Phosphate Buffered Saline Tween-20 (PBST) (see Recipes)
Equipment
LI-COR Blocking Buffer (LI-COR, Odyssey, catalog number: 927-40003)
Multichannel pipettes (Mettler-Toledo International, catalog number: L12-200XLS)
FinnpipetteTM Novus multichannel pipette (Thermo Fisher Scientific, Thermo ScientificTM, catalog number: 46300800)
Software
Image Studio Lite (LI-COR Biosciences, https://www.licor.com/bio/image-studio/)
Procedure
Plate 2,000 to 10,000 cells in single wells or duplicates in a 96-well plate, in appropriate culture medium, for 24 to 48 h prior to performing ICW.
Note: Include appropriate positive control cells and blank wells containing only medium for every assay. Cell number may need to be optimized for the cell type.
Chill 100% methanol at -20 °C for 15 min.
Remove media by flicking plate, then using a multichannel pipette to remove any residual media (Video 1).
Note: It was determined that flicking the plate on a stack of paper towels (turning the plate upside down rapidly and tapping gently) to decant the media was preferred over mechanical removal. Fewer cells were disrupted. This is especially true for less adherent cells.
Video 1. Procedure for flicking plate.
Add 150 µL of methanol to each of the 96 wells and incubate for 20 min at 4 °C (without shaking).
Notes:
Methanol should be added very gently down the walls of each of the wells.
Be cautious that wells do not dry out throughout the process. A manual multichannel pipette will suffice for few wells in a 96-well plate. However, an electronic multichannel pipette is advisable for a high-throughput experiment (Video 2).
Video 2. Procedure for adding methanol slowly using electronic multichannel pipette.
Flick plate to remove methanol, then using the multichannel pipette remove any residual methanol.
Note: See Video 1 in step 3 for flicking procedure.
Permeabilize cells using 150 µL of permeabilizing buffer with gentle shaking at room temperature for 30 min.
Flick plate to remove permeabilizing buffer, then using the multichannel pipette, remove any residual permeabilizing buffer.
Note: See Video 1 in step 3 for flicking procedure.
Block for 1.5 h using 50 µL LI-COR blocking buffer with gentle shaking at room temperature
Note: At this point, the plate can be stored at 4 °C overnight. Plates stored for longer than 4 days need to be checked for bacterial growth.
Flick plate to remove blocking buffer, then using the multichannel pipette, remove any residual buffer.
Note: See Video 1 in step 3 for flicking procedure.
Add 50 µL of 1:50 to 1:500 primary antibody and incubate overnight at 4 °C with gentle shaking.
Note: It is advised to use antibodies that are validated for ChIP or immunofluorescence. Each antibody will need to be optimized for concentration; typically, 1:50–1:500 dilutions are used due to differences in antibody affinity.
Carefully remove antibody. This can be accomplished by either flicking the plate or using the multichannel pipette if the antibody will be saved. For the latter, care should be taken to avoid disrupting the cells on the bottom of the well with the pipette tips. To avoid disrupting the cell monolayer, angle the plate at ~45° and position the pipette tips at the interface of the wall of the well and the bottom of the well. Slowly pipette the antibody solution into the pipette.
Note: Some primary antibodies can be saved and reused if desired. However, the number of reuses has to be determined for each antibody separately.
Add 150 µL of PBST to each well using the multichannel pipette and place plate on a shaker for 5 min at room temperature.
Remove PBST by flicking plate.
Note: See Video 1 in step 3 for flicking procedure.
Repeat steps 12 and 13 for a total of five times.
Add 50 µL of 1:800 secondary antibody, cover plate with aluminum foil to protect antibody from light, and incubate 1 h at room temperature with gentle shaking.
Note: Due to the sensitivity of the fluorescent antibodies to light, be sure to keep plate covered with aluminum foil after this step.
Carefully remove antibody. See step 11.
Add 150 µL of PBST to each well using the multichannel pipette and place plate on a shaker for 5 min at room temperature.
Carefully remove the wash buffer by flicking plate.
Repeat steps 17 and 18 for a total of five times.
Perform one wash with PBS for 5 min while shaking the plate.
Flick plate to remove PBS, blot the plate, clean the bottom of the plate, and scan.
Note: At this point, since the plate has yet to be blotted for the endogenous control, it is necessary to ensure a layer of PBS is maintained in the plate to prevent it from drying out.
In order to scan the plate on the LI-COR Biosciences software, select the “plate” setting and focus at “4.0 mm” along with resolution and quality according to preference.
Note: Focus set to 4.0 mm usually works best. However, this setting may need to be adjusted based on the manufacturer of the plate used. See Figures 1 and 2 below for location of plate and software settings.
Figure 1. Plate location on LI-COR, in this case positioned in the bottom left corner.
Figure 2. Plate settings on LI-COR, including selected region for scanning based on the location of the plate.
Reblot the plate with the endogenous control antibody at a dilution of 1:500 to 1:1,000 either for 2.5 h at room temperature or overnight at 4 °C.
Carefully remove antibody. See step 11.
Wash each well by adding 150 µL of PBST using the multichannel pipette and incubate the plate on a shaker for 5 min at room temperature.
Repeat step 25 for a total of five times.
Add 50 µL of 1:800 secondary antibody to each well, cover the plate with aluminum foil, and incubate 1 h at room temperature with gentle shaking.
Carefully remove antibody.
Wash each well by adding 150 µL of PBST using the multichannel pipette and incubate the plate on a shaker for 5 min at room temperature.
Repeat step 29 for a total of five times.
Perform one wash with PBS for 5 min while shaking the plate.
Flick plate to remove PBS and blot the plate dry before the final scan.
Scan the plate using the suggested starting Odyssey scan parameters:
Resolution: 84 µM
Quality: Medium
Focus offset: 4.0 mm
Intensity: Adjust as necessary such that signal is evident for positive samples but not for negative controls (i.e., empty wells or cells not incubated with the primary antibody).
Note: See Figure 2 in step 22 for the setting parameters.
The specific plate format selected under the “analysis settings” tab of the software will create a grid that can be adjusted to match the wells on the scanned image for further analysis (see Figure 3 below).
Note: It is important to place the plate parallel to the scale markings on the scanner in order to align the plate template onto the scanned image.
Examples of using the ICW protocol to identify clones knocked out for a particular gene are shown in Figures 4–6. In this case, Cas9 targeting KMT5C was transfected into cells, and individual clones were isolated and propagated. Using the ICW protocol, expanded clones were then evaluated for the downstream histone modification generated of KMT5C, histone 4 lysine 20 trimethylation (H4K20me3). Clones with variability in KMT5C activity were identified using the ICW protocol (Figure 4) and were confirmed via western blotting (Figure 5). In a similar way, clones overexpressing a doxycycline-inducible KMT5C were screened using the ICW protocol (Figure 6).
Figure 3. Image depicting the analysis setting options on the LI-COR software, including quantification of signal intensity in each identified well in the table at the bottom.
Figure 4. Selection of single clones knocked out for KMT5C by quantifying a downstream effector, H4K20me3 mark via ICW. Parent cell or KO clones (clones a-e) were plated in duplicates in a 96-well plate (10,000 cells/well). 48 h post-plating, cells were blocked using LI-COR blocking buffer, permeabilized using permeabilizing buffer, incubated with 1:400 H4K20me3 (Active Motif) primary antibody overnight on a shaker at 4 °C, and detected using anti-mouse LI-COR secondary antibodies. Then, the plate was scanned and re-blotted overnight on a shaker at 4 °C using a 1:500 concentration of GAPDH (Cell Signaling) primary antibody and detected using anti-rabbit LI-COR secondary antibodies.
Figure 5. Clones identified through ICW, validated via western blot. Parent cells or KO clones (Clones a-e) were plated in a 6-well plate at 4 × 105 cells/well. 48 h post-plating, lysates were isolated, quantified, and separated using polyacrylamide gel electrophoresis. Post-transfer onto a PVDF membrane, the membrane was blocked using LI-COR blocking buffer and incubated overnight in 1:500 H4K20me3 antibody or in 1:10,000 β-ACTIN (Cell Signaling) primary antibody overnight on a shaker at 4 °C, and detected using anti-mouse or anti-rabbit LI-COR secondary antibodies, respectively.
Figure 6. Single clones selected post-doxycycline mediated induction of KMT5C via H4K20me3 quantification by ICW. Either parental cells or doxycycline inducible KMT5C-single clones (clones 1–4) were plated at 10,000 cells/well in replicates of four in a 96-well plate. Doxycycline (2 µg/mL) or equivalent volume of PBS was added to two wells for each cell line at the time of plating. 48 h post-treatment, cells were blocked using LI-COR buffer, permeabilized using permeabilizing buffer, incubated with 1:400 H4K20me3 (Active Motif) primary antibody overnight on a shaker at 4 °C, and detected using anti-mouse LI-COR secondary antibodies. Then, the plate was scanned and reblotted overnight on a shaker at 4 °C in 1:500 GAPDH (Cell Signaling) primary antibody and detected using anti-rabbit LI-COR secondary antibodies.
Notes
During screening of single clones, cells can be plated in single wells, without counting. However, calculating relative signal of protein of interest to that of the positive control, post-normalizing to signal of the endogenous control is necessary.
Scanning overnight dried plates (in the dark) after blotting for both the protein of interest and the endogenous control can yield more uniform and sharper signals.
We recommend validating the candidate single clones identified through ICW via other protein quantification techniques such as western blot or immunofluorescence.
Recipes
1× PBS
800 g NaCl
20 g KCl
144 g Na2HPO4·2H2O
24 g KH2PO4
8 L of distilled water
Permeabilizing buffer (0.2% Triton X in 1× PBS)
50 mL 1× PBS
100 µL Triton X
1× PBST
1 L of 1× PBS
1 mL Tween-20
Acknowledgments
We thank Chennan Li for comments regarding use of the ICW protocol. This work was supported by National Institutes of Health NCI-R01CA205420 to A.L. Kasinski. A.S. Pal was supported by a Purdue Research Foundation (PRF) Research Grant award by the Department of Biological Sciences, Purdue University, a SIRG grant administered through the Purdue Center for Cancer Research, Purdue University, a Cancer Prevention Internship Program Graduate Research Assistantship funded by Purdue University, and a Bilsland Dissertation Fellowship awarded by the Department of Biological Sciences, Purdue University. A.M. Agredo was supported by a Ross Fellowship administered through Purdue University. R. The Graphical Abstract was created using BioRender.com. Use of this protocol has been reported in an original body of work published in Cancer Research (Pal et al., 2022).
Competing interests
The authors declare no competing financial interests.
References
Arnoldo, A., Kittanakom, S., Heisler, L. E., Mak, A. B., Shukalyuk, A. I., Torti, D., Moffat, J., Giaever, G. and Nislow, C. (2014). A genome scale overexpression screen to reveal drug activity in human cells. Genome Med 6(4): 32.
Boveia, V. and Schutz-Geschwender, A. (2015). Quantitative Analysis of Signal Transduction with In-Cell Western Immunofluorescence Assays. Methods Mol Biol 1314: 115-130.
Hoffman, G. R., Moerke, N. J., Hsia, M., Shamu, C. E. and Blenis, J. (2010). A high-throughput, cell-based screening method for siRNA and small molecule inhibitors of mTORC1 signaling using the In Cell Western technique. Assay Drug Dev Technol 8(2): 186-199.
Humphrey, S. E. and Kasinski, A. L. (2015). RNA-guided CRISPR-Cas technologies for genome-scale investigation of disease processes. J Hematol Oncol 8: 31.
Khoury, L., Zalko, D. and Audebert, M. (2013). Validation of high-throughput genotoxicity assay screening using gammaH2AX in-cell western assay on HepG2 cells. Environ Mol Mutagen 54(9): 737-746.
Li, C. and Kasinski, A. L. (2020). In Vivo Cancer-Based Functional Genomics. Trends Cancer 6(12): 1002-1017.
Pal, A. S., Agredo, A. M., Lanman, N. A., Clingerman, J., Gates, K. and Kasinski, A. L. (2020). Loss of SUV420H2 promotes EGFR inhibitor resistance in NSCLC through upregulation of MET via LINC01510. bioRxiv: 2020.2003.2017.995951.
Pal, A. S., Agredo, A., Lanman, N. A., Son, J., Sohal, I. S., Bains, M., Li, C., Clingerman, J., Gates, K. and Kasinski, A. L. (2022). Loss of KMT5C Promotes EGFR Inhibitor Resistance in NSCLC via LINC01510-Mediated Upregulation of MET. Cancer Res 82(8): 1534-1547.
Schnaiter, S., Furst, B., Neu, J., Waczek, F., Orfi, L., Keri, G., Huber, L. A. and Wunderlich, W. (2014). Screening for MAPK modulators using an in-cell western assay. Methods Mol Biol 1120: 121-129.
Szlachta, K., Kuscu, C., Tufan, T., Adair, S. J., Shang, S., Michaels, A. D., Mullen, M. G., Fischer, N. L., Yang, J., Liu, L., et al. (2018). CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response. Nat Commun 9(1): 4275.
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4,490 | https://bio-protocol.org/en/bpdetail?id=4490&type=0 | # Bio-Protocol Content
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Peer-reviewed
A Fast and Reliable Method to Generate Pure, Single Cell-derived Clones of Mammalian Cells
ZH Zhe Han *
BM Bindhu K. Madhavan *
SK Serap Kaymak
PN Peter Nawroth
VK Varun Kumar
(*contributed equally to this work)
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4490 Views: 2589
Reviewed by: Ralph Thomas BoettcherJungeun Yu Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Cancers Jun 2021
Abstract
Stable cell cloning is an essential aspect of biological research. All advanced genome editing tools rely heavily on stable, pure, single cell-derived clones of genetically engineered cells. For years, researchers have depended on single-cell dilutions seeded in 96- or 192-well plates, followed by microscopic exclusion of the wells seeded with more than or without a cell. This method is not just laborious, time-consuming, and uneconomical but also liable to unintentional error in identifying the wells seeded with a single cell. All these disadvantages may increase the time needed to generate a stable clone. Here, we report an easy-to-follow and straightforward method to conveniently create pure, stable clones in less than half the time traditionally required. Our approach utilizes cloning cylinders with non-toxic tissue-tek gel, commonly used for immobilizing tissues for sectioning, followed by trypsinization and screening of the genome-edited clones. Our approach uses minimal cell handling steps, thus decreasing the time invested in generating the pure clones effortlessly and economically.
Graphical abstract:
A schematic comparison showing the traditional dilution cloning and the method described here. Here, a well-separated colony (in the green box) must be preferred over the colonies not well separated (in the red box).
Keywords: Stable mammalian cell clones Transfection Plasmid Cell culture Tissue-tek
Background
Genetically engineered expression and genome manipulating plasmids are routinely utilized (Soutoglou and Misteli, 2008; Toiber et al., 2013; Simon et al., 2019). Studies involving the characterization of cellular localization, or recruitment of a factor to a cell organelle under basal or induced conditions, depend on a short-lasting ectopic expression of the desired gene (Soutoglou and Misteli, 2008). However, modern biological processes and physiological studies involve long-term characterization, requiring stable cell lines expressing or inhibiting the function of a specific gene or cluster of genes (Condreay et al., 1999). In addition, the varying percentage of transfected cells also generates a wide range of undesired experimental variation. Thus, the generation of pure lines of genetically engineered cells is essential in studying any given protein's function more accurately and reproducibly.
Over the decades, several ways have been devised to generate genetically engineered pure cells (Condreay et al., 1999; Aranda et al., 2014; Giuliano et al., 2019; Singh, 2019). Dilution cloning and fluorescence-activated cell sorting (FACS) are the most commonly used (Giuliano et al., 2019; Singh, 2019). However, both these techniques have their advantages and disadvantages. Dilution cloning is the cheapest method to generate stable cell lines, as it does not involve unique and expensive instrumentation (Singh, 2019). However, this technique is very time-consuming and highly laborious. Indeed, many scientists spend a considerable amount of time each day identifying and marking the wells in a 96-well plate showing colony growth from a single cell, and marking the wells that receive multiple or no cells. Similarly, as an alternative to dilution cloning, FACS requires advanced sorting instrumentation and a sorting expert. In addition, FACS can sometimes be stressful for cells, thus altogether challenging the desired outcome.
To overcome these drawbacks, we generated a simple and easy method for generating stable, single cell-derived clones of anchorage-dependent cells. This method neither involves a labor-intensive step nor expensive instrumentation. Our protocol utilizes the inherent property of the cells to attach to the tissue culture (TC) surface and the use of a selection marker to identify and then select the desired cells. Over time, the stable cells that survive the selection will be from a small colony. These colonies will be refined by encircling them with a cloning cylinder and a non-toxic gel. Considering the innovative design, simple steps, and ease of applicability, any cell culture-trained personnel can follow this method for generating stable cells. The protocol presented is labor-saving and economical, with high reproducibility in developing pure, stable, single cell-derived clones, suitable for long-term and extensive scale up use in subsequent experiments.
Materials and Reagents
Materials
6-well clear flat bottom TC-treated multiwell cell culture plate (Gibco, catalog number: 353046)
100 mm TC-treated cell culture dish (Corning, Falcon, catalog number: 353003)
150 mm Nunc EasYDish culture dish (Thermo, catalog number: 150468)
T75 TC flask (Greiner Cell STAR T75, catalog number: 658170)
15 mL centrifuge tube, conical bottom sterile (Corning, Falcon, catalog number: 352099)
Cryogenic vials, 1.2 mL (Corning, catalog number: 430487)
1.5 mL tubes (Sarstedt, catalog number: 72.690.301)
Pyrex Cloning Cylinders (Corning, catalog number: 3166-10)
Pipette tips 10–200 µL (Greiner bio-one, catalog number: GB775362)
Micropipette (Thermo scientific, Finnpipette F1, catalog number: GJ06928)
Universal permanent marker pen (Schneider, catalog number: Maxx 222)
Artis Tweezer (Sigma, catalog number: 18072ARS)
Reagents
0.05% Trypsin-EDTA (PAN Biotech, catalog number: P10-040100)
Puromycin (Invivo Gen, catalog number: ant-pr-1)
Turbofect® Transfection reagent (Thermo Scientific, catalog number: R0531)
DMEM (1×, Gibco, catalog number: 31885-023)
Dimethyl sulfoxide (DMSO; Thermo Scientific, catalog number: 85190)
Dulbecco's Phosphate buffered saline without Ca and Mg (Sigma, catalog number: D8537-500ML)
pSp-Cas9(BB)-2A-Puro (PX459) V2.0 Plasmid (Addgene, catalog number: 62988)
SIRT1 gRNA (CAACAGGTTGCGGGAATCCAA) (Sigma; Oligo: 8815731198-000040)
Tissue-Tek® O.C.T. Compound (Sakura, catalog number: 4583)
Protein assay dye concentrate (Biorad, catalog number 5000006)
Anti-SIRT1 antibody (Cell Signaling, catalog number: 9475S)
Anti-β-Actin antibody (Cell Signaling, catalog number: 8457S)
Anti-Rabbit-IgG HRP conjugated (Cell Signaling, catalog number: 7074)
Hemocytometer (Sigma, catalog number: Z359629)
Penicillin/Streptomycin (Pan Biotech, catalog number: P06-07100)
Fetal bovine serum (FBS), Heat Inactivated (Gibco, catalog number: A38401-02)
L-Glutamine (Pan Biotech, catalog number: P04-80100)
Protease inhibitor cocktail 100× (Cell Signaling, catalog number: 5871)
Plasmid preparation Kit (Qiagen, catalog number: 12362)
Glycine (Sigma, catalog number: G8898)
Tris-Base (Trizma; Sigma, catalog number: T1503)
EDTA (Acros, catalog number: 147850010)
Tween-20 (Sigma, catalog number: P9416)
Glycerol (Honeywell, catalog number: 15523)
Sodium dodecyl sulfate (SDS; Bio-Rad, catalog number: 161-0302)
Bromophenol blue (BPB; Merck, catalog number: 1.08122.0005)
Dithiothreitol (DTT; Sigma, catalog number: D9779)
β-Mercaptoethanol (β-ME; Sigma, catalog number: M3148)
Mini-Protean TGX Gels (Bio-Rad, catalog number: 4561094)
Color Prestained protein standard marker (Cell Signaling, catalog number: P7719S)
Solutions and Media
Tris-Glycine SDS-PAGE running buffer (5×) (see Recipes)
Lysis buffer (see Recipes)
Basal cell culture medium (see Recipes)
Cell freezing medium (see Recipes)
5× SDS PAGE Loading dye or Laemmli’s buffer (see Recipes)
Equipment
TC incubator (Binder,model: CB 170, catalog number: 9640-0009)
Refrigerated benchtop centrifuge (Sigma, model: 3-18KS, rotor number: 11133)
Refrigerated Microcentrifuge (Eppendorf, model: 5430 R, rotor number: FA-45-30-11)
Ultra-low freezer (Thermo Scientific, catalog number: TSX60086D)
Liquid Nitrogen storage (Wharton, model: K-Series)
Compound Microscope (Wilovert, Hund Wetzlar, catalog number: 008.0309.0)
Procedure
Principle: This protocol is based on two principles; the first utilizes the inherent proliferation potential of the cells used in genetic manipulation (expression or deletion of the desired gene). The second principle relies on the availability of a functional drug-resistant gene for selection in the plasmid backbone. These two principles will be combined to rapidly and easily generate reliably stable, single cell-derived clones.
The detailed procedure describing the step-by-step method for generating the stable clones of cells comprises five (A–E) Parts:
(A) Preparation of cells and design of the pre-experimental set-up
(B) Transfection
(C) Selection and recovery of cells
(D) Colony selection followed by micro-trypsinization in cloning cylinders
(E) Testing of gene expression or gene editing
Before you begin: Prepare and stock the required reagents, medium, cell culture dishes, or plates in sufficient quantity for the planned work. In addition, prepare the study plasmids needed to prepare the stable clones (like CRISPR or fluorescent tagged-protein expressing plasmids or others) with a plasmid preparation kit (refer to Materials and Reagents section).
Preparation of cells and design of the pre-experimental set-up
In this preparatory phase, plan the pre-experiment set-up as follows:
Take a vial of the desired cells out of the liquid nitrogen tank and plate them in a T75 culture flask in 15 mL of basal cell culture medium, routinely used for maintaining these cells. If the cells are already in culture, set aside a T75 flask of healthy, well-growing cells. Usually, 0.5 × 105–1 × 105 cells are sufficient for this step.
Culture these cells in a TC incubator, adjusted to the needs of the cells used. For Hela/U2OS cells, we use a TC incubator maintained at 37 °C, 5% CO2, and 90–95% Relative Humidity (R.H.).
When the culture is 75–80% confluent, aspirate the supernatant and rinse cells with 10–15 mL of Calcium/Magnesium free PBS (1×). Trypsinize the cells to obtain a single-cell suspension for re-seeding.
Seed the cells in a 6-well plate, so they are about 70–75% confluent the next day. Approximately 0.8 × 105–2.4 × 105 cells work very well for most cells. Usually, we seed a single well of cells for each transfection and an additional well for the negative control.
Note: If the kill curve (obtained by incubating the cells with an increasing concentration of the selection drug needed to kill cells over 2–5 days) of the cell type used is not known for the desired selection marker, then seed 6 lanes in triplicate (6 × 3 wells) of the 96-well plate. To begin with, seed approximately 0.5 × 104–1.2 × 104 cells in each well of this plate. More details on kill curve preparation were described previously (Delrue et al., 2018).
Incubate cells in the TC incubator, as indicated in Step A2, or under the basal growth conditions required for the experimental cells.
Transfection of the cells and selection
In this part, we will transfect the cells with the desired plasmid meant to express a gene or for sequence-specific genome editing (such as CRISPR) or others as needed. For this, we suggest following the below-mentioned steps:
Replace the culture medium from each well of the 6-well plate with fresh medium (2 mL/well).
Prepare the transfection mix as shown in the table (Table 1).
Table 1. Preparation of the transfection mix used for cell transfection.
Components needed for transfecting the cells/well
Mix A (Plasmid or DNA Part) Mix B (Transfection Reagent Part)
DMEM* 200–(X) µL DMEM* 200–A µL
Desired Plasmid 0.5–2 µg (X µL) Turbofect Reagent A µL (6 µL)
Total Volume of Mix A 200 µL Total Volume of Mix B 200 µL
Now mix Mix A and Mix B, and incubate at 25 °C for 15 min
Total volume: 200 µL + 200 µL = 400 µL
* This DMEM does not contain FBS or any antibiotics.
Notes:
This protocol uses the Turbofect® transfection reagent (a cationic polymer in water, which forms a compact, stable complex with DNA). Still, any other transfection reagent suitable for DNA transfection could be used for transfection. In that case, please follow the parameters suggested by the manufacturer of the alternative transfection reagent.
We successfully tested these conditions (as described in Table 1) with Hela, U2OS, NIH-3T3, HEK293, and A549 cells using the Turbofect® transfection reagent. However, for other cells, one needs to define the conditions that yield maximum transfection efficiency with minimal toxicity.
After incubation, transfer the transfection mixture in drop-wise (in a total of 400 µL/well) manner to each well. Do not remove the growth medium from the cells before adding the transfection mix. Place the plate back in the TC incubator.
After 6 hours of transfection, replace the medium with fresh basal cell culture medium (2.0 mL per well) and place it back in the TC incubator.
Selection and recovery of cells
This part provides the details on selecting the transfected from the non-transfected cells. Considering the inherent properties of the antibiotic-resistant genes in the plasmid used for transfection, these can be utilized (such as neomycin, puromycin, or others) for selecting the transfected cells. For this, we suggest following the succeeding steps:
Replace the culture medium from each well of the 6-well plate with fresh medium containing an appropriate selection agent. Do not forget to add the selection agent containing medium to a non-transfected (negative) control. For example, we aim to generate homozygous SIRT1-/- Hela cells using the CRISPR-Cas9 system (details of the vector and the gRNA sequence are provided in the methods section) using a CRISPR-Cas9 vector backbone containing the puromycin gene as a eukaryotic selection marker. Therefore, in this case, we use puromycin at a 1.0 μg/mL concentration (determined by the kill curve for our Hela cell stock; refer to Step A4). Re-incubate the cells in the TC incubator as stated above.
Note: Shorter selection with puromycin mainly propagates the CRISPR plasmid as an episomal vector. However, a more extended duration selection with puromycin will select the cells stably integrated with this plasmid. Though shorter or longer selection does not affect the desired genetic manipulations (CRISPR-mediated genome editing). We recommend keeping the antibiotic selection for a longer duration because the stably integrated plasmid can be utilized as a tool (in case of cross-contamination) in these cells.
Replace the used medium (and also the dead cells) with fresh medium containing the appropriate selection agent as utilized in Step C1, every 48 h. During this time, keep track of the untransfected well (negative control). Within 3–5 days, all untransfected cells will die. This indicates the selection agent is working. The negative control well will be discarded at this stage. Continue selection of transfected cells for an additional week. Further, one can observe the selection much longer to keep a positive pressure or prevent the heterochromatinization of the integrated backbone. This ensures continuous expression of the desired gene.
Trypsinize the transfected cells that survive after selection. Re-seed cells from every well into two culture dishes (15 cm, about 40–100 cells in each plate, respectively) (Figure 1) with about 20 mL of medium containing the selection agent described in Step C1.
Figure 1. Selection, tryspsinization, and re-seeding. The schematic representation shows drug selection, trypsinization, and cell re-seeding in a fresh cell culture dish (15 cm).
Incubate the cells in the TC incubator and allow them to form individual colonies. Replace the medium every 4th day and keep the selection. Single cells will form separate colonies, and the size of these colonies will grow over time. Compound microscope can be used to determine the progress in colony growth.
After approximately 10 days, the colonies will be more or less visible to the naked eye (Figure 2), particularly when checked against a dark background. However, a brief analysis with a compound microscope is always helpful.
Figure 2. Selection and marking of the colonies. A. Schematic representation shows the appearance of colonies after 10–14 days of selection. The individual colonies are marked with a laboratory marker pen at the outer bottom surface of the cell culture dish, as shown in green curves. The colonies which are too close (red rectangle) remain unselected. B. Representative compound microscopy image of Hela cells after 13 days of re-seeding on a cell culture dish.
Mark the individual colonies using a lab marker from the bottom of the plate without removing the medium. To keep the selection pure, the colonies that are very close to each other should not be selected.
Note: Usually, when 40 or 100 cells are used, colonies are well separated from each other. However, there are chances that some of the colonies have originated from 2 different cells; such clones can be distinguished during the characterization process described in Part E.
Mark 12–36 colonies in total. More colonies can be marked; however, the indicated numbers are sufficient to obtain several stable, single cell-derived clones. Transfer the marked cell culture dish back to the TC incubator.
Representative data Part C: This section presents the data from our recent Hela cell lines generated using CRISPR-Cas9-based genome editing. After about 13 days of re-seeding, the cells survived during the initial puromycin (1 μg/mL) selection. The visible colonies are shown in Figure 2B. The colonies will start becoming visible after approximately 8–10 days.
Colony selection followed by micro-trypsinization in cloning cylinders
In this part, we will transfer the selected colonies to the wells of 6-well plates. This step is critical. Therefore, it needs both attention and speed.
Arrange the following items in a clean TC laminar hood, so they are well within reach without moving out or wasting any time. The sequence of arrangement is shown in Table 2.
Table 2. The sequence of item arrangement for transferring the clones to parent and copy plates.
S.No. Name of the item Remarks
1 Cloning cylinders* Place them in a fresh sterile dish
2 Forceps Sterile, curved ones are better for holding cylinders
3 Pre-warmed trypsin 0.05% (w/v); sufficient volume
4 Pipette tip boxes Sufficient, sterile; 1–200 μL tips for micropipette
5 Micropipette Range 20–200 μL
6
6-well plates (sterile)
Parent plate wells can be labeled as 1P, 2P, 3P, and so on
Copy plate wells can be labeled as 1C, 2C, 3C, etc.
* Cloning cylinders supplied non-sterile; these can be sterilized by placing/submerging them in a water filled glass beaker that is then autoclaved.
Remove the cell culture medium from the previously marked cell culture dish (from Step C6) and gently rinse colonies with PBS (1×; free from CaCl2 and MgCl2); thereafter, remove the PBS.
Using sterile forceps, take the cloning cylinder and place it directly around the marked colony so that the colony resides in the center of the cylinder. To minimize stress on the cells, work quickly!
Repeat step (Step D3) for the other colonies on the dish; while doing this, please ensure that you do not move the already secured cloning cylinders. A standard 15 cm dish can accommodate 30–50 well-separated cloning cylinders; however, 20–30 cylinders are typically more than enough to begin with.
Once the placing of cloning cylinders is finished, use the Tissue-tek bottle and dispense enough of this medium around all the cloning cylinders without touching or moving them (Figure 3 and Video 1). One must pay attention not to drop Tissue-tek inside the cylinder. Tissue-tek is a viscous, sticky, high-density liquid; thus, one does not need any time to immobilize the cloning cylinder.
Figure 3. Tissue-tek mediated immobilization of cloning cylinders. A. A snapshot shows the bottle of embedding fluid, named Tissue-Tek®. B. The pictorial depiction shows the cloning immobilization of the cylinders by surrounding them with Tissue-tek (in yellow).
Video 1. Placing of cloning cylinder and their immobilization with Tissue-tek.
Add 100 μL of pre-warmed trypsin (0.05%) to fill the cavity of each cloning cylinder (Figure 4). Place the back of the culture dish lid and keep it aside for 2–4 min (in the TC laminar hood). During this incubation, start arranging the parent and the copy 6-well plates in parallel (Figure 5).
Note: The concept of parent and copy plates is similar to that of bacterial replica plating. The copy plate will be utilized for initial characterization, and then a selected number of desired clones will be amplified from the parent plate.
Figure 4. Micro-trypsinization of colonies in cloning cylinders. Pictorial representation showing the cloning cylinders surrounded by Tissue-tek (yellow) before or during trypsinization of the colonies. Trypsin is shown in red.
Figure 5. Seeding of cells in Parent and Copy plates. A. Labeling pattern of a 6-well plate. B. Scheme shows the transfer of a cell suspension from the cloning cylinder to the indicated wells of the parent or the copy plate.
After 2–4 min of incubation, use a microscope to verify if the cells have detached from the surface. Close monitoring of 2–3 colonies is more than enough.
Mix the trypsinized cell suspension by repeated pipetting with a 200 μL micropipette (usually, 2–3 times, to form a homogenous mixture of cells), and then transfer the cell suspension from the cloning cylinder to the 6-well parent (approximately 30 μL) and copy (approximately 70 μL) plate. This will ensure that enough cells are transferred and simultaneously prevents accidental mix-up of clones. Repeat this for all other cylinders, one by one. Keep on maintaining the parent plate under antibiotic selection. However, to ensure stable clone selection, the copy plate can be devoid of selection at this stage.
Note: Ensure the proper labeling of wells like (P1, P2…… and C1, C2…….). In addition, ensure that you transfer the cell suspension accurately in the parent and the respective copy well without any error.
Transfer the plates to the TC incubator and maintain them as described in Step A2.
Change the exhausted medium every other day.
Most copy plate wells will be confluent within 3–5 days. These cells can be harvested and frozen at -80 °C for a suitable time, or proceed directly to Part E.
Keep monitoring the growth of the parent plates. Once these wells become confluent, trypsinize and freeze them in appropriately marked cryotubes in the freezing medium (see Recipes).
Representative data Part D: To generate the SIRT1-/- Hela cells, cloning cylinders were placed on the well-separated colonies. After the desired number of cloning cylinders was secured, these were immobilized by the addition of Tissue-tek on the outside of these cylinders (Figure 6A). After immobilizing these cylinders, pre-warmed trypsin was used to dissociate the cells from the colonies surrounded using cloning cylinders (Figure 6B).
Figure 6. Cloning cylinders surround Hela cell colonies. A. Representative image showing the immobilized cloning cylinders surrounding the colonies of Hela cells. B. The representative image shows the trypsinization of colonies in immobilized cloning cylinders.
Testing of gene expression or gene editing
The harvested cells can be processed to analyze the outcome, such as CRISPR-based knock-out or the stable expression of any factor. This part will use immunoblotting to determine if the desired result is achieved. For this, the below-given steps can be followed:
Resuspend the cell pellet in ice-cold lysis buffer (please see Recipes section) supplemented with protease inhibitors to a final concentration of 1×.
Incubate the tubes on ice for 20 min, for complete lysis of the harvested cells.
Now centrifuge the tubes at 14,000 rpm (20,800 rcf) at 4 °C for 15 min.
Collect the supernatant of the lysate in pre-labeled tubes for immunoblotting. Simultaneously, prepare the lysate from untransfected control cells for comparison of the expression pattern.
Quantify the total protein content of these lysates.
Note: This method used the Protein assay dye concentrate as a protein quantification reagent. However, other protein quantification methods or reagents can quantify total protein content.
Load and run the SDS-PAGE with approximately 20 μg of the total lysate and analyze it for the desired expression pattern, using the appropriate antibody.
Note: The detailed protocol on SDS-PAGE can be found in the following references (Al-Tubuly, 2000; Hellewell, 2017).
Data analysis
We selected 14 colonies and analyzed them for SIRT1 expression. The mentioned SIRT1 gRNA was directed around the Exon-1 of the human SIRT1 gene. Therefore, a complete absence of SIRT1 protein was expected in homozygous clones. Similarly, the heterozygous clones were expected to present a decreased expression of SIRT1. Upon immunoblotting of the copy colonies, we observed that colony numbers 2, 3, 5, 8, 9, and 11 were SIRT1-/- Hela cells, whereas colony numbers 1, 4, 6, 7, 10, 12, 13, and 14 were originated from SIRT1+/+ or SIRT1+/- cells (Figure 7).
Figure 7. Immunoblotting of the Hela cell genome-edited clones. Representative immunoblot showing the SIRT1 bands detected in the lysates of the wild-type (control) or gSIRT1 edited Hela clones (colonies 1 to 14). The blue dotted line represents two independent but simultaneously performed immunoblots. β-Actin serves as a loading control.
Recipes
Tris-Glycine SDS-PAGE running buffer (5×)
Reagent Final concentration Amount
Tris-base 125 mM 15.1 g
Glycine 1.25 M 94 g
SDS 0.5% 5 g
H2O n/a to 1,000 mL
Lysis buffer (Store at 4 °C for up to 1 month)
Reagent Final concentration Amount
NaCl (5 M) 150 mM 3 mL
Tris-HCl (1 M, pH 8.0) 50 mM 5 mL
EDTA (0.5 M, pH 8.0) 5 mM 1 mL
NP-40 (IGEPAL CA-630) 1% 1 mL
Sodium deoxycholate (10%) 0.5% 5 mL
Sodium dodecylsulfate (SDS; 10%) 0.1% 1 mL
H2O n/a to 1,000 mL
Keep ice cold. Just before use, supplement (1×) it with a Protease inhibitor cocktail (100×).
Basal cell culture medium (Store at 4 °C up to 4 months)
Reagent Final concentration Amount
DMEM (1 g/L D-Glucose) 1× 440 mL
Fetal bovine serum 10% 50 mL
Penicillin/Streptomycin (100×) 1× 5 mL
L-Glutamine (100×) 1× 5 mL
Total n/a 500 mL
Pre-warm to 37 °C before use.
Cell freezing medium
Reagent Final concentration Amount
Basal cell culture medium 80% 8 mL
Fetal bovine serum 10% 1 mL
DMSO 10% 1 mL
5× SDS PAGE Loading dye or Laemmli’s buffer
Reagent Final concentration
Tris-Cl buffer (pH 6.8) 250 mM
SDS (electrophoresis grade) 10% (w/v)
Bromophenol blue 0.5% (w/v)
Glycerol 100 mM
DTT or β-ME 10% (w/v)
Note: Loading buffer lacking thiol reagents can be stored at room temperature. Add the thiol reagent from 1 M (DTT) or 14 M (β-ME) stocks just before use.
Acknowledgments
This study was supported by the Deutsche Forschungsgemeinschaft (SFB 1118 & GRK 1874-DIAMICOM). We thank all members of our group and the ALMF/EMBL for their support. This protocol was established to generate the clones used in the following publications: Kumar et al. (2017), Kumar et al. (2020), Madhavan et al. (2021a), and Madhavan et al. (2021).
Competing interests
The authors declare no competing financial interests. Correspondence and requests for materials should be addressed to V.K. ([email protected] or [email protected]).
References
Al-Tubuly, A. A. (2000). SDS-PAGE and Western Blotting. Methods Mol Med 40: 391-405.
Aranda, A., Bezunartea, J., Casales, E., Rodriguez-Madoz, J. R., Larrea, E., Prieto, J. and Smerdou, C. (2014). A quick and efficient method to generate mammalian stable cell lines based on a novel inducible alphavirus DNA/RNA layered system. Cell Mol Life Sci 71(23): 4637-4651.
Condreay, J. P., Witherspoon, S. M., Clay, W. C. and Kost, T. A. (1999). Transient and stable gene expression in mammalian cells transduced with a recombinant baculovirus vector. Proc Natl Acad Sci U S A 96(1): 127-132.
Delrue, I., Pan, Q., Baczmanska, A. K., Callens, B. W. and Verdoodt, L. L. M. (2018). Determination of the Selection Capacity of Antibiotics for Gene Selection. Biotechnol J 13(8): e1700747.
Giuliano, C. J., Lin, A., Girish, V. and Sheltzer, J. M. (2019). Generating Single Cell-Derived Knockout Clones in Mammalian Cells with CRISPR/Cas9. Curr Protoc Mol Biol 128(1): e100.
Hellewell, A. L., Rosini, S. and Adams, J. C. (2017). A Rapid, Scalable Method for the Isolation, Functional Study, and Analysis of Cell-derived Extracellular Matrix. J Vis Exp(119): 55051.
Kumar, V., R. Agrawal, A. Pandey, S. Kopf, M. Hoeffgen, S. Kaymak, O. R. Bandapalli, V. Gorbunova, A. Seluanov, M. A. Mall, S., et al. (2020). Compromised DNA repair is responsible for diabetes-associated fibrosis.EMBO J 39(11): e103477.
Kumar, V., T. Fleming, S. Terjung, C. Gorzelanny, C. Gebhardt, R. Agrawal, M. A. Mall, J. Ranzinger, M. Zeier, T. Madhusudhan, S., et al. (2017). Homeostatic nuclear RAGE-ATM interaction is essential for efficient DNA repair.Nucleic Acids Res 45(18): 10595-10613.
Madhavan, B. K., Han, Z., Singh, B., Bordt, N., Kaymak, S., Bandapalli, O. R., Kihm, L., Shahzad, K., Isermann, B., Herzig, S., Nawroth, P. and Kumar, V. (2021). Elevated Expression of the RAGE Variant-V in SCLC Mitigates the Effect of Chemotherapeutic Drugs. Cancers (Basel) 13(11): 2843.
Madhavan, B. K., Z. Han, A. Sickmann, R. Pepperkok, P. P. Nawroth and V. Kumar (2021). A laser-mediated photo-manipulative toolbox for generation and real-time monitoring of DNA lesions. STAR Protoc 2(3): 100700.
Simon, M., Van Meter, M., Ablaeva, J., Ke, Z., Gonzalez, R. S., Taguchi, T., De Cecco, M., Leonova, K. I., Kogan, V., Helfand, S. L., et al. (2019). LINE1 Derepression in Aged Wild-Type and SIRT6-Deficient Mice Drives Inflammation. Cell Metab 29(4): 871-885 e875.
Singh, A. M. (2019). An Efficient Protocol for Single-Cell Cloning Human Pluripotent Stem Cells. Front Cell Dev Biol 7: 11.
Soutoglou, E. and Misteli, T. (2008). Activation of the cellular DNA damage response in the absence of DNA lesions. Science 320(5882): 1507-1510.
Toiber, D., Erdel, F., Bouazoune, K., Silberman, D. M., Zhong, L., Mulligan, P., Sebastian, C., Cosentino, C., Martinez-Pastor, B., Giacosa, S., et al. (2013). SIRT6 recruits SNF2H to DNA break sites, preventing genomic instability through chromatin remodeling. Mol Cell 51(4): 454-468.
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1 Q&A
Thanks for suggesting this easy and efficient way of isolating colonies. However, the tissue-tek isn't sterile. Will the cell culture get contaminate?
1 Answer
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May 18, 2023
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4,491 | https://bio-protocol.org/en/bpdetail?id=4491&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Combination of Sterile Injury and Microbial Contamination to Model Post-surgical Peritoneal Adhesions in Mice
JB Julia Bayer
DS Deborah Stroka
PK Paul Kubes
DC Daniel Candinas
JZ Joel Zindel
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4491 Views: 1590
Reviewed by: Zinan ZhouFereshteh AzediDivya Murthy
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Original Research Article:
The authors used this protocol in Nature Communications Dec 2021
Abstract
Abdominal surgeries are frequently associated with the development of post-surgical adhesions. These are irreversible fibrotic scar bands that appear between abdominal organs and the abdominal wall. Patients suffering from adhesions are at risk of severe complications, such as small bowel obstruction, chronic pelvic pain, or infertility. To date, no cure exists, and the understanding of underlying molecular mechanisms of adhesion formation is incomplete. The current paradigm largely relies on sterile injury mouse models. However, abdominal surgeries in human patients are rarely completely sterile procedures. Here, we describe a modular surgical procedure for simultaneous or separate induction of sterile injury and microbial contamination. Combined, these insults synergistically lead to adhesion formation in the mouse peritoneal cavity. Surgical trauma is confined to a localized sterile injury of the peritoneum. Microbial contamination of the peritoneal cavity is induced by a limited perforation of the microbe-rich large intestine or by injection of fecal content. The presented protocol extends previous injury-based adhesion models by an additional insult through microbial contamination, which may more adequately model the clinical context of abdominal surgery.
Graphical abstract:
Keywords: Post-surgical adhesion Microbe contamination Peritoneum Mice Surgery Peritoneal button Cecal ligation and puncture Peritoneal adhesion index
Background
Abdominal surgeries are lifesaving procedures. However, they can lead to post-surgical peritoneal adhesions, a fibrotic complication that arises from any insults within the peritoneal cavity. The peritoneal cavity and its organs are lined by the peritoneum, comprising a protective monolayer of mesothelial cells and subjacent connective tissue. Normally, the peritoneum provides a frictionless surface to ensure that intra-abdominal organs, such as the intestines, can move freely. However, the movement of organs is compromised in patients suffering from peritoneal adhesions. These are intra-abdominal scar bands forming between the abdominal wall and abdominal organs (Ellis et al., 1999; Hellebrekers and Kooistra, 2011; Zwicky et al., 2021). Peritoneal adhesions lead to severe adhesion-related complications, such as small bowel obstruction, chronic pelvic pain, and secondary infertility in women (Hellebrekers and Kooistra, 2011; Zwicky et al., 2021). This poses a major health burden for patients and challenges our health care systems (van Goor, 2007; ten Broek et al., 2013). Adhesion-related complications in the US health care system alone cost several billion dollars per year to treat (Sikirica et al., 2011). Currently, the only approved treatment for adhesions is the use of so-called anti-adhesive barriers. These are biocompatible barrier materials that can be inserted after abdominal surgery resulting in a slight reduction of adhesions. However, the beneficial effect of anti-adhesive barriers for patients is limited and does not rely on a specific molecular mechanism; thus, their regular use in daily practice is not supported (ten Broek et al., 2014; Huang and Ding, 2019; Strik et al., 2019; Fatehi Hassanabad et al., 2021). As such, it is essential to investigate the underlying molecular mechanisms of adhesion formation to develop specific prevention and treatment options in the future.
The current paradigm of adhesion formation states that peritoneal injury induces inflammation and coagulation, resulting in fibrin deposition (Hellebrekers and Kooistra, 2011). More recent results suggest that fibrin deposition may be accompanied by an aggregation reaction of GATA6+ peritoneal macrophages (Zindel et al., 2021b). The resulting clot of fibrin and macrophages is proposed to transform into stable adhesions by the process of extracellular matrix deposition by myofibroblasts (Fischer et al., 2020; Sandoval et al., 2016; Zindel et al., 2021a; Zwicky et al., 2021). This paradigm is largely based on results gained from research in rodents using surgical injury models. The most commonly used models have been described and reviewed elsewhere (Oncel et al., 2005; Whang et al., 2011; Kraemer et al., 2014; Bianchi et al., 2016; Sandoval et al., 2016; Tsai et al., 2018; Fischer et al., 2020; Zindel et al., 2021b). In mice, the predominant adhesion model includes the creation of a sterile, ischemic, button-shaped injury of the peritoneum. This model has been referred to as the peritoneal button (PB) model. Other models include the induction of peritoneal injury by abrasion, diathermia, or by introducing sterile foreign material. In summary, all these models rely on sterile peritoneal injuries to induce and study adhesion formation. However, peritoneal insult in clinical abdominal surgeries differs from those standardized, sterile mouse models. Most importantly, surgical trauma to the peritoneum may be accompanied by an acute microbial contamination. This frequently happens when small amounts of intestinal microbes are spilled during the resection and reconstruction phases of abdominal surgery procedures. In fact, a clinical study has linked bacterial peritonitis to an increased risk of subsequent admission due to post-surgical adhesions (Parker et al., 2005).
In a recent paper, we tested the hypothesis that sterile peritoneal injury and microbial contamination independently trigger adhesion formation (Zindel et al., 2021a). First, we confirmed that the PB model of sterile injury (Zindel et al., 2021b) reproducibly led to peritoneal adhesions. Interestingly, a similar amount of adhesions was induced using a modified cecal ligation and puncture (CLP) model. Unlike the standard CLP, which is widespread in sepsis research (Hubbard et al., 2005; Rittirsch et al., 2009; Dejager et al., 2011), in the modified CLP only a small part of the cecum was ligated. This decreased the amount of microbial contamination resulting in a non-lethal septic insult to the peritoneal compartment, which reproducibly led to the formation of peritoneal adhesions. Importantly, the combination of PB and CLP resulted in significantly more adhesions than each procedure alone, indicating that sterile injury and microbes synergistically trigger events that lead to adhesion formation. Surgical induction of bacterial contamination was further found to be interchangeable with administration of native or heat-inactivated cecal slurry (CS) (Starr et al., 2014) during laparotomy, resulting in comparable adhesion scores. In summary, we found that sterile injury and microbial contamination independently and synergistically cause peritoneal adhesions.
Here, we describe in detail the surgical procedures used in our previous publication (Zindel et al., 2021a). We show how adhesions can be caused by a modular system of surgically induced insults. These modules comprise peritoneal injury (PB), microbial contamination (CLP or CS), or a combination thereof (Figure 1A–C). We further describe how adhesions can be quantified using a clinical scoring system (Figure 1D, Table 1). Compared to preexisting methodologies of adhesion mouse models, the presented protocol is extended by the factor of intraperitoneal microbial contamination, an important driver of post-surgical adhesions (Zindel et al., 2021a). Apart from the use in post-surgical adhesion studies, we suggest that adapted forms of the presented modular mouse system could be applied in other research areas, such as abdominal infection or chronic pelvic pain research.
Table 1. Peritoneal adhesion index (PAI)
Grade Description Explanation
0
1
2
3
None
Flimsy
Dense
Fibrotic/Vascularized
Peritoneal button (PB) is free and covered with mesothelium
Adhesion separates spontaneously when opening the peritoneal cavity
Adhesion separates bluntly, without bleeding
Adhesion needs sharp dissection, visible vascularization, bleeding occurs upon dissection
4 Complete PB is completely covered by adhesion; dissection results in organ damage
Figure 1. Overview of the proposed modular surgery model system for peritoneal adhesion induction in mice. A. Localized sterile surgical trauma is induced by generating one peritoneal button (PB) per abdominal quadrant. B. Polymicrobial contamination is surgically induced by cecal ligation and puncture (CLP). C. Polymicrobial contamination is alternatively induced by peritoneal administration of cecal slurry (CS). Combinations of the modular components PB (A), CLP (B), and CS (C) are used to synergistically induce adhesion formation in the mouse peritoneal cavity. D. Within seven days post-surgery, peritoneal adhesion severity is scored at six different locations for tenacity and vascularization (Table 1). These locations are: the four PB (1–4), the midline incision (5), and adhesions that occur between intestines (6). At each scoring location, peritoneal adhesions are assigned a grade between 0 (minimum) and 4 (maximum) according to the criteria (Table 1). The sum of the six scores yields the total peritoneal adhesion index (PAI).
Materials and Reagents
C57BL/6JRccHsd mice (Envigo, Netherlands)
Note: Female and male mice, 8–12 weeks of age. After arrival at the facility, the mice are given seven days of acclimation. Mice are housed in specific-pathogen-free (SPF) conditions with a 12 h day-night cycle and ad libitum access to drinking water and standard chow diet (3432 Maintenance Vitamin-fortified, irradiated > 25 kGy, KLIBA NAFAG, 3432.PX.V20). The ambient room temperature is 20 ± 2 °C, and humidity is kept at 50 ± 10%.
Saline 0.9% (B. Braun Medical AG, Swissmedic: 29554)
Storage at room temperature. See manufacturer instructions for shelf-life.
Eye ointment (Vitamin A Blache, Bausch & Lomb Swiss AG, Swissmedic: 22398)
Storage at room temperature. See manufacturer instructions for shelf-life.
Cecal slurry, prepared as previously described (Starr et al., 2014)
Storage at -80 °C. Bacterial viability is maintained at 99.5% for up to six months (Starr et al., 2014).
Isoflurane (AttaneTM, Isoflurane ad us. vet., Provet AG, Piramal Critical Care, Swissmedic: 56761002)
Storage at room temperature. See manufacturer instructions for shelf-life.
Buprenorphine 0.3 mg/1 mL (Temgesic®, Indivior Schweiz AG, Swissmedic: 41931)
Storage at room temperature. See manufacturer instructions for shelf-life.
Fentanyl 0.1 mg/2 mL (Sintetica SA, Swissmedic: 53987)
Storage at room temperature. See manufacturer instructions for shelf-life.
Medetomidine 1 mg/1 mL (Medetor® ad us. vet., Virbac AG, Swissmedic: 58407002)
Storage at room temperature. See manufacturer instructions for shelf-life.
Midazolam 15 mg/3 mL (Dormicum®, CPS Cito Pharma Services GmbH, Swissmedic: 44448)
Storage at room temperature. See manufacturer instructions for shelf-life.
Triple mix (see Recipes)
70% ethanol (see Recipes)
Storage at room temperature.
Buprenorphine working solution (see Recipes)
Equipment
Suture material
Polypropylene suture 4-0 (1.5 Ph. Eur.) with RB-1 needle (Ethicon, catalog number: 8871H)
Polypropylene suture 6-0 (0.7 Ph. Eur.) with P-1 needle (Ethicon, catalog number: MPP8697H)
Polyglactin 910 suture 4-0 (1.5 Ph Eur.), absorbable (Ethicon, catalog number: V1224)
Needles and syringes
26 G × 3/8’’ needle (BD MicrolanceTM 3, catalog number: 300300)
25 G × 5/8’’ needle (BD MicrolanceTM 3, catalog number: 300600)
1 mL Luer lock syringe (BD PlastiPakTM, catalog number: 303172)
0.5 mL Insulin-50 syringe, G30 0.3 × 0.8 mm (Omican®, B. Braun Medical AG, catalog number: 9151117S)
Retraction system
Small base plate (20 × 30 cm) (Fine Science Tools, catalog number: 18200-03)
2 short fixators (Fine Science Tools, catalog number: 18200-01)
2 tall fixators (Fine Science Tools, catalog number: 18200-02)
Elastomer (2 m roll) (Fine Science Tools, catalog number: 18200-07)
2 blunt retractors (2.5 mm wide) (Fine Science Tools, catalog number: 18200-10)
2 sharp retractors (0.5 mm wide) (Fine Science Tools, catalog number: 18200-08)
Surgical instruments
Surgical scissors – ToughCut® (Fine Science Tools, catalog number: 14054-13)
Student fine scissors (Fine Science Tools, catalog number: 91461-11)
Adson forceps (Fine Science Tools, catalog number: 11027-12)
Delicate suture tying forceps (Fine Science Tools, catalog number: 11063-07)
Graefe forceps, 1*2 teeth (Fine Science Tools, catalog number: 11054-10)
Blunted forceps (e.g., Fine Science Tools, catalog number: 11651-10)
Crile hemostats (Fine Science Tools, catalog number: 13004-14)
Needle holder – Durogrip® (Aesculap, catalog number: BM012R)
Additional equipment
Steam indicator tape (3M Health Care, catalog number: 1322-24MM)
Autoclave (MELAG, MELAtronic® 23)
Scale (Mettler Toledo, catalog number: PE 2000)
Aesculap Isis rodent shaver (AgnTho’s, catalog number: GT421)
Heating pad (Beurer GmbH, catalog number: HK 40)
Surgical microscope
Surgical tape
Veterinary operating table heated mat (Peco Services, Mediheat V500DVstat)
Surgical drape, 45 × 37 cm (3M Health Care, catalog number: 9067)
Cellulose swaps (Cosanum AG, catalog number: 630045212044)
Anesthesia system (Rothacher Medical GmbH, Combi-vet®)
Note: The techniques described here usually result in a bloodless surgical procedure. Therefore, no cautery devices are needed in experienced hands. For inexperienced small animal surgeons, we recommend having a cautery device (e.g., Low Temperature Cautery Kit, FST Fine Science Tools, 18019-00) ready.
Procedure
Preparation of surgical equipment
Autoclave surgical instruments.
Note: Alternatively, surgical instruments can be submerged in 70% ethanol (3 min) and ddH2O (3 min) subsequently.
Clean work surface, heating plate, and retraction system with 70% ethanol.
Cover heating plate with 1–2 surgical drapes and adjust heating plate temperature to 37 °C.
Prewarm buprenorphine (0.05 mg/mL working solution) to 37 °C on heating plate.
Arrange surgical equipment (Figure 2A–2C).
Note: Hemostat opening width is maximized to approximately 5 mm (tip distance). This facilitates generation of equally sized peritoneal buttons. The labels on Adson forceps’ handles assist in the formation of peritoneal buttons at distinct sites of the parietal peritoneum (Figure 2B).
Anesthesia and pre-surgical preparations
Weigh mouse and note down body weight.
Place the mouse into induction chamber for anesthesia with 5% v/v isoflurane in medical oxygen (1.2 L/min).
Place the anesthetized mouse on surgical drape/heating plate to prevent hypothermia and maintain anesthesia with 2.5% v/v isoflurane in medical oxygen (1.2 L/min) via the nose cone.
Note: Assess anesthetic depth by toe and eye reflex. If necessary, adjust percentage v/v isoflurane. Monitor the respiratory rate of the mouse during entire surgical procedure. If necessary, adjust percentage v/v isoflurane.
Apply 0.1 mg/kg body weight pre-warmed buprenorphine (0.05 mg/mL working solution) by subcutaneous (s.c.) femoral injection.
Apply eye ointment to prevent drying of the eyes.
Turn the mouse on its dorsal side and fixate the extremities with surgical tape to ensure proper tension and continuous anesthesia induction via the nose cone.
Place two cellulose swaps next to each side of the abdomen.
Shave the abdomen using the rodent shaver.
Remove the hair using the two cellulose swaps and remove additional hair using surgical tape.
Apply 70% ethanol to disinfect the shaved skin using cellulose swap.
Note: Apply ethanol sparingly on the shaved skin to reduce excessive heat loss.
Figure 2. Equipment and pre-surgery set-up. A. Surgical instruments and materials are set up on a heating plate covered with a sterile surgical drape. B. Distance marks are indicated on the handle of the Adson forceps for assistance during peritoneal button creation. Maximum opening distance of the hemostat is restricted to approximately 5 mm for assistance during peritoneal button formation. C. Listed items correspond to the respective letters in (A) and (B).
Surgical procedure
Laparotomy
Skin incision: perform a median vertical incision (approximately 25 mm) (Figure 3A):
Grasp the abdominal skin midline approximately 25 mm inferior to the xiphoid (Graefe forceps).
Extend the cut approximately towards, but no further than, the xiphoid (surgical scissors). Incision should be 25 mm or from pubic to xiphoid bone, whichever is shorter.
Note: Ensure not to penetrate into the peritoneal cavity at this step.
Perform a matching median vertical incision in the peritoneal wall (Figure 3B–3C):
Perforate the linea alba (e.g., by using fine scissors).
Note: Take care not to injure intra-abdominal organs. This can be achieved by pulling the abdominal wall up. As soon as the linea alba is perforated, air enters into the abdominal cavity, which separates the abdominal wall from the underlying organs.
The access through the linea alba is extended towards the symphysis and the xiphoid process to match the skin incision in length (fine scissors).
Notes:
1) Take care not to injure intra-abdominal organs. This can be ensured by pulling the peritoneal wall up while extending the cut.
2) The linea alba has no major blood vessels and this incision technique should not result in any visible bleeding. If bleeding occurs, one of the rectus abdomini muscles was likely injured. This can be salvaged by using diathermy. We use cellulose swabs only to clean the skin. We do not recommend using cellulose inside the peritoneal cavity at all, as this may influence adhesion formation that may be difficult to standardize.
After exposing the peritoneal cavity, place one retractor at each corner of the opening. Adjust distance of the fixators ensuring good access to the peritoneal cavity (Figure 3D).
Figure 3. Laparotomy. A. Median vertical incision is performed in the abdominal skin using surgical scissors and forceps. B. The abdominal wall is perforated through the linea alba (black arrow) using fine scissors. Gently pulling the abdominal wall up prevents intraperitoneal organ damage. C. Incision measures 25 mm (distance d) or from pubic to xiphoid bone, whichever is shorter. D. The peritoneal cavity is exposed by placing four retractors as displayed. Scale bar (A–D): 5 mm.
Adhesions are induced by three modular components (Figure 1A–C): Peritoneal buttons (PB), Cecal Ligation and Puncture (CLP), and Cecal Slurry (CS). Typical component combinations include: PB alone, PB + CLP, and PB + CS.
Module 1: Peritoneal button (PB) formation (Figure 1A)
Gently press the handle of the Adson forceps from outside to the peritoneal wall (Figure 4A).
Note: The assistance distance mark at the forceps handle is visible through the abdominal wall.
Clamp a portion (approximately 5 mm) of the parietal peritoneum 8–10 mm lateral from the incision in the first quadrant using the hemostat (Figure 4B–D).
Note: Labels at the forceps’ handle can help to standardize the location for the peritoneal button. Controlling maximum hemostat opening can facilitate formation of equally sized peritoneal buttons (see also Note A.5.).
Ligate the grasped portion with three subsequent surgical knots at its base using a polypropylene suture 4-0 (suture tying forceps, needle holder) (Figure 4E–F).
Carefully remove the hemostat (Figure 4G).
Repeat the described steps (C2a–d.) three additional times, resulting in one button in each peritoneal quadrant (Figure 4H).
Module 2: Cecal ligation and puncture (CLP) procedure (Figure 1B)
Carefully remove retractors.
Locate the cecum using blunt anatomic forceps or another blunt surgical tool (e.g., needle holder).
Note: The cecum is typically found in the left lower quadrant.
Gently mobilize the cecum and bring it in front of the abdominal wall (Figure 5A).
Ligate the cecum (2 mm) with a polyglactin 910 suture 4-0. Tie the suture tight with three subsequent surgical knots (suture tying forceps, needle holder) (Figure 5B–C).
Note: Severity grade could theoretically vary by ligating different lengths of the cecum. However, increasing the length of the ligated cecum portion should be explicitly stated in the research protocols submitted to the authorities, as this may result in significant morbidity and mortality for the animals.
Perforate the ligated cecum using a 25 G needle by a single through-and-through puncture (Figure 5D).
Remove the needle.
A small portion of feces from both puncture sides exits the ligated cecum.
Relocate the cecum into the abdominal cavity.
Figure 4. Surgical peritoneal button formation. A. Gently pressing the handle of the Adson forceps against the abdominal wall allows access to the peritoneum. Distance marks (black arrow, blue line) support standardized peritoneal button formation. B. The hemostat is used to clamp a 5 mm section (distance d) of the peritoneal wall. C. Clamped peritoneum portion. D. Gentle retraction of the hemostat ensures good access for suture tying. E–F. Three consecutive surgical knots are created at the base of the clamped peritoneum portion using a polypropylene suture 4-0. G. Peritoneal button in the upper right quadrant. H. Two out of four peritoneal buttons are displayed (white arrows). Scale bar (A–H): 2.5 mm.
Figure 5. Surgical cecal ligation and puncture. A. Exteriorized cecum. B–C. Cecal ligation is performed at 2 mm distance (distance d) from the apex ceci using a polyglactin 910 suture 4-0. Three consecutive surgical knots are utilized. D. Perforation of the ligated cecum portion is achieved by a single through-and-through puncture using a 25 G needle. Abbreviations: ce = cecum. Scale bar (A–D): 2 mm.
Module 3: Cecal slurry (CS) administration (Figure 1C)
Thaw frozen CS in 37 °C water bath.
Mix CS thoroughly.
Optional: Heat inactivation of CS is performed by 20 min incubation at 72 °C.
Administer 100 μL CS (native or heat-inactivated) or the respective control directly into the open peritoneal cavity using a 1 mL syringe or a P200 pipette.
Note: Fluid volumes of up to 100 μL can usually be pipetted into the peritoneal cavity without compromising the subsequent closure of the abdominal cavity. If this approach leads to contamination of the surgical incision site, CS can also be administered using a 0.5 mL insulin-50 syringe after closing the abdominal wall.
Carefully remove retractors.
Wound closure
Close the muscular peritoneal wall and the skin with an all-layer running suture (polypropylene suture 6-0, (suture tying) forceps, needle holder).
Note: The integrity of this running suture and the respective knots is absolutely paramount. Suture failure can lead to wound infection or a burst abdomen resulting in significant suffering and death. We recommend formal small rodent surgery training for all investigators prior to commencing experiments.
Post-surgical monitoring
Carefully remove the fixation tape and the nose cone.
Place the mouse back in its cage, which is placed on a heating pad.
Monitor mice according to the protocol approved by authorities. In our hands, pre-surgically untreated mice (C57BL/6 background) did not develop sepsis. Nonetheless, since sepsis might occur in the hands of others or when mice are treated with immunocompromising regimens prior to surgery, we strongly recommend monitoring for signs of sepsis [e.g., murine sepsis score (Shrum et al., 2014)], in addition to a standard pain score sheet.
Adhesion assessment (post-surgical day 7)
Work space preparations:
Clean work surface with 70% ethanol.
Cover work surface with surgical drapes.
Prepare autoclaved surgical instruments, fresh cellulose swaps, and surgical tape.
Weigh mouse and note down body weight.
Anesthetize mouse by s.c. injection of Triple mix (see Recipes, dosage for terminal experiments 6 μL/g body weight) using a 0.5 mL insulin-50 syringe.
Assess anesthetic depth by toe and eye reflex approximately 15 min after injection. As soon as reflexes are lost, the mouse can be transferred to the surgical drape.
Turn the mouse on its dorsal side and fixate the extremities with surgical tape to ensure proper tension.
Apply 70% ethanol to disinfect the abdominal skin using cellulose swap.
Expose the peritoneum around the midline suture by removing the skin from the parietal side towards the midline with a U-shape incision (surgical scissors, Adson forceps).
Access the abdominal cavity using an inverted U-shape incision (fine scissors, blunted forceps).
Note: Use different sets of surgical instruments for steps E7 and E8 to keep the abdominal cavity free of hair.
Adhesions (Figure 6A–F) are scored by two different observers according to the selected adhesion scoring method, in this case the peritoneal adhesion index (PAI) scheme (Figure 1D, Table 1). The PAI score is a composite score based on previously published adhesion scores evaluating adhesion tenacity and vascularization (Mazuji, 1964; Nair, 1974; Zühlke et al., 1990; Coccolini et al., 2013). The total PAI aggregates the individual adhesion scores from six separate locations: PB 1st quadrant, PB 2nd quadrant, PB 3rd quadrant, PB 4th quadrant, midline incision, and interintestinal. Each location score ranges from grade 0 (minimum) to grade 4 (maximum). Consequently, the total PAI per mouse can attain values from 0 (minimum) to 24 (maximum). In Figure 6A–F examples of adhesions assessed at post-surgery day 7 are displayed:
Grade 0: no adhesion (Figure 6A)
Grade 1: flimsy adhesion (Figure 6B)
Grade 2: dense adhesion (Figure 6C)
Grade 3: fibrotic and vascularized adhesion (Figure 6D)
Grade 4: complete adhesion (Figure 6E–F)
If required, tissue biopsies, such as peritoneal buttons and peritoneal adhesions, can be collected for further investigation, for example histological analyses or flow cytometry.
Figure 6. Peritoneal adhesion assessment using the peritoneal adhesion index (PAI). A. Peritoneal button (white arrow) is free and covered with mesothelium. Corresponds to grade 0 of the PAI scale. B. A flimsy adhesion connects the peritoneal button (white arrow) to the omentum, but separates spontaneously during the process of peritoneal cavity opening. Corresponds to grade 1 of the PAI scale. C. A dense adhesion connects the peritoneal button (white arrow) to the omentum and separates bluntly without bleeding. Corresponds to grade 2 of the PAI scale. D. A fibrotic and slightly vascularized adhesion connects the peritoneal button (white arrow) to the omentum. Upon dissection, bleeding occurs. Corresponds to grade 3 of the PAI scale. E. The peritoneal button (white arrow) is completely covered (only the suture reveals its location) by the adhesion connecting the mesentery to the abdominal wall. Corresponds to grade 4 of the PAI scale. F. A complete adhesion connects parts of the midline incision (black arrow) to peritoneal cavity organs, including cecum and intestine. Dissection results in organ damage. Corresponds to grade 4 of the PAI scale. Abbreviations: adh = adhesion; aw = abdominal wall; ce = cecum; in = intestine; me = mesentery; om = omentum. Scale bar (A-F): 1.5 mm.
Data analysis
Detailed information on data analyses are provided in the original, open-access publication (Zindel et al., 2021a). In brief, adhesions in mice that underwent the herein described surgical procedures (PB alone, CLP alone, PB + CLP, PB + CS) were assessed according to the PAI at post-surgical day 7. As shown in Figure 1d of the original research article, PB alone as well as CLP alone successfully induced peritoneal adhesions to similar extent. The combination of the two surgical procedures, PB and CLP, led to significantly higher peritoneal adhesion scores compared to when each procedure was applied individually. In Supplemental Figure 1e of the original research article it is shown that the combinations PB + CLP and PB + CS result in comparable peritoneal adhesion scores. In our recent publication (Zindel et al., 2021a), data represent independent animals per group (n). We generally used non-parametric tests (Wilcoxon) with correction for multiple testing using R. Multiple testing was corrected using Holm’s sequential Bonferroni post-hoc test, and p = 0.05 was considered as the threshold of significance.
Notes
In the related paper (Zindel et al., 2021a), only female mice were used. However, since then, we have started to use both female and male mice. Our data do not suggest a systematic difference in adhesion formation between sexes using this model. To reduce bias, we recommend training the procedures until a steady state (i.e., low standard deviation) in surgery time, adhesion index, or other quality indicators is reached. Mean (± SD) operation time for experienced surgeons was 12.3 (± 1.5) min for PB + CLP procedure and 10.6 (± 1.0) min for PB + CS procedure (unpublished data, n = 46 and n = 18 independent mice per group). Some variability in the resulting adhesion formation (adhesion index) will remain even for well-standardized investigators. In our hands, median (IQR) adhesion index was 10 (3) for PB + CLP and 9 (3.25) for PB + CS [reported in Zindel et al. (2021a) Figure 1d-e, Figure S1e].
Recipes
70% ethanol
Reagent Final concentration Amount
Ethanol (absolute) 70% 700 mL
ddH2O n/a 300 mL
Total n/a 1000 mL
Buprenorphine working solution (dosage = 0.1 mg/kg body weight)
Reagent Final concentration Amount
Buprenorphine (0.3 mg/mL) 0.05 mg/mL 1 mL
NaCl 0.9% n/a 5 mL
Total n/a 6 mL
Triple mix (dosage for terminal experiment = 6 μL/g body weight)
Reagent Final concentration Amount
Fentanyl (0.05 mg/mL) 0.017 mg/mL 1 mL
Midazolam (5 mg/mL) 1.7 mg/mL 1 mL
Medetomidine (1 mg/mL)
Saline 0.9%
Total
0.17 mg/mL
n/a
n/a
0.5 mL
0.5 mL
3 mL
Acknowledgments
This work is based on our previous publication in Nature Communications (Zindel et al., 2021a). Funding was provided by Swiss National Science Foundation (P1BEP3_181641) and by an early career grant by the Department of Teaching and Research, Insel Gruppe AG. We thank T. Nussbaumer and R. Tombolini for the breeding and husbandry of mice. We further thank R. Tombolini for lab management and technical support with surgical models. We thank F. Baier for providing us with specialized camera equipment and technical instruction for surgery documentation. We thank A. Keogh for his linguistic support.
Competing interests
The authors declare no competing interests.
Ethics
Animal experiments in Switzerland were carried out in accordance with Swiss federal regulations and were approved by the cantonal committee on animal experimentation in Bern, Switzerland (BE 18/17 and BE 55/18). Animal experiments conducted in Canada were in accordance with Canadian legislation and policies and approved by the institutional animal care committee of the University of Calgary in Calgary, Canada (AC19-0148 JZ-PA).
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4,492 | https://bio-protocol.org/en/bpdetail?id=4492&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Aerotaxis Assay in Caenorhabditis elegans to Study Behavioral Plasticity
QL Qiaochu Li
DM Daniel-Cosmin Marcu
PD Paul H. Dear §
KB Karl Emanuel Busch
(§Deceased)
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4492 Views: 1245
Reviewed by: Sunanda MarellaAnnika NicholsEinav Gross
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Original Research Article:
The authors used this protocol in eLIFE Nov 2020
Abstract
C. elegans shows robust and reproducible behavioral responses to oxygen. Specifically, worms prefer O2 levels of 5–10% and avoid too high or too low O2. Their O2 preference is not fixed but shows plasticity depending on experience, context, or genetic background. We recently showed that this experience-dependent plasticity declines with age, providing a useful behavioral readout for studying the mechanisms of age-related decline of neural plasticity. Here, we describe a technique to visualize behavioral O2 preference and its plasticity in C. elegans, by creating spatial gradients of [O2] in a microfluidic polydimethylsiloxane (PDMS) chamber and recording the resulting spatial distribution of the animals.
Keywords: C. elegans Oxygen Aerotaxis Oxygen-sensing neurons Experience-dependent plasticity Aging Microfluidics Behavioral assay
Background
C. elegans senses and responds to diverse environmental stimuli, including light, odors, temperature, touch, and environmental O2 and CO2. In addition, C. elegans can learn from and remember their previous culture environment and sensory experience (Ward, 1973; Hedgecock and Russell, 1975; Chalfie and Sulston, 1981; Bargmann and Horvitz, 1991; Cheung et al., 2005; Persson et al., 2009; Busch et al., 2012; Kodama-Namba et al., 2013; Fenk and de Bono, 2015). The mapped connectome of the nervous system and the profiled transcription of all 118 classes of neurons make C. elegans a powerful model to study the molecular and genetic mechanisms of neural plasticity. Worms increase their locomotory speed to move away from a high O2 environment (such as 21% O2), and slow down at lower [O2] of around 7% (Cheung et al., 2005; Persson et al., 2009; Busch et al., 2012). Four O2-sensing neurons in C. elegans, URX (a neuron pair) and AQR in the head, and PQR in the tail, are tonically activated by 21% O2 and show low activity for as long as they are exposed to 7% O2 (Busch et al., 2012). Tonic activity of these neurons is necessary and sufficient to set the behavioral state according to the ambient O2 concentration for many minutes and even hours. The behavioral responses to O2 change dynamically according to environmental context, previous culture conditions, and age (Li et al., 2020).
Here, we describe a technique to visualize the worms’ O2 preference in young and aged animals. We show that this assay can be applied to study behavioral plasticity, where animals shifted to a different O2 environment reprogram their O2 preference. We explain how to record aerotaxis behavior in spatial O2 gradients and how to calculate aerotaxis indices that reflect the behavioral plasticity and its change with age.
Materials and Reagents
Adhesive tape (Ultratape invisible tape, 19 mm wide)
Worm pick
50 mL Luer syringes (BD Medical, catalog number: 300865)
3-way Luer stopcocks (Kendall Argyle Ez-Flo, catalog number: 8888173518)
Needles (h-medical GmbH, BD Microlance 3, Intramedic Luer Stub adapter 23-gauge, catalog number: 300700)
Polyethylene Tubing, i.d. 0.58 mm (PE 50, BD Intramedic, catalog number: 427411)
55 mm plates (VWR, vented Petri dishes, catalog number: 391-0865)
90 mm plates (Fisherbrand Petri dishes 3-vent, catalog number: 12694785)
Liquid OP50 culture (bacterial stock gift from Julie Ahringer; 2×-YT growth medium stock from Formedium, catalog number: YDB24L; see Recipes)
C. elegans strain AX204 (npr-1(ad609)) cultured at 20 °C, genotype available from the Caenorhabditis Genetics Center (CGC) as strain DA609
Sodium chloride (Fisher Scientific, catalog number: S/3160/60)
BactoTM peptone (Becton Dickinson, catalog number: 211677)
Agar (Formedium, catalog number: AGA03)
Cholesterol (95% stabilized; ACROS Organics, catalog number: 110191000)
Calcium chloride (ACROS Organics, catalog number: 423520025)
Magnesium sulfate (ACROS Organics, catalog number: 213110025)
70% (v/v) ethanol in dH2O
dH2O
KH2PO4 (ACROS Organics, catalog number: 271080025)
K2HPO4 (ACROS Organics, catalog number: 424190025)
1 M KPO4 buffer pH 6.0 (see Recipes)
Nematode growth medium (NGM) agar plates (see Recipes)
Polydimethylsiloxane (PDMS) chamber design
Film photomask (JD Photo Data)
SU-8 2150 photoresist (MicroChem, SU-8 200 Series)
PDMS prepolymer mixture (Dow Corning, Sylgard 184 Silicone Elastomer, material number: 101697)
Scalpel
20-gauge stub adapter (BD Intramedic, Luer-Stub Adapters, catalog number: 22-044086)
Polyethylene PE50 tubing, i.d. 0,58 mm (BD Intramedic, catalog number: 427411)
Access to a microfluidics facility (see also comment below)
Equipment
Dissecting stereomicroscope (Leica, model: S9D)
20 °C incubator (Termaks, model: KB8400)
37 °C shaker (Infors HT 1300002 Unitron Incubator Shaker)
Hypoxia chamber (Coy Laboratory Products, Glove box Coy O2 control 2 person polymer, model/catalog number: 8375280)
Syringe pump (World Precision Instruments, Aladdin, model: AL6000)
33.7 × 20.0 × 0.4 mm PDMS microfluidic assay chamber (see Figure 1 for detailed design). Chamber is stored at room temperature in a plastic container to avoid dust.
5.0 MP CMOS USB camera (PointGrey Research Inc. (now Teledyne FLIR), Grasshopper3, part no. GS3-U3-51S5M-C)
Gas cylinders with 21% O2 (BOC Special Gases, catalog number: 226723-L-B) and 7% O2 (BOC Special Gases, catalog number: 226828-L-C), each with nitrogen as balance gas and no addition of CO2
Plate spreader
Figure 1. Polydimethylsiloxane (PDMS) chamber design. A. Schematic illustration of designed PDMS chamber dimensions; the height of the resulting chambers varies between 0.2 and 0.4 mm, but a height of 0.4 mm is recommended for optimal gas flow. B. COMSOL 3.4 simulation, illustrating transition from turbulent flow near gas inlets of PDMS chamber to smooth flow as gas crosses between the chamber’s pillars. C. COMSOL 3.4 simulation, illustrating the smooth concentration gradient created by diffusion in the behavioral arena when gas mixtures with different concentrations of O2 are pumped in at either end of the chamber; overlay illustrates chamber division into nine equal grids for animal counting and aerotaxis index calculation. Color bar represents [O2] in the chamber. D. Top view photograph of PDMS chamber with PE50 tubing connected to gas inlets and outlets.
Software
Affinity Designer (Serif Europe, affinity.serif.com/designer/)
Microsoft Office Excel (Microsoft Corporation, Redmond, USA)
For PDMS chamber design
AutoCAD (Autodesk)
COMSOL Multiphysics (COMSOL Inc.)
Procedure
PDMS chamber design
We used soft lithography techniques to create the microfluidics device for behavioral analysis (Qin et al., 2010). We designed the PDMS chamber in AutoCAD (Autodesk) with overall dimensions of 33.7 × 20.0 × 0.4 mm (Figure 1A), of which the behavioral arena was an area in the center totaling 27 × 15 mm (AutoCAD file available on request). The dimensions of the behavioral arena allow for easy division into a 9-grid rectangle along the length of the PDMS chamber during the data analysis step of the experiment, resulting in grids of size 3 × 15 mm. The behavioral arena is bordered at either end across the longest dimension by an array of 64 pillars of size 0.85 × 0.155 × 0.4 mm. On either side beyond the pillars is an array of four evenly spaced holes acting as gas inlets (outer holes) and outlets (middle holes), so that the total distance between the two arrays of holes is 28.7 mm. The distance between pillars is roughly 0.08 mm, allowing for smooth (non-turbulent) airflow from the gas inlets into the PDMS chamber according to simulations performed in COMSOL Multiphysics 3.4 (COMSOL Inc., 2007) (Figure 1B). When gas mixtures at two different concentrations are pumped through the inlet pairs on either end of the PDMS chamber, this non-turbulent flow allows for a smooth concentration gradient to form inside the PDMS chamber (Figure 1C).
We printed the PDMS chamber design onto a film photomask (JD Photo Data) at 128,000 dpi with negative polarity. The polyester film photomask has a size of 10" × 12", a thickness of 0,18 mm, and is coated with an emulsion layer composed of gelatine, silver halide, and other chemicals. To make the master molds, we then spin-coated a silicon wafer with a 200-µm layer of SU-8 2150 photoresist (MicroChem, SU-8 2000 Series) at 2,000 r.p.m. for 30 s and patterned the resulting mold by photolithography. We then poured a 3 mm thick layer of PDMS prepolymer mixture (Dow Corning, Sylgard 184 Silicone Elastomer, Mat. No. 101697) over the mold and cured it for >1 day at room temperature. We then peeled the PDMS off the mold and cut off excess PDMS using a scalpel. Finally, we punched four inlets and four outlets with a 20-gauge stub adapter (BD Intramedic, Luer-Stub Adapters, catalog number: 22-044086) and connected the inlets with PE50 tubing (Figure 1D) to valves controlling the flow of different gas mixtures from a syringe pump.
If no access to a microfluidics facility is available, the PDMS chamber can be produced by a commercial foundry. Send an AutoCAD file to the company and specify the depth of the device, e.g., 100 µm. A list of companies that offer custom microfluidic chips can be found here: https://www.elveflow.com/microfluidics-research-horizon-europe/industrial-partner/microfluidic-foundries/.
Animal preparation
Seed 55 mm NGM plates with ~300 μL of liquid OP50 culture in the center of each plate and let them dry at room temperature two days before use.
For assaying 1-day-old adults: Pick 150–200 L4 stage animals the night before the assay onto an OP50 seeded NGM plate and culture animals at 21% (atmospheric) O2 in a temperature-controlled room at 20 °C; prepare at least two plates.
For assaying 7-day-old adults: Pick 150–200 L4 stage animals onto an OP50 seeded NGM plate and then transfer to newly seeded plates every 1–2 days, and culture animals at 21% O2 at 20 °C; prepare at least two plates.
The day before the assay, transfer half of the plates to hypoxia chamber (Figure 2) at 7% O2 at 20 °C. Hypoxia chamber setting: Humidity, 38%; O2 concentration, 7%.
Figure 2. Hypoxia chamber for worm culture.
Assay plate preparation
Two days before the assay, seed 90 mm NGM plates with 100 µL OP50 bacteria to form a thin bacterial food lawn, using a sterile plate spreader.
On the day of the assay, strip the lawn of OP50 from the area that will be outside of the PDMS chamber, by placing a block of PDMS on the agar where no bacteria are wanted and then lifting it. This way, bacterial food is only present inside the behavioral arena, which helps to reduce escaping of the worms from the PDMS chamber.
Equipment preparation
Clean the PDMS chamber at the start of each assay day by dipping it in 70% ethanol in dH2O, then remove the ethanol by dipping the chamber in dH2O. Inject air through the tubing to remove any residual liquid from the tubes and chamber and allow to dry. Residual bacteria and other dirt can be stripped from the chamber with adhesive tape. Between assays on the same day, clean the PDMS chamber with dH2O only and inject air through the tubing to remove any residual liquid. After the final assay of the day, clean the PDMS chamber with 70% ethanol in dH2O, then again with dH2O.
Before each assay, fill two 50 mL syringes with 7% O2, close the attached stopcock, then attach a 23-gauge Luer stub adapter to the tip of each syringe.
Before each assay, fill two 50 mL syringes with 21% O2, close the attached stopcock, then attach a 23-gauge Luer stub adapter to the tip of each syringe.
Aerotaxis assay
Transfer 100–150 animals to the assay plate; place the animals randomly next to the food lawn, but not directly on it.
Wait for 5 min until most animals have moved to the food lawn. Place a 30 × 15 × 0.2 mm PDMS microfluidic assay chamber over the animals.
Connect two syringes at each end of the inlet tubing of the PDMS chamber to pump 7% O2 or 21% O2, respectively, into the chamber at a pumping rate of 1.5 mL/min (Figure 3). After 30 min, record the location of animals in the chamber with a CMOS camera mounted on a stereo microscope with white light illumination from a transmitted light base, for distribution analysis and aerotaxis index quantification.
Open the images in Affinity Designer (or similar software such as Adobe Illustrator), and draw a rectangle with nine horizontal sections so that the image is equally divided into nine grids or bins from left to right (Figure 3). Count the animal number in each grid and record the numbers into an Excel file. If an animal appears across grids, count it into the grid containing the largest part of the animal’s body.
Figure 3. Aerotaxis assay setup. A. Schematic representation of gas delivery system to PDMS chamber during experiments. Worms of strain AX204 are placed underneath a PDMS chamber. An O2 gradient of 7%–21% is generated by pumping 7% and 21% O2 at opposite sides of the chamber at a flow rate of 1.5 mL/min with the help of a syringe pump. Residual air flows out of the chamber through two of the remaining free slots (black arrows). The last two slots are plugged, which does not affect the efficiency of the O2 gradient formation. The behavioral arena inside the PDMS chamber is divided into nine grids for animal counting and aerotaxis index calculation. B. Picture of PDMS chamber placed on 90 mm assay plate.
Data analysis
For each condition, the assay should be performed 6–8 times on at least two different days.
Calculate the mean and SEM of the number of animals in each grid over the 6–8 assays, and draw the distribution graph in Excel (Figure 4A, 4B).
Calculate the aerotaxis index as: (number of animals in high O2 area – number of animals in low O2 area)/total animal number (Figure 4C). For the experimental design in Figure 3, the low O2 area is considered as the four grids closest to the chamber end pumping 7% O2. The high O2 area is considered as the four grids closest to the chamber pumping 21% O2. The central grid is excluded from calculations. Alternative experimental designs (Gray et al., 2004; Chang et al., 2006; Oda et al., 2017) pump 0% O2 (nitrogen gas) and 21% O2 (air) at the low and high O2 ends, respectively. In such designs, the three grids closest to the end pumping 0% O2 are excluded from calculations, the central three grids are considered low O2, and the three grids closest to the end pumping 21% O2 are considered high O2. The basic formula for calculating the aerotaxis index remains the same.
Use the Mann–Whitney U test for statistical analysis (for details, see Li et al., 2020, Figure 1).
Figure 4. Representative data for 1- and 7-day old worms cultured at 21% O2. O2 preference of 1-day-old and 7-day-old AX204 adults cultured at 21% O2 and after animals were either kept at 21% O2 or shifted to 7% O2 for overnight culturing. In general, animals accumulate in the low (7%) O2 side, meaning that they prefer low O2 and avoid high O2. A. Day 1 adults shifted from 21% to 7% O2 for 12 h alter their O2 preference and accumulate in a narrower range of O2 near 7% compared to those kept at 21% O2 throughout. B. Day 7 adults also accumulate in the low O2 side, but shifting them to 7% O2 overnight does not reprogram their O2 preference. Mean ± sem, n=6–8 assays. C. Day 1 adults cultured at 21% show plasticity after shifted to 7% O2, whereas day 7 adults cultured at 21% O2 show no plasticity after shifted to 7% O2. Mean ± SEM, *p < 0.05, ns, p > 0.05, Mann-Whitney U test. Adapted from Li et al. (2020).
Notes
Use fresh OP50 culture to seed assay plates. Animals tend to avoid lawns seeded from old OP50 cultures, which will decrease the reliability of the assays. We usually use OP50 cultures not older than 7 days, if they were stored at 4 °C.
Animals need to be cultured on newly seeded OP50 plates, because the thick food lawn on older culture plates can affect the O2 concentration experienced by the worms. We usually seed plates and let them dry at room temperature two days before transferring.
Some studies (e.g., Gray et al., 2004; Chang et al., 2006) use the term “hyperoxia avoidance index” instead of “aerotaxis index.” The two are mathematically equivalent. However, there is no standardized definition for either term, and consideration should be given to the specific oxygen concentration ranges used in calculating the index in each study.
Recipes
1 M KPO4 buffer pH 6.0
108.3 g of KH2PO4, 35.6 g of K2HPO4, and dH2O to 1 L
Nematode growth medium (NGM) agar plates
Mix 17 g of agar, 2.5 g of peptone, 3 g of NaCl, and 975 mL dH2O; autoclave and cool to 55 °C.
Then add autoclaved solutions: 25 mL of KPO4 (1 M pH 6.0), 1 mL of CaCl2 (1 M), 1 mL of MgSO4 (1 M). Add 1 mL of filter-sterilized cholesterol (5 mg/mL cholesterol in ethanol).
Pour into plates (8.5 mL per 55 mm plate, and 13.0 mL per 90 mm plate) and store lid side down in a tightly closed box at room temperature or in a cold room.
Lid side down storage will reduce the amount of evaporation and dehydration the plates experience during storage. If storing in a cold room, allow plates to warm up to room temperature before seeding with OP50.
Liquid OP50 culture
Mix 31 g of 2×-YT broth with dH2O up to a total volume of 1 L.
Autoclave and cool to room temperature.
Aliquot in flasks, approximately 100 mL each.
Add one colony of OP50 E. coli bacteria streaked out on an agar plate to a flask of 2×-YT media, then secure the cap back onto the flask with tape without screwing tight (to allow air circulation while preventing spillage or contamination).
Incubate overnight at 37 °C on a shaker (180–200 rpm). Store upright in a refrigerator at 4 °C and use within 7 days.
Acknowledgments
This protocol was adapted from Li et al. (2020). The authors would like to acknowledge Mario de Bono for his support in developing the microfluidics device and aerotaxis assay. QL was supported by a University of Edinburgh Global Research Scholarship and a Principal’s Career Development Scholarship. The Wellcome Trust (109614/Z/15/Z) and the Medical Research Council (MR/ N004574/1) supported this work.
Competing interests
The authors declare no competing interests.
References
Bargmann, C. I. and Horvitz, H. R. (1991). Chemosensory neurons with overlapping functions direct chemotaxis to multiple chemicals in C. elegans. Neuron 7(5): 729-742.
Busch, K. E., Laurent, P., Soltesz, Z., Murphy, R. J., Faivre, O., Hedwig, B., Thomas, M., Smith, H. L. and de Bono, M. (2012). Tonic signaling from O2 sensors sets neural circuit activity and behavioral state. Nat Neurosci 15(4): 581-591.
Chalfie, M. and Sulston, J. (1981). Developmental genetics of the mechanosensory neurons of Caenorhabditis elegans. Dev Biol 82(2): 358-370.
Chang, A. J., Chronis, N., Karow, D. S., Marletta, M. A. and Bargmann, C. I. (2006). A distributed chemosensory circuit for oxygen preference in C. elegans. PLoS Biol 4(9): e274.
Cheung, B. H., Cohen, M., Rogers, C., Albayram, O. and de Bono, M. (2005). Experience-dependent modulation of C. elegans behavior by ambient oxygen. Curr Biol 15(10): 905-917.
Fenk, L. A. and de Bono, M. (2015). Environmental CO2 inhibits Caenorhabditis elegans egg-laying by modulating olfactory neurons and evokes widespread changes in neural activity. Proc Natl Acad Sci U S A 112(27): E3525-3534.
Gray, J. M., Karow, D. S., Lu, H., Chang, A. J., Chang, J. S., Ellis, R. E., Marletta, M. A. and Bargmann, C. I. (2004). Oxygen sensation and social feeding mediated by a C. elegans guanylate cyclase homologue. Nature 430(6997): 317-322.
Hedgecock, E. M. and Russell, R. L. (1975). Normal and mutant thermotaxis in the nematode Caenorhabditis elegans. Proc Natl Acad Sci U S A 72(10): 4061-4065.
Kodama-Namba, E., Fenk, L. A., Bretscher, A. J., Gross, E., Busch, K. E. and de Bono, M. (2013). Cross-modulation of homeostatic responses to temperature, oxygen and carbon dioxide in C. elegans. PLoS Genet 9(12): e1004011.
Li, Q., Marcu, D. C., Palazzo, O., Turner, F., King, D., Spires-Jones, T. L., Stefan, M. I. and Busch, K. E. (2020). High neural activity accelerates the decline of cognitive plasticity with age in Caenorhabditis elegans. Elife 9: e59711.
Oda, S., Toyoshima, Y. and de Bono, M. (2017). Modulation of sensory information processing by a neuroglobin in Caenorhabditis elegans. Proc Natl Acad Sci 114(23): E4658-E4665.
Persson, A., Gross, E., Laurent, P., Busch, K. E., Bretes, H. and de Bono, M. (2009). Natural variation in a neural globin tunes oxygen sensing in wild Caenorhabditis elegans. Nature 458(7241): 1030-1033.
Qin, D., Xia, Y. and Whitesides, G. M. (2010). Soft lithography for micro- and nanoscale patterning. Nat Protoc 5(3): 491-502.
Ward, S. (1973). Chemotaxis by the nematode Caenorhabditis elegans: identification of attractants and analysis of the response by use of mutants. Proc Natl Acad Sci U S A 70(3): 817-821.
Article Information
Copyright
Li et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
How to cite
Category
Neuroscience > Behavioral neuroscience > Animal model
Neuroscience > Behavioral neuroscience > Chemotaxis
Biological Sciences > Biological techniques
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4,493 | https://bio-protocol.org/en/bpdetail?id=4493&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
A Semi-quantitative Scoring System for Green Histopathological Evaluation of Large Animal Models of Acute Lung Injury
IS Iran A. N. Silva
NG Nika Gvazava
DB Deniz A. Bölükbas
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Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4493 Views: 2100
Reviewed by: Meenal SinhaJohnatas Dutra SilvaJulie WeidnerJennifer L. Larson-Casey
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Original Research Article:
The authors used this protocol in The American Journal of Physiology-Lung Cellular and Molecular Physiology Mar 2020
Abstract
Acute respiratory distress syndrome (ARDS) is a life-threatening, high mortality pulmonary condition characterized by acute lung injury (ALI) resulting in diffuse alveolar damage. Despite progress regarding the understanding of ARDS pathophysiology, there are presently no effective pharmacotherapies. Due to the complexity and multiorgan involvement typically associated with ARDS, animal models remain the most commonly used research tool for investigating potential new therapies. Experimental models of ALI/ARDS use different methods of injury to acutely induce lung damage in both small and large animals. These models have historically played an important role in the development of new clinical interventions, such as fluid therapy and the use of supportive mechanical ventilation (MV). However, failures in recent clinical trials have highlighted the potential inadequacy of small animal models due to major anatomical and physiological differences, as well as technical challenges associated with the use of clinical co-interventions [e.g., MV and extracorporeal membrane oxygenation (ECMO)]. Thus, there is a need for larger animal models of ALI/ARDS, to allow the incorporation of clinically relevant measurements and co-interventions, hopefully leading to improved rates of clinical translation. However, one of the main challenges in using large animal models of preclinical research is that fewer species-specific experimental tools and metrics are available for evaluating the extent of lung injury, as compared to rodent models. One of the most relevant indicators of ALI in all animal models is evidence of histological tissue damage, and while histological scoring systems exist for small animal models, these cannot frequently be readily applied to large animal models. Histological injury in these models differs due to the type and severity of the injury being modeled. Additionally, the incorporation of other clinical support devices such as MV and ECMO in large animal models can lead to further lung damage and appearance of features absent in the small animal models. Therefore, semi-quantitative histological scoring systems designed to evaluate tissue-level injury in large animal models of ALI/ARDS are needed. Here we describe a semi-quantitative scoring system to evaluate histological injury using a previously established porcine model of ALI via intratracheal and intravascular lipopolysaccharide (LPS) administration. Additionally, and owing to the higher number of samples generated from large animal models, we worked to implement a more sustainable and greener histopathological workflow throughout the entire process.
Keywords: Green histology Histological score system Acute lung injury Acute respiratory distress syndrome Large animal model
Background
Acute respiratory distress syndrome (ARDS) is a highly heterogeneous and life-threatening disease with reported mortality rates ranging from 30%–50% worldwide (Gonzales et al., 2015; Maca et al., 2017; Potere et al., 2020). Caused by a variety of infectious and non-infectious injuries (e.g., trauma, surgery, burn wounds, gastric aspiration, or inhalation of highly toxic substances), ARDS is characterized by diffuse alveolar damage that causes a rapid decline in lung function (Matthay et al., 2019). Infectious causes of ARDS may be direct lung injury through different pathogens, including viral (e.g., SARS-CoV-2), bacterial (e.g., Streptococcus pneumoniae), and fungal colonization (e.g., aspergillosis in mechanically ventilated patients). Additionally, ARDS also commonly results from indirect lung injury through systemic infection (e.g., urinary tract and soft tissue or skin infections), fragments of pathogens [e.g., lipopolysaccharide (LPS)], and inflammatory cytokines in sepsis patients (Lee, 2017).
The clinical diagnosis of ARDS uses the Berlin criteria, which consists of four main characteristics (ARDS Definition Task Force et al., 2012; Ferguson et al., 2012): 1) timing within one week of known injury or new/worsening respiratory symptoms; 2) presence of bilateral opacities consistent with pulmonary edema visible on chest imaging (X-ray or CT scan), which are not fully justified by lobar/lung collapse or nodules; 3) respiratory failure not fully justified by heart failure or fluid overload (hydrostatic edema has to be excluded); and 4) hypoxemia [partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ≤ 300mm Hg with positive end expiratory pressure (PEEP) or continuous positive airway pressure (CPAP) ≥ 5 cm H2O]. Compromised oxygenation levels can be further divided into three levels: Mild, Moderate, and Severe. Despite this improved classification system, ARDS remains a disease with high clinical heterogeneity, with no effective pharmacologic treatments.
While in vitro models recapitulating some features of ARDS exist, the use of both small and large animal models remains the main experimental tool for preclinical research. Several different models have been used to mimic the onset and development of acute lung injury (ALI), with the major factor differentiating them being the manner or source of injury. Different agents, such as oleic acid, lipopolysaccharide (LPS), gastric contents (or hydrochloric acid directly), hyperoxia, and bacterial or viral administration have all been shown to be capable of inducing acute lung injury as well as the use of high tidal volumes and low PEEP to induce ventilator induced lung injury (Ballard-Croft et al., 2012; Matute-Bello et al., 2008; Arora et al., 2019; Tiba et al., 2021). The choice of injury method and species used depends on the features to be investigated as well as the treatment modalities to be evaluated. As for many other diseases, small animal models using rodents have been widely explored due to their versatility, reproducibility, ease in model standardization, and use of genetically manipulated strains to help uncover disease pathomechanisms. However, the incorporation of clinical standard of care, such as mechanical ventilation, or more subspecialized care, such as extracorporeal membrane oxygenation (ECMO), is extremely challenging in rodent models; therefore, large animal models are most commonly used in these cases (Matute-Bello et al., 2011; Kulkarni et al., 2022).
Porcine models of ARDS have attracted interest because their size and general anatomy is similar to humans, allowing for clinically relevant interventions and measurement techniques (Ballard-Croft et al., 2012; Moodley et al., 2016). Furthermore, the Berlin criteria can be used to evaluate and confirm large animal models due to the fact that a) the timing and type of injury is known, b) the origin of edema can be confirmed by monitoring cardiac parameters and fluid support intake before injury onset, and c) oxygenation levels can be readily measured through serial blood gases. However, chest imaging using CT can be challenging to incorporate due to the short duration of injury models utilized for ARDS, lack of available equipment, or challenges with transport logistics (Hellbach et al., 2018). Therefore, the current gold standard to compensate for the absence of high-resolution chest imaging and to exclude other differential diagnoses is to confirm tissue level injury in animal models by examining the extent of histological tissue damage (Matute-Bello et al., 2008; Wang et al., 2008; Leiphrakpam et al., 2021).
In order to evaluate tissue level injury, histological sections across different time points are required. As artifacts arising from improper preparation can convolute the interpretation of histological findings, careful histological processing of tissue is required to achieve proper insight into the pathological state of the injured tissue (Hsia et al., 2010). The most widely used histopathological processing technique for ALI across species utilizes formalin-fixation and paraffin embedding (FFPE), which provides high morphological and cellular level resolution. In order to generate FFPE samples, the biopsied pieces of tissue need to be properly fixed, followed by tissue processing and paraffin embedding. Next, thin sections are generated and placed on microscopic slides, followed by staining, and finally, microscopy and image analysis. All of these steps are time-consuming and labor intensive, and can thus be prone to variability (Hsia et al., 2010).
As large animal models often generate considerable sample numbers, efficient and reproducible workflows are needed for processing and analyzing histological sections. Furthermore, traditional histological processing uses toxic chemicals for both the environment and the end-user (de Aquino et al., 2016; Kandyala et al., 2010; Purdie et al., 2011). This provided a secondary motivation to the development and implementation of a more sustainable and greener histological workflow, achieving several of the sustainability goals in Agenda 2030 (United Nations, 2015). We focused on goal 3—good health and well-being—and goal 12—responsible consumption and production. Xylene removal from the clearing steps can dramatically reduce the overall amount of xylene used (goal 12) and improve the health and well-being of the histopathologist (goal 3). Therefore, we replaced xylene with isopropanol, which is environmentally and occupationally safer (Falkeholm et al., 2001). When possible, we also used revitalized histological equipment or repurposed commonly available items to make histological processing more accessible to laboratories lacking the resources for some of the high-end and specialized equipment used for histological processing.
Once histological sections are generated, they can be used to validate the extent of injury. As histological analysis can be subjective, the use of semi-quantitative scoring systems is viewed as highly relevant for confirming ARDS in animal models and for evaluating potential therapies (Meyerholz and Beck, 2018). The development of a validated histological score system of ALI in large animal models has been deemed a priority in the field (Kulkarni et al., 2022). Objectively comparing histological injury is known to be challenging, even for highly trained pathologists. Previous histological scoring systems for small animal models relied on the use of scoring multiple randomized fields of view in bright-field microscopy. However, slide scanning technology is becoming more common and accessible to more laboratories. Slide scanning technology therefore opens up new possibilities for histological scoring in a digital format. Therefore, we developed a new histological scoring system for assessing the extent of pulmonary tissue damage in hematoxylin and eosin-stained sections generated from porcine models of ARDS, which could be used by researchers with varying degrees of histological experience. While histological scoring of specific biomarkers can be useful, this becomes challenging in large animal models where molecular tools are not always available. Furthermore, the presence or absence of certain biomarkers may change depending on the source of injury. Therefore, to simultaneously achieve our abovementioned goals, we chose to implement our histological scoring system with hematoxylin and eosin-stained sections generated using green histological processing techniques.
Materials and Reagents
15 mL conical tube (Sarstedt, catalog number: 62.554.502)
Glass petri dish, 12 cm diameter (Thermo Scientific, catalog number: 41042030)
Scalpel blade, no. 21 (Heraco AB, catalog number: 7978)
Scalpel, no. 4, (Heraco AB, catalog number: 7972)
Forceps curved, 2 mm Tip, 12 cm (Agnthos, catalog number: 11003-12)
Paraffin (Histolab, Histowax; catalog number: 00403)
Stainless steel base molds 1.5 × 1.5 × 0.5 cm (VWR International AB, catalog number: 89498-710)
Glass slides (Microscopic slides, Fisher Scientific; catalog number:10149870)
Wheaton Coplin staining jars (Sigma-Aldrich, catalog number: S5766-6EA)
Cover slips 24 × 50 mm (Histolab, Thermo Scientific; catalog number: 06660)
10% neutral-buffered formalin (Sigma-Aldrich, catalog number: HT501128-4L)
Phosphate buffered solution (PBS) (Thermo Scientific, catalog number: 18912014)
Tissue processing/embedding cassettes (Histolab, catalog number: 41701)
Absolute ethanol (VWR International AB; catalog number: BAKR3406.5000)
Isopropanol (Fisher Scientific, catalog number: 15518744)
Xylene (Merck, catalog number: 1330-20-7)
Hematoxylin (Merck, catalog number: 105175)
Glacial acetic acid (Sigma-Aldrich, catalog number: 64-19-7)
Pertex mounting media (Histolab, Thermo Scientific; catalog number: 00871.0500)
Eosin Y solution 0.5% aqueous (Working Solution) (see Recipe 1) (VWR International AB, catalog number: 1098441000)
Graded ethanol solutions and ethanol-isopropanol mixtures (Recipe 2)
Equipment
Tissue processor (Myr, Automated Spin Tissue Processor, model: STP 120) (Figure 1)
Microtome (Leitz, model: 1516 Automated) (Figure 2A)
Slide heater (Wealtec Corp., model: HB-1, catalog number: 1092001) (Figure 2B)
Water bath (JP Selecta, model: N291451, catalog number: 12027874) (Figure 2C)
Cooling tray stored at -20 °C (33 × 27 × 5 cm) (Menuett, model: 009551) (Figure 2D)
Custom-made Paraffin Dispensing Tank (ROYAL Catering, catalog number: 317320191080) retrofitted with a 16 mm diameter and 55 mm external length stainless steel spigot (The Kitchen Lab, Sweden; AM-SIGNSTEK304) (Figure 2E)
Natural convection oven (BINDER, catalog number: ED56 8012-1018)
VS120-S6-096 virtual microscopy slide scanning system (Olympus, Tokyo, Japan)
Figure 1. Spin Tissue Processor (STP 120) showing individual containers numbered 1-12 and the programmable interface.
Figure 2. Histopathology area, developed with revitalized, refurbished, and repurposed equipment. A) Manual microtome (revitalized); B) Block heater (refurbished); C) Water bath (revitalized); D) Cooling tray (repurposed); E) Paraffin tank dispenser (water boiler retrofitted with a stainless-steel spigot).
Software
OlyVIA 3.8 (Olympus)
Graphpad Prism 9 (La Jolla, CA)
Optional: Microsoft® PowerPoint® and Microsoft Excel® for Microsoft 365 MSO (Version 2201 Build 16.0.14827.20158) 64-bit
Adobe Acrobat Pro DC version: 21.011.20039.0
Procedure
Tissue collection
All biopsies should be randomly sampled from the same anatomical location from anesthetized and mechanically ventilated pigs, as previously described (Stenlo et al., 2020, 2021). Samples should be taken by the same surgeon across all animals and timepoints to minimize differences in the sampling procedure. Prior to administering any injurious agents or sham treatment controls (e.g., saline), baseline samples are obtained. A small wedge resection is taken from the right lower lobe through a small thoracotomy and used for baseline samples. Endpoint samples from both the right and left lungs (upper and lower lobes) are taken as small wedge resections through a sternotomy. Wedge resections for biopsies are sampled randomly within the same anatomical location within each lobe to decrease bias. For scoring, biopsies from similar lobes are compared against one another, as different lobes have different susceptibilities to severe lung injury in these models. See Note 1 for details on tissue sampling in porcine models.
Immediately after the samples are taken, biopsies of 0.5–1.0 cm3 should be placed in a sterile 15 mL conical tube, with 10% neutral buffered formalin solution, with at least two times the volume of the tissue for fixation. Leave at 4 °C overnight (at least 12 h and up to 48 h).
After fixation, replace formalin with fresh and sterile PBS solution. The tissue can be stored at 4 °C in PBS until processing. See Note 2 for details on longer term storage in these conditions.
Prepare the workspace for sectioning tissue biopsies (Figure 3A).
The tissue should be stabilized with the help of forceps and sectioned into multiple small pieces in a glass petri dish with a sterilized scalpel (Figure 3B). Prepare segments of approximately 5 mm in the longest dimension and no smaller than 3 mm thick (or the thickness of the slots in the cassettes). Using forceps, place them in the tissue processing/embedding cassettes (Figure 3C).
Figure 3. Tissue sectioning from biopsies prior to tissue processing. A) Preparation for tissue sectioning; B) Sectioning of the tissue with a scalpel; C) Transfer of the tissue sections into a pre-labeled cassette.
Up to 80 cassettes containing tissue should be placed into the first container (container 1) of an Automated Spin Tissue Processor STP-120 (Figure 1), or equivalent, for subsequent tissue processing (dehydration and clearing) and paraffin infiltration, according to the protocol described in the next sections. The steps outlined in Sections B–D should be programmed into the tissue processor. See Notes 3 and 4 for details on programming the tissue processor.
Waste formalin solutions, and all subsequently described solutions should be discarded according to local chemical and biohazardous waste regulations (see Note 5 for further details).
Dehydration (graded ethanol series and isopropanol)
Solutions of graded ethanol should be prepared ahead of time in deionized water or isopropanol as described below (step B3) and placed into the tissue processor containers. See Recipe 2 for further details.
The basket containing the cassettes should be slowly immersed into the lowest concentration ethanol container (container 1), stirring at 60 rotations per minute with changes in rotational direction every 60 seconds. The rotational agitation helps to achieve a more homogenous and complete infiltration of tissue with the dehydration and ethanol mixtures, due to increased diffusion as compared to immersion based protocols (Ostrander, 1996; Suvarna et al., 2018).
Set the automatic tissue processor for each of the solutions and incubation times:
Container 1: ethanol 30% – 1.5 h
Container 2: ethanol 50% – 1.5 h
Container 3: ethanol 70% – 1.5 h
Container 4: ethanol 80% – 1.5 h
Container 5: ethanol 80% – 1.5 h
Container 6: ethanol–isopropanol 80–20% – 1.5 h
Container 7: ethanol–isopropanol 80–20% – 1.5 h
Clearing (Diaphanization)
Since xylene is associated with health hazards and an unfavorable environmental profile, isopropanol can be used to replace xylene as both a dehydrating and a clearing agent. The following steps occur immediately after Section B.
Container 8: isopropanol 100% – 1.5 h
Container 9: isopropanol 100% – 1.5 h
Container 10: isopropanol 100% – 1.5 h
Paraffin wax infiltration
To ensure complete infiltration of the paraffin into the full tissue thickness, the dehydrated and cleared tissue segments in the cassettes are automatically moved to the final containers in the tissue processor, which contain molten paraffin, in two different steps at 65 °C controlled temperature.
Container 11: Paraffin – 6 h
Container 12: Paraffin – 12 h
Paraffin embedding
Place 5–10 pieces of paraffin infiltrated tissue into the metal base mold with the lung parenchyma facing down (or according to the orientation needed); fill the bottom portion of the histology cassette and mold with molten paraffin, covering the tissue (Figure 4A–C).
Quickly place the bottom portion of the histology cassette on top of the molten paraffin. Let the entire assembly cool down for at least 10 min on the cooling tray, until the paraffin has completely solidified (Figure 4D).
After the solidification is complete, the paraffin block and cassette case can be easily removed for subsequent sectioning.
Figure 4. Paraffin embedding of the tissue. A) Pour molten paraffin into the pre-warmed mold; B) Transfer the specimens and orient in the appropriate direction, considering that the blocks should be cut parallel to the base of the mold; C) Place the bottom of the cassette on top of the mold filled with paraffin, ensuring that the paraffin fills the grates in the cassette; D) Representative image of the process to cool down and solidify the paraffin-infiltrated tissue and liquid paraffin on the pre-chilled cooling tray; E) Representative image of solidified, paraffin-infiltrated tissue after cooling.
Sectioning of paraffin-embedded tissue
Place the wax block on the microtome specimen holder with the surface parallel to the blade.
Set the microtome to cut 5 µm thick sections (Figure 5A–B). See Note 6 for more details on section thickness.
Use forceps to pick up the sectioned tissue, and transfer to a pre-warmed water bath at 40 °C. Allow the tissue to float flat on the water surface (Figure 5C) until no visible creases can be seen in the paraffin (Figure 5D). (See Notes 7–9 for further details on the water bath).
Carefully place the floating sections onto the histological glass slides as desired for subsequent staining and imaging.
Slides containing tissue sections should be allowed to dry overnight on the glass slides. For long-term storage, keep them covered at room temperature until staining (see Note 10 for more details).
Figure 5. Sectioning of the paraffin block. A) Microtome set up for sectioning paraffin blocks; B) Sectioning of the tissue; C) Transfer of the sectioned tissue with wrinkles to a water bath; D) Relaxation of the paraffin ribbon in the water bath prior to mounting on microscope slides.
Hematoxylin and eosin (H&E) staining
Slides should be placed overnight in an oven at 65 °C in horizontal slide racks to allow the excess paraffin to melt away prior to deparaffinization and staining (Figure 6A).
For all the steps below, place slides into Coplin jars filled with the following solutions and for the designated incubation times. Each step below is listed according to a new solution into which it is placed (i.e., if the same solution is listed for two subsequent steps, the slides should be placed into a new container with fresh solution). Coplin jars may be reused throughout the protocol if sufficiently rinsed and dried between steps.
Deparaffinization
Coplin Jar 1: Xylene – 3 min (see Notes 11 and 12 regarding potential xylene substitution)
Coplin Jar 2: Xylene – 3 min
Rehydration
Coplin Jar 3: Ethanol 100% – 3 min
Coplin Jar 4: Ethanol 100% – 3 min
Coplin Jar 5: Ethanol 90% – 3 min
Coplin Jar 6: Ethanol 70% – 3 min
Coplin Jar 7: Rinse in deionized water – 1 min
Staining
Coplin Jar 8: Stain with hematoxylin solution – 7 min
Coplin Jar 9: Rinse once in deionized water
Wash in running tap water, ensuring water flow is not directly on the slides (see Figure 6C) – 15 min
Coplin Jar 10: Incubate/wash in distilled water – 2 min
Coplin Jar 11: Immerse the sections in Eosin Y (0.5%) – 10 min
Wash in running tap water, ensuring water flow is not directly on the slides (see Figure 6C) – 5 min
Dehydration and mounting
Coplin Jar 12: Ethanol 80% – 3 min
Coplin Jar 13: Ethanol 100% – 3 min
Coplin Jar 14: Ethanol 100% – 3 min
Coplin Jar 15: Xylene – 3 min (see Notes 11 and 12 regarding potential xylene substitution)
Coplin Jar 16: Xylene – 3 min
Add 2–3 drops of mounting media to the slide and carefully add the cover slip on top, ensuring there are no bubbles
Let the sections dry overnight in the fume hood/suction bench (Figure 6D).
See Note 5 for details on waste removal procedures.
Figure 6. Deparaffinization and H&E staining. A) Example slide placed horizontally into the oven for paraffin removal overnight; B) Slide placed into Coplin jar; C) Wash in running tap water, ensuring that the water flow is gentle enough to slowly exchange the water without disturbing tissue sections on the slides; D) Stained and mounted slide.
Image collection via automated slide scanning
Bright field images are obtained with a VS120 virtual microscopy slide scanning system (Olympus, Tokyo, Japan), using 20× and 40× objectives. Images for each slide should be extracted at three different digital magnifications (4×, 10×, and 20×) in the OlyVIA Olympus Software viewer, and assembled per slide into a Microsoft PowerPoint presentation containing a small scoring box (Table 1) for subsequent digital scoring by blinded scorers, as described below (see Figure 7 for example score sheets). Randomize the slides using a random number generator in Microsoft Excel (see Note 13 for further details). Identical acquisition settings and image brightness adjustments must be used for all the conditions (see Note 14 for further details).
Figure 7. Representative examples of three different scoring sheets supplied to reviewers for the histological scoring system. Three different examples of the photomicrographs at three digital magnifications (4×, 10×, and 20× to provide representative views across magnifications). The score sheet uses a modified version of Table 1 on each page to collect information.
Scoring
As evident in the literature (Rosenthal et al., 1998; Martin and Matute-Bello, 2011; Ballard-Croft et al., 2012; Engel et al., 2020), the porcine model of ALI can have different features than those of small animal models (Wang et al., 2008). Therefore, and based on our previous experience in small and large animal models of ALI, we selected seven histological features for our porcine scoring system (inflammatory cells, hyaline membranes, proteinaceous debris, thickening of alveolar wall, hemorrhage, atelectasis, and a general injury score entitled ‘enhanced injury’) (see Figure 8). The selection of these main features has been recently and independently confirmed by an international panel of experts to be present and relevant in animal models of ARDS (Matute-Bello et al., 2011; Kulkarni et al., 2022) (see Note 15 for further details on the selection of the relevant features for large animal models). Previous histological scoring systems for lung and other organs have been developed, prior to the more widespread use of slide scanning technology, for use with manual microscopy methods (Gibson-Corley et al., 2013). Therefore, previous scoring methods have used randomization of multiple, high magnification regions and scoring of features utilizing a binary or three-point system (Guenthart et al., 2019; Frick et al., 2021; Leiphrakpam et al., 2021). However, scoring systems in small animal lung injury models have evolved to have larger score ranges to increase their sensitivity (e.g., for pulmonary fibrosis) (Ashcroft et al., 1988; Hubner et al., 2008). Therefore, we opted for a range of 0 (no damage)—8 (extensive damage) for each of the seven features selected as relevant (see Figure 8).
Figure 8. Representative photomicrographs of H&E stained sections demonstrating the different features selected for development of the lung tissue injury score system in low and high magnification. Black arrowheads demonstrate examples of features.
Scorers should be given a standardized training form with example histological images not contained in their scoring set. These images should contain text describing each feature, as well as arrows demonstrating each feature, as some animals with severe injury can contain multiple features in one image. The scorers should then be instructed to give scores depending on the severity of injury of these features on the scanned slides. Figure 8 presents an example of an overview of the features to be scored. See Notes 16 and 17 for details on the number of scorers and expertise.
Table 1. Features of acute lung injury to score in H&E stained histological sections of porcine lung tissue. The score range is 0 (null) to 8 (severe) for each of the features mentioned.
Features Scoring Feature Description
A – Inflammatory cell Visible inflammatory cells in air and interstitial spaces
B – Hyaline membranes
Acellular deposit (i.e., devoid of hematoxylin staining) in the alveolar region and stained with eosin
C – Proteinaceous debris
Acellular debris in airspaces
D – Thickening of alveolar wall Alveolar wall thickening (i.e., at least >1 cell layer thick)
E – Enhanced injury
Overall impression of tissue level injury
F – Hemorrhage
Visible red blood cells in the interstitium or airspaces
G – Atelectasis
Complete or partial collapse of distal airspaces
Total Score = (Sum/56) × 100
Data analysis
Once all the scores are received, slides should be unblinded and organized in a data processing software, such as Microsoft Excel. The total score is then calculated for each scorer and slide (see Table 1). The maximum score per scanned slide is 56. This total score can then be transformed to a total score range of 0–100, as shown in Table 1. Then, based on the fact that the raw scoring data is often comprised of low numbers of scorers, where normality cannot formally be tested for, the median of all scores for each slide is used for further analysis (Gibson-Corley et al., 2013). The use of the median total score of each feature or slide across all scorers also helps to reduce the potential impact of outliers. Data is then visualized and analyzed using GraphPad Prism 9 (GraphPad Software Inc, La Jolla, CA, USA). Examples of scoring by researchers with different experience levels are shown in Figure 9. Values can be compared between all the features or scores and between experimental groups using one- or two-way ANOVA for repeated measures with Kruskal–Wallis test or Mann–Whitney U, with p-values of ≤ 0.05 considered significant. Non-parametric testing and presentation of median for central tendency is the most appropriate statistical analysis and representation because semi-quantitative scoring systems are ordinal, and therefore the differences between different scores cannot be assumed to be linear. Examples of slides identified with no damage (Minimum), mild damage (2/3), moderate damage (4), pronounced damage (5/6), and extensive damage (Maximum) for each feature are shown in Figure 10.
Figure 9. Scoring outcomes and relative reproducibility across different independent scorers with different levels of experience (novice, moderate, and expert). Representative total scores from the three example sheets shown in Figure 7 and transformed to a scale of 0–100. The total score and the ability of users to distinguish between different severities of injuries did not differ dramatically based on experience (see Note 17 for classification based on experience). These samples were selected to represent a range of the scores our system detected (low, mild, and extensive level of lung injury), as judged by the blinded scorers. See Figure 7 (score sheet 34 as an example for low level of lung injury, sheet 22 for mild level of injury, and sheet 24 for high level of lung injury). The horizonal line represents the median of all scorers for each slide.
Figure 10. Photomicrographs of sections stained with H&E demonstrating a range of scores across all features. Score ‘Minimum: absence of injury’; ‘Score 2/3’: mild injury; ‘Score 4’: moderate injury; ‘Score 5/6’: pronounced injury; and ‘Maximum’: extensive damage and highest score given. Arrows demonstrate examples of features.
Notes
The selection of an appropriate tissue sampling method, such as the number of samples and randomization method, must be defined prior to the onset of the experiment. In large animals, this is preferably done according to the gross anatomical location of structures of interest for the specific model. Systematic, randomized approaches for obtaining representative samples help to avoid systemic bias and guarantee consistency across the different steps of histological processing (Albl et al., 2016; Blutke and Wanke, 2018).
The maximum time that we have stored tissue in PBS at 4 °C and subsequently successfully used this protocol for tissue processing, and H&E staining was 18 months.
Most automatic tissue processors do not come with pre-set programs validated for different tissue types and protocols. Therefore, it is important to validate all protocols (e.g., manually or with a small sample set) before the utilization of new protocols in different automatic tissue processors.
For some steps in our protocol, the same solution is used in two sequential containers (or similar for staining steps). This occurs when incubation of the tissue or sections with high purity solutions is needed. As an example, some residual isopropanol is initially transferred to the first paraffin container. Therefore, a second paraffin container of the same type of molten paraffin is used, for a longer time, to ensure complete infiltration of tissue.
This protocol generates both chemical and biohazardous waste products that should be disposed of in accordance with local waste regulations.
Section thicknesses from 3–5 µm can be used. We have found 5 µm sections to be preferable for porcine lung studies.
The water bath should be cleaned frequently, and a lid should be kept on it at all times to avoid contamination. Just prior to sectioning and pre-warming, the lid should be removed to visually inspect the water bath, looking for particles or signs of turbidity in the water. If there are any signs of particulate matter, the bath should be changed to fresh deionized water.
Prior to sectioning, the water bath should be pre-warmed to 40 °C. Sections should then be carefully transferred to the water bath (individual sections or ribbon of serial sections). If serial sections are needed, we recommend transferring one section or ribbon at a time, so that the user can keep track when placing sections on glass slides (either individual paraffin sections or multiple sections per slide).
Sections are allowed to float until there are no more visible folds/wrinkles in the paraffin, indicating that the paraffin is warmed and that the section can lay flat on the glass microscope slide. As long as the water bath is not too warm and does not melt the paraffin sections, the sections are stable for as long as needed to section. In our normal protocol, this takes no longer than 30 min per paraffin block. We adhere sections to glass sides per block before moving to the next block to ensure that there is no mixing of samples between blocks.
Microscopic slides containing paraffin tissue sections can be stored long term at room temperature, covered to protect from dust, prior to staining.
While the images above and those used in our previously reported papers (Stenlo et al., 2020, 2021) were obtained following a procedure in which xylene was used for the deparaffinization steps, several more sustainable, environmentally-friendly alternatives exist. In particular, we have used a commercially available compound containing d-limonene (Histo-Clear, National Diagnostics) for deparaffinization (step G3) using 3 × 10 min incubations, and for the final clearing (steps G4d and G4e) 3 × 10 min prior to mounting. We have successfully used this protocol for porcine lung tissue (Figure 11) following the above-described xylene-free tissue processing protocol. Additionally, we have used this protocol for normal, IPF, and long-term COVID-19 human lung tissues (Lindstedt et al., 2021).
Figure 11. Example of H&E staining of porcine lung tissue using xylene-free tissue processing, deparaffinization, and final clearing protocols.
The xylene-free tissue processing and staining protocol described here is also compatible with tissue processing and evaluation of bioengineered hydrogel materials, such as bioinks and bioprinted constructs containing extracellular matrix components and/or alginate (De Santis et al., 2021). Aggressive solvents, such as xylene, can cause dissolution of engineered materials during processing.
To implement randomization, repeated slides were used as distractors, as well as regions not scored for the present study (e.g., upper lobes) (Gibson-Corley et al., 2013).
High resolution images and corresponding example scores are available at the EMBL BioImage Archive Accession Number S-BIAD419 with corresponding acquisition settings. However, image acquisition settings must be determined according to the end user’s equipment, since there may be a difference between images obtained from different microscopes and capture software. We used Brightness: 50%, Contrast: 50%, and Gamma: 1% for the images presented in this protocol.
It is widely acknowledged that the lungs need to be perfusion-fixed through the vessels, or gravity-fixed through the airways, to quantitatively measure the degree of atelectasis (Hsia et al., 2010; Kulkarni et al., 2022). However, we have regularly found that we are able to differentiate between baseline and animals receiving saline controls or LPS administration if samples are fixed immediately after excision (with greater extent of atelectasis in pigs receiving LPS). Therefore, while this method of tissue fixation is not sufficient for quantitative morphology, it allows a comparative assessment from baseline samples and biopsies taken serially from the same pig, thus making it a reproducible and reliable parameter to use for semi-quantitative scoring.
To minimize the effect of scoring outliers, more than three researchers should perform scoring.
We have found that this scoring system is robust, and even those with limited prior knowledge are able to score similarly to those with prior and extensive training (i.e., >10 years) in preclinical pulmonary histology. Novice: very limited to no experience; Moderate: some experience with histology (>1 year); and expert: high experience with acute and chronic preclinical models of pulmonary histology (e.g., >10 years).
Recipes
Eosin Y solution 0.5% aqueous (working solution)
Activate the eosin in the working solution by adding 50 µL of glacial acetic acid per 100 mL of the eosin and shake vigorously before use. Working solution should be used within 1–2 weeks.
Graded ethanol solutions and ethanol-isopropanol mixtures
Dilute the absolute ethanol in deionized water or isopropanol at room temperature according to the concentration needed for each step. Solutions can be prepared ahead of time and stored in closed containers to ensure that the alcohol concentrations do not change over time.
Acknowledgments
The authors thank all the members of the Lung Bioengineering and Regeneration (LBR) Laboratory (Lund University, Lund, Sweden) for helpful discussions throughout the manuscript preparation and for critical reading of the final manuscript. The authors would also like to thank the scoring reviewers, Oskar Hallgren and Sinem Tas, and colleagues that performed the pilot training, Emil Rehnberg, Victoria Ptasinski, and Martina de Santis, for their help in improving and developing this project. The authors are particularly grateful to the StemTherapy Imaging Core Facility and especially to Emanuela Monni for helpful discussions, training in slide scanning, and technical assistance in capturing the images. This work was funded by a Wallenberg Molecular Medicine Fellowship from the Knut and Alice Wallenberg Foundation.
Competing interests
There are no competing interests to report from any of the authors.
Ethics
The methods used for the animal model are described in detail in Stenlo et al. (2020 and 2021). All animals received standard care according to local and international regulations. This study was approved by the Ethics Committee (Dnr 8401/2017) for Animal Research and followed the Principles of Laboratory Animal Care of the National Society for Medical Research, USA and the Guide for the Care and Use of Laboratory Animals, published by the National Academies Press (1996).
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Preparation of a Single-cell Suspension from Drosophila Wing Imaginal Discs
SY Shu Yang
BS Brooke Sears
XZ Xiaoyan Zheng
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4494 Views: 1572
Reviewed by: Pilar Villacampa AlcubierreJer-Yen YangLijuan DuSandhya Ganesan
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Original Research Article:
The authors used this protocol in eLIFE Jan 2022
Abstract
The wing imaginal discs in Drosophila larvae are a pair of sac-like structures that later form the wings of the adult fly. During the past decades, wing discs have been used as a simple and accessible model system, for identifying genes and deciphering signaling cascades that play crucial roles in many aspects of development. In this protocol, we describe a simple method for preparing a cell suspension from wing discs (see Graphical abstract). This method can also be applied to the preparation of single-cell suspensions from other types of Drosophila tissues. When combined with genetic labeling, the dissociated cells are suitable for downstream analysis, such as flow cytometry. This method was recently used to isolate different populations of cells from Drosophila imaginal discs (Yang et al., 2022).
Graphical abstract:
Procedures to prepare a single-cell suspension from Drosophila imaginal discs. Illustration of the main steps to dissect, temporarily store, and dissociate imaginal discs from Drosophila larvae. Refer to the Procedure section for detailed description of each step.
Keywords: Cell dissociation Tissue dissociation Drosophila Epithelial cells Imaginal discs
Background
The wing imaginal discs (wing discs) are located within the body cavity of the larvae and give rise to the wing, wing hinge, and the dorsal half of the body wall in the second thoracic segment (Tripathi and Irvine, 2022). The wing discs first form from a cluster of approximately 30 cells, which is located in the second thoracic segment during embryogenesis. These cells undergo extensive proliferation during larval stages, to form a mature larval wing disc of approximately 35,000 to 50,000 cells (Milan et al., 1996; Tripathi and Irvine, 2022). The majority of the wing disc is comprised of epithelial cells, with associated myoblasts, tracheal cells, neurons, and glia. Given the simplicity and accessibility of these structures, wing discs have been widely used as a model system for studying many aspects of biology, including tissue patterning, growth control, morphogenesis, and signal transduction.
In Drosophila, the Gal4/upstream activating sequence (UAS) transgenic system (Brand and Perrimon, 1993) can be used to label specific populations of cells via the expression of a fluorescent reporter gene, such as green fluorescent protein (GFP). The labeled GFP-positive cells can then be isolated from GFP-negative cells via fluorescence-activated cell sorting (FACS). In this protocol, we describe a simple method for the preparation of an epithelial cell suspension. This method was recently used to isolate different populations of cells from Drosophila imaginal discs following Gal4/UAS-based genetic labeling (Yang et al., 2022). This method can also be applied to the preparation of single-cell suspensions from other types of Drosophila tissues.
Materials and Reagents
9 depression spot plate (Pyrex, catalog number: 89090-482)
60 mm Petri dish (Thermo Fisher Scientific, catalog number: AS4051)
1.5 mL low retention microcentrifuge tubes (Thermo Fisher Scientific, catalog number: 21-402-903)
200 µL ultra-low retention micropipette tip (USA Scientific, catalog number: 1161-1700)
1,250 µL ultra-low retention micropipette tip (USA Scientific, catalog number: 1161-1720)
BD needles, 21 gauge (BD, catalog number: 305165)
BD needles, 25 gauge (BD, catalog number: 305125)
5 mL FACS tubes with a 35 µm strainer cap (Olympus PlasticsTM, catalog number: 28-154)
Schneider's Drosophila medium (Thermo Fisher Scientific, catalog number: 21720)
Fetal bovine serum, qualified, heat-inactivated, USDA-approved regions (Omega Scientific, catalog number: FB-02)
Penicillin-streptomycin (P/S) (Thermo Fisher Scientific, catalog number: 10378016)
Non-enzymatic cell dissociation solution (Sigma, catalog number: C1544)
Elastase (Sigma, catalog number: E0258)
Propidium iodide (InvitrogenTM, catalog number: P3566)
10× PBS (for 1 L) (see Recipes)
1× PBS (see Recipes)
Elastase cell dissociation solution (see Recipes)
S2 medium (for 500 mL) (see Recipes)
Equipment
Nikon TS100 dissecting microscope
#3 forceps for transferring larvae (Fine Science Tools, catalog number: 11231-30)
#5 forceps for dissecting imaginal discs (Fine Science Tools, catalog number: 11295-51)
Single Channel Pipette, 2–20 µL
Single Channel Pipette, 100–1000 µL
3 mL syringe (BD, catalog number: 309577)
Magnetic micro stir bar (StirBars, catalog number: SBM-0603-MIC)
Magnetic stirrer
Procedure
Dissection
Prepare 1,000 µL of S2 medium for each 1.5 mL low retention microcentrifuge tube. Keep the tubes on ice.
Transfer wandering third instar larvae from the inside wall of fly culturing bottles into a 60 mm Petri dish with #3 forceps, and wash them five times with 5 mL of 1× PBS, until all residual food is removed.
Using #3 forceps, transfer ~10–20 clean larvae into one depression plate spot filled with 1.5 mL of fresh cold 1× PBS.
Use a pair of #5 forceps to dissect out the imaginal discs (wing and haltere discs) from the larvae in cold 1× PBS.
Note: Video- or image-based descriptions of imaginal disc dissection procedures can be found elsewhere (Morimoto and Tamori, 2017; Purves and Brachmann, 2007; Witte et al., 2021).
Use #5 forceps to gently transfer the dissected discs into another well of the same depression plate filled with cold 1× PBS.
Each time, collect ~10 pairs of dissected imaginal discs in the depression plate before continuing to the next step.
Cut a P20 micropipette tip with scissors, and then coat it by pipetting the remaining carcasses several times up and down.
Wash the coated tip by pipetting fresh cold 1× PBS several times up and down before usage.
Use the coated P20 micropipette tip to transfer the dissected imaginal discs from the depression plate into the 1.5 mL low retention microcentrifuge tube with cold S2 medium. Discard the remaining carcasses.
Notes:
The coating procedure is critical to prevent sticking and loss of dissected tissue during transfer.
The use of a P20 micropipette minimizes the transfer of excess 1× PBS into S2 medium, limiting unwanted dilution.
Imaginal discs can be kept in ice-cold S2 medium for up to 4 h before tissue dissociation begins. In total, collect ~100–200 pairs of discs in each 1.5 mL low retention microcentrifuge tube before tissue dissociation.
Cell Dissociation
Allow the imaginal discs to settle to the bottom of the microcentrifuge tube by gravity, and then remove the S2 medium using a P1000 pipette.
Add 1,000 μL of non-enzymatic cell dissociation solution, and gently wash the imaginal discs by inverting the microcentrifuge tube.
Allow the imaginal discs to settle to the bottom of the microcentrifuge tube, and then remove the non-enzymatic cell dissociation solution using a P1000 pipette.
Repeat Steps B2 and B3, and wash the imaginal discs three times. In the final round of washing, remove as much solution as possible.
Add 1,000 μL of elastase cell dissociation solution into the microcentrifuge tube.
Add a clean magnetic micro stir bar into the microcentrifuge tube. Close the cap and invert the tube, to allow the stir bar to sink to the cap.
Place the inverted microcentrifuge tube in the center of a magnetic stirrer. Increase the stirring speed slowly to avoid spinout.
Incubate the imaginal discs with elastase cell dissociation solution in the magnetic stirrer at room temperature for 20–30 min.
While waiting, pre-wash P1250 micropipette tips and 3 mL syringes with 21G and 25G needles, by passing S2 medium through the tips or needles ten times.
Add 500 μL of S2 medium to the elastase cell dissociation solution and, using a pre-washed P1250 tip, gently pipette the solution up and down twenty times.
Gently pass the solution through the pre-washed 21G needle ten times, then through the 25G needle another ten times. Avoid creating bubbles when passing the solution through the needles.
Pre-wet a 35 µm cell strainer cap and its attached falcon tube with 500 µL of S2 medium. Discard the S2 medium flow-through.
Transfer the total 1,500 μL solution containing dissociated cells with a pre-washed P1250 tip and filter the solution through the wet cell strainer cap into the falcon tube. Continue tapping the tube until all of the solution goes through the strainer cap.
Wash the microcentrifuge tube with 500 μL of S2 medium and filter the solution through the cell strainer cap into the same falcon tube (total 2,000 μL).
Add the desired fluorescent dye (e.g., propidium iodide) and keep the tube on ice until FACS.
Note: ~100–200 pairs of imaginal discs (wing and haltere discs) can yield 5 × 106–10 × 106 dissociated cells at a concentration of 2 × 106–5 × 106 per mL, with a viability of ~90%. Figure 1 shows representative images of dissociated imaginal disc cells before and after cell sorting.
Figure 1. Images of dissociated imaginal disc cells before and after cell sorting.
Dissociated wing disc cells from late third instar larvae carrying ptc-gal4 and UAS-mCD8GFP. (A) GFP positive and negative cells before FACS. (B) GFP-positive cells after FACS. (C) Zoomed view of post-FACS sorted GFP positive cells. Hoechst 33342 (blue) is used to visualize the entire cell population. Scale bars: 50 μm.
Recipes
10× PBS (for 1 L)
80 g NaCl
2 g KCl
14.4 g Na2HPO4 (anhydrous)
2.4 g KH2PO4
1 L dH2O
Mix well, and filter sterilize.
1× PBS (for 1 L)
100 mL 10× PBS
900 mL dH2O
Mix well, and filter sterilize.
Elastase cell dissociation solution
Elastase protein powder was reconstituted in ddH2O to 5 mg/mL.
Then, the solution was diluted to 0.4 mg/mL in the fresh cell dissociation solution.
S2 medium (for 500 mL)
500 mL Schneider's Drosophila medium
50 mL fetal bovine serum
5 mL penicillin-streptomycin (P/S)
Acknowledgments
This work is supported by National Institutes of Health grants R01GM117440 to X.Z. This protocol was used to isolate different populations of cells from Drosophila imaginal discs (Yang et al., 2022). The graphical abstract was generated with the help of Biorender (https://app.biorender.com/).
Competing interests
The authors declare that they have no conflicts of interest with the contents of this article.
References
Brand, A.H., and Perrimon, N. (1993). Targeted Gene-Expression as a Means of Altering Cell Fates and Generating Dominant Phenotypes. Development 118(2): 401-415.
Milan, M., Campuzano, S. and Garcia-Bellido, A. (1996). Cell cycling and patterned cell proliferation in the wing primordium of Drosophila. Proc Natl Acad Sci U S A 93(2): 640-645.
Morimoto, K. and Tamori, Y. (2017). Induction and Diagnosis of Tumors in Drosophila Imaginal Disc Epithelia. J Vis Exp(125): 55901.
Purves, D. C. and Brachmann, C. (2007). Dissection of imaginal discs from 3rd instar Drosophila larvae. J Vis Exp(2): 140.
Tripathi, B. K. and Irvine, K. D. (2022). The wing imaginal disc. Genetics 220(4).
Witte, L., Linnemannstons, K., Honemann-Capito, M. and Gross, J. C. (2021). Visualization and Quantitation of Wg trafficking in the Drosophila Wing Imaginal Epithelium. Bio-protocol 11(11): e4040.
Yang, S., Wu, X., Daoutidou, E. I., Zhang, Y., Shimell, M., Chuang, K. H., Peterson, A. J., O'Connor, M. B., and Zheng, X. (2022). The NDNF-like factor Nord is a Hedgehog-induced extracellular BMP modulator that regulates Drosophila wing patterning and growth.Elife 11: e73357.
Article Information
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Yang et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
How to cite
Category
Cell Biology > Cell isolation and culture > Cell isolation
Developmental Biology > Cell signaling
Biological Sciences > Biological techniques
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Von Willebrand Factor Multimer Analysis by Low Resolution SDS-Agarose Gel Electrophoresis
HG Herbert Gritsch
MS Margit Stimpfl
PT Peter L. Turecek
Published: Vol 12, Iss 16, Aug 20, 2022
DOI: 10.21769/BioProtoc.4495 Views: 1885
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Original Research Article:
The authors used this protocol in Thrombosis Research May 2021
Abstract
Von Willebrand factor (VWF) is a complex glycoprotein found in plasma, composed of disulfide-bond-linked multimers with apparent molecular weights between 500 kDa and 20,000 kDa. After release of VWF from storage granules, it is cleaved in flowing blood by the specific metalloproteinase ADAMTS13, resulting in a highly characteristic cleavage pattern and structure. As the structure of VWF multimers determines diagnosis of von Willebrand disease, which has different sub-types with different multimer- and cleavage patterns, VWF analysis is performed using low-resolution horizontal SDS-agarose gel electrophoresis. However, almost every laboratory uses a different protocol, and all experimental details are rarely, if at all, described. Therefore, the results from similar methods may be substantially different. Here, we present a detailed description of a validated VWF multimer method that we have developed. It has been successfully used for over more than 20 years in quality control of recombinant and plasma-derived VWF drug products, and in preclinical and clinical studies with VWF drug candidates. As most of the published methods, it enables visualization of VWF multimers separated by electrophoresis by immunostaining with a polyclonal anti-human VWF antibody followed by a secondary antibody coupled to alkaline phosphatase. VWF appears as a series of regularly spaced bands on the low and middle molecular weight range of the gel, with an unresolved zone in the high molecular weight (HMW) range, where ultra-large multimers are found. An example is shown below. This low-resolution agarose gel electrophoresis allows the determination of the number of VWF multimers with high reproducibility.
Graphical abstract:
Example of electrophoretic analysis of multimer structure of four batches of a recombinant VWF drug substance.
Keywords: Von Willebrand Factor VWF Von Willebrand Disease VWD Multimers VWF Immunostaining
Background
Von Willebrand factor (VWF) is the largest soluble plasma protein, with essential functions in blood coagulation, control of bleeding, and angiogenesis. It is a complex glycoprotein with a mature subunit of 2,050 amino acids (Turecek et al., 2017). Approximately 19% of its molecular size are N- and O-linked carbohydrates, some of which resembling important blood group antigens. VWF is synthesized in endothelial cells and megakaryocytes. Intracellular polymerization starts with the formation of disulfide bridged dimers, which subsequently assemble into multimeric structures via additional disulfide bonds, creating multimers with apparent molecular masses between 500 kDa and 20,000 kDa. VWF is released into the circulation from its storage granules as ultra-large VWF with ultra-high molecular weight (UHMW). These UHMW multimers are potent mediators of platelet adhesion to other platelets and to subendothelial structures exposed upon vessel damage. However, under normal circumstances, UHMW VWF multimers are rapidly cleaved by the plasma protease ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 repeats) to smaller sized multimers with lower hemostatic and, thus, lower thrombogenic potential. ADAMTS13 specifically cleaves VWF at the bond between Tyr1605 and Met1606, generating 140-kDa N-terminal and 176-kDa C-terminal fragments, thus, regulating multimer size. The number of VWF multimers is generally seen as an indicator of functionality because more binding sites (e.g., for collagen and platelets) are exposed from larger multimers when the molecules become elongated under shear stress in the vasculature (Favaloro et al., 2021).
The main function of VWF is to mediate platelet binding and aggregation at sites of vascular injury. This process is known as primary hemostasis. VWF is critical for the formation of the primary hemostatic platelet plug by serving as glue between platelets through binding to platelet receptors glycoprotein (GP) Ib-IX-V and αIIbβ3 integrin, in promoting primary platelet adhesion and aggregation following vessel injury, and promoting binding of platelet aggregates to subendothelial matrix proteins such as collagens, which become exposed to flowing blood when lesions occur in vessels (Bryckaert et al., 2015). Shear forces in blood vessels promote folding and unfolding of VWF, essentially regulating its binding properties to receptors, which are further controlled by limited proteolytic cleavage by ADAMTS13. Furthermore, VWF serves as chaperone protein for coagulation factor VIII (FVIII) through tight binding, maintaining a highly controlled equilibrium between free and bound FVIII, which is also dependent on multimer size. Additionally, VWF determines the circulatory half-life of FVIII. All these functions of VWF depend on multimer size, and the degree of VWF multimerization correlates with the ability to promote platelet aggregation, as an essential step in blood coagulation.
Defects in VWF and ADAMTS13 are involved in hemostatic and thrombotic disorders. Deficiencies in VWF result in von Willebrand disease (VWD). VWD is the most common inherited bleeding disorder in the world, with an estimated prevalence of symptomatic disease of approximately 1 in 1000 individuals. VWD is a heterogeneous disease with different genetic subtypes, called type 1, type 2 (with subtypes 2A, 2B, 2M, and 2N), and type 3 (Peyvandi et al., 2019). In addition to genetic analysis, differential diagnosis of VWD and its subtypes requires determination of VWF activity by different functional assays and determination of the multimer pattern. Phenotypic von VWD classification largely relies on analysis of multimeric distributions of VWF and evaluation of its structure. Examples of typical multimer patterns, as seen in VWF subtype patients, can be found in textbooks and review articles (e.g., Schneppenheim and Budde, 2011). Although VWF multimer analysis is labor intensive, non-standardized, and limited to specialized laboratories, efforts have been made recently to establish ranges for VWF multimer distribution (Vangenechten and Gadisseur, 2020).
Inherited or immune mediated deficiencies of ADAMTS13 impair VWF cleavage, resulting in an increased portion of ultra-large multimers, which can cause thrombosis in the microvasculature. This disease is called thrombotic thrombocytopenic purpura (TTP), and its differential diagnosis requires VWF multimer analysis. Most recently, an impairment of the ratio of VWF and ADAMTS13 was identified as the main determinant of severity of COVID-19, with highly elevated levels of VWF and reduced ADAMTS13 resulting in thrombosis of the microvasculature, particularly in the lungs (Turecek et al., 2021; Seth et al., 2022).
Since the development of the first electrophoretic methods to separate and visualize multimers of VWF, the principle of these methods has not changed (Ruggeri and Zimmerman, 1981). Despite some modest improvements, the quality of test results largely depends on the quality and concentration of the agarose gel and the equipment used. Thus, the most demanding diagnostic test for VWD is still the VWF multimer analysis, an investigation that challenges even the most seasoned laboratory technologist (Lillicrap, 2013). Therefore, it is a limitation that methods are often not fully described with all the experimental details required to make the analytical system robust and reproducible. While multimer analysis of VWF is now performed for more than 40 years (Meyer et al., 1980), only a few publications describe the experimental methods, and even these do not give precise indications on how to perform the analysis. Here, we describe a validated method for electrophoretic separation of VWF multimers in low resolution SDS-agarose gels, with subsequent visualization by immunostaining (Aihara et al., 1986), allowing densitometric analysis. The method equally qualifies for analysis of VWF in blood from humans and other species, diagnosis of VWD subtypes, and characterization of VWF preparations derived from human or animal blood, produced by expression in cell culture systems, or by vectors used in gene therapy (Turecek et al., 2010). This method has been successfully used in quality control of recombinant and plasma-derived VWF drug products, and in preclinical and clinical studies with VWF drug candidates (Turecek et al., 1997).
Materials and Reagents
Material
Flatbed electrophoresis apparatus and Multiphor II electrophoresis unit (with ceramic cooling plate), GE Healthcare, IL, USA (or equivalent)
Power Supply
Cryo thermostat, Modell MultiTemp III, (Cytiva, Uppsala, Sweden)
Hairdryer
Horizontal shaker
pH-meter
Vortex mixer
Water bath (up to 90 °C)
Pipettes and tips
Plastic test tubes 12 × 55 mm
Glass and plastic laboratory trays, approximately 14 × 26 × 6 cm
Glass plates, float glass, 11.5 × 23.0 × 0.2 cm (or equivalent)
Clamps for electrophoresis plates
Rubber seals for gel plates, U-shaped cut, approximately 1.5 mm thick
Rubber seals rectangular cut, 10 mm long, 4 mm wide, 1.5 mm thick
Disposable syringes, cannulas, and locking cone
GelbondFilm for agarose gel 124 × 258 mm (product: 80112932; Cytiva, Uppsala, Sweden)
Chromatography paper 1CHR (Whatman WHA1001917; Sigma, Vienna, Austria) and 3CHR (Whatman WHA3003917; Sigma, Vienna, Austria)
Paper towels/kitchen roll
Laboratory balances
Reagents
Purified water
Agarose SEAKEM HGT (prod. 50040; Lonza, Rockland, USA)
Agarose Biozym Plaque Agarose (prod. 840101; Biozym Scientific GmbH, Oldendorf, Germany)
Tris(hydroxymethyl-aminomethane)
Sodium dodecyl sulfate pellets (SDS)
Ethylen-diamin-tetraacetic acid-di-sodium salt EDTA
NaCl
Glycine
Bromophenol-blue
Triton X100
Na2HPO4·2H2O
NaH2PO4·H2O
Antibody rabbit anti-human-VWF (product A0082 DAKO, Agilent Technologies, Glostrup, Denmark)
Secondary antibody goat-anti-rabbit-IgG-ALP-conjugated. (product 111-055-003; Jackson ImmunoResearch Laboratories, Inc., West Grove, PA, USA)
AP Conjugate Substrate Kit (product 1706432, BioRad Laboratories, Hercules, CA, USA)
Human normal plasma pool (e.g., Precision Biologics, Rockville, USA)
0.9% NaCl
Separation gel buffer (see Recipes)
Stacking gel buffer (see Recipes)
Sample buffer (see Recipes)
Running buffer for electrophoresis apparatus (see Recipes)
Bromophenol blue solution (see Recipes)
PBS-Buffer for immuno-staining (in gel staining) (see Recipes)
Washing buffer/antibody dilution buffer (see Recipes)
Equipment
Densitometer GS-900 (BioRad Laboratories, Hercules, CA, USA)
Software Image Lab (BioRad Laboratories, Hercules, CA, USA) and/or Image Quant TL (Cytiva, Uppsala, Sweden)
Multiphor II Electrophoresis-System with cooling unit (Figure 1).
Microwave oven
Figure 1. Electrophoresis system: Cooling unit (left) and flatbed apparatus (right)
Procedure
Prepare the glass cassette for hand-made agarose gel
On a plane glass plate, glue rectangular rubber seals (10 mm long; 4 mm wide; 1.5 mm thick) on the long side of the glass plate (1.5 cm under the longitudinal edge)—14 pieces at regularly spaced distance. These will form the loading wells for samples (Figure 2A).
Place a separate plane glass plate on the bench (11.5 × 23.0 × 0.2 cm). Cut gelbond film to a length of 23 cm. With a few drops of purified water, fix the gelbond film with its hydrophobic side on the glass plate, avoiding air bubbles (Figure 2B).
Wet the U-shaped rubber seal and place it on the gelbond film (Figure 2C). Place the other glass plate with the loading rubber seals on top, so it forms a casting mold (cassette) (Figure 2D).
Fix the glass cassette with clamps (Figure 2E).
Figure 2. Preparation of the gel cassette.
Casting of separation gel
Caution: Hot liquids, handle with care. Wear protective equipment to prevent injury.
Prepare a 1% agarose gel. Suspend 0.5 g agarose SEAKEM HGT with 50 mL of separation gel buffer and heat the solution in a microwave oven (e.g., 900 W; interrupt heating when liquid starts to foam, remove from oven, and gently agitate; repeat procedure until complete dissolution). Draw this solution into a 50 mL syringe, close the syringe with a cone, and incubate it in a water bath at approximately 90 °C for approximately 30 min.
Place the glass cassette upright in a pre-warmed water bath at 60 ± 5 °C. To cast the gel, place a cannula on the syringe and slowly fill the hot agarose into the glass cassette (on one upper side of the glass cassette) until approximately 1 cm below the loading wells.
Take the glass cassette out of the water bath and allow the gel to set. Keep at room temperature (RT) for approximately 1 h, standing upright.
Casting of stacking gel
Caution: Hot liquids, handle with care. Wear protective equipment to prevent injury.
Suspend 0.2 g agarose SEAKEM HGT with 25 mL of stacking gel buffer in the microwave oven until complete dissolution. Cool to approximately 60–70 °C, and pipette the agarose on top of the separation gel until reaching the upper end of the cassette.
Once the cassette is fully filled, keep a small volume of stacking gel for Procedure F.
Allow the gel to set for approximately 1 h at RT. Open the glass cassette by carefully removing the clamps and the upper glass plate. Take out the gelbond film with the adhesive agarose gel.
Preparing the electrophoresis apparatus
Turn on the cryostat to cool down the flatbed ceramic plate at approximately 10 °C.
Add the running buffer (approximately 1 L per flatbed chamber) to the reservoirs at each end of the gel chamber.
Pipette a few drops of running buffer on the ceramic plate, and place on top the gelbond film with the gel, with the loading wells on the cathodic side.
Filter papers (1CHR) soaked with running buffer are placed as follows: five layers of paper (23 cm × 15 cm), one end in the cathodic buffer vessel, the other end attached to the cathodic end of the gel (do not overlap the gel), and on top another five layers slightly overlapping the agarose gel (keep at approximately 1 cm distance to the sample application wells). Repeat the same procedure on the anodic end of the gel, with five layers of 23 cm × 15 cm paper and five layers of 23 cm × 23 cm paper.
Sample preparation/loading
Caution: Hot liquids, handle with care. Wear protective equipment to prevent injury.
Dilute samples and assay control to the same VWF concentration (preferably 1 IU VWF:Ag/mL), using 0.9% NaCl as diluent.
Mix 0.2 g Biozym Plaque Agarose with 10 mL of sample buffer, and heat in the microwave oven until completely dissolved. Cool down in water bath to approximately 60 °C.
Mix 50 µL of diluted sample, 50 µL of sample buffer, 10 µL of bromophenol blue solution, and 100 µL of Biozym Plaque Agarose.
Incubate at 60 ± 5 °C for 20 ± 5 min.
Load a volume of 50 µL per loading well.
Electrophoresis
Close the lid and start the electrophoresis.
Running time: 15–20 h.
Running conditions: 25 mA constant for 1–3 h, until samples are fully run out of the wells. Interrupt the run to fill the empty wells with stacking gel (30 µL). Continue the separation with 8–10 mA for 14–16 h, until the bromophenol blue line has reached the end of the gel.
After separation, VWF multimers are visualized by either direct in-gel staining or after blot transfer. The protocol below describes the in-gel procedure only.
In gel immuno-staining
Drying the gel
After finishing the gel run, remove the filter papers and wash the gel with purified water on a horizontal shaker for approximately 1–3 h, changing the water for a minimum of five times. The bromophenol blue line should no longer be visible.
Press the gel for 45 min: Place two chromatography paper sheets (3CHR) soaked with purified water on the gel, two more dry papers, and five more kitchen towels. Place one glass plate on top, and press with approximately 2 kg (e.g., place two 1 L bottles with water on top).
After pressing, remove all paper sheets, fix the gel on the bench, and carefully dry the gel with a hair dryer for approximately 30 min.
Immuno-staining
Note: The following procedure is for detection of human VWF. For visualization of VWF from other species, appropriate antibodies need to be selected.
Primary antibody: rabbit anti-human-VWF (A0082)
Place the gel in a tray.
The antibody is diluted to 1 µg/mL in washing buffer/antibody dilution buffer. Prepare a solution of 100 mL per gel, and add to the tray.
Incubate the gel under gentle agitation (shaker) for approximately 16 h.
Pour off the antibody solution and wash the gel with washing buffer/antibody dilution buffer for 5 h.
Secondary antibody: goat-anti-rabbit-IgG-ALP-conjugated
Dilute the secondary antibody with washing buffer/antibody dilution buffer to 0.6 µg/mL (100 mL per gel).
Place the gel into the diluted secondary antibody and incubate under gentle agitation for approximately 16 h.
Pour off the secondary antibody and wash the gel for 1 h in washing buffer/antibody dilution buffer.
Repeat the washing procedure for a further 3–4 h in PBS buffer for immunostaining (without Triton X100), by changing the buffer a minimum of five times.
Immuno-staining according to package insert from AP-Kit (Bio-Rad)
Prepare a solution with 4 mL of kit buffer, 1 mL of reagent A, and 1 mL of reagent B from the AP-Kit. Fill up to 100 mL with purified water.
Use a fresh tray. Place the gel in the staining solution and incubate on a shaker at RT for approximately 10–30 min. The incubation time depends on the band intensity. The bands must be clearly visible, without significant background stain.
Place the gel in purified water to stop staining. Wash with purified water for approximately 20 min.
Fix the gel horizontally on the sides with adhesive strips, and dry the gel either by air drying or with a hair dryer.
Data analysis
Gels can be analyzed visually through side-by-side analysis—the number of multimers, countable with the naked eye, can be recorded (Figure 3) or by densitometry (Figure 4).
Figure 3. VWF multimer gel. Multimer gel. Lanes 1–4: recombinant VWF. Lane 5: normal human plasma pool.
For densitometric analysis, the gels are scanned with a densitometer (GS 900) and analyzed with an appropriate software (for example, Image Lab or Image Quant TL).
For each lane, the distance between the top of the separation gel and the lowest multimer band (corresponding to VWF dimers) is assigned a migration value of 1.0. The distance of the largest VWF multimer band in the sample lane is then measured and expressed as a fraction of this, denoted relative migration distance (Rf). The proportion of the total migration distance of the VWF dimer band that is occupied by all of the other multimers in the sample lane is therefore 1-Rf (Figure 4).
Figure 4. Densitometric analysis (details are described in Turecek et al., 2021). VWF: Ag concentration of the test sample was adjusted to 1 IU/ mL and separated on a 1% agarose gel, followed by immunostaining and densitometry. Multimer pattern (left) and densitogram (right). “a” is the migration distance of the largest VWF multimer, “b” is the migration distance of the smallest VWF (dimer), assigned a migration value of 1.000.
To enable a comparison between different electrophoresis gel runs, this value is reported as a percentage of the 1-Rf value for a normal plasma sample separated on the same gel. An increased percentage value indicates the presence of UHMW VWF multimers in the test sample.
In this example, the relative migration distance (Rf) of the largest VWF multimer was 0.392. The proportion of the separation lane that is occupied by VWF multimers (smallest to largest) is therefore 1-Rf, in this example, calculated as 1.000 – 0.392 = 0.608. The 1-Rf value for the test sample may be calculated as a percentage of the 1-Rf for a control sample run on the same gel to normalize results.
Recipes
Separation gel buffer
pH pH 8.8 ± 0.1
Ingredients 0.375 M Tris
0.1% SDS
Preparation: Dissolve 45.43 g Tris and 1 g SDS with approximately 800 mL of purified water, adjust to pH 8.8 ± 0.1 with 25% HCl and fill up to 1,000 mL.
Stacking gel buffer
pH pH 6.8 ± 0.1
Ingredients 0.125 M Tris
0.1% SDS
Preparation: Dissolve 7.57 g Tris and 0.5 g SDS with approximately 400 mL of purified water, adjust to pH 6.8 ± 0.1 with 25% HCl and fill up to 500 mL.
Sample buffer
pH pH 8.0 ± 0.1
Ingredients 0.01 M Tris
0.001 M EDTA
2% SDS
Preparation: Dissolve 0.121 g Tris, 0.0372 g EDTA, and 2.0 g SDS with approximately 80 mL of purified water, adjust to pH 8.0 ± 0.1 with 25% HCl and fill up to 100 mL.
Running buffer for electrophoresis apparatus
pH pH 8.4 ± 0.1
Ingredients 0.05 M Tris
0.384 M Glycine
0.1% SDS
Preparation: Dissolve 12.11 g Tris, 57.65 g Glycine, and 2.0 g SDS with 2,000 mL of purified water. The pH value automatically reaches 8.4 ± 0.1.
Bromophenol blue solution
Ingredients Bromophenol blue
Sample buffer
Preparation: Dissolve 0.1 g Bromophenol blue in 50 mL of sample buffer.
Washing buffer/antibody dilution buffer
Ingredients Triton X100
PBS-buffer for immuno-staining
Preparation: Dilute 10 g Triton X100 in 1,000 mL of PBS buffer for immuno-staining.
PBS-Buffer for immuno-staining (in gel staining)
pH pH 7.4 ± 0.1
Ingredients 0.01 M Na2HPO4·2H2O
0.01 M NaH2PO4·H2O
0.154 M NaCl
Preparation: Mix the two buffer solutions to reach pH 7.4 ± 0.1.
Preparation of PBS-solution secondary Phosphate:
Dissolve 17.8 g Na2HPO4·2H2O and 90 g NaCl in 10 L of purified water.
Preparation of PBS-solution primary Phosphate:
Dissolve 5.52 g NaH2PO4·H2O and 36 g NaCl in 4 L of purified water.
Dilute approximately 5 L of PBS-solution secondary Phosphate with PBS-solution primary Phosphate to reach pH 7.4 ± 0.1.
Washing buffer/antibody dilution buffer
Ingredients Triton X100
PBS-buffer for immuno-staining
Preparation: Dilute 10 g Triton X100 in 1,000 mL of PBS buffer for immuno-staining.
Acknowledgments
The basic protocol has been implemented in our laboratory in the mid 1980s by Fritz Elsinger. Since then, we are permanently pursuing VWF multimer analysis using the described electrophoresis method. Over the years the protocol was consistently optimized by subtle improvements. These had been elaborated in collaboration with many technicians working on the method. We acknowledge expert technical support from Alena Kratochwil, Ingrid Neunteufl, Gertrude Maurer, Gabriele Müllner, Nina Pruckner, Astrid Bogat, and Julia Lasnik.
Competing interests
HG, PLT and MS are employees of Baxalta Innovations GmbH, a Takeda company, PLT holds relevant Takeda patents and Takeda stock.
References
Aihara, M., Sawada, Y., Ueno, K., Morimoto, S., Yoshida, Y., de Serres, M., Cooper, H. A. and Wagner, R. H. (1986). Visualization of von Willebrand factor multimers by immunoenzymatic stain using avidin-biotin peroxidase complex. Thromb Haemost 55(2): 263-267.
Bryckaert, M., Rosa, J. P., Denis, C. V. and Lenting, P. J. (2015). Of von Willebrand factor and platelets. Cell Mol Life Sci 72(2): 307-326.
Favaloro, E. J., Pasalic, L., Henry, B. and Lippi, G. (2021). Laboratory testing for ADAMTS13: Utility for TTP diagnosis/exclusion and beyond. Am J Hematol 96(8): 1049-1055.
Lillicrap, D. (2013). von Willebrand disease: advances in pathogenetic understanding, diagnosis, and therapy. Blood 122(23): 3735-3740.
Meyer, D., Obert, B., Pietu, G., Lavergne, J. M. and Zimmerman, T. S. (1980). Multimeric structure of factor VIII/von Willebrand factor in von Willebrand's disease. J Lab Clin Med 95(4): 590-602.
Peyvandi, F., Kouides, P., Turecek, P. L., Dow, E. and Berntorp, E. (2019). Evolution of replacement therapy for von Willebrand disease: From plasma fraction to recombinant von Willebrand factor. Blood Rev 38: 100572.
Ruggeri, Z. M. and Zimmerman, T. S. (1981). The complex multimeric composition of factor VIII/von Willebrand factor. Blood 57(6): 1140-1143.
Seth, R., McKinnon, T. A. J. and Zhang, X. F. (2022). Contribution of the von Willebrand factor/ADAMTS13 imbalance to COVID-19 coagulopathy. Ame J Physiol Heart Circ Physiol 322(1): H87-H93.
Schneppenheim, R. and Budde, U. (2011). von Willebrand factor: the complex molecular genetics of a multidomain and multifunctional protein. J Thromb Haemost.9, Suppl 1:209-15.
Turecek, P. L., Gritsch, H., Pichler, L., Auer, W., Fischer, B., Mitterer, A., Mundt, W., Schlokat, U., Dorner, F., Brinkman, H. J., van Mourik, J. A. and Schwarz, H. P. (1997). In vivo characterization of recombinant von Willebrand factor in dogs with von Willebrand disease. Blood 90(9): 3555-3567.
Turecek, P. L., Peck, R. C., Rangarajan, S., Reilly-Stitt, C., Laffan, M. A., Kazmi, R., James, I., Dushianthan, A., Schrenk, G., Gritsch, H., et al. (2021). Recombinant ADAMTS13 reduces abnormally up-regulated von Willebrand factor in plasma from patients with severe COVID-19. Thrombosis Research 201: 100-112.
Turecek, P. L., Schrenk, G., Rottensteiner, H., Varadi, K., Bevers, E., Lenting, P., Ilk, N., Sleytr, U. B., Ehrlich, H. J. and Schwarz, H. P. (2010). Structure and function of a recombinant von Willebrand factor drug candidate. Semin Thromb Hemost 36(5): 510-521.
Turecek, P. L., Spannagl, M., Kragh, T., Allmaier, G., Turecek, M., Schrenk, G., Gritsch, H., Obermann-Slupetzky, O., Ewenstein, B. M. and Valentino, L. A. (2017). The role of ultralarge multimers in recombinant human von Willebrand factor - a review of physico-and biochemical studies and findings in in vivo models and in humans with von Willebrand disease. Hamostaseologie 37(S 01): S15-S25.
Vangenechten, I. and Gadisseur, A. (2020). Improving diagnosis of von Willebrand disease: Reference ranges for von Willebrand factor multimer distribution. Res Pract Thromb Haemost 4(6):1024-1034.
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4,496 | https://bio-protocol.org/en/bpdetail?id=4496&type=0 | # Bio-Protocol Content
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Carbamoyltransferase Enzyme Assay: In vitro Modification of 5-hydroxymethylcytosine (5hmC) to 5-carbamoyloxymethylcytosine (5cmC)
WY Weiwei Yang
ND Nan Dai
YL Yu-Cheng Lin
WJ William Johnson
RV Romualdas Vaisvila
PW Peter Weigele
YL Yan-Jiun Lee
IS Ira Schildkraut
IJ Ivan R. Corrêa Jr.
LE Laurence Ettwiller
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4496 Views: 843
Reviewed by: Gal HaimovichQin Tang Anonymous reviewer(s)
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Cited by
Original Research Article:
The authors used this protocol in eLIFE Nov 2021
Abstract
Nucleic acids in living organisms are more complex than the simple combinations of the four canonical nucleotides. Recent advances in biomedical research have led to the discovery of numerous naturally occurring nucleotide modifications and enzymes responsible for the synthesis of such modifications. In turn, these enzymes can be leveraged towards toolkits for DNA and RNA manipulation for epigenetic sequencing or other biotechnological applications. Here, we present the protocol to obtain purified 5-hydroxymethylcytosine carbamoyltransferase enzymes and the associated assays to convert 5-hydroxymethylcytosine to 5-carbamoyloxymethylcytosine in vitro. We include detailed assays using DNA, RNA, and single nucleotide/deoxynucleotide as substrates. These assays can be combined with downstream applications for genetic/epigenetic regulatory mechanism studies and next-generation sequencing purposes.
Keywords: DNA modification RNA modification 5-hydroxymethylcytosine 5-carbamoyloxymethylcytosine Carbamoyltransferase
Background
Modification and hyper modification of canonical nucleotides can be found in all domains of life. In bacteriophages, nucleotide modifications are often used as a strategy to evade bacterial immunity, most notably the restriction/modification system. Thus, bacteriophages tend to have a broad array of modifications present throughout their genomes. For example, the genome of T4 bacteriophages uses hydroxymethylated deoxycytidine triphosphate (dCTP) as substrate during DNA synthesis, effectively replacing dC with 5dhmC. Incorporated 5dhmC is further post-synthetically glycosylated, resulting in DNA containing glycosylated 5-hydroxymethylcytosine (Lehman and Pratt, 1960). Recent studies have aimed at expanding the repertoire of known modifications by mining the microbiomes for DNA-modifying enzymes (Ferrer et al., 2005).
In a previous study, we developed the Metagenomics Genome–Phenome Association (MetaGPA) framework to associate genetic data with phenotypic traits at the level of an entire microbiome (Yang et al., 2021). As a case study, we applied MetaGPA to sewage and ocean microbiome samples and successfully identified enzymes associated with cytosine modifications in the DNA. Experimental follow-up on these associations allowed us to identify and validate a novel DNA/RNA modifying enzyme, the 5-hydroxymethylcytosine carbamoyltransferase. This enzyme catalyzes the formation of a previously unknown form of cytosine modification, the 5-carbamoyloxymethylcytosine, using 5-hydroxymethylcytosine in DNA, RNA, or single nucleotides as substrates. Here, we describe the protocol for cloning, expressing, and purifying the enzyme from E. coli. We also describe the protocol for assaying this enzyme in vitro on both nucleic acid polymers and single nucleotides, which greatly expands its potential applications. As shown previously (Yang et al., 2021), the carbamoyltransferase reaction can be included in a next-generation sequencing-based method for genomic mapping of modified cytosines. Other possible applications include genetic engineering, DNA/RNA polymerase kinetics, and post-synthetic modification regulations.
Materials and Reagents
Consumables
Low retention 10 μL tips (VWR, catalog number: 89135-572)
Low retention 200 μL tips (VWR, catalog number: 76175-406)
Low retention 1,000 μL tips (VWR, catalog number: 76175-412)
1.5 mL microcentrifuge tube (Eppendorf, catalog number: 022363204)
8 strip 0.2 mL PCR tubes (VWR, catalog number: 20170-010)
15 mL centrifuge tubes (VWR, catalog number: 21008-103)
50 mL centrifuge tubes (VWR, catalog number: 21008-242)
5 mL serological pipets (VWR, catalog number: 89130-908)
10 mL serological pipets (VWR, catalog number:89130-888)
25 mL serological pipets (VWR, catalog number: 89130-900)
Weigh boats (any source)
Gloves (any source)
Oligo clean & concentrator kit (Zymo Research, catalog number: D4060)
Oligo clean-up and concentrator kit (Norgen Biotek, catalog number: 34100)
For carbamoyltransferase enzyme expression and purification:
Bacteria culture tube (any source)
Carbamoyltransferase plasmid pET28-Kan-his-CT (available upon request)
Competent DH5-alpha E. coli cells (New England Biolabs, catalog number: C2987H)
T7 Express competent E. coli cells (New England Biolabs, catalog number: C2566)
2 L flask (VWR)
Kanamycin stock solution, 40 mg/mL (self-prepared, powder from Americanbio, catalog number: CU01100-00200)
IPTG, 500 mM (self-prepared, powder from TEKnova, catalog number: I3305)
Phenylmethanesulfonyl fluoride (PMSF), 1 M (self-prepared, powder from MilliporeSigma, catalog number: 78830)
HisTrap HP 5 mL column (Cytiva, catalog number: 17524801)
10%–20% Tris-Glycine SDS-PAGE gel (Thermo, Invitrogen, catalog number: XP10205BOX)
Tris-glycine SDS running buffer, 10× (Thermo, Invitrogen, catalog number: LC2675)
Protein ladder (New England Biolabs, catalog number: P7717S)
Blue protein loading dye with reducing reagent (New England Biolabs, catalog number: B7703S)
DTT (MilliporeSigma, catalog number: D9779)
SimplyBlue SafeStain reagent (Thermo, Life Technologies, catalog number: LC6065)
HiTrap Q 5 mL column (Cytiva, catalog number: 17115401)
Bradford protein assay kit (Thermo, catalog number: PI23200)
Dialysis tubing, 6–8 kD (VWR, catalog number:28170-138)
LB agar plate containing 40 μg/mL kanamycin (self-prepared)
LB media (see Recipes)
Iron II solution (see Recipes)
Carbamoylphosphate solution (see Recipes)
TE buffer (see Recipes)
Cell lysis buffer (see Recipes)
HisTrap column buffer A (see Recipes)
HisTrap column buffer B (see Recipes)
HiTrap Q column buffer A (see Recipes)
HiTrap Q column buffer B (see Recipes)
Dilution buffer (see Recipes)
Dialysis buffer (see Recipes)
Ultrapure EDTA, 0.5 M, pH 8.0 (ThermoFisher, catalog number: 15575020), store at RT
Tris-HCl, 1 M, pH 8.0 (Amresco, catalog number: E298-NEB-2L), store at RT
Tris-HCl, 1 M, pH 7.5 (Amresco, catalog number: E199-NEB-2L), store at RT
NaCl (MilliporeSigma, catalog number: 203505), store at RT
Glycerol (self-prepared), store at RT
Imidazole (MilliporeSigma, catalog number: I2399), store at RT
Tryptone (MilliporeSigma, catalog number: T7293), store at RT
Yeast extract (MilliporeSigma, catalog number: Y1625), store at RT
Nuclease-free water (New England Biolabs, catalog number: B1500), store at RT
Ammonium iron (ii) sulfate hexahydrate, 500 μM (MilliporeSigma, catalog number: 203505), store at RT
For carbamoyltransferase enzyme assay:
Phage T4gt genomic DNA (self-prepared), store in TE buffer at -20 °C
Note: E. coli bacteriophage T4 is known to have cytosine glucosylation and hydroxymethylation in its genome (Flodman et al., 2020). T4gt is a mutant deficient in DNA glucosyltransferase, and thus its genomic DNA contains 5-hydroxymethylcytosine. Up to 95% of cytosines in the T4gt genomic DNA are replaced by 5-hydroxymethylcytosine. The propagation of T4gt was done using T7 express (NEB, catalog number: C2566), and the bacterial host was grown in LB medium at 37 °C. The host was infected with phage at the log phase until the culture reached lysis. The phages in supernatant were pelleted by 10% PEG8000 and centrifugated. The genomic DNA of T4gt phage was extracted using phenol/chloroform.
5hmC DNA oligo: 5’-TGTCCGATAGACT/5dhmC/TACGCA (IDT, 5’-TGTCCGATAGACT/i5HydMe-dC/TACGCA), store at -20 °C
5hmC RNA oligo: 5’-GGAGTGAGAAGATGGT/5hmC/TAGGTGTTTATTGGTGATGAA (synthesized with in vitro transcription), store at -20 °C
5-hydroxymethyl dCTP, 100 mM (Zymo Research, catalog number: D1045), store at -20 °C
5-hydroxymethyl CTP, 100 mM (Trilink Biotechnologies, catalog number: N-1087), store at -20 °C
5’-hydroxymethylcytosine Carbamoyltransferase, store at -20 °C
Note: Please see Procedure Section A for expression and purification of the enzyme.
Proteinase K (New England Biolabs, catalog number: P8107), store at -20 °C
Thermolabile Proteinase K (New England Biolabs, catalog number: P8111), store at -20 °C
NEBuffer 2.1, 10× (New England Biolabs, catalog number: B7202), store at -20 °C
Ammonium iron (ii) sulfate hexahydrate, 500 μM (MilliporeSigma, catalog number: 203505, see recipe section), store at RT
Note: Iron (ii) solution should be freshly prepared for the experiment
Carbamoylphosphate, 100 mM (MilliporeSigma, catalog number: C4135, see Recipes), store at -20 °C
Note: Carbamoylphosphate solution should be freshly prepared for the experiment.
ATP, 100 mM (New England Biolabs, catalog number: N0450), store at -20 °C
Nuclease-free water (New England Biolabs, catalog number: B1500), store at RT
1× TE buffer (self-prepared, see Recipes), store at RT
Tris-HCl, 1 M, pH 8.0 (Amresco, catalog number: E298-NEB-2L), store at RT
Tris-HCl, 1 M, pH 7.5 (Amresco, catalog number: E199-NEB-2L), store at RT
NaCl, 5 M (self-prepared), store at RT
Glycerol (self-prepared), store at RT
Ultrapure EDTA, 0.5 M, pH 8.0 (ThermoFisher, catalog number: 15575020), store at RT
Zymo oligo clean & concentrator kit (Zymo Research, catalog number: D4060)
Norgenbiotek oligo clean-up and concentrator kit (Norgenbiotek, catalog number: 34100)
Nucleoside Digestion Mix (New England Biolabs, catalog number: M0649)
Equipment
Thermal cycler (Bio-Rad, T100, catalog number: 1861096)
Fast protein liquid chromatography (FPLC) system (GE Healthcare, model: AKTA GO)
Gel electrophoresis power supply (Thermo, model: EC105)
SDS-PAGE gel electrophoresis system (Invitrogen, model: Xcell surelock mini-cell, catalog number: EI0001)
Gel photography system (AlphaImager HP)
Sonicator for E. coli cell disruption (Misonix, model: S-4000)
Bacteria incubation shaker (New Brunswick Scientific, model: Innova 44)
Agar plate incubator at 37 °C (Napco, model: 310)
UV/Visible spectrophotometer (Amersham Biosciences, model: Ultrospec 2100 pro)
Centrifuge (Beckman Coulter, model: Avanti J-E)
Table-top centrifuge (Eppendorf, model: 5415D)
Vortex shaker
Water bath or heat block
Ice bath
Pipette
Procedure
Expression and purification of His-carbamoyltransferase protein
Figure 1. Major steps for expression and purification of protein.
Transform 50 μL of competent DH5-alpha cells with 10–50 ng of pET28-Kan-his-CT plasmid (follow the manufacturer protocol) and spread 20–30 μL on an agar LB plate containing 40 μg/mL kanamycin. Incubate the plate overnight at 37 °C.
Inoculate 10–50 mL of LB medium containing 40 μg/mL kanamycin in a bacteria culture tube or shaking flask with a single colony from the plate. Grow overnight at 37 °C while shaking at 250 rpm.
Optional: Verify the integrity of the insert by sanger sequencing.
In the next morning, inoculate 1 L of LB medium containing 40 μg/mL kanamycin in a shaking flask with 10–25 mL overnight culture (roughly 1:40 to 1:100 ratio). Grow the cells at 37 °C while shaking at 250 rpm until OD600nm reaches 0.6. Save 1–2 mL cell culture as un-induced control. Pellet the 1–2 mL cells by centrifuging for 5 min at 10,000 × g and freeze in -20 °C for short-term storage.
Note: This step may take several hours. Check OD600nm every 1–1.5 h in the first few hours and then more frequently. Be aware that the cells grow fast in log phase and the OD600nm can increase rapidly when near 0.6.
Transfer the cells to a shaker pre-chilled to 16 °C and let it sit for 20 min to cool down the cell culture.
Note: This step is performed to guarantee that carbamoyltransferase protein expression is induced at its optimal temperature (~16 °C).
Add IPTG at 0.4 mM (stock concentration is 0.4 M, 1,000×) and 1 μM iron II (stock concentration is 500 μM, 500×) to the culture, and continue growth at 16 °C while shaking at 250 rpm for ~24 h. Carbamoyltransferase protein expression is confirmed in step A6, before the entire 1 L volume of culture is processed in step A7.
Note: Iron (ii) is added to facilitate protein folding.
Check protein expression with SDS-PAGE gel.
Harvest 1 mL culture, and pellet cells by centrifuging for 5 min at 10,000 × g.
Note: The purpose of taking 1 mL from the 1 L culture is for the confirmation of protein expression before the entire 1 L culture is harvested and processed. Note that this 1 mL culture is induced, and the 1 mL control culture taken in step A3 is un-induced.
Resuspend the pellet and un-induced cell pellets (saved in step A3) in 1 mL cell lysis buffer.
Lyse the cells in a 1.5 mL microcentrifuge tube on ice with 3–5 cycles of 20 s on/20 s off pulses using sonicator with a microtip. 10 μL is saved as crude lysate. The rest of the volume (1 mL – 10 μL = 990 μL) is used in step A6d.
Pellet the inclusion bodies by centrifuging the sonicated cell suspension at full speed for 10 min at 4°C, and transfer supernatant to a new 1.5 mL microcentrifuge tube.
Mix 10 μL crude lysate taken in step A6c, 10 μL nuclease-free water, and 10 μL blue protein loading dye (3× with reducing reagent added) to get a final volume of 30 μL.
Mix 10 μL of soluble samples (supernatant from step A6d), 10 μL of nuclease-free water, and 10 μL of blue protein loading dye (3× with reducing reagent added) to get a final volume of 30 μL.
Heat samples from steps 6Ae and 6Af at 95 °C for 5 min.
Assemble the SDS-PAGE gel and gel running apparatus, fill with 1× running buffer, load the samples and protein ladder, and run gel at 150 V for approximately 1 h.
Stain the gel with SimplyBlue staining reagent, take picture of the gel, and confirm expression of carbamoyltransferase protein in crude lysate and soluble portion.
Note: The estimated size of carbamoyltransferase enzyme is 63kDa. Presence of protein in soluble lysate should be confirmed before large-scale purification in the next step.
Harvest cells from 1 L cell culture from step A5 by centrifuging for 15 min at 5,000 × g at 4 °C.
Cell resuspension and sonication:
Directly resuspend cell pellet in 30 mL of HisTrap buffer A (or 4 mL buffer per gram of pellet).
Sonicate the cells on ice with 5 s on/5 s off pulses for 30–40 cycles. Set power to max level.
Note: The number of cycles needed for complete disruption of cells depends on the model of sonicator. It is suggested to do a pre-test to determine the best sonication condition before performing the actual experiment.
Centrifuge the sonicated cell suspension for 30 min at 23,000 × g at 4 °C.
Transfer supernatant (~30 mL) and mix with equal volume of HisTrap buffer A for loading to the AKTA purifier. Add the appropriate volume of 1M PMSF to a final concentration of 0.4 mM to prevent protein degradation.
Note: Save 0.1 mL sample as before purification control. Here, the total loading volume is about 60 mL, and the suggested loading volume range is between 50 and 100 mL.
First purification using HisTrap HP 5 mL column on AKTA.
Equilibrate the column with 10 column volume (CV) of HisTrap buffer A.
Load sample at 2 mL/min.
Wash out unbound proteins of the column using 10× CV HisTrap buffer A.
Elute protein using a linear gradient from 0%–100% HisTrap buffer B for a total of 10× CV. Set fraction volume to collect 2 mL per fraction tube.
Check purified proteins in each fraction by adding 5 μL of sample with 15 μL of nuclease-free water and 10 μL of blue protein loading dye (3×, reducing agent added) to get a final volume of 30 μL.
Heat samples at 95 °C for 5 min.
Load the samples and run SDS-PAGE gel (see Figure 2 for example of protein purification with HisTrap column).
Stain the gel with SimplyBlue staining reagent, and take picture of the gel.
Pool fractions with concentrated proteins.
Figure 2. Stained SDS-PAGE gel with samples from the purification with HisTrap column. Arrow marks band of carbamoyltransferase expression at 63 kDa. For this particular example, we pooled fraction 12–18.
Second purification using HiTrap Q column on AKTA.
Mix pooled fractions with 7× volume of dilution buffer so that the final salt concentration is approximately 50 mM.
Equilibrate the column with 10 column volume (CV) of Q buffer A.
Load sample at 3 mL/min.
Wash out unbound proteins of the column using 10× CV Q buffer A.
Elute protein using a linear gradient from 0%–100% Q buffer B for a total of 10× CV. Set fraction volume to collect 2 mL per fraction tube.
Check purified proteins in each fraction by adding 5 μL of sample with 15 μL of nuclease-free water and 10 μL of blue protein loading dye (3×, reducing agent added) to get final volume of 30 μL.
Heat samples at 95 °C for 5 min.
Load the samples and run SDS-PAGE gel (see Figure 3 for example of protein purification with HiTrap Q column).
Stain the gel with SimplyBlue staining reagent (following manufacturer instructions), and take picture of the gel.
Pool fractions with concentrated proteins.
Figure 3. Stained SDS-PAGE gel with samples from the purification with Hitrap Q column. Arrow marks band of carbamoyltransferase expression at 63 kDa. For this particular example, we pooled fraction 9–13.
Transfer purified protein to a dialysis tubing bag (MWCO: 6–8 kD). Dialyze overnight against dialysis buffer at 4 °C.
Carefully transfer samples from dialysis tubing bag and determine concentration of purified carbamoyltransferase using the Bradford protein assay kit (following manufacturer instructions).
Aliquot purified carbamoyltransferase into 50 μL per microcentrifuge tube and store at -20 °C.
dsDNA enzymatic assay
DNA denaturation: 5-hydroxymethylcytosine carbamoyltransferase has a preference for ssDNA; therefore, it is critical to denature dsDNA to ssDNA for optimal conversion.
Prepare 1–2 μg genomic DNA in 5 μL of nuclease-free water or TE buffer in PCR tube
Note: The reaction with T4gt genomic DNA (containing 90–90% 5hmC) is shown as example.
Heat to denature dsDNA in a thermal cycler set at 95 °C for 10 min.
Immediately transfer the tube into an ice bath to avoid re-annealing.
Critical: DNA denaturation is a reversible process. When the temperature is cooled down slowly, denatured ssDNA will anneal again. Thus, it is critical to transfer the heated sample and immediately embed the tube completely in the ice bath.
Add reaction mix (see Table 1) to denatured DNA sample, keep the tube on ice, and mix thoroughly by pipetting up and down for 10 times.
Table 1. Reaction mix for dsDNA modification
Reagent Stock Conc. Final Conc. 50 μL Rxn.
5hmC denatured DNA - 1–2 μg 5 μL
NEBuffer 2.1 10× 1× 5 μL
Iron II solution 500 μM 10 μM 1 μL
Carbamoylphosphate2 100 mM 10 mM 5 μL
ATP 100 mM 5 mM 2.5 μL
Enzyme - 1–7 μM See footnote1
Nuclease-free water - - Bring up to 50 μL
Total - - 50 μL
1 The volume of enzyme added to the reaction should not exceed 10% of the total volume.
2 Carbamoylphosphate has a short half-life at room temperature. Therefore, it is recommended to always keep the solution on ice and to add the enzyme right before the incubation step.
Incubate the reaction in a thermal cycler set to 30 °C for 3 h.
Inactivate the reaction by adding 2 μL of Proteinase K, mix thoroughly, and continue incubating at 37 °C for 30 min.
Follow the Zymo oligo clean & concentrator kit manual to purify DNA product, resuspend, and recover DNA in 20 μL TE buffer or Elution buffer provided in the kit.
After purification, the conversion rate can be measured by quantitative liquid chromatography (see Data analysis).
Use the purified reactions for downstream analysis, or otherwise store at -20 °C.
ssDNA oligo and RNA oligo enzymatic assay
Prepare 5hmC ssDNA or RNA oligo: no denaturation is needed for single-stranded oligos; just prepare 1 μg of oligos in suitable volume between 1–5 μL with nuclease-free water or TE buffer.
Note: Examples of ssDNA or RNA oligo sequences are provided in the Materials and Methods section.
Add reaction mix (see Table 2) to oligo sample, keep the tube on ice, and mix thoroughly by pipetting up and down 10 times.
Table 2. Reaction mix for ssDNA or RNA modification
Reagent Stock Conc. Final Conc. 50 μL Rxn.
ssDNA/RNA oligo - 1 μg 1–5 μL
NEBuffer 2.1 10× 1× 5 μL
Iron II solution 500 μM 10 μM 1 μL
Carbamoylphosphate2 100 mM 10 mM 5 μL
ATP 100 mM 5 mM 2.5 μL
Enzyme - 1–7 μM See footnote1
Nuclease-free water - - Bring up to 50 μL
Total - - 50 μL
1 The volume of enzyme added to the reaction should not exceed 10% of the total reaction volume.
2 Carbamoylphosphate has a short half-life at room temperature. Therefore, it is recommended to always keep the solution on ice and to add the enzyme right before the incubation step.
Incubate the reaction in a thermal cycler set to 30 °C for 3 h.
Inactivate the reaction by adding 2 μL of Proteinase K, mix thoroughly, and continue incubating at 37 °C for 30 min.
For purification of short oligos ≤21 nt, we generally see better recovery with Norgenbiotek Oligo clean-up and concentrator kit. Otherwise, follow the Zymo oligo clean & concentrator kit manual. Resuspend and recover converted DNA/RNA oligo in 20 μL of TE buffer or Elution buffer provided in the kit.
After purification, the conversion rate can be measured by quantitative liquid chromatography (see Data analysis).
Use the purified reactions for downstream analysis, or otherwise store at -20 °C.
Single nucleotide/deoxynucleotide enzymatic assay
Prepare 1:10 dilution of dhmCTP or hmCTP (dilute to 10 mM) with nuclease-free water.
Add reaction mix (see Table 3) to sample, keep the tube on ice, and mix thoroughly by pipetting up and down 10 times.
Table 3. Reaction mix for dhmCTP or hmCTP modification
Reagent Stock Conc. Final Conc. 50 μL Rxn.
dhmCTP or hmCTP 10 mM 0.2 mM 1 μL
NEBuffer 2.1 10× 1× 5 μL
Iron II solution 500 μM 10 μM 1 μL
Carbamoylphosphate2 100 mM 10 mM 5 μL
ATP 100 mM 5 mM 2.5 μL
Enzyme - 1–7 μM See footnote1
Nuclease-free water - - Bring up to 50 μL
Total - - 50 μL
1 The volume of enzyme added to the reaction should not exceed 10% of total reaction volume.
2 Carbamoylphosphate has a short half-life at room temperature. Therefore, it is recommended to always keep the solution on ice and to add the enzyme right before the incubation step.
Incubate the reaction in a thermal cycler set to 30 °C for 3 h.
Inactivate the reaction by adding 2 μL of Proteinase K, mix thoroughly, and continue incubating at 37 °C for 30 min. Because no purification will be performed to clean up Proteinase K, if it remains a concern for downstream analysis, use thermolabile proteinase K instead and perform additional heat inactivation at 55 °C for 10 min.
After the reaction, the conversion rate can be measured by quantitative liquid chromatography (see Data analysis).
Use the reactions for downstream analysis, or otherwise store at -20 °C.
Data analysis
Quantification of the enzymatic reaction is done by measuring the conversion rate of 5dhmC/5hmC to 5dcmC/5cmC using liquid chromatography. To prepare nucleosides for quantitative analysis, we use Nucleoside Digestion Mix (New England Biolabs, catalog number: M0649) and follow the manual for incubation. No additional purification is required for LC-MS analysis. LC-MS analysis was performed on an Agilent 1200 Series LC/MS system equipped with a G1315D diode array detector and a 6120 Single Quadrupole Mass Detector in both positive (+ESI) and negative (-ESI) electrospray ionization modes. LC was performed on a Waters Atlantis T3 column (4.6 × 150 mm, 3 μm) with a gradient mobile phase consisting of aqueous ammonium acetate (10 mM, pH 4.5) and methanol. The identity of each peak was confirmed by MS. The relative abundance of each nucleoside was determined by the integration of each peak at 260 nm or its respective UV absorption maxima. Since the extinction coefficient constant for 5dcmC or 5cmC was not available, the relative quantification was performed by measuring the decrease of 5dhmC or 5hmC. The total abundance of 5dhmC/5hmC and converted 5dcmC/5cmC was normalized to a no enzyme treatment control.
Figure 4 shows an example of nucleoside peaks with a reaction performed on 5dhmC ssDNA (marked in red, sequence provided in Materials and Methods). A no enzyme reaction control is also included (marked in blue). Note the complete disappearance of 5dhmC in the red sample, which suggested almost complete conversion of 5dhmC to 5dcmC. Three replicate reactions were performed for statistical analysis.
Figure 4. Quantification of carbamoyltransferase conversion rate in ssDNA oligo containing an internal 5dhmC.
Notes
The optimal concentration of enzyme for the assay depends on the active units of purified enzyme, and thus can vary from batch to batch. We recommend conducting enzyme serial dilutions to first determine the optimal molarity concentration for the reaction. For calculation of enzyme molarity, use the formula: Molarity = Moles of enzyme/volume of reaction = Mass/(Molecular weight * volume of reaction). The molecular weight of carbamoyltransferase is 63,000 g/mol.
For dsDNA enzymatic assay, we normally see up to 70% conversion using the T4gt genomic DNA; the conversion of 5dhmC to 5dcmC on ssDNA (sequence provided in Materials and Reagents) can reach nearly 100% (example data shown in Data analysis; we suggest using purification batch with ssDNA conversion rate no less than 95%); the conversion for single nucleotide/deoxynucleotide is expected to be between 60%–90%.
Recipes
LB media
Weigh 10 g of tryptone, 5 g of yeast extract, and 10 g of sodium chloride.
Dissolve in 1 L H2O.
Sterilize by autoclaving.
Iron II solution (prepare fresh, this recipe makes 50 mL)
Weigh 10 mg of ammonium iron (ii) sulfate hexahydrate powder.
Dissolve in 5 mL of nuclease-free water to get 5 mM.
Dilute 1:10 with nuclease-free water to get stock concentration at 500 μM.
Carbamoylphosphate solution (prepare fresh)
Weigh 18 mg of carbamoyl phosphate powder.
Dissolve in 1 mL of nuclease-free water to get stock concentration at 100 mM.
TE buffer
Reagent Final concentration Amount
EDTA (0.5 M, pH 8.0) 1 mM 0.2 mL
Tris-HCl (1 M, pH 8.0) 10 mM 1 mL
Nuclease-free water n/a 98.8 mL
Total n/a 100 mL
Cell lysis buffer
Reagent Final concentration Amount
NaCl (5 M) 250 mM 5 mL
Tris-HCl (1 M, pH 7.5) 20 mM 2 mL
Nuclease-free water n/a 93 mL
Total n/a 100 mL
HisTrap Buffer A
Reagent Final concentration Amount
NaCl (5 M) 250 mM 25 mL
Tris-HCl (1 M, pH 7.5) 20 mM 10 mL
Imidazole (2.5 M, pH 8.0) 20 mM 4 mL
Nuclease-free water n/a 461 mL
Total n/a 500 mL
HisTrap Buffer B
Reagent Final concentration Amount
NaCl (5 M) 500 mM 30 mL
Tris-HCl (1 M, pH 7.5) 20 mM 6 mL
Imidazole (2.5 M, pH 8.0) 750 mM 90 mL
Nuclease-free water n/a 174 mL
Total n/a 300 mL
Dilution buffer
Reagent Final concentration Amount
Tris-HCl (1 M, pH 7.5) 20 mM 6 mL
Glycerol 5% 15 mL
Nuclease-free water n/a 279 mL
Total n/a 300 mL
HiTrap Q Buffer A
Reagent Final concentration Amount
NaCl (5 M) 50 mM 5 mL
Tris-HCl (1 M, pH 7.5) 20 mM 10 mL
Glycerol 5% 25 mL
Nuclease-free water n/a 460 mL
Total n/a 500 mL
HiTrap Q Buffer B
Reagent Final concentration Amount
NaCl (5 M) 1.5 M 90 mL
Tris-HCl (1 M, pH 7.5) 20 mM 6 mL
Glycerol 5% 15 mL
Nuclease-free water n/a 189 mL
Total n/a 300 mL
Dialysis buffer (same as protein storage buffer)
Reagent Final concentration Amount
Glycerol 50% 500 mL
Tris-HCl (1 M, pH 7.5) 20 mM 20 mL
NaCl (5 M) 100 mM 20 mL
DTT (1 M) 1 mM 1 mL
Nuclease-free water n/a 459 mL
Total n/a 1,000 mL
Acknowledgments
This work is funded by New England Biolabs Inc.
Competing interests
All authors are employees of New England Biolabs Inc., a manufacturer and vendor of molecular biology reagents, including several enzymes and buffers used in this work.
References
Ferrer, M., Martinez-Abarca, F. and Golyshin, P. N. (2005). Mining genomes and 'metagenomes' for novel catalysts. Curr Opin Biotechnol 16, 588-593.
Flodman, K., Correa Jr, I. R., Dai, N., Weigele, P. and Xu, S. Y. (2020). In vitro Type II restriction of bacteriophage DNA with modified pyrimidines. Front Microbiol 11: 604618.
Lehman, I. R. and Pratt, E. A. (1960). On the structure of the glucosylated hydroxymethylcytosine nucleotides of coliphages T2, T4, and T6. J Biol Chem 235: 3254-3259.
Yang, W., Lin, Y. C., Johnson, W., Dai, N., Vaisvila, R., Weigele, P., Lee, Y. J., Correa Jr, I. R., Schildkraut, I. and Ettwiller, L. (2021). A genome-phenome association study in native microbiomes identifies a mechanism for cytosine modification in DNA and RNA. Elife 10: 70021.
Article Information
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Yang et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
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Biochemistry > Protein > Expression
Biochemistry > Protein > Isolation and purification
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Split-Chloramphenicol Acetyl Transferase Assay to Study Protein-Protein Interactions and Ubiquitylation in Escherichia coli
AF Amir Florentin *
AK Alina Kordonsky *
EY Elon Yariv *
RA Reut Avishid
NE Noa Efron
EA Edache Akogwu
GP Gali Prag
(*contributed equally to this work)
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4497 Views: 1486
Reviewed by: David PaulNeha Nandwani Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Journal of Molecular Biology Oct 2021
Abstract
Protein-protein interactions and protein modifications play central roles in all living organisms. Of the more than 200 types of post-translational modifications, ubiquitylation is the most abundant, and it profoundly regulates the functionality of the eukaryotic proteome. Various in vitro and in vivo methodologies to study protein interactions and modifications have been developed, each presenting distinctive benefits and caveats. Here, we present a comprehensive protocol for applying a split-Chloramphenicol Acetyl-Transferase (split-CAT) based system, to study protein-protein interactions and ubiquitylation in E. coli. Functional assembly of bait and prey proteins tethered to the split-CAT fragments result in antibiotic resistance and growth on selective media. We demonstrate assays for protein interactions, protein ubiquitylation, and the system response to small compound modulators. To facilitate data collection, we provide an updated Scanner Acquisition Manager Program for Laboratory Experiments (SAMPLE; https://github.com/PragLab/SAMPLE) that can be employed to monitor the growth of various microorganisms, including E. coli and S. cerevisiae. The advantage posed by this system lies in its sensitivity to a wide range of chloramphenicol concentrations, which allows the detection of a large spectrum of protein-protein interactions, without the need for their purification. The tight linkage between binding or ubiquitylation and growth enables the estimation of apparent relative affinity, and represents the system’s quantitative characteristics.
Graphical abstract:
Keywords: Chloramphenicol Acetyl Transferase Bacterial two hybrid Protein-protein interaction Ubiquitylation readout Self-ubiquitylation Ubiquitin E3-ligase
Background
Most cellular processes are carried out and controlled by protein-protein interactions (PPIs) and post-translation protein modifications (PTMs). Therefore, detecting PPIs and PPI-dependent PTMs is critical for understanding normal and pathological conditions, and for potential therapeutic development. Indeed, many methodologies have been developed for identification and characterization of PPIs and PTMs. Each of these methods has its own benefits and caveats. In the 1980s, phage display and genetic yeast two-hybrid systems were developed to study PPIs (Smith, 1985; Fields and Song, 1989; Bair et al., 2008). These methods allowed, for the first time, a high-throughput screening of a large repertoire of proteins or peptides. A great benefit of these methods is the linkage to the DNA sequence encoding the identified polypeptide. However, in the phage display systems, proteins interact in the extra-cellular environment, a process that leads to many false positive interactions, due to misfolding. In contrast, complementation of the split-Gal4 transcription factor in the yeast nucleus is required to activate the reporter, and consequently limits the positive readouts of the screen. Cleverly, Stagljar and co-workers circumvented this with a split-ubiquitin system [a system previously developed by Johnsson and Varshavsky (Johnsson et al., 1994)], in which the interaction of membrane proteins induces a proteolytic cleavage that releases a fused nuclear transcription factor, activating reporter genes in the nucleus (Stagljar et al., 1998). Additionally, Michnick and co-workers developed two excellent Protein-fragment Complementation Assays (PCA) based on split dihydrofolate reductase (DHFR) and split-TEM-1 (β-lactamase) enzymes (Pelletier et al., 1998; Galarneau et al., 2002). The split-DHFR system provides growth phenotypic readouts, both in bacteria and yeast. However, seeding of fairly low cell concentrations is required to prevent non-specific growth (Levin-Kravets et al., 2021). Split-reporters that provide fluorescence or luminescence are widely used to detect PPIs. Forster resonance energy transfer by fluorescence lifetime imaging (FRET-FLIM) and bimolecular fluorescence complementation (BiFC) are useful in live cell imaging (Majoul et al., 2002; Walter et al., 2004). The advantage of this approach is the information regarding the cellular localization of the PPIs. Nevertheless, these methods require sophisticated microscopy equipment, which can frequently be a limiting factor.
Eukaryotic protein interactions are often regulated by transient PTMs that challenge the identification of these PPIs. The high sensitivity of mass-spectrometry technologies are beneficial for the detection of a large spectra of PPIs and PTMs (Blagoev et al., 2003; Peng et al., 2003). However, redundancy within the modifier enzymes challenges their linking to their respective targets. Protein microarray serves as an alternative, comprehensive approach for identification of PTMs, while linking them to their modifier enzyme (Gupta et al., 2007). Sequence and structure-based in silico approaches provide predictions of PPIs, and thus facilitate analysis using the above described methods (Marcotte et al., 1999; London et al., 2012; Keren-Kaplan et al., 2013; Jumper et al., 2021). Among over 200 different PTMs in the eukaryotic proteome, ubiquitylation is the most abundant and complex modification, with over 600 ubiquitin E3-ligases in humans. Here, we present a detailed protocol for a recently developed application to detect and quantify PPIs and ubiquitylation, using a recombinant system that is expressed in E. coli, and based on Split-chloramphenicol Acetyl-Transferase (Split-CAT) (Levin-Kravets et al., 2021). Bacterial growth efficiency is the system readout, which can be estimated as endpoint, or continuously measured to obtain kinetics readouts. Contradictory to selection systems that report growth based on synthesis of essential metabolites, such as uracil, thymidine, or histidine, which pose limits on seeding concentration, the Split-CAT system modifies the antibiotic, thus allowing high-density seeding of bacteria. The sensitivity to a wide concentration range of chloramphenicol allows the detection of a large spectrum of affinities of PPIs. The tight correlation between binding or ubiquitylation and growth efficiency allows the estimation of apparent relative affinity (Keren-Kaplan et al., 2016). The system was constructed with several compatible plasmids, which provides modularity, and facilitates its transfer to different bacteria (Figure 1).
Figure 1. Concept of the Split-CAT selection system. The DNA plasmids encoding the system are shown on the left side. The activities of the proteins encoded by the system are shown to the right. (A) Shows a scheme of the PPI study. (B) Shows a scheme of the ubiquitylation study.
Split-CAT as reporter in self-ubiquitylation assay
Here, we demonstrate how to harness the Split-CAT system for a self-ubiquitylation assay, using the ubiquitin E3-ligase NleG6-2 of EHEC as an example. In this assay, we co-express the E3-ligase along with a cognate ubiquitylation cascade, including ubiquitin, E1, and E2 in a 96-well plate, or in an agar Petri dish (Figure 2). In this system, the NleG6-2 serves both as a ligase and as a ubiquitylation target, and therefore it was fused to the N-CAT fragment. The C-CAT fragment is fused to ubiquitin. Upon self-ubiquitylation, a stable covalent isopeptide bond between the C-terminus of ubiquitin and a lysine residue in the E3-ligase facilitates functional assembly of the split-CAT, giving rise to CAM resistance, and growth on selective media (Figure 2A). As a negative control, we co-express the system without the E1 and E2 enzymes (∆E1, ∆E2 in Figure 2B). In this scenario, an attenuated E. coli growth is seen, due to antibiotic tolerance only in low antibiotic concentrations. Without CAM (curve with light blue circles), the growth of the strain with self-ubiquitylation (resistance) is identical to the ∆E1, ∆E2 strain (tolerance). But what is the optimal CAM concentration to run the assay? We found that expression of different protein cascades provides different optimal CAM concentrations. Here, we describe how to identify the optimal CAM concentration for further experiments, where one wishes to study the effect of mutations, small molecule modulators, and more on the ubiquitylation process. We recommend setting the experiment up with increased CAM concentrations, varied from zero to approximately 32 μg/mL (as shown in Figure 2). Cumulative growth is the integral (area under curve) of the growth curve in each of the CAM concentrations (Figure 2C and 2F). This provides a single value that represents the growth efficiency. A plot of the growth efficiencies against CAM concentrations (similar to an IC50 curve) is shown in Figure 2C. The growth efficiency of the strain with ‘resistance’ (light blue) is more significant than that of the strain with ‘tolerance’ (red). Subtraction of the two curves (Res.–Tol.) results in an optimum curve (Figure 2D). The maximum of the curve in Figure 2D provides an optimal CAM concentration for downstream experiments, where one can study the effect of mutants or small molecule modulators.
Materials and Reagents
Tubes 1.5, 15, 50 mL (LIFEGENE catalog numbers: LMCT1.7B, LTB15, LTB50)
Multichannel pipet (Gilson PIPETMAN L Multichannel P12x200L, catalog number: FA10012)
LB agar (1.5% agar, BD DifcoTM Agar, catalog number: 11793523)
Petri dishes 90, 50 mm (MINIPLAST, catalog numbers: 820-090-01-017, 872-050-05-000)
Black matte spray paint for plastic Petri dish covers (RUST-OLEUM 2X Ultra Cover Ultra Matte Spray)
96-well plate (CORNING, catalog number: 3596)
Highly efficient E. coli competent cells, recA- strain (such as Mach1 or DH5α; ThermoFisher, catalog number: C862003 and 18265017 respectively)
Gibson assembly mix (NEB, catalog number: E2611S)
DNA plasmids: pC-CAT-Ub, pTarget-N-CAT and pE3 (available from our laboratory for academic use).
Antibiotics such as ampicillin, kanamycin, streptomycin, and chloramphenicol (FORMEDIUM, catalog number: AMP25, CAISSON LABS, catalog number: 05212005, CHEM-IMPEX INTERNATIONAL, catalog number: 0028, FORMEDIUM, catalog number: CLA01)
Luria-Bertani (LB) medium (NEOGEN, catalog number: NCM0173A)
SOC medium (FORMEDIUM, catalog number: SOC0201)
Equipment
Spectrophotometer (MRC, model: Spectro-V11D)
Vortex (Scientific Industries, model: Vortex-Genie 2, catalog number: SI-0236)
Thermostatic water bath (Fried Electric, WBS)
Incubators (for Petri dishes and shaker for tubes, MRC LABORATORY-INSTRUMUNTS, catalog number: BOD-80, INFORS HT, Ecotro1)
Flatbed office (US-letter/A4) scanner (such as Epson, model: Perfection V19 or V37)
Plate reader-shaker-incubator (TECAN, Sunrise)
Software
SAMPLE (https://github.com/PragLab/SAMPLE)
Fiji/ImageJ (https://fiji.sc or https://imagej.nih.gov/ij/) and its plugin Time Series Analyzer V3 (Balaji J. 2007); https://imagej.nih.gov/ij/plugins/time-series.html)
Analysis software such as Excel, KaleidaGraph, GraphPad Prism or SigmaPlot
Procedure
Cloning of bait and prey or ubiquitylation proteins
We recommend employing the Gibson assembly methodology for cloning (Gibson et al., 2009). However, other methodologies may be used.
We will not provide a protocol for cloning here, but we would like to address a few important points regarding the structure of the final DNA plasmids in the system:
We recommend using a constitutive promoter, such as an un-regulated PTac. We recommend avoiding the use of IPTG, as it inhibits growth. Expression from the T7-promoter requires inducible T7-RNA polymerase, and therefore is also not recommended.
In plasmids for the expression of multiple genes (polycistronic), such as pC-CAT-Ub, that also expresses E1 (UBA1) and E2 (such as yeast Ubc4) enzymes, Shine-Dalgarno (SD) Ribosome Binding Site (RBS) sequences must be designed in front of each of the expressed genes (Prag et al., 1997).
To maintain stabilized copies of each of the plasmids, we recommend using compatible origins of replication (Figure 1).
Co-transformation of plasmid DNA
Use 20–50 μL of highly efficient [108 cfu/µg of DNA (pUC19)] E. coli competent cells. We mainly use Mach1 T1R competent cells prepared by the Inoue Method in our laboratory (Inoue et al., 1990; Sambrook and Russell, 2006). Alternatively, these cells can be purchased from ThermoFisher. The benefit of Mach1 T1R cells is their higher growth rate, which accelerates and thus facilitates the study. Nevertheless, other cells, including DH5α, W3110, or HMS174 can be used.
Use 300–500 ng of each plasmid (Figure 1).
Note: Co-transformation of multiple plasmids is an inefficient procedure that requires high concentrations of DNA. If co-transformation of three plasmids fails, try to transform in steps, i.e., first transform one or two plasmids; then prepare competent cells harboring these plasmid(s), and transform them with the third plasmid.
To facilitate co-transformation, incubate the cells with the DNA plasmids on ice for 30 min, followed by a 45 s heat shock in a 42 °C water bath. Return the mixture to ice for 2 min, and add 1 mL of SOC medium. Incubate in a shaking incubator at 37 °C for 60 min.
Spread all the content of the transformed culture on prewarmed LB agar plates, supplemented with 15 μg/mL kanamycin and 12.5 μg/mL streptomycin (half concentrations of standard selective media plates for transformation; for three plasmids, use third concentrations of each antibiotic, and add 33 μg/mL ampicillin).
Place the plates in a stationary incubator at 37 °C overnight.
Store the plates in a refrigerator at 4 °C for future use (up to 1–2 weeks).
Preparation of culture starters
Prepare a volume of 5–10 mL LB culture of each sample (test, positive control, negative control, etc.), supplemented with 15 μg/mL kanamycin and 12.5 μg/mL streptomycin (we use 50 mL tubes).
Incubate the starters in a shaker incubator at 180 rpm and 37 °C for ~1–3 h, or until the cultures reach 0.3–0.5 OD600nm.
Note: The growth rate in the starters can significantly vary. If one of the strains reaches ~0.5 OD600nm before others, take it out of the incubator, and store it on the bench at room temperature. Cultures should be harvested in the early logarithmic phase of ~0.4 OD600nm. Significant deviation of this concentration can affect the results. Solutions with high O.D. may contain a large number of dead bacteria.
To reduce noise, we recommend spinning down the bacteria, pour the old LB, and replace it with fresh LB that lacks antibiotics. Based on the measured OD600nm, add the appropriate volume to achieve 0.4 OD600nm.
For the spotting assay on an agar plate, adjust the OD of the cultures to 0.2 in new microcentrifuge tubes, at a volume of 500 μL. For a 96-well plate assay, adjust the OD to 0.4 at a volume of 10 mL.
Performing the assay
Assay with 96 well-plate reader in liquid medium
We first determine the optimal CAM concentration for the following binding or ubiquitylation assays. This is done by a series of growth experiments with increasing CAM concentrations, for comparing the growth efficiency of the wild-type with a negative control bacterial strain. The optimal CAM concentration is the one that presents the largest growth difference between the wild-type and the negative control (Figure 2A–2D).
Figure 2. Self-ubiquitylation of NleG6-2 ubiquitin E3-ligase. (A) Assays of NleG6-2 self-ubiquitylation dependent resistance under increased chloramphenicol (CAM) concentrations (0-light blue, 2-red, 4-green, 6-blue, 8-magenta, 10-dark green, 12-yellow, 16-cyan, and 32-brown μg/mL). (B) As a negative control for the experiment shown in A: tolerance growth for a strain that lacks ubiquitylation and resistance (∆E1, ∆E2) is shown. (C) Relative IC50 based on the cumulative growths (integrals) shown in A and B. (D) A curve showing the optimal CAM concentration to run downstream assays. (E) Spotting assay on LB agar Petri dish showing self-ubiquitylation of NleG6-2. The selection system provides a readout for self-ubiquitylation of NleG6-2 in red. Specific negative control for the ubiquitylation (∆E1, ∆E2) in green. Negative controls of only N- or C-CAT fragments are in blue and magenta, respectively. Positive control of the full-length CAT (CAT-FL) is in cyan. (F) The values in the bar-plot represent the ‘relative cumulative growth’ (integrals) of the growth curves shown in plot E.
We recommend growing the bacteria in 0, 2, 4, 6, 8, 10, 12, 16, and 32 μg/mL of final CAM concentrations. First, prepare 10 mL of LB media supplemented with increased 2× CAM concentrations (i.e., 0, 4, 8, 12, 16, 20, 24, 32, and 64) in 15 mL tubes.
We recommend using a multi-channel pipettor to set the 96 well-plate. First, dispense half of the final volume of the 2× CAM LB (75 μL) in each well. Use a 25 mL pipetting reservoir for a multi-channel pipettor, start with the low concentration, and reuse the reservoir with increased CAM concentrations.
Then, dispense the culture (2× OD600) 75 μL in each well, from a 25 mL pipetting reservoir, and mount the 96 well-plate in the shaker reader.
We typically grow the bacteria at 37°C with continuous shaking, and read the OD600 at 20 min intervals. A typical assay takes 12–24 h.
Repeat the above set for the negative control. In the case of the ubiquitylation cascade, there are many negative control options, including ubiquitin mutant at the C-terminus (such as Ub-R77), deletion, or catalytically dead mutants of E1 and E2 enzymes, or targets that lack the E3 recognition element. For PPI experiments, replacement of the prey or the bait with a non-relevant protein is a useful negative control. In the negative control cells, we recommend expressing similar amounts and size of proteins to pose similar burden.
Note: Targets that contain ubiquitin-binding domain(s) (UBDs, such as Rpn10) typically undergo E3-independent ubiquitylation and may be used as a simple positive control.
As mentioned, cumulative growth for each CAM concentration was used to arrive at a single value representing growth efficiency. To arrive at this value, subtract the growth of the negative control from the wild type at each CAM concentration to obtain the optimal concentration for downstream experiments (Figure 2D).
Split-CAT based spots assay on agar plates
The two following assays (depicted in Figure 2E–2F and Figure 3A–3C) provide examples for using the system on regular agar Petri dishes with the spotting assay. Here, we will focus on how to handle and set up these experiments, while in the next example (Figure 4), we will focus on how to collect and analyze the data of these spotting assays. Figure 2E–2F demonstrates the growth curves of E. coli strains that express a self-ubiquitylation system of NleG6-2 and the indicated controls, as well as their quantifications. These assays were performed on agar plates, as described below. Similarly, in Figure 3A–3C, PPIs and ubiquitylation assays of Rpn10 are shown, using the same spot assay procedure.
Prepare LB agar mini (50 mm) plates supplemented with the desired concentration of CAM (between 2–32 μg/mL; as described above, in the 96-well plate assay).
Spot 2.0–2.5 μL of the adjusted OD600 (0.2) cultures on agar plates. We recommend spotting at least three technical repetitions of each strain to calculate the standard deviation.
A grid print below the plate may facilitate the spotting array.
Cover the plate with a black Petri dish cover, and mount on the scanner (Figure 4).
Note: Mount the plates on the scanner with their bottom face down; the scanner scans through the agar. Black covers prevent reflection of the spots on the plastic dish. We spray a compatible Petri dish cover with standard black matte spray paint (at the inner side, to eliminate reflection), and sterilize the covers with 70% ethanol, for multiple uses. Alternatively, one can purchase premade black covers, or use glass Petri dish covers that can be autoclaved (Figure 4).
Figure 3. Split-CAT assay for protein-protein interactions, ubiquitylation, and small molecule modulator. Split-CAT spot assay reporting Rpn10 ubiquitylation and Rpn10:Ub non-covalent binding on selective agar media supplemented with 12 μg/mL CAM. (A) Representative scan at 24 h post seeding. (B) Relative growth curves acquired with the time series analyzer V3 plugin. Quantification of the scans during 36 h represented in A, with standard deviation (n=3). (C) Relative cumulative growth of the curves in B. Single values of the integrals (area under curves) shown in B, presented as a bar-plot with standard deviation (n=3). (D) The E1 inhibitor PYR-41 (50 μM), arrests Rpn10 ubiquitylation dependent growth in liquid medium (24 μg/mL CAM).
Incubate plates at 28–37°C for 12–48 h, and scan images in intervals of 0.5–2 h, using SAMPLE software for further quantification and analyses of the growth efficiency (time-lapse scanning). This incubation and use of the SAMPLE software will be discussed further in a later section.
Figures 2D and 2E demonstrate results of NleG6-2 self-ubiquitylation assay, with the above-described spotting assay on agar plates.
Note: The CAM concentration in this experiment is 12 μg/mL. Growth on liquid or solid media presents different antibiotic resistance.
Split-CAT assays for protein-protein interaction, ubiquitylation, and small molecule modulators
The Split-CAT system may report non-covalent PPIs, covalent PPIs, such as ubiquitylation, and the activity of small molecule modulators. To demonstrate these three utilities, we chose the Ub-receptor Rpn10 as reporter for binding and/or ubiquitylation (Figure 3 and Video 1). Rpn10 is one of the ubiquitin-receptors of the proteasome, and it binds ubiquitin in a non-covalent manner. We discovered that this non-covalent binding directs Rpn10 ubiquitylation to a specific lysine residue (Keren-Kaplan et al., 2012). Therefore, Rpn10 serves as reporter for both binding and ubiquitylation (Figures 3A–3C). As ubiquitylation turns the dynamic non-covalent binding into a stable covalent bond (due to the lack of deubiquitylation and degradation in the bacteria), it significantly increases the stability of the assembled split-CAT, thus providing resistance to a significantly higher CAM concentration (Levin-Kravets et al., 2021). Moreover, like other Ub-receptors (also known as UBD-containing proteins), Rpn10 undergoes ubiquitylation directly by E2 (Levin-Kravets et al., 2016). This simplifies the presented system, as we do not need E3. The above assays were performed on LB-agar plates, to demonstrate their simplicity.
Video 1. Bacterial growth time-lapse shows Rpn10:ubiquitin non-covalent binding versus ubiquitylation.
For small molecule screening, liquid LB is recommended instead of LB-agar, as it allows the use of 96 and 384 well plates. In figure 3D, we demonstrated the system responses to the small molecule PYR-41, an inhibitor of E1 (Yang et al., 2007). Note that, since Rpn10 binds ubiquitin in a non-covalent manner (Figure 3A–3C), we increased the CAM concentration from 12 to 24 μg/mL to detect the effect of E1 inhibition. At 24 μg/mL CAM, non-covalent ubiquitin binding to Rpn10 does not promote growth, but as seen in figure 3D, ubiquitylation promotes growth. The assembly of the split-CAT fragments supports selective growth at this concentration, owing to ubiquitylation (covalent binding) but not to non-covalent binding.
For small molecule screening, liquid LB is recommended instead of LB-agar, as it allows the use of 96 and 384 well plates. In figure 3D, we demonstrated the system responses to the small molecule PYR-41, an inhibitor of E1 (Yang et al., 2007). Note that, since Rpn10 binds ubiquitin in a non-covalent manner (Figure 3A–3C), we increased the CAM concentration from 12 to 24 μg/mL to detect the effect of E1 inhibition. At 24 μg/mL CAM, non-covalent ubiquitin binding to Rpn10 does not promote growth, but as seen in figure 3D, ubiquitylation promotes growth. The assembly of the split-CAT fragments supports selective growth at this concentration, owing to ubiquitylation (covalent binding) but not to non-covalent binding.
Data collection with flatbed scanner
Following spotting the bacteria onto LB agar Petri-dishes, mount the dishes with their bottoms facing down on an office flatbed scanner located in an incubator (i.e., the spots are scanned through the agar; Figure 4A). To capture time-lapse images from the scanner at a defined intervals (typically, 30–60 min), we developed a specialized software dubbed SAMPLE (Scanner Acquisition Manager Program for Laboratory Experiments, Figure 4B–4C), which is available from our website or in github (https://github.com/PragLab/SAMPLE). The software is available for Windows version 7 or newer. SAMPLE will automatically recognize scanners connected to the computer, with a windows image acquisition (WIA) compatible driver installed, i.e., the original manufacturer driver of the scanner. It allows for multiple scanners to simultaneously monitor growth with a single computer. SAMPLE was written using Python (Python Software Foundation, ver. 3.8, https://www.python.org), but is available as a standalone Windows executable. Figures 4B–4C show the graphical user interface for this software.
Figure 4. SAMPLE: a data acquisition software to capture time-lapse scans. (A) Flatbed scanner stacked with black covered dishes in the incubator. (B) SAMPLE includes a simple graphical interface, which allows the user to initially set up the parameters of the time-lapse scan. (C) A second window shows the progress of the scan process.
Data quantification of scans and analyses
Use Fiji or ImageJ for the analysis and quantification of the scans (images). First, download and install the “Time Series Analyzer V3” plugin algorithm into the ImageJ/Fiji from http://rsb.info.nih.gov/ij/plugins/time-series.html.
Figure 5. Quantification of the assay using Fiji. (A) Import of sequence of scan images into Fiji. (B) Crop images. (C) Select spots using ‘Time Series Analyzer’ and (D) Quantification the selected ROIs.
To import the scans, click the “File” menu → select “Import” → “Image Sequence” → choose selected images directory → Check “Use virtual stack” → click “OK” (Figure 5A).
Crop the images to facilitate the analysis. Select the region of the plate → Click “Image” menu → Crop (Figures 5B).
Invoke “Time Series Analyzer V3” from the “Plugin” menu → select “Auto ROI (Region Of Interest) Properties” → adjust to “25 × 25” (pixels.) → Check the “Add on click” → click on the center of a desired set of spots (circles showing the ROI will appear; Figure 5C).
Hit the “Get average” button in the “Time Series V3” window (“Time trace Average” and “Plot Values” windows, including a plot and the alpha numeric data, will appear; Figure 5D).
Copy the raw numeric data to a spreadsheet (such as MS Excel) → Assemble data of different culture types. We recommend repeating the spotting assay in at least three independent cell cultures.
We ignore the derived standard errors, and use the raw data to calculate standard deviation instead.
To produce a time-lapse movie, one can save the ‘image sequence’ in various formats (using the ‘Save As’ option), such as AVI or Animated Gif (see Video 1).
Note: Change the ROI properties and number of samples in each spot, as desired. When choosing the desired ROIs, pick the homogenous area in the center of the spot to avoid marginal effects.
Following the quantification with Fiji, we use the Synergy software KaleidoGraph for data analysis, including sigmoidal curve fitting and integrals calculations. Other commercially available software, such as SigmaPlot, may apply. Given limited access to such software, one may skip the curve fitting and estimate the cumulative growth by summing the entire measured densities over time using Microsoft Excel, and present it as bar-plot with the appropriate standard deviations.
Acknowledgments
We thank Ilan Rosenshine, from the faculty of medicine, Hebrew University, Jerusalem, for kindly providing the plasmid DNA of NleG6-2. This research was supported by the Israeli Science Foundation (grants numbers 651/16 and 1440/21), by the Cooperation Program in Cancer Research of the Deutsches Krebsforschungszentrum (DKFZ) and Israel’s Ministry of Science and Technology (MOST), and by Acceleration Grant program of the Israel Cancer Research Fund (ICRF) Award Number: 940283. The current protocol is derived from the original paper of the Split-CAT system that was published in the Journal of Molecular Biology (JMB) by Levin-Kravets et al. (2021).
Competing interests
GP has equity in Coltac therapeutics LTD, other authors declare no competing interests.
Company and patents: Patents: US10982252, US20200385706, and US20210356467.
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Evaluation of Mitochondrial Turnover Using Fluorescence Microscopy in Drosophila
FM Felipe Martelli
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4498 Views: 1401
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Original Research Article:
The authors used this protocol in eLIFE Feb 2022
Abstract
Mitochondrial dysfunction is associated with perturbations in the cellular oxidative status, changes in energy production and metabolic rate, and the onset of pathological processes. Classic methods of assessing mitochondrial dysfunction rely on indirect measures, such as evaluating mitochondrial DNA copy numbers, or direct but more costly and skilled techniques, such as electron microscopy. The protocol presented here was recently implemented to evaluate mitochondrial dysfunction in response to insecticide exposure in Drosophila melanogaster larvae, and it relies on the use of a previously established MitoTimer mutant strain. MitoTimer is a genetically engineered mitochondrial protein that shows green fluorescence when newly synthetized, irreversibly turning into red as mitochondria age. The protocol described here allows for the easy and direct assessment of shifts in mitochondrial turnover, with tissue-specific accuracy. This protocol can be adapted to assess changes in mitochondrial turnover in response to drugs, rearing conditions, and/or mutations in larva, pupa, or adult fruit flies.
Keywords: Mitochondrial turnover Mitochondria Oxidative stress Drosophila Dissection Tissue imaging Fluorescence microscopy Insecticide
Background
Mitochondria are dynamic organelles that generate most of the chemical energy (ATP) required to sustain cellular activity in eukaryotes (Chan, 2020). These organelles are also involved in the activation of cell death by apoptosis, regulation of Ca2+ homeostasis, synthesis of phospholipids and β-oxidation of fatty acids, as well as the activation, differentiation, and survival of immune cells (Nunnari and Suomalainen, 2012; Chan, 2020). Given the central role of mitochondria in a diverse range of vital cellular activities, the balance between mitogenesis (production of new mitochondria by growth and division) and mitophagy (selective degradation of old/defective mitochondria by autophagy) is tightly regulated by the cell. Whilst mitogenesis is coordinated with vascularization and enhanced oxygen delivery for optimal energy production (Nunnari and Suomalainen, 2012), mitophagy ensures proper mitochondrial function by preventing that defective organelles accumulate and perpetuate damage to healthy ones (Bell and Tower, 2021). This turnover maintains cellular homeostasis, and it may lead to degenerative and age-related disorders when impaired (Chan, 2020; Bell and Tower, 2021).
As we age, mitochondrial gene expression, mitochondrial metabolic rates, and mitochondrial turnover decrease (Bell and Tower, 2021). Such phenomenon is conserved in different species (Landis et al., 2004; Frenk and Houseley, 2018; Leboutet et al., 2020). Mitochondrial defects arise mostly from damage caused by reactive oxygen species (ROS). Many ROS are by-products of oxidative phosphorylation, as leaked electrons from the electron transport chain react with oxygen creating superoxide, the primary mitochondrial ROS (Shadel and Horvath, 2015). Distinct ROS molecules perform a plethora of cellular signalling functions under natural conditions, regulating physiology and metabolism (Valko et al., 2007; Shadel and Horvath, 2015). ROS only become a problem under situations of oxidative stress, which is caused by an exacerbated ROS generation, or reduced cellular antioxidant capacity. In this scenario, ROS can damage lipids, proteins, and nucleic acids, affecting cell homeostasis. Given that great part of ROS are produced in mitochondria, these organelles are prone to oxidative damage, triggering a cycle where damaged mitochondria lead to more ROS generation (Islam, 2017; Pizzino et al., 2017). Mitochondrial dysfunction and mitochondrial ROS are considered key players in aging and aging-associated neurodegenerative disorders, such as Alzheimer’s and Parkinson’s diseases, or multiple sclerosis (Liu et al., 2015; Islam, 2017; Bell and Tower, 2021; Johnson et al., 2021).
A number of methods exist to measure mitochondrial (dys)function. A common indirect measure for mitochondria abundance is to detect mitochondrial DNA copy number (Filograna et al., 2021), but that provides no accurate measure of mitochondrial stress. Assays that measure ATP levels (Brand and Nicholls, 2011) or the activity level of mitochondrial aconitase (Yan et al., 1997) are also methods of estimating changes in mitochondrial metabolic rate or oxidative status. However, such methods, or the ones used to assess mitochondrial respiration (Smolina et al., 2017), require the use of isolated cells or isolated mitochondria. That may cause damage to the organelles during the isolation process, or may remove them from the cellular context (Brand and Nicholls, 2011). Other approaches include more skilled and costly techniques, such as electron microscopy for assessing mitochondria number and morphology (Duranova et al., 2020). A range of fluorescent probes that target the generation of ROS and other metabolites in mitochondria, and changes in mitochondrial membrane potential, are also available (Chu et al., 2021). However, these protocols are more laborious, requiring extra steps to incorporate the probes. In comparison to these methods, the use of genetically engineered MitoTimer mutants offers an easy readout of the levels of newer and older/stressed mitochondria that requires no organelle isolation, no additional staining, or the use of probes, and is less costly. MitoTimer is based on a Timer mutant protein of DsRed engineered with a mitochondrial-targeting sequence. This protein shows green fluorescence when newly synthetized, irreversibly turning into red over time (Ferree et al., 2013; Hernandez et al., 2013; Laker et al., 2014). While the green signal is mostly determined by MitoTimer synthesis, mitochondrial biogenesis, or protein import, the red signal is mainly affected by stress, degradative pathways, mitochondrial proteases, or the ubiquitin–proteasome system (Ferree et al., 2013).
Two recent studies on the mechanisms of action of low insecticide doses used MitoTimer reporter flies to assess the effects of insecticide exposure on mitochondrial turnover (Martelli et al., 2020; Martelli et al., 2022). These studies revealed that the insecticides, spinosad and imidacloprid, caused a rise of both newer and older/stressed mitochondria, suggesting an increase in both mitogenesis and mitochondrial stress. This hypothesis was further corroborated by the observation by electron microscopy of a higher overall number of mitochondria, as well as defective mitochondria, and increased levels of ROS by Dihydroethidium (DHE) staining in insecticide exposed flies (Martelli et al., 2020; Martelli et al., 2022). The protocol used in these studies is described here. This protocol can be promptly adapted for testing the effect of drugs, rearing conditions, or mutations on mitochondrial stress at different life stages of Drosophila. MitoTimer reporters are also available in C. elegans, mice, and mouse cell culture (Laker et al., 2014; Gottlieb and Stotland, 2015).
Materials and Reagents
1.7 mL microtubes (Axygen, catalog number: MCT-175-C)
48-well Nunc cell plate (Thermo Scientific, catalog number: 150687)
Micropipette 200 µL tips (Axygen, catalog number: T-200-Y)
Double-sided tape
Cotton (Genesee Scientific, catalog number: 51-101)
25 × 95 mm polystyrene Drosophila culture vials (Genesee Scientific, catalog number: 32-109RL)
Microscopy slides (Westlab, catalog number: 663-249)
Cover slips (Trajan, catalog number: 471112440M)
90 mm Petri dishes
MitoTimer reporter Drosophila strain (Bloomington Drosophila Stock Center, # line: 57323)
Neuronal Gal4 driver Drosophila strain (Bloomington Drosophila Stock Center, # line: 458)
Phosphate-buffered saline (PBS) (Sigma-Aldrich, catalog number: P5493)
16% Formaldehyde solution (Thermo Fisher Scientific, catalog number: 28908)
Spinosad (Sigma-Aldrich, catalog number: 33706)
Dimethyl Sulfoxide (DMSO) (Sigma-Aldrich, catalog number: 276855-100ML)
Vectashield 10 mL Mounting medium (Vector, catalog number: VEH1000)
Analytical standard sucrose (Merk, product number: 47289)
Fly media (1 L) (see Recipes)
Apple juice-agar plates (1 L) (see Recipes)
Tegosept (250 mL) (see Recipes)
Acid mix (250 mL) (see Recipes)
20% Sucrose solution (200 mL) (see Recipes)
5% Sucrose solution (200 mL) (see Recipes)
1,000 ppm spinosad solution in DMSO (see Recipes)
4% Formaldehyde solution (see Recipes)
Equipment
Dissecting forceps (Fine Science Tools, Dumont #5 Forceps, catalog number:1195-10)
Brush (Artist First Choice Taklon round size 3)
Stereo microscope (Zeiss, model: Stemi 2000-C)
Confocal microscope (Leica, model: SP8 Confocal microscope)
Delicate task wipers (Kimtech Science Kimwipes, manufacturer code: 34120A)
Micropipette P200 (Gibson, catalog number: FA10005M)
Incubator 25 °C (Thermoline Scientific)
500 mL laboratory bottles (Sigma-Aldrich, catalog number: Z305197-10EA)
Agitator (Benchmark Scientific Inc, Super Nutation Mixer, catalog number: B3D 1320)
Stove
Software
ImageJ/FIJI (NIH, https://fiji.sc/)
Excel (Microsoft)
R (The R Foundation, https://www.r-project.org/)
Inkscape (https://inkscape.org/)
Procedure
Drosophila rearing
Set a vial containing fly media with twenty Neuronal Gal4 driver Drosophila adult virgin females and five MitoTimer reporter Drosophila adult males.
Keep vials in an incubator at 25 °C, and transfer adult flies to a new vial containing fly media every 24 h.
Set 2 to 4 vials with adults laying eggs per day, to collect enough larvae of the desired stage (early third instar larvae are used here).
Larvae collection
To collect early third instar larvae, wait 4 to 5 days from egg laying, depending on larvae population density per vial.
Recover larvae from the food using the sucrose extraction method (Nichols et al., 2012). Select a vial containing larvae, and cover half of it with 20% sucrose solution (Figure 1A).
Using a brush, gently disrupt the top food layer and wait for a couple of minutes. The larvae will float, and the food will sink back to the bottom.
Using a brush, collect the larvae and transfer them to an apple juice-agar plate (Figure 1B).
Insecticide exposure
Using the micropipette, load a 48-well Nunc plate with 200 µL of 5% sucrose solution per well.
Under the stereo microscope, select early third instar larvae (Figure 1C) and, using a pair of forceps, gently transfer 25 larvae per well (Figure 1D).
For the insecticide exposure, create a 5x insecticide solution by diluting a 1,000 ppm insecticide stock solution in 5% sucrose solution (or equivalent dose of DMSO for controls) (Denecke et al., 2015).
Add 50 µL of the 5× stock solution to each well containing larvae to be exposed, and give the plate a gentle swirl (Figure 1D).
Keep the plate with larvae under insecticide exposure at 25 °C and protected from light for 2 h (or desirable number of hours), until exposure is over.
Once exposure time is over, using a pair of forceps, gently transfer larvae to a new well containing 250 µL of 1× PBS (Figure 1E).
Tissue dissection and fixation
Transfer larva from the PBS containing well to a microscopy slide containing a drop of 1× PBS.
Under the stereo microscope, begin the dissection. Using two pairs of forceps, hold the larval body at the midpoint, and pull the anterior and posterior regions apart (Figure 1F).
Using a pair of forceps, gently transfer the anterior body section to a microtube containing 500 µL of 4% formaldehyde solution (Figure 1G).
Keep the microtubes at slow agitation in a bench agitator for 20 min, to fix the sample.
With a micropipette, slowly and completely remove the fixative solution, whilst avoiding touching the sample. Dispose of the toxic formaldehyde waste appropriately.
Gently add 500 µL of 1× PBS back to the microtube, to avoid damaging the sample, and place the microtube back on the agitator for another 5 min.
Repeat the previous step two more times.
Under the stereo microscope, add a drop of 1× PBS to a new microscopy slide. Using a pair of forceps, gently transfer the fixed sample from the microtube onto the slide (Figure 1H).
Conclude the dissection by holding the anterior body section sideways with two pairs of forceps, and gently pull them apart from each other to tear the cuticle. Once the brain is located, use the forceps to clear the surrounding tissues. If PBS starts to dry out, add more of it accordingly.
Mounting slides for fluorescence microscopy
Clear the remaining tissue from the slide, leaving only the brain.
Using a delicate task wiper’s tip, carefully drain the excess of PBS. Moistening the wiper’s tip in distilled water before touching the PBS, as far away from the fixed sample as possible, will reduce its dragging capacity, and prevent the sample from being sucked into the wiper.
Add a small drop of Vectashield on the top of the fixed sample, only enough to cover it. Using a pair of forceps, if necessary, adjust sample orientation.
Cut two small pieces of double-sided tape, and place them flanking the sample in Vectashield.
Place the coverslip on the top, aligning its border with the double-sided tape (Figure 1I).
Figure 1. Experimental procedure. A. Use the sucrose extraction method to recover larvae from the vial. B. Using a brush, transfer larvae to an apple-juice agar plate. C. Selected early third instar larvae. D. Transfer 25 larvae to a well pre-loaded with 5% sucrose solution, and expose them to insecticide. E. Once exposure is over, transfer larvae to a new well containing 1× PBS solution. F. Under the microscope, begin dissection by separating anterior and posterior body parts. G. Transfer the anterior body part to a microtube containing fixative solution. After fixing the sample, perform three washing steps by replacing the solution in the microtube with 1× PBS. H. Under the microscope, conclude dissection, and isolate the brain from the other tissues. I. Mount the slide for microscopy using double-sided tape, Vectashield, and a cover slip.
Imaging
Proceed to image acquisition with a fluorescent microscope immediately.
To ensure consistency and accuracy in the measurements, set optimal values of laser power and gain with a control sample, and maintain the same settings across all samples.
Once the desired area is localized, acquire both green (excitation/emission 488/518 nm) and red (excitation/emission 543/572 nm) signals at 200× magnification.
Acquire at least 20 images across the z-stack for every sample.
Data analysis
Analyzing microscopy images on ImageJ
Open the image files on ImageJ and use the freehand selection tool to create a selection area around the area of interest (e.g., whole brain, ventral nerve cord, or optic lobes—used here).
On the top menu, under Analyze, select Measure.
Copy the mean values of fluorescence intensity generated to an Excel spreadsheet.
For every sample, acquire three independent measurements along the z-stack that are representative of the sample signal.
Use the same selection area and same z-stack images for both green and red MitoTimer signal measurements per sample.
Obtain measurements from the same regions in the different samples.
Use at least 10 individual samples per treatment condition for a consistent evaluation of changes on mitochondrial turnover.
Identify microscopy images that are representative of control and treated conditions and, using a suitable program (e.g., Inkscape), organize these images for publication (Figure 2A).
Statistical analyses
On an Excel spreadsheet, organize the data in columns to show treatment condition, nature of the signal, sample replicate number, and signal values (Figure 2B).
Save the file as mitotimer.csv
Open the software R and download the packages lme4 and car
To perform statistical analysis, use the following script:
library(lme4)
library(car)
mitotimer=read.csv(file.choose("mitotimer"),header=TRUE)
model<-lmer(value~signal*treatment+(1|replicate),REML=FALSE,na.action= na.omit,data=mitotimer)
summary(model)
car::Anova(model)
The script generates a generalized linear mixed model that compares treatment and MitoTimer signal values. It also uses the three independent measurement replicates per sample as a random effect. The analysis is followed by an ANOVA test that provides test statistics and the p-values.
Figure 2. Data analysis and representation of mitochondrial turnover results. A. Example confocal microscopy image of green and red MitoTimer signal in the optic lobes of third instar larval brains. Control and spinosad exposed individuals are represented. B. Example of how to organize a .csv table containing the MitoTimer fluorescence signals measured using ImageJ. This table is used to perform the statistical analysis in R. C. Normalized mean fluorescence intensity of MitoTimer signals in optic lobes (n = 20 larvae/treatment; three image sections/larva). Generalized linear mixed model followed by ANOVA. (***) p-value <0.001.
Data normalization and plotting
To facilitate data visualization and plotting, represent the data in terms of normalized mean fluorescence intensity.
Independently for green and red MitoTimer signals, calculate the mean fluoresce intensity of control samples. For a given control group, divide each individual sample value by the group mean and then multiple it by 100. Using that same group mean value, perform the same operation for the respective treated samples. At the end, control groups should have mean green and red signal values of 100, and the treated samples should have values normalized to their respective controls.
Using a suitable program (e.g., R) graphically represent the data in the form of bar plots or box plots, ideally including dot plots (Figure 2C).
Notes
Spinosad was used here to test its capacity to generate oxidative stress. However, this protocol can be applied to the same end for testing the effect of other drugs, rearing conditions, and/or mutations on mitochondrial turnover.
Given the exposure method used here, early third instar larvae are preferable, as late wandering third instars may crawl out of the wells or start pupation during exposure, and first or second instars would offer extra challenges for dissection, given their smaller size. However, other life stages may be selected depending on the research focus, including pupal and adult stages.
Image acquisition under the confocal microscope should be performed immediately after microscopy slides are ready, to guarantee sample integrity and the reliability of the signal acquired.
If performing insecticide/drug exposures for a fixed time with large sample groups, do not start exposure of all groups at the same time. Instead, start the exposure of each group at a different time, creating regular intervals of 10 or 15 min between them (or as required). That will allow time for sample dissection and microscopy of smaller sample batches, while ensuring that all individuals are exposed to roughly the same time.
Handle formaldehyde inside the fume hood, as it is toxic, and dispose of its waste as required.
More than one sample can be transferred to the same microtube with 4% formaldehyde solution. However, if doing so, transfer all these samples from the dissection slide into the microtube at once, to ensure that they are all fixed for the same amount of time.
Here, an elav-Gal4 driver was used to drive MitoTimer expression in neurons. Other Gal4 drivers can be used to different ends. Drosophila Gal4 driver strains can be found on the website of Bloomington Drosophila Stock Center (https://bdsc.indiana.edu/).
Recipes
Fly media (1 L)
Water 800 mL
Maize meal 60 g
Dried active yeast 15 g
Agar 6 g
Acid mix 7.5 mL
Tegosept 5 mL
Set the stove heat to high and in a pot add water and agar. Simmer and bring it to boil. After boiling the mixture for a couple of minutes, reduce the heat to medium, and add maize meal and dried active yeast. Simmer the mixture until homogenous, and turn off the heat. Wait a couple of minutes before adding acid mix and Tegosept while simmering. Dispense around 10 mL of fly media per vial, and wait for 12 h for it to set before closing the vials with cotton. Vials with fly media can be kept in a 4 °C fridge for a month but must be brought to room temperature before usage.
Apple juice-agar plates (1 L)
Water 720 mL
Agar 20 g
Apple juice 200 mL
Brewer’s yeast 7 g
Glucose 52 g
Sucrose 26 g
Tegosept 6 mL
Set the stove heat to high and, in a pot, add water and agar. Simmer and bring it to boil. After boiling the mixture for a couple of minutes, reduce the heat to medium and add apple juice, brewer’s yeast, glucose, and sucrose. Simmer the mixture until homogeneous, and turn off the heat. Wait a couple of minutes before adding Tegosept, and do it while simmering. Dispense enough media to fully cover the petri dish. Wait for it to solidify, and keep it upside down in the fridge at 4 °C; it must be brought to room temperature before usage.
Tegosept (250 mL)
Distilled water 137 mL
Propionic acid 103 mL
Orthophosphoric acid 10 mL
Add distilled water, propionic acid, and orthophosphoric acid into a 500 mL glass bottle. The solution can be kept at room temperature.
Acid mix (250 mL)
Ethanol 95% 250 mL
p-Hydroxybenzoic acid methyl ester 25 g
Add ethanol, distilled water, and p-Hydroxybenzoic acid methyl ester into a 500 mL glass bottle. The solution can be kept at room temperature.
20% Sucrose solution (200 mL)
Distilled water 160 mL
Analytical standard sucrose 40 g
Add distilled water and sucrose into a 500 mL glass bottle and give it a swirl until completely dissolved. It can be kept in the 4 °C fridge for a month, but must be brought to room temperature before usage.
5% Sucrose solution (200 mL)
Distilled water 190 mL
Analytical standard sucrose 10 g
Add distilled water and sucrose into a 500 mL glass bottle and give it a swirl until completely dissolved. It can be kept in the 4 °C fridge for a month but must be brought to room temperature before usage.
1,000 ppm spinosad solution in DMSO
DMSO 1 mL
Spinosad 1 mg
Add DMSO and Spinosad into a 1.7 mL microtube and vortex vigorously for a few minutes until solubilized. Store the insecticide dilution in a freezer (-20 °C) protected from light to prevent degradation. Create small volume aliquots (approximately 100 µL each) to avoid multiple freeze-thaw cycles.
4% Formaldehyde solution
Distilled water 375 µL
16% Formaldehyde solution 125 µL
Add distilled water and 16% formaldehyde to a 1.7 mL microtube.
Acknowledgments
The author was supported by a Victorian Latin America Doctoral Scholarship (Victorian Government and the University of Melbourne), an Alfred Nicholas Fellowship (University of Melbourne), and a University of Melbourne Faculty of Science Travelling Scholarship.
Original research paper: Martelli, F., Hernandes, N. H., Zuo, Z., Wang, J., Wong, C. O., Karagas, N. E., Roessner, U., Rupasinghe, T., Robin, C., Venkatachalam, K., et al. (2022). Low doses of the organic insecticide spinosad trigger lysosomal defects, elevated ROS, lipid dysregulation, and neurodegeneration in flies.Elife 11: e73812.
Competing interests
The author declares no conflicts of interest.
Ethics
Genetic modified Drosophila strain were maintained in a physical containment insectary facility following the biosafety guidelines by the Office of Research Ethics & Integrity at the University of Melbourne.
References
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High-Efficiency Retroviral Transduction for Type 1 Regulatory T Cell Differentiation
MM Michael C. McGee
AA Avery August
WH Weishan Huang
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4499 Views: 1259
Reviewed by: David PaulVishal Nehru Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Nature Communications Jun 2017
Abstract
Type 1 regulatory T (Tr1) cells are an immunoregulatory CD4+ Foxp3- IL-10high T cell subset with therapeutic potential for various inflammatory diseases. Retroviral (RV) transduction has been a valuable tool in defining the signaling pathways and transcription factors that regulate Tr1 differentiation and suppressive function. This protocol describes a method for RV transduction of naïve CD4+ T cells differentiating under Tr1 conditions, without the use of reagents such as polybrene or RetroNectin. A major advantage of this protocol over others is that it allows for the role of genes of interest on both differentiation and function of Tr1 cells to be interrogated. This is due to the high efficiency of RV transduction combined with the use of an IL10GFP/Foxp3RFP dual reporter mouse model, which enables successfully transduced Tr1 cells to be identified and sorted for functional assays. In addition, this protocol may be utilized for dual/multiple transduction approaches and transduction of other lymphocyte populations, such as CD8+ T cells.
Keywords: Retrovirus Transduction Type 1 regulatory cells Primary T cell Cell signaling T cell differentiation T cell engineering
Background
Type 1 regulatory T (Tr1) cells are an immunoregulatory Foxp3- CD4+ T cell subset that is able regulate inflammation and induce tolerance, making them a promising candidate for immunotherapies (Mobs et al., 2010; Gol-Ara et al., 2012; Roncarolo et al., 2014; Bohm et al., 2015). Therefore, signaling pathways and transcription factors regulating Tr1 differentiation and suppressive function are of great clinical interest. RV transduction of CD4+ T cells has been an effective tool in this endeavor (Wu et al., 2013; Mascanfroni et al., 2015; Karwacz et al., 2017). Many studies use Tr1 differentiation as an endpoint because detection of IL-10 and Foxp3 require terminal methods, such as fixation of cells. As a result, signaling pathways and transcription factors regulating the suppressive function of Tr1 cells are less understood than those required for differentiation. This protocol was developed to investigate the role of signaling pathways and transcription factors downstream of TCR/ITK, which regulate both Tr1 differentiation and suppressive function (Huang et al., 2017). The use of an IL10GFP/Foxp3RFP dual reporter mouse model, high efficiency of RV transduction, and bicistronic retroviral vectors that enable transduced cells to be identified via expression of a reporter gene allows sufficient numbers of live transduced Tr1 cells to be isolated for functional assays. Another advantage of this protocol is that it does not make use of chemical transduction enhancers, such as RetroNectin or polybrene, which may be cost-prohibitive and cause cytotoxicity (Kurachi et al., 2017; Eremenko et al., 2021). In addition, the protocol described here may also be utilized for dual transduction strategies and other lymphocyte populations, such as CD8+ T cells.
Materials and Reagents
Eppendorf® Safe-Lock microcentrifuge 1.5 mL tubes (Sigma-Aldrich, catalog number: T9661)
70 μm Cell Strainer (Vita Scientific, catalog number: NSTF90051)
CytoOne T75 filter cap TC flask (USA Scientific, catalog number: CC7682-4875)
100 mm Dish, Tissue Culture-Treated (VWR, catalog number: 25382-428)
Corning® 96-well Clear Flat Bottom Polystyrene TC-treated Microplates (Corning, catalog number: 3596)
0.45 µm Sterile Polyethersulfone Syringe Filter (VWR, catalog number: 28145-493)
10 mL BD Luer-LokTM Syringe (BD, catalog number: 309605)
Axygen 96 Well Clear V-Bottom 550 µL Polypropylene Deep Well Plate (Axygen, catalog number: P-96-450V-C)
IL10GFP/Foxp3RFP dual reporter mouse model (generated as we previously reported in Huang et al., 2017)
Rag-/- mouse model (Jackson Laboratory, Strain #: 002216)
Note: All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) at the Louisiana State University (protocol #: 18-047 and 21-039).
MS Columns (Miltenyibiotec, catalog number: 130-042-201)
LS Columns (Miltenyibiotec, catalog number: 130-042-401)
InVivoMAb anti-mouse CD3ϵ [clone: 145-2C11] (Bio X Cell, catalog number: BE0001-1)
InVivoMAb anti-mouse CD28 [clone: 37.51] (Bio X Cell, catalog number: BE0015-1)
Mouse IL-27 (NS0-expressed) Protein (R&D Systems, catalog number: 2799-ML-010)
Retro-XTM Concentrator (Takara Bio, catalog number: 631456)
Opti-MEMTM, Reduced Serum Medium (Thermo Fisher Scientific, catalog number: 31985070)
Mirus Bio TransIT®-293 Transfection Reagent (VWR, catalog number: 10766-968)
Plat-E cells, a retrovirus packaging cell line described in Morita et al. (2000)
Bicistronic retroviral vector (e.g., pGC-IRES-Thy1.1, pMI-IRES-hCD2, pGC-IRES-BFP2. See Acknowledgments for details).
RPMI 1640 Medium (Fisher Scientific, catalog number: 11-875-119)
DMEM (Fisher Scientific, catalog number: 11-965-118)
Fetal Bovine Serum (Thermo Fisher Scientific, catalog number: 10082147)
1 M HEPES solution (Cytiva, catalog number: SH30237.01)
100× Nonessential Amino Acids (Corning, catalog number: 25-025-ci)
100 mM Sodium Pyruvate (Hyclone, catalog number: sh30239.01)
200 mM L-Glutamine (Hyclone, catalog number: SH30034.02)
100× Penicillin/Streptomycin Solution (Hyclone, catalog number: SV30010)
Puromycin dihydrochloride (Sigma-Aldrich, catalog number: P7255)
Blasticidin S.HCl Solution in HEPES buffer 10 mg/mL (A.G. Scientific, catalog number: B-1247-SOL)
Red Blood Cell (RBC) Lysis Buffer (10×) (Tonbo Biosciences, catalog number: TNB-4300)
Anti-biotin Microbeads (Milteny Biotec, catalog number: 130-090-485)
Mitomycin C (CAS 50-07-7) (Santa Cruz Biotechnology, catalog number: SC-3514B)
3% Acetic Acid with Methylene Blue (StemcellTM Technologies; catalog number: 07060)
Biotin Anti-human/mouse CD45R (B220) [clone: RA3-6B2] (Tonbo Biosciences, catalog number: 30-0452)
Biotin Anti-CD19 monoclonal antibody [clone: HIB19] (Thermo Fisher Scientific, catalog number: 13-0199-82)
Biotin Anti-CD8α rat monoclonal antibody [clone: 53-6.7] (Biolegend, catalog number: 100704)
Biotin Anti-mouse TER-119 [clone: TER-119] (Tonbo Bioscience, catalog number: 30-5921)
Biotin Anti-CD49b (pan-NK cells) rat monoclonal antibody [clone: DX5] (Biolegend, catalog number: 108904)
Biotin Anti-NK1.1 [clone: PK136] (Tonbo Bioscience, catalog number: 30-5941)
Biotin Anti-TCRγδ [clone: GL 3] (eBioscience, catalog number: 13-5711-85)
Biotin Anti-Ly-6G/Ly-6C (Gr-1) rat monoclonal antibody [clone: RB6-8C5] (Biolegend, catalog number: 108404)
Biotin Anti-mouse CD122 (IL-2Rβ) [clone: 5H4] (Biolegend, catalog number: 105904)
Biotin Anti-CD25 rat monoclonal antibody [clone: PC61] (Biolegend, catalog number: 102004)
Biotin Anti-CD44 rat monoclonal antibody [clone: IM7] (Biolegend, catalog number: 103003)
Biotin Anti-CD11b rat monoclonal antibody [clone: M1/70] (Biolegend, catalog number: 101204)
Biotin anti-CD11c monoclonal antibody [clone: 3.9] (Thermo Fisher Scientific, catalog number: 13-0116-82)
Biotin Anti-mouse F4/80 [clone: BM8] (Biolegend, catalog number: 123106)
Ghost DyeTM Violet 510 (Tonbo Biosciences, catalog number: 13-0870-T100)
FITC Anti-mouse TCRβ [clone: H57-597] (Tonbo, catalog number: 35-5961)
Phycoerythrin (PE) Anti-mouse CD25 monoclonal antibody [clone: PC61.5] (Tonbo Biosciences, catalog number: 50-0251)
Allophycocyanin (APC) Anti-CD4 rat monoclonal antibody [clone: GK1.5] (Biolegend, catalog number: 100412)
PE-Cy7 Anti-CD62L rat monoclonal antibody [clone: MEL-14] (Tonbo Bioscience, catalog number: 60-0621-U100)
Pacific BlueTM Anti-human CD2 (hCD2) antibody [clone:TS1/8] (Biolegend, catalog number: 309216)
PE Anti-rat CD90/mouse CD90.1 (Thy-1.1) antibody [clone: OX-7] (Biolegend, catalog number: 202523)
Full DMEM (see Recipes)
Full DMEM + Puromycin/Blasticidin (see Recipes)
Full RPMI (see Recipes)
1× RBC Lysis Buffer (see Recipes)
Primary biotin antibodies master mix (see Recipes)
Magnetic anti-biotin microbeads + sorting antibody master mix (see Recipes)
Equipment
LSR Fortessa X-20 (BD Biosciences)
FACS Aria II Cell Sorter (BD Biosciences)
Avanti J-15R Centrifuge (Beckman Coulter)
Eppendorf Centrifuge 5420 (Eppendorf AG)
MACS® MultiStand (Miltenyi Biotec, catalog number: 130-042-303)
FormaTM Series 3 Water Jacketed CO2 Incubator (Thermo Fisher, catalog number: 4110)
Software
FlowJo (FlowJo, LLC)
FACS DIVA software version 9.0 (BD Biosciences)
GraphPad Prism (GraphPad Software)
Procedure
Retrovirus Production
Note: All handling of retroviral production and transduction occurred under a BSL-2 hood. RV produced from Plat-E are replication incompetent and ecotropic. However, many commonly used genes of interest have been identified as oncogenes, e.g., HRasG12V (Huang et al., 2017).
Maintain Plat-E cells in a T75 flask with full DMEM + Puromycin/Blasticidin (see Recipes).
Seed 4 × 106 Plat-E cells into a 100 mm dish with full DMEM media without Puromycin/Blasticidin.
Transfect Plat-E cells at ~70%–80% confluent, normally ~18–24 h after seeding.
Warm OPTI-MEM and TransIT®-293 to room temperature.
Pipette 1 mL of OPTI-MEM into a polypropylene 1.5 mL Eppendorf tube.
Add 10–15 μg bicistronic retroviral vector plasmid DNA to OPTI-MEM. Gently pipette to mix.
Note: Adjust total plasmid for optimal transfection efficiency. In our experience, 10–15 μg is appropriate for most plasmids.
Before use, vortex TransIT®-293 for 0.5 seconds. Pipette 30–45 μL TransIT®-293 to the OPTI-MEM + plasmid mixture. Gently pipette to mix.
Note: A ratio of 1 μg plasmid DNA to 3 μL TransIT®-293 works well for most plasmids. Adjust total amount of plasmid DNA and ratio DNA:TransIT®-293 reagent to optimize.
Incubate transfection mixture at room temperature for 20 min.
Add transfection mixture dropwise to cells, evenly distributed across the plate. Rock gently back and forth to spread evenly.
Return cells to incubator.
At 24 h post-transfection, collect culture media, and replace with fresh prewarmed full DMEM media.
Centrifuge the collected media at 600 × g and 4 °C for 5 min, then pass through a 0.45 μm filter into a clean 50 mL tube. Store filtered media at 4 °C.
Repeat steps 11 and 12 at 48- and 60-h post transfection, and combine filtered media into a single 50 mL tube.
Add one volume of Retro-X concentrator per three volumes of filtered media.
Gently invert tube to mix.
Incubate at 4 °C overnight.
Centrifuge at 1,500 × g and 4 °C for 45 min.
Discard supernatant. Resuspend pellet in 1/10th of the original volume, in full RPMI media.
Use concentrated RV media immediately, or store at -80 °C in single use aliquots. Under these conditions, RV may be stored up to 2 years after production.
Isolation of Naïve CD4+ T cells
Collect spleen and lymph nodes (superficial cervical, brachial, and inguinal are easily accessible) from IL10GFP/Foxp3RFP dual reporter mouse model.
Homogenize tissues through a 70 μm cell strainer via grinding, and transfer to a 15 mL centrifuge tube.
Centrifuge at 600 × g for 5 min.
Discard supernatant and resuspend cells in 1 mL of 1× RBC lysis buffer (see Recipe 4). Add RBC Lysis Buffer to 5 mL. Incubate at room temperature for 5 min.
Add 2 mL of full RPMI media to neutralize the lysis reaction. Centrifuge at 600 × g for 5 min.
Discard supernatant, resuspend in 1 mL of full RPMI media, and transfer to a 1.5 mL tube.
Centrifuge at 1,500 × g for 1 min, aspirate supernatant, and resuspend in primary biotin antibody master mix (see Recipe 5), using 200 μL per mouse. Remove irregular clumps if any are present.
Incubate on ice for 15 min, shaking every 5 min.
During incubation, prepare magnetic anti-biotin microbeads + sorting antibody master mix (see Recipe 6).
Add 1 mL of full RPMI media to cells. Centrifuge at 1,500 × g for 1 min, aspirate supernatant, and resuspend in magnetic anti-biotin microbeads + sorting antibody master mix.
Incubate cells on ice for 15 min, shaking every 5 min.
While cells are incubating, prepare MS or LS magnetic separation columns on the MACS Multistand. Pre-wet columns with full RPMI media at room temperature. Load a sterile collection tube under the magnetic separation column.
MS column holds one spleen. Pre-wet with 0.5 mL of full RPMI media.
LS column holds four spleens. Pre-wet with 2 mL of full RPMI media.
Add 1 mL of full RPMI media to cells. Centrifuge at 1,500 × g for 1 min, and aspirate supernatant.
Resuspend cells in 550 μL of full RPMI media. Take 500 μL from the top of the tube, and load into magnetic separation columns. Allow media to flow through.
To increase yield, add 550 μL of RPMI to the 1.5 mL tube. Take 500 μL from the top of the tube, and load into magnetic columns.
Allow cells to flow through the column into the sterile collection tube. The naïve T cells are in the flow-through and are ready for sorting (Figure 1A).
Figure 1. Naïve CD4+ T Cell Isolation Gating Strategy. Schematic representation of naïve CD4+ T cell isolation (A). Representative FACS plots of gating strategy for isolating naïve CD4+ T cells by flow sorting for in vitro differentiation (B). Adapted from Huang et al. (2017).
Prepare flow sorting collection tubes by adding 1 mL of cold full RPMI media to 15 mL tubes.
To isolate naïve CD4+ T cells, sort CD44loCD62LhiCD25-Foxp3RFP-TCRβ+CD4+ cells via FACS Aria II Cell Sorter (BD Biosciences). An example of the gating strategy is presented in Figure 1B (Huang et al., 2017).
Centrifuge purified naïve CD4+ T cells at 600 × g for 5 min. Discard supernatant. Resuspend at 1 × 106 cells/mL in full RPMI media.
Tr1 Cell Differentiation
To obtain antigen presenting cells (APCs), homogenize spleen of Rag-/- mouse through a 70 μm strainer into 5 mL of full RPMI media.
Add Mitomycin C to a final concentration of 50 μg/mL. Incubate at 37 °C for 30 min.
Centrifuge at 600 × g for 5 min. Discard supernatant.
Resuspend cells in 1 mL of full RPMI media. Transfer to a 1.5 mL tube.
Wash cells by centrifuging at 1,500 × g for 1 min. Aspirate supernatant. Resuspend in 1 mL of full media. Repeat wash step a total of four times.
Aliquot 10 μL of cells into 90 μL of 3% Acetic Acid with Methylene Blue. Mix by pipetting, and count APCs using a hemocytometer and light microscope. Resuspend at 3 × 106 cells/mL.
Mix equal volumes of Mitomycin C treated Rag-/- APCs and purified naïve CD4+ T cells. The final ratio of naïve CD4+:APCs is 1:3 at 0.5 × 106/mL naïve CD4+ T cells, with 1.5 × 106/mL APCs.
Add anti-CD3ϵ, anti-CD28, and IL-27 to the CD4+:APCs mixture at a final concentration of:
1 μg/mL anti-CD3ϵ (145-2C11)
1 μg/mL anti-CD28 (37.51)
25 ng/mL IL-27
Plate 200 mL of cells per well in a 96-well flat bottom plate.
Incubate at 37 °C and 5% CO2.
Transduction
Note: All handling of retroviral production and transduction occurred under a BSL-2 biosafety cabinet.
Transduce CD4+ T cells after ~18–24 h in culture.
Centrifuge the 96-well plate at 1,500 × g and 37 °C for 5 min.
Carefully remove 170 μL of media, starting from the top of well to avoid disturbing the cells.
Add 20 μL of the concentrated RV (Section A) to the wells.
Empty parent bicistronic retroviral vectors are used as controls (i.e., pGC-IRES-Thy1.1 for gene of interest-IRES-Thy1.1).
Centrifuge the plate at 1,500 × g and 37 °C for 2 h.
Place the 96 well plate back in the incubator at 37 °C for 2 h.
Add 150 μL of prewarmed media to each well with original culture conditions (described in step C8).
Analyze Tr1 cell differentiation, or sort cells for functional assays, 48–72 h post transduction.
Analysis of Tr1 Cell Differentiation
Prepare flow cytometry staining master mix:
30 μL of PBS per sample
1:200 dilution of APC Anti-CD4 Rat [clone: GK1.5], Ghost DyeTM Violet 510, and anti-reporter antibody (e.g., Pacific Blue Anti-hCD2 [clone:TS1/8], PE anti-Thy1.1 [clone: OX-7])
Transfer cells into V-bottom staining plate.
Centrifuge cells at 1,000 × g for 1 min.
Invert plate to remove supernatant.
Add 30 μL of staining master mix to each well, and pipette up and down to resuspend. Incubate at room temperature, protected from light for 20 min.
Add 230 μL of PBS to each well. Centrifuge cells at 1,000 × g for 1 min. Invert plate to remove supernatant.
Resuspend pellet in 280 μL of PBS. Transfer to flow cytometry tubes for analysis.
Use gating strategy in Figure 2, to successfully identify transduced (RV Reporter+) and nontransduced (RV Reporter-) cells. Collect an adequate number of each cell for proper analysis.
Figure 2. Data Collection Gating Strategy. Naïve IL10GFP/Foxp3RFP reporter CD4+ cells were cultured under Tr1 differentiating conditions and RV transduced with control-Thy1.1. Representative FACS plots of gating strategy for collection of RV transduced Thy1.1+ (Reporter+) and nontransduced Thy1.1- (Reporter-) CD4+ cells.
Sorting Transduced Tr1 Cells for Functional Assays
Combine the cells 48–72 h post transduction in a 15 mL tube.
Centrifuge at 600 × g for 5 min. Aspirate supernatant
Resuspend in full RPMI media with 1:200 dilution of:
Ghost DyeTM Violet 510
APC Anti-CD4 Rat [clone: GK1.5]
Anti-Reporter antibody (e.g., Pacific Blue Anti-hCD2 [clone:TS1/8], PE anti-Thy1.1 [OX-7])
Incubate on ice for 15 min, shaking every 5 min.
Transfer to 1.5 mL tube. Incubate on ice for 15 min, shaking every 5 min.
Add 1 mL of full RPMI media to cells. Centrifuge at 1,500 × g for 1 min, aspirate supernatant.
Resuspend cells in 1 mL of full RPMI media, and transfer to tube for sorting.
Using the gating strategy from Huang et al. (2017) to sort for Lymphocyte/Singlet/Live/CD4+/ RV Reporter+/IL10GFP+Foxp3RFP-.
Note: Including Reporter-IL10GFP+Foxp3RFP- cells is useful as another control.
Proceed to use purified cells in functional assays.
Data analysis
Use gating strategy lymphocyte/singlets/live cells/CD4+/Reporter+CD4+ cells for analysis of Tr1 differentiation (Figure 3).
Figure 3. Gating Strategy for Analysis of RV Transduced Tr1 cells. CD4+ T cells were transduced with HRasG12V-IRES-BFP2 RV particles. Representative FACS plots of gating strategy for analysis of RV transduced (BFP+) and nontransduced (BFP-) IL10GFP+ Foxp3RFP- Tr1 cells.
The frequency of IL10GFP+Foxp3RFP-CD4+ T cells can be compared via t-test or one-way ANOVA with an appropriate post hoc test in GraphPad Prism, depending on the number of experimental groups. Reporter- cells can be analyzed as an internal control.
Notes
Including the classic Tr1 markers LAG3 and CD49b (Gagliani et al., 2013) provides further evidence of Tr1 differentiation and is highly recommended.
Overexpression of transcription factors in the Reporter+ cells should be verified via nuclear staining. The eBioscienceTM Foxp3/Transcription Factor Staining Buffer Set (Thermo Fisher, 00-5523-00) is recommended.
In our hands, the protocol described here produces high efficiency of transduction with several different bicistronic retroviral vector backbone plasmids, such as pGC-IRES-Thy1.1, pMI-IRES-hCD2, and pGC-IRES-BFP2.
The efficiency of Plat-E cell transfection (Section A) is a critical step in achieving optimal RV titers and downstream RV transduction efficiency. This can be easily assessed via flow cytometry of Plat-E cells after RV media has been harvested, via gating on viable/Reporter+ cells.
The size and biological function of an insert affect both Plat-E transfection efficiency and RV transduction efficiency. In our hands, transduction efficiency drops substantially with an insert ~2,500 bp, unless it promotes T cell activation (e.g., constitutively active STAT5).
The high efficiency of transduction allows this protocol to be used for dual transduction experiments and transduction of CD8+ T cells under IL-10 inducing conditions (Figure 4).
Figure 4. Gating Strategy for Analysis of dual RV Transduced Tr1 cells. Representative FACS plots of IL10GFP+ Foxp3RFP- Tr1 cells transduced with HRasG12V-IRES-BFP2 and caSTAT5-IRES-Thy1.1.
Recipes
Full DMEM
DMEM
10% FBS
10 mM HEPES solution (pH 7.5)
1× Nonessential amino acids
1 mM Sodium pyruvate
2 mM L-Glutamine
1× Penicillin/Streptomycin Solution
Full DMEM + Puromycin/Blasticidin
DMEM
10% FBS
10 mM HEPES solution (pH 7.5)
1× Nonessential amino acids
1 mM Sodium pyruvate
2 mM L-Glutamine
1× Penicillin/Streptomycin Solution
1 μg/mL Puromycin
10 μg/mL Blasticidin
Full RPMI
RPMI 1640 Medium
10% FBS
10 mM HEPES solution (pH 7.5)
1× Nonessential amino acids
1 mM Sodium Pyruvate
2 mM L-Glutamine
1× Penicillin/Streptomycin Solution
1× RBC Lysis Buffer
50 mL of 10× RBC Lysis Buffer
450 mL of ddH2O
Primary biotin antibodies master mix
200 μL of full RPMI media per mouse
Biotin antibodies to a final concentration of:
5 μg/mL: Anti- B220, CD19, and CD8
2.5 μg/mL: Anti- Ter119, DX5/CD49b, NK1.1 1, TCRγδ, Gr-1 1, CD122, CD25 CD11c, CD11b, and F4/80
0.25 μg/mL: Anti-CD44
Magnetic anti-biotin microbeads + sorting antibody master mix
80 μL of full RPMI Media per mouse
20 μL of anti-biotin microbeads per mouse (Milteny Biotec anti-biotin microbeads)
1:200 Ghost DyeTM Violet 510
1:200 FITC Anti-TCRβ [clone: H57-597]
1:200 PE Anti-CD25 [clone: PC61.5]
1:200 APC Anti-CD4 [clone: GK1.5]
1:200 PE-Cy7 Anti-CD62L [clone: MEL-14]
Acknowledgments
This work is generously supported by National Institutes of Health (R21-AI129422, R56-AI146226, R01-AI138570, and R01-AI151139). M.C.M. is supported by a Careers in Immunology Fellowship from the American Association of Immunologists. W.H. is fellow recipient of the Research Publication Grant in Engineering, Medicine, and Science from the American Association of University Women. We would like to express our gratitude to Drs J. Sun, C. Li, and Y. M. Son for the Plat-E cell line and helpful discussions. We also thank Drs A. Pernis and S. Gupta (pGC) and T. Malek and A. Yu (pMI) for retroviral plasmid backbones. pLKO.3 Thy1.1 (gift from Drs C. Benoist and D. Mathis; Addgene plasmid # 14749) and mTagBFP2-Lifeact-7 (gift from Dr. M. Davidson; Addgene plasmid # 54602) were used to clone Thy1.1 and BFP2 into the respective plasmid backbones, respectively. The protocol presented here was adapted from previously published work (Huang et al., 2017).
Competing interests
M.C.M. declares no conflict of interest. A patent disclosure was filed by W.H. and A.A. on the application of RAS signaling in Tr1 cell differentiation and function at Cornell University, when the original research on RAS signaling was published in 2017. W.H. received funding from MegaRobo Technologies, Ltd and A.A. received funding from 3M, which were not relevant to the research presented in this work.
Ethics
All experimental procedures are approved by the Institutional Biosafety and Animal Care and Use Committees at the Louisiana State University under protocol 18015 (12/10/2018 – present) for biosafety level 2 research, and protocols IACUCAM 18-047 (5/23/2018 – 5/22/2021) and IACUCAM 21-039 (4/26/2021 – 4/25/2024) for animal use.
References
Bohm, L., Maxeiner, J., Meyer-Martin, H., Reuter, S., Finotto, S., Klein, M., Schild, H., Schmitt, E., Bopp, T. and Taube, C. (2015). IL-10 and regulatory T cells cooperate in allergen-specific immunotherapy to ameliorate allergic asthma. J Immunol 194(3): 887-897.
Eremenko, E., Taylor, Z. V., Khand, B., Zaccai, S., Porgador, A. and Monsonego, A. (2021). An optimized protocol for the retroviral transduction of mouse CD4 T cells. STAR Protoc 2(3): 100719.
Gagliani, N., Magnani, C. F., Huber, S., Gianolini, M. E., Pala, M., Licona-Limon, P., Guo, B., Herbert, D. R., Bulfone, A., Trentini, F., et al. (2013). Coexpression of CD49b and LAG-3 identifies human and mouse T regulatory type 1 cells.Nat Med 19(6): 739-746.
Gol-Ara, M., Jadidi-Niaragh, F., Sadria, R., Azizi, G. and Mirshafiey, A. (2012). The role of different subsets of regulatory T cells in immunopathogenesis of rheumatoid arthritis. Arthritis 2012: 805875.
Huang, W., Solouki, S., Koylass, N., Zheng, S.-G. and August, A. (2017). ITK signalling via the Ras/IRF4 pathway regulates the development and function of Tr1 cells. Nature Communications 8: 15871.
Karwacz, K., Miraldi, E. R., Pokrovskii, M., Madi, A., Yosef, N., Wortman, I., Chen, X., Watters, A., Carriero, N., Awasthi, A., et al. (2017). Critical role of IRF1 and BATF in forming chromatin landscape during type 1 regulatory cell differentiation. Nat Immunol 18(4): 412-421.
Kurachi, M., Kurachi, J., Chen, Z., Johnson, J., Khan, O., Bengsch, B., Stelekati, E., Attanasio, J., McLane, L. M., Tomura, M., et al. (2017). Optimized retroviral transduction of mouse T cells for in vivo assessment of gene function.Nat Protoc 12(9): 1980-1998.
Mascanfroni, I. D., Takenaka, M. C., Yeste, A., Patel, B., Wu, Y., Kenison, J. E., Siddiqui, S., Basso, A. S., Otterbein, L. E., Pardoll, D. M., et al. (2015). Metabolic control of type 1 regulatory (Tr1) cell differentiation by AHR and HIF1-α. Nat Med 21(6): 638-646.
Mobs, C., Slotosch, C., Loffler, H., Jakob, T., Hertl, M. and Pfutzner, W. (2010). Birch pollen immunotherapy leads to differential induction of regulatory T cells and delayed helper T cell immune deviation. J Immunol 184(4): 2194-2203.
Morita, S., Kojima, T. and Kitamura, T. (2000). Plat-E: an efficient and stable system for transient packaging of retroviruses. Gene Ther 7(12): 1063-1066.
Roncarolo, M. G., Gregori, S., Bacchetta, R. and Battaglia, M. (2014). Tr1 cells and the counter-regulation of immunity: natural mechanisms and therapeutic applications. Curr Top Microbiol Immunol 380: 39-68.
Wu, C., Pot, C., Apetoh, L., Thalhamer, T., Zhu, B., Murugaiyan, G., Xiao, S., Lee, Y., Rangachari, M., Yosef, N., et al. (2013). Metallothioneins negatively regulate IL-27-induced type 1 regulatory T-cell differentiation. Proc Natl Acad Sci U S A 110(19): 7802-7807.
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Bradford Protein Assay
Fanglian He
In Press
Published: Mar 20, 2011
DOI: 10.21769/BioProtoc.45 Views: 515126
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Abstract
The Bradford protein assay is used to measure the concentration of total protein in a sample. The principle of this assay is that the binding of protein molecules to Coomassie dye under acidic conditions results in a color change from brown to blue. This method actually measures the presence of the basic amino acid residues, arginine, lysine and histidine, which contributes to formation of the protein-dye complex. Unlike the BCA assay, reducing agents (i.e., DTT and beta—mercaptoethanol) and metal chelators (i.e., EDTA, EGTA) at low concentration do not cause interference. However, the presence of SDS even at low concentrations can interfere with protein-dye binding. This technique was invented by Bradford (1976).
Materials and Reagents
Bovine Serum Abumin (BSA) (Sigma-Aldrich)
Coomassie Brilliant Blue G-250 (Sigma-Aldrich, catalog number: 27815 )
Methanol
Phosphoric acid (H3PO4)
Bradford reagent (see Recipes)
Equipment
Spectrophotometer (Tecan)
Whatman #1 paper (Whatman)
Procedure
Standard assay procedure (for sample with 5-100 µg ml-1 protein)
Prepare five to eight dilutions of a protein (usually BSA) standard with a range of 5 to 100 µg protein.
Dilute unknown protein samples to obtain 5-100 µg protein/30 µl.
Add 30 µl each of standard solution or unknown protein sample to an appropriately labeled test tube.
Set two blank tubes. For the standard curve, add 30 µl H2O instead of the standard solution. For the unknown protein samples, add 30 µl protein preparation buffer instead. Protein solutions are normally assayed in duplicate or triplicate.
Add 1.5 ml of Bradford reagent to each tube and mix well.
Incubate at room temperature (RT) for at least 5 min. Absorbance will increase over time; samples should incubate at RT for no more than 1 h.
Measure absorbance at 595 nm.
Microassay procedure (<50 µg ml-1 protein):
Prepare five standard solutions (1 ml each) containing 0, 10, 20, 30, 40 and 50 µg ml-1 BSA
Pipet 800 μl of each standard and sample solution (containing for <50 µg ml-1 protein) into a clean, dry test tube. Protein solutions are normally assayed in duplicate or triplicate.
Add 200 μl of dye reagent concentrate to each tube and vortex.
Follow the procedure described above for the standard assay procedure.
Recipes
Bradford reagent
Dissolve 50 mg of Coomassie Brilliant Blue G-250 in 50 ml of methanol and add 100 ml 85% (w/v) phosphoric acid (H3PO4).
Add the acid solution mixture slowly into 850 ml of H2O and let the dye dissolve completely (note: Do not add H2O into the acid solution).
Filter using Whatman #1 paper to remove the precipitates just before use.
Store in a dark bottle at 4 °C.
Acknowledgments
This work was done in the Andrew Binns Lab in the Department of Biology at University of Pennsylvania, USA and supported by National Science Foundation grants MCB 0421885 and IOS-0818613.
References
Bradford, M. M. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248-254.
Stoscheck, C. M. (1990). Quantitation of protein. Methods Enzymol 182: 50-68.
Article Information
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© 2011 The Authors; exclusive licensee Bio-protocol LLC.
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Biochemistry > Protein > Quantification
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4,500 | https://bio-protocol.org/en/bpdetail?id=4500&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
Generation of iMyoblasts from Human Induced Pluripotent Stem Cells
DG Dongsheng Guo
KD Katelyn Daman
DD Danielle Fernandes Durso
JY Jing Yan
CJ Charles P. Emerson Jr.
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4500 Views: 1950
Reviewed by: Gal HaimovichXiaokang Wu Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in eLIFE Jan 2022
Abstract
Skeletal muscle stem cells differentiated from human-induced pluripotent stem cells (hiPSCs) serve as a uniquely promising model system for investigating human myogenesis and disease pathogenesis, and for the development of gene editing and regenerative stem cell therapies. Here, we present an effective and reproducible transgene-free protocol for derivation of human skeletal muscle stem cells, iMyoblasts, from hiPSCs. Our two-step protocol consists of 1) small molecule-based differentiation of hiPSCs into myocytes, and 2) stimulation of differentiated myocytes with growth factor-rich medium to activate the proliferation of undifferentiated reserve cells, for expansion and cell line establishment. iMyoblasts are PAX3+/MyoD1+ myogenic stem cells with dual potential to undergo muscle differentiation and to self-renew as a regenerative cell population for muscle regeneration both ex vivo and in vivo. The simplicity and robustness of iMyoblast generation and expansion have enabled their application to model the molecular pathogenesis of Facioscapulohumeral Muscular Dystrophy and Limb-Girdle Muscular Dystrophies, to both ex vivo and in vivo muscle xenografts, and to respond efficiently to gene editing, enabling the co-development of gene correction and stem cell regenerative therapeutic technologies for the treatment of muscular dystrophies and muscle injury.
Graphical abstract:
Keywords: Human induced pluripotent stem cells (hiPSCs) iMyoblast Muscular dystrophy Myogenesis Differentiation Reserve cell
Background
Human-induced pluripotent stem cells (hiPSCs) (Takahashi et al., 2007) reprogrammed from somatic cells retain the genetic background of donor cells and have the ability to self-renew and differentiate into cell types of the three germ layers, providing a powerful tool for investigating human myogenesis, muscular dystrophies, and therapeutic development. Over the past decades, several strategies have been developed to differentiate hiPSCs into skeletal muscle, including regulating growth factors and signal pathways that control muscle development during embryogenesis (Chal et al., 2016; Xi et al., 2017), overexpressing transcription factors (Dekel et al., 1992; Darabi et al., 2012; Abujarour et al., 2014), generating myogenic gene reporter iPSC cell lines (Wu et al., 2018; Al Tanoury et al., 2020), or fluorescence-activated cell sorting (FACS) for myogenic cell surface markers (Uezumi et al., 2016).
Here, we report the development of a transgene-free protocol to isolate and expand PAX3+ human skeletal muscle stem cells, iMyoblasts, from patient and unaffected control hiPSCs using a two-step gene-free myogenic induction protocol. The first step utilizes commercially available reagents to generate cultures of differentiated iMyoctyes (Caron et al., 2016). The second step utilizes growth factor-rich medium to stimulate the proliferation of quiescent undifferentiated reserve cells embedded in differentiated iMyocyte cultures, to maintain their growth as PAX3+/MYOD1+/CD82+ iMyoblasts, and to establish low passage frozen cell stocks (Guo et al., 2022). Myogenic reserve cells have been previously identified in mouse and human satellite cell cultures (Yoshida et al., 1998; Laumonier et al., 2017). By contrast, previous gene-free myogenesis protocols have primarily utilized human embryonic stem cell lines (hESCs) and FACS isolation methods to recover cells expressing PAX7+ (Shelton et al., 2014; van der Wal et al., 2018).
iMyoblasts isolated as reserve cells from differentiated hiPSC cultures using our protocol have been extensively characterized as myogenic progenitors. PAX3+/MYOD1+/CD82+ iMyoblasts can be maintained in culture for more than 12 passages and greater than 30 population doublings, while retaining their potential to differentiate into myotubes and to self-renew as reserve cells. Single-cell RNA Seq reveals that iMyoblasts have embryonic/fetal transcriptomes. Following xenoengraftment into the mouse tibialis anterior (TA) fast twitch muscle, iMyoblasts undergo muscle fiber differentiation and myosin isoform switching for adult muscle myosin isoform expression, revealing their plasticity to undergo adult muscle differentiation in response to cues in the in vivo muscle environment. iMyoblasts also populate muscle xenografts and can regenerate muscle in response to injury, providing evidence that iMyoblasts behave as myogenic stem cells with dual potential to undergo muscle differentiation and to self-renew as a regenerative cell population. When generated from iPSCs of Facioscapulohumeral Muscular Dystrophy (FSHD) patient fibroblasts or myoblasts, iMyoblasts express the FSHD disease gene, DUX4, and its downstream target genes, at levels comparable to primary FSHD biopsy myoblasts after differentiation. iMyoblasts from Limb-Girdle Muscular Dystrophy (LGMD) R7 and R9 (formerly LGMD2G and 2I) and Walker Warburg Syndrome (WWS) patients modeled their molecular disease pathologies and were responsive to small molecule and gene editing therapeutics (Iyer et al., 2019; Guo et al., 2022). These findings establish the utility of iMyoblasts for investigating human myogenesis and disease pathogenesis and for the co-development of gene editing and muscle stem cell therapies.
Materials and Reagents
Materials
Cell culture 6-well plate, flat bottom (Falcon, catalog number: 353046)
BioCoat collagen I 6-well clear plate (Corning, catalog number: 356400)
15 cm dishes (Nunc, catalog number: 168381)
100 mm TC-treated culture dish (Corning, catalog number: 430167)
1,000 μL graduated filter tips (USA Scientific, catalog number: 1122-1830)
200 μL graduated filter tips (USA Scientific, catalog number: 1120-8810)
20 μL graduated filter tips (USA Scientific, catalog number: 1123-1810)
10 μL graduated filter tips (USA Scientific, catalog number: 1120-3810)
1.5 mL microcentrifuge tube (Axygen, catalog number: MCT-150-C-S)
15 mL PP centrifuge tubes (Corning, catalog number: 430791)
50 mL PP centrifuge tubes (Corning, catalog number: 430829)
0.2 μm Nalgene Rapid-Flow sterile single use vacuum filter units (Thermo Scientific, catalog number: 566-0020)
Cell lifter (Bio Basic, catalog number: SP91151)
Bench coat or diapers
Sharp-pointed surgical dissecting scissors (Fisherbrand, catalog number: 08-940)
Two autoclaved 500 mL (Corning, catalog number: 1060-500) or 1 L beakers (Corning, catalog number: 6480-1L)
500 mL graduated cylinder (Fisherbrand, catalog number: 08-550G)
Magnetic stir bar, sterilized (Fisherbrand, catalog number: 14-512-129)
50 mL syringe (no needle), sterile (Fisherbrand, catalog number:14-955-455)
Cryovials (Corning, catalog number: 430488)
0.2 mL PCR 8-tube strips (USA Scientific, catalog number: 1402-2900)
Hard-shell PCR plate 384-well, thin-wall (Bio-Rad, catalog number: HSP3805)
Microseal seals (Bio-Rad, catalog number: MSB1001)
Reagents
Dulbecco’s phosphate-buffered saline, 1× (Corning, catalog number: 21-031-CV)
DMEM and Ham's F-12, 50/50 Mix (Corning, catalog number: MT10090CV)
Matrigel hESC-qualified matrix (Corning, catalog number: 354277)
ROCK inhibitor Y-27632 (STEMCELL Technologies, catalog number: 72307)
StemMACS iPS-Brew XF, human (Miltenyi Biotec, catalog number: 130-104-368)
StemMACS passaging solution XF (Miltenyi Biotec, catalog number:130-104-688)
Skeletal muscle differentiation kit (Amsbio, catalog number: SKM-KITM)
Fetal bovine serum (Hyclone, catalog number: SH3007103)
Dimethyl sulfoxide (Fisher, catalog number: BP231-100)
TrypLE express enzyme (Gibco, catalog number: 12605010)
Cell culture grade water (Corning, catalog number: 25-055-CM)
Gelatin from bovine skin (Sigma, catalog number: G9391)
Calcium chloride dihydrate (Sigma, catalog number: 233506)
Ethanol, 200 proof (Fisher Scientific, catalog number: 04-355-223)
Day 12 SPF premium fertilized white leghorn chicken eggs (Charles River, North Franklin, CT)
HBSS without calcium and magnesium (Corning, catalog number: 21-022-CV)
RNeasy Plus mini kit (Qiagen, catalog number: 74136)
SuperScript III first-strand synthesis system (Invitrogen, catalog number: 18080-051)
iQ SYBR® green supermix (Bio-Rad, catalog number: 170-8826)
Distilled water, DNAse, RNAse free (Invitrogen, catalog number: 10977-015)
Paraformaldehyde solution 4% in PBS (Santa Cruz, catalog number: sc-281692)
DAPI (Sigma, catalog number: 9542)
Triton X-100 (Thermo Scientific, catalog number: A16046)
Bovine serum albumin (Sigma, catalog number: A9647)
Goat serum (Gibco, catalog number: 16210064)
Horse serum (Gibco, catalog number: 16050130)
N-2 Supplement (100×) (Gibco, catalog number:17502048)
Insulin-transferrin-selenium (ITS-G) (100×) (Gibco, catalog number: 41400045)
CHIR 99021 (Stemcell, catalog number: 72052)
SB431542 (Selleck chem, catalog number: S1067)
Prednisolone (Sigma, catalog number: P6004)
Antibodies used for IF (Table 1)
Table 1. Antibodies used for IF
Antibody Vendor Catalog number Dilution
Primary antibody
MyoD1 (Clone: 5.8A) Dako M3512 1:50
MF20 DSHB MF 20 1:100
MEF2C Sigma HPA005533 1:100
Secondary antibody
Goat anti-mouse IgG Alexa Fluor 488 Invitrogen A11001 1:500
Goat anti-mouse IgG2b Alexa Fluor 488 Invitrogen A21141 1:500
Donkey anti-rabbit IgG Alexa Fluor 488 Invitrogen A21206 1:500
Antibodies used for FACS assay (Table 2)
Table 2. Antibodies used for FACS assay
Antibody Vender Catalog number
APC mouse anti-human CD56 BD 555518
PE anti-human CD82 BioLegend 342103
FITC anti-human CD318 BioLegend 324004
APC anti-human ERBB3 BioLegend 324708
FITC anti-human NGFR BioLegend 345104
PE anti-human CD18 BioLegend 373407
0.1% gelatin (see Recipes)
HMP medium (see Recipes)
2× HMP freeze medium (see Recipes)
N2 medium for differentiation (Chal et al., 2016) (see Recipes)
Prednisolone medium for differentiation, modified from Al Tanoury et al. (2021) (see Recipes)
Equipment
Pipettes
4 °C Fridge, -20 °C freezer and -80 °C freezer
Biological safety cabinet (Thermo Scientific, catalog number: 1323TS)
Forma series II water-jacketed CO2 incubator (Thermo Scientific, catalog number: 3110)
In vitro hypoxic cabinet (Coy Laboratory, catalog number: O2 Control Cabinet Model 4)
Eclipse TS100 inverted routine microscope (Nikon, catalog number: Eclipse TS100)
DC300F digital microscope camera (Leica)
IEC CL30R centrifuge (Thermo)
Thermo Scientific Sorvall Legend XTR Centrifuge (Thermo)
Countess II automated cell counter (Invitrogen, catalog number: AMQAX1000)
Countess cell counting chamber slides (Invitrogen, catalog number: C10312)
Oil-free vacuum pump OFP-400 (Thermo)
Refrigerated vapor traps (Thermo)
Digital series SpeedVacTM systems (Thermo, mode SPD111V)
NanoDrop 1000 spectrophotometer (Thermo scientific)
C1000 touch thermal cycler (Bio-Rad)
CFX Opus 384 real-time PCR system (Bio-Rad)
Procedure
Chick Embryo Extract Preparation
Spread out bench coat and/or diapers to contain the mess.
Fill three 15 cm Petri dishes with ice-cold HBSS and put the dishes on ice.
Stab a hole into each chick egg using the pointed end of a pair of scissors, and then cut a window out of each eggshell.
Remove the embryo and place it in 15 cm Petri dish with ice-cold HBSS.
Decapitate embryo using sterile scissors, leaving as much of the neck as possible.
Rinse embryos two times in another two 15 cm Petri dishes with ice-cold HBSS to remove blood. Refresh HBSS as necessary.
Store embryos in a sterile beaker with HBSS on ice until all embryos have been collected.
Transfer the embryos (no HBSS) into a 50 mL syringe (no needle) and macerate embryos by pushing through the 50 mL syringe into an ice-cold, sterile graduated cylinder.
Add an equal volume of ice-cold HBSS, transfer to another sterile beaker with a stir bar, cover with aluminum foil, and stir gently at 4 °C for 1 h.
Transfer 45 mL to sterile 50 mL centrifuge tubes and spin at 4 °C for 1 h at 10,000 rpm.
Collect supernatant (Chick Embryo Extract) and store in aliquots at -80 °C. Five dozen eggs make approximately 200–250 mL final Chick Embryo Extract.
Maintenance of Human iPSCs (hiPSCs)
Maintain the hiPSCs in matrigel-coated 6-well plate in StemMACS iPS-Brew X medium at 5% CO2/37 °C /5% CO2 incubator and change the medium every day.
Passage of hiPSC
Check the hiPSCs confluence. When the hiPSCs grow to 95% confluence, it is time to passage the cells. We usually passage the cells every four to five days.
6-well plate matrigel coating: aliquot 250 μL of matrigel per tube and store at -80 °C. When coating plates, thaw aliquoted matrigel on ice and then dilute matrigel with 25 mL of cold DMEM/F12 (1:100). Add 1mL of diluted matrigel to each well of a 6-well plate and keep the plate in the incubator for more than 30 min before use; and then aspirate the matrigel and add 2 mL of StemMACS iPS-Brew XF supplemented with 10 μM of ROCK inhibitor Y-27632.
Aspirate the medium supernatant and wash the cells with 2 mL of DMEM/F12.
Add 1 mL of StemMACS passaging solution XF per well and incubate the plate in the incubator until the cells detach from the plate. It takes approximately 1.5–2 min for the cells at colony edges to start to lift off.
Aspirate the StemMACS passaging solution XF and add 3 mL of StemMACS iPS-Brew XF supplemented with ROCK inhibitor Y-27632.
Gently detach the colonies using a cell lifter and gently pipette up and down two to three times (1 mL pipette setting 900 μL) to break up the colonies into smaller cell clusters.
Transfer the cell clusters into a fresh coated 6-well plate with a splitting ratio between 1:5 and 1:20. Transfer the plate into the incubator and gently shake the plate to evenly distribute the cell clusters.
After 48 h, replace medium with fresh StemMACS iPS-Brew XF without ROCK inhibitor and continue with daily medium changes.
hiPSC Myogenic Differentiation
A commercial skeletal muscle differentiation kit, including SKM01 Skeletal Muscle Induction Medium, SKM02 Myoblast Medium, and SKM03 Myotube Medium, was selected for hiPSCs myogenic differentiation. The myogenic differentiation was completed based on the kit instructions with modifications.
hiPSCs myogenic progenitor cell induction (S1 cells)
Dissociate hiPSCs into single cells after the cells have reached 60%–80% confluence, aspirate the medium, and wash the cells with DMEM/F12. Add 1 mL of TrypLE:0.5 mM EDTA (3:1) per well and incubate in a 37 °C incubator for approximately 5 min.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium and collect the cells in a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of warm Skeletal Muscle Induction Medium (SKM01).
Count the number of viable cells.
Plate 25,000 cells onto collagen I-coated 6-well plate with the density of 2,500 cells/cm2 in SKM01 medium.
Place the cells in 5% O2/5% CO2/37 °C incubator and gently shake the plate to evenly distribute the cell clusters.
Change fresh SKM01 medium every other day.
Passage the cells at day 6
Aspirate the medium and wash with PBS.
Add 1 mL of TrypLE per well and incubate the plate in a 37 °C incubator for 3–5 min until all of the cells detach from the plate.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium and collect the cells in a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of warm Skeletal Muscle Induction Medium (SKM01).
Replate the cells onto collagen I-coated 6-well plate with a ratio of 1:4 in SKM01 medium.
Change SKM01 medium every other day until day 10 during maintenance of cultures in 5% O2/5% CO2/37 °C incubator.
Commitment of S1 cells to myogenic progenitors (S2 cells)
After 10 days in SKM01 Skeletal Muscle Induction Medium, dissociate S1 cells and replate into Skeletal Myoblast Medium (SKM02) for S2 myogenic progenitor induction.
Aspirate the medium and wash with PBS.
Add 1 mL of TrypLE per well and incubate the plate at 37 °C incubator for 5 min until all of the cells detach from the plate.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium and collect the cells in a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of warm HMP medium.
Count the number of viable cells.
Take 25,000 cells per well of a 6-well plate with the density of 2,500 cells/cm2 to a 1.5 mL tube and centrifuge at 168 × g for 3–5 min. The remaining cells can be frozen in aliquots for future use (see note 1 “S1 cell cryopreservation and thawing” for more detail).
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of warm SKM02 medium.
Replate the resuspended cells to collagen I-coated 6-well plate (Corning, catalog number: 356400) and add another 1 mL of SKM02 medium.
Place the cells in 5% O2/5% CO2/37 °C incubator and gently shake the plate to evenly distribute the cell clusters.
Change fresh SKM02 medium every other day until the cells reach confluence. It usually takes 7–8 days.
Skeletal Muscle Differentiation
After 7–8 days in SKM02 medium, aspirate the SKM02 medium and add 2 mL of warm SKM03 Myotube Medium.
Move the plate to 5% CO2/37 °C incubator and change SKM03 medium every other day until day 7 (Figure 1A).
Reserve Cell Isolation and iMyoblast Expansion
After 7 days in SKM03 medium, dissociate S3 cells and replate directly onto gelatin-coated dishes in HMP medium to stimulate growth of iMyoblasts and isolate iMyoblast lines. HMP medium includes chick embryo extract enriched with FGF and growth factors (Seed et al., 1988) required to activate reserve cells and then maintain iMyoblast growth and expansion. Representative images of proliferating S3 iMyocytes and iMyoblasts are shown in Figure 1.
Aspirate the medium and wash with PBS.
Add 0.5–1 mL of TrypLE per well and incubate the plate in a 37 °C incubator. Approximately 5 min later, most of the cells detach from the plate, and there are still some single cells attached to the plate.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium and gently detach the cells using a cell lifter.
Collect the cells into a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 5 mL of warm HMP medium.
Replate 0.5–1 mL of cell suspension onto 0.1% gelatin-coated 10 cm dishes in 10 mL of HMP medium.
Culture plates in 5% CO2/37 °C incubator after gently shaking plates to evenly distribute the cells.
The next day iMyoblasts should attach to the plates; change fresh HMP medium daily.
After 4–6 days in HMP medium, dissociate the cells from plate for expansion.
Aspirate the medium and wash with PBS.
Add 1.5 mL of TrypLE per 10 cm dish and incubate the plate at 37 °C for approximately 5 min until all of the cells detach from the plates.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium.
Collect the cells into a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 2 mL of warm HMP medium.
Count the number of viable cells.
Plate 150,000–200,000 (0.15–0.2 M) cells onto 0.1% gelatin-coated 10 cm dishes in HMP medium.
Move the plate into 5% CO2/37 °C incubator and shake the plate gently to evenly distribute the cell clusters.
Change fresh HMP medium daily until day 4.
Passage the cells again to expand the reserve cells.
After initial S3 cell dissociation and replating, cultures include iMyoblasts and residual fiber-like cells. These fiber-like cells do not survive several passages, providing enriched cultures of iMyoblasts (Figure 1B) that can either be further expanded or frozen in aliquots for future use.
Aspirate the medium and wash with PBS.
Add 1.5 mL of TrypLE per 10 cm dish and incubate the plate at 37 °C for approximately 5 min until all the cells detach from the plates.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium.
Collect the cells into a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 2 mL of warm HMP medium.
Count the number of viable cells.
Add an equal volume of 2xHMP freeze medium and mix well.
Aliquot to cryovials according to 1 mL per cryovial.
Transfer the cryovials to freezing container and put the freezing container into a -80 °C freezer.
Transfer the cryovials to a liquid nitrogen tank for long time storage the next day.
Figure 1. Representative image of differentiated S3 iMyocytes and proliferating iMyoblasts. Representative phase images of (A) S3 iMyocytes after 7 days of differentiation (17U); (B) proliferating iMyoblasts (17U). Scale bar = 100 μm. 17U iMyocytes and 17U iMyoblasts were isolated from iPSCs of a healthy control human subject.
iMyoblast Characterization
iMyoblasts were characterized using qPCR for gene expression, immunofluorescence (IF), FACS assay, and differentiation (Figure 2).
Figure 2. qPCR assays of iMyoblast and iMyotube muscle regulatory and differentiation gene expression. (A) qPCR assays of MyoD, PAX3, PAX7, and MYF5 in cultures of 17U proliferating iMyoblasts, which express MYOD and PAX3, compared to 17Ubic adult bicep biopsy myoblasts, which express MYOD, PAX3, PAX7, and MYF5. (B) qPCR assay of CKM and MYH8 muscle protein RNAs in undifferentiated 17U iMyoblast cultures and differentiated iMyotube cultures. ΔCT relative to housekeeping gene RPL13A is shown as mean ± SD. Each dot corresponds to data from individual biological replicates. 17U iMyoblasts and 17Ubic were isolated from iPSC and muscle of a healthy control human subject.
qPCR assay for gene expression
RNA isolation from cell pellets
Collect cell pellets (iMyoblasts or differentiated iMyotubes) and isolate RNA using the RNA mini plus kit following the protocol.
Measure RNA concentration using Nanodrop; if needed, concentrate the RNA using Speedvac concentrator plus.
cDNA Synthesis
Prepare RNA/primer mix on ice in a 0.2 mL PCR tube. Mix thoroughly and centrifuge briefly.
Component Amount
Up to 2 μg n μL
50 μM Oligo (dT)20 1 μL
Random hexamers 1 μL
10 mM dNTP mix 1 μL
RNase-free water To 10 μL
Incubate the PCR tube at 65 °C for 5 min, then place on ice for at least 1 min.
Prepare the following cDNA synthesis mix and add each component in the indicated order. Mix thoroughly and centrifuge briefly.
Component Amount for 1 reaction
10× RT buffer 2 μL
25 mM MgCl2 4 μL
0.1 M DTT 2 μL
RNaseOUT (40 U/μL) 1 μL
SuperScript III RT (200 U/μL) 1 μL
Add 10 μL of cDNA synthesis mix to each RNA/primer mixture. Mix thoroughly and centrifuge briefly. Proceed with the following incubation protocol.
Temperature Run Time
25 °C 10 min
50 °C 50 min
85 °C 5 min
4 °C hold
Collect reactions by brief centrifugation and add 1 μL of RNase H to each tube. Centrifuge briefly.
Incubate for 20 min at 37 °C.
Dilute cDNA synthesis product to 10 ng/μL for qPCR or store at -20 °C freezer.
qPCR using iQ SYBR Green
Thaw iQ SYBR green supermix and cDNA, if stored at -20 °C freezer, on ice or cold room.
Make 20× primer stock at 6 mM stock. Final concentration of primer stock in reaction will be 300 nM: add 6 μL of forward primer (100 mM stock), 6 μL of reverse primer (100 mM stock), and 88 μL of dH2O. Mix thoroughly and centrifuge briefly. The primers used are listed in Table 3.
Table 3. Primers used for qPCR assays
Gene name NCBI Gene ID Sequence (5'-3')
RPL13A 23521 For: AACCTCCTCCTTTTCCAAGC
Rev: GCAGTACCTGTTTAGCCACGA
CKM 1158 For: ATGCCATTCGGTAACACCCAC
Rev: GCTTCTTGTAGAGTTCAAGGGTC
MYH8 4626 For: AATGCAAGTGCTATTCCAGAGG
Rev: ACAGACAGCTTGTGTTCTTGTT
MYOD1 4654 For: GCGGAACTGCTACGAAGG
Rev: AGGGCTCTCGGTGGAGAT
PAX3 5077 For: CACCTTCACAGCAGAACAGC
Rev: CAGCTTGCTTCCTCCATCTT
PAX7 5081 For: GGGAAGAAAGAGGAGGAGGA
Rev: TTCAGTGGGAGGTCAGGTTC
MYF5 4617 For: CCACCTCCAACTGCTCTGAT
Rev: TGATCCGGTCCACTATGTTG
Prepare the master mix on ice by adding the components below, except cDNA. Mix extra 10% for more reactions. Mix thoroughly and centrifuge briefly.
Component 10 μL total volume
iQ SYBR Green Supermix (2×) 5 μL
6 mM for/rev primer stock (20×) 0.5 μL
Water 3.5 μL
Dispense 9 μL of aliquots into each well of 384-well PCR plate.
Add 1 μL of cDNA samples to PCR tubes/well.
Alternative: cDNA could also be diluted into 5 ng/μL and add 2 μL of cDNA to the master mix below:
Component 10 μL total volume
iQ SYBR Green Supermix (2×) 5 μL
6 mM for/rev primer stock (20×) 0.5 μL
Water 2.5 μL
Seal the plate and centrifuge briefly. Proceed to the incubation below:
Step Temperature Reaction time
1 95 °C 2 min
2 95 °C 10 s
3 60 °C 30 s + Plate read
4 Go to step 2, 39 more times
5 Melt Curve, 65 °C to 95 °C, increment 0.5 °C 5 s + Plate read
End
Perform data analysis according to instrument-specific instructions.
IF staining for MF20, MYOD1
iMyoblasts are plated or differentiated in 24-well plate or 4-well chamber slide for IF staining.
Aspirate the medium and wash the cells with 500 μL of PBS.
Add room-temperature 2% PFA and incubate for 30 min at 37 °C.
Wash the plates three times with PBS.
Add permeabilizing solution (PBS containing 2% bovine albumin, 2% goat serum, 2% horse serum, and 0.2% Triton X-100) for 30 min at room temperature.
Incubate with primary antibody/antibodies listed in Table 1 in PBS at 4 °C overnight.
Wash three times with PBS.
Incubate with secondary antibodies listed in Table 1 for 1 h at room temperature covered with tin foil to block the light and wash three times with PBS.
Incubate with DAPI for 3–5 min covered with tin foil.
Wash three times with PBS.
Take images using a Nikon Eclipse TS 100 inverted microscope.
iMyoblast differentiation
iMyoblasts were maintained on gelatin-coated 10 cm plates in HMP growth medium and passaged at 70%–90% confluence.
Dissociate the iMyoblasts and replate onto gelatin-coated plates. We usually plate 120,000 cells per well in 6-well plates for qPCR gene expression and plate 30,000 cells per well in 24-well plates or 4-well chamber slides for IF staining assay.
Feed the cells with HMP medium every day until more than 90% confluence.
Aspirate HMP medium and wash with PBS.
Add 2 mL of N2 medium or N2 + Prednisolone medium per well for 6-well plate or 0.5 mL per well for 24-well plate or 4-well chamber slide.
Note: N2 + Prednisolone medium increases iMyoblast differentiation.
Incubate the plates in 37 °C/5% CO2 incubator for 2–7 days depending on the experimental plan. Representative images of iMyotube cultures of iMyoblasts after differentiation in N2 medium and in N2 + Prednisolone medium and then immunostained with MF20 myosin antibody and DAPI, are shown in Figure 3.
Figure 3. MF20 staining of iMyotubes. 17U iMyoblasts were differentiated in (A) N2 defined differentiation medium and (B) N2 medium supplemented with Prednisolone, as described. Cultures were maintained in these differentiation media for 7 days and then fixed and immunostained with myosin MF20 antibody. 17U iMyoblasts were isolated from iPSCs of a healthy control human subject. Scale bars = 100 μm.
FACS analysis
Culture iMyoblasts on 10 cm dishes coated with 0.1% gelatin, feeding daily until cells reach 50%–70% confluence.
Aspirate medium and wash cells with PBS.
Add 1.5 mL of TrypLE per 10 cm dish, and incubate the plate at 37 °C for approximately 5 min until all of the cells detach from the plates.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium.
Collect the cells into a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 3–5 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of PBS.
Count the number of viable cells.
Prepare two 1.5 mL tubes, label one with sample ID and isotype control and the other with sample ID and antibody (CD56, CD82).
Transfer 100,000 cells to the tube labeled with sample ID and isotype control and other cells to the tube labeled with sample ID and antibody.
Centrifuge at 120 × g for 5 min, aspirate supernatant without disturbing the cell pellet, and resuspend cells in 100 μL of PBS.
Add 4 μL of APC-mouse IgG1 isotype control to the tube labeled with sample ID and isotype control, and add APC-CD56 antibody to the tube labeled with sample ID and antibody according to 10 μL of antibody per 106 cells. Antibodies used for FACS assays are listed in Table 2.
Incubate on ice for 30–60 min in the dark.
Centrifuge at 120 × g for 5 mins.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 100 μL of PBS including 0.2% FBS.
Filter the samples with 40 μm filter.
Run FACS assay using BD FACS Aria.
Analyze the FACS data using Flowjo software. A representative FACS assay for 17U iMyoblasts is shown in Figure 4.
Figure 4. FACS assay of CD56 and CD82 of proliferating 17U iMyoblasts. iMyoblast cultures include CD56+/CD82+ and CD56-/CD82+ cells. CD82 is expressed in >90% of iMyoblast cultures, and the percentage of CD56+ varies from 15% to 50% for different lines. 17U iMyoblasts were isolated from iPSCs of a healthy control human subject.
Notes
S1 cell cryopreservation and thawing
After 10 days of induction in SKM01 medium, the S1 cells can be frozen and thawed again for subsequent differentiation.
Aspirate the medium and wash with PBS.
Add 1 mL of TrypLE per well and incubate the plate at 37 °C incubator for 5 min until all of the cells detach from the plate.
Neutralize the enzymatic reaction by adding 2 mL of HMP medium, collect the cells in a 15 mL PP centrifuge tube, and then centrifuge the cells at 168 × g for 4 min.
Aspirate supernatant without disturbing the cell pellet and resuspend cells in 1 mL of warm HMP medium.
Count the number of viable cells.
Adjust the S1 cell density to 300,000–400,000/mL with HMP medium.
Add an equal volume of 2× HMP Freeze medium and mix well.
Aliquot to cryovials according to 0.15–0.2 million per cryovial.
Transfer the cryovials to a freezing container and put the freezing container into a -80 °C freezer.
Transfer the cryovials to a liquid nitrogen tank for long term storage.
Gelatin coating
In a biosafety cabinet, add sufficient 0.1% gelatin to coat the first dish or well. Aspirate the solution using a sterile pipette and use it to coat the second dish. Repeat until all the dishes have been coated.
Airdry the plates or dishes in the biological safety cabinet.
Store in original sleeve at room temperature.
Recipes
0.1% gelatin
Reagent Final concentration Amount
Gelatin power 0.1% 0.5g
H2O n/a 500 mL
Total n/a 500 mL
Dissolve 1 g gelatin in 1 L tissue-culture grade water, mix well, and autoclave. Keep the 0.1% gelatin at room temperature.
HMP medium
Filter, sterilize, and store at 4 °C for up to one week.
Reagent Final concentration Amount
Ham's F10 Medium N/A 390 mL
FBS 20% 100 mL
CaCl2 1.2 mM 2.4 mL of 250 mM stock
Antibiotic antimycotic 1% 5 mL
Chick embryo extract 1% 5 mL
Add F10, FBS, CaCl2, and antibiotic antimycotic to Nalgene Rapid-Flow sterile single use vacuum filter units and connect to the vacuum in a tissue culture hood. Add chick embryo extract when 95% of reagents have passed through the filter to avoid blocking the filter. Store HMP at 4 °C for up to one week.
2× HMP freeze medium
Reagent Final concentration Amount of 50 mL
FBS 50% 25 mL
DMSO 20% 20 mL
HMP 30% 15 mL
N2 medium for differentiation (Chal et al., 2016)
Reagent Final concentration Amount
DMEM/F12 N/A 48.5 mL
N2 1% 500 μL
Insulin-transferrin-selenium 1% 500 μL
L-glutamine 1% 500 μL
Prednisolone medium for differentiation, modified from Al Tanoury et al. (2021)
Reagent Final concentration Amount of 50 mL
DMEM/F12 N/A 48.5 mL
N2 1% 500 μL
Insulin-transferrin-selenium 1% 500 μL
L-glutamine 1% 500 μL
CHIR99021 1 μM 50 μL of 1 mM stock
SB431542 10 μM 50 μL of 10 mM stock
Prednisolone 10 μM 50 μL of 10 mM stock
Acknowledgments
This work was funded by grants to CPE from the Muscular Dystrophy Association (480265) and NICHD Wellstone Muscular Dystrophy Cooperative Research Center P50 (HD060848). This protocol was derived from Guo et al. (2022).
Competing interests
Dongsheng Guo, Katelyn Daman, Jing Yan, and Charles P. Emerson Jr. are co-inventors on a patent application entitled "Methods And Compositions For Treatment Of Muscle Disease With iPSC-Induced Human Skeletal Muscle Stem Cells.” Dongsheng Guo and Charles P. Emerson Jr. are co-inventors of a patent "Microhomology Mediated Repair Of Microduplication Gene Mutations" (17/051,632).
Ethics
Human subjects: informed consent was obtained from patients who donated tissue for production of cell lines used in these studies. IRB protocols approved by UMass Medical School IRB: H00006581-10 and H00006581-11; IRB protocol approved by Kennedy Krieger Institute IRB: B0410080117; IRB protocol approved by the University of Iowa IRB: 200510769.
References
Abujarour, R., Bennett, M., Valamehr, B., Lee, T. T., Robinson, M., Robbins, D., Le, T., Lai, K. and Flynn, P. (2014). Myogenic differentiation of muscular dystrophy-specific induced pluripotent stem cells for use in drug discovery. Stem Cells Transl Med 3(2): 149-160.
Al Tanoury, Z., Rao, J., Tassy, O., Gobert, B., Gapon, S., Garnier, J. M., Wagner, E., Hick, A., Hall, A., Gussoni, E., et al. (2020). Differentiation of the human PAX7-positive myogenic precursors/satellite cell lineage in vitro. Development 147(12): dev187344.
Al Tanoury, Z., Zimmerman, J. F., Rao, J., Sieiro, D., McNamara, H. M., Cherrier, T., Rodriguez-delaRosa, A., Hick-Colin, A., Bousson, F., Fugier-Schmucker, C., et al. (2021). Prednisolone rescues Duchenne muscular dystrophy phenotypes in human pluripotent stem cell-derived skeletal muscle in vitro. Proc Natl Acad Sci U S A 118(28): e2022960118.
Caron, L., Kher, D., Lee, K. L., McKernan, R., Dumevska, B., Hidalgo, A., Li, J., Yang, H., Main, H., Ferri, G., et al. (2016). A Human Pluripotent Stem Cell Model of Facioscapulohumeral Muscular Dystrophy-Affected Skeletal Muscles. Stem Cells Transl Med 5(9): 1145-1161.
Chal, J., Al Tanoury, Z., Hestin, M., Gobert, B., Aivio, S., Hick, A., Cherrier, T., Nesmith, A. P., Parker, K. K. and Pourquie, O. (2016). Generation of human muscle fibers and satellite-like cells from human pluripotent stem cells in vitro. Nat Protoc 11(10): 1833-1850.
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4,501 | https://bio-protocol.org/en/bpdetail?id=4501&type=1 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
The Canu Genome Assembly Pipeline Using Nanopore Long Reads
GL Guifang Lin
SL Sanzhen Liu
Published: Sep 5, 2022
DOI: 10.21769/BioProtoc.4501 Views: 1188
Reviewed by: Thibaud T. RenaultHassan RasouliHainan Zhao
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Abstract
Long sequencing reads have greatly improved assemblies of genomes with all sizes. The current Oxford Nanopore technology can regularly produce reads longer than 20 kb with less than 10% sequencing errors. To use long reads that contain relatively high errors, algorithms have been developed for genome assembly and sequence polishing. This pipeline shows the process of the genome assembly from raw data to polished assembled contigs, including basecalling from Nanopore raw reads using the Guppy basecaller, genome assembly with the Canu genome assembler, and sequence polishing using both Nanopore long reads and Illumina short reads, with Nanopolish and Pilon, respectively. Small fungal datasets were used to illustrate the pipeline. The pipeline has been demonstrated to produce high-quality genome assemblies of fungal and plant genomes.
Graphical abstract:
Flowchart from raw data to genome assembly.
The pipeline includes three major steps: basecalling, read assembly, and polishing of assembled contigs. Software Guppy, Canu, Nanopolish, and Pilon are used with other bioinformatics tools in this pipeline.
Keywords: Nanopore Long reads Basecalling Genome assembly Polishing
Background
The genome assembly has been dramatically improved with newly developed long-read sequencing technologies. Oxford Nanopore sequencing has been used for genome assemblies of a wide range of species, including the large and complex maize genome (Lin et al., 2021). Using Nanopore long-read sequencing technology, single-stranded DNA or RNA molecules pass through a nanopore protein affecting the ionic current during the movement (Jain et al., 2016). The electrical signals captured by the sensors are converted to sequencing reads with a basecaller (Jain et al., 2016; Wick et al., 2019). Output sequencing reads are typically within a range of lengths, largely depending on the size of input molecular fragments. Nanopore long reads have a relatively high rate of errors, dominated by small insertions or deletions. Recently, the error rate has been markedly reduced with optimized library chemistry and improved basecalling algorithms (Wang et al., 2021). Multiple genome assemblers have been developed to take advantage of long reads, considering high error rates (Li, 2016; Koren et al., 2017; Kolmogorov et al., 2019). Canu has been demonstrated to be a reliable assembler that corrects/trims reads and assembles cleaner reads. Here, we employed Canu for genome assembly using Oxford Nanopore long reads, followed by contig polishing with Nanopolish and Pilon (Walker et al., 2014; Loman et al., 2015). We demonstrate the procedure using read data from a chromosomal segment of a fungal genome (Figure 1) (Peng et al., 2019; He et al., 2020). The codes and parameters used here have been shown to be applicable for assemblies of plant genomes (Lin et al., 2021).
Software and Data sets
Software
Guppy Basecaller [(Oxford Nanopore Technologies, 2022); version 6.0.6; https://community.nanoporetech.com]
Canu [(Koren et al., 2017); version 2.2; https://github.com/marbl/canu]
Nanopolish [(Loman et al., 2015); version 0.13.3; https://github.com/jts/nanopolish]
Pilon [(Walker et al., 2014); version 1.24; https://github.com/broadinstitute/pilon]
Minimap2 [(Li, 2018b); version 2.17; https://github.com/lh3/minimap2]
BWA [(Li, 2013); version 0.7.17; https://github.com/lh3/bwa]
SAMtools [(Li et al., 2009); version 1.12; https://github.com/samtools/samtools]
MUMmer4 [(Marçais et al., 2018); version 4.0.0; https://mummer4.github.io/]
Seqtk [(Li, 2018a); version 1.3; https://github.com/lh3/seqtk]
Installation
Download the bio-protocol repository from GitHub.
git clone https://github.com/Bio-protocol/Nanopore_genome_assembly.git
cd Nanopore_genome_assembly
Download Guppy from the Oxford Nanopore Community webpage. Due to the copyright, the website for downloading the software is not provided. Users can register at nanoporetech.com to access the latest version of Guppy software. Here, we show the example for the installation of Guppy version 6.0.6.
# Example for downloading Guppy (version 6.0.6)
pushd lib
curl -L -o ont-guppy-cpu_6.0.6_linux64.tar.gz <Guppy downloading site>
tar -xvzf ont-guppy-cpu_6.0.6_linux64.tar.gz
rm ont-guppy-cpu_6.0.6_linux64.tar.gz
popd
Download Pilon.
For using Pilon Java script, no installation is required.
pushd lib
pilon_site=https://github.com/broadinstitute/pilon/releases/download/v1.24/pilon-1.24.jar
curl -L -o pilon-1.24.jar $pilon_site
popd
Most tools can be installed through conda (https://docs.conda.io). Create a conda environment and install packages.
conda create -n npasm
conda activate npasm
conda install -c bioconda -c conda-forge -c defaults canu=2.2 nanopolish=0.13.2
conda install -c bioconda samtools seqtk minimap2 bwa mummer4
conda deactivate
Input data
Fast5 is a binary HDF5 file format for storing the raw electrical signal level data of Oxford Nanopore sequencing reads (Wang et al., 2021). To produce a small dataset, a subset of fast5 data was extracted from the Nanopore Whole Genome Sequencing (WGS) data of the wheat blast fungal isolate B71, using the fast5_subset tool (nanoporetech). In detail, B71 Nanopore fastq reads (SRR12459118) called from fast5 were first aligned to the reference genome (B71Ref1.5) using minimap2. We then extracted fast5 data of half of reads mapped to the region from 1,000,000 to 1,050,000 on chromosome 5 (chr5:1000000-1050000) of B71Ref1.5 using fast5_subset, which were saved in the following three fast5 files. These fast5 files are used for Guppy basecalling and Nanopolish polishing.
input/ont_fast5/fast5/B71example0.fast5
input/ont_fast5/fast5/B71example1.fast5
input/ont_fast5/fast5/B71example2.fast5
Illumina read data mapped to the same chromosome 5 region were extracted from the trimmed paired-end 250 bp Illumina reads of B71 (SRR6232156) using seqtk. Briefly, Illumina WGS reads were mapped to B71Ref1.5 using BWA-MEM. Reads mapped to the region chr5:1000000–1050000 of B71Ref1.5 were extracted. The extracted paired-end reads are used for Pilon polishing.
input/illumina_fastq/B71_example.illumina.R1.pair.fq.gz
input/illumina_fastq/B71_example.illumina.R2.pair.fq.gz
The ref.fasta contains the sequence of the region chr5:1000000–1050000 of B71Ref1.5.
input/ref.fasta
Procedure
Case study
The workflow was constructed based on the Linux system and the Slurm job scheduling system. The following script runs all steps together, from raw reads to the polished assembly, without using the Slurm scheduler. The whole process of this example takes several hours to finish.
cd workflow
sh local.asm.sh &
cd ..
The following scripts provide the step-by-step guide for the whole process. Note that we assume that the working directory is “Nanopore_genome_assembly” cloned from the GitHub repository.
Guppy basecalling. The fast5 data was converted to fastq data using the Guppy software released by the Oxford Nanopore company.
# define variables
infolder=input/ont_fast5/fast5 # input folder
flowcell=FLO-MIN106 # Flow cell
kit=SQK-LSK109 # Ligation kit
trim=dna # trimming strategy
nbc=4 # number of basecallers
cpb=4 # cpus per basecaller
outdir=cache/1o-basecall # create a output folder
mkdir $outdir # create a output folder
# basecall use CPU
lib/ont-guppy-cpu/bin/guppy_basecaller -i $infolder \
--save_path $outdir \
--trim_strategy $trim \
--flowcell $flowcell \
--kit $kit \
--cpu_threads_per_caller $cpb \
--num_callers $nbc
The parameters --flowcell and --kit are required to select the config file or the basecalling model. For the combination of flowcell FLO-MIN106 and kit SQK-LSK109, dna_r9.4.1_450bps_hac.cfg is the default config model for a high accuracy model. Two other models include dna_r9.4.1_450bps_fast.cfg for a fast model and dna_r9.4.1_450bps_sup.cfg for a super accurate model. “--config” can be used to select one of the other two models. More detailed information about the basecaller can be referred to the Guppy manual (Oxford Nanopore Community webpage).
# define variablesin
folder=input/ont_fast5/fast5 # input folder
flowcell=FLO-MIN106 # Flow cell
kit=SQK-LSK109 # Ligation kit
configfile=dna_r9.4.1_450bps_fast.cfg # basecall model config file
trim=dna # trimming strategy
nbc=4 # number of basecallers
cpb=4 # cpus per basecaller
outdir=cache/1o-basecall # create a output folder
mkdir $outdir # create a output folder
# basecall use CPU
lib/ont-guppy-cpu/bin/guppy_basecaller -I $infolder \
--save_path $outdir \
--trim_strategy $trim \
--config $configfile \
--cpu_threads_per_caller $cpb \
--num_callers $nbc
The Guppy basecalling is a computationally intensive task. For a large dataset, the GPU version of Guppy is highly recommended. Alternatively, a Slurm-based CPU Guppy basecalling script using multiple threads, as shown below, can be implemented.
cd workflow
sh 1-basecall_slurm.sh
cd ..
Perform the genome assembly using Canu. For this example, the genome size is expected to be 50 kb (genomeSize=50k). Nanopore reads longer than 5 kb (minReadLength=5000) are loaded into the assembler. For alignments among reads, an overlapping length longer than 1 kb is required (minOverlapLength=1000). Longest reads covering 60x coverage are corrected and used for the assembly (corOutCoverage=60).
source activate base
conda activate npasm
# define variables
infastq=cache/1o-basecall/pass/*fastq # the input data
out=demo # the prefix of output genome assembly
mergefastq=cache/1o-basecall/${out}.fastq # the merged input data
# Merge the multiple fastq files
cat $infastq > $mergefastq
# run canu
canu -d cache/2o-${out}.asmv0.1 -p ${out}.v0.1 \
genomeSize=50k \
minReadLength=5000 \
minOverlapLength=1000 \
-nanopore $mergefastq \
corOutCoverage=60 \
&> cache/2o-$out.asmv0.1.log
conda deactivate
To submit the job on the Slurm system, run the following script.
cd workflow
sh 2-asm_slurm.sh
cd ..
Polish the draft assembled contigs using Nanopolish. First, Nanopore reads are indexed using “nanopolish index”. In this step, reads in the fastq format are linked to the fast5 raw data to allow Nanopolish to access the signal data. Second, fastq reads are aligned to the Canu draft assembly using “minimap2”. Third, variants are generated using “nanopolish variants”. Finally, a polished genome is generated from variants using “nanopolish vcf2fasta”.
source activate base
conda activate npasm
# define variables
inprefix=demo
infastq=cache/1o-basecall/$inprefix.fastq # the merged fastq with nanopore reads.
outaln=2o-example
ncpu=4
out=$inprefix
outdir=cache/3o-nanopolish
mkdir $outdir
mypath=`pwd`
seqsumList=$mypath/$outdir/1o-seqsum_list
log=$mypath/$outdir/1o-run.log
reads=$mypath/$outdir/ont.fasta
f5Dir=$mypath/input/ont_fast5/fast5
fqsum_dir=$mypath/cache/1o-basecall/sequencing_summary.txt
npDir=$mypath/lib/nanopolish
ref=$mypath/cache/2o-$out.asmv0.1/$out.v0.1.contigs.fasta
# reads index
seqtk seq -L 5000 $infastq > $reads
ls $fqsum_dir -1 > $seqsumList
$npDir/nanopolish index -d $f5Dir -f $seqsumList $reads &>$log
# alignment
minimap2 -ax map-ont --secondary=no $ref $reads 1>$outdir/${outaln}.sam 2>$outdir/$outaln.log
samtools view -b $outdir/$outaln.sam | samtools sort -o $outdir/$outaln.bam
samtools index $outdir/$outaln.bam
rm $outdir/${outaln}.sam
# nanopolish
prefix=np
bam=$mypath/$outdir/$outaln.bam
log=$mypath/$outdir/np.log
date > $log
$npDir/nanopolish variants --consensus -o $outdir/polished.vcf \
-r $reads \
-b $bam \
-g $ref \
>> $log
$npDir/nanopolish vcf2fasta --skip-checks -g $ref $outdir/polished.vcf 1> $outdir/${out}.v0.1.${prefix}.fasta 2>>$log
date >> $log
Nanopolish is also a computationally intensive job. A large genome assembly can be split to run the nanopolish variants in parallel. Here is the code developed to run through the Slurm scheduler:
cd workflow
sh 31-nanopolish_merge_slurm.sh
cd ..
When the Nanopolish step is finished, multiple polished contigs can be merged using the following code:
cd workflow
sh 32-nanopolish_slurm.sh
cd ..
Further polish the assembly using Pilon with Illumina reads. First, Illumina short reads are aligned to the polished genome assembly from the Nanopolish step using “BWA-MEM”. Then, Pilon is used for further polishing.
# define variables
outdir=cache/4o-pilon
mkdir $outdir
out=demo
mypath=`pwd`
pilonJar=$mypath/lib/pilon-1.24.jar
ref=$mypath/cache/3o-nanopolish/demo.v0.1.np.fasta
refname=$(echo $ref |sed 's/.*\///g')
newasm=$mypath/$outdir/demo.v0.1.np.pilon.fasta
log=$mypath/$outdir/1o-pilon.log
pe1=$mypath/input/illumina_fastq/B71_example.illumina.R1.pair.fq.gz
pe2=$mypath/input/illumina_fastq/B71_example.illumina.R2.pair.fq.gz
tmpdir=1otmp
mkdir $outdir/$tmpdir
# alignment
pushd $outdir/$tmpdir
ln -s $ref .
bwa index $refname
out=1o-read2asm
bwa mem $refname $pe1 $pe2 > ${out}.sam
cd ..
# pilon
java -Xmx96g -jar $pilonJar \
--genome $tmpdir/$refname \
--frags $tmpdir/${out}.sort.bam \
--output 1o-pilon \
--outdir . \
--minmq 40 \
--minqual 15 \
--changes --vcf &>1o-pilon.log
# cleanup
rm $tmpdir -rf
# rename the sequence
sed 's/_pilon//g' 1o-pilon.fasta >$newasm
rm 1o-pilon.fasta
popd
# copy the final assembly to the output folder
cp $newasm output
Compare the final genome assembly to the reference sequence.
# define variables
outdir=output/final_genome_qc
mkdir $outdir
outprefix=polished2ref
dnadiff -p $outdir/$outprefix input/ref.fasta output/demo.v0.1.np.pilon.fasta
show-coords $outdir/${outprefix}.delta > $outdir/${outprefix}.aligned.txt
show-snps $outdir/${outprefix}.delta > $outdir/${outprefix}.variants.txt
Result interpretation
Check the comparison report.
tail -n +4 output/final_genome_qc/polished2ref.report |head
Output 1:
[REF] [QRY]
[Sequences]
TotalSeqs 1 1
AlignedSeqs 1(100.00%) 1(100.00%)
UnalignedSeqs 0(0.00%) 0(0.00%)
[Bases]
TotalBases 50000 124197
AlignedBases 50000(100.00%) 50006(40.26%)
UnalignedBases 0(0.00%) 74191(59.74%)
In the report file, the number of query (QRY) sequences is 1, and total bases of query sequences are 124,197 bp. The result shows that the final genome assembly has one contig with a size of 124,197 bp. The Canu assembly report (cache/2o-demo.asmv0.1/demo.v0.1.report) can be used to check for the draft assembly statistics.
Check the aligned regions.
tail -n +4 output/final_genome_qc/polished2ref.aligned.txt
Output 2:
[S1] [E1] | [S2] [E2] | [LEN 1] [LEN 2] | [% IDY] | [TAGS]
================================================================================
1 50000 | 41062 91067 | 50000 50006 | 99.98 | ref tig00000001
The result shows that the 50 kb reference (ref) sequence can be aligned to tig00000001 from 41,062 bp to 91,067 bp. The identity between the aligned reference and the assembly sequence is 99.98%.
Check the variants between the reference and the new assembly.
tail -n +4 output/final_genome_qc/polished2ref.variants.txt
Output 3:
[P1] [SUB] [P2] | [BUFF] [DIST] | [R] [Q] | [FRM] [TAGS]
================================================================================
531 . T 41593 | 0 531 | 0 0 | 1 1 ref tig00000001
531 . T 41594 | 0 531 | 0 0 | 1 1 ref tig00000001
531 . T 41595 | 0 531 | 0 0 | 1 1 ref tig00000001
23126 . A 64191 | 0 23126 | 0 0 | 1 1 ref tig00000001
23126 . A 64192 | 0 23126 | 0 0 | 1 1 ref tig00000001
23126 . A 64193 | 0 23126 | 0 0 | 1 1 ref tig00000001
25942 T . 67008 | 1 24059 | 0 0 | 1 1 ref tig00000001
25943 T . 67008 | 1 24058 | 0 0 | 1 1 ref tig00000001
46397 . T 87463 | 0 3604 | 0 0 | 1 1 ref tig00000001
46397 . T 87464 | 0 3604 | 0 0 | 1 1 ref tig00000001
The 10 variants in the two sequences aligned region can be interpreted as 4 INDELs, which results in the identity of 99.98%. The INDEL is a common error type for long reads sequencing.
Discussion
The total length of the final genome assembly is 124,197 bp, which contains the 50 kb reference sequence in the middle of the contigs. This is because sampled reads cover flanking regions of the 50 kb reference sequence, which should not be a problem when using real data.
Input fastq data can be examined using software NanoPlot (De Coster et al., 2018; He et al., 2020) to summarize the overall error rate and the length distribution of reads. Such information could help determine parameters to run Canu. KAD can be used to evaluate the error rate of the final assembly (He et al., 2020). To evaluate the completeness of the genome, the BUSCO tool (Simão et al., 2015) can be used. The contiguity can be indicated by the N50 of the genome assembly, calculated by GenomeQC (Manchanda et al. 2020) or other tools. To resolve nodes to improve the chromosome contiguity, the genome assembly graph produced by Canu can be manually examined using Bandage (Wick et al., 2015). For fungal genomes, the Canu assembly using Nanopore data is likely to be a telomere-to-telomere chromosome assembly. This is unlikely to occur for all chromosomes of plant genomes. On the contrary, hundreds or thousands contigs might be in the final assembly contigs. Due to large numbers of contigs, carefully make sure all contigs are passed to each next step of analyses. If needed, additional data (e.g., HiC data, BioNano optical mapping data, or reference genomes) can be used for scaffolding. For assembly of a large plant genome, the same procedure as documented here can be followed. However, a few parameters need to be modified, including genome size. More computing resources are typically needed for plant genome assembly. For example, -gridOptions="--time=4-00:00:00" was requested for the Canu assembly of maize inbred line A188 (https://github.com/liu3zhenlab/A188Ref1). For large numbers of raw reads for plant genome assembly, GPU-based Guppy basecalling may be adapted. The newer Guppy, which updates basecalling models, is expected to result in higher-accuracy sequences of reads. Raw fast5 data could be recalled prior to each assembly procedure using the latest Guppy with an improved model.
The Oxford Nanopore long read technology is improving rapidly. The latest Oxford Nanopore flowcell and chemistry are expected to produce Q20+ raw reads, equivalent to >99% base accuracy (https://nanoporetech.com/q20plus-chemistry). Although producing Q20+ data has not become a regular process, sooner or later the technology will achieve a high accuracy. Higher base accuracy will dramatically shorten the computing time of the assembly, allowing the exploration of assemblies with different parameter combinations. Based on our experience, the parameters “minOverlapLength” and "corOutCoverage” in Canu could be adjusted to explore their impacts on the continuity of the assembly. With the improved base quality of raw reads, “correctedErrorRate” could be modified as well.
Acknowledgments
G. Lin and S. Liu were supported by the USDA NIFA (award no. 2018-67013-28511 and 2021-67013-35724) and by the NSF (award no. 1741090 and 2011500).
Competing interests
There are no conflicts of interest or competing interests.
References
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He, C., Lin, G., Wei, H., Tang, H., White, F. F., Valent, B. and Liu, S. (2020). Factorial estimating assembly base errors using k-mer abundance difference (KAD) between short reads and genome assembled sequences. NAR Genom Bioinform 2(3): lqaa075.
Jain, M., Olsen, H. E., Paten, B. and Akeson, M. (2016). The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol 17(1): 239.
Kolmogorov, M., Yuan, J., Lin, Y. and Pevzner, P. A. (2019). Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37(5): 540-546.
Koren, S., Walenz, B. P., Berlin, K., Miller, J. R., Bergman, N. H. and Phillippy, A. M. (2017). Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 27(5): 722-736.
Li, H. (2013). Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. In: arXiv [q-bio.GN]. arXiv. http://arxiv.org/abs/1303.3997.
Li, H. (2016). Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32(14): 2103-2110.
Li, H. (2018a). Toolkit for processing sequences in FASTA/Q formats. GitHub. https://github.com/lh3/seqtk.
Li, H. (2018b). Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics34(18): 3094-3100.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16): 2078-2079.
Lin, G., He, C., Zheng, J., Koo, D. H., Le, H., Zheng, H., Tamang, T. M., Lin, J., Liu, Y., Zhao, M., et al. (2021). Chromosome-level genome assembly of a regenerable maize inbred line A188. Genome Biol 22(1): 175.
Loman, N. J., Quick, J. and Simpson, J. T. (2015). A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 12(8): 733-735.
Manchanda, N., Portwood, J. L., 2nd, Woodhouse, M. R., Seetharam, A. S., Lawrence-Dill, C. J., Andorf, C. M. and Hufford, M. B. (2020). GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations. BMC Genomics 21(1): 193.
Marçais, G., Delcher, A. L., Phillippy, A. M., Coston, R., Salzberg, S. L. and Zimin, A. (2018). MUMmer4: A fast and versatile genome alignment system. PLoS Comput Biol 14(1): e1005944.
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Peng, Z., Oliveira-Garcia, E., Lin, G., Hu, Y., Dalby, M., Migeon, P., Tang, H., Farman, M., Cook, D., White, F. F., et al. (2019). Effector gene reshuffling involves dispensable mini-chromosomes in the wheat blast fungus. PLoS Genet 15(9): e1008272.
Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. and Zdobnov, E. M. (2015). BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19): 3210-3212.
Walker, B. J., Abeel, T., Shea, T., Priest, M., Abouelliel, A., Sakthikumar, S., Cuomo, C. A., Zeng, Q., Wortman, J., Young, S. K., et al. (2014). Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9(11): e112963.
Wang, Y., Zhao, Y., Bollas, A., Wang, Y. and Au, K. F. (2021). Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol 39(11): 1348-1365.
Wick, R. R., Judd, L. M. and Holt, K. E. (2019). Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome Biol 20(1): 129.
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Supplementary information
Data and code availability: All data, analysis, and codes have been deposited to GitHub: https://github.com/Bio-protocol/Nanopore_genome_assembly.git
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4,502 | https://bio-protocol.org/en/bpdetail?id=4502&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
A New Tool for the Flexible Genetic Manipulation of Geobacillus kaustophilus
RA Ryotaro Amatsu *
KM Kotaro Mori *
SI Shu Ishikawa
WM Wilfried J. J. Meijer
KY Ken-ichi Yoshida
(*contributed equally to this work)
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4502 Views: 871
Reviewed by: Alessandro DidonnaAksiniya Asenova Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Microbial Cell Factories Mar 2022
Abstract
Geobacillus kaustophilus, a thermophilic Gram-positive bacterium, is an attractive host for the development of high-temperature bioprocesses. However, its reluctance against genetic manipulation by standard methodologies hampers its exploitation. Here, we describe a simple methodology in which an artificial DNA segment on the chromosome of Bacillus subtilis can be transferred via pLS20-mediated conjugation resulting in subsequent integration in the genome of G. kaustophilus. Therefore, we have developed a transformation strategy to design an artificial DNA segment on the chromosome of B. subtilis and introduce it into G. kaustophilus. The artificial DNA segment can be freely designed by taking advantage of the plasticity of the B. subtilis genome and combined with the simplicity of pLS20 conjugation transfer. This transformation strategy would adapt to various Gram-positive bacteria other than G. kaustophilus.
Graphical abstract:
Keywords: Bacillus subtilis Conjugation Geobacillus kaustophilus Gram-positive Homologous recombination Transformation
Background
Geobacillus kaustophilus HTA426 is a thermophilic Gram-positive bacterium isolated from sediments of the Mariana Trench (Nazina et al., 2001; Takami et al., 2004). It grows at temperatures ranging from 48 to 74 °C (optimal temperature of 60 °C) and is a promising chassis for high-temperature bioprocessing with the advantages of preventing contamination by mesophilic bacteria and lowering the cost of controlling fermentation heat. However, this bacterium is difficult to transform by natural competence or electroporation, and an approach based on a conjugation system for Gram-negative bacteria has been developed (Suzuki and Yoshida, 2012). This method has the disadvantage of not being able to select transformants that acquired mutations with adverse effects on growth. Therefore, better techniques for manipulating the genome of G. kaustophilus are needed.
Conjugation is one of the three main mechanisms for horizontal gene transfer in bacteria. Conjugative elements, which often are located on plasmids, encode all the proteins required for their transfer from a donor cell to a recipient cell. Conjugative elements encode adhesins or organelles facilitating interaction with recipient cells. In almost all conjugative systems only a single strand of the DNA (ssDNA) is transferred. Generation of the ssDNA is done by a relaxase, often assisted by one or two auxiliary proteins, that introduces a site- and strand-specific nick in a region of the plasmid named origin of transfer (oriT). After nicking, the relaxase remains covalently attached to the 5′ end of the DNA, and the generated 3′ end is used as a primer for DNA synthesis resulting in a rolling-circle mode of replication, thereby generating the ssDNA molecule that is destined for transfer into the recipient cell. Conjugative elements encode a sophisticated transferosome (type IV secretion system) connecting the donor and recipient cells. The relaxosome complex, which is composed of a number of proteins including the relaxase, is recruited to the cytosolic side of the transferosome in the donor cell, after which it guides the transfer of the ssDNA into the recipient cell (Christie et al., 2014; Christie, 2016; Waksman, 2019).
pLS20 is a 65 kb conjugative plasmid isolated from Bacillus subtilis var. natto (Tanaka and Koshikawa, 1977); it can transfer itself among various Bacillus species (Koehler and Thorne, 1987). Contrary to most conjugative systems that require prolonged interactions between donor and recipient cells on solid medium, efficient conjugation of pLS20 is achieved by mixing donor and recipient cells in liquid medium (Tanaka and Koshikawa, 1977; Singh et al., 2013; Miyano et al., 2018). Genes involved in pLS20 conjugation (genes 28–74) form a large operon controlled by a strong promoter named Pc. Regulation of pLS20 conjugation genes has been studied in detail (for a review, see Meijer et al., 2021). Gene 27 encodes RcopLS20, which is the master regulator of the conjugation operon. In its default state, conjugation is suppressed due to binding of RcopLS20 to its two operator sites within the Pc region, strictly repressing the Pc promoter. Gene 25 encodes an antirepressor named RappLS20, which activates conjugation by relieving repression from RcopLS20 and forming a Rap/Rco complex. Gene 26 encodes a quorum sensing peptide, Phr*pLS20, that regulates the activity of RappLS20. phrpLS20 synthesizes a small pre-proprotein. After being secreted, PhrpLS20 is proteolytically cleaved, generating the mature Phr*pLS20 peptide corresponding to its 5 C-terminal residues. When taken up by donor cells, Phr*pLS20 inactivates RappLS20 by changing its conformation upon binding to it, returning the system to its default repressed state (Singh et al., 2013). Ectopic overproduction of RappLS20 increased the efficiency of conjugation by weakening the effect of Phr*pLS20 (Singh et al., 2013).
A derivative of pLS20 lacking oriTpLS20, pLS20catΔoriT, is defective in conjugation (Miyano et al., 2018). However, we have recently shown that pLS20catΔoriT can mediate the transfer of large regions of the bacterial chromosome between B. subtilis cells when a copy of oriTpLS20 is present on the chromosome in the donor cell (Miyano et al., 2018). Inspired by this, we have developed a strategy to transform G. kaustophilus that allows for flexible manipulation of its chromosome (Mori et al., 2022). Here, we present the protocol to transform G. kaustophilus by pLS20-mediated conjugative transfer of a chromosomal DNA of B. subtilis designed to function in G. kaustophilus.
Materials and Reagents
Note: All reagents can be stored at room temperature unless otherwise specified.
Construction of the donor strain
B. subtilis 168 (Mori et al., 2022)
B. subtilis YNB211 (Mori et al., 2022)
G. kaustophilus MK244 (Mori et al., 2022)
pUCG18T (Mori et al., 2022)
LB medium (2% agar) (BD Difco, catalog number: 240230)
10% SDS (Nacalai Tesque, catalog number: 30562-04)
Lysozyme (Wako, catalog number: 129-06723)
Phenol/Chloroform/Isoamyl alcohol (25:24:1) (Wako, catalog number: 311-90151), store at 4 °C
70% Ethanol
99.5% Ethanol
KOD -Plus- Neo polymerase (Toyobo, catalog number: KOD-401), store at -20 °C
Agarose for electrophoresis gel (ME, Nacalai Tesque, catalog number: 01133-24)
In silico Molecular Cloning software for designing PCR primers (In Silico Biology, Inc., catalog number: IMCGF01)
Primer pairs used for the PCR reaction of five fragments
Fragment A1:
aprE-U-f1 ccggtacttgccaccacatcataac
aprE-U-r cagtaacctcatcaagccaagctacctctcgctatttccgtagagactcg
Fragment A2:
aprE-D-f2 gacagaggaattagatacattcgcgttaatcaacgtacaagcagctgcac
aprE-D-r ggccgagcagtattcgaatgtcaag
Fragment B1:
degA-U-f gtagcttggcttgatgaggttactg
degA-U-r2 catcggtcataaaatccgtatccttggttactttcatcgctcatcattc
Fragment B2:
degA-D-f2 ctgcaaggcgattaagttgggtaacagtgaaatcgtaaggatgtgagcag
degA-D-r cgcgaatgtatctaattcctctgtc
Fragment C1:
kan-f aaggatacggattttatgaccgatg
kan-r2 gttacccaacttaatcgccttgcag
Primers used for the recombinant PCR reactions that ligate the five fragments.
aprE-U-f3-nested caccgagctcatagcttgtcgcgatcacctcatcc
aprE-D-r2-nested tgctttcgctgattacaacattggtgacgctgcct
DNA purification kit (Wizard® SV Gel and PCR Clean-Up System, Promega, catalog number: A9281)
7.5 mg/mL Kanamycin sulfate stock solution in water (Wako, catalog number: 113-00343)
Solution A (see Recipes)
Solution B (see Recipes)
100× Trace element (see Recipes)
TKE buffer (see Recipes)
50× TAE buffer (see Recipes)
C-1 and C-2 medium for transformation (see Recipes)
Conjugation and selection of transconjugant (transformant)
7.5 mg/mL Kanamycin sulfate stock solution in water (Wako, catalog number: 113-00343)
10 mg/mL Chloramphenicol stock solution in 70% ethanol (Wako, catalog number: 030-19452)
100 mM IPTG stock solution in water (Nacalai Tesque, catalog number: 367-93-1)
LB medium (see Recipes)
LBMSM medium (see Recipes)
Southern blotting analysis
Primers used for amplification of a template DNA for synthesizing RNA probe
Km-probe-f taatacgactcactatagggtatggctctcttggtcgtc
Km-probe-r tctgattccacctgagatgc
Agarose for electrophoresis gel (SP, Nacalai Tesque, catalog number: 01163-76)
DNA Molecular Weight Marker II, DIG-labeled (Roche, catalog number: 11218590910)
DNA purification kit (Wizard® SV Gel and PCR Clean-Up System, Promega, catalog number: A9281)
T7 RNA polymerase (Roche, catalog number: 10881767001), store at -20 °C
DIG RNA Labeling Mix, 10× conc. (Roche, catalog number: 11277073910), store at -20 °C
Restriction enzymes
Cla I (Takara, catalog number: 1034A), store at -20 °C
Sac II (Takara, catalog number: 1079A), store at -20 °C
DIG Easy Hyb (Roche, catalog number: 11603558001), store at 4 °C
Amersham Hybond-N+ (GE Healthcare, catalog number: RPN82B)
Hybridization bag (Hybridization Bags Hybri-Bag Hard, COSMO BIO, catalog number: S-1001)
Blocking Reagent (Roche, catalog number: 11096176001)
Anti-Digoxigenin-AP, Fab fragment (Roche, catalog number: 11093274910), store at 4 °C
CSPD, ready-to-use (Roche, number: 11755633001), store at 4 °C
20× SSC buffer (see Recipes)
Maleic acid buffer (see Recipes)
Denaturing solution (see Recipes)
Neutralizing solution (see Recipes)
High-stringency wash solution (see Recipes)
Low-stringency wash solution (see Recipes)
Detection buffer (see Recipes)
Equipment
Construction of the donor strain
Thermal cycler (for example, Takara Bio, Thermal Cycler Dice Touch TP350, or equivalent)
Centrifuge (for example, TOMY, MX-307, or equivalent)
Spectrophotometer (for example, GE Healthcare, NanoVue Plus, or equivalent)
Agarose gel electrophoresis apparatus (for example, Takara Bio, Mupid®-2plus, or equivalent)
Incubator (for example, PHCbi, MIR-H163, or equivalent)
Conjugation and selection of transconjugant (transformant)
Two incubator shakers, one set at 37 °C and the other at 60 °C (TAITEC, Bioshaker BR-43FM-MR, or equivalent)
Centrifuge (TOMY, MX-307, or equivalent)
Two incubators, one is set at 37 °C and the other 60 °C (PHCbi, MIR-H163, or equivalents)
Spectrophotometer (SHIMADZU, UV-1800, or equivalent)
300 mL baffled Erlenmeyer flask
Southern blotting (or: Southern blot analysis)
Thermal cycler (Takara Bio, Thermal Cycler Dice Touch TP350, or equivalent)
Spectrophotometer (GE Healthcare, NanoVue Plus, or equivalent)
Agarose gel electrophoresis apparatus (Bio-Rad, Sub-Cell GT Cell, or equivalent)
Transfer apparatus (Bio Craft, Vacuum Transfer BS-31, or equivalent)
UV crosslinker (UVP, CL-1000, or equivalent)
Shaker (Bio Craft, Labo Shaker BC-730, or equivalent)
Chemiluminescence imager (Bio-Rad, ChemiDoc XRS+, or equivalent)
Procedure
Construction of the donor strain
Isolation of DNA from bacterial strains
Grow bacterial cells in 5 mL of LB medium at 37 °C overnight with shaking.
Collect bacterial cells of 1.5 mL of culture in a test tube by centrifugation at 8,152 × g for 3 min at room temperature.
Suspend the cells in 500 µL of TKE buffer containing 1 mg of freshly added lysozyme.
Incubate the tube for 30 min at 37 °C.
Add 50 µL of 10% SDS and mix thoroughly.
Add 500 µL of phenol/chloroform/isoamyl alcohol (25:24:1) and mix vigorously.
Centrifuge the tube at 20,380 × g for 10 min at 4 °C, and then transfer 200 µL of supernatant to a new tube; avoid transferring the white interface.
Add 500 µL of 99.5% ethanol to the tube, mix and stand on ice for 10 min, and centrifuge at 20,380 × g for 5 min. Discard the supernatant.
Wash the DNA pellet carefully with 0.7 mL of 70% ethanol and place the sample 10 min at 37 °C to evaporate remains of ethanol.
Add 100 µL of distilled water and place 10 min at 37 °C to dissolve the DNA gently.
Measure the concentration of DNA using a spectrophotometer such as NanoVue Plus.
Setting up recombinant PCR reaction to generate the “gene cassette”
The schematic organization of the ΔiolQGK::kan cassette, replacing the iolQGK coding region of G. kaustophilus with a thermostable kanamycin-resistance gene, is used in this protocol as an example (Figure 1). This gene cassette was generated by recombinant PCR, ligating the five PCR fragments as follows.
Amplify the five fragments individually (A1, A2, B1, B2, and C1) by PCR using KOD -Plus- neo polymerase. The specific primer pairs used to amplify each of the fragments are listed above in the Materials and Reagents section. It is strongly recommended to check the correct amplification of each PCR fragment by agarose gel electrophoresis. The PCR reactions are composed and carried out as follows:
PCR reaction:
Components Volume Final Concentration
10× PCR Buffer 5 μL 1×
2 mM dNTPs 5 μL 0.2 mM each
25 mM MgSO4 3 μL 1.5 mM
Primer (10 μM each) 0.75–1.5 μL 0.15–0.3 μM each
Template DNA variable Plasmid/PCR fragment DNA ~50 ng/50 μL Genomic DNA ~200 ng/50 μL
KOD -Plus- Neo (1 U/μL) 1 μL 1 U/50 μL
H2O variable
Total 50 μL
Thermal cycler conditions:
Initial Denaturation 98 °C 2 min
30 cycles 98 °C 10 s
68 °C 30 s/kb
Hold 4 °C
Purify the PCR reactions using a DNA purification kit and determine the concentration of the purified DNA by measuring OD260nm.
Mix all the amplified and purified fragments in a 1:1:1:1:1 molar ratio.
Run the recombinant PCR for the recombination of the five fragments using primers aprED-r2-nested and aprEU-f3-nested. The PCR reaction is the same as described above, but set the thermal cycler conditions as follows:
Thermal cycler conditions:
Initial Denaturation 98 °C 2 min
30 cycles 98 °C 10 s
68 °C 2.5 min
Hold 4 °C
Figure 1. Strategy to generate the ΔiolQGK::kan cassette (recombinant product). Five fragments are amplified by PCR using the primer pairs mentioned in A.14. Two fragments correspond to “upstream” and “downstream” regions of the B. subtilis aprE locus and are named A1 and A2, respectively. Two other fragments corresponding to sequences located upstream and downstream of G. kaustophilus MK244 iolQGK are named B1 and B2, respectively; the DNA fragment containing the kanamycin-resistance gene of pUCG18T is named C1. Fragments A1 and A2 are designed to be approximately 1 kb long, and fragments B1 and B2 are approximately 3 kb. The specific primers, indicated as arrows, are listed in the Materials and Reagents section. Colored regions of bent arrows correspond to 5′ extensions designed to create overlap with a flanking region in the final recombinant product. Overlapping sequences are indicated using different colors. The five individual PCR fragments are linked together by PCR to form one long “gene cassette” fragment.
Transformation
The presence of pLS20 lowers competence levels (Singh et al., 2012). Therefore, it is recommended to generate the final B. subtilis donor YNB213 in two steps. First, the five-fragment recombinant product generated by PCR is used to transform competent B. subtilis 168 cells. Second, chromosomal DNA isolated from a kanamycin-resistant transformant of this transformation is then used to transform competent B. subtilis YNB211 cells harboring pLS20catΔoriT and containing both the oriTpLS20 and the IPTG-inducible rappLS20 present on the chromosome at the yhfK and amyE loci, respectively (Miyano et al., 2018; Mori et al., 2022). Transformation of B. subtilis is performed as follows:
Grow a strain of B. subtilis to be transformed overnight (~16 h) on an LB 2% agar plate at 30 °C to form colonies.
Pick up a fresh colony and use it to inoculate 5 mL of C-1 medium in a test tube to allow the cells to grow at 37 °C with vigorous shaking (at least 200 rpm) for 2.5 h.
Collect the cells by centrifugation at 6,000 rpm at room temperature for 3 min.
Suspend the cell pellet in 10 mL of C-2 medium in a new test tube and incubate the tube with shaking at 37 °C for 40 min.
Transfer 1 mL of the C-2 medium culture into a new tube containing less than 100 µL of DNA solution (1–10 µg/mL).
Incubate the tube with shaking at 37 °C for 2 h.
Spread the culture onto plates containing appropriate antibiotics to select transformants.
Conjugation and selection of transconjugant (Figure 2)
Based on the previous findings that the addition of sorbitol (Kananavičiūtė et al., 2015), MgCl2, and maleic acid-NaOH buffer (Wyrick and Rogers, 1973) was effective in increasing the efficiency of transformation by electroporation and stabilizing L-form cells, we developed a modified medium, named LBMSM, suitable for elevating the efficiency of this transformation of G. kaustophilus mediated by conjugation.
Preparation of donor culture
Grow B. subtilis YNB213 overnight on an LB 2% agar plate containing 10 µg/mL chloramphenicol at 37 °C to form colonies.
Pick up a fresh colony and use it to inoculate 5 mL of LB liquid medium containing 10 µg/mL chloramphenicol, pre-warmed at 37 °C in a test tube.
Grow overnight at 37 °C with shaking at 200 rpm.
In a 300 mL baffled Erlenmeyer flask pre-warmed at 37 °C, dilute the culture in 10 mL of LBMSM medium containing 1.0 mM IPTG to reach an OD600 of 0.05 (check using a spectrophotometer).
Grow the cells at 37 °C with shaking at 200 rpm until OD600 reaches 0.6–0.8, and use this as the donor culture.
Preparation of recipient culture
Grow G. kaustophilus MK244 overnight on an LB 2% agar plate at 60 °C to form colonies.
Pick up a fresh colony and inoculate it into 10 mL of LB liquid medium pre-warmed to 60 °C in a 300 mL Erlenmeyer flask.
Grow the cells at 60 °C for 2 h with shaking at 200 rpm.
Dilute the culture (to make OD600 adjusted to 0.01 using a spectrophotometer) in 10 mL of LBMSM medium in a 300 mL baffled Erlenmeyer flask pre-warmed at 60 °C.
Allow the cells to grow at 60 °C with shaking at 200 rpm until OD600 reaches 0.6–0.8 measured with a spectrophotometer, and use this as the recipient culture.
Mating
Mix 2 mL of the donor culture and 8 mL of the recipient culture in a sterilized 300 mL Erlenmeyer flask.
Stand the mixed culture at 37 °C for 90 min, and then allow the cells to grow at 60 °C for 180 min with shaking at 200 rpm.
Colony formation of transconjugant
Transfer the mating culture into a test tube and centrifuge at 8,152 × g for 2 min and resuspend the pellet in 1.2 mL of LB liquid medium pre-warmed at 60 °C in a 1.5 mL tube.
Spread the suspension onto LB 2% agar plates containing 7.5 µg/mL of kanamycin pre-warmed at 60 °C (200 µL on each Petri dish 9 cm in diameter).
As negative control experiments, spread separately donor and recipient cells onto LB 2% agar plates containing 7.5 µg/mL of kanamycin pre-warmed at 60 °C.
Incubate the plates at 60 °C overnight and score the number of colonies.
Colony formation of recipient
Sample a small portion (~100 µL) of the mating culture, dilute it 107-fold, and spread 100 µL of the dilution on LB 2% agar plates.
Incubate the plates at 60 °C overnight and score the number of colonies.
Figure 2. A schematic presentation of the conjugation procedure. Donor strain B. subtilis YNB213 and recipient strain G. kaustophilus MK244 were grown independently. Mating was performed by mixing two cultures in a 1 to 4 ratio of donor and recipient cells, followed by further incubation to enhance colony formation.
Southern blot analysis
Southern blot analysis allows us to detect a specific DNA sequence in chromosomal DNA samples, which usually involves four successive steps, including (i) Fragmentation of chromosomal DNA with restriction enzymes, (ii) Separation of DNA fragments by electrophoresis, (iii) Transfer of the DNA onto the membrane, and (iv) Detection of DNA on the membrane using the probe. It is important to choose appropriate restriction enzymes for the fragmentation of chromosomal DNA. In the case of this protocol, we decided on Cla I and Sac II (Figure 3). For the detection of DNA on the membrane, a fluorescence-based nonradioactive technology with a DIG-labeled RNA probe is used for the detection of target DNA.
Preparation of DIG-labeled RNA
Run PCR to amplify the stretch corresponding to the kanamycin-resistance gene using KOD -Plus- neo polymerase and the primer pairs Km-probe-f and Km-probe-r. The PCR reactions are composed and carried out as follows:
PCR reaction:
Components Volume Final Concentration
10× PCR Buffer 5 μL 1×
2 mM dNTPs 5 μL 0.2 mM each
25 mM MgSO4 3 μL 1.5 mM
Primer (10 μM each) 0.75–1.5 μL 0.15–0.3 μM each
pUCG18T DNA variable ~50 ng/50 μL
KOD -Plus- Neo (1 U/μL) 1 μL 1 U/50 μL
H2O variable
Total 50 μL
Thermal cycler condition:
Initial Denaturation 98 °C 2 min
30 cycles 98 °C 10 s
68 °C 30 s/kb
Hold 4 °C
Using the DNA purification kit, purify the amplified DNA as the template for in vitro transcription.
Perform the in vitro transcription of the template DNA using T7 RNA polymerase and DIG RNA Labeling Mix, following the protocol provided by the manufacturer. This step generates a DIG-labeled RNA probe.
Store the DIG-labeled RNA probe at -80 °C until being used.
Digestion and electrophoresis of the genomic DNA
Extract genomic DNAs and measure OD260 to determine their concentration.
Digest 3 µg of genomic DNAs with appropriate restriction enzymes at 37 °C for at least 1 h to complete the digestion.
Subject the digested DNAs in parallel with the size markers (DNA Molecular Weight Marker II, DIG-labeled) to 1.0% agarose gel electrophoresis.
Run the electrophoresis for 1 h at 100 V.
Blotting, hybridization, and detection
Soak the agarose gel successively in 150 mL of (i) 0.25 M HCl (30 min), (ii) denaturing solution (30 min), and (iii) neutralizing solution (30 min).
Transfer DNAs in the gel onto a positively charged nylon membrane (Amersham Hybond-N+), using the transfer apparatus (Vacuum Transfer BS-31) as instructed by the supplier.
Crosslink the transferred DNAs to the membrane with UV crosslinker L-1000 with accumulative radiation set to 0.07 J/cm2.
Transfer the membrane into a hybridization bag, and fill up the bag with 30 mL of DIG Easy Hyb at 50 °C for at least 10 min for pre-hybridization.
Denature the DIG-labeled RNA probe by boiling the water solution containing the probe for 10 min and then snap-cool by placing the sample on ice.
Soak the membrane in the bag filled with 30 mL of DIG Easy Hyb containing 100 ng/mL of denatured DIG-labeled RNA probe at 42 °C overnight with gentle shaking.
Wash the membrane twice for 5 min with 150 mL of low-stringency wash solution at room temperature with gentle shaking.
Wash the membrane twice for 15 min with 150 mL of pre-warmed high-stringency wash solution at 65 °C with gentle shaking.
Wash the membrane briefly with 150 mL of maleic acid buffer with gentle shaking.
Soak the membrane in blocking reagent diluted in 150 mL of maleic buffer for 30 min at room temperature to prevent non-specific binding of antibodies.
Transfer the membrane into a hybridization bag and incubate for 30 min with 30 mL of blocking reagent containing 1/104 volume of Anti-Digoxigenin-AP, Fab fragment (20 mL of blocking reagent per 100 cm2 of membrane should be used).
Wash the membrane twice with 150 mL of wash buffer for 15 min with gentle shaking.
Transfer the membrane into a new hybridization bag and equilibrate with 30 mL of detection buffer for 3 min.
Discard the detection buffer and incubate the membrane with 30 mL of detection buffer containing CSPD at 37 °C for 5–10 min (20 mL of detection buffer should be used per 100 cm2 of membrane).
Detect the chemiluminescence signal using ChemiDoc XRS+ following the instructions of the supplier.
Figure 3. Physical maps of the relevant regions of the chromosomes of donor, recipient, and transconjugant strains.
Data analysis
Conjugation and selection of transconjugant
Evaluate the efficiency judging from the value of CFUtransconjugant/CFUrecipient, which usually is approximately 1.0 × 10-9.
Count the number of colonies that appear on the plates containing kanamycin incubated at 60 °C overnight. Calculate CFUtransconjugant as follows:
CFUtransconjugant = Mean ± SD of colony numbers per plate × 1.2 mL/200 μL/10 mL
For example, when 3, 3, and 5 colonies were formed on three plates, respectively:
CFUtransconjugant = 3.7 ± 1.2 ×1.2/0.2/10 = 2.2 ± 0.7
Count the number of colonies that appear on the plates without kanamycin incubated at 60 °C overnight. Calculate CFUrecipient as follows:
CFUrecipient = Mean ± SD of colony numbers per plate × 107 × 1 mL/100 μL
For example, when 18, 13, and 11 colonies were formed on three plates, respectively:
CFUrecipient = 14.0 ± 3.6 × 107 × 1.0 /0.1 = 1.4 ± 0.36 × 109
Southern blot analysis
Take a picture of the chemiluminescence signal on the membrane to visualize the bands of DNA fragments containing the kanamycin-resistance gene (Figure 4).
Estimate the length of each band in relation to the positions of the size marker DNAs electrophoresed in parallel with the samples.
Check against the physical maps of the chromosome to ensure that the kanamycin-resistance gene has been inserted at the desired location. Proper insertion of the kanamycin-resistance gene, in this case, is confirmed by the appearance of a specific combination of bands on the membrane: a 5,456 bp band from both transconjugant and donor for SacII digestion, an 8,581 bp band from transconjugant or a 6,172 bp band from a donor for ClaI digestion, and a 3,583 bp band from both transconjugant and donor for SacII and ClaI double digestion.
Figure 4. Results of Southern blot analysis. Chromosomal DNAs of the Recipient (lanes 1, 4, and 7), Transconjugant (lanes 2, 5, and 8), and Donor (lanes 3, 6, and 9) strains digested with Sac II (lanes 1–3), Cla I (lanes 4–6), and Cla I & Sac II (lanes 7–9) were subjected to agarose gel electrophoresis in parallel with size marker DNA fragments (M) followed by Southern blot analysis probing for the kanamycin-resistance gene.
Recipes
LB medium
Reagent Final concentration Amount
LB (Difco Lennox) 2% 20 g
H2O
Total 1,000 mL
Autoclave at 121 °C for 20 min.
LBMSM
Reagent Final concentration Amount
LB (Difco Lennox) 2% 20 g
H2O 500 mL
After autoclaving the above at 121 °C for 20 min, add the following solutions sterilized separately.
1.25 M sorbitol 0.5 M 400 mL
0.4 M MgCl2 0.02 M 50 mL
0.4 M maleic acid-NaOH buffer (pH 7.0) 0.02 M 50 mL
Total 1,000 mL
Solution A
Reagent Final concentration Amount
K2HPO4 0.16 M 5.6 g
KH2PO4 0.088 M 2.4 g
(NH3)2SO4 0.03 M 0.8 g
Sodium citrate·2H2O 0.0068 M 0.4 g
H2O
Total 200 mL
Autoclave at 121 °C for 20 min.
Solution B
Reagent Final concentration Amount
MgSO4·7H2O 0.010 M 0.5 g
Glucose 0.056 M 2 g
H2O
After autoclaving the above, add the following solutions sterilized separately.
2 mg/mL FeCl3·4H2O 4.02 × 10-6 M 80 µL
0.1 mg/mL MnSO4·5H2O 1.66 × 10-7 M 80 µL
100× trace element × 0.2 400 µL
Total 200 mL
100× Trace element
Reagent Final concentration Amount
CaCl2·2H2O 4.97 × 10-3 M 0.73 g
ZnCl2 1.25 × 10-3 M 0.17 g
CuCl2·2H2O 2.52 × 10-4 M 0.043 g
CoCl2·6H2O 2.52 × 10-4 M 0.06 g
Na2MoO4·2H2O 2.48 × 10-3 M 0.06 g
H2O
Total 1,000 mL
Autoclave at 121 °C for 20 min.
C-1 medium
Reagent Final concentration Amount
Solution A 2.5 mL
Solution B 2.5 mL
After autoclaving the above at 121 °C for 20 min, add the following solutions sterilized separately.
5% yeast extract 0.05% 50 µL
10% casamino acids 0.10% 10 µL
5 mg/mL L-Trp 50 µg/mL 50 µL
Total 5 mL
C-2 medium
Reagent Final concentration Amount
Solution A 5.0 mL
Solution B 5.0 mL
After autoclaving the above at 121 °C for 20 min, add the following solutions sterilized separately.
5% yeast extract 0.05% 10 µL
10% casamino acids 0.10% 10 µL
5 mg/mL L-Trp 5 µg/mL 10 µL
Total 10 mL
50× TAE buffer
Reagent Final concentration Amount
Tris (hydroxymethyl) aminomethane 2 M 242 g
Acetic acid 1 M 57.1 mL
Na2EDTA·2H2O 0.5 M 18.6 g
H2O
Total 1,000 mL
Autoclave at 121 °C for 20 min.
TKE buffer
Reagent Final concentration Amount
1 M Tris-HCl buffer (pH 8.0) 0.1 M 10 mL
0.5 M Na2EDTA (pH 8.0) 0.05 M 10 mL
1 M KCl 0.1 M 10 mL
H2O 70 mL
Total 100 mL
Autoclave at 121 °C for 20 min.
20× SSC
Reagent Final concentration Amount
Sodium citrate·2H2O 0.3 M 88.2 g
NaCl 3 M 175.3 g
H2O
Total 1,000 mL
Adjust pH to 7 with 14 N HCl.
Autoclave at 121 °C for 20 min.
Maleic acid buffer
Reagent Final concentration Amount
Maleic acid 0.1 M 11.61 g
NaCl 0.15 M 8.77 g
NaOH 0.18 M 7.2 g
H2O
Total 1,000 mL
Adjust pH to 7.5.
Autoclave at 121 °C for 20 min.
Denaturing solution
Reagent Final concentration Amount
NaCl 1.5 M 87.6 g
NaOH 0.5 M 20 g
H2O
Total 1,000 mL
Neutralizing solution
Reagent Final concentration Amount
1 M Tris-HCl buffer (pH 7.5) 0.5 M 500 mL
NaCl 1.5 M 87.6 g
H2O
Total 1,000 mL
Low-stringency wash solution
Reagent Final concentration Amount
20× SSC 0.1× SSC 30 mL
10% SDS 0.2% 12 mL
H2O
Total 600 mL
High-stringency wash solution
Reagent Final concentration Amount
20× SSC 2× SSC 180 mL
10% SDS 0.2% 12 mL
H2O
Total 600 mL
Detection buffer
Reagent Final concentration Amount
Tris 0.1 M 12.1 g
NaCl 0.1 M 5.84 g
MgCl2 0.05 M 4.76 g
H2O
Total 1,000 mL
Adjust pH to 9.5.
Acknowledgments
The authors thank Valeria Verrone and Anil Wipat for their indispensable contribution to the original research paper where this protocol was derived from Mori et al. (2022). This study was supported by KAKENHI 18H02128.
Competing interests
This protocol is related to a patent and is only permitted for use in academic research. In particular, the distribution of the strains YNB211 and YNB213 requires the conclusion of an appropriate material transfer agreement.
References
Christie, P. J., Whitaker, N. and Gonzalez-Rivera, C. (2014). Mechanism and structure of the bacterial type IV secretion systems. Biochim Biophys Acta 1843(8): 1578-1591.
Christie, P. J. (2016). The Mosaic Type IV Secretion Systems. EcoSal Plus 7(1).
Kananavičiūtė, R., Kanišauskaitė, I., Novickij, V. and Čitavičius, D. J. (2015). Geobacillus stearothermophilus NUB3621R genetic transformation by electroporation. Biologija61(3-4): 101-108.
Koehler, T. M. and Thorne, C. B. (1987). Bacillus subtilis (natto) plasmid pLS20 mediates interspecies plasmid transfer. J Bacteriol 169(11): 5271-5278.
Meijer, W. J. J., Boer, D. R., Ares, S., Alfonso, C., Rojo, F., Luque-Ortega, J. R. and Wu, L. J. (2021). Multiple Layered Control of the Conjugation Process of the Bacillus subtilis Plasmid pLS20. Front Mol Biosci 8: 648468.
Miyano, M., Tanaka, K., Ishikawa, S., Takenaka, S., Miguel-Arribas, A., Meijer, W. J. J. and Yoshida, K. I. (2018). Rapid conjugative mobilization of a 100 kb segment of Bacillus subtilis chromosomal DNA is mediated by a helper plasmid with no ability for self-transfer. Microb Cell Fact 17(1): 13.
Mori, K., Fukui, K., Amatsu, R., Ishikawa, S., Verrone, V., Wipat, A., Meijer, W. J. J. and Yoshida, K. I. (2022). A novel method for transforming Geobacillus kaustophilus with a chromosomal segment of Bacillus subtilis transferred via pLS20-dependent conjugation. Microb Cell Fact 21(1): 34.
Nazina, T. N., Tourova, T. P., Poltaraus, A. B., Novikova, E. V., Grigoryan, A. A., Ivanova, A. E., Lysenko, A. M., Petrunyaka, V. V., Osipov, G. A., Belyaev, S. S., et al. (2001). Taxonomic study of aerobic thermophilic bacilli: descriptions of Geobacillus subterraneus gen. nov., sp. nov. and Geobacillus uzenensis sp. nov. from petroleum reservoirs and transfer of Bacillus stearothermophilus, Bacillus thermocatenulatus, Bacillus thermoleovorans, Bacillus kaustophilus, Bacillus thermodenitrificans to Geobacillus as the new combinations G. stearothermophilus, G. th. Int J Syst Evol Microbiol 51(Pt 2): 433-446.
Singh, P. K., Ramachandran, G., Duran-Alcalde, L., Alonso, C., Wu, L. J. and Meijer, W. J. (2012). Inhibition of Bacillus subtilis natural competence by a native, conjugative plasmid-encoded comK repressor protein. Environ Microbiol 14(10): 2812-2825.
Singh, P. K., Ramachandran, G., Ramos-Ruiz, R., Peiró-Pastor, R., Abia, D., Wu, L. J. and Meijer, W. J. (2013). Mobility of the native Bacillus subtilis conjugative plasmid pLS20 is regulated by intercellular signaling. PLoS Genet 9(10): e1003892.
Suzuki, H. and Yoshida, K. (2012). Genetic transformation of Geobacillus kaustophilus HTA426 by conjugative transfer of host-mimicking plasmids. J Microbiol Biotechnol 22(9): 1279-1287.
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Peer-reviewed
Chromosome Scaffolding of Diploid Genomes Using ALLHiC
YW Yi-Bin Wang
XZ Xing-Tan Zhang
Published: Sep 20, 2022
DOI: 10.21769/BioProtoc.4503 Views: 657
Reviewed by: Alba BlesaSanzhen Liu Anonymous reviewer(s)
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Abstract
High-throughput chromosome conformation capture (Hi-C) technology has become an economical and robust tool for generating a chromosome-scale assembly. However, high-quality chromosome scaffoldings are limited by the number of short and chimeric contigs, making the assembly quality unsatisfactory in most cases. Here, we present a Hi-C scaffolding protocol based on ALLHiC, which integrates multiple functions to break chimeric contigs and generate chromosome-scale scaffolds. In addition, we describe a convenient way to curate the remaining misassemblies. This pipeline has been successfully applied to many genome projects, including our previously published banyan tree and oolong tea genomes.
Keywords: Genome assembly Chromosome-scale assembly Hi-C Scaffolding Diploid ALLHiC
Background
Construction of a chromosome-scale assembly is a step-by-step process, including generating a contig-level assembly and linking contigs into scaffolds or chromosomes by long-range linking information, such as optical maps, 10× Genomics Linked-Reads, or Hi-C (Zhang et al., 2019; Zhang et al., 2020a). Hi-C (Lieberman-Aiden et al., 2009) is a technology derived from 3C (Chromosome Conformation Capture) technology integrated with next-generation sequencing, which serves as an economical and robust method widely used in many genome projects (Dudchenko et al., 2017; Zhang et al., 2020b). Hi-C can capture many chromatin proximities in parallel and span a long distance of genomic regions, even separated by >200 Mb. Hence, based on proximity information from Hi-C, contigs can be linked into chromosome-scale assemblies with great clarity.
In the past decade, several Hi-C scaffolding algorithms have been developed, including LACHESIS (Burton et al., 2013), SALSA (Ghurye et al., 2017), and 3D-DNA (Dudchenko et al., 2017). Our team also developed a Hi-C scaffolding algorithm, namely ALLHiC. Although initially designed for chromosome phasing in polyploid genomes (Zhang et al., 2019), ALLHiC also shows capability for chromosome-scale assembly in diploid genomes. Here, we describe a pipeline for chromosome scaffolding of diploid genomes by ALLHiC, from an initial contig-level assembly to a high-quality chromosomal-scale assembly (Figure 1). This pipeline uses the Hi-C paired-end reads to generate a mosaic genome assembly of diploids and provides a method to correct chimeric scaffolds. Moreover, this pipeline has been successfully applied in the diploid chromosome scaffolding in the banyan tree (Zhang et al., 2020b) and oolong tea genomes (Zhang et al., 2021).
Figure 1. Workflow of our pipeline of chromosome-scale scaffolding using ALLHIC.
Software and Data sets
Software
Linux OS
Miniconda (latest version) ()
Bwa (version 0.7.17) (https://github.com/lh3/bwa)
samtools (version 1.9) (http://www.htslib.org/)
bedtools (https://github.com/arq5x/bedtools2)
ALLHiC (https://github.com/tangerzhang/ALLHiC)
asmkit (version 0.0.1) (https://github.com/wangyibin/asmkit)
ParaFly (version 2013-01-21) (http://parafly.sourceforge.net)
3D-DNA (https://github.com/aidenlab/3d-dna)
juicebox_scripts (https://github.com/phasegenomics/juicebox_scripts)
Perl (version 5) (https://perl.org)
Python (version 3) (https://python.org)
Matplotlib (version 3.3.4) (https://matplotlib.org)
Pandas (version 1.3.0) (https://pandas.pydata.org)
Pysam (version 0.18.0) (https://pysam.readthedocs.io/en/latest)
Numpy (version 1.16.5) (https://www.numpy.org)
Windows/MacOS
Juicebox (https://github.com/aidenlab/Juicebox)
Data sets
The input data of our pipeline are Hi-C data with fastq format and draft assembly with fasta format.
A small testing data set could be downloaded from google drive (https://drive.google.com/file/d/1oE6HpOTZ6rFSlVLOjO0EpIH_-cULCWec/view?usp=sharing).
Note: These small data sets were generated from Arabidopsis thaliana; the contig assembly was downloaded from 1001 genomes (https://1001genomes.org/data/MPI/MPISchneeberger2011/releases/current/Ler-1/Assemblies/Allpaths_LG/Ler-1.allpaths_lg.final.assembly.fasta), and Hi-C data downloaded from http://ibi.hzau.edu.cn/3dmodel/download/mp2014_raw_data.tar.gz.
Procedure
Note: This procedure is introduced based on our testing data sets.
Installation of required software
Note: Conda should be installed first.
Install the conda package manager.
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
sh Miniconda3-latest-Linux-x86_64.sh
Install the bwa, samtools, bedtools, and Perl via conda.
conda install -c bioconda bwa samtools bedtools
conda install -c conda-forge perl
Install the python package of matplotlib, NumPy, pysam, and pandas via conda.
conda install matplotlib numpy pandas pysam
Install the ALLHiC, 3D-DNA, and juicebox_scripts via GitHub. We recommend installing these packages into “~/software.”
ALLHiC
git clone https://github.com/tangerzhang/ALLHiC.git
chmod -R 755 ALLHiC
echo “export
PATH=$HOME/software/ALLHiC/bin:$HOME/software/ALLHiC/scripts:$P
ATH” >> ~/.bash_profile
3D-DNA
git clone https://github.com/aidenlab/3d-dna.git
juicebox_scripts
git clone https://github.com/phasegenomics/juicebox_scripts.git
Install the asmkit and ParaFly.
asmkit
wget https://github.com/wangyibin/asmkit/releases/download/v0.0.1/asmkit
mv asmkit ~/bin
ParaFly
wget https://sourceforge.net/projects/parafly/files/parafly-r2013-01-21.tgz
tar xzvf parafly-r2013-01-21.tgz
cd parafly-r2013-01-21
./configure –prefix=`pwd`
make install
mv bin/ParaFly ~/bin
Correction of the draft contigs
Misjoined contigs can be detected based on abnormal Hi-C signals (Dudchenko et al., 2017). This function has been integrated into the ALLHiC pipeline, and users can apply ALLHiC_corrector to break chimeric contigs.
Map Hi-C reads to the draft assembly.
Prepare the genome alignment index of draft assembly.
bwa index draft.asm.fasta
samtools faidx draft.asm.fasta
Map the Hi-C reads into draft assembly; meanwhile, retain primary alignments and sort the alignments.
bwa mem -5SPM -t 10 draft.asm.fasta Lib_R1.fastq.gz Lib_R2.fastq.gz \
| samtools view -hF 256 - \
| samtools sort -@ 10 -o sorted.bam -T tmp.ali
Create the index files of the above-sorted alignment file using samtools and break the misjoined contigs by Hi-C signals.
samtools index -@ 10 sorted.bam
ALLHiC_corrector -m sorted.bam -r draft.asm.fasta -o
seq.HiCcorrected.fasta -t 10
Map Hi-C reads to corrected assembly and filter Hi-C signals
Create the index files based on the corrected genome assembly from step B2 (seq.HiCcorrected.fasta). Then, align the Hi-C data to corrected assembly, retain primary alignments, and sort the alignments.
bwa index seq.HiCcorrected.fasta
bwa mem -5SPM -t 10 seq.HiCcorrected.fasta Lib_R1.fastq.gz Lib_R2.fastq.gz \
| samtools view -hF 256 - \
| samtools sort -@ 10 -o sample.bwa_mem.bam -T tmp.ali
Filter the alignments based on the quality by MAPQ filtering using samtools. Here, alignments with mapping quality lower than 30 were removed from the alignment file generated in step C1. After filtering, the multiply alignments and low-quality alignments will be removed.
samtools view -bq 30 sample.bwa_mem.bam > sample.unique.bam
Retain the paired-end reads located within 1,000 bp genomic regions of the restriction sites and generate a reduced BAM file, only containing paired-end reads.
PreprocessSAMs.pl sample.unique.bam seq.HiCcorrected.fasta HINDIII
Partition
Assign contigs into a defined number of groups (k), where -k <int> is the number of groups, -e <string> is the motif of restriction enzyme, -r is the corrected assembly, and -b is the filtered alignments from step C3.
ALLHiC_partition -r seq.HiCcorrected.fasta -e HINDIII (e.g. HindIII: AAGCTT; MboI: GATC; Arima: GATC,GANTC) -k group_count -b sample.unique.REduced.paired_only.bam
Optimization
The optimization step was dedicated to order and orientate contigs from each group; the resulting command lines could be executed in parallel using the ParaFly program. The following command lines generate k numbers of files (.tour) containing the intermediate and final optimization results.
RE=AAGCTT
for i in {1..k}; do echo “allhic optimize sample.unique.REduced.paired_only.count_${RE}.${k}g${i}.txt sample.unique.REduced.paired_only.clm”; done > cmd.list
ParaFly -c cmd.list -CPU 4
Building
The chromosome-level sequences (fasta) and contig assignment (agp) can be generated using the following command line.
ALLHiC_build seq.HiCcorrected.fasta
Curation
Chimeric errors may be introduced into the chromosomal-scale assemblies due to misjoined contigs or ambiguous Hi-C reads mapping. However, these misassemblies could largely be manually fixed in Juicebox. The following command lines convert ALLHiC results into the input files for Juicebox curation.
Create a hic format file which can be imported into the Juicebox.
Asmkit bam2links sample.unique.Reduced.paired_only.bam out.links
asmkit agp2assembly groups.agp groups.assembly
bash ~/software/3d-dna/visualize/run-assembly-visualizer.sh groups.assembly out.links
Juicebox (https://github.com/aidenlab/Juicebox/wiki) is a graphical software that can be run in local machines (Windows or macOS) and be used to curate the misassemblies by Hi-C signals. After careful curation, a modified assembly can be exported.
Import files of group.hic and group.assembly (Figure 2A and 2B).
Curation of misassemblies can be manually followed by video (https://www.youtube.com/watch?v=Nj7RhQZHM18).
After curation, export assembly file of group.review.assembly (Figure 2C).
Figure 2. Steps for curation on Juicebox.
(A) Import group.hic file. (B) Import group.assembly. (C) Export group.review.assembly file.
Convert modified assembly into agp location file and create the final chromosome-scale assembly.
python ~/software/juicebox_scripts/juicebox_scripts/juicebox_assembly_converter.py -a groups.review.assembly -f seq.HiCcorrected.fasta -s
Assessment of the final assembly
Statistics of the chromosome length and anchoring rate.
statAGP.pl groups.review.agp
Plot the heatmap of whole genome and per chromosome.
Get group length.
samtools faidx groups.review.fasta
cut -f 1,2 groups.review.fasta.fai > len.txt
Only keep chromosomal level assembly for plotting.
grep Chr len.txt > chrn.list
Plot heatmap in 500 kb resolution and output in pdf format.
ALLHiC_plot sample.bwa_mem.bam groups.review.agp chrn.list 500k pdf
Figure 3. Assessment of final chromosome-scale assembly.
(A) Assembly statistics from location agp file. (B) Whole-genome heatmap of the chromosome-scale assembly.
Result interpretation
The final results of this protocol are a contig location file (groups.review.agp) and a chromosome-scale assembly file (group.review.fasta). Furthermore, the final chromosome-scale assembly can be assessed by assembly statistics and whole-genome heatmap (Figure 3).
Acknowledgments
This work was supported by Shenzhen Science and Technology Program (Grant No. RCYX20210706092103024) and the National Key Research and Development Program of China (2021YFF1000900). This protocol was adapted from Zhang et al. (2019).
Competing interests
The authors declare no competing interests.
References
Burton, J. N., Adey, A., Patwardhan, R. P., Qiu, R., Kitzman, J. O. and Shendure, J. (2013). Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat Biotechnol 31(12): 1119-1125.
Dudchenko, O., Batra, S. S., Omer, A. D., Nyquist, S. K., Hoeger, M., Durand, N. C., Shamim, M. S., Machol, I., Lander, E. S., Aiden, A. P., et al. (2017). De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356(6333): 92-95.
Ghurye, J., Pop, M., Koren, S., Bickhart, D. and Chin, C.-S. (2017). Scaffolding of long read assemblies using long range contact information. BMC Genomics 18(1): 527.
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326(5950): 289-293.
Zhang, X., Chen, S., Shi, L., Gong, D., Zhang, S., Zhao, Q., Zhan, D., Vasseur, L., Wang, Y., Yu, J., et al. (2021). Haplotype-resolved genome assembly provides insights into evolutionary history of the tea plant Camellia sinensis. Nat Genet 53(8): 1250-1259.
Zhang, X., Wu, R., Wang, Y., Yu, J. and Tang, H. (2020a). Unzipping haplotypes in diploid and polyploid genomes. Comput Struct Biotechnol J 18: 66-72.
Zhang, X., Wang, G., Zhang, S., Chen, S., Wang, Y., Wen, P., Ma, X., Shi, Y., Qi, R., Yang, Y., et al. (2020b). Genomes of the Banyan Tree and Pollinator Wasp Provide Insights into Fig-Wasp Coevolution. Cell 183(4): 875-889 e817.
Zhang, X., Zhang, S., Zhao, Q., Ming, R. and Tang, H. (2019). Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nat Plants 5(8): 833-845.
Supplementary information
Data and code availability: All data, analysis, and codes have been deposited to GitHub: https://github.com/Bio-protocol/chromosome_scaffolding_of_simple_diploid_genomes_using_ALLHiC.git
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Systems Biology > Genomics > Sequencing
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4,504 | https://bio-protocol.org/en/bpdetail?id=4504&type=0 | # Bio-Protocol Content
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Microscopic Detection of DNA Synthesis in Early Mitosis at Repetitive lacO Sequences in Human Cells
KY Kazumasa Yoshida
RI Riko Ishimoto
MF Masatoshi Fujita
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4504 Views: 1344
Reviewed by: Gal HaimovichDavid PaulVaibhav B. Shah
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Original Research Article:
The authors used this protocol in The Journal of Cell Biology Jan 2021
Abstract
In the human cell cycle, complete replication of DNA is a fundamental process for the maintenance of genome integrity. Replication stress interfering with the progression of replication forks causes difficult-to-replicate regions to remain under-replicated until the onset of mitosis. In early mitosis, a homology-directed repair DNA synthesis, called mitotic DNA synthesis (MiDAS), is triggered to complete DNA replication. Here, we present a method to detect MiDAS in human U2OS 40-2-6 cells, in which repetitive lacO sequences integrated into the human chromosome evoke replication stress and concomitant incomplete replication of the lacO array. Immunostaining of BrdU and LacI proteins is applied for visualization of DNA synthesis in early mitosis and the lacO array, respectively. This protocol has been established to easily detect MiDAS at specific loci using only common immunostaining methods and may be optimized for the investigation of other difficult-to-replicate regions marked with site-specific binding proteins.
Keywords: DNA replication Replication stress DNA repair Mitosis MiDAS Repetitive DNA BrdU Immunofluorescence
Background
A basic principle of the cell cycle is to ensure that mitosis follows the completion of DNA replication. During S phase, various replication stresses, such as DNA lesions, conflicts with transcription, and tightly bound protein complexes, interfere with DNA replication and cause a genomic instability related to various genetic diseases (Muñoz and Méndez, 2017). To prevent or minimize the deleterious consequences of replication stress, cells have evolved DNA damage response mechanisms, including DNA repair pathways (Yoshida and Fujita, 2021). Stalled replication forks activate checkpoint pathways that halt the cell cycle progression (Lemmens and Lindqvist, 2019; Mocanu and Chan, 2021). However, it has been revealed that upon mild replication stress that modestly slows down the replication fork, cells can enter the mitosis with some under-replicated DNA (Lukas et al., 2011; Bertolin et al., 2020; Lezaja and Altmeyer, 2021; Mocanu and Chan, 2021). Mild replication stress causes incomplete replication without activating G2/M checkpoint, especially at difficult-to-replicate regions such as chromosomal fragile sites, centromeres, and telomeres (Sarlós et al., 2017; Özer and Hickson, 2018; Lokanga et al., 2021). Such regions with under-replicated DNA activate mitotic DNA synthesis (MiDAS) in early mitosis to complete DNA replication, whereas some regions remain incomplete and will be resolved in the subsequent cell cycle (Minocherhomji et al., 2015; Özer and Hickson, 2018; Bertolin et al., 2020; Lezaja and Altmeyer, 2021).
MiDAS is a kind of homology-directed repair DNA synthesis that involves repair of stalled replication intermediates and POLD3 (an accessory subunit of polymerase δ)-dependent conservative DNA synthesis, analogous to break-induced replication (Kockler et al., 2021; Epum and Haber, 2022). Basic protocols for detection of MiDAS were originally developed by Hickson and colleagues (Minocherhomji et al., 2015; Bhowmick et al., 2016; Garribba et al., 2018). Briefly, cells are treated with low dose (0.4 μM) aphidicolin and RO-3306. Aphidicolin, a DNA polymerase inhibitor, slows down DNA replication and induces under-replication, while RO-3306, an inhibitor of cyclin-dependent kinase 1, arrests cells at G2 phase. Cells are then released into mitosis in the presence of a nucleoside analog ethynyl deoxyuridine (EdU) to label newly synthesized DNA. Following click reaction, MiDAS is visualized as EdU foci on prophase chromatin by fluorescence microscopy.
Here, we describe a detailed method for detection of MiDAS at under-replicated regions evoked by repetitive lacO sequences in human U2OS 40-2-6 cells (Figure 1). U2OS 40-2-6 cell, a U2OS-derived cell line carrying lacO array and estrogen receptor (ERT2)–fused LacI gene, was generated to investigate DNA damage response to replication stress induced by tight DNA–protein complexes on the human chromosome (Ishimoto et al., 2021). Treatment with 4-hydroxytamoxifen (4-OHT) induces rapid formation of lacO–LacI complexes that interfere with DNA replication. Notably, we also found that even in the absence of LacI, repetitive lacO sequences are intrinsically difficult to replicate, remaining under-replicated until mitosis and consequently triggering MiDAS. In the method presented here, nascent DNA is labeled by another nucleoside analog bromodeoxyuridine (BrdU), and lacO array is visualized by immunostaining of LacI proteins bound to the array. In our ER–LacI induction system, replication stress is induced at the specific chromosomal locus using the sequence-specific DNA-binding proteins. MiDAS at the specific locus can therefore be easily detected using common immunostaining methods, without fluorescent in situ hybridization (FISH) used in the protocol developed by Hickson and colleagues. This protocol may be optimized for other repetitive fragile sites where MiDAS functions, such as telomeres, centromeres, and ribosomal DNA arrays.
Figure 1. Flowchart of the assay for detection of mitotic DNA synthesis at the lacO array.
Materials and Reagents
Lab-Tek II, 4-well chamber glass slides (Thermo Fisher, Nunc, catalog number: 154526)
Chamber removal tool (included with chamber slides)
Glass Coplin jar, 5 slides type (AsOne, catalog number: 4-567-01)
Syringe filter unit, PES 0.22 μm (Merk Millipore, catalog number: SLGPR33RS)
Syringe filter unit, PVDF 0.45 μm (Merk Millipore, catalog number: SLHVR33RS)
Rectangular dish (Eiken Chemical, catalog number: AW2000)
Cotton swab
Paper towel (Nippon Paper Crecia, catalog number: 37105)
Glass coverslips, 24 × 60 mm (Matsunami Glass, catalog number: C024601)
Nail polish (clear topcoat)
Human cell line U2OS 40-2-6 (Ishimoto et al., 2021), a U2OS-derived cell line carrying lacO array and ERT2-LacI gene generated from U2OS 2-6-3 cells (Janicki et al., 2004). U2OS 40-2-6 cells, and the original U2OS 2-6-3 cells, contain an approximately 200-copy array of 256 lacO repeats (approximately 50,000 copies of lacO sequences in total). The array is stably integrated into the chromosomal locus 1p36 in chromosome 1.
Dulbecco’s modified Eagle’s medium (D-MEM) (high glucose with L-glutamine) (e.g., Wako, catalog number: 043-30085)
Fetal bovine serum (FBS) (e.g., Nichirei, catalog number: 175012)
RO-3306 (e.g., Sigma-Aldrich, catalog number: SML0569)
4-Hydroxytamoxifen (4-OHT) (e.g., Abcam, catalog number: ab141943)
Ethanol (e.g., Nacalai Tesque, catalog number: 14713-53)
10× phosphate-buffered saline (PBS) (e.g., Wako, catalog number: 048-29805), diluted to 1×
Bromodeoxyuridine (BrdU) (e.g., Sigma-Aldrich, catalog number: B5002)
Saline (e.g., Otsuka Normal Saline, Otsuka Pharmaceutical)
PIPES (e.g., Dojindo, catalog number: 347-02224)
0.1 M EGTA-2Na solution (e.g., Nacalai Tesque, catalog number: 37346-05)
Triton X-100 (e.g., Wako, catalog number: 169-21105)
MgCl2 (e.g., Wako, Catalog number: 133-00165)
37% formaldehyde solution (e.g., Nacalai Tesque, catalog number: 16223-55)
Rabbit anti-LacI antibody, homemade (Ishimoto et al., 2021)
Thimerosal (e.g., Nacalai Tesque, Catalog number: 21624-74), dissolved with water to 10% (w/v)
Alexa 594 donkey anti-Rabbit IgG (Molecular Probes, catalog number: A21207)
Methanol (e.g., Nacalai Tesque, catalog number: 21915-93)
HCl (e.g., Wako, catalog number: 080-01066), diluted to 1 M
Mouse anti-BrdU antibody, clone: 3D4 (BD Pharmingen, catalog number: 555627)
Alexa 488 goat anti-Mouse IgG (Molecular Probes, catalog number: A11029)
4’, 6-diamidino-2-phenylindole (DAPI) (e.g., Wako, catalog number: 043-18804)
Fluoro-KEEPER antifade reagent (Nacalai Tesque, catalog number: 12593-64)
RO-3306 stock solution (see Recipes)
4-OHT stock solution (see Recipes)
BrdU stock solution (see Recipes)
PTEMF buffer (see Recipes)
FBS for antibody working solution (see Recipes)
Antibody working solutions (see Recipes)
DAPI stock solution (see Recipes)
Note: In our lab, we routinely use DAPI, Alexa 488, and Alexa 594 for triple staining of DNA and two interest proteins. Other combinations of fluorophores may be possible.
Equipment
Cell culture incubator (ASTEC, model: SCA-165D)
Water aspirator (e.g., FLINN scientific, model: AP1136)
Widefield fluorescence microscope equipped with a cooled CCD camera, an LED illumination source, and filters to image Alexa 488, Alexa 594, and DAPI (e.g., Keyence, BZ-X700). Similar conventional fluorescence microscopes would be applicable.
40× objective lens [e.g., Nikon, CFI (chromatic aberration free infinity) Plan Apo λ 40×/0.95 NA]. Higher magnification objectives, such as a 63× lens, may also be applicable.
Software
Microscope operating software (e.g., Keyence, the BZ-X viewer software)
Procedure
Cell synchronization and induction of LacI binding
Plate U2OS 40-2-6 cells at 4 × 104 cells in 0.5 mL of D-MEM medium supplemented with 8% FBS for each well of a 4-well chamber slide, so that the cells are 50%–60% confluent the next day.
Incubate cells in a cell culture incubator with 5% CO2 at 37 °C overnight.
Add RO-3306 to a final concentration of 7 μM to the D-MEM medium supplemented with 8% FBS in each well.
(Optional) For induction of LacI binding in S phase, add 4-OHT to a final concentration of 1 μM.
Note: LacI binding in S phase induces additional replication stress; however, it does not increase a frequency of MiDAS, probably because of the limited capacity for MiDAS (Ishimoto et al., 2021).
Incubate cells with RO-3306 at 37 °C for 20 h to synchronize cells at late G2 phase.
After 16 h incubation, to induce LacI binding in G2 phase, add 4-OHT to a final concentration of 1 μM (4 h treatment with 4-OHT in the presence of RO-3306) for the remaining 4 h of incubation with RO-3306.
Release into mitosis and labeling with BrdU
After 20 h incubation, cells are now in late G2 phase.
Wash cells three times with 1 mL of 1× PBS, pre-warmed to 37 °C, to remove RO-3306.
Add 0.5 mL of pre-warmed D-MEM medium supplemented with 8% FBS.
Simultaneously, add BrdU to a final concentration of 10 μM to label nascent DNA.
Incubate cells at 37 °C for 20 min, allowing cells to enter prophase.
Note: Be quick with washing and treating cells to limit exposure to room temperature (RT), which may disturb cell cycle progression. Pre-warming PBS and D-MEM to 37 °C is also critical for rapid and synchronous entry into mitosis.
Cell fixation, permeabilization, and immunostaining of LacI
Gently remove growth medium with a water aspirator attached with a yellow tip (200 μL).
Carefully add 1 mL of ice-cold PBS to each well.
Gently remove PBS, and carefully add 1 mL of PTEMF buffer for simultaneous fixation and permeabilization of the cells.
Incubate at RT for 20 min.
Aspirate PTEMF buffer and disassemble chambers from the glass slide. Be careful not to dry out cells during disassembly.
Note: Glass slides could be handled by hand, but tweezers should be used to remove and transfer the slides from the solution in Coplin jar.
Wash slides by immersing them in Coplin jar containing 50 mL of ice-cold PBS, three times for 5 min each.
Place slides in a rectangular dish facing up and remove excess PBS in the hydrophobic area around the wells with a cotton swab. Be quick not to dry out cells.
Add 95 μL of primary anti-LacI antibody solution (diluted 1:500, see Recipes) to each well.
Close the lid of rectangular dish and incubate at RT for 1 h.
Gently drain the antibody solution by tilting slides on paper towel.
Wash slides with ice-cold PBS in Coplin jar three times for 5 min each.
Place slides in a rectangular dish facing up and remove excess PBS with a cotton swab. Be quick not to dry out cells.
Add 95 μL of Alexa 594 secondary anti-rabbit antibody solution (diluted 1:1,000, see Recipes) to each well.
Close the rectangular dish and incubate at RT for 1 h.
From now on, shield the samples from light to avoid photobleaching of fluorescent dyes.
Re-fixation, DNA denaturation, and immunostaining of BrdU
Gently drain the antibody solution by tilting slides on paper towel.
Wash slides with 50 mL of ice-cold PBS in Coplin jar, three times for 5 min each.
Refix samples by immersing slides in Coplin jar containing 100% methanol (pre-chilled in -30 °C freezer overnight) for 10 min on the bench (at RT).
Wash slides with 50 mL of ice-cold PBS in Coplin jar, three times for 5 min each.
To denature DNA, immerse slides in Coplin jar containing 50 mL of 1M HCl for 15 min at RT.
Note: DNA denaturation is required for immunostaining of BrdU; however, too much treatment with HCl may cause weak DAPI staining at step E3.
Wash slides with ice-cold PBS in Coplin jar, three times for 5 min each.
Place slides in a rectangular dish facing up and remove excess PBS with a cotton swab. Be quick not to dry out cells.
Add 95 μL of primary anti-BrdU antibody solution (diluted 1:200, see Recipes) to each well.
Close the rectangular dish and incubate at RT for 1 h.
Gently drain the antibody solution by tilting slides on paper towel.
Wash slides with ice-cold PBS in Coplin jar, three times for 5 min each.
Place slides in a rectangular dish facing up and remove excess PBS with a cotton swab. Be quick not to dry out cells.
Add 95 μL of Alexa 488 secondary anti-mouse antibody solution (diluted 1:1,000, see Recipes) to each well.
Close the rectangular dish and incubate at RT for 1 h.
DAPI staining and mounting
Gently drain the antibody solution by tilting slides on paper towel.
Wash slides with 50 mL of ice-cold PBS in Coplin jar, three times for 5 min each.
Immerse slides in Coplin jar containing DAPI working solution (0.2 μg/mL, protected from light) in PBS for 15 min at RT.
Wash slides with 50 mL of ice-cold PBS in Coplin jar, three times for 5 min each.
Place slides on a paper towel facing up and remove excess PBS by cotton swab, taking care to prevent cells from drying out.
Add one drop of Fluoro-KEEPER antifade reagent to each well of the slide.
Mount with a glass coverslip, ensuring to avoid air bubbles.
Wipe off excess Fluoro-KEEPER antifade reagent from the edge of the coverslip.
Seal with nail polish at the edge of the coverslip and let it out to dry and cure at RT for at least 2 h or overnight.
Proceed to microscopy or store the slide at 4 °C for 1–2 months, keeping protected from light.
Image acquisition
Image the slide using a fluorescence microscope.
Find an area including cells in prophase/prometaphase using the DAPI channel and focus on LacI foci using the Alexa 594 channel.
Acquire images for each channel (DAPI, Alexa 488, and Alexa 594) consecutively at the same field position without changing the focus (Figure 2).
To evaluate the induction of MiDAS at lacO arrays, calculate colocalization frequencies of BrdU foci with lacO arrays. The numbers of prophase/prometaphase nuclei with a LacI focus and frequencies of nuclei in which BrdU signal forms a focus on the LacI focus are manually scored. Although prophase/prometaphase cells are enriched in this condition, BrdU foci colocalized with lacO foci can be observed in prophase/prometaphase and metaphase cells. In contrast, BrdU incorporation is not detected in G2-arrested cells (not released from RO-3306), as previously reported (Ishimoto et al., 2021).
Note: These images should be compared with the control assays without BrdU labeling (Figure 2, bottom) to confirm the specificity of the BrdU signals.
Figure 2. Representative images of mitotic DNA synthesis at the lacO array. The colocalization of LacI and BrdU is indicated by the white arrow. Scale bar = 10 μm.
Recipes
RO-3306 stock solution
Dissolve RO-3306 in DMSO to a stock concentration of 1 mM and store aliquots at -80 °C. Pre-warm to 37 °C before use.
4-OHT stock solution
Dissolve 4-OHT in 100% ethanol to a stock concentration of 125 μM and store aliquots at -30 °C. Pre-warm to 37 °C before use.
BrdU stock solution
Dissolve BrdU in saline to a stock concentration of 10 mg/mL (32.5 mM) and store aliquots at -80 °C.
PTEMF buffer
20 mM PIPES, pH 6.8
10 mM EGTA
0.2% Triton X-100
1 mM MgCl2
4% formaldehyde
Note: Prepare a solution without formaldehyde, filtrate with 0.22 μm filter, and store at 4 °C. Add formaldehyde freshly for each experiment.
FBS for antibody working solution
Add thimerosal to FBS to a concentration of 0.1% and filtrate with 0.45 μm filter. Store at 4 °C or at -30 °C for long-term storage.
Antibody working solutions
Dilute antibodies in 1× PBS supplemented with 10% FBS. Freshly prepare for each experiment.
Detection of LacI
Primary antibody: Rabbit anti-LacI, 1:500
Secondary antibody: Alexa 594 anti-Rabbit, 1:1,000
Detection of BrdU
Primary antibody: Mouse anti-BrdU, 1:200
Secondary antibody: Alexa 488 anti-Mouse, 1:1,000
DAPI stock solution
Dissolve DAPI in water to a stock concentration of 1 mg/mL, protected from light. Store at -30 °C.
Acknowledgments
This work was supported by grants from the Japan Society for the Promotion of Science (KAKENHI JP15K18478 and JP22H02603), the Fukuoka Foundation for Sound Health Cancer Research Fund, and the Mochida Memorial Foundation for Medical and Pharmaceutical Research. This protocol was adapted from our previous work (Ishimoto et al., 2021). Basic methods for detection of MiDAS were originally developed by the laboratory of Dr. Ian Hickson (Minocherhomji et al., 2015; Bhowmick et al., 2016)
Competing interests
The authors declare no conflicting interests.
References
Bertolin, A. P., Hoffmann, J. S. and Gottifredi, V. (2020). Under-Replicated DNA: The Byproduct of Large Genomes? Cancers (Basel) 12(10): 2764.
Bhowmick, R., Minocherhomji, S. and Hickson, I. D. (2016). RAD52 Facilitates Mitotic DNA Synthesis Following Replication Stress. Mol Cell 64(6): 1117-1126.
Epum, E. A. and Haber, J. E. (2022). DNA replication: the recombination connection. Trends Cell Biol 32(1): 45-57.
Garribba, L., Wu, W., Ozer, O., Bhowmick, R., Hickson, I. D. and Liu, Y. (2018). Inducing and Detecting Mitotic DNA Synthesis at Difficult-to-Replicate Loci. Methods Enzymol 601: 45-58.
Ishimoto, R., Tsuzuki, Y., Matsumura, T., Kurashige, S., Enokitani, K., Narimatsu, K., Higa, M., Sugimoto, N., Yoshida, K. and Fujita, M. (2021). SLX4-XPF mediates DNA damage responses to replication stress induced by DNA-protein interactions. J Cell Biol 220(1): e202003148.
Janicki, S. M., Tsukamoto, T., Salghetti, S. E., Tansey, W. P., Sachidanandam, R., Prasanth, K. V., Ried, T., Shav-Tal, Y., Bertrand, E., Singer, R. H., et al. (2004). From silencing to gene expression: real-time analysis in single cells. Cell 116(5): 683-698.
Kockler, Z. W., Osia, B., Lee, R., Musmaker, K. and Malkova, A. (2021). Repair of DNA Breaks by Break-Induced Replication. Annu Rev Biochem 90: 165-191.
Lemmens, B. and Lindqvist, A. (2019). DNA replication and mitotic entry: A brake model for cell cycle progression. J Cell Biol 218(12): 3892-3902.
Lezaja, A. and Altmeyer, M. (2021). Dealing with DNA lesions: When one cell cycle is not enough. Curr Opin Cell Biol 70: 27-36.
Lokanga, R. A., Kumari, D. and Usdin, K. (2021). Common Threads: Aphidicolin-Inducible and Folate-Sensitive Fragile Sites in the Human Genome. Front Genet 12: 708860.
Lukas, C., Savic, V., Bekker-Jensen, S., Doil, C., Neumann, B., Pedersen, R. S., Grofte, M., Chan, K. L., Hickson, I. D., Bartek, J., et al. (2011). 53BP1 nuclear bodies form around DNA lesions generated by mitotic transmission of chromosomes under replication stress. Nat Cell Biol 13(3): 243-253.
Minocherhomji, S., Ying, S., Bjerregaard, V. A., Bursomanno, S., Aleliunaite, A., Wu, W., Mankouri, H. W., Shen, H., Liu, Y. and Hickson, I. D. (2015). Replication stress activates DNA repair synthesis in mitosis. Nature 528(7581): 286-290.
Mocanu, C. and Chan, K. L. (2021). Mind the replication gap. R Soc Open Sci 8(6): 201932.
Muñoz, S. and Méndez, J. (2017). DNA replication stress: from molecular mechanisms to human disease. Chromosoma 126(1): 1-15.
Özer, Ö. and Hickson, I. D. (2018). Pathways for maintenance of telomeres and common fragile sites during DNA replication stress. Open Biol 8(4): 180018.
Sarlós, K., Biebricher, A., Petermann, E. J. G., Wuite, G. J. L. and Hickson, I. D. (2017). Knotty Problems during Mitosis: Mechanistic Insight into the Processing of Ultrafine DNA Bridges in Anaphase. Cold Spring Harb Symp Quant Biol 82: 187-195.
Yoshida, K. and Fujita, M. (2021). DNA damage responses that enhance resilience to replication stress. Cell Mol Life Sci 78(21-22): 6763-6773.
Article Information
Copyright
© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Cancer Biology > Genome instability & mutation > Cell biology assays
Cancer Biology > General technique > Cell biology assays
Cell Biology > Cell imaging > Fluorescence
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4,505 | https://bio-protocol.org/en/bpdetail?id=4505&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
A Bio-protocol resource
Peer-reviewed
Production, Purification, and Fluorometric Activity Assay of Human Aldehyde Dehydrogenases
RP Raquel Pequerul
SP Sergio Porté
XP Xavier Parés
MP Mileidys Pérez-Alea
JF Jaume Farrés
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4505 Views: 1080
Reviewed by: ASWAD KHADILKARMario ValentinoKomuraiah Myakala
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Cited by
Original Research Article:
The authors used this protocol in Communications Biology Apr 2022
Abstract
Human aldehyde dehydrogenase (ALDH) isoforms are NAD(P)+-dependent enzymes catalyzing the oxidation of a wide spectrum of aldehydes to their corresponding carboxylic acids. ALDH families 1 and 3 are associated with stemness, chemoresistance, and tumor progression across multiple tumor types. ALDH2 is involved in ethanol metabolism, and its deficiency is associated with a wide range of diseases. This protocol includes a method for recombinant protein production and affinity purification under reducing conditions that apply to ALDH family 1 and 3 isoforms, to produce high yields of pure, catalytically active protein (10–30 mg/L of culture). It also includes their respective enzymatic activity assays, optimized and based on the fluorescence emission of NAD(P)H at 460 nm, using hexanal (for ALDH1A1, 1A2, 1A3, and 2) or p-nitrobenzaldehyde (for ALDH3A1) as a substrate. These assays offer higher sensitivity than common UV-visible spectrophotometry and avoid interference of compounds that mask NAD(P)H absorption at 340 nm. The protocol could be adapted to high-throughput screenings using a fluorescent microplate reader. Not a single protocol existed in the literature that comprehensively addressed the methodology entailed in the production, purification, and fluorometric activity assays of the five isoforms. This standardized protocol, allowing a side-by-side comparison between the various isoforms and studies, is filling the gap and supersedes previously partial and scattered methodological information, representing an important contribution to the field. Here, high amounts of pure, soluble, stable, and catalytically active protein are obtained, which are suitable for crystallization trials and for the identification and characterization of substrates and inhibitors with therapeutic potential in the diagnostic and treatment of cancer and other diseases.
Keywords: Aldehyde dehydrogenase ALDH overexpression Affinity chromatography Standard enzymatic activity Fluorometric assay
Background
The aldehyde dehydrogenase (ALDH) superfamily consists of a cluster of evolutionarily related NAD(P)+-dependent enzymes catalyzing the oxidation of a wide spectrum of aldehydic substrates, generated from various endogenous and exogenous precursors to their corresponding carboxylic acids. Accordingly, ALDHs participate in several cellular processes, including the detoxification of endobiotic and xenobiotic compounds. The ALDHs comprise 19 isoforms that are active in most mammalian tissues, with the highest level in the liver, followed by the kidney, uterus, and brain (Koppaka et al., 2012). The different isoforms present different subcellular localization (cytoplasm, mitochondria, endoplasmic reticulum, and nucleus) and assemble into dimers or tetramers to form the active protein (Marchitti et al., 2008).
Among the ALDH isoforms, ALDH members from families 1 and 3 have received increased attention as potential therapeutic targets in the treatment of cancer and other pathological conditions. The enzymatic activities of members from ALDH family 1 (e.g., ALDH1A1, ALDH1A2, and ALDH1A3) and family 3 (e.g., ALDH3A1) are commonly used as cancer stem cell markers, and are reported as involved in proliferation, drug resistance, and metastasis, which together contribute to cancer aggressiveness and poor prognosis (Feng et al., 2009; Greco et al., 2014; Li et al., 2014; Rebollido-Rios et al., 2020). Additionally, ALDH family 1 participates in the regulation of hundreds of genes during early developmental stages, via the production of retinoic acid (Iturbide et al., 2021). ALDH2, which is actually an ALDH family 1 member when considering sequence identity (Vasiliou et al., 2013), is the major enzyme involved in the oxidation of acetaldehyde during ethanol metabolism (Klyosov et al., 1996). The functional inactivation of ALDH2 is robustly associated with the development of certain types of cancers, including oropharyngolaryngeal, esophageal, stomach, colon, lung, head, and neck cancers (Muto, 2000; Yokoyama et al., 2001). Altogether, ALDH families 1 and 3 are considered promising targets for the diagnosis and treatment of cancer and other diseases (Duan et al., 2016). In addition, ALDH enzymes metabolize toxic aldehydes from lipid peroxidation to counterbalance the effects of reactive oxygen species (Singh et al., 2014).
With the aim to find novel, potent, and selective inhibitors against ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, and ALDH3A1, the overexpression, purification, and determination of the specific enzyme activity of these five isoforms become essential procedures for structure-function studies and the identification and characterization of putative inhibitory molecules (Jiménez et al., 2019; Pequerul et al., 2020; Ibrahim et al., 2021, 2022; Castellví et al., 2022). Thus, it is of prime importance to tackle and optimize reproducible methodologies to obtain recombinant ALDH isoforms, as well as to develop side-by-side protocols for determining the standard enzymatic activity of members of human ALDH families 1 and 3. Only if the standard conditions are perfectly established, could we obtain high protein amounts for crystallization trials and structure-based drug design, as well as for developing screening procedures for novel inhibitors against ALDH isoforms.
Since ALDH1A1, ALDH1A2, ALDH1A3, and ALDH2 exhibit a role in the physiological oxidation of alkanals such as hexanal, this aldehyde was used as a substrate to measure the standard activity of these isoforms. Hexanal is a product of lipid peroxidation, and its concentration is increased in cancer (Janfaza et al., 2019). ALDH3A1 participates actively in the metabolism of exogenous aromatic aldehydes, such as cinnamaldehyde, anisaldehyde, vanillin, and benzaldehyde, which are usually found in food components (Laskar and Younus, 2019). Accordingly, p-nitrobenzaldehyde, which is chemically more reactive than benzaldehyde, was used as a standard substrate for this isoform.
Materials and Reagents
1.5 mL sterile tube (Sudelab, catalog number: 1002208)
250 mL Beckman tubes (Beckman Coulter, catalog number: 356011)
0.45-µm filters (ACEFESA, Whatman, catalog number: GE10462100)
1-mL quartz cuvettes (Teknokroma, Starna, catalog number: ST-29-F/Q/10)
96-well microplates (Sarstedt, catalog number: 82.1581.100)
E. coli BL21 (DE3) pLysS competent cells (Sigma-Aldrich, Novagen, catalog number: 69451-M)
pET-30 Xa/LIC expression vector kit (Sigma-Aldrich, Novagen, catalog number: 70073)
ALDH/pET-30 Xa/LIC constructs (Proteogenix, custom order catalog number: GS-GS002—Gene Synthesis Service—and GS-SBG03—Subcloning into expression vector for gene <3,000 bp; https://www.proteogenix.science/custom-gene-synthesis/)
Kanamycin (Kn) (Sigma-Aldrich, catalog number: 60615)
Chloramphenicol (Cm) (Sigma-Aldrich, catalog number: C0378)
Glycerol (Sigma-Aldrich, catalog number: G5516)
Kolle handle loop (Auxilab, P. SELECTA, catalog number: BRG501)
Tryptone (Sigma-Aldrich, catalog number: 95039)
Yeast extract (Thermo Fisher Scientific, catalog number: 212750)
Sodium chloride (NaCl) (Sigma-Aldrich, catalog number: S9625)
Isopropyl β-d-1-thiogalactopyranoside (IPTG) (Sigma-Aldrich, catalog number: I6758)
Trizma base (Sigma-Aldrich, catalog number: T6066)
Imidazole (Sigma-Aldrich, catalog number: I202)
Lysozyme (Roche, catalog number: 10837059001)
DNase (Roche, catalog number: 10104159001)
Triton-X 100 (Sigma-Aldrich, catalog number: X-100)
Phenylmethanesulfonyl fluoride solution (PMSF) (Sigma-Aldrich, catalog number: 93482)
DL-Dithiothreitol (DTT) (ACEFESA, Panreac AppliChem, catalog number: A1101)
PD 10 desalting column (GE Healthcare, catalog number: 17-0851-01)
Coomassie Brilliant Blue R 250 (Sigma-Aldrich, catalog number: 1.12553)
Bovine serum albumin (BSA) (Roche, catalog number: 10711454001)
Bradford reagent (ACEFESA, Panreac AppliChem, catalog number: A6932,0500)
Sodium dodecyl sulfate (SDS) (Sigma-Aldrich, catalog number: L3771)
BenchMarkTM protein ladder (Thermo Fisher Scientific, catalog number: 10747012)
Sucrose (Sigma-Aldrich, catalog number: S0389)
Bromophenol blue sodium salt (Sigma-Aldrich, catalog number: B5525)
Glycine (Sigma-Aldrich, catalog number: W328707)
Methanol (MetOH) (ACEFESA, LABKEM, catalog number: MTOL-0GH-2K5)
Acetic acid (VWR, catalog number: 20103.295)
HEPES (Sigma-Aldrich, catalog number: H3375)
Ethylenediaminetetraacetic acid (EDTA) (Sigma-Aldrich, catalog number: E5134)
Nicotinamide adenine dinucleotide (NAD+) (Apollo Scientific, catalog number: BIB3011)
Nicotinamide adenine dinucleotide (reduced form) (NADH) (Apollo Scientific, catalog number: BIB3012)
Hexanal (Sigma-Aldrich, catalog number: H9008)
Magnesium chloride (Sigma-Aldrich, catalog number: M-2670)
Nicotinamide adenine dinucleotide phosphate (NADP+) (Apollo Scientific, catalog number: BIB3013)
Nicotinamide adenine dinucleotide phosphate (reduced form) (NADPH) (Apollo Scientific, catalog number: BIB3014)
p-Nitrobenzaldehyde (Sigma-Aldrich, catalog number: 72800)
LB culture medium (see Recipes)
2× YT culture medium (see Recipes)
Bind buffer (see Recipes)
Elution buffer (see Recipes)
Equilibration buffer (see Recipes)
5× TMR charge buffer (see Recipes)
Running buffer (see Recipes)
Coomassie Blue colorant (see Recipes)
De-stain solution (see Recipes)
Reaction buffer A (see Recipes)
Reaction buffer B (see Recipes)
Reaction buffer C (see Recipes)
20 mM NAD+ stock solution (see Recipes)
500 µM NADH stock solution (see Recipes)
40 mM NADP+ stock solution (see Recipes)
500 µM NADPH stock solution (see Recipes)
2 mM hexanal (see Recipes)
2 mM p-nitrobenzaldehyde (see Recipes)
Equipment
Bibby ScientificTM StuartTM block heater (Fisher Scientific, catalog number: 10489438)
Incubator shaker (VWR, New Brunswick, model: Innova® 43)
UV-Vis spectrophotometer (Agilent Technologies, model: Cary 60)
Centrifuge (Beckman Coulter, model: Avanti® J-26 XP)
Fixed-angle rotor (Beckman Coulter, model: JA-14)
Fixed-angle rotor (Beckman Coulter, model: JA-25.50)
Sonic dismembrator (Fisher Scientific, model: FisherbrandTM Model 705)
ÄKTATM start FPLC (Fast Protein Liquid Chromatography) purification system (Cytiva, catalog number: 29022094)
Multiplate reader (Tecan, model: Tecan® Spark)
Bransonic cleaner (Fisher Scientific, model: B200)
PowerPacTM basic power supply (Bio-Rad, catalog number: 1645050)
Cary Eclipse fluorescence spectrometer (Agilent Technologies)
Software
Unicorn 7 (GE Healthcare/Cytiva, https://www.cytivalifesciences.com/en/us/shop/chromatography/software/unicorn-7-p-05649)
Spark ControlTM (Tecan, https://lifesciences.tecan.es/multimode-plate-reader?p=tab--3)
Cary WINUV (Agilent Technologies, https://www.agilent.com/en/product/molecular-spectroscopy/uv-vis-uv-vis-nir-spectroscopy/uv-vis-uv-vis-nir-software/cary-winuv-software)
Procedure
Transformation of E. coli BL21 (DE3) pLysS competent cells with ALDH/pET-30 Xa/LIC constructs using the regular heat-shock method
Thaw E. coli BL21 (DE3) pLysS competent cells on an ice bath. Transfer 100 µL of cell suspension into a 1 mL sterile tube.
Add 1 ng of ALDH/pET-30 Xa/LIC construct to the cells.
Mix gently by pipetting up and down, and incubate on an ice bath for 5 min.
Heat-shock cells at 42 °C for 30 s using a block heater.
Note: Do not heat shock for more than 45 s.
Incubate on an ice bath for 2 min.
Immediately add 1 mL of LB media to the cells.
Incubate tubes for 1 h at 37 °C with agitation at 250 rpm.
Centrifuge at 16,100 × g for 5 min.
Remove 1 mL of supernatant and resuspend the pellet in the remaining LB media.
Spread 100 µL of cells onto LB plates containing 50 µg/mL kanamycin (Kn) and 34 µg/mL chloramphenicol (Cm).
Incubate overnight (O/N) at 37 °C.
Pick colonies and prepare an O/N culture in 5 mL of LB media containing 50 µg/mL Kn and 34 µg/mL Cm.
Prepare a bacterial glycerol stock with 400 µL of O/N culture and 100 µL of 80% glycerol.
Vortex.
Store the glycerol stock at -80 °C.
Expression and purification of recombinant human ALDH enzymes
Prepare an overnight (O/N) cell culture (25 mL of LB media) using the E. coli BL21 (DE3) pLysS cells containing ALDH/pET-30 Xa/LIC constructs in glycerol stock stored at -80 °C, with 50 µg/mL Kn and 34 µg/mL Cm (add 25 µL of each antibiotic using 50 mg/mL Kn and 34 mg/mL Cm solutions).
Inoculate the cells using a Kolle handle loop under sterile conditions.
Incubate O/N at 37 °C with agitation at 250 rpm, using an Innova 43 Incubator Shaker.
Measure the optical density (O.D.) at 595 nm using a spectrophotometer and inoculate the 25 mL of O/N culture in 1 L of 2× YT with 50 µg/mL Kn and 34 µg/mL Cm (add 1 mL of each antibiotic using 50 mg/mL Kn and 34 mg/mL Cm solutions).
Incubate until O.D.595 is 0.8.
Collect a 1 mL aliquot of pre-induction cell culture and keep it at -20 °C for further electrophoretic analysis (pre-induction aliquot). Induce the remaining culture with 1 mM IPTG.
Incubate O/N at 22 °C in an orbital shaker with agitation at 250 rpm.
Collect a 1 mL aliquot of IPTG post-induction cell culture and keep it at -20 °C for further electrophoretic analysis (post-induction aliquot).
Dispense the culture in 250 mL Beckman tubes.
Centrifuge at 12,400 × g (JA-14 rotor) and 4 °C for 10 min.
Discard the supernatant and resuspend the pellet with 35 mL of 20 mM Tris/HCl, 0.5 M NaCl, and 5 mM imidazole, pH 8.0 (bind buffer).
Lyse by freeze-thawing; keep the cell extracts O/N at -20 °C.
Thaw the cell extract at room temperature (RT).
Add 1 mg/mL lysozyme (700 μL of 50 mg/mL stock solution), 20 μg/mL DNase (350 μL of 2 mg/mL stock solution), 1% Triton-X 100 (1.5 mL of 20% stock solution), 1 mM PMSF (350 μL of 0.1 M stock solution), and 5 mM DTT (175 μL of 1 M stock solution).
Incubate on ice in an orbital shaker with agitation at 250 rpm for 20 min to obtain a less viscous sample.
Sonicate at 35% amplitude for 2 min (2 s ON – 1 s OFF) to obtain a homogeneous sample solution.
Collect a 1 mL aliquot of sonicated sample, centrifuge at 16,100 × g for 20 min, and keep the soluble fraction and the pellet separately at -20 °C, for further electrophoretic analysis (soluble and insoluble fraction after sonication aliquots, respectively). Proceed to the purification step.
Centrifuge the sonicated sample at 15,000 × g (JA-25.50 rotor) and 4 °C for 20 min.
Filtrate the supernatant through 0.45 µm filters.
Collect a 1 mL aliquot of supernatant and keep it at -20 °C for further electrophoretic tests. Proceed to the purification step.
Set the purification by affinity chromatography on a nickel-charged chelating SepharoseTM Fast Flow 5 mL column (HisTrap), using an ÄKTATM FPLC purification system.
After loading the sample, apply an increasing stepwise gradient of imidazole (5, 60, 100, and 250 mM) in 20 mM Tris/HCl, 0.5 M NaCl, 1 M imidazole, pH 8.0 (elution buffer) to enzyme elution (Figure 1):
1% imidazole, 10 column volumes (CV), 10 mL fractions
5.5% imidazole, 10 CV, 10 mL fractions
9.5% imidazole, 10 CV, 10 mL fractions
24.5% imidazole, 5 CV, 1 mL fractions
Figure 1. FPLC elution profile of a (His)6-ALDH on a nickel-charged chelating SepharoseTM Fast Flow 5 mL column (HisTrap) using an ÄKTATM FPLC purification system. The blue line represents the amount of eluted protein measured by the absorbance at 280 nm and the green line represents the stepwise imidazole gradient. FT: flowthrough or unbound protein fraction. WB: weakly bound protein fraction. P: peak with protein of interest.
Collect 1 mL aliquots of flowthrough (FT) and weakly bound (WB) protein fractions for further electrophoretic analysis.
Add 2.5 mL of eluted protein sample (24.5% imidazole fraction) in the PD 10 desalting column and remove imidazole with 3.5 mL of 50 mM mM Tris/HCl, 0.5 M NaCl, pH 8.0 (equilibration buffer).
Add 5 mM DTT, and prepare 200 μL protein aliquots by snap freezing in liquid nitrogen and storing at -20 °C.
Preparation and analysis of samples by SDS-PAGE
Prepare eight dilutions of bovine serum albumin (BSA) as a calibration curve (Bradford, 1976) with a range of 2.5 to 40 µg/mL in a 96-well plate.
Add 5 µL of each BSA dilution in a 96-well plate (duplicates).
Add 5 µL of pure recombinant protein to a 96-well plate (duplicates).
Add 245 µL of Bradford reagent to each well and mix.
Incubate at RT for at least 5 min and for no more than 1 h (He, 2011).
Measure absorbance at 595 nm using a spectrophotometer.
Centrifuge pre- and post-induction aliquots at 16,100 × g and 4 °C for 20 min.
Discard the supernatant and add 400 µL of bind buffer to thoroughly resuspend the pellet.
Add 1 mg/mL lysozyme (8 μL of 50 mg/mL stock solution), 20 μg/mL DNase (4 μL of 2 mg/mL stock solution), 1% Triton-X 100 (20 µL of 20% stock solution), and 1 mM PMSF (4 μL of 0.1 M stock solution).
Incubate on an ice bath for 20 min to obtain a less viscous sample.
Sonicate pre- and post-induction lysates in an ultrasonic bath for 10 min.
Note: For small volumes, it is recommended to use an ultrasonic bath instead of the sonic dismembrator instrument (used to obtain the cell homogenate, step B.16).
Add 400 µL of bind buffer to the insoluble fraction after sonication (step A.16).
Prepare seven samples containing 50 µL to be analyzed by SDS-PAGE as follows:
Add 25 µL of each purification step sample (pre-induction, post-induction, insoluble fraction after sonication, soluble fraction after sonication, FT, and WB).
Add 15 µL of Milli-Q water.
Add 10 µL of TMR charge buffer 5×.
For pure recombinant protein, load 2 μg onto SDS-PAGE according to the Bradford method of protein quantification (include Milli-Q water up to 40 µL and add 10 µL TMR charging buffer 5×).
Denature the samples at 95 °C for 10 min in a block heater.
Load 10 µL of BenchMarkTM protein ladder and 25 µL of each sample on an SDS-PAGE gel (Figure 2), and apply 100 V for 90 min using an electrophoresis PowerpacTM basic power supply through an SDS-PAGE assembly in running buffer.
Figure 2. SDS-PAGE analysis of ALDH expression and purification steps. MW marker: BenchMarkTM protein ladder; a) soluble fraction before induction; b) soluble fraction after IPTG induction; c) insoluble fraction after sonication; d) soluble fraction after sonication; e) affinity chromatography flowthrough; f) weakly bound protein fraction; g) 2 μg peak P (protein of interest—the ALDH band is marked with an arrow and corresponds to approximately 60 kDa, that is 55 kDa corresponding to the ALDH subunit plus 5 kDa from the His tag).
Stain the SDS-PAGE gel with 20 mL of Coomassie Blue in a staining vessel, at RT, with agitation for 20 min.
De-stain the SDS-PAGE gel O/N with 50 mL of de-stain solution at RT with agitation.
Enzymatic methodology for the determination of specific activity of ALDH
Determination of standard activity of ALDH1A1, ALDH1A2, and ALDH2 using hexanal as a substrate (Table 1)
Prepare three different enzyme dilutions from the corresponding enzyme stock solution in reaction buffer A (see Recipes) to reach a suitable activity for steady-state kinetics.
Note: It is essential to obtain a range of enzyme concentrations in which the substrate oxidation occurs under initial rate conditions.
Add 830 µL (805 µL for ALDH1A1 assay) of reaction buffer A into a 1 mL quartz cuvette.
Prepare an internal standard control containing 840 µL (815 µL for ALDH1A1 assay) of reaction buffer A.
Note: The internal standard control cuvette contains all compounds included in the assay mixture, except for enzyme.
Load 10 µL of each enzyme dilution in every single 1 mL quartz cuvette, except for the internal standard control cuvette.
Dilute NAD+ cofactor to 500 µM in reaction assay by adding 25 µL of 20 mM NAD+ stock.
Dilute NADH internal standard to 5 µM in reaction assay by adding 10 µL of NADH stock at 500 µM.
Note: The NADH internal standard is added to all cuvettes to establish a basal detection signal. Besides, in the internal standard control cuvette, 5 µM NADH enables the obtention of the absolute enzymatic rates from the units of relative fluorescence (see Data analysis section).
Mix by gentle inversion.
Start the reaction by adding 125 µL of 2 mM hexanal substrate stock solution into the cuvettes at a final saturating concentration of 250 µM (for ALDH1A1, add 150 µL of 0.2 mM hexanal substrate stock solution, and work at a final saturating concentration of 30 µM).
Note: The saturating concentration of hexanal is different for ALDH1A1 (30 µM) and for ALDH1A2 and ALDH2 (250 µM) (Pequerul et al., 2020).
Read the samples at excitation wavelength of 340 nm and collect the emission fluorescence at 460 nm for at least 600 s at 25 °C, using a Cary Eclipse fluorescence spectrometer.
Determination of standard activity of ALDH1A3 using hexanal as a substrate (Table 1)
Prepare three different enzyme dilutions from the corresponding enzyme stock solution in reaction buffer B (see Recipes) to reach a suitable activity for steady-state kinetics.
Add 830 µL of reaction buffer B into a 1 mL quartz cuvette.
Prepare an internal standard control containing 840 µL of reaction buffer B.
Load 10 µL of each enzyme dilution in every single 1 mL quartz cuvette, except for the internal standard control cuvette.
Dilute NAD+ cofactor to 500 µM in reaction assay by adding 25 µL of 20 mM NAD+ stock.
Dilute NADH internal standard to 5 µM in reaction assay by adding 10 µL of 500 µM NADH stock.
Mix by gentle inversion.
Start the reaction by adding 125 µL of 2 mM hexanal substrate stock solution into the cuvettes, at a final saturating concentration of 250 µM.
Read the samples at excitation wavelength of 340 nm and collect the emission fluorescence at 460 nm for at least 600 s at 25 °C, using a Cary Eclipse fluorescence spectrometer.
Determination of standard activity of ALDH3A1 using p-nitrobenzaldehyde as a substrate (Table 1)
Prepare three different enzyme dilutions from the corresponding enzyme stock solution in reaction buffer C (see Recipes) to reach a suitable activity for steady-state kinetics.
Add 830 µL of reaction buffer C into a 1 mL quartz cuvette.
Prepare an internal standard control containing 840 µL of reaction buffer C.
Load 10 µL of each enzyme dilution in every single 1 mL quartz cuvette, except for the internal standard control cuvette.
Dilute NADP+ cofactor to 1 mM in reaction assay by adding 25 µL of 40 mM NADP+ stock.
Dilute NADPH internal standard to 5 µM in reaction assay by adding 10 µL of 500 µM NADPH stock.
Mix by gentle inversion.
Start the reaction by adding 125 µL of 2 mM p-nitrobenzaldehyde substrate stock solution into the cuvettes, at a final saturating concentration of 250 µM.
Read the samples at an excitation wavelength of 340 nm and collect the emission fluorescence at 460 nm for at least 600 s at 25 °C, using a Cary Eclipse fluorescence spectrometer.
Table 1. Composition of the reaction mixture for the different ALDH enzymatic assays
Component ALDH1A1, 1A2, 2 ALDH1A3 ALDH3A1
Buffer 50 mM HEPES, pH 8 50 mM HEPES, pH 8 50 mM Tris/HCl, pH 8
Mg2+ − 30 mM −
EDTA 0.5 mM − −
DTT 0.5 mM 5 mM 5 mM
NAD+ 0.5 mM 0.5 mM −
NADP+ − − 1 mM
NADH 5 µM 5 µM −
NADPH − − 5 µM
Substrate 30 µM hexanal for 1A1
250 µM hexanal for 1A2 and 2
250 µM hexanal 250 µM pnitrobenzaldehyde
Data analysis
Calculation of specific enzymatic activity in µmol/min·mg (U/mg) (Solobodowska et al., 2012)
Adjust the slope for reaction assay cuvettes and obtain the units of relative fluorescence (UF) corresponding to the internal standard control cuvette (5 µM NAD(P)H internal standard),
where dF/dt is the slope of the time dependent fluorescence, Cst is the NAD(P)H concentration, and Fst is the standard fluorescence.
Obtain the absolute rates in U/mg (Figure 3 and Table 2), according to eq. 1
Figure 3. Screenshot of an Excel sheet showing representative raw data for the calculation of specific activity of ALDH1A1 using eq. 1.
Table 2. Specific activity (in U/mg) of ALDH1A1, ALDH1A2, ALDH1A3, ALDH2, and ALDH3A1
ALDH1A1 ALDH1A2 ALDH1A3 ALDH2 ALDH3A1
0.11 1.08 0.35 0.48 3.21
Enzymatic activity was measured at 25 °C using a Cary Eclipse spectrometer. ALDH1A1, ALDH1A2, and ALDH2 were assayed in reaction buffer A. ALDH1A3 assays were performed in reaction buffer B. NAD+ concentration was 500 μM, and hexanal was used as a substrate at saturating concentration. ALDH3A1 experiments were measured in reaction buffer C. NADP+ concentration was 1 mM, and a saturating concentration of p-nitrobenzaldehyde was used as a substrate.
Notes
The human ALDH1A1, 1A2, 1A3, 2, and 3A1 isoforms have been recombinantly expressed in a heterologous system and purified in soluble and enzymatically stable active forms.
Among the three ALDH1A enzymes, ALDH1A1 showed the lowest specific activity (0.11 U/mg) at a saturating concentration of hexanal, while ALDH1A2 exhibited the highest (1.1 U/mg). ALDH1A3 and ALDH2 showed intermediate rates of 0.35 and 0.48 U/mg, respectively. The specific activity of ALDH3A1 using a saturating concentration of p-nitrobenzaldehyde was 3.21 U/mg, the highest activity measured among these five ALDH isoforms.
ALDH1A3 is the ALDH1A isoform most dependent on DTT. The enzyme activity decreases when DTT is removed from the reaction buffer. The specific activity is 4-fold higher when 5 mM DTT is added to ALDH1A3 reaction buffer. Consequently, the ALDH1A3 reaction buffer contains a DTT concentration 10-fold higher when compared to those of ALDH1A1 and ALDH1A2 reaction buffers.
Related to the reaction buffer composition, a quite distinct pattern was observed for each enzyme when the effect of magnesium ions was studied in the presence of hexanal as a substrate (Pequerul et al., 2020). The highest activity of ALDH1A3 is shown at 30 mM MgCl2; thus, this Mg2+ concentration is present in the ALDH1A3 reaction buffer. In contrast, the chelating agent EDTA is included in the reaction buffer of ALDH1A1, ALDH1A2, and ALDH2.
It is essential to use a range of concentrations of active enzyme in which the substrate oxidation occurs under initial rate conditions (see step D1a).
The internal standard control cuvette contains all compounds included in the assay mixture except for enzyme (see step D1c).
The NADH internal standard is added to all cuvettes to establish a basal detection signal. Additionally, in the internal standard control cuvette, 5 µM NADH enables us to obtain the absolute enzymatic rates from the units of relative fluorescence (see step D1f).
The saturating concentration of hexanal is different for ALDH1A1 (30 µM) and for ALDH1A2 and ALDH2 (250 µM) (see step D1h).
Routinely, the N-terminal (His)6 tag is not removed after the affinity purification step, and it is kept for subsequent biochemical and structural studies. The N-terminal extension is located in the external part of the monomer structure and does not affect the stability, the oligomerization state, or the enzymatic activity of ALDHs (Pequerul et al., 2020; Castellví et al., 2022).
Summary of the statement
The protocol includes a method of recombinant protein production and affinity purification under reducing conditions that have been applied to ALDH family 1 and 3 isoforms to produce high yields of pure, soluble, stable, and catalytically active protein (10–30 mg/L of culture). It also includes their respective enzymatic activity assays, optimized and based on the fluorescence emission of NAD(P)H at 460 nm, using hexanal (for ALDH1A1, 1A2, 1A3, and 2) or pnitrobenzaldehyde (for ALDH3A1) as a substrate. The methodology is suitable for protein crystallography, and for the identification and characterization of substrates and inhibitors with diagnostic and therapeutic potential in the treatment of cancer and other diseases.
The urgent need for robust protocols to study ALDHs is well supported by the increasing interest of the scientific community in ALDH isoforms as cancer biomarkers, with more than 700 indexed publications only in the last five years (data extracted from the PubMed database, using as search terms ALDH and cancer). In addition, fluorogenic ALDH substrates combined with the pan-inhibitor N,N’-diethylaminobenzaldehyde (e.g., AldefluorTM assay) are widely used to identify ALDH isoforms in cancer stem cells. This is often a misleading factor that draws incorrect conclusions about the identity of particular ALDH isoforms, thus warranting the search for more selective inhibitors to improve the assay accuracy (Zhou et al., 2019, Ibrahim et al., 2022). Finally, despite the suitability of ALDH isoforms as drug targets for cancer therapy, there is a lack of potent and selective enzyme inhibitors to be developed for in vivo administration and translated to the clinical context. Our manuscript makes a step forward to establish and disseminate a fully optimized and validated protocol for ALDHs.
Recipes
LB culture medium
Dilute 10 g of tryptone, 10 g of NaCl, and 5 g of yeast extract in 1 L of Milli-Q water. Adjust pH to 7.0 using NaOH.
2× YT culture medium
Dilute 16 g of tryptone, 5 g of NaCl, and 10 g of yeast extract in 1 L of Milli-Q water. Adjust pH to 7.0 using NaOH.
Bind buffer
Dilute 0.34 g of imidazole (5 mM), 29.22 g of NaCl (0.5 M), and 2.4 g of Tris (20 mM) in 1 L of Milli-Q water. Adjust pH to 8.0 using HCl.
Elution buffer
Dilute 13.61 g of imidazole (1 M), 5.8 g of NaCl (0.5 M), and 0.48 g of Tris (20 mM) in 200 mL of Milli-Q water. Adjust pH to 8.0 using HCl.
Equilibration buffer
Dilute 29.22 g of NaCl (0.5 M) and 2.4 g of Tris (20 mM) in 1 L of Milli-Q water. Adjust pH to 8.0 using HCl.
5× TMR charging buffer
Dilute 8.55 g of sucrose (0.5 M), 5 g of SDS (10%), 1.89 g of Tris (312.5 mM), 0.14 g of EDTA (10 mM), and 1.92 g of DTT (250 mM) in 50 mL of Milli-Q water. Adjust pH to 6.9 and add 25 mg bromophenol blue.
Running buffer
Dilute 30.2 g of Tris (250 mM), 10 g of SDS (10%), and 140.3 g of glycine (1.87 M) in 1 L of Milli-Q water. Do not adjust pH.
Coomassie Blue colorant
Dilute 2.5 g/L Coomassie Brilliant Blue R 250 in 45% Milli-Q water, 45% MetOH, and 10% acetic acid.
De-stain solution
Prepare 60 mL of Milli-Q water, 30 mL of MetOH, and 10 mL of acetic acid.
Reaction buffer A (for ALDH1A1, ALDH1A2, and ALDH2 activity assays)
Dilute 11.92 g of HEPES (50 mM), 0.19 g of EDTA (0.5 mM), and 0.077 g of DTT (0.5 mM) in 1 L of Milli-Q water. Adjust pH to 8.0.
Reaction buffer B (for ALDH1A3 activity assays)
Dilute 11.92 g of HEPES (50 mM), 6.1 g of MgCl2 (30 mM), and 0.77 g of DTT (5 mM) in 1 L of Milli-Q water. Adjust pH to 8.0.
Reaction buffer C (for ALDH3A1 activity assays)
Dilute 6.06 g of Tris (50 mM) and 0.77 g of DTT (5 mM) in 1 L of Milli-Q water. Adjust pH to 8.0 using HCl.
20 mM NAD+ stock solution
Dilute 0.014 g of NAD+ in 1 mL of the corresponding reaction buffer.
500 µM NADH stock solution
Dilute a small amount of NADH (approximately a spatula tip) in 1 mL of the corresponding reaction buffer and measure the absorbance using a spectrophotometer. Calculate the concentration by the Lambert-Beer equation (Abs = ϵ·c·l), where ϵ is the molar absorptivity of NADH (6.22 mM−1·cm−1), c is the concentration of NADH, and l is the path length of the cuvette. For baseline, add 995 µL of the corresponding buffer in a 1 mL quartz cuvette and establish the zero. Then, add 5 µL of NADH stock and mix by inversion. Set up the spectrophotometer to scan the sample and obtain the absorbance of NADH at 340 nm. Obtain the stock concentration of NADH and prepare a work solution of 500 µM NADH in a 1 mL final volume (C1·V1 = C2·V2).
40 mM NADP+ stock solution
Dilute 0.014 g in 1 mL of reaction buffer C.
500 µM NADPH stock solution
Prepare an NADPH stock solution in reaction buffer C, as it was explained for 500 µM NADH stock solution (see Recipe 14).
2 mM Hexanal
Dilute 9.84 µL of hexanal in 40 mL of the corresponding reaction buffer.
2 mM p-nitrobenzaldehyde
Dilute 0.012 g p-nitrobenzaldehyde in 40 mL of reaction buffer C.
Acknowledgments
This research was funded by the Spanish Ministerio de Ciencia e Innovación (Agencia Estatal de Investigación, grant number PID2020-119424RB-I00 / AEI / 10.13039/501100011033). Raquel Pequerul obtained financial support from the company Advanced BioDesign through a research contract agreement with Universitat Autònoma de Barcelona.
Competing interests
The authors declare that there are no competing interests.
References
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Duan, J. J., Cai, J., Guo, Y. F., Bian, X. W. and Yu, S. C. (2016). ALDH1A3, a metabolic target for cancer diagnosis and therapy. Int J Cancer 139(5): 965-975.
Feng, J., Qiu, Q., Khanna, A., Todd, N. W., Deepak, J., Xing, L., Wang, H., Liu, Z., Su, Y., Stass, S. A., et al. (2009). Aldehyde dehydrogenase 1 is a tumor stem cell-associated marker in lung cancer. Mol Cancer Res 7(3): 330-338.
Greco, N., Schott, T., Mu, X., Rothenberg, A., Voigt, C., McGough, R. L., 3rd, Goodman, M., Huard, J. and Weiss, K. R. (2014). ALDH Activity Correlates with Metastatic Potential in Primary Sarcomas of Bone. J Cancer Ther 5(4): 331-338.
He, F. (2011). Bradford Protein Assay. Bio-101: e45.
Ibrahim, A. I. M., Ikhmais, B., Batlle, E., AbuHarb, W. K., Jha, V., Jaradat, K. T., Jimenez, R., Pequerul, R., Pares, X., Farres, J., et al. (2021). Design, Synthesis, Biological Evaluation and In Silico Study of Benzyloxybenzaldehyde Derivatives as Selective ALDH1A3 Inhibitors. Molecules 26(19).
Ibrahim, A. I. M., Batlle, E., Sneha, S., Jimenez, R., Pequerul, R., Pares, X., Rungeler, T., Jha, V., Tuccinardi, T., Sadiq, M., et al. (2022). Expansion of the 4-(Diethylamino)benzaldehyde Scaffold to Explore the Impact on Aldehyde Dehydrogenase Activity and Antiproliferative Activity in Prostate Cancer. J Med Chem 65(5): 3833-3848.
Iturbide, A., Ruiz Tejeda Segura, M. L., Noll, C., Schorpp, K., Rothenaigner, I., Ruiz-Morales, E. R., Lubatti, G., Agami, A., Hadian, K., Scialdone, A., et al. (2021).Retinoic acid signaling is critical during the totipotency window in early mammalian development. Nat Struct Mol Biol 28(6): 521-532.
Janfaza, S., Banan Nojavani, M., Nikkhah, M., Alizadeh, T., Esfandiar, A. and Ganjali, M. R. (2019). A selective chemiresistive sensor for the cancer-related volatile organic compound hexanal by using molecularly imprinted polymers and multiwalled carbon nanotubes. Microchim Acta 186(3): 137.
Jiménez, R., Pequerul, R., Amor, A., Lorenzo, J., Metwally, K., Aviles, F. X., Pares, X. and Farres, J. (2019). Inhibitors of aldehyde dehydrogenases of the 1A subfamily as putative anticancer agents: Kinetic characterization and effect on human cancer cells. Chem Biol Interact 306: 123-130.
Klyosov, A. A., Rashkovetsky, L. G., Tahir, M. K. and Keung, W. M. (1996). Possible role of liver cytosolic and mitochondrial aldehyde dehydrogenases in acetaldehyde metabolism. Biochemistry 35(14): 4445-4456.
Koppaka, V., Thompson, D. C., Chen, Y., Ellermann, M., Nicolaou, K. C., Juvonen, R. O., Petersen, D., Deitrich, R. A., Hurley, T. D. and Vasiliou, V. (2012). Aldehyde dehydrogenase inhibitors: a comprehensive review of the pharmacology, mechanism of action, substrate specificity, and clinical application. Pharmacol Rev 64(3): 520-539.
Laskar, A. and Younus, H. (2019). Aldehyde toxicity and metabolism: the role of aldehyde dehydrogenases in detoxification, drug resistance and carcinogenesis. Drug Metab Rev 51(1):42-64.
Li, Z., Xiang, Y., Xiang, L., Xiao, Y., Li, F. and Hao, P. (2014). ALDH maintains the stemness of lung adenoma stem cells by suppressing the Notch/CDK2/CCNE pathway. PLoS One 9(3): e92669.
Marchitti, S. A., Brocker, C., Stagos, D. and Vasiliou, V. (2008). Non-P450 aldehyde oxidizing enzymes: the aldehyde dehydrogenase superfamily. Expert Opin Drug Metab Toxicol 4(6): 697-720.
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Pequerul, R., Vera, J., Gimenez-Dejoz, J., Crespo, I., Coines, J., Porte, S., Rovira, C., Pares, X. and Farres, J. (2020). Structural and kinetic features of aldehyde dehydrogenase 1A (ALDH1A) subfamily members, cancer stem cell markers active in retinoic acid biosynthesis. Arch Biochem Biophys 681: 108256.
Rebollido-Rios, R., Venton, G., Sanchez-Redondo, S., Iglesias, I. F. C., Fournet, G., Gonzalez, E., Romero Fernandez, W., Borroto Escuela, D. O., Di Stefano, B., Penarroche-Diaz, R., et al. (2020). Dual disruption of aldehyde dehydrogenases 1 and 3 promotes functional changes in the glutathione redox system and enhances chemosensitivity in nonsmall cell lung cancer. Oncogene 39(13): 2756-2771.
Singh, S., Brocker, C., Koppaka, V., Chen, Y., Jackson, B. C., Matsumoto, A., Thompson, D. C. and Vasiliou, V. (2013). Aldehyde dehydrogenases in cellular responses to oxidative/electrophilic stress. Free Radic Biol Med 56: 89-101.
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Vasiliou, V., Thompson, D. C., Smith, C., Fujita, M. and Chen, Y. (2013). Aldehyde dehydrogenases: from eye crystallins to metabolic disease and cancer stem cells. Chem Biol Interact 202(1-3): 2-10.
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Zhou, L., Sheng, D., Wang, D., Ma, W., Deng, Q., Deng, L. and Liu, S. (2019). Identification of cancer-type specific expression patterns for active aldehyde dehydrogenase (ALDH) isoforms in ALDEFLUOR assay. Cell Biol Toxicol 35(2): 161-177.
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4,506 | https://bio-protocol.org/en/bpdetail?id=4506&type=0 | # Bio-Protocol Content
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Detection of Alternative End-Joining in HNSC Cell Lines Using DNA Double-Strand Break Reporter Assays
NZ Nan Zuo
LM Lin Ma
WH Weitao Hu
YD Yongqiang Deng
LW Lanlan Wei
QL Qi Liu
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4506 Views: 1296
Reviewed by: Pilar Villacampa AlcubierreHongLok Lung Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Science Translational Medicine Feb 2021
Abstract
The main cellular pathways to repair DNA double-strand breaks (DSBs) and protect the integrity of the genome are homologous recombination (HR), non-homologous end-joining (NHEJ), and alternative end-joining (Alt-EJ). Polymerase theta-regulated Alt-EJ is an error-prone DSB repair pathway characterized by microhomology usage. Considering its importance in cancer treatment, technologies for detection of Alt-EJ in cancer cells may facilitate the study of the mechanisms of carcinogenesis and the development of new therapeutic targets. DSB reporter assay is the classical method for detecting Alt-EJ, which is primarily based on components of EJ2-puro cassette integration, I-SceI cleaving, and flow cytometry analysis. Here, we described an assay based on a modified I-Scel plasmid that can screen head and neck squamous cell carcinoma (HNSC) cells that were successfully transfected using selection medium with hygrovetine. We expect that this protocol will improve the fidelity and accuracy of reporter assays.
Graphical abstract:
Schematic overview of the workflow for establishment of Alt-EJ reporters.
Keywords: Alternative end-joining Reporter assays DNA double-strand break Flow cytometry Head and neck squamous cell carcinoma
Background
DNA double-strand breaks (DSBs) are among the most dangerous forms of DNA lesions and must be efficiently and accurately repaired to prevent genomic instability, tumorigenesis, or cell death (Rahimian et al., 2020; Huang et al., 2021). To deal with endogenous and exogenous threats, cells have evolved multiple DSB repair pathways, mainly including homologous recombination (HR), non-homologous end-joining (NHEJ), and alternative end-joining (Alt-EJ) (Mateos-Gomez et al., 2015; Liu et al., 2019; Wang et al., 2021; Fujii et al., 2022). Of these, Alt-EJ is an error-prone form of DSB repair that leads to chromosomal rearrangements and genomic instability (Liu et al., 2019; Caracciolo et al., 2021; Valikhani et al., 2021). It has been reported that Alt-EJ plays a crucial role in BRCA2-deficient cancers, human papillomavirus-associated cancers, and tumors deficient in the TGF-β signaling pathway (Ceccaldi et al., 2015; Liu et al., 2018, 2019, 2021, 2022; Guix et al., 2022). However, there are still many unknown aspects of Alt-EJ, such as the mechanisms for Alt-EJ regulation, Alt-EJ in tumor development, and DNA damage responses. To further explore the relevant mechanisms and target Alt-EJ for therapeutic benefits, the methods for Alt-EJ detection need to be established and standardized.
Reporter assays, proposed by Gunn et al. (2012), are the most commonly used tools for measuring Alt-EJ (Gunn et al., 2012). EJ2GFP-puro, a non-functional fluorescent protein expression cassette, needs to be integrated into the genome of the cells to be tested. Following the generation of a DSB in the cassette by I-SceI, the expression of the green fluorescent protein is resumed if the cell adopts Alt-EJ for repairing this DSB (Bennardo et al., 2008) (Figure 1). However, due to a lack of suitable screening conditions, the results are inevitably influenced by the efficiency of transfection. Here, we utilized another retroviral system with antibiotic resistance to make DSB and screen for target cells, a method adapted from Muraki et al. (2013). The results are presented in our recent publications (Liu et al., 2018, 2021). This method can avoid the influence of transfection efficiency on the experimental results and improve the accuracy and reproducibility of Alt-EJ study.
Our protocol has been successfully applied in the HNSC cell line SAS, as well as in the glioblastoma cell line U251 (Liu et al., 2018). Theoretically, this protocol could also be applied in other tumor or normal cell lines that require detection of Alt-EJ levels, but further validation is still needed. We can judge the mutational potential of cell chromosomes by testing the levels of Alt-EJ in sorted cells, and thus further explore the development and treatment of relevant cancers.
Figure 1. Diagram of the EJ2GFP-puro cassette. EJ2-GFP contains a GFP expression cassette that is disrupted by the I-SceI cleavage site. Repair by Alt-EJ results in restoration of GFP protein expression.
Materials and Reagents
Pipette tips 10 μL, 200 μL, and 1,250 μL (BEAVER, catalog numbers: 43140, 43143, 43152)
Pipettes set (Gilson, catalog numbers: GFAM00140)
Centrifuge tubes 15 mL and 50 mL (BEAVER, catalog numbers: 43008, 43009)
EP tube 1.5 mL (AXYGEN, catalog numbers: MCT-150-C-S)
Cell culture plate 6-well, 48-well, 24-well, and 96-well (CORNING, catalog numbers: 3516, 3548, 3526, 3599)
100 mm cell culture plates (BEAVER, catalog numbers: 43701)
HNSC cell line SAS (RIKEN BRC, catalog numbers: RCB1974)
Human embryonic kidney cell line HEK293T (ATCC, catalog number: CRL-3216)
Bovine growth serum (HyClone, catalog number: SH30541.03)
Dulbecco’s modified Eagle’s medium, DMEM (Gibco, catalog number: 31966047)
Streptomycin-penicillin (Gibco, catalog number: 15140122)
Trypsin-EDTA (Gibco, catalog number: 25300096)
Lipofectamine 2000 (Invitrogen, catalog number: 11668019)
Opti-MEM (Gibco, catalog number: 51985026)
EJ2GFP-puro (Addgene, catalog number: 44025)
pQCXIH-I-SceI (a gift from Dr. John P. Murnane, University of California San Francisco)
Puromycin (Sigma-Aldrich, catalog number: P8833)
Hygrovetine (Selleck, catalog number: S2908)
Round-bottom tubes with cell strainer cap, 5 mL (Falcon, catalog number: 38030)
LY2157299 (SelleckChem, catalog number: S2230)
Olaparib (LC Laboratories, catalog number: O-9201)
PBS (see Recipes)
SAS/HEK 293T medium (see Recipes)
Equipment
Cell culture incubator (Thermo Fisher Scientific, catalog number: 51026283)
Neubauer counting chamber (Carl Roth, catalog number: PC72.1)
Centrifuge (Eppendorf, catalog numbers: 5804)
CytoFLEX flow cytometer (Beckman Coulter, catalog numbers: B49008AC)
Software
FlowJo software for FACS analysis
Procedure
Stable integration of EJ2GFP-puro into SAS cells
Twenty-four hours prior to transfection, plate SAS cells in a 6-well plate at 5 × 105 cells per well. Each well contains 2 mL of SAS medium.
For each well, prepare one Mix A and one Mix B, each in a 1.5 mL tube. Mix gently with finger flicking and incubate for 5 min.
Component Mix A Mix B
EJ2GFP-puro 2 μg -
Lipofectamine 2000 - 5 μL
Opti-MEM To 125 μL 120 μL
Total 125 μL 125 μL
Add Mix A to Mix B, mix gently, and incubate at room temperature for at least 20 min.
After washing the cells twice with 2 mL of 1× PBS, aspirate the PBS.
After adding the mixture to SAS cells, incubate at 37 °C and 5% CO2.
After 6 h of incubation, replace the mixture with SAS medium containing 2 mg/mL of puromycin.
Change the SAS medium containing 2 mg/mL of puromycin every 2–3 days until the cells reach 80%–90% confluence.
Trypsinize cells with trypsin-EDTA and count them.
Mix 60 cells with fresh SAS medium (containing 2 mg/mL of puromycin) to form a 6 mL cell suspension.
Add 100 μL of cell suspension to each well of a 96-well plate (100 μL of PBS for wells at the edge).
Four hours after plating, record the well with only one cell for subsequent screening.
When confluence exceeds 50% of well area, seed cells progressively into 48-well plates, 24-well plates, and 6-well plates. Select the cell line in the best condition for amplification and subsequent experiments. As there is a possibility that the selected monoclonal cell line is puromycin resistant and not EJ2GFP-puro successfully transfected, other monoclonal EJ2-puro-SAS cells will also need to be frozen for reserve.
Generation of I-SceI-induced DSBs
Retrovirus preparation
One day before packaging, plate 5 × 106 HEK 293T cells on a 100 mm cell culture plate containing 10 mL of HEK293T medium.
Prepare one Solution A and one Solution B, each in a 1.5 mL tube. Mix gently and incubate for 5 min.
Component Solution A Solution B
pQCXIH-I-SceI 20 μg -
Lipofectamine 2000 - 75 μL
Opti-MEM To 1,250 μL 1,125 μL
Total 1,250 μL 1,250 μL
Mix Solution A and Solution B together and let it sit at room temperature for at least 20 min.
Wash the HEK 293T twice with 10 mL of 1× PBS.
Add the mixture (Solution A and Solution B) to HEK 293T and incubate for 6 h at 37 °C and 5% CO2.
After 6 h of incubation, remove the transfection medium and replace with fresh HEK293T medium. Continue to incubate at 37 °C and 5% CO2.
After 72 h, harvest virus-containing medium. Virus-containing medium can be stored temporarily at 4 °C for 3 days or in a -80 °C refrigerator for approximately 6 months.
Generation of DSBs using I-SceI in SAS cells
One day before infection, plate monoclonal EJ2-puro-SAS in a 6-well plate (containing 2 mL of SAS medium) at 5 × 105 cells per well.
Incubate the monoclonal reporter cells with a mixture of 1 mL of virus-containing medium and 1 mL of SAS medium for 24 h.
After 24 h, select infected cells with fresh SAS medium containing 400 mg/mL hygromycin for 10 days. Refresh the medium every 2–3 days. GFP-expressing cells are clearly visible under fluorescent microscopy (Figure 2).
Figure 2. Representative images of GFP-expressing cells under fluorescent microscopy. Images of SAS (A) without or (B) with I-Scel transfection. Scale bar = 10 µm.
Flow cytometry detection of GFP+ cells
Wash the infected cells (at least 1 × 106 cells) twice with 1× PBS and trypsinize into single cell suspension.
Wash again with 1× PBS, spin at 500 × g for 5 min, resuspend in 1 mL of 1× PBS, and force cells through a flow tube with cell strainer cap.
Set the gate of GFP/FITC-Area on flow cytometry to detect the proportion of GFP+ cells (Figure 3). The efficiency of Alt-EJ detection by flow cytometry is further validated by two classical inhibitors. One is TGFBR1 inhibitor LY2157299, which leads to an upregulation of Alt-EJ levels. The other is PARP1 inhibitor Olaparib, which leads to a down-regulation of Alt-EJ levels. As shown in Figure 3E, our improved reporter assay accurately reflected the effect of both inhibitors on the regulation of Alt-EJ levels.
Figure 3. Flow cytometry detection of GFP+ SAS cells. (A) Negative control without I-SceI expression. (B) Control with I-SceI expression. (C) TGFBRI inhibition with LY2157299 (0.4 μmol/L for 48 h) to increase Alt-EJ. (D) PARP1 inhibition with Olaparib (10 μmol/L for 48 h) to decrease Alt-EJ. (E) Percentage of GFP-positive cells of SAS-EJ2-puro. NC: negative control; *P < 0.05; ***P < 0.001.
Recipes
1× PBS
Dissolve 137 mM of NaCl, 2.7 mM of KCl, 7.5 mM of Na2HPO4·12H2O, and 9.1 mM of KH2PO4 in 1 L ddH2O (pH 7.4).
SAS/HEK 293T medium
445 mL of DMEM supplemented with 50 mL of bovine growth serum and 5 mL of streptomycin-penicillin.
Data analysis
Flow cytometry
Gate cells of interest by setting up plots for forward scatter versus side scatter.
Using the forward scatter height versus forward scatter area excludes the doublets.
Untransfected cells were used as a negative control to identify the gate for detecting GFP expression negative cells. This gate was then used to evaluate the level of GFP expression in the target cells after transfection.
Acknowledgments
This study was supported by the Natural Science Foundation of China (82073007; Q. L.). The authors wish to acknowledge Prof. Jeremy Stark, Prof. Mary Helen Barcellos-Hoff, Prof. John Murnane, and Mr. Trevor Jones for their kind help and support with the results of this study. The protocol described here is adapted from previous studies (Gunn et al., 2012; Muraki et al., 2013).
Competing interests
The authors declare no competing interests.
References
Bennardo, N., Cheng, A., Huang, N. and Stark, J. M. (2008). Alternative-NHEJ is a mechanistically distinct pathway of mammalian chromosome break repair. PLoS Genet 4(6): e1000110.
Caracciolo, D., Riillo, C., Di Martino, M. T., Tagliaferri, P. and Tassone, P. (2021). Alternative Non-Homologous End-Joining: Error-Prone DNA Repair as Cancer's Achilles' Heel. Cancers (Basel) 13(6).
Ceccaldi, R., Liu, J. C., Amunugama, R., Hajdu, I., Primack, B., Petalcorin, M. I., O'Connor, K. W., Konstantinopoulos, P. A., Elledge, S. J., Boulton, S. J., et al. (2015). Homologous-recombination-deficient tumours are dependent on Poltheta-mediated repair. Nature 518(7538): 258-262.
Fujii, S., Sobol, R. W. and Fuchs, R. P. (2022). Double-strand breaks: When DNA repair events accidentally meet. DNA Repair 112: 103303.
Gunn, A. and Stark, J. M. (2012). I-SceI-based assays to examine distinct repair outcomes of mammalian chromosomal double strand breaks. Methods Mol Biol 920: 379-391.
Huang, R. and Zhou, P. K. (2021). DNA damage repair: historical perspectives, mechanistic pathways and clinical translation for targeted cancer therapy. Signal Transduct Target Ther 6(1): 254.
Liu, Q., Lopez, K., Murnane, J., Humphrey, T. and Barcellos-Hoff, M. H. (2019). Misrepair in Context: TGFbeta Regulation of DNA Repair. Front Oncol 9: 799.
Liu, Q., Palomero, L., Moore, J., Guix, I., Espin, R., Aytes, A., Mao, J. H., Paulovich, A. G., Whiteaker, J. R., Ivey, R. G., et al. (2021). Loss of TGFbeta signaling increases alternative end-joining DNA repair that sensitizes to genotoxic therapies across cancer types. Sci Transl Med 13(580).
Liu, Q., Chen, G., Moore, J., Guix, I., Placantonakis, D. and Barcellos-Hoff, M. H. (2022). Exploiting Canonical TGFbeta Signaling in Cancer Treatment. Mol Cancer Ther 21(1): 16-24.
Liu, Q., Ma, L., Jones, T., Palomero, L., Pujana, M. A., Martinez-Ruiz, H., Ha, P. K., Murnane, J., Cuartas, I., Seoane, J., et al. (2018). Subjugation of TGFbeta Signaling by Human Papilloma Virus in Head and Neck Squamous Cell Carcinoma Shifts DNA Repair from Homologous Recombination to Alternative End Joining. Clin Cancer Res 24(23): 6001-6014.
Guix, I., Liu, Q., Pujana, M. A., Ha, P., Piulats, J., Linares, I., Guedea, F., Mao, J. H., Lazar, A., Chapman, J., et al. (2022). Validation of Anticorrelated TGFbeta Signaling and Alternative End-Joining DNA Repair Signatures that Predict Response to Genotoxic Cancer Therapy. Clin Cancer Res 28(7): 1372-1382.
Mateos-Gomez, P. A., Gong, F., Nair, N., Miller, K. M., Lazzerini-Denchi, E. and Sfeir, A. (2015). Mammalian polymerase theta promotes alternative NHEJ and suppresses recombination. Nature 518(7538): 254-257.
Muraki, K., Han, L., Miller, D. and Murnane, J. P. (2013). The role of ATM in the deficiency in nonhomologous end-joining near telomeres in a human cancer cell line. PLoS Genet 9(3): e1003386.
Rahimian, E., Amini, A., Alikarami, F., Pezeshki, S. M. S., Saki, N. and Safa, M. (2020). DNA repair pathways as guardians of the genome: Therapeutic potential and possible prognostic role in hematologic neoplasms. DNA Repair 96: 102951.
Valikhani, M., Rahimian, E., Ahmadi, S. E., Chegeni, R. and Safa, M. (2021). Involvement of classic and alternative non-homologous end joining pathways in hematologic malignancies: targeting strategies for treatment. Exp Hematol Oncol 10(1): 51.
Wang, M., Chen, S. and Ao, D. (2021). Targeting DNA repair pathway in cancer: Mechanisms and clinical application. MedComm (2020) 2(4): 654-691.
Article Information
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Cancer Biology > Genome instability & mutation > Genetics
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Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4507 Views: 1000
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Original Research Article:
The authors used this protocol in Nature Communications Sep 2021
Abstract
The incorporation of non-standard amino acids (nsAAs) within proteins and peptides through genetic code expansion introduces novel chemical functionalities such as photo-crosslinking and bioconjugation. Given the utility of Bacillus subtilis in fundamental and applied science, we extended existing nsAA incorporation technology from Escherichia coli into B. subtilis, demonstrating incorporation of 20 unique nsAAs. The nsAAs we succeeded in incorporating within proteins conferred properties that included fluorescence, photo-crosslinking, and metal chelation. Here, we describe the reagents, equipment, and protocols to test for nsAA incorporation at a small scale (96-well plate and culture tube scales). We report specific media requirements for certain nsAAs, including two variants for different media conditions. Our protocol provides a consistent and reproducible method for incorporation of a chemically diverse set of nsAAs into a model Gram-positive organism.
Keywords: Bacillus subtilis Genetic code expansion Synthetic biology Non-standard amino acid Noncanonical amino acid Unnatural amino acid Translational control
Background
For decades, non-standard amino acids (nsAAs) have been used to introduce chemistries that are not ordinarily found in biological systems through genetically encoded site-specific incorporation within target proteins in live cells. When incorporated within proteins, nsAAs have been used for bioconjugation (Chin et al., 2002b; Seitchik et al., 2012), biocontainment (Mandell et al., 2015; Rovner et al., 2015), photo-crosslinking (Chin et al., 2002a, 2002b), fluorescence (Wang et al., 2006), and biomaterial production (Israeli et al., 2020). Akin to the ribosomally mediated process of translation for standard amino acids, nsAAs require a unique aminoacyl-tRNA synthetase and tRNA pair that exhibits minimal cross talk with other cellular components for codon recognition and addition of the nsAA to the growing polypeptide chain. The systems used to enable this for nsAAs are referred to as orthogonal translation systems (OTS), and they usually contain an aminoacyl-tRNA synthetase (AARS) and tRNA from an evolutionarily distant microbial species, such as the archaea Methanocaldococcus jannaschii or Methanomethylophilus alvus (Dumas et al., 2015; Beranek et al., 2019). Most commonly, the OTS is engineered to have a CUA anticodon for incorporation of the nsAA at the amber stop codon, UAG. This technology has been developed primarily in Escherichia coli and mammalian cell lines, thus limiting its use to a handful of organisms (Dumas et al., 2015). Extensive characterization of nsAAs technology in these species has led to discoveries of specific enzyme mechanisms, protein–protein interactions, and protein structures (Xie et al., 2004; Ai et al., 2011; Zhao et al., 2020).
Bacillus subtilis is a prime target for expansion of nsAA incorporation technology due to its broad utility as a Gram-positive rhizobacterium model in applied and fundamental research. B. subtilis has been used to study a variety of biological phenomena, including asymmetric cell division, biofilm formation, and sporulation (Losick et al., 1986; Kearns et al., 2005; McKenney et al., 2013; Bisson-Filho et al., 2017), which could be further investigated through incorporation of functional nsAAs such as those for post-translational modifications or photo-crosslinking. Having been conferred the status Generally Regarded As Safe (GRAS) by the US FDA, B. subtilis has also been used as a probiotic and vaccine vector for plants, animals, and humans (Cutting, 2011; Oh et al., 2020). Such applications could benefit from the site-specific incorporation of nsAAs within proteins for augmented capabilities or for the implementation of safeguards such as synthetic auxotrophy. B. subtilis is commercially used to produce antibiotics, cosmetic small molecules, and proteins (Westers et al., 2004; Stein, 2005; Su et al., 2020; Park et al., 2021). Given the variety of potential applications for B. subtilis in fundamental and applied science, we must continue to advance the tools available to scientists working with this organism.
Recent work from our groups demonstrated the potential application of site-specific nsAA incorporation within proteins in B. subtilis, including validation of theoretical protein–protein interactions, and tuning of cell wall biosynthesis with nsAA titration (Stork et al., 2021). Our study also provided preliminary evidence of the portability of this technology from E. coli to B. subtilis. Thus, the method presented here describes the application of these technologies, but it also establishes a fundamental base upon which the community can continue to build new technologies.
Existing technology for nsAAs incorporation in Bacilli species has been limited to a specific, single nsAA for a specific purpose (Scheidler et al., 2020; Tian et al., 2020). Our method presents the first demonstration of incorporation of a broad spectrum of nsAAs within proteins in B. subtilis for a variety of functions, including bioconjugation, photo-crosslinking, and fine-tuned control of protein expression. We demonstrated the incorporation of 20 unique nsAAs with six different orthogonal translation systems. In particular, we were able to incorporate 13 unique nsAAs with a single OTS system providing a platform strain for a diverse range of applications. This method also demonstrates the best overall nsAA incorporation with an upwards of 60% of native protein produced, thus far the best reported in B. subtilis. Some existing limitations to this system include background incorporation of the nsAA at natural stop codon sites and apparent limitations of the incorporation level in rich media. Despite those, this method provides an opportunity to introduce new tools to chemical biology and B. subtilis communities.
Materials and Reagents
Consumables
14 mL culture tubes (Fisher Scientific, FisherbrandTM, catalog number: 149566B)
Petri dishes (Fisher Scientific, FisherbrandTM, catalog number: FB0875713)
Multichannel reservoir (Fisher Scientific, BiotixTM, catalog number: 12111089)
Deep well 96-well plates (Fisher Scientific, FisherbrandTM, catalog number: 12566611)
Black walled 96-well microplates (Fisher Scientific, Greiner-Bio, catalog number: 07-000-166)
Breathable microplate seal covers (Fisher Scientific, Andwin Scientific, catalog number: NC1660916)
1 mL cuvettes (Fisher Scientific, FisherbrandTM, catalog number: 14955128)
PCR strips (Fisher Scientific, BrandTech, catalog number: 14380941)
Serological pipettes (Fisher Scientific, Basix, catalog number: 14-955-235)
15 mL conical tubes (Fisher Scientific, Basix, catalog number: 14955237)
Inoculation loops/toothpicks (Loops: FisherbrandTM, catalog number: 22-363-602)
B. subtilis strains are available here: https://bgsc.org/search.php?Search=bDS
Associated annotated DNA sequences are available in the supplemental data to the original Nature communications publication: https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-021-25691-4/MediaObjects/41467_2021_25691_MOESM6_ESM.zip
Non-standard Amino Acids
L-4,4-Biphenylalanine (BipA) (Peptech, catalog number: AL506)
L-4-Azidophenylalanine (pAzF) (abcr-GmbH, catalog number: AB308874)
Coumarin-nsAA (CouAA) (Sigma-Aldrich, catalog number: 792551)
L-4-Benzoylphenylalanine (BpA) (Peptech, catalog number: AL660)
L-4-Boc-lysine (boc-K) (Chem Impex Int’l, catalog number: 00363)
L-5-Hydroxytryptophan (5OHW) (Sigma-Aldrich, catalog number: 107751)
L-4-methyl-phenylalanine (4MeF) (Peptech, catalog number: AL096)
L-4-propargyloxy-phenylalanine (pPrF) (Combi-Blocks, catalog number: QW-3179)
L-4-amino-phenylalanine (4AmiF) (Peptech, catalog number: AL305)
L-4-aminomethyl-phenylalanine (4AmiMeF) (Peptech, catalog number: AL300)
L-benzenepentanoic acid, alpha-amino (BzpA) (Peptech, catalog number: AL514)
L-4-Nitro-phenylalanine (pNitroF) (Peptech, catalog number: AL061)
L-4-cyano-phenylalanine (pCNF) (Fisher Scientific, catalog number: AAH63572MD)
L-4-Fluoro-phenylalanine (pFF) (Peptech, catalog number: AL021)
L-4-Iodo-phenylalanine (pIF) (Peptech, catalog number: AL261)
L-4-Acetyl-phenylalanine (pAcF) (Peptech, catalog number: AL624)
L-4-methoxy-phenylalanine (4MeOF) (Alfa aesar, catalog number: H63096)
L-2-Naphthylalanine (NapA) (Peptech, catalog number: AL121)
L-bipyridyl-phenylalanine (biPyrA) (No longer commercially available)
L-4-tert-Butyl-tyrosine (tBut-Y) (Sigma-Aldrich, catalog number: 533130)
Additional Reagents
IPTG (Thermo ScientificTM, catalog number: FERR0392)
Glucose (Thermo ScientificTM, catalog number: AA1109036)
Glutamate (Acros Organics, catalog number: 156211000)
Ammonia sulfate (Sigma-Aldrich, catalog number: A4418)
Magnesium chloride, anhydrous (Sigma-Aldrich, catalog number: M8266)
Calcium chloride, dihydrate (Sigma-Aldrich, catalog number: 223506)
Manganese chloride (Sigma-Aldrich, catalog number: 416479)
Zinc chloride, anhydrous (Fisher Scientific, catalog number: AA1235722)
Thiamine-HCl (Sigma-Aldrich, catalog number: T1270)
Hydrochloric acid (10N) (RICCA Chemical Company, catalog number: 3770-32)
Iron (III) chloride, anhydrous (Fisher Scientific, catalog number: AAA1628122)
Potassium phosphate (monobasic) (Sigma-Aldrich, catalog number: P9791)
MOPS (free acid) (Fisher Scientific, TCI America, catalog number: M0707)
Chloramphenicol (Sigma-Aldrich, catalog number: C0378)
Kanamycin sulfate (Sigma-Aldrich, catalog number: K4000)
Phosphate buffered saline (tablet form) (Sigma-Aldrich, catalog number: P4417)
Sodium hydroxide (Acros Organics, catalog number: 134070010)
Media
LB Broth, Lennox (Fisher Scientific, Fisher BioReagentsTM, catalog number: BP9722500)
LB Agar, Lennox (Fisher Scientific, Fisher BioReagentsTM, catalog number: BP9745500)
S750 (1 L) (see Recipes)
ammoniaS750 (1 L) (see Recipes)
10× S750 salts (1 L) (see Recipes)
100× metals (500 mL) (see Recipes)
Equipment
Note: Equipment specifications are largely recommendations as this protocol has been validated for a series of different instruments.
-80 °C freezer
Incubator (Thermo Scientific, catalog number: 51-028-065HPM) or Shaking Incubator (Infors-HT Multitrons)
Microplate readers (protocol performed on both the Molecular Devices SpectraMax i3X or BioTek H1M Synergy)
Spectrophotometer (Thermo Scientific, catalog number: 840301000)
Plate shaker (Thermo Scientific, catalog number: 88882005)
Rotor drum (FisherBrand, catalog number: 14-251-251)
Pipettes (Fisher Scientific, Eppendorf Research Plus)
Pipettor (Fisher Scientific, Eppendorf EasyPet 3, catalog number: 12-654-105)
Vortex mixer (Scientific Industries, Inc. Vortex-Genie 2, catalog number: SI-0236)
Software
Excel
Software associated with plate reader used
Procedure
S750 protocol for tubes and 96-well plates
Remove glycerol stock that contains desired B. subtilis strain from -80 °C freezer. Streak cells from the glycerol stock onto an LB agar plate. Antibiotics may be useful for confirming strain identity but are not necessary as incorporation constructs are stable integrations. Incubate overnight at 37 °C. See Note 1 for essential controls that should be included in every experiment.
On the next day, pick desired colonies from the LB plate and transfer to 1 mL of S750 media in culture tubes. Mix vigorously by pipetting up and down to break up biofilms and promote suspension growth. These serve as the seed cultures for the experiment, without induction of heterologous gene expression. See Note 2 for optional media conditions.
Grow in a 37 °C shaking incubator or rotor drum for 4–6 h, to an OD between 0.2 and 0.7.
Prepare experimental media (which will serve to induce heterologous gene expression and nsAA incorporation) by adding the desired IPTG and nsAA to S750. IPTG final concentration is 1 mM, which is 1,000× of a 1 M stock solution. IPTG is typically added to all cultures including nsAA, except in the case of titration; for double titration see Figure 1. nsAA final concentration is usually 100 μM for most tyrosine-derived nsAAs. 1 mM should be used for boc-K, 5OHW, and CouAA. Similarly, other concentrations can be used for titration (see Figure 1 for an example). Different nsAAs will exhibit different titration dynamics due to the differences in binding to their cognate synthetases.
For a 96-well plate format, a suggested higher throughput strategy is to prepare the master mix media unique to each nsAA in 15 mL tubes, then transfer to reservoir and distribute 300 μL with a 1 mL multichannel into a 2 mL deep well plate. In our experience, culture volumes above 300 μL do not aerate well in the deep 96-well plate format. See Figure 2 for the suggested media layout.
For single culture tubes, use no more than 1 mL media per tube for aeration reasons.
Figure 1. Double titration with nsAAs and transcriptional inducers. A UAG-mNeongreen construct under the control of a pHyperspank promoter was expressed with variable levels of nsAA and IPTG; a very sensitive induction was possible with low levels of IPTG and titration of nsAA. The signal was normalized to a positive control construct, where a TAC tyrosine codon replaced the UAG stop codon and 1 mM IPTG was provided. For more details, see Data analysis.
Figure 2. Suggested plate layout for easy plate-filling. This plate layout is easy to set up with a multichannel pipette with minimal errors.
Measure OD of the seed cultures, then dilute them with additional S750 to start the experimental cultures at a theoretical density of 0.002 with desired cells.
For a 96-well plate setup, dilute cultures with S750 in a PCR tube to OD 0.2, then use a multichannel to distribute 3 μL across the plate as desired, to achieve a final OD of 0.002 in 300 μL of experimental media.
For single culture tubes, dilute media appropriately to final OD 0.002. For example, add 4 μL of OD 0.5 seed culture to 1 mL of S750 containing IPTG and nsAA.
Incubate tubes/plate overnight, shaking at 37 °C.
For 96-well deep well plates, cover with a breathable cover (see Note 4b). Example data are in Figure 3a.
For clear-bottomed shallow 96-well plates used in time courses, cover with a transparent breathable cover. Shaking should be set to a fast speed, though either orbital or double orbital can be used. Read OD600 and fluorescence every 5–10 min. For the mNeongreen reporter, reading at 488/530 is acceptable, though many different filter settings will work for mNeongreen. Example data in Figure 3b.
For single culture tubes, grow in a 37 °C shaking incubator or rotor drum.
Read endpoint data after overnight growth. Extensively long growth periods will see some decrease of signal, but anything between 14 and 24 h is usually adequate.
For fluorescence readout, dilute culture 1:1 with PBS, mix thoroughly, transfer 200 μL to clear-bottomed plates, and read OD and fluorescence. If the nsAA used is itself fluorescent, such as CouAA, spin down cells and wash them two to three times in PBS before resuspending in PBS for the plate reader experiment. If attempting microscopy, do washes in 1.5 mL tubes, carefully removing as much of the wash as possible in each case, and thoroughly resuspend pellets by pipetting. CouAA’s broad fluorescence spectrum grants very high background unless it is sufficiently washed out.
For nanoLuciferase readout, add 100 μL culture to a plate, take ODs, then add 100 μL of Nano-Glo luciferase reagent. The Nano-Glo will lyse cells, making OD measurements taken after addition unreliable.
Figure 3. nsAA incorporation data. (A) Endpoint data for nsAA incorporation, using different nsAAs for different AARSs: BipA for bipARS, pAzF for napARS, CouAA for CouRS, BpA for bpaRS, boc-K for the AbkRS. Data processed as discussed in Data Analysis. Biological triplicates were averaged; error bars represent the standard deviation. (B) Time courses for nsAA incorporation; shaded area is standard deviation among biological triplicates.
Variant for incorporation with ammoniaS750 (slower growth, less reliable, more accessible import)
When trying to do incorporation of nsAAs that do not import well into the cell (likely due to being large and hydrophobic), import may be improved by using media lacking competing amino acids, such as S750 where ammonia is the sole nitrogen source (see recipes for ammoniaS750).
Bacillus will grow in this media and incorporation will occur, but significantly more slowly. Replace both the seed culture and experimental media with ammoniaS750, and allocate roughly 50% more growth time, especially for the seed culture, which may take 6–8 h to reach a high enough OD for seeding (minimum OD is approximately 0.2).
Variant for incorporation with LB (less reliable, higher background, hindered cellular import)
Replace S750 LB starter culture and experimental cultures with LB.
Spin down cells and resuspend with PBS prior to measuring fluorescence. Cells do not need to be spun down for luminescence.
Data analysis
Data analysis of nsAA incorporation is straightforward, and results should be interpretable from raw data without manipulation, as shown in Figure 4. However, to achieve final data, follow the steps below. Also see Supplemental Excel file 1 for an example of data processing.
Average biological replicates of fluorescence/luminescence data from the WT controls without nsAA, then subtract 90% of that value from the fluorescence/luminescence values of all samples. Since low background synthetases without nsAA tend to produce very little observable background incorporation, if the full WT background is subtracted then the nsAA fluorescence values will often be negative. This complicates graphing and downstream data analysis, such as determination of fold-induction. Since the WT fluorescence is very low, the difference between 90% and 100% is extremely small—usually smaller than the standard deviation between the three WT biological replicates. This results in background-normalized incorporation data.
Subtract plate reader background OD (from reading blank media wells; it should be constant per given plate reader) from OD values. This can be anywhere between 0.001 and 0.04 for many plate readers. This results in normalized OD data. Note any especially low OD values and consider data from those wells suspect. Most nsAAs described here should not significantly hinder growth, except for 5OHW, which was observed to decrease final OD.
Divide background-normalized incorporation data by the normalized OD data. This results in OD-normalized incorporation data. Skip this step for time course analysis.
Divide all averages by OD-normalized fluorescence/luminescence data from the TAC positive control lacking a TAG stop codon. This results in final data as a fraction of protein expression without nsAA incorporation. See Figure 4 and Supplemental Excel file 1for examples.
Use standard deviation among three biological replicates to plot error bars.
Figure 4. Data analysis example. (A) Raw fluorescence data from plate reader, with no normalizations. (B) Data processed according to data normalization, with background subtracted, OD normalized, and normalized to maximum possible expression of a reporter lacking a UAG codon.
Notes
Always include WT B. subtilis (Py79) as a negative control and a TAC-reporter positive control strain to properly normalize experiment-to-experiment signal. The TAC-reporter positive control contains the sense codon TAC, which encodes tyrosine, instead of the nonsense codon TAG at the desired site of nsAA incorporation in the reporter protein. It provides a measure of how much protein expression would be expected if the rate of nsAA incorporation was not a limiting factor and normalizes data across experiments. These strains can be obtained through BGSC (see Materials and Reagents).
Adding inducer to the starter cultures is optional but not recommended, as it does not seem to have any effect on final signal. Antibiotic in the starter and experimental cultures is also optional but is unnecessary for stably integrated constructs and can slow growth. Be sure not to add antibiotic to WT controls.
Starter cultures
This protocol recommends starting cultures from colonies instead of freezer stocks. It is possible to start cultures from freezer stocks, but starter cultures grown this way grow unreliably and usually take longer to reach an appropriate OD. The same is true for cultures from old plates (>2–3 days). Both of these approaches can be used if needed but ensure that cells have at least gone through two doublings before starting experimental cultures from seed cultures.
Higher ODs than 0.7 do work for starter cultures, but results will not be as reliable.
Protocol Variants
The basic 300 μL S750 plate reader endpoint incorporation protocol is extremely reliable when performed correctly. When testing a new synthetase or nsAA, execute that protocol first to demonstrate that incorporation is working before attempting larger cultures, richer media, or other protocol variants.
Because of Bacillus’ need for aeration, it is better to shake 96-well plates overnight at 1,000 rpm with a 3 mm orbital volume. However, robust incorporation has been observed in 96-well plates with a standard incubator’s 250 rpm overnight shaking.
When attempting to purify protein-containing nsAA, the Gram-positive BugBuster kit was found to be very effective for purification of protein from stationary-phase Bacillus subtilis grown overnight in S750.
Background normalization
In general, it is not necessary to change background subtraction during data analysis based on OD. This is because B. subtilis in S750 has relatively low autofluorescence, and after overnight growth almost all cultures will have reached saturation.
However, other media, such as LB, will have higher autofluorescence and potentially more variable ODs. In these cases, it may be necessary to create a linear autofluorescence normalization curve, where several different cultures of WT Py79 at different ODs are measured, then plotted, and a linear autofluorescence curve created. That curve can then be used to subtract autofluorescence based on OD.
Recipes
S750 (1 L)
100 mL of 10× S750 salts
10 mL of 100× metals
10 mL of 1 M glutamate
20 mL of 50% glucose
860 mL of ddH2O
ammoniaS750 (1 L)
100 mL of 10× S750 salts
10 mL of 100× metals
20 mL of 10% w/v ammonia sulfate
20 mL of 50% glucose
850 mL of ddH2O
10× S750 salts (1 L)
104.7 g of MOPS (free acid)
13.2 g of ammonia sulfate, anhydrous
6.8 g of potassium phosphate monobasic, anhydrous
To 1 L with ddH2O
100× metals (500 mL)
100 mL of 1 M magnesium chloride
35 mL of 1 M calcium chloride
2.5 mL of 1 M manganese chloride
5 mL of 10 mM zinc chloride
25 mL of 2 mg/mL thiamine-HCl
1 mL of 1 M HCl
5 mL of 50 mM iron (III) chloride
326.5 mL of ddH2O
Acknowledgments
This work was supported by NSF collaborative research grants MCB-2027074 (to E.C.G.) and MCB-2027092 (to A.M.K.). M.A.J. was partially supported by funding from the Department of Education – Graduate Assistance in Areas of National Need (P200A210065) and from the National Institute of General Medical Sciences of the National Institutes of Health under a Chemistry-Biology Interface Training Grant (T32GM133395).
This protocol is adapted from Stork et al. (2021).
Competing interests
The authors declare the following competing interests: A.M.K. has related financial interests in Nitro Biosciences.
References
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Analysis of Lipid-linked Oligosaccharides Synthesized in vivo in Schizosaccharomyces pombe
AV Ayelen Valko *
GG Giovanna L. Gallo *
AW Ariel D. Weisz
AP Armando J. Parodi
CD Cecilia D’Alessio
(*contributed equally to this work)
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4508 Views: 804
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Original Research Article:
The authors used this protocol in Journal of Cell Science Mar 2022
Abstract
Dolichol diphosphate-linked oligosaccharides (LLO) are the sugar donors in N-glycosylation, a fundamental protein post-translational modification of the eukaryotic secretory pathway. Defects in LLO biosynthesis produce human Congenital Disorders of Glycosylation Type I. The synthesis of LLOs and the transfer reactions to their protein acceptors is highly conserved among animal, plant, and fungi kingdoms, making the fission yeast Schizosaccharomyces pombe a suitable model to study these processes. Here, we present a protocol to determine the LLO patterns produced in vivo by S. pombe cells that may be easily adapted to other cell types. First, exponentially growing cultures are labeled with a pulse of [14C]-glucose. LLOs are then purified by successive extractions with organic solvents, and glycans are separated from the lipid moieties in mild acid hydrolysis and a new solvent extraction. The purified glycans are then run on paper chromatography. We use a deconvolution process to adjust the profile obtained to the minimal number of Gaussian functions needed to fit the data and determine the proportion of each species with respect to total glycan species present in the cell. The method we provide here might be used without any expensive or specialized equipment. The deconvolution process described here might also be useful to analyze species in non-completely resolved chromatograms.
Graphical abstract:
Workflow for the labeling, extraction, separation, and identification of LLO species in S. pombe. (A) Radioactive pulse of S. pombe cells with [14C]-glucose for 15 min at 28 °C. (B) Organic extraction of LLOs from labeled yeasts sequentially using methanol, chloroform, H2O, chloroform:methanol:H2O (1:1:0.3), 0.02 M HCl (to separate glycans from dolichol), and chloroform:methanol:H2O (1:16:16). (C) Preparation of the sample for chromatography on paper: drying by airflow and radioactivity check. (D) Loading of samples in chromatographic paper and descendent chromatography in a glass chamber. The obtained plots (CPM versus running distance) need to be analyzed to identify single glycan species.
Keywords: Chromatogram deconvolution Endoplasmic reticulum Lipid-linked oligosaccharide Metabolic labeling Schizosaccharomyces pombe Yeast N-glycosylation
Background
N-glycosylation is a frequent post-translational modification in the secretory pathway of eukaryotic cells involved in glycoprotein folding in the endoplasmic reticulum (ER). During N-glycosylation, a glycan composed of three glucoses (Glc), nine mannoses (Man), and two N-acetyl glucosamines (G3M9) is transferred in a single reaction step from a dolichol diphosphate oligosaccharide (LLO) donor to a consensus sequence present in proteins entering the ER (Cali et al., 2008). The reaction is catalyzed by the oligosaccharyltransferase (OST), which discriminates among completed and non-completed LLOs. The LLOs are synthesized stepwise in the ER membrane by different ALG gene products, first in the cytosolic side and then in the luminal side of the ER membrane (Figure 1) (Aebi, 2013; Stanley et al., 2015). Defects in LLOs synthesis result in their poor recognition by OST and thus less efficient transfer to proteins, leaving empty some normally occupied N-glycosylation sites. This hypoglycosylation of proteins may have profound effects in the cell and lead to several different Congenital Disorders of Glycosylation (CDG) type I (Ondruskova et al., 2021). These diseases are difficult to diagnose. The first confirmation usually arrives when hypoglycosylation is observed in serum transferrin, and a defect in LLO synthesis is assumed. To know which ALG genes are defective in each patient, either the biochemical analysis of LLO or a whole exome sequencing are required (Chang et al., 2018; Ng and Freeze, 2018; Wilson and Matthijs, 2021). The core machinery of LLO synthesis and N-glycosylation is highly conserved among eukaryotic species (Aebi, 2013), particularly between the fission yeast Schizosaccharomyces pombe and mammals (Fernandez et al., 1994). S. pombe is easily handled, facilities required for its growth and maintenance are inexpensive, and many biochemical and genetic tools are already developed for this organism. For these reasons, S. pombe has become a suitable model organism for research, and several molecular tools developed and optimized for use in this model organism have been used in mammalian cells (Hagan, 2016).
We present here a detailed protocol to specifically identify the LLO species synthesized in S. pombe in vivo. The key step of the protocol is to stop protein synthesis with inhibitors preventing glycan transfer to proteins while radioactive labeled LLOs are being synthesized. Cultures are compared under similar nutritional growth conditions, in order to avoid differences in LLO structures due to environmental conditions or metabolic constraints (Gershman and Robbins, 1981; Chapman and Calhoun, 1988). We then extract LLOs from the labeled cells and analyze them either by HPLC or by paper chromatography. To better identify the peaks obtained, we developed a deconvolution process using a Gaussian function available in a Microsoft Excel Solver datasheet provided here. This method allows a better visualization of the peaks, making them easily comparable with the standards run in parallel, and provides an accurate quantification of each peak. With the protocol described here, we were able to distinguish the LLOs produced in 16 S. pombe strains that synthesize combinatorial possible structures of LLOs (GXMY, where X is the number of Glc residues in the glycan, ranging from three to zero, and Y is the number of Man units, ranging from nine to five) (Gallo et al., 2022). This low-cost method has the advantages of being readily available for almost all laboratories, providing high accuracy, and being easily adapted to any cell type, simplifying the determination of the LLO biosynthetic step blocked in a particular cell mutant or synthesized by the organism being studied. Moreover, the method we provide to obtain the deconvolution of the LLO profiles may be used for other chromatographic resolutions.
Figure 1. Synthesis of LLOs and glycan transfer to nascent proteins in the ER. The G3M9 LLO is built in the ER membrane step-by-step by monosaccharide addition mediated by specific glycosyltransferases encoded by alg (asparagine-linked glycosylation) genes. Two N-acetylglucosamines and five Man are transferred to the dolichol from nucleotide-sugars on the cytoplasmic side of the ER membrane. Then, the LLO intermediate bearing five Man residues is flipped to the ER lumen, where four additional Man residues are added by the ALG3-, ALG9-, and ALG12-encoded ER luminal dolichol-dependent mannosyltransferases. Finally, three Glc residues are incorporated by the ALG6-, ALG8-, and ALG10-encoded dolichol-dependent glucosyltransferases. Once completed, the LLO is transferred by OST to nascent polypeptides entering the ER through the translocon.
Materials and Reagents
Materials
Conical tubes, 50 mL (Biologix, catalog number: 10-9502)
Polypropylene centrifuge bottle with Screw-On Cap, 250 mL (Beckman Coulter, catalog number: 356011)
Polypropylene centrifuge bottle with Screw-On Cap, 50 mL (Beckman Coulter, catalog number: 357003)
Metal spatula
Glass beads 0.5 mm diameter (Millipore Sigma, Sigma, catalog number: G8772)
Glass tubes (Kimax, catalog number: 45048)
Glass eyedropper
Chromatography paper sheets (Sartorius Stedim FN3 580 × 600 mm)
Scintillation 20 mL glass counting vials (Wheaton, catalog number: 986532)
Reagents
Yeast extract (BactoTM, catalog number: 212750), store at room temperature (RT)
Adenine (Millipore Sigma, Sigma, catalog number: A8626), store at RT
Yeast nitrogen base (YNB) (Thermo Fisher Scientific, BD Difco, catalog number: DF0392-15-9), store at RT
Puromycin 10 mg/mL (InvivoGen, catalog number: ant-pr-1), store at 4 °C
Cycloheximide 2 mg/mL (Millipore Sigma, catalog number: C-6255), store at -20 °C
D-[14C(U)]-Glc (Perkin Elmer, catalog number: NEC042V20UC), store at 4 °C
Glucose 1 M (Dextrose 1-hydrate, Biopack, catalog number: 9812.08), store at RT
Methanol 99.9% (Millipore Sigma, Merck, catalog number: 106009), store at RT
Chloroform (Merck, catalog number: 107024), store at RT
1-propanol 98% (Millipore Sigma, Merk, catalog number: 100997), store at RT
Nitromethane (Millipore Sigma, catalog number: 270423), store at RT
Hydrochloric acid fuming 37% for analysis (Merck, catalog number: 1003171000)
PPO-POPOP scintillation cocktail (concentrated scintillator PPO-POPOP, RPI, catalog number: 111045)
Milli Q water
Yeast extract medium supplemented with adenine (YEA) (see Recipes)
Yeast nitrogen base (YNB) without glucose (see Recipes)
Radioactive solution to label a 500 μL sample (see Recipes)
Chloroform:methanol:water (1:1:0.3) (see Recipes)
Chloroform:methanol:water (1:16:16) (see Recipes)
0.02 N HCl (see Recipes)
Equipment
1 L glass flask
Orbital shaker (for flasks) set at 28 °C (Forma Scientific, model: 4581)
OD600 reader (Amersham Biosciences, model: Ultraspec 10)
Centrifuge (Beckman Avanti) with rotors JA-14 and JA-20
Thermomixer set at 28 °C (Thermo-shaker, mrc)
Water bath (Vicking SRL)
Airflow (Aquarium air pump RS-Electric, model: RS-15000)
Analog benchtop centrifuge (Rolco)
Vortex (Scientific Industries, model: Vortex-genie 2)
Freezer -20 °C (KENT)
Glass chromatography chamber (Homemade)
Scintillation counter (Pharmacia, RackBeta 1214/1219)
NOTE: The equipment described here may easily be replaced for common lab equipment of other brands.
Software
Microsoft Excel (version 2016) (Microsoft.com)
Procedure
In vivo labeling of LLOs
Harvesting S. pombe cells (4 h)
Inoculate a 50 mL Falcon tube containing 5 mL of sterile YEA medium with an isolated colony of the desired S. pombe strain. Grow overnight at 28 °C and 250 rpm in an orbital shaker.
The following morning inoculate 250 mL of sterile YEA in a 1 L glass flask with 1 mL of the overnight S. pombe culture.
Grow at 28 °C and 250 rpm until reaching the exponential growth phase (OD = 1–1.5). The time may vary depending on the strain.
Centrifuge 200 mL of the grown culture in 250 mL centrifuge bottles at 3,000 × g and 4 °C for 5 min.
Discard the supernatant.
Resuspend the pellet in 30 mL of cold 1% YNB. In this step, it is convenient to first resuspend the cells in 10 mL of ice-cold YNB using a 10 mL glass pipette and a pipette aid, and then add the remaining 20 mL.
Transfer the 30 mL sample to a 50 mL centrifuge bottle tube previously weighed. Keep it on ice. Weighing the tubes will be important later to calculate the wet mass of cells.
Centrifuge at 3,000 × g and 4 °C for 5 min and discard the supernatant.
Resuspend the pellet in 30 mL of YNB as described in step A6 and centrifuge as in step A8.
Discard the supernatant. Remove the remaining drops by placing the tube face down over a tissue paper.
Wash the pellet again with YNB by repeating steps A9–A10.
Weigh the tube with the pellet and calculate the wet mass of cells by subtracting the weight of each empty tube. Add two volumes of cold YNB per gram of cells (v/w). If you have 0.5 g of wet weight, you should add 1 mL of media. Resuspend cells with a pipette.
Take 500 μL of the cell suspension and place it into a new 50 mL centrifuge bottle, where the labeling will be performed.
Preparing reagents for radioactive pulse (15–30 min)
Add 200 μCi of [14C]-glucose per sample in a glass tube within a chemical hood and dry by exposure to a constant airflow at room temperature. Follow the approved procedures to manipulate radioactive liquids in your institution.
Once dried, solubilize the radioactive material in 50 μL of YNB containing 50 mM Glc (see Recipe 3).
Yeast cells labeling (20 min)
Add the protein synthesis inhibitors puromycin and cycloheximide to the 500 μL cell suspension from step A13 to reach final concentrations of 50 μg/mL and 70 μg/mL, respectively. Incubate tubes for 2 min at 28 °C.
Add the entire radioactive solution to the cell suspension. Incubate the sample at 28 °C for 15 min at 200 rpm using a thermomixer.
Stop the pulse by transferring all the cells to a glass tube containing 5 mL methanol.
Extraction of LLOs
Notes:
This step will take 6 h the first day and 4 h the next day if the protocol is interrupted at step 19; alternatively, 10 h if it is entirely performed on the same day.
Extraction of LLOs follows the following rationale: these compounds have both large hydrophilic and hydrophobic moieties. Thus, they are insoluble in solvents as chloroform:methanol (3:2), which is poorly hydrophilic but able to solubilize phospholipids, or in methanol or water, which are poorly hydrophobic but able to solubilize water-soluble metabolites. On the contrary, chloroform:methanol:water (1:1:0.3) is a single-phase solvent that displays both hydrophilic and hydrophobic features and thus is able to extract dolichol-linked oligosaccharides.
Centrifuge the glass tube at 2,000 × g for 3 min at room temperature and discard the supernatant carefully.
Notes:
All the following centrifugation steps of Procedure D should be performed under these same conditions.
Follow institutional rules to discard radioactive material.
Add 5 mL of chloroform:methanol (3:2) and resuspend the pellet completely by vortexing. This pellet is particularly tough to resuspend. To do so, it is convenient to place a small spatula in the tube at the moment of vortexing. The spatula must be actively kept inside the tube during the shaking of the sample. Remove the spatula from the tube after the pellet has been resuspended and leave it in a large beaker containing water until next use.
Repeat steps D1–D2 twice, completing three total extractions with chloroform:methanol (3:2).
Add 5 mL of methanol and resuspend the pellet as in step D2.
Centrifuge and discard the supernatant.
Finally, add 5 mL of Milli Q water and resuspend the pellet by vortexing, using the spatula to help.
Centrifuge and discard the supernatant.
Resuspend cells in 2 mL of ice-cold water and 0.5–1 mL of glass beads.
Vortex the sample for 10 min. Stop the vortexing every 1 min to put the sample on ice for 1 min and thus avoiding overheating.
Centrifuge.
Add Milli Q water to complete a volume of 5 mL.
Centrifuge and carefully discard the supernatant using an eyedropper.
Repeat four more times the water extraction steps D11–D12.
Add 5 mL of chloroform:methanol:water (1:1:0.3) and resuspend the pellet vigorously by vortexing.
Centrifuge.
Note: After centrifugation, it is common to see two phases in the supernatant instead of one. If this is the case, use an eyedropper to carefully add methanol drop by drop until observing just one phase.
Collect the supernatant in a new glass tube and start drying the sample using an airflow at room temperature. It is possible to accelerate the process by drying the supernatant at higher temperatures, placing the tube in a water bath under the air flow, without exceeding 40 °C (see Figure 2).
Figure 2. Schematic representation of the water bath and the adapted airflow used for drying samples. A commercial air pump for fish tanks was employed to supply airflow.
In parallel, add 5 mL of chloroform:methanol:water (1:1:0.3) to the remaining pellet obtained in step D15 and mix it by vortexing. Centrifuge.
Collect this new supernatant using an eyedropper and pool it with the supernatant obtained in step D15 while it is being dried.
Repeat steps D16–D17 three more times. At the end of this extraction step, all the collected supernatants from a single sample will be pooled and dried in the same tube. If desired, it is possible to keep this final dried sample at -20 °C overnight and continue with the remaining steps the following day.
Add 1 mL of 0.02 M HCl to the dried extract and boil the sample for 15 min in a water bath. If the sample was frozen, leave at room temperature 5 min before boiling to avoid the fracture of the glass tube by temperature contrast.
Note: The acid hydrolysis step is necessary to separate glycans from dolichol moieties.
Put the boiled samples back at room temperature and wait for them to cool down.
Add sequentially 3 mL of chloroform and 2 mL of methanol to each sample and mix by vortexing.
Centrifuge.
After step D23, two phases will be formed. Recover the upper phase (water phase) in a new glass tube using an eyedropper whose tip has previously been bent upwards to avoid collecting any lower phase. Remove the water phase slowly and carefully, to avoid mixing the phases.
Start the drying of the water phase by exposure to a constant airflow at room temperature.
Wash the remaining lower phase by adding 1 mL of chloroform:methanol:water (1:16:16) previously prepared and centrifuge.
Collect once again the upper phase using an eyedropper with the bent tip and pool it with the previous water phase while it is being dried. Wait for the pooled samples to dry completely. It is possible to pause the protocol here by keeping the dried sample at -20 °C.
Chromatography (72–82 h)
Resuspend the dried sample in 52 μL of Milli Q water at room temperature.
Check if the sample has been properly labeled with the radioactive reagents by measuring a 2 μL aliquot in a counting vial and adding 1 mL of scintillation liquid. Measure the radioactivity using a scintillation counter. Check that the aliquot has more than 200–300 CPM.
Note: From this step, you may choose to analyze the samples by paper chromatography (protocol provided here) or by HPLC, as described in Stigliano et al. (2011).
Load the remaining 50 μL of the sample drop by drop on a chromatographic paper, as shown in Figure 3. Let the sample dry there before placing the paper within the chromatography chamber.
Run the sample by descending chromatography using 1-propanol:nitromethane:water (5:2:4). Approximately 50 mL of 1-propanol:nitromethane:water should be added to the chamber that holds the top of the paper (see Figure 3). Importantly, the run must be monitored at least once per day in order to prevent paper dryness. If required, add more solvent to the chamber. It is important to run in parallel (same paper) radioactive standards, as they will be used to identify the glycan species behind each peak (Figure 3). These standards can be obtained from a labeled chicken oviduct, as previously described by Parodi et al. (1981), or by purifying N-glycans from S. pombe strains of already known structures, as described in Fernandez et al. (1994). Once you perform this protocol and clearly identify the identity of pure peaks, you may also use those LLOs as standards. At 25 °C, a running time between 70 and 80 h would provide an optimal separation of the standard peaks, depending on the glycan species. To monitor the velocity of the chromatography, an additional standard sample can be run in parallel, on a different piece of chromatographic paper (external standard). Thus, this paper can be processed separately to obtain the position of the reference peaks at time 48 h and, based on that, decide when to stop the main running.
Figure 3. Design of the chromatography paper and loading the sample. (A) Recommended layout for chromatographic paper. In this case, four running trails were drawn. At least one of these trails should be used to run in parallel an internal standard sample composed of known labeled glycan species. (B) Indication of how the chromatographic paper should be folded before hanging it in the chromatographic chamber. (C) A detail of the area where the sample should be loaded in each trail is highlighted in yellow. (D) Illustrative picture showing how to load the sample into the paper. (E) Schematic illustration of the chromatographic chamber and the chromatographic paper hung inside.
Remove the paper from the chromatography chamber, air dry it, and then cut each lane in 4 cm × 1 cm fractions. Place each fraction in counting vials and add 0.5 mL of scintillation liquid. It is not necessary for the liquid to cover the paper as it gets embedded.
Quantify the radioactive signal from each tube using a scintillation counter with a program for 14C radiation.
Data analysis
To obtain the radioactive profile of the LLO species, plot the intensity of the signal (counts per minute, CPM) versus the running length (cm) in the Excel sheet included in the following link. Figure 4A shows, as an example, representative chromatograms obtained for wildtype and Δalg8/Δalg12 S. pombe mutant strains (Gallo et al., 2022). LLOs patterns are measured in standardized conditions (see Procedure A–C of the protocol) that must be employed consistently across all experiments. Thus, as these patterns depend almost entirely on the genotype of the tested strains, the technique described here (which processes an enormous number of cells simultaneously) leads to robust and solid results, with a high level of reproducibility from replicate to replicate, and among different laboratories. Nevertheless, performing at least two independent replicates is required.
Figure 4. Representative profiles of labeled samples (A) before and (B) after deconvolution. LLO glycan patterns found in the S. pombe wildtype strain and Δalg8/Δalg12 mutant strain. In the wildtype strain, one single peak (G3M9) can be recognized, whilst in the mutant strain two not well resolved peaks (that belong to G1M7 and M7, respectively) were found. The running distance of a labeled mix of N-glycan composed by G3M9, M9, M8, M7, M6, and M5 is shown above the profiles.
Quantify the proportion of each species within a sample by a deconvolution process using a Gaussian fit applied to the obtained chromatographic profile.
Note: The data analysis strategy is to combine one or more Gaussian functions to perform a non-linear fitting of the measured profile. The included Excel sheet ‘DeconvolutionDataSheet.xlsx ’ implements the fit of up to seven independent Gaussian functions on the same profile. The procedure follows a least square fitting criterion for optimization.
Load the obtained profile in the Excel sheet as a list of Running length (cm) and Counts (CPM) paired data (cells from A12 to B61) (see Figure 5).
Figure 5. Excel Datasheet required to perform data analysis. The Excel sheet shows the number of peaks and their parameters (upper left), the data (bottom left), the plot of unprocessed data (upper right), and the processed data (bottom right). Note that a new sheet must be used for each strain.
Enable one or more Gaussian functions to fit the measured profile, setting the value ‘1’ in row 7 from columns D to J. Set the value of ‘0’ to disable.
Notes:
Each column from D to J corresponds to an independent Gaussian function.
Calculate Gaussian function values as:
Set the baseline value in cell D2 to the minimum value measured in Counts.
Note: Use a constant value as baseline in order to subtract the base signal if needed.
For each enabled function (columns D to J), set approximated values for each peak height, center, and width (rows 3–5). Use the plot on the right as a visual aid for guessing the initial parameters as close as possible to the expected result.
Sum up the baseline and all the enabled Gaussian functions for each data point (cells C12–C61).
Note: Calculate the optimization function (in cell C2) as follows:
where
Open from the Excel menu the Data/Solver.
Complete the solver parameters as follows:
Target: $C$2
To: Min
Changing cells (you must define here the range of parameters you want to use in the fitting optimization)
Method: GRG Nonlinear
Number of fitted Gaussian functions Changing cells, solver parameter
1 $D$2;$D$3:$D$5
2 $D$2;$D$3:$E$5
3 $D$2;$D$3:$F$5
4 $D$2;$D$3:$G$5
5 $D$2;$D$3:$H$5
6 $D$2;$D$3:$I$5
7 $D$2;$D$3:$J$5
Press Resolve button and wait for execution. Then, accept to keep the Solver solution.
Read the proportional area for each band from row 8, columns D–J.
Note: Calculate the area of each band from the adjusted parameters as:
Compare the profiles of duplicates and perform an average of each species in each strain.
Formulas definitions or references:
G: Value of the Gaussian function
Height: Fitting parameter indicating the maximum CPM of the peak
RL: Experimental chromatographic running length in cm
Center: Fitting parameter indicating the position of the peak maximum in cm
Width: Fitting parameter associated to the broadness of the peak in cm
𝜖: Function used by Solver to achieve the fitting
Cpm: Experimental measurement for each RL in CPM
Area: Relative quantification of the identified band
Notes
There is a limit for this deconvolution procedure to distinguish between overlapping bands.
Decreased spatial resolution may affect results.
Recipes
Yeast extract medium supplemented with adenine (YEA)
Reagent Final concentration Amount
Yeast extract 5 g/L 5 g
Glucose 30 g/L 30 g
Adenine 75 mg/L 75 mg
H2O n/a Complete to 1 L
Total n/a 1,000 mL
Autoclave for 20 min at 120 °C
Yeast nitrogen base (YNB) without glucose
Reagent Final concentration Amount
YNB 1% 10 g
H2O n/a Complete to 1 L
Total n/a 1,000 mL
Autoclave for 20 min at 120 °C
Radioactive solution to label a 500 μL sample
Reagent Final concentration Amount
[14C]-glucose 200 μCi 200 μL. Dry completely
Glucose (1 M) 50 mM 2.5 μL
1% YNB n/a 50 μL
Total n/a 50 μL
Chloroform:methanol:water (1:1:0.3)
Reagent Final concentration Amount
Chloroform n/a 435 mL
Methanol n/a 435 mL
H2O n/a 130 mL
Total n/a 1,000 mL
Chloroform:methanol:water (1:16:16)
Reagent Final concentration Amount
Chloroform n/a 30 mL
Methanol n/a 485 mL
H2O n/a 485 mL
Total n/a 1,000 mL
0.02 N HCl
Reagent Final concentration Amount
Hydrochloric acid 37% (fuming) 0.02 N 0.83 mL
H2O n/a Complete to 500 mL*
Total n/a 500 mL
*Note: Never add water to the acid. Place some distilled water in a volumetric flask, add fuming HCl, and then add water up to 500 mL.
Acknowledgments
This work was supported by the Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT, Argentina) [PICT2017-1076 to C.D’.] and the National Research Council (CONICET, Argentina) [PIP-11220150100759 to C.D]. C.D. is a Career Investigator of the National Research Council (CONICET, Argentina). A.V. and G.L.G. are CONICET fellows. This protocol derives from the original paper (Gallo et al., 2022).
Competing interests
The authors declare no competing interests.
References
Aebi, M. (2013). N-linked protein glycosylation in the ER. Biochim Biophys Acta 1833(11): 2430-2437.
Cali, T., Vanoni, O. and Molinari, M. (2008). The endoplasmic reticulum crossroads for newly synthesized polypeptide chains. Prog Mol Biol Transl Sci 83: 135-179.
Chang, I. J., He, M. and Lam, C. T. (2018). Congenital disorders of glycosylation. Ann Transl Med 6(24): 477.
Chapman, A. E. and Calhoun, J. C. t. (1988). Effects of glucose starvation and puromycin treatment on lipid-linked oligosaccharide precursors and biosynthetic enzymes in Chinese hamster ovary cells in vivo and in vitro. Arch Biochem Biophys 260(1): 320-333.
Fernandez, F. S., Trombetta, S. E., Hellman, U. and Parodi, A. J. (1994). Purification to homogeneity of UDP-glucose:glycoprotein glucosyltransferase from Schizosaccharomyces pombe and apparent absence of the enzyme from Saccharomyces cerevisiae. J Biol Chem 269(48): 30701-30706.
Gallo, G. L., Valko, A., Herrera Aguilar, N., Weisz, A. D. and D'Alessio, C. (2022). A novel fission yeast platform to model N-glycosylation and the bases of congenital disorders of glycosylation type I. J Cell Sci 135(5).
Gershman, H. and Robbins, P. W. (1981). Transitory effects of glucose starvation on the synthesis of dolichol-linked oligosaccharides in mammalian cells. J Biol Chem 256(15): 7774-7780.
Hagan, I. M. C., A. M.; Grallert, A.; Nurse. P. (2016). Fission Yeast: A laboratory manual. Cold Spring Harbor Laboratory Press. ISBN: 978-1-621820-82-6.
Ng, B. G. and Freeze, H. H. (2018). Perspectives on Glycosylation and Its Congenital Disorders. Trends Genet 34(6): 466-476.
Ondruskova, N., Cechova, A., Hansikova, H., Honzik, T. and Jaeken, J. (2021). Congenital disorders of glycosylation: Still "hot" in 2020. Biochim Biophys Acta Gen Subj 1865(1): 129751.
Parodi, A. J., Quesada Allue, L. A. and Cazzulo, J. J. (1981). Pathway of protein glycosylation in the trypanosomatid Crithidia fasciculata. Proc Natl Acad Sci U S A 78(10): 6201-6205.
Stanley, P., Taniguchi, N. and Aebi, M. (2015). In: N-Glycans. rd, Varki, A., Cummings, R. D., Esko, J. D., Stanley, P., Hart, G. W., Aebi, M., Darvill, A. G., Kinoshita, T., Packer, N. H., et al. (Eds.) Essentials of Glycobiology. 99-111.
Stigliano, I. D., Alculumbre, S. G., Labriola, C. A., Parodi, A. J. and D'Alessio, C. (2011). Glucosidase II and N-glycan mannose content regulate the half-lives of monoglucosylated species in vivo. Mol Biol Cell 22(11): 1810-1823.
Wilson, M. P. and Matthijs, G. (2021). The evolving genetic landscape of congenital disorders of glycosylation. Biochim Biophys Acta Gen Subj 1865(11): 129976.
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Feb 2022
Abstract
Cancer cells often overexpress glutaminase enzymes, in particular glutaminase C (GAC). GAC resides in the mitochondria and catalyzes the hydrolysis of glutamine to glutamate. High levels of GAC have been observed in aggressive cancers and the inhibition of its enzymatic activity has been shown to reduce their growth and survival. Numerous GAC inhibitors have been reported, the most heavily investigated being a class of compounds derived from the small molecule BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide). X-ray structure determination under cryo-cooled conditions showed that the binding contacts for the different inhibitors were largely conserved despite their varying potencies. However, using the emerging technique serial room temperature crystallography, we were able to observe clear differences between the binding conformations of inhibitors. Here, we describe a step-by-step protocol for crystal handling, data collection, and data processing of GAC in complex with allosteric inhibitors using serial room temperature crystallography.
Graphical abstract:
Workflow for serial room temperature crystallography. Diagram showing the processing and scaling routine for crystals analyzed using serial room temperature crystallography.
Keywords: Glutaminase GAC Glutamine metabolism BPTES Serial crystallography
Background
We solved a number of X-ray crystal structures of glutaminase C (GAC) bound to different BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide)-class allosteric inhibitors under cryogenic crystallographic conditions (Huang et al., 2018; Milano et al., 2022). Although they vary in potency for GAC, the structures show that the contacts between the small molecule inhibitors and GAC are largely conserved. In order to visualize differences at the binding interface between GAC and the inhibitors, we employed fixed-target serial room temperature synchrotron crystallography (Wierman et al., 2019; Milano et al., 2022). An advantage of using serial room temperature X-ray crystallography is to help overcome any cryo-induced structural biases, such as “trapping” the protein/ligand in a distinct conformation as a result from crystal freezing. Although this technique requires substantially more crystals than cryogenic crystallography due to radiation damage to the sample, it can yield structures that are more dynamic and fluid. Consequently, structures solved using room temperature X-ray crystallography are capable of revealing differences in proteins and protein/ligand complexes that perhaps are more physiologically relevant. We recently used this technique to solve the structure of apo GAC (Illava et al., 2021). We hypothesized that structures of the GAC/inhibitor complexes at room temperature would make it possible to visualize subtle changes in the binding characteristics of the small molecules that were not evident from the low-temperature cryo-structures. Indeed, we were able for the first time to observe clear structural differences in the binding poses between two allosteric inhibitors of widely different potencies in the GAC/inhibitor complexes solved at room temperature. Here, we describe a detailed protocol for crystal handling, data collection, and data processing when employing serial room temperature crystallography (Figure 1).
Materials and Reagents
Pipette tips (USA Scientific, TipOne, catalog number: 1111-3700)
GAC/inhibitor crystals (room temperature)
Equipment
Forceps (Fisher Scientific, catalog number: 09-753-50)
Micro tools set (Hampton Research, catalog number: HR4-811)
Pipettes (Rainin, catalog number: 17008649)
Light microscope (Olympus)
Hex key
Crystallography sample supports (MiTeGen)
Sample loading box: humidity controlled and includes optical microscope
Sample loading station: connected to a vacuum pump (controlled by a foot pedal) for sample wicking
Sample supports: include a frame containing the support film and a goniometer base
Sample Mylar seals
Software
XDS Package (https://xds.mr.mpg.de)
CCP4 Program Suite (https://www.ccp4.ac.uk)
Filtering program cut_XDS and script to run it cut_XS.csh (https://www.chess.cornell.edu/macchess/mx/mx_software)
Procedure
Handling and loading of GAC/inhibitor crystals (Figure 2)
All crystals are grown in 24-well plates at room temperature using the hanging drop vapor diffusion method. Crystals are handled in a humidity-controlled environment to help prevent crystal dehydration.
Assemble sample support by inserting the frame into the goniometer base and tighten with a hex key.
Remove a coverslip containing GAC crystals from one of the wells of the crystal tray.
Under the microscope and using the micro tools, pick up crystals and place them onto the film of the sample support. The landscape of the film enables the crystals to settle in random orientations, maximizing data collection. Pre-wet the film with well solution if necessary. The crystals can lie anywhere on the film.
After 20 or more crystals (100 × 100 × 100 μM3 in size) are on the film, transfer the sample support into the loading box and place on sample loading station.
Looking through the optical scope, use the foot-pedal controlled vacuum to wick away excess liquid on the sample film.
Remove the white covering around the sample frame (on both sides) to expose the adhesive gasket.
Apply the Mylar sealing film on both sides of the frame to cover and protect the crystals from drying.
The completed sample support containing the crystals is now ready to be mounted in the beamline hutch and exposed to X-rays.
Figure 2. Serial room temperature crystallography sample handling system. (A) Sample support containing a thin film within a rectangular frame mounted into a goniometer base. The frame is surrounded by an adhesive gasket protected by a white covering. (B) Humidity-controlled sample loading box containing an optical microscope. (C) Sample loading station that connects to a vacuum pump for liquid wicking. (D) GAC crystals on the film of the sample support.
Data collection and processing
Data were collected at the Cornell High Energy Synchrotron Source (CHESS) at Cornell University on beamline ID7B2 (FlexX).
Sample supports containing GAC crystals are mounted in the beamline hutch on a goniometer and raster scanned in 20 μm steps, recording 5° of oscillation at each position.
Each step of the raster scanning is completed in 0.75–0.5 s, with 0.25 s for data acquisition (25 frames, 0.2°, and 10 ms/frame), corresponding to a 1.3 Hz raster rate.
Individual oscillation frame sets are processed with XDS (processing indicated that GAC crystallized in both orthorhombic and monoclinic crystal forms. Overall, the monoclinic crystal form produced the best data quality for GAC. We selected for this polymorph by filtering the data based on unit cell dimensions and angles in XDS and reprocessed the datasets).
The data are then scaled using XSCALE (part of the XDS software package).
Datasets that poorly agree with each other are removed through filtering methods.
For GAC, data is filtered based on agreement of each 25-frame set with the entire set for a support, using a script (cut_XS.csh) to remove discrepant sets (with the program cut_XDS) and rescaled (with XSCALE). R-factors on intensities between an individual set and the average of all sets were used for filtering discrepant data.
Lists of the accepted 25-frame sets from the different sample supports are then combined using a text editor such as gedit, producing a control file for XSCALE.
XSCALE is then used with this control file to rescale the combined data to generate a merged dataset.
The merged dataset can be further filtered, as in step 6, with various values of the parameter (R-factor) defining discrepant data. The datasets are filtered in order to achieve satisfactory data completeness and statistical values.
Using CCP4 programs pointless, aimless, and ctruncate, the merged dataset is then converted into an mtz file for structure determination.
Acknowledgments
This work was supported by grants to R.A.C. (GM122575, CA201402), L.A.M. [University of Pittsburgh Medical Center Competitive Medical Research Fund (CMRF)], and to CHEXS (DMR-1829070), and MacCHESS (P30GM126166). We also thank MiTeGen for supplying key resources for the serial room temperature X-ray crystallography experiments. Parts of this protocol were adapted from previously described methods (Illava et al., 2021; Milano et al., 2022).
Competing interests
The authors declare that they have no conflicts of interest with the contents of this article.
References
Huang, Q., Stalnecker, C., Zhang, C., McDermott, L. A., Iyer, P., O'Neill, J., Reimer, S., Cerione, R. A. and Katt, W. P. (2018). Characterization of the interactions of potent allosteric inhibitors with glutaminase C, a key enzyme in cancer cell glutamine metabolism. J Biol Chem 293(10): 3535-3545.
Milano, S. K., Huang, Q., Nguyen, T. T., Ramachandran, S., Finke, A., Kriksunov, I., Schuller, D. J., Szebenyi, D. M., Arenholz, E., McDermott, L. A., et al. (2022). New insights into the molecular mechanisms of glutaminase C inhibitors in cancer cells using serial room temperature crystallography. J Biol Chem 298(2): 101535.
Wierman, J. L., Pare-Labrosse, O., Sarracini, A., Besaw, J. E., Cook, M. J., Oghbaey, S., Daoud, H., Mehrabi, P., Kriksunov, I., Kuo, A., et al. (2019). Fixed-target serial oscillation crystallography at room temperature. IUCrJ 6(Pt 2): 305-316.
Illava, G., Jayne, R., Finke, A. D., Closs, D., Zeng, W., Milano, S. K., Huang, Q., Kriksunov, I., Sidorenko, P., Wise, F. W., et al. (2021). Integrated sample-handling and mounting system for fixed-target serial synchrotron crystallography. Acta Crystallogr D Struct Biol 77(Pt 5): 628-644.
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
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Category
Biophysics > X-ray crystallography
Drug Discovery > Drug Design
Biological Sciences > Biological techniques
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451 | https://bio-protocol.org/en/bpdetail?id=451&type=0 | # Bio-Protocol Content
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Determination of Nectar Nicotine Concentration in N. attenuata
ER Eva Rothe
MS Matthias Schöttner
DK Danny Kessler
IB Ian T. Baldwin
Published: Vol 3, Iss 8, Apr 20, 2013
DOI: 10.21769/BioProtoc.451 Views: 10969
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Original Research Article:
The authors used this protocol in The Plant Journal Aug 2012
Abstract
In this protocol, the determination of the nicotine concentration in nectar of Nicotiana attenuata is described. This method is applicable for the investigation of small amounts of nectar (above 1 μl). It is a high-throughput protocol optimized and streamlined for one skilled person to process approximately 100 nectar samples per day.
Materials and Reagents
Nicotiana attenuata
Nicotine-D3 (Cambridge Isotope laboratories, catalog number: DLM-1818-0.5 )
Ammonium hydroxide 25% (Fluka, catalog number: 44273-100 ML-F )
Methanol (Merck KGaA, catalog number: 1.06007.2500 )
Solvent A (see Recipes)
Solvent B (see Recipes)
Equipment
Varian 1,200 triple quad LC-MS system
Phenomenex Gemini NX 50 x 2 mm column, 3 μm C18 (Phenomenex, catalog number: 593381-9 )
1.5 ml Eppendorf tubes
1.5 ml GC vials (www.wicom.de)
25 μl glass capillary (BLAUBRAND®, intraMark) (BRAND GMBH + CO KG, Wertheim, catalog number: 708722 )
Procedure
The best time to collect nectar from N. attenuata is in the morning between 4:00 and 7:00 am, as the maximum nectar accumulation is reached around 4:00 am and remains stable until the sun rises or the lights in the glasshouse are switched on. As flowers of N. attenuata remain open for two nights, one must make sure that the same floral stage is used for collections. Usually newly opened flowers are used, which requires removal of all open flowers 24 h before the actual sampling in order to be sure to collect floral nectar from the same floral stage-- one- and two-day-old flowers are hard to tell apart from each other.
Nectar from flowers is collected by inserting a clean 25 μl glass capillary into the corolla tube until it reaches the base of the nectaries (Figure 1). With practice, a complete nectar sample can be obtained by holding the capillary with one hand and the corolla tube with the other and removing the tube against the counter-pressure of the inserted capillary (Video 1). This technique requires some training in order to avoid damage to the ovary and contamination of the nectar. Alternatively, the complete corolla can be detached from the rest of the flower by simply pulling on the corolla tube. The nectar remains at the base of the tube from which it can be collected with a 25 μl glass capillary (Video 2).
Figure 1. Floral nectar collection with a glass capillary
Video 1. Nectar collection from N. attenuata flowers - method 1
Video 2. Nectar collection from N. attenuata flowers - method 2
Nectar of single flowers is collected separately in 1.5 ml Eppendorf tubes. 2 μl or 1.5 μl (for flowers with low nectar volume) of nectar are transferred into a new tube containing 400 μl water and 20 ng of the internal standard nicotine-D3.
Particles are removed by centrifugation (10 min at 12,000 x g, at 4 °C) and the supernatant is transferred into 1.5 ml GC vials.
10 μl of the solution are analyzed using a Varian 1,200 triple quad LC-MS system (http://www.varianinc.com) connected to an ESI source with a capillary voltage of 35 V, solvent A ; Solvent B. The gradient (min/% B): 0/5; 0.5/5; 2/80; 6.5/80; 8.5/5; 10/5 (Figure 2) is used with a Phenomenex Gemini NX 5 x 2 mm column, particle size 3 μm. The pH of the mobile phase is the most important parameter which determines nicotine's retention on the column. The starting conditions focus nicotine on the column, while sugars and salts are eluted. The steep gradient guarantees sharp nicotine peaks. The time for reconditioning the column is strongly instrument dependent. The short reconditioning time in our program is adapted to accommodate our slow auto sampler. The transition of the precursor ion nicotine [M + H]+ = 163 and nicotine-D3 [M + H]+ = 166 to the fragment (m/z) = 130 at a collision energy of 14.5 V is recorded for quantification. Quantification was achieved by isotope dilution and can be calculated by the following formula: amount nicotine (ng/μl nectar) = area of targeted compound/area ISD (internal standard = nicotine - D3) x amount ISD (ng/μl nectar).
Figure 2. Methanol gradient.
Recipes
Solvent A
Add 1 ml of 25% ammonium hydroxide solution to 1 L Milipore H2O
Mix carefully, adjust pH to 10 [according to the pka of Nicotine, which is 8.05 (Fujita et al., 1971) the pH should be 10 or higher, to maintain nicotine in its neutral form. The upper pH is limited by the column chemistry and may be adjusted with concentrated ammonia or a few drops of 1:10 diluted formic acid].
Solvent B
Methanol
Acknowledgments
This work was supported by the Max Planck Gesellschaft. The protocol was adapted from the publication: Kessler et al. (2012).
References
Fujita, T., Nakajima, M., Soeda, Y. and Yamamoto, I. (1971). Physicochemical properties of biological interest and structure of nicotine and its related compounds. Pesticide Biochem Physiol 1(2): 151-162.
Kessler, D., Bhattacharya, S., Diezel, C., Rothe, E., Gase, K., Schottner, M. and Baldwin, I. T. (2012). Unpredictability of nectar nicotine promotes outcrossing by hummingbirds in Nicotiana attenuata. Plant J 71(4): 529-538.
Article Information
Copyright
© 2013 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Rothe, E., Schöttner, M., Kessler, D. and Baldwin, I. T. (2013). Determination of Nectar Nicotine Concentration in N. attenuata. Bio-protocol 3(8): e451. DOI: 10.21769/BioProtoc.451.
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Category
Plant Science > Plant biochemistry > Other compound
Biochemistry > Other compound > Alkaloid
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4,510 | https://bio-protocol.org/en/bpdetail?id=4510&type=0 | # Bio-Protocol Content
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Protein Tyrosine Phosphatase Biochemical Inhibition Assays
MB Marek R. Baranowski
JW Jiaqian Wu
YH Ye Na Han
LL Lester J. Lambert
NC Nicholas D. P. Cosford
LT Lutz Tautz
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4510 Views: 1561
Reviewed by: Chiara AmbrogioZheng Zachory WeiKarem A Court
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Jan 2022
Abstract
Disturbance of the dynamic balance between protein tyrosine phosphorylation and dephosphorylation, modulated by protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs), is known to be crucial for the development of many human diseases. The discovery of agents that restore this balance has been the subject of many drug research efforts, most of which have focused on tyrosine kinase inhibitors (TKIs), resulting in the development of more than 50 FDA-approved TKIs during the past two decades. More recently, accumulating evidence has suggested that members of the PTP superfamily are also promising drug targets, and efforts to discover tyrosine phosphatase inhibitors (TPIs) have increased dramatically. Here, we provide protocols for determining the potency of TPIs in vitro. We focus on the use of fluorescence-based substrates, which exhibit a dramatic increase in fluorescence emission when dephosphorylated by the PTP, and thus allow setting up highly sensitive and miniaturized phosphatase activity assays using 384-well or 1536-well microplates and a continuous (kinetic) assay format. The protocols cover PTP specific activity assays, Michaelis–Menten kinetics, dose-response inhibition assays, and dose-response data analysis for determining IC50 values. Potential pitfalls are also discussed. While advanced instrumentation is utilized for compound spotting and liquid dispensing, all the assays can be adapted to existing equipment in most laboratories. Assays are described for selected PTP drug targets, including SHP2 (PTPN11), PTP1B (PTPN1), STEP (PTPN5), and VHR (DUSP3). However, all protocols are applicable to members of the PTP enzyme family in general.
Graphical abstract:
Keywords: Protein tyrosine phosphatase SHP2 PTP1B VHR DUSP Inhibitor Dose-response assay Michaelis–Menten IC50
Background
Protein tyrosine phosphorylation is a reversible posttranslational modification (PTM) and a fundamentally important mechanism in eukaryotic cell signal transduction and regulation (Hunter, 2009). Perturbations in tyrosine phosphorylation can lead to the development of many human diseases, including cancer, neurological disorders, autoimmunity, and immunodeficiency, as well as cardiovascular, metabolic, and infectious diseases (Tautz et al., 2006; Vang et al., 2008; Labbe et al., 2012; Goebel-Goody et al., 2012; Zhang, Z. Y. et al., 2015; Menegatti, 2022). Targeting protein tyrosine kinases (PTKs) has been a major focus of drug discovery efforts in the last two decades, resulting in more than 50 FDA-approved tyrosine kinase inhibitors (TKIs) (Cohen et al., 2021). On the other hand, the discovery of clinical candidates that target protein tyrosine phosphatases (PTPs) has significantly lagged behind the kinases for multiple reasons (reviewed in Tautz et al., 2013; Tonks, 2013; Stanford and Bottini, 2017). Unquestionably, an inflection point in tyrosine phosphatase inhibitor (TPI) research was the discovery of SHP099, the first truly selective and drug-like inhibitor of the SHP2 (PTPN11) phosphatase (Chen et al., 2016). The compound has since served as a blueprint for several investigational drugs that are currently being tested in phase 1/2 clinical trials for the treatment of solid tumors (Song et al., 2022).
The success in bringing SHP2 inhibitors into the clinic has garnered a new wave of interest in targeting PTPs. Here, we provide protocols for determining the potency of TPIs in enzymatic phosphatase assays. The experiments described cover: 1) PTP activity assays, to determine a suitable enzyme concentration; 2) Michaelis–Menten kinetics, to determine the Michaelis–Menten constant (Km) of the substrate for a specific PTP; and 3) dose-response inhibition assays and dose-response data analysis, to determine IC50 values of potential inhibitors. We utilized advanced instrumentation for automated compound spotting and liquid dispensing. However, the assays described herein can be adapted to existing equipment in most laboratories. While our protocols are applicable to PTPs in general, we show examples that utilize four specific phosphatases with promising therapeutic potential in various diseases, including cancer [SHP2, PTP1B (Vainonen et al., 2021)], type II diabetes [PTP1B (Zhang, Z. Y. et al., 2015)], Alzheimer’s disease [STEP (Lambert et al., 2021)], as well as arterial thrombosis, sepsis, and septic shock [VHR (Tautz et al., 2015; Singh et al., 2015)].
Figure 1. Generic protein phosphatase substrates used for PTP enzymatic assays. (A) The colorimetric substrate p-nitrophenyl phosphate (pNPP). (B) The fluorogenic substrates 6,8-difluoro-4-methylumbelliferyl phosphate (DiFMUP), 3-O-methylfluorescein phosphate (OMFP), and fluorescein diphosphate (FDP).
Historically, a widely used generic protein phosphatase substrate is p-nitrophenyl phosphate (pNPP) (Bessey et al., 1946) (Figure 1A). Conversion of pNPP generates p-nitrophenol, which can be directly monitored via its absorbance at 405 nm. While the absorbance of p-nitrophenol is linear over a relatively wide range of concentrations (approximately 5–500 μM), colored small molecules of interest can absorb light at similar frequencies, resulting in potential false negative results. Moreover, relatively high concentrations of recombinant PTPs (in the mid nanomolar range) are typically required to produce sufficient p-nitrophenol signal to background (S/B) and signal to noise (S/N) ratios. More recently, fluorogenic protein phosphatase substrates such as 6,8-difluoro-4-methylumbelliferyl phosphate (DiFMUP), 3-O-methylfluorescein phosphate (OMFP), or fluorescein diphosphate (FDP) (Figure 1B) have been utilized for PTP fluorescence intensity assays (Huang et al., 1999; Welte et al., 2005; Tierno et al., 2007; Tautz and Sergienko, 2013). These substrates have a low fluorescence in the phosphorylated state but become strong fluorophores when dephosphorylated. Typically, PTP assays using fluorogenic substrates are several orders of magnitude more sensitive than comparable pNPP assays, thus requiring significantly less recombinant PTP enzyme (picomolar to low nanomolar concentrations). Additionally, the fluorescence emission of the dephosphorylated products can be measured over a wide range of concentrations (approximately 10 nM to >100 μM) with excellent S/B and S/N ratios for highly reproducible PTP assays in continuous (kinetic) mode, which allows for the most accurate determination of the initial velocity rates (V). PTP assays using fluorogenic substrates can be easily miniaturized and performed in 384-well or 1536-well formats, allowing for efficient dose-response testing of candidate inhibitors. For the protocols provided here, we employ DiFMUP and/or OMFP with standard volume 384-well microplates. These plates do not require automated liquid handling and are amenable to manual liquid transfers using multichannel pipettes. However, laboratories with advanced equipment will experience no difficulty in adapting the protocols to a 1536-well format, as we have successfully performed similar assays using 1536-well microplates in a total assay volume as small as 5 μL.
Notes and Considerations
PTPs typically are most active at a pH between 5.5 and 6 (Groen et al., 2005). Our standard assay buffer that works well for most PTPs is Bis-Tris used at pH 6 (see Recipe 1). Buffer systems closer to physiological pH (e.g., Tris buffer at pH 7.4) may be used as well. For inhibition assays, we recommend not using buffers containing sulfonic acids such as HEPES, which can compete with inhibitor binding at the active site. A reducing agent such as dithiothreitol (DTT) ensures that the PTP catalytic cysteine is in the active, reduced state. It also prevents potentially oxidizing compounds from nonspecifically inhibiting the PTP through oxidation of the catalytic Cys. The addition of a detergent such as 0.01% Tween 20 is highly recommended, as it stabilizes the protein over the course of the assay and reduces the likelihood of promiscuous, aggregate-based inhibition (Feng and Shoichet, 2006). Bovine serum albumin (BSA) or globulin proteins may be used as detergent substitutes. For a detailed description of buffer optimization experiments, we refer to our previous publication (Tautz and Sergienko, 2013).
Fluorogenic substrates such as DiFMUP or OMFP may encounter compound spectral interference, either via compound autofluorescence or compound-induced fluorescence quenching. In our experience, the DiFMUP assay, which relies on the near-UV/blue spectral range (λex = 360 nm, λem = 460 nm), is more prone to such interference than the red-shifted OMFP assay (λex = 485 nm, λem = 535 nm). A pre-read of the assay plate (containing enzyme solution and compound) before addition of the substrate will typically show any potential compound autofluorescence. Likewise, IC50 curves going beyond 100% inhibition may indicate fluorescence quenching. When compound fluorescence interference is suspected, an increase in fluorescent product by using either greater enzyme concentrations or longer reaction times, while still staying within the linear range of substrate conversion, could lessen such interference effects. However, the best approach to mitigate such issues is to retest the suspected compounds using orthogonal substrates (e.g., using OMFP and/or pNPP instead of DiFMUP).
In our protocols, we use acoustic droplet dispensing of compound DMSO stock solutions, allowing for the transfer of nanoliter quantities. Specifically, when we use 384-well standard volume plates and a total assay volume of 25 μL, we transfer 250 nL of compound DMSO stock solution, which results in a final DMSO concentration of 1% that is typically well tolerated by recombinant PTPs. For manual transfer of compound stock solutions using a pipette, we recommend transferring no less than 1 μL to ensure accuracy. In our experience, when using a 1 μL transfer, the corresponding final DMSO concentration of 4% has no considerable effect on PTP stability or activity. In any case, the DMSO content should be kept at an equal amount in all wells, including wells for positive and negative controls.
Whenever feasible, we prefer using OMFP over DiFMUP because of the OMFP red-shifted excitation and emission wavelengths compared to DiFMUP, which lower the chances of compound fluorescence interference. However, one potential issue is the limited aqueous solubility of OMFP that requires initial dissolution in DMSO, resulting in extra DMSO added to the reaction mixtures. Using a 10 mM OMFP stock solution in DMSO (which reaches the limit of OMFP solubility in DMSO), the final DMSO concentration is usually manageable for most PTPs, for which OMFP Km values are in the mid- to low-micromolar range. However, for some PTPs (e.g., SHP2), the OMFP Km is in the high micromolar range, which makes it difficult (or impossible) to keep the final DMSO concentration at the recommended ≤5%, which ensures negligible impact on the stability and activity of the recombinant PTP.
Materials and Reagents
384-well black, flat bottom, standard volume microplates (Greiner Bio-One FLUOTRAC 200, catalog number: 781076)
Aluminum adhesive plate seals (Sigma-Aldrich, catalog number: Z721557)
1.5 mL Eppendorf tubes
15 mL conical tubes
50 mL conical tubes
Recombinant human PTPs with a purity of at least 95% according to SDS-PAGE gel electrophoresis: full-length SHP2 wild-type (SHP2-WT), SHP2 catalytic domain (SHP2cat, aa 237–529), PTP1B (aa 1–300), full-length STEP46, and full-length VHR.
Dually phosphorylated IRS-1 peptide (synthesized by PepMic, Suzhou, China) for activating SHP2-WT
Bis-Tris (Research Product International, catalog number: B75000)
Sodium chloride (NaCl, Sigma-Aldrich, catalog number: S3014)
EDTA tetrasodium salt dihydrate (BioWorld, catalog number: 40500024)
3-O-methylfluorescein phosphate cyclohexylammonium salt (OMFP; in-house synthesis)
6,8-difluoro-4-methylumbelliferyl phosphate (DiFMUP; ThermoFisher Scientific, catalog number: D22065)
Tween 20 (Fisher Bioreagents, catalog number: BP337)
DL-dithiothreitol (DTT; BioWorld, catalog number: 40400120)
Dimethyl sulfoxide (DMSO; Sigma-Aldrich, catalog number: D8418)
Milli-Q water: water purified using a Millipore Milli-Q lab water system
Bis-Tris buffer (see Recipes)
10 mM OMFP stock solution in DMSO (see Recipes)
10 mM DiFMUP stock solution in water (see Recipes)
1 M DTT stock solution (see Recipes)
Equipment
Fluorescence microplate reader with filters for 360 nm, 460 nm, 485 nm, and 535 nm (Tecan, Spark Multimode Microplate Reader)
Tabletop centrifuge with a swinging-bucket rotor (Eppendorf, 5810R equipped with A-4-62 rotor and MTP bucket)
MultidropTM Combi reagent dispenser (Thermo Fisher Scientific, catalog number: 5840300)
Small tube dispensing cassette (Thermo Fisher Scientific, catalog number: 24073290 or 24073295)
E1-ClipTipTM multichannel pipettes (Thermo Fisher Scientific, various volumes)
Echo® 555 Liquid Handler (Labcyte)
Note: To spin down plates, the Eppendorf tabletop centrifuge was used at 1,000 rpm (approximately 172 × g).
Software
Chemical and Biological Information Systems (CBIS, ChemInnovation Software, Inc.)
GraphPad PrismTM v.9 (GraphPad Software, LLC.)
MagellanTM data analysis software (Tecan)
Microsoft® Excel (Microsoft)
Note: Slopes from kinetic progression curves can be calculated using either Magellan, GraphPad Prism, or Excel. Michaelis–Menten parameters can be calculated in GraphPad Prism (or equivalent programs). Both GraphPad Prism and CBIS allow for straightforward analysis of dose-response data and calculation of IC50 values. CBIS has the advantage of providing a more automated and convenient environment for analyzing larger data sets.
Procedure
PTP Activity Assay using DiFMUP or OMFP
Note: The following procedure can be used to determine a suitable PTP concentration for the inhibition assays, and to compare or confirm the specific activity of recombinant PTP batches.
Thaw the protein stock solution on ice and mix gently.
Prepare 50 mL of substrate buffer (SB): add 5 µL of Tween-20 to 50 mL of Bis-Tris pH 6 buffer (see Recipes for details).
Note: Store SB at room temperature for no longer than one week. Alternatively, store SB at 4 °C in the dark for several months or freeze for long-term storage.
Prepare 10 mL of enzyme buffer (EB): add 50 µL of a 1 M DTT stock solution to 10 mL SB.
Note: Keep EB on ice for no longer than eight hours.
Prepare 1 mL of 500 nM enzyme intermediate solution (EIS). Use EB to dilute PTP stock solution to 500 nM and keep on ice.
Prepare PTP enzyme solution (ES) (100 µL for each) at 1.25× final concentration by serial dilutions from the EIS and using the EB (Table 1). For instance, for an OMFP assay, make enzyme solutions at 12.5 nM (ES1), 6.25 nM (ES2), 3.12 nM (ES3), 1.56 nM (ES4), and 0.781 nM (ES5) for final enzyme concentrations of 10 nM, 5 nM, 2.5 nM, 1.25 nM, and 0.625 nM. For DiFMUP assays, lower PTP concentrations are typically necessary. For instance, make enzyme solutions at 3.12 nM (ES1), 1.56 nM (ES2), 0.781 nM (ES3), 0.391 nM (ES4), and 0.195 nM (ES5) for final enzyme concentrations of 2.5 nM, 1.25 nM, 0.625 nM, 0.312 nM, and 0.156 nM (Figure 2A).
Table 1. Enzyme solutions for PTP activity assay
OMFP Assay DiFMUP Assay
Concentration of PTP in the 1.25× working solution (nM) Final PTP concentration (nM) Concentration of PTP in the 1.25× working solution (nM) Final PTP concentration (nM)
ES1 12.5 10 3.12 2.5
ES2 6.25 5 1.56 1.25
ES3 3.12 2.5 0.781 0.625
ES4 1.56 1.25 0.391 0.312
ES5 0.781 0.625 0.195 0.156
Using a multichannel pipette, manually dispense EB and ES into a 384-well assay plate. Add 20 µL of EB to wells A1–E1 (no-enzyme control). Add 20 µL of ES1 to wells A2–A5 (for quadruplicate measurements). Similarly, add ES2 /3 /4 /5 to wells B2–B5, C2–C5, D2–D5, and E2-E5, respectively (Figure 2B).
Figure 2. Enzyme serial dilution scheme (A) and assay plate layout (B) for PTP activity assay. EIS, enzyme intermediate solution; ES, enzyme solution; EB, enzyme buffer; SS, substrate solution; BG, background.
Using a tabletop centrifuge with a swinging-bucket rotor, spin-down the plate for a few seconds, cover the plate with a lid (or with an additional plate), and incubate at room temperature for 20 min.
Using a 10 mM substrate stock solution and SB, prepare 1 mL of substrate solution (SS) at 5× final concentration. Use a final substrate concentration close to the Km value. If the Km of the substrate for the PTP is not known, choose 50 µM as the substrate concentration, for instance, to make a 250 µM SS. Keep SS at room temperature in the dark until use. Prepare fresh for each experiment.
Set up the microplate reader for a 30 min read in kinetic mode (see notes about microplate reader settings).
Using a multichannel pipette, add 5 µL of SS to each well (A1 through E5), immediately spin-down the plate for a few seconds, and start measurements using the microplate reader.
Analyze the fluorescence intensity data using linear regression and calculate regression coefficients (R2) and initial velocity rate (V) from the slopes, using programs such as Magellan (Tecan plate reader software), GraphPad Prism, Microsoft Excel, or similar. Representative data are shown in Figure 3.
Figure 3. Continuous (kinetic) phosphatase activity assay. Representative PTP activity progression curves using OMFP (A) or DiFMUP (B) as the substrate. Plots show fluorescence intensity values in relative fluorescence units (RFU) read every minute over a 30 min period for reactions with the indicated concentrations of PTP1B or enzyme buffer (EB; no-enzyme control, background). Each data point represents the average from four reaction wells ± standard deviation (SD). Simple linear regression has been fitted to the data. Values for initial velocity rates V (slopes), regression coefficients (R2), signal to background (S/B), and signal to noise (S/N) are presented in the tables below. S/B and S/N ratios were calculated from relative fluorescence values at the 10 min time point.
Note: The main criteria for determining a suitable enzyme concentration for inhibition assays are the linearity of the PTP reaction and the S/B and S/N ratios of the reaction. Linearity over the 30 min reaction can be assumed with a linear regression coefficient of R2 > 0.99. S/B and S/N ratios calculated from raw fluorescent emission values at the 10 min time point should be >10. (The 10 min time point corresponds to the length of the PTP reaction we recommend for the kinetic inhibition assays.) Judging from the progression curves shown for the PTP1B reaction with OMFP ( Figure 3A), we would recommend a PTP1B concentration of 2.5 nM, which yields acceptable linearity and S/B and S/N ratios. From the progression curves of the PTP1B reaction with DiFMUP (Figure 3B ) it is apparent that at the top two PTP1B concentrations (2.5 nM and 1.25 nM) the substrate is completely depleted within the 30 min reaction period. At 0.625 nM PTP1B, the progression curve still starts to plateau after 20 min, resulting in an R2 of 0.98. The lowest two PTP1B concentrations tested (0.312 nM and 0.156 nM) yield acceptable linearity in this experiment.
SHP2-WT Activity Assay using DiFMUP
Note: SHP2-WT adopts an autoinhibited conformation, in which one of its two SH2 domains blocks access to the active site. To assay SHP2-WT activity and test SHP2 inhibitors, a dually phosphorylated peptide derived from the insulin receptor substrate 1 (IRS-1) serves as a surrogate binding protein and is used to activate SHP2-WT (Raveendra-Panickar et al., 2022). The procedure described below determines the optimal IRS-1 concentration for SHP2-WT activation.
Thaw the protein stock solution on ice and mix gently.
Prepare SB, EB, and EIS as described in section A.
Prepare SHP2-WT ES at 2.5× final concentration (1 mL). For instance, for 0.5 nM final SHP2-WT concentration make a 1.25 nM ES: add 2.5 µL of SHP2-WT EIS to 997.5 µL EB, mix gently, and keep on ice.
Prepare serial dilutions of the IRS-1 peptide at 2.5× final concentration in EB using a 1 mM peptide stock solution. Choose dilutions in a wide range, e.g., 10 µM, 5 µM, 2.5 µM, 1.25 µM, 0.625 µM, 0.3125 µM, 0.15625 µM, and 0 µM, for final concentrations of 4 µM, 2 µM, 1 µM, 0.5 µM, 0.25 µM, 0.125 µM, 0.0625 µM, and 0 µM (Figure 4A).
Prepare eight 1.5 mL Eppendorf tubes on ice.
Dispense 198 µL of EB into tube 1.
Dispense 100 µL of EB into tubes 2–8.
Add 2 µL of the IRS-1 stock solution into tube 1, and gently mix.
Transfer 100 µL from tube 1 into tube 2 and mix, by gently pipetting up and down.
Continue the serial dilution until tube 7.
Discard 100 µL of the solution from tube 7.
Add 100 µL of SHP2-WT ES into each of the eight tubes and incubate on ice for 20 min.
Dispense solutions to 384-well assay plate for a quadruplicate experiment (Figure 4B).
Add 20 µL of EB to wells A1–A4 (no enzyme control).
Add 20 µL of tube 8 to wells B1–B4 (SHP2-WT, no peptide).
Add 20 µL of tube 7 to wells C1–C4 (SHP2-WT, lowest peptide concentration).
Continue with tubes 6 through 1, dispensing to wells D1–D4, E1–E4, F1–F4, G1–G4, H1–H4, I1–I4.
Figure 4. IRS-1 titration for SHP2-WT activity assay. (A) IRS-1 peptide serial dilution scheme. (B) Assay plate layout. Add 20 µL of enzyme buffer (EB; background control) or enzyme solutions (ES), followed by 5 µL of substrate solution (SS). (C) SHP2-WT (0.5 nM) activity (expressed as initial velocity rate V) in the presence of different IRS-1 peptide concentrations using DiFMUP (100 µM) as the substrate. For comparison, the activity of recombinant SHP2 catalytic domain (SHP2cat; 0.5 nM) without IRS-1 peptide is included. Enzyme buffer was used in the no-enzyme control experiment. The data represent the mean ± SD. Statistical significance of SHP2-WT activation by IRS-1 was determined using the unpaired t-test (n = 4; n.s.: not significant; ****p < 0.0001).
Spin-down the plate for a few seconds, cover the plate, and incubate at room temperature for 20 min.
Prepare SS at 5× final concentration (1 mL). Add 50 µL of DiFMUP stock solution to 950 µL of SB to make a 500 µM DiFMUP SS for a final DiFMUP concentration of 100 µM. Keep SS at room temperature in the dark until use. Prepare fresh for each experiment.
Set up the microplate reader for a 10 min read in kinetic mode (see notes about microplate reader settings).
Using a multichannel pipette, add 5 µL of SS to each well (A1 through I4). Immediately spin-down the plate for a few seconds and start measurements using the microplate reader.
Analyze the fluorescence intensity data using linear regression and calculate R2 and V from the slopes using programs such as Magellan (Tecan plate reader software), GraphPad Prism, Microsoft Excel, or similar.
Note: As shown in Figure 4C, the maximum activation of SHP2-WT is reached at an IRS-1 peptide concentration of 500 nM, which we employed in the SHP2-WT Michaelis–Menten and inhibition assays described previously (Raveendra-Panickar et al., 2022).
Michaelis–Menten Kinetics
Note: The purpose of the Michaelis–Menten experiment is to determine the Michaelis–Menten constant (Km) of the chosen substrate for a specific PTP under specific assay conditions. The Km value is important for the inhibition assays, in which the substrate is typically used at a concentration equal to the Km. This makes inhibitor IC50 values comparable between different PTPs.
Thaw the protein stock solution on ice and mix gently.
Prepare SB, EB, and EIS as described in section A.
Prepare ES at 1.25× final concentration (2 mL) and keep on ice.
Note: A suitable final enzyme concentration for this experiment should be based on the results from the PTP activity assay (section A).
Prepare a serial dilution of substrate at 5× final concentration (Figure 5, step 1). Prepare eight to ten different SS spanning approximately three orders of magnitude in concentration. For instance, prepare the highest concentrated SS at 1 mM (for a 200 µM final concentration) and do a 1:1 serial dilution. Prepare the serial dilution in a 384-well plate for convenient transfer to reaction wells, using a multichannel pipette.
Prepare the highest concentrated SS (SS1) in an Eppendorf tube. For instance, mix 10 µL of a 10 mM substrate stock solution with 90 µL of SB for SS1 at 1 mM.
Add 30 µL of SS1 to well A6 of a 384-well assay plate.
Add 30 µL of SB to wells B6–J6.
Add 30 µL of SS1 to well B6 and mix, by gently pipetting up and down.
Transfer 30 µL from well B6 to well C6 and mix, by gently pipetting up and down.
Continue the serial dilution through well J6.
Add 20 µL of EB to wells A1–J1 (no-enzyme control used for background correction).
Add 20 µL of ES to wells A2–J4 (enzyme reaction wells in triplicate for each substrate concentration) (Figure 5, step 2).
Spin-down the plate for a few seconds, cover the plate, and incubate at room temperature for 20 min.
Set up the microplate reader for a 10 min read in kinetic mode (see notes about microplate reader settings).
Using a multichannel pipette, transfer 5 µL of SS from column 6 (rows A–J) to columns 1–4 (rows A–J) (Figure 5, step 2). Immediately spin-down the plate for a few seconds and start measurements using the microplate reader.
Figure 5. Substrate serial dilution scheme and assay plate layout for Michaelis–Menten kinetics assay. In step 1, a substrate serial dilution (1:1) is prepared at 5× final concentration. In step 2, 5 µL of each substrate solution (SS) is transferred into column 1, which serves as the background control and contains 20 µL of enzyme buffer (EB), and columns 2–4, which serve as the triplicate PTP reaction wells and contain 20 µL of enzyme solution (ES).
Analyze the fluorescence intensity data from columns 1–4 (rows A–J) using linear regression and calculate R2 and V from the slopes using programs such as Magellan (Tecan plate reader software), GraphPad Prism, Microsoft Excel, or similar.
Analyze the background-corrected V values using the Michaelis–Menten equation and non-linear regression, and a program such as GraphPad Prism. Data from a representative Michaelis–Menten experiment using STEP46 with OMFP are shown in Figure 6.
Note: It is important to ensure that the PTP reaction is within the linear range for all concentrations included in the analysis. If necessary, adjust the enzyme concentration. Make sure the substrate concentrations cover concentration ranges below and above the Km value. For SHP2-WT, the Michaelis–Menten experiment should be conducted in the presence of IRS-1 peptide at a concentration as determined in section B. The SHP2-WT ES containing IRS-1 peptide should be prepared as described in section B.
Figure 6. Michaelis–Menten kinetics. (A) Initial velocities rates (V) in relative fluorescence units per minute (RFU/min) from a Michaelis–Menten experiment for STEP46 (2.5 nM) using OMFP at the indicated concentrations. Initial rates for the enzyme buffer (EB) control (Vcontrol (EB); background) and for the STEP46 reaction in triplicate ( V1–3) were calculated from raw fluorescence emission data using the Magellan Tecan Microplate Reader software. (B) Michaelis–Menten plot using the background-corrected initial rates (V1-corr, V2-corr, V3-corr) for STEP46 from (A). The data (represented as the mean ± SD) was fitted to the Michaelis–Menten equation model (eq. 5), and the Michaelis–Menten constant (Km) was calculated using GraphPad Prism. The dashed lines indicate the STEP46 maximum velocity (Vmax) and half-maximum velocity (Vmax/2).
10-Point Dose-Response PTP Inhibition Assay
Note: We used a Labcyte Echo® 555 Liquid Handler to spot DMSO (for controls) and compound solutions in DMSO (for 10-point dose-responses) via acoustic droplet dispensing. For a standard volume 384-well assay plate with a 25 μL total assay volume, we transferred 250 nL DMSO solution into each well. For manual transfer of compound stock solutions using a pipette, we recommend transferring no less than 1 μL (for accuracy reasons) and keeping the final DMSO concentration ≤5%. We recommend testing a wide range of compound concentrations of at least four log steps (e.g., 100, 33, 11, 3.7, 1.2, 0.41, 0.14, 0.045, 0.015, 0.005 μM final compound concentration). The provided volumes for ES and SS are for testing of up to four 384-well assay plates and may be adjusted according to needs.
Prepare a black, standard volume 384-well assay plate. Spot 250 nL of DMSO into negative and positive control wells (columns 1 and 2, respectively). Spot 250 nL of compound DMSO solutions in triplicate into columns 3–23.
Note: The total number of compounds that can be tested per 384-well plate is 11 (see Figure 7A for the plate map).
Thaw the protein stock solution on ice and mix gently.
Prepare SB (50 mL): add 5 µL of Tween-20 to 50 mL of Bis-Tris pH 6 buffer (see Recipes for details).
Note: Store SB at room temperature for no longer than one week.
Prepare EB (50 mL): add 250 µL of a 1 M DTT stock solution to 50 mL of SB.
Note: Keep EB on ice for no longer than eight hours.
Prepare 500 nM EIS (1 mL). Use EB to dilute PTP stock solution to 500 nM and keep on ice.
Prepare ES (approximately 45 mL) at 1.25× final concentration in a 50 mL conical tube. For instance, for 2.5 nM final PTP concentration, add 290 µL of EIS to 46.11 mL of EB, mix gently, and keep on ice.
Note: A suitable final enzyme concentration for the inhibition assay should be based on the results from the PTP activity assay (section A). For experiments with OMFP, we typically use 2.5 or 5 nM PTP final concentration. For experiments with DiFMUP, we typically use ≤0.5 nM PTP final concentration.
Prepare SS (approximately 15 mL) at 5× final substrate concentration in a 15 mL conical tube. For instance, for a 6 µM final substrate concentration, add 45 µL of the 10 mM substrate stock solution to 14.955 mL of SB, mix, and store at room temperature in the dark until use.
Note: The final substrate concentration for a specific PTP is determined by the substrate Km value obtained in the Michaelis–Menten experiment (section C).
Using a multichannel pipette, add 20 µL of EB to column 2 (positive control) of the spotted 384-well assay plate.
Using a MultidropTM Combi reagent dispenser, add 20 µL of ES to all wells, except those in column 2.
Using a tabletop centrifuge with a swinging-bucket rotor, spin-down the plate for a few seconds, cover the plate with a lid (or with an additional plate), and incubate at room temperature for 20 min.
Set up the microplate reader for a 10 min read in kinetic mode (see notes about microplate reader settings).
Using a MultidropTM Combi reagent dispenser, add 20 µL of SS to the entire plate, immediately spin-down the plate for a few seconds, and start measurements using the microplate reader.
Analyze the fluorescence intensity data using linear regression and calculate R2 and V from the slopes using programs such as Magellan (Tecan plate reader software), GraphPad Prism, Microsoft Excel, or similar. Make sure the linearity of the PTP reaction is acceptable and Z’ values are ≥0.5. For details on Z’-factor definition, please see the Data analysis section below.
Normalize the initial velocity rates using the positive (100% inhibition) and negative (0% inhibition) control values and analyze the normalized data using a nonlinear regression dose-response inhibition model (log inhibitor vs. response, variable slope, four parameters) using programs such as GraphPad Prism or CBIS, to obtain IC50 values. Data from a representative 10-point dose-response inhibition assay for VHR with OMFP are shown in Figure 7.
Figure 7. Representative data from a 10-point dose-response VHR inhibition assay. (A) Plate setup and initial velocity rates. Column 1 serves as the negative control (vehicle control). Column 2 serves as the positive control (contains no enzyme). Eleven candidate compounds (marked with different colors) were tested in a 10-point dose-response format in triplicate (100, 33, 11, 3.7, 1.2, 0.41, 0.14, 0.045, 0.015, and 0.005 μM final compound concentration). Wells K23 through P24 (white) do not contain DMSO or compound and are excluded from the analysis. (B) Assay plate statistical data. Initial rates for positive and negative controls are represented as mean ± SD. For Z’-factor definition and calculation see Data analysis section. (C) Example of normalized inhibition data and fitted IC50 curve (IC50 ± SE; analyzed in GraphPad Prism).
Data analysis
Statistical assay parameters
Signal to background (S/B):
where and are mean fluorescence values of reaction and background (no-enzyme control), respectively.
Signal to noise (S/N):
where SDBKGD is the standard deviation of background (zero-enzyme reaction).
Z’-factor:
where SDn and SDp and and are the standard deviations and means of the negative and positive control initial velocity values, respectively. The Z’-factor is a statistical parameter for the quality of the assay without intervention of test compounds (Zhang, J. H. et al., 1999). Z’ values above 0.5 indicate acceptable assay performance.
Initial velocities/slopes
All experiments were run in kinetic mode with a fluorescence intensity read every minute. The slopes of the progression curves were determined in Magellan (Tecan plate reader software), or by fitting a simple linear regression model to the kinetic data in GraphPad Prism or Excel, using the following equation:
where F represents fluorescence intensity in relative fluorescence units (RFU), x represents time (min), V represents the represents initial velocity (slope; RFU/min), and b represents the y-axis intercept (1/RFU).
Michaelis–Menten Kinetics
To determine the Michaelis–Menten constant Km (substrate concentration that yields the half-maximal velocity), the Michaelis–Menten model and GraphPad Prism were used to fit the data to the Michaelis–Menten equation:
where V represents initial velocity, Vmax the maximum enzyme velocity, and c the substrate concentration.
IC50 Determination
Initial velocity rates were normalized using the mean positive (100% inhibition) and mean negative (0% inhibition) control values to calculate the percentage of inhibition (%inhib):
where Vnc indicates the mean initial velocity rate from the negative control wells (vehicle control), Vpc indicates the mean initial velocity rate from the positive control wells (no-enzyme control), and Vinhib indicates the initial velocity rate from the reaction wells with compound at a specific concentration.
IC50 values were calculated from the %inhib by nonlinear regression, using CBIS or GraphPad Prism software. The data were fitted to a log[Inhibitor] vs. response, variable slope (four parameters) model:
where Bottom and Top are the bottom and top plateau, respectively, X is the ligand concentration, and HillSlope is the steepness of the curve.
Notes about the MultidropTM Combi reagent dispenser
It is important to fully prime the cassette tubes to avoid bubbles in the plastic tubes, which may result in dispensing errors. After each usage, flush tubes thoroughly with Milli-Q water, 70% ethanol, and again Milli-Q water.
Microplate Reader Settings – OMFP Assay
Experiment type: Kinetic Loop
Mode: Kinetic
Kinetic Cycles: 11
Interval time: 1 min
Measurement type: Fluorescence intensity
Mode: Fluorescence top reading
Excitation: Filter
Excitation wavelength: 485 nm
Excitation bandwidth: 20 nm
Emission: Filter
Emission wavelength: 535 nm
Emission bandwidth: 25 nm
Gain: 40 Manual
Mirror: automatic
Number of flashes: 10
Integration time: 40 µs
Lag time: 0 µs
Settle time: 0 ms
Total kinetic run time: 9 min 59 s
Microplate Reader Settings – DiFMUP Assay
The settings are the same as for the OMFP assay except:
Excitation wavelength: 360 nm
Excitation bandwidth: 35 nm
Emission: Filter
Emission wavelength: 465 nm
Emission bandwidth: 35 nm
Recipes
Bis-Tris buffer
50 mM Bis-Tris pH 6.0, 50 mM NaCl, 0.5 mM EDTA
In 800 mL of Milli-Q water, dissolve 10.5 g of Bis-Tris, 2.9 g of NaCl, and 208 mg of EDTA. Set pH to 6.0 with 1 M hydrochloric acid. Fill with Milli-Q water to 1 L. Store at 4 °C for up to one year.
10 mM OMFP stock solution in DMSO
Dissolve 26.3 mg of OMFP cyclohexylammonium salt in 5 mL of pure DMSO. Sonication (using a sonicator bath) may be needed to fully dissolve OMFP to a clear solution. Prepare aliquots as needed, and store at -80 °C.
10 mM DiFMUP stock solution in water
Dissolve 10 mg of DiFMUP in 3.42 mL of Milli-Q water. Prepare aliquots as needed, and store at -80 °C.
1 M DTT stock solution
Dissolve 771 mg of DTT in 5 mL of Milli-Q water. Prepare aliquots as needed, and store at -80 °C.
Acknowledgments
Research reported in this publication was supported by the National Institutes of Health under Awards Numbers R01AG065387, R21AG067155, R21AI160161, and R21CA195422 (to L.T.), and NCI Cancer Center Support Grant P30CA030199. Funding for this project has also been provided by the Polish National Science Center under award number UMO-2019/32/T/ST4/00071 (to M.B.). Additionally, this project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Chemical Biology Consortium Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The protocols described in here are partly derived from our recent research paper (Raveendra-Panickar et al., 2022).
Competing interests
The authors declare that they have no conflicts of interest with the contents of this article.
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4,511 | https://bio-protocol.org/en/bpdetail?id=4511&type=0 | # Bio-Protocol Content
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Introducing Article Processing Charges to Create a Sustainable Future
Fanglian He
Caroline Shamu
Vivian Siegel
Published: Vol 12, Iss 17, Sep 5, 2022
DOI: 10.21769/BioProtoc.4511 Views: 4460
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Fanglian He is Publisher, Caroline Shamu is Editor-in-Chief and Vivian Siegel is Advisory Board Chair for Bio-protocol journal.
Launched in 2011 by a group of Stanford researchers, Bio-protocol journal aims to improve research reproducibility by curating and hosting peer-reviewed, high quality protocols from across the life sciences. Thanks to the financial support of its passionate founders, Bio-protocol is proud to have published over 4000 high quality protocols, with no fees for publication or access since its founding. The journal has attracted approximately two million readers yearly, from more than 125 countries. While celebrating the success of the Bio-protocol journal on its 10th anniversary, we must also develop a sustainable business model to help the journal continue to thrive in its next decade and beyond. We will therefore introduce an Article Processing Charge of $1,200 for protocol articles submitted on or after March 1, 2023 that go on to be accepted for publication.
APC will support a more stable business model
We believe Article Processing Charges (APCs) are the best way to support Bio-protocol to achieve its mission for the long term. We had hoped that the journal could be free to people submitting to or using any protocols shared on Bio-protocol and that advertising revenue could become a primary source of financial support for the journal. However, like many other open access journals, we have struggled to make this model work for Bio-protocol—and, after 10 years, we have made the difficult decision that we need to find another way to fund Bio-protocol in a way that will be sustainable in the short and long term. Like many other journals, we have decided that implementing APCs makes the most sense (Shieber, 2009; Schekman and Patterson, 2016).
The charges will only partially cover Bio-protocol operating costs, but they will be a critical component of a financially stable structure—one that allows us to pay our staff living wages, to invest in improvements to the journal, and to build a platform that truly supports the exchange and discussion of protocols in the life sciences, to improve research reproducibility and accelerate discovery.
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Concomitant with implementing APCs, Bio-protocol will become a fully open access journal. Thus, Bio-protocol’s APCs may be covered by funding agencies that support open access publications in this way. Also, as part of the implementation of APCs, Bio-protocol will introduce an option for authors to request a fee waiver if they cannot afford the publication charges. Regardless of whether a fee waiver is in place, all submissions will follow the same editorial process. Editorial decisions will not be based on any author’s ability to pay the APCs. Authors who do not want to pay an APC, and also are not eligible for a waiver, can choose to post their protocols for free on the Bio-protocol preprint server.
Bio-protocol has a talented and dedicated staff, passionate editorial and reviewing boards, and a supportive and growing community; it is a great place to publish and discuss life science protocols (Taking on reproducibility with a team). We are so proud of what the journal has accomplished over the last 10 years and remain committed to its longevity and growth. We hope that this transition to a sustainable business model will allow Bio-protocol to continue to serve the research community for generations.
Acknowledgements
We would like to thank the Bio-protocol Advisory Board and Editorial team members for their constructive comments and inputs.
Competing interests
No competing interests declared.
References
Shieber, S. M. (2009). Equity for open-access journal publishing. PLoS Biol. 7(8):e1000165.
Schekman, R., Patterson, M. (2016). Building a sustainable future for eLife. Elife. e21230.
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4,512 | https://bio-protocol.org/en/bpdetail?id=4512&type=0 | # Bio-Protocol Content
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14C-paraquat Efflux Assay in Arabidopsis Mesophyll Protoplasts
JX Jin-Qiu Xia *
QL Qian-Qian Liu *
CX Cheng-Bin Xiang
(*contributed equally to this work)
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4512 Views: 785
Reviewed by: Yingnan Hou Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Molecular Plant Sep 2021
Abstract
Weeds compete with crops for growth resources, causing tremendous yield losses. Paraquat is one of the three most common non-selective herbicides. To study the mechanisms of paraquat resistance, we need to trace the movement of paraquat in plants and within the cell. 14C is a radioactive carbon isotope widely used to trace substances of interest in various biological studies, especially in transport analyses. Here, we describe a detailed protocol using 14C-paraquat to demonstrate paraquat efflux in Arabidopsis protoplasts.
Keywords: 14C-paraquat Isotope Protoplasts Efflux transport Arabidopsis
Background
Paraquat (PQ), a non-selective broad-spectrum herbicide, has been widely used in weed control. It mainly acts on plant green tissue and is relatively safe for soil microorganisms and plant roots (Huang et al., 2019). It competes for electrons from the photosynthesis system I (PS I) and reacts with oxygen, producing a large quantity of reactive oxygen species (ROS) that destroy the photosynthesis system and ultimately kill plants (Apel and Hirt, 2004). However, with the heavy use of PQ, resistant weeds have emerged (Hawkes, 2014). Through extensive studies of PQ-resistant weeds and Arabidopsis, several molecular mechanisms of PQ resistance have been unraveled. These include disrupted PQ transport that blocks it from reaching its target, PQ sequestration into the vacuole and apoplast, enhanced ability to scavenge ROS, and PQ detoxification (Chen et al., 2009; Fujita et al., 2012; Xi et al., 2012; Li et al., 2013; Luo et al., 2016; Lv et al., 2021; Xia et al., 2021; Huang et al., 2022; Nazish et al., 2022).
To study the function of the MATE transporter DTX6, we designed an experiment using 14C-paraquat and Arabidopsis protoplasts to confirm its PQ-exporting activity from cytosol to apoplast, which assisted us in revealing the PQ resistance mechanism via sequestration.
Materials and Reagents
50 mL centrifuge tube with round bottom
2 mL centrifuge tube with round bottom
70 μm Nylon mesh (EMD Millipore, CLS431751)
3–4 weeks old Arabidopsis plants
Scintillation fluid (Perkin-Elmer, Waltham, catalog number: 6013321)
14C-paraquat (American Radiolabeled Chemicals Inc. ARC 1311). Store at -20 °C
NaCl (Sinopharm Chemical Reagent Co., Ltd., CHINA, CAS: 7647-14-5)
CaCl2 (Sinopharm Chemical Reagent Co., Ltd., CHINA, CAS: 10043-52-4)
KCl (Sinopharm Chemical Reagent Co., Ltd., CHINA, CAS: 7447-40-7)
MES (SIGMA, USA CAS: 1266615-59-1)
W5 solution (see Recipes)
Equipment
Centrifuge with temperature control (Allegra X-22R Benchtop Centrifuge, Beckman Coulter, Indianapolis, USA)
Automated cell counter (IC1000, Shanghai RuiYu Biotech Co. Ltd., Shanghai, CHINA)
Ventilation cabinet (YKD-DAT004F, Wuxi Safoo Safety Equipment Co. Ltd., Wuxi, CHINA)
Scintillation vial (Perkin-Elmer, Waltham, USA)
Liquid scintillation counter (Tri-Carb 2910 TR, Perkin-Elmer, Waltham, USA)
-20 °C freezer
Procedure
Isolate protoplasts according to Yoo et al. (2007) and suspend in cold W5 solution (see Recipes).
Count the protoplasts with a cell counter to estimate their concentration. Centrifuge at 40 × g and 4 °C for 2 min. Decant the supernatant and resuspend the protoplasts in cold W5 solution to approximately 3 × 106 protoplasts/mL. This protoplast preparation is ready for 14C-paraquat loading (Figure 1).
Figure 1. Experimental scheme of 14C-paraquat loading into and efflux out of Arabidopsis mesophyll protoplasts.
Thaw out 14C-paraquat (3.1 mM, 0.1 μCi/μL) and dilute 10 times with W5 solution at room temperature.
Add the same volume of diluted 14C-paraquat solution to the protoplast preparation, to obtain a final concentration of 3 μM 14C-paraquat. Incubate for 1 h at room temperature to load paraquat into the protoplasts.
Centrifuge the protoplasts at 40 × g and 4 °C for 2 min. Discard the supernatant with the unloaded 14C-paraquat and wash the protoplasts with 15 mL of cold W5 solution 2–3 times.
Resuspend the protoplasts in 13 mL of W5 solution at room temperature and immediately initiate the paraquat efflux assay.
At different time points (0, 10, 20, and 40 min) after W5 solution resuspension, transfer 1 mL of protoplasts suspension into a 2 mL round-bottom centrifuge tube. Take at least three replicates at each time point.
Immediately centrifuge the aliquoted samples (40 × g, 2 min, 4 °C). Transfer the supernatant to a scintillation vial. Resuspend the protoplast pellet in 1 mL of W5 solution and transfer it to a scintillation vial. Then add 5 mL of scintillation fluid to each sample. Detect radioactivity on a liquid scintillation counter.
Analyze and present data as shown in Figure 2.
Note: 14C-paraquat waste was disposed according to the University’s safety management of isotopes.
Figure 2. Data analyses and presentation. (A) Calculation of 14C-paraquat retention in protoplasts at different time points. t=i: time of 14C-paraquat protoplasts efflux (0, 10, 20, and 40 min). CPMt=i: mean value of 14C-paraquat radioactivity retention in protoplasts at different time points. CPMt=0: mean value of 14C-paraquat radioactivity retention in protoplasts at the initial time. At=i: percentage of 14C-paraquat radioactivity retention in protoplasts at different time points relative to the initial time. (B) Paraquat retention in the protoplasts, measured in the Col-0 and DTX6 overexpression line (OE-13) (Xia et al., 2021). Paraquat retention was defined as a percentage of the 14C-paraquat loaded in the protoplasts. Values are mean ± SD (n = 3). Different letters indicate significant differences (P < 0.05; one-way ANOVA).
Recipes
W5 solution
154 mM NaCl
125 mM CaCl2
5 mM KCl
2 mM MES
pH 5.7
Acknowledgments
This protocol was adapted from previous work (Zhang et al., 2014; Qin et al., 2021); we would like to thank the authors of these studies for their protocols.
Competing interests
No conflict of interest declared.
References
Apel, K. and Hirt, H. (2004). Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu Rev Plant Biol 55: 373-399.
Chen, R., Sun, S., Wang, C., Li, Y., Liang, Y., An, F., Li, C., Dong, H., Yang, X., Zhang, J. and Zuo, J. (2009). The Arabidopsis PARAQUAT RESISTANT2 gene encodes an S-nitrosoglutathione reductase that is a key regulator of cell death. Cell Res 19(12): 1377-1387.
Fujita, M., Fujita, Y., Iuchi, S., Yamada, K., Kobayashi, Y., Urano, K., Kobayashi, M., Yamaguchi-Shinozaki, K. and Shinozaki, K. (2012). Natural variation in a polyamine transporter determines paraquat tolerance in Arabidopsis. Proc Natl Acad Sci U S A 109(16): 6343-6347.
Hawkes, T. R. (2014). Mechanisms of resistance to paraquat in plants. Pest Manag Sci 70(9): 1316-1323.
Huang, Y., Zhan, H., Bhatt, P. and Chen, S. (2019). Paraquat Degradation From Contaminated Environments: Current Achievements and Perspectives. Front Microbiol 10: 1754.
Huang, Y. J., Huang, Y. P., Xia, J. Q., Fu, Z. P., Chen, Y. F., Huang, Y. P., Ma, A., Hou, W. T., Chen, Y. X., Qi, X., et al. (2022). AtPQT11, a P450 enzyme, detoxifies paraquat via N-demethylation.J Genet Genomics S1673-8527(22)00127-8.
Li, J., Mu, J., Bai, J., Fu, F., Zou, T., An, F., Zhang, J., Jing, H., Wang, Q., Li, Z., et al. (2013). Paraquat Resistant1, a Golgi-localized putative transporter protein, is involved in intracellular transport of paraquat. Plant Physiol 162(1): 470-483.
Luo, C., Cai, X. T., Du, J., Zhao, T. L., Wang, P. F., Zhao, P. X., Liu, R., Xie, Q., Cao, X. F., and Xiang, C. B. (2016). PARAQUAT TOLERANCE3 is an E3 ligase that switches off activated oxidative response by targeting histone-modifying PROTEIN METHYLTRANSFERASE4b.PLoS Genet 12: e1006332.
Lv, Z., Zhao, M., Wang, W., Wang, Q., Huang, M., Li, C., Lian, Q., Xia, J., Qi, J., Xiang, C., et al. (2021). Changing Gly311 to an acidic amino acid in the MATE family protein DTX6 enhances Arabidopsis resistance to the dihydropyridine herbicides. Mol Plant 14(12): 2115-2125.
Nazish, T., Huang, Y. J., Zhang, J., Xia, J. Q., Alfatih, A., Luo, C., Cai, X. T., Xi, J., Xu, P. and Xiang, C. B. (2022). Understanding paraquat resistance mechanisms in Arabidopsis thaliana to facilitate the development of paraquat-resistant crops. Plant Commun 3(3): 100321.
Qin, P., Zhang, G., Hu, B., Wu, J., Chen, W., Ren, Z., Liu, Y., Xie, J., Yuan, H., Tu, B., et al. (2021). Leaf-derived ABA regulates rice seed development via a transporter-mediated and temperature-sensitive mechanism. Sci Adv 7(3): eabc8873.
Xi, J., Xu, P. and Xiang, C. B. (2012). Loss of AtPDR11, a plasma membrane-localized ABC transporter, confers paraquat tolerance in Arabidopsis thaliana. Plant J 69(5): 782-791.
Xia, J. Q., Nazish, T., Javaid, A., Ali, M., Liu, Q. Q., Wang, L., Zhang, Z. Y., Zhang, Z. S., Huang, Y. J., Wu, J., et al. (2021). A gain-of-function mutation of the MATE family transporter DTX6 confers paraquat resistance in Arabidopsis. Mol Plant 14(12): 2126-2133.
Yoo, S. D., Cho, Y. H. and Sheen, J. (2007). Arabidopsis mesophyll protoplasts: a versatile cell system for transient gene expression analysis. Nat Protoc 2(7): 1565-1572.
Zhang, H., Zhu, H., Pan, Y., Yu, Y., Luan, S. and Li, L. (2014). A DTX/MATE-type transporter facilitates abscisic acid efflux and modulates ABA sensitivity and drought tolerance in Arabidopsis. Mol Plant 7(10): 1522-1532.
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Plant Science > Plant physiology > Biotic stress
Cell Biology > Cell signaling > Development
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4,513 | https://bio-protocol.org/en/bpdetail?id=4513&type=0 | # Bio-Protocol Content
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In situ Dephosphorylation Assay with Recombinant Nil Phosphatase
NN Nilay Nandi *
CT Charles Tracy *
Helmut Krämer
(*contributed equally to this work)
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4513 Views: 1180
Reviewed by: Gal HaimovichRajan Thakur Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in eLIFE Jan 2022
Abstract
The activity of numerous autophagy-related proteins depends on their phosphorylation status, which places importance on understanding the responsible kinases and phosphatases. Great progress has been made in identifying kinases regulating autophagy, but much less is known about the phosphatases counteracting their function. Genetic screens and modern proteomic approaches provide powerful tools to identify candidate phosphatases, but further experiments are required to assign direct roles for candidates. We have devised a novel protocol to test the role of purified phosphatases in dephosphorylating specific targets in situ. This approach has the potential to visualize context-specific differences in target dephosphorylation that are not easily detected by lysate-based approaches such as Western blots.
Graphical abstract:
Keywords: Autophagy Acinus Nilkantha Phosphorylation Metal-dependent phosphatases Cdk5 Drosophila
Background
Tight regulation of autophagy is important as both insufficient and excessive autophagic flux can doom individual cells and shorten organismal life span (Doherty and Baehrecke, 2018; Levine and Kroemer, 2019). This is well illustrated by the function of acinus, an upstream regulator of the Atg1 master regulator of autophagy (Tyra et al., 2020). In Drosophila, excessive acinus levels cause autophagy-dependent death (Haberman et al., 2010), whereas Cdk5-dependent phosphorylation and the resulting activation of acinus function contributes to the extension of life span by promoting basal autophagy (Nandi et al., 2017). A genetic screen identifying the phosphatase balancing Cdk5-mediated acinus activation pointed to the Nilkantha (Nil) phosphatase (Nandi et al., 2022), a functional homolog to mammalian metal-dependent PPM1A/B phosphatases (Kamada et al., 2020). In vitro phosphorylated and purified proteins or peptides have classically been used for testing the activity of phosphatases on specific substrates (e.g., Berndsen et al., 2019). This class of phosphatases poses challenges for the in vitro assessment of their activity towards specific targets. Their required N-terminal myristoylation (Chida et al., 2013) precludes simple bacterial expression. Furthermore, metal-dependent PPM-type phosphatases interact with substrates at sites distinct from the phosphorylated residue (Kamada et al., 2020). This constitutes a challenge for testing their activity on multiprotein complexes, such as the ASAP complex that contains the RNPS1 and SAP18 subunits in addition to acinus, and that has proven difficult to purify or reconstitute (Murachelli et al., 2012). Therefore, it may be important to present subunits of multiprotein complexes, such as acinus, in the appropriate functional context to assess their dephosphorylation. To address these issues, we describe here our protocol to purify Drosophila Nil and human PPM1B expressed in Drosophila S2 cells and use these phosphatases to assess dephosphorylation of endogenous acinus protein in its endogenous context in fixed and permeabilized tissue samples (Nandi et al., 2022). We expect that this protocol can be easily adapted to other phosphatase/substrate combinations, if phospho-specific antibodies are available for the site to be dephosphorylated.
Materials and Reagents
500 mL vacuum filter/storage bottle (Corning, catalog number: 430769)
25 cm2 flask (Corning, catalog number: 430639)
Six-well plate (Falcon, catalog number: 353046)
96-well assay plate (Costar, catalog number: 2595)
1.5 mL microfuge tube (Eppendorf, catalog number: 0030119487)
15 mL conical centrifuge tube (Thermo Scientific, catalog number: 339651)
Micro slides, single frosted, precleaned 75 × 25 mm (Corning, catalog number: 2948-75X25)
Cover glass, thickness 1.5, 22 × 40 mm (Corning, catalog number: 2980-224)
S2 cells [Drosophila Genomics Resource Center (DGRC): Stock Number 6]
Schneider’s Drosophila medium (Gibco, catalog number: 21720)
Fetal bovine serum (FBS) (Sigma, catalog number: F4135)
TransIT-2020 (Mirus, catalog number: MIR 5400)
Nil expression plasmid: pPuro-MT-Nil-Twin-streptag (Nandi et al., 2022)
NilD231N mutant expression plasmid: pPuro-MT-NilD231N-Twin-streptag (Nandi et al., 2022)
Cupric sulfate pentahydrate (MP Biomedicals, catalog number: 0219511783)
NaCl (Fisher Scientific, catalog number: BP358-1)
KCl (Fisher Scientific, catalog number: BP366-500)
Na2HPO4 (Sigma-Aldrich, catalog number: S5136100G)
KH2PO4 (Sigma-Aldrich, catalog number: P5655100G)
HCl (Fisher Scientific, catalog number: A481-212)
Tris base (Fisher Scientific, catalog number: BP152-5)
NP40 (Accurate Chemical, catalog number: A56009)
Phenylmethylsulfonyl fluoride (PMSF) (Thermo Scientific, catalog number: 36978)
Protease inhibitor (Roche, catalog number: 05892970001)
Phosphatase inhibitor (Roche, catalog number: 04906837001)
MagStrep “type3” XT beads (IBA, catalog number: 2-4090-002)
Ethylene glycol-bis(β-aminoethyl ether)-N,N,N′,N′-tetra-acetic acid (EGTA) (RPI, catalog number: E57060-250.0)
Sodium acetate, anhydrous (Thermo Scientific, catalog number: A131840B)
Dithiothreitol (DTT) (RPI, catalog number: D11000-25.0)
1 M manganese chloride (MnCl2) (RPI, catalog number: M20100-50.0)
1 M magnesium chloride (MgCl2) (Thermo Scientific, catalog number: J61014EQE)
Puromycin dihydrochloride (MP Biomedicals, catalog number: 0219453980)
Paraformaldehyde (Electron Microscopy Sciences, catalog number: 19208)
NaOH, 50% w/w (Thermo Scientific, catalog number: 33382A1)
Sodium phosphate monobasic monohydrate (Sigma-Aldrich, catalog number: 71507-250g)
Sodium phosphate (Sigma-Aldrich, catalog number: 342483-500g)
L-Lysine (Sigma-Aldrich, catalog number: L-5626)
di-sodium hydrogen phosphate anhydrous (Fluka, catalog number: 71636)
Sodium m-periodate (Sigma, catalog number: S-1147)
HaltTM protease inhibitor single-use cocktail (100×) (Thermo Scientific, catalog number: 1860932)
Vectashield mounting media with fluorescence with DAPI (Vector Laboratories, catalog number: H-1200)
Nail polish, advanced hard (Sally Hansen, catalog number: 45121)
Normal goat serum (MP Biomedicals, catalog number: 191356).
Rabbit anti-pS437-Acn (1:1000) (Nandi et al., 2017). Long-term storage of aliquots at -80 °C; aliquots in use stored at 4 °C
Goat anti-Rabbit IgG (H+L) cross-adsorbed secondary antibody, Alexa Fluor 488 (Invitrogen, catalog number: A11088). Store at 4 °C
SYLGARD 184 (Sigma, catalog number: 761036)
Magnesium chloride hexahydrate (Fisher Chemical, catalog number: M33-500)
Cadmium chloride (Fisher Chemical, catalog number: C10-500)
Saponin from quillaja bark (Sigma, catalog number: S7900-100G)
Parafilm (Thermo Scientific, catalog number: S37440)
2× Laemmli sample buffer (Bio-Rad, catalog number: 1610737)
Bovine serum albumin (BSA) (RPI, catalog number: 9048-46-8)
10% protein gel (Bio-Rad, catalog number: 4568035)
Nitrocellulose blotting membrane (Cytiva, catalog number: 10600003)
Blotting system (Bio-Rad, catalog number: 1703930)
Total protein stain (LiCor, catalog number: 926-11015)
S2 cell media (see Recipes)
1× PBS (see Recipes)
Puromycin dihydrochloride (10 mg/mL) (see Recipes)
0.7 M CuSO4 (see Recipes)
Lysis buffer (see Recipes)
2× stock phosphatase assay buffer (see Recipes)
Biotin elution buffer (see Recipes)
8% paraformaldehyde (see Recipes)
0.4 M Sorenson's phosphate buffer stock (see Recipes)
0.1 M di-sodium hydrogen phosphate buffer (see Recipes)
Lysine stock (see Recipes)
Periodate-lysine-paraformaldehyde fixative (see Recipes)
10% saponin (see Recipes)
1 M DTT (see Recipes)
Phosphatase assay buffer (see Recipes)
Equipment
Electrophoresis chamber (Bio-Rad, catalog number: 1658004)
Incubator set at 37 °C (Thermo Scientific, Heratherm IGS60, catalog number: 51028063)
Biosafety cabinet (The Baker Company, model: SG403)
Incubator set at 25 °C (Shel Lab, model: SRI3)
CountessTM automated cell counter (Invitrogen, model: AMQAX2000)
Inverted microscope for cell culture (Nikon, TMS: 213340)
Microfuge tube rotator (Thermo Scientific, catalog number: 88881001)
Magnetic microfuge tube rack (Thermo Scientific, catalog number: MR02)
Western blot scanner (Li-Cor, Odyssey: 9120)
Leica L2 microscope (Leica Microsystems)
Orbital shaker complete (Bellco Biotechnology; SKU: 7744-01010)
Fine forceps #5 (Fine Science Tools, catalog number: 11254-20)
Fine forceps #55 (Fine Science Tools, catalog number: 11255-20)
LSM 710 confocal microscope (Zeiss), with a 63× NA 1.4 objective
Software
Image Studio (Li-Cor, https://www.licor.com/bio/image-studio/)
ImageJ (NIH, https://imagej.nih.gov/ij/)
Adobe Photoshop (Adobe, https://www.adobe.com/products/photoshop.htmL)
Zen (black edition) (Zeiss, https://www.micro-shop.zeiss.com/en/us/softwarefinder/software-categories/zen-black/)
Procedure
Figure 1. Flow chart of key steps in protocol. Notice that purified phosphatase after step B and mounted tissues after step F can be stored frozen, constituting possible breakpoints in the procedure.
S2 cell transfection
Note: All steps should be done in a biosafety cabinet.
Prepare S2 cell media + 10% FBS (see Recipe 1).
Revive S2 cells following DGRC instructions, available at https://dgrc.bio.indiana.edu/include/file/general_maintenance.pdf.
Maintain cells in a 25 °C incubator at a density between 2 × 106 and 1 × 107 (6 mL final volume) in a 25 cm2 flask.
Transfect and harvest S2 cells using the following 5-day protocol.
Day 1: Passage cells into a new 25 cm2 flask.
Day 2: Count the cells that were passaged on day 1.
Determine cell density using CountessTM automated cell counter.
Plate 2 × 106 cells per well of a six-well plate in 2.5 mL final volume.
Day 3: Transfect S2 cells.
Warm transIT-2020 reagent to room temperature and vortex gently.
Pipette 250 µL of serum-free Schneider’s Drosophila medium into a microfuge tube.
Pipette 2.5 µg of DNA of phosphatase expression plasmid (pPuro-MT-Nil-Twin-streptag) to media in step b and mix gently.
Pipette 7.5 µL of TransIT-2020 into the DNA/media mixture and mix gently.
Incubate at room temperature for 30 min.
Pipette transfection mixture dropwise to cells plated on day 2 and cover entire well.
Swirl plate gently to mix.
Place six-well plate in 25 °C incubator.
Select for transfected cells using puromycin (optional).
Allow transfected cells to recover for 48 h.
Prepare a 10 mg/mL puromycin solution in water.
Transfer cells from six-well plate to a 25 cm2 flask; add S2 cell media up to a final volume of 6 mL.
Allow cells to grow until confluent.
Remove S2 cell media and floating cells and transfer to new 25 cm2 flask.
Allow cells to grow to reach confluency.
Keep as a backup if the first selection fails.
Begin selection of confluent cells by adding 6 mL of fresh S2 cell media + puromycin [10 µg/mL final concentration (see Recipe 3)].
Remove S2 media every two days and add fresh S2 cell media + 10 µg/mL puromycin.
Be sure to remove all floating debris.
Monitor cell death daily using inverted microscope.
Continue selection with 10 µg/mL puromycin until 90%–95% of cells are dead.
Add fresh S2 cell media + 2 µg/mL puromycin to the few remaining cells and allow the transfected cells to grow until confluent. This may take 2–3 weeks. Maintain selected cells at normal density with 2 µg/mL puromycin after selection is complete.
Plate 2.5 × 106 cells (2.5 mL) per well in a six-well plate to be induced.
Day 4: Induce phosphatase expression from pMT plasmid for 24 h. Pipette 2.5 µL of a 0.7 M CuSO4 solution (see Recipe 4) to each well with transfected cells.
Day 5: Harvest cells after 24 h of induction.
Dislodge cells by pipetting the medium up and down.
Transfer cell suspension to a 15 mL conical centrifuge tube.
Centrifuge 5 min at 1,000 × g at room temperature.
Remove supernatant.
Wash cells by suspending in 1 mL of 1× PBS (see Recipe 2).
Transfer cell suspension to a 1.5 mL microfuge tube.
Centrifuge 5 min at 1,000 × g at room temperature.
Remove supernatant.
Freeze cells at -80 °C or proceed to protein purification.
Nil protein purification
Prepare lysis buffer (see Recipe 5).
Add 1 mL of lysis buffer to cell pellet and suspend cells by pipetting up and down.
Incubate cells/lysis buffer at 4 °C for 1 h with rotation.
Centrifuge homogenate at 20,000 × g and 4 °C for 20 min.
Wash 20 µL MagStrep “type3” XT magnetic beads three times with lysis buffer.
Transfer lysate to washed beads.
Incubate beads/lysate for 1 h at 4 °C with rotation.
Prepare biotin elution buffer (see Recipe 7). Warm to 37 °C.
Wash beads three times with 500 µL lysis buffer.
Add 25 µL of biotin elution buffer to beads.
Incubate 10 min with occasional mixing/vortexing.
Remove beads from eluate using magnetic microfuge tube rack.
Aliquot eluate containing phosphatase (5 µL each) and store at -20 °C.
Quantify phosphatase concentration.
Mix 10 µL of eluates with 10 µL of 2× Laemmli sample buffer and DTT to 0.1 M.
Prepare serial dilutions of BSA in 20 µL of 1× Laemmli sample buffer ranging from 1 µg–0.1 ng. Include DTT to 0.1 M.
Boil samples for 3 min at 100 °C.
Load eluate samples and BSA dilution series samples on a 10% protein gel.
Run gel for 1 h at 150 V in electrophoresis chamber.
Transfer protein contents from gel onto a nitrocellulose membrane using blotting system.
Stain membrane with a total protein stain.
Image membrane with a Western blot scanner.
Use software associated with Western blot scanner to quantify BSA and eluate bands.
Determine eluate protein concentration by comparing quantification of band of interest to those of BSA serial dilutions.
In situ dephosphorylation assay
Dissect third instar larvae in 300 µL of ice-cold 1× PBS (see Recipe 2) under a dissecting microscope on a silicone dish. Gently hold the larva at the middle with forceps and firmly hold the larval mouth hooks with other forceps. Then, pull the mouth parts away from the rest of the body to get a single mass of brain with attached eye-antennal imaginal discs and salivary glands, as well as other tissues (larval carcass). For a comprehensive description of such dissection see the video in Hsiao et al. (2012).
Fix 10–15 larval carcasses in a 200 µL drop of periodate-lysine-paraformaldehyde for 20 min on the same silicone dish (at room temperature; no shaking required) (see Recipe 12 for fixative preparation).
Transfer fixed larval carcasses in a well of a 96-well plate with 200 µL of PBS and wash for 10 min with gentle rotation on an orbital shaker.
For each of the following washes and incubations, gently use forceps to move carcasses into the next well on the 96-well plate with the indicated solution, and then incubate on an orbital shaker with gentle rotation unless otherwise specified.
Wash two times in 200 µL of 1× PBS for 10 min (see Recipe 2).
Permeabilize larval carcasses in 200 µL of PBSS (PBS + 0.3% saponin) for 10 min.
Repeat the previous step one more time.
Wash fixed and permeabilized tissues twice in 200 µL of 1× PBS for 10 min.
Treat larval carcasses with 50 ng of wild-type Nil phosphatase without or with 100 µM CdCl2 or with 50 ng of the inactive NilD231N phosphatase in 100 µL of phosphatase assay buffer (see Recipe 15), for 3 h in 37 °C incubator. Nil, like other metal-dependent phosphatases, including its human homologs PPM1A/B, is potently inhibited by cadmium (Kamada et al., 2020; Nandi et al., 2022).
Wash phosphatase-treated larval carcasses three times in 200 µL of 1× PBS for 10 min.
To block unspecific antibody binding, incubate larval carcasses in PBSS + 5% normal goat serum for 30 min.
Stain blocked larval carcasses with primary antibody (phospho-specific antibody for pS437-acinus raised in rabbit, 1:1,000) in 200 µL of PBSS + 5% normal goat serum overnight at room temperature on an orbital shaker. Cover wells with parafilm for overnight incubation.
Wash antibody-stained tissues four times in PBSS for 10 min to remove unbound primary antibody.
Stain blocked larval carcasses with goat anti-rabbit IgG (H+L) cross-adsorbed secondary antibody (1:500) in PBSS + 10% normal goat serum for 3 h in the dark at room temperature.
Note: Protect specimen from unnecessary light exposure during and after secondary antibody staining with aluminum foil.
Wash secondary antibody–stained tissues four times in PBSS for 10 min to remove unbound secondary antibody.
Add a small drop of Vectashield with DAPI to a microscope slide. Mount eye discs from the stained larval carcasses in that Vectashield with DAPI. DAPI stains the nuclei.
Slowly lower the coverslip onto the drop of Vectashield in which eye discs are mounted. Take care to minimize air bubbles.
Seal the edges of the coverslip to the slide with clear nail polish.
Store slides in the dark at -20 °C until imaging.
Image eye discs on a confocal microscope with a 63× objective for pS437-Acn staining. Acquire Confocal Z-stacks at 1 µm step size using Zen software.
Data analysis
To examine pS437-Acn staining in larval eye discs with different phosphatase treatments, open confocal images with ImageJ and smooth with a Gaussian blur of one. Generate Z-projection of three optical sections of eye discs encompassing mainly photoreceptor cells and examine pS437-Acn level in eye discs. Repeat experiments at least three times with three samples each. In complex tissues, such as eye imaginal discs, take care to select equivalent regions of interest for quantification (see Figure 2 for an example).
Figure 2. In situ dephosphorylation of acinus. (A) Micrographs of representative eye imaginal discs, treated with (+) or without (-) Nil phosphatase and stained for pS437-Acn and DNA, as indicated. Yellow squares point to equivalent regions of interest, just posterior to the morphogenetic furrow. (B) Quantification of pS437-acinus staining from three different eye discs.
Recipes
S2 Cell Media
500 mL of S2 cell media and 50 mL of FBS. Assemble 500 mL vacuum filter/storage bottle and connect to vacuum. Filter S2 cell media and FBS into storage container. Store at 4 °C.
1× PBS
137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, and 2 mM KH2PO4. Adjust pH to 7.4 with HCl before finalizing volume with water. Autoclave and store at room temperature.
Puromycin dihydrochloride (10 mg/mL)
Dissolve 100 mg of puromycin dihydrochloride in 10 mL of ddH2O. Aliquot and store at -20 °C.
0.7 M CuSO4
Combine 174.78 g of cupric sulfate pentahydrate and water up to 1 L. Autoclave and store at room temperature.
Lysis buffer
50 mM Tris pH 8.0, 150 mM NaCl, 1.0% NP40, 0.1 mM PMSF, 1× protease inhibitor, and 1× phosphatase inhibitor. Add water to desired volume. Store at 4 °C.
2× stock phosphatase assay buffer (used in biotin elution buffer and phosphatase assay buffer below)
100 mM Tris-HCl (pH 7.5), 80 mM NaCl, and 0.2 mM EGTA. Store at 4 °C.
Biotin elution buffer
Add 0.12 g of biotin to 5 mL of 2× stock phosphatase assay buffer. Adjust pH to 8.0 with 1 M NaOH to dissolve biotin. Add dH2O to final volume of 10 mL. Store at 4 °C.
8% paraformaldehyde
Heat 200 mL of ddH2O to 55 °C. Add two drops of 50% w/w NaOH. Add 20 g of paraformaldehyde and stir continuously until solution is clear. Do not exceed 60 °C. Filter through vacuum filter/storage bottle. Top off to 250 mL. Aliquot and freeze at -80 °C.
0.4 M Sorenson's phosphate buffer stock
Dissolve 7.176 g of sodium phosphate monobasic monohydrate in 100 mL of ddH2O.
Dissolve 49.4 g of sodium phosphate in 750 mL of ddH2O.
Combine the two solutions above and top off to 1 L with ddH2O. The resulting solution should have a pH of 7.6.
Autoclave and store at room temperature.
Dilute to 0.1 M by adding 3 volumes of ddH2O before use.
0.1 M di-sodium hydrogen phosphate buffer
Dissolve 14.196 g of Na2HPO4 in 1 L of ddH2O final volume. Autoclave and store at room temperature.
Lysine stock
Dissolve 16.4 g of L-Lysine in 300 mL of ddH2O. Adjust pH to 7.4 by adding 0.1 M Na2HPO4.
Add ddH2O to 450 mL. Add 0.1 M Sorenson's phosphate buffer to 900 mL. Aliquot and store at -80 °C.
Periodate-lysine-paraformaldehyde fixative
Note: Always make fresh.
Mix 3 mL of 0.1 M lysine solution with 1 mL of 8% paraformaldehyde/H2O.
Add 10 mg of sodium meta-periodate.
This makes the following final concentrations:
2% paraformaldehyde, 0.01 M Na meta periodate, 0.075 M lysine, and 0.035 M phosphate buffer.
10% saponin
10 g of saponin dissolved in 100 mL of deionized water. Aliquot and store at -20 °C.
1 M DTT
Combine 1.55 g of DTT with 10 mM sodium acetate, pH 5.2, to a final volume of 10 mL. Completely dissolve DTT, aliquot, and store at -20 °C.
Phosphatase assay buffer
Note: Always make fresh.
500 µL of 2× stock phosphatase assay buffer
1 µL of 1 M DTT
40 µL of 1 M MnCl2
40 µL of 1 M MgCl2
1 µL of 0.1 M PMSF
10 µL of 100× HaltTM protease inhibitor single-use cocktail (EDTA-free)
408 µL of dH2O
This makes the following final concentrations:
40 mM MgCl2, 40 mM MnCl2, 50 mM Tris pH 8.5, 40 mM NaCl, 0.1 mM EGTA, 1× EDTA-free protease inhibitor, and 0.1 mM PMSF.
Acknowledgments
We thank Zuhair Zaidi for help with original analysis of the nil phenotype. This work was funded by NIH grants R01EY010199 and R01AI155426.
This protocol was derived from the original research paper "A phosphoswitch at acinus-serine(437) controls autophagic responses to cadmium exposure and neurodegenerative stress" (Nandi et al., 2022).
Competing interests
We declare no competing interest.
References
Berndsen, K., Lis, P., Yeshaw, W. M., Wawro, P. S., Nirujogi, R. S., Wightman, M., Macartney, T., Dorward, M., Knebel, A., Tonelli, F., et al. (2019). PPM1H phosphatase counteracts LRRK2 signaling by selectively dephosphorylating Rab proteins.Elife 8: e50416.
Chida, T., Ando, M., Matsuki, T., Masu, Y., Nagaura, Y., Takano-Yamamoto, T., Tamura, S. and Kobayashi, T. (2013). N-Myristoylation is essential for protein phosphatases PPM1A and PPM1B to dephosphorylate their physiological substrates in cells. Biochem J 449(3): 741-749.
Doherty, J. and Baehrecke, E. H. (2018). Life, death and autophagy. Nat Cell Biol 20(10): 1110-1117.
Haberman, A. S., Akbar, M. A., Ray, S. and Krämer, H. (2010). Drosophila acinus encodes a novel regulator of endocytic and autophagic trafficking. Development 137(13): 2157-2166.
Hsiao, H.Y., Johnston, R.J., Jr., Jukam, D., Vasiliauskas, D., Desplan, C., and Rister, J. (2012). Dissection and immunohistochemistry of larval, pupal and adult Drosophila retinas. J Vis Exp 69: 4347.
Kamada, R., Kudoh, F., Ito, S., Tani, I., Janairo, J. I. B., Omichinski, J. G. and Sakaguchi, K. (2020). Metal-dependent Ser/Thr protein phosphatase PPM family: Evolution, structures, diseases and inhibitors. Pharmacol Ther: 107622.
Levine, B. and Kroemer, G. (2019). Biological Functions of Autophagy Genes: A Disease Perspective.Cell 176(1-2): 11-42.
Murachelli, A.G., Ebert, J., Basquin, C., Le Hir, H., and Conti, E. (2012). The structure of the ASAP core complex reveals the existence of a Pinin-containing PSAP complex. Nat Struct Mol Biol 19(4): 378-386.
Nandi, N., Tyra, L. K., Stenesen, D. and Krämer, H. (2017). Stress-induced Cdk5 activity enhances cytoprotective basal autophagy in Drosophila melanogaster by phosphorylating acinus at serine(437). Elife 6: pii: e30760.
Nandi, N., Zaidi, Z., Tracy, C. and Krämer, H. (2022). A phosphoswitch at acinus-serine(437) controls autophagic responses to cadmium exposure and neurodegenerative stress. Elife 11: e72169.
Tyra, L. K., Nandi, N., Tracy, C. and Krämer, H. (2020). Yorkie Growth-Promoting Activity Is Limited by Atg1-Mediated Phosphorylation.Dev Cell 52(5): 605-616.e607.
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4,514 | https://bio-protocol.org/en/bpdetail?id=4514&type=0 | # Bio-Protocol Content
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Human Skin Explant Preparation and Culture
JS Jessica L. Shannon
SK Stephen J. Kirchner
JZ Jennifer Y. Zhang
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4514 Views: 2144
Reviewed by: Giusy TornilloDongsheng JiangGiovanna Piovani
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Original Research Article:
The authors used this protocol in Stem Cell Reports Mar 2022
Abstract
The ex vivo experimentation with surgically discarded human skin represents a unique methodology amenable for mechanism and pharmacologic agent studies without the involvement of human subjects. Here, we describe a protocol that includes preparation, culture, and stimulation of human skin explants, and subsequent analyses by quantitative reverse transcription PCR and immunostaining. This protocol may also be applied for ex vivo studies of murine skin, reducing animal numbers and potentially harmful treatments. In our hands, this protocol has been used for wound healing, viral infection, and hair growth–related studies.
Graphical abstract:
Cartoon of explant skin culture. Skin explant sits on top of a gelatin surgical sponge saturated with culture medium at an air–liquid interface.
Keywords: Human skin Tissue explant Organ culture Ex vivo Cutaneous immunity Cutaneous wound healing
Background
Genetic animal models are powerful in recapitulating complex tissue environment with intact circulation. Mice are by far the most frequently used animal for gene function, disease modeling, and pharmacological studies. However, murine skin and human skin are architecturally different and show differences in their responses to injury (Zomer and Trentin, 2018). It is not surprising that findings using murine skin often need corroboration in human skin models that harbor tissue-resident immune cells (Zomer and Trentin, 2018).
Significant technical advances have been achieved in epidermal keratinocyte culture in vitro, allowing procurement and expansion of primary keratinocytes. However, monolayer cell culture does not always recapitulate in vivo processes and often lacks tissue-resident immune cells. The organotypic cell culture model generated with primary or immortalized keratinocytes allows three-dimensional epidermal stratification and incorporation of certain dermal cells such as fibroblasts (Smits et al., 2017). Each of these methods has limitations in recapitulating skin biology.
Our lab has adapted a protocol for using surgically discarded human skin samples for ex vivo studies (Shannon et al., 2022), such as wound assays, cytokine stimulation, and viral infections. The protocol described below includes necessary materials, reagents, equipment, and procedures.
Materials and Reagents
1.7 mL microtube (Genesee Scientific, catalog number: 22-281LR)
SURGIFOAM® absorbable gelatin sponge (Ethicon, catalog number: 1969)
12-well cell culture plates, flat bottom wells, TC-treated (GenClone 25-106)
Sterile 1× phosphate buffered saline (PBS) (Gibco, catalog number: 14190144)
Penicillin–streptomycin–glutamine (100×) (Gibco, catalog number: 10378016)
EpiLifeTM CF kit (Gibco, catalog number: MEPICF500)
Note: This kit contains 500 mL of EpiLifeTM calcium-free media and 500 μL of 0.06 M CaCl2 (see Recipes).
Human keratinocyte growth supplement (HKGS, 100×) (Gibco, catalog number: S0015)
Adwin scientific Tissue-Tek Cryomold, intermediate (Fisher Scientific, catalog number: NC9511236)
Tissue-Tek optimum cutting temperature (OCT) compound (VWR, catalog number: 25608-930)
Rat anti-human Integrin α6 CD49f antibody (BioLegend, catalog number: 313602, diluted 1:500)
Alexa Fluor 647-conjugated goat anti-rat secondary antibody (BioLegend, catalog number: 313609). Diluted 1:400
Prolong Gold antifade reagent (ThermoFisher Scientific, catalog number: P36930)
TRIzolTM reagent (ThermoFisher Scientific, catalog number: 15596026)
Hoechst 33342, trihydrochloride, trihydrate (ThermoFisher Scientific, catalog number: H3570)
iScripTM cDNA synthesis kit (Bio-Rad, catalog number: 1708891)
Culture medium (see Recipes)
Wash buffer (see Recipes)
70% ethanol (see Recipes)
Equipment
CO2 incubator (Panasonic, model: MCO-170AICUVL-PA)
Technocut® disposable scalpels, sterile, MYCO Medical, No. 20 (VWR, catalog number: 10148-894)
Forceps (VWR, catalog number: 89259-946)
Surgical scissors (VWR, catalog number: 76192-134)
Pipettes (ThermoFisher Scientific, model: FinnpipetteTM F2 variable volume pipettes, catalog number: 4701070)
Olympus IX73 fluorescent microscope (Olympus Corporation Microscopy Technologies)
Nanodrop 1000
-80 °C freezer
Leica Cryocut 1800
Procedure
Solution Preparation
Note: The following steps should be completed in a biosafety cabinet with laminar flow to maintain sterility. Wipe all containers and reagents with 70% ethanol prior to placement in the laminar flow tissue culture hood and use sterile technique during all steps.
Wash buffer (see Recipe 1)
Prepare wash buffer by diluting 100× penicillin–streptomycin–glutamine (100×) 1:100 in 1× PBS.
Culture medium (see Recipe 2)
Skin Preparation
Note: Surgically excised skin should be maintained at 4 °C and used as soon as possible after removal.
Remove subcutaneous fat from skin using forceps and wash with PBS containing 1× concentration of penicillin–streptomycin–glutamine (Shannon et al., 2022).
Use a scalpel to carefully trim off laser-cut edges from surgical excised skin sample.
Prepare 12-well culture plates with 0.5–1.0 mL of EpiLifeTM CF media (supplement free) with 2 cm × 2 cm surgical gelatin sponge. Allow foam to absorb media (MacLeod et al., 2013; Shannon et al., 2022). The culture media should completely saturate the surgical sponge and fill the well by approximately 25%.
Cut tissue into 1 cm × 1 cm squares and place skin, dermis side-down, on gelatin sponge squares pre-saturated with culture media (prepared in step B3). Ensure the epidermis maintains an air interface and that the dermis has contact with the media-soaked sponge. The tissue should not be submerged in media.
Incubate tissue at 37 °C and 5% CO2.
Change media every 2–3 days by aspirating media from the well using a 1 mL sterile serological pipette. Avoid any contact between the aspiration tip and the gelatin sponge by gently tilting the plate to pool media from the bottom. Add fresh media to the well without disturbing the gelatin sponge and skin explant and ensure that the skin maintains in air–liquid interface.
Skin explants can be maintained in this fashion for up to four weeks (Companjen et al., 2001; Steinstraesser et al., 2009).
Note: Successful use of skin explant for wound healing studies has been reported up to two weeks, though epidermal thickening is evident in ex vivo skin cultures within the first week (Xu et al., 2012; Neil et al., 2020), and epidermal barrier function is reported to remain intact for up to four weeks (Steinstraesser et al., 2009). However, tissue viability decreases over time. It is important to optimize culture conditions and experimental parameters.
Ex vivo Wounding
To generate ex vivo wounds, hold scissors vertically to inflict 20–30 cuts to skin tissue. Do not mince the tissue: these wounds should be shallow, and each cut should be approximately half the length of the explant.
Note: Incisional wounds may not be immediately obvious by the naked eye.
Wounded samples should be collected within 24 h using Trizol reagent for RNA extraction or snap frozen in OCT compound for immunofluorescence staining.
Cytokine Stimulation
If cytokine stimulation is necessary, prepare media supplemented with cytokines of choice [e.g., IL-1β (Companjen et al., 2001), IL-15, or IL-27 (Suwanpradid et al., 2021)] and add 0.5–1.0 mL per well as described in step B3.
Carefully transfer explant to the freshly prepared 12-well plate without allowing media to touch the epidermal surface.
Skin can be collected and carefully removed from the gelatin sponge within two days after cytokine treatment.
Tissue Collection
Immunostaining
Cut tissue into 2 mm × 2 mm squares and place the skin with dermis side down in the bottom of an intermediate Tissue-Tek cryomold.
Slowly add OCT compound to cover the tissue sample, avoiding bubbles.
Pop any bubbles with a 10 µL pipette tip if necessary.
Allow the OCT to settle on a flat surface at room temperature for 10 min.
Snap freeze the tissue by resting cryomold on dry ice on a flat surface until frozen.
Store the frozen OCT blocks in a -80 °C freezer until use.
For immunostaining, 7–10 µm thick cryo-sections containing both epidermis and dermis are obtained from the OCT blocks using a Cryostat.
RNA analysis
Mince tissue thoroughly using scissors and transfer minced tissue to a clean microcentrifuge tube containing at least 800 μL of Trizol reagent for each explant.
Vortex sample and incubate at room temperature for 5–15 min to allow tissue lysis by Trizol.
Centrifuge tubes containing the lysed tissues at 12,000 × g for at least 10 min at 4 °C. Carefully transfer supernatant to a clean tube for standard RNA isolation techniques, such as ethanol precipitation or commercially available kits designed for RNA extraction.
Example results
Immunostaining
Following the methods described above, generate ex vivo wounds on human tissue for 24 h and freeze in OCT compound. Warm 8 µm sections to room temperature prior to fixation with 4% paraformaldehyde for 15 min and permeabilization with 0.1% Triton for 15 min.
Incubate sections with the rat anti-human Integrin α6 CD49f antibody overnight at 4 °C in a moist chamber.
Wash slides with PBS with 0.1% Triton, and incubate for 1 h with Alexa Fluor 647-conjugated goat anti-rat secondary antibody (diluted 1:400).
After subsequent washing, stain nuclei using Hoechst diluted 1:10,000 for 10 min.
Mount slides using Prolong Gold antifade reagent and cover with a coverslip prior to imaging on a fluorescent microscope (Figure 1).
Figure 1. Immunostaining for integrin α6 (ITGA6/CD49f, magenta) in human skin explants that were wounded ex vivo and cultured for 24 h. Tissues were sectioned to 8 μm thickness. Scale bars = 50 μm.
RT-qPCR
Isolate total RNA from Trizol reagent per the manufacturer’s instructions, followed by treatment with DNase I.
Quantify RNA using Nanodrop 1000 and generate cDNA using cDNA synthesis kit. Amplification is detected using Fast SYBR Green Master Mix (Applied Biosystems) or SYBR green blue (PCR biosystems); 10 ng cDNA is used per qPCR reaction.
Perform qPCR with the following primers:
Gene Forward (5’-3’) Reverse (3’-5’)
S100a7 CCTGCTGACGATGATGAA TGGCTCTGCTTGTGGTAG
GAPDH ATGGGAAGGTGAAGGTCGGA CAGCGTCAAAGGTGGAGGAGT
Use GAPDH expression as internal control (see primer sequences).
Normalize fold changes calculated for gene expression in human samples to untreated or unwounded controls, as indicated. Data are represented as fold change or using ΔΔCt method as indicated (Figure 2).
Figure 2. qPCR showing relative mRNA levels of S100a7 in response to ex vivo wounding (W) 24 h after injury (A) or topical treatment with 100 ng of thymic stromal lymphopoietin (TSLP) for 16 hours (B). Data presented are from four independent experiments using two different human donors in technical duplicate. Error bars represent ± SEM. Statistical analysis was performed using the two-tailed unpaired Student’s t-test, under the untested assumption of normality. A p-value of <0.05 was considered statistically significant; **: p < 0.01 and ****: p < 0.0001.
Recipes
Wash Buffer
Reagent Final concentration Amount
1× phosphate buffered saline 1× 495 mL
100× penicillin–streptomycin–glutamine 1× 5 mL
Total n/a 500 mL
Culture Medium
Thaw one vial containing 5 mL of 100× HKGS to room temperature and gently swirl to mix.
Swirl 0.5 mL of 0.06 M calcium solution to mix (included in EpiLifeTM CF kit).
Wipe the outside of the containers with 70% ethanol to sanitize prior to moving to tissue culture hood.
Draw 5 mL of 100× HKGS and add to 495 mL of EpiLifeTM calcium free medium.
Slowly add calcium stock to 500 mL of medium to reach a final concentration of 0.06 mM Ca2+.
Store unused solution at 4 °C for up to one month.
70% ethanol
Reagent Final concentration Amount
Ethanol (absolute) 70% 700 mL
H2O n/a 300 mL
Total n/a 1,000 mL
Acknowledgments
We would like to thank Jutamas Suwanpradid and Yingai Jane Jin of Duke University for protocol development. This work is in part supported by NIH/NIAID grant R01-AI139207 and NIH/NIAMS grant R01-AR068991 and the Department of Dermatology at Duke University. This protocol was adapted from methods described in previous publications (Macleod et al., 2013; Shannon et al., 2022).
Competing interests
All authors declare no competing interests.
Ethics
Normal skin samples were obtained from otherwise discarded and deidentified tissues of adult male and female patients undergoing abdominoplasty at Duke University Medical Center. All human samples for this study were obtained according to the protocols approved by the Institutional Review Board at Duke University.
References
Companjen, A. R., van der Wel, L. I., Wei, L., Laman, J. D. and Prens, E. P. (2001). A modified ex vivo skin organ culture system for functional studies. Arch Dermatol Res 293(4): 184-190.
MacLeod, A. S., Hemmers, S., Garijo, O., Chabod, M., Mowen, K., Witherden, D. A. and Havran, W. L. (2013). Dendritic epidermal T cells regulate skin antimicrobial barrier function. J Clin Invest 123(10): 4364-4374.
Neil, J. E., Brown, M. B. and Williams, A. C. (2020). Human skin explant model for the investigation of topical therapeutics. Sci Rep 10(1): 21192.
Shannon, J. L., Corcoran, D. L., Murray, J. C., Ziegler, S. F., MacLeod, A. S. and Zhang, J. Y. (2022). Thymic stromal lymphopoietin controls hair growth. Stem Cell Reports 17(3): 649-663.
Smits, J. P. H., Niehues, H., Rikken, G., van Vlijmen-Willems, I., van de Zande, G., Zeeuwen, P., Schalkwijk, J. and van den Bogaard, E. H. (2017). Immortalized N/TERT keratinocytes as an alternative cell source in 3D human epidermal models. Sci Rep 7(1): 11838.
Steinstraesser, L., Rittig, A., Gevers, K., Sorkin, M., Hirsch, T., Kesting, M., Sand, M., Al-Benna, S., Langer, S., Steinau, H. U., et al. (2009). A human full-skin culture system for interventional studies. Eplasty 9: e5.
Suwanpradid, J., Lee, M. J., Hoang, P., Kwock, J., Floyd, L. P., Smith, J. S., Yin, Z., Atwater, A. R., Rajagopal, S., Kedl, R. M., et al. (2021). IL-27 Derived From Macrophages Facilitates IL-15 Production and T Cell Maintenance Following Allergic Hypersensitivity Responses. Front Immunol 12: 713304.
Xu, W., Jong Hong, S., Jia, S., Zhao, Y., Galiano, R. D. and Mustoe, T. A. (2012). Application of a partial-thickness human ex vivo skin culture model in cutaneous wound healing study. Lab Invest 92(4): 584-599.
Zomer, H. D. and Trentin, A. G. (2018). Skin wound healing in humans and mice: Challenges in translational research. J Dermatol Sci 90(1): 3-12.
Article Information
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Biological Sciences > Biological techniques
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PG Patricia Gasalla *
CJ Claudia Jove *
AB Azucena Begega *
(*contributed equally to this work)
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4515 Views: 1088
Reviewed by: Edgar Soria-GomezWeiyan Jia Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Behavioral Neuroscience Jun 2017
Abstract
Feeding behavior is a complex experience that involves not only sensory (i.e., visual, odor, taste, or texture) but also affective or emotional aspects (i.e., pleasure, palatability, or hedonic value) of foods. As such, behavioral tests that assess the hedonic impact of foods are necessary to fully understand the factors involved in ingestive behavior. In this protocol, we use the taste reactivity (TR) test to characterize the hedonic responses of rats to flavors paired with either lithium chloride–induced nausea or internal pain produced by hypertonic NaCl, two treatments that reduce voluntary consumption. This application of the TR test demonstrates how emetic and non-emetic (somatic pain in particular) treatments produce dissociable patterns of hedonic reactions to fluids: only emetic treatments result in the production of aversive orofacial responses, reflecting conditioned nausea, whereas somatic pain produces immobility, reflecting conditioned fear. Other methods, such as the microstructural analysis of licking behavior, do not reliably distinguish conditioned nausea and fear, a key advantage of the more selective TR procedure. This protocol also contains guidance for adaptation to other species and designs.
Keywords: Taste aversion Hedonic responses Orofacial reactivity Nausea Internal pain Rats
Background
In rats, pairing a novel flavored solution with nausea produced by the administration of emetic drugs such as lithium chloride (LiCl) results in the subsequent reduction in consumption of that flavor, a learning phenomenon termed conditioned taste aversion (CTA) (see Reilly and Schachtman, 2009 for a review). Critically, not only does CTA result in decreased consumption of that flavor, but there is also evidence of a change in its palatability or hedonic qualities, as suggested by John Garcia, the pioneer in studying this learning phenomenon (Garcia et al., 1955). However, CTA is not exclusively produced by emetic treatments. Pairing flavors with a wide variety of other aversive events, including pain produced by footshock or injection of hypertonic saline, as well as the administration of many drugs of abuse, reliably produces reductions in voluntary consumption (e.g., Pelchat et al., 1983; Parker, 1995; Arthurs et al., 2012). Thus, one central issue in this protocol is whether emetic and non-emetic treatments produce the same sorts of behavioral affective reactions to fluids. The taste reactivity (TR) protocol we describe here can be generalized for many uses, including determining whether a novel substance or intervention is aversive because it produces pain or nausea (and similarly whether a treatment ameliorates pain/nausea). Additionally, this procedure is amenable to be adapted for studying the neural mechanisms of hedonic evaluation (Inui and Simura, 2017), or for examining the role of anhedonia in psychiatric and neurological disorders such as depression and schizophrenia (Ward et al., 2012).
The optimal method affording a direct assessment of the hedonic impact of flavors is the TR test (Grill and Norgren, 1978). This involves examining orofacial reactions—stereotyped oromotor and somatic consummatory responses—elicited during the intraoral infusion of the fluid in the rat’s oral cavity. These orofacial responses can be classified as aversive (e.g., gaping, chin rubbing, and paw treading), elicited when infused with unpleasant sour or bitter tastes, or appetitive (e.g., tongue protrusions, mouth movements, and paw licks), elicited by pleasant, sweet tastes. When infused with a palatable taste (e.g., saccharin) previously paired with LiCl-induced nausea, rats display aversive responses, reflecting a shift in the hedonic value of the flavor from positive to negative. Importantly, this technique is selective to disgust, in contrast to the reduction in consumption that may simply reflect taste avoidance without a change in affective responses. As mentioned above, pairing a flavor with peripheral pain or with rewarding drugs, such as cocaine or amphetamine, results in a reduction in subsequent voluntary consumption of that flavor, but not in the production of orofacial aversive responses (Parker, 1995). This dissociation in the impact of emetic drugs and other aversive events supports the suggestion that a reduction in fluid intake may be motivated by two different processes: a taste associated with nausea causes a reduction in its palatability (CTA), whereas a taste associated with a drug of abuse or peripheral pain is avoided because it signals a potential danger or a disturbance in homeostasis regulation [taste avoidance learning (TAL)] (see Parker 2003, 2014).
The hedonic value of flavors can also be examined by analyzing the microstructure of licking behavior during voluntary consumption (Davis, 1989; Dwyer, 2012). The ingestive behavior of rodents consuming fluids consists of sustained runs of licks separated by pauses of varying length (clusters); the mean number of licks in a cluster (lick cluster size) is directly related to the nature and concentration of the solution ingested. Lick cluster size shows a positive monotonic relationship to the concentration of palatable sweet solutions, decreasing monotonically with an increased concentration of unpalatable quinine solutions. In the context of taste aversion learning, pairing an otherwise palatable taste with nausea results in a reduction of lick cluster size, similar to that produced by exposure to quinine. However, reductions in cluster size cannot be unambiguously attributed to conditioned disgust (for example, these do not distinguish between the effects of hypertonic saline and isotonic lithium chloride as described here) in the absence of careful observation of orofacial behavioral reactions directly indicative of a particular emotional response. With this issue in mind, here we use the orofacial reactivity protocol to selectively characterize hedonic responses to flavors paired with either nausea or internal pain caused by injection of hypertonic saline.
Materials and Reagents
PE-160 intramedic polyethylene tubes (Becton Dickinson, MD, USA, catalog number: 427431) attached to an infusion pump, for intraoral infusion
15-gauge stainless steel needles (Kruuse, Denmark, catalog number: 120753), to implant intraoral cannula
Microlance 3 25 g × 5/8" hypodermic needles (Becton Dickinson, MD, USA, catalog number: 300600), for injection procedures
Animals: Wistar rats (280–393 g, male, 9 weeks old; University of Oviedo vivarium, Spain)
Fluids used for intraperitoneal injections: LiCl (0.15 M,10 mL/kg) (VWR Chemicals, catalog number: 25007-230), NaCl (1.5 M, 10 mL/kg), and isotonic saline (0.9%,10 mL/kg) (VWR Chemicals, catalog number 27810-262)
Flavor used for intraoral infusion: 0.1% (w/w) saccharin sodium (Sigma-Aldrich, Merck, catalog number: 47839)
Ketamine hydrochloride (50 mg/kg) (Sigma-Aldrich, Merck, catalog number: 1356009)
Medetomidine hydrochloride (0.15 mg/kg) (Sigma-Aldrich, Merck, catalog number: 1179333)
Ketoprofen (1.5 mg/kg) (Sigma-Aldrich, Merck, catalog number: 1356632)
Enrofloxacin (0.3 mg/kg) (Sigma-Aldrich, Merck, catalog number: 17849)
Chlorhexidine (0.3 mg/kg) (Sigma-Aldrich, Merck, catalog number: 282227)
PE-90 intramedic polyethylene tubes (Becton Dickinson, MD, USA, catalog number: 427519) for intraoral cannula
O-ring Mini Stix ligature ties (TP Orthodontics Inc., IN, USA, catalog number: 383-927), to hold securely the PE-90 tubes in the oral cavity
Injection syringes 1 mL (Becton Dickinson, catalog number: 309628) and 5 mL (BD, catalog number: 309646)
Equipment
Custom-made TR apparatus (see Figure 1)
Infusion pump (KD Scientific Inc, MA)
Video camera (Sony Optical 20×) connected to a desktop computer
Figure 1. Taste reactivity apparatus. Front view of the TR apparatus with the different components. (A) Infusion chamber. (B) Infusion pump. (C) Mirror at a 45° angle. (D) Video camera. (E) Computer. See Note 2 for a more detailed description of the apparatus.
Software
The Observer XT 9.0 (Noldus Information Technology, Sterling, VA) event-recording program, to score videos. This computer software is an automated system that makes it possible to record the behavior of animals directly in the TR chamber and code the sequence and duration of the behaviors exhibited in a quantitative way.
Procedure
See Figure 2 for a schema depicting the different steps of the protocol.
Figure 2. Behavioral protocol to investigate hedonic responses using the TR test.
House rats individually in standard (e.g., 42 × 26 × 20 cm) polycarbonate cages in a colony room under controlled standard conditions (12 h light/dark cycles starting at 8 am; ambient temperature of 21 °C). Always make food available in the home cages. Note that individual housing is to prevent rats from pulling out cannula from cage mates.
Cannulation surgery
Surgically implant rats with an intraoral cannula using the method described by Parker (1995) and as previously used in our laboratory (Gasalla et al., 2016, 2017). The cannulation procedure (see Figure 3) is described in detail in Note 4 below.
Monitoring and habituation
After recovery from the surgery, place rats on a water-restriction schedule, comprising 1 h daily access to water (given approximately 2 h after any experimental fluid exposure) and free access to food in the home cage. Home cage food and water intake can be monitored, but this is not essential. Then, habituate rats to the infusion procedure by delivering a 1 mL water infusion (rate of infusion 1 mL/min) in the TR apparatus.
Intraoral conditioning
The next four days constitute the conditioning phase. On these sessions, place rats in the TR apparatus (with their cannula attached to the infusion pump for fluid delivery). Intraorally infuse them with the saccharin solution for 2 min (1 mL/min) and deliver an injection of LiCl (group Lithium), hypertonic NaCl (group Hypertonic), or isotonic saline (group Isotonic), immediately after the intraoral infusion. Give the rats water-recovery days in the home cage after the second and fourth conditioning sessions. Video-record the orofacial responses displayed by the rats during the infusion of the saccharin solution.
Orofacial reactivity test
Perform a TR test the day after the last conditioning session. Deliver an intraoral administration of the saccharin solution for 2 min (1 mL/min) while video-recording the rats’ orofacial responses.
Figure 3. Cannulation procedure. The figure shows two steps of the cannulation procedure. (A) Insert a guide needle inside the mouth. (B) Insert the intraoral cannula through the needle. See Note 4 for a more detailed description of the cannulation procedure.
Scored orofacial reactions:
Appetitive responses: tongue protrusions (extension of the tongue out of the mouth), mouth movements (movement of the lower mandible without opening the mouth), and paw licks (midline extension of the tongue directed to the forepaws). Use the total number of seconds that the rats display the responses as the appetitive response score. For representative appetitive TR responses, see Figure 4A and Video 1 showing orofacial responses scored in this protocol.
Aversive responses: gaping (rapid–large amplitude opening of the mandible with retraction of the corners of the mouth), chin rubbing (mouth or chin in direct contact with the floor or wall of the chamber and body projected forward), paw treading (forward and backward movements of the forepaws in synchronous alternation), forelimb flails (rapid horizontal movements of the forelimbs to remove fluid from the fur), and head shakes (rapid side-to-side head movements with the mouth open in order to remove the fluid out of the mouth). Sum these scores to provide a total aversive response score (see Figure 4B and Video 1 for representative aversive responses).
Assess the percentage of time spent immobile over the infusion period (scored as suppression of all movements in the rat, with the exception of those required for respiration) as an index of conditioned fear. In addition, score the frequency of passive dripping (each occasion on which a drop of fluid is allowed to leak out of the mouth to the floor without other orofacial reactions; see Figure 4C and Video 1).
Figure 4. Representative orofacial reactivity responses. (A) Appetitive responses: tongue protrusion, paw licking, and lateral tongue protrusions. (B) Aversive responses: gaping, head shaking, chin rubbing, and forelimb flailing. (C) Passive responses: dripping and immobility (Based on Inui and Shimura, 2017).
Video 1. Orofacial responses video-recorded during the intraoral infusion of the flavor.
After completion of the behavioral procedures, score the videos using the Observer XT 9.0 event-recording program.
Data analysis
Separately analyze the responses (appetitive, aversive, passive dripping, and immobility) scored during the conditioning sessions and test with 3 (group) × 5 (session) mixed ANOVAs. Detailed information on data analyses appears in the original research article (Dwyer et al., 2017). Figure 5 shows representative results obtained in the research. Pairing a taste with either LiCl-induced nausea or internal pain reduced appetitive responses, but these two aversive events had clearly dissociable effects on other responses: only pairing with nausea results in the production of aversive orofacial responses to the taste, whereas pairing with internal pain results in the taste eliciting immobility and passive dripping. In addition, both nausea and internal pain reduced voluntary consumption of the paired flavor (data not shown).
Figure 5. Representative results of the intraoral conditioning (C1-C4) and test sessions. (A) Mean duration of appetitive orofacial responses. (B) Mean number of aversive orofacial responses. (C) Mean time spent immobile as a percentage of the total time tested. (D) Mean number of passive dripping events (adapted from Dwyer et al., 2017). Error bars represent the standard error of mean (SEM).
Notes
This protocol is designed for rats as subjects but is suitable for use with other rodents, including outbred mice (e.g., Kiefer et al., 1998), transgenic mice (e.g., Travers et al., 2007), and shrews (e.g., Parker, 2006).
The TR apparatus is made of clear Plexiglas sides (26 × 23 × 14 cm) with a dark lid, placed on a table with a clear Plexiglas top. Two 50 W white lights on each side of the table provided illumination. A mirror beneath the chamber at a 45° angle facilitated viewing/filming of the ventral surface of the rat during the intraoral infusion. Recording from this angle is essential to unambiguously observe the orofacial reactions, which can otherwise be obscured if the recording is from the side or above. As shown in Video 1, the recording should frame the head region of the animal as closely as possible.
For the purpose of anesthesia, the rats are intraperitoneally injected with ketamine (50 mg/kg) combined with medetomidine hydrochloride (0.15 mg/kg). After surgery, the rats are subcutaneously injected with the anti-inflammatory ketoprofen (1.5 mg/kg) and the antibiotic enrofloxacin (0.3 mg/kg).
In order to implant the cannula, a thin-walled 15-gauge stainless steel needle is inserted at the back of the neck, subcutaneously directly around the ear, and brought out behind the first molar inside the mouth. A length of Iintramedic polyethylene tube with an inner diameter of 0.86 mm and an outer diameter of 1.27 mm is then run through the needle, after which the needle is removed. Two square elastic discs are placed over the tubing and drawn to the exposed skin at the back of the neck with the purpose of stabilizing the cannula. The tubing is held secure in the oral cavity by an O-ring, which is sealed behind the tubing prior to cannulation surgery. Following surgery, rats are monitored for three days and have their cannula flushed daily with chlorhexidine (0.3 mg/kg) to prevent infection.
Fluids are administered to the rats through an infusion pump connected to the implanted cannula. While the rats are infused with the fluids, their orofacial responses are recorded using a video camera connected to a computer. Later, the videos are manually scored by two independent raters blind to the experiment using the event-recording program. An inter-rater reliability score for each response of at least 75% is deemed acceptable.
In the current protocol, appetitive and aversive responses are scored on different scales (duration vs. frequency) because they display very different properties: appetitive responses are typically displayed over extended periods of time, whereas aversive responses occur as isolated behaviors (see Berridge, 2000). Passive dripping and immobility are scored exclusively, such that time spent dripping is not also recorded as immobile. The different scales on which the responses are scored require each to be analyzed separately (as in the example described above). The TR analysis often uses a subset of the reactions (in particular, the “strong aversive” reactions of gaping, chin rubbing, and paw treading) to focus on clear aversive responses.
Parameters such as drug doses used for anesthesia and cannulation surgery, the volume of fluids administered, or the infusion rate during intraoral conditioning and testing are specific to the current experimental protocol. These procedural details may vary according to factors such as the weight of the rats or the species of rodent used in the study. Above, we specify an infusion rate of 1 mL/min over a period of 2 min. Higher infusion rates can be aversive due to the involuntary exposure to fluids at a rate higher than voluntary ingestion. Lower infusion rates are possible, although rates below 0.5 mL/min can result in insufficient solution exposure to elicit orofacial reactions. Longer infusion times are possible; however, infusion periods longer than 5 min tend to result in an increase in unconditioned passive and aversive responses. The use of multiple exposure sessions in the current protocol is required to track the acquisition of conditioned nausea and fear. When the TR test is used to probe unconditioned reactions (e.g., to palatable sucrose vs. unpalatable quinine), a single session per solution may be sufficient (especially if the exposure period is lengthened beyond the 2 min specified above).
As noted above, some procedural details of the TR method can be adapted for other species of rodents, in particular parameters such as the infusion rate and the amount of fluid infused. In mice and shrews, the infusion rate is usually 0.1 mL over a period of 1 min. Longer infusion rates generally induce more aversive reactions to sweet and bitter taste solutions in these rodents (Cagniard and Murphy, 2009).
Acknowledgments
This work was supported by grants from the Ministry of Science and Innovation of Spain (MCI20-PID-2019-104177GB-100) to A.B. and M.L. and the Regional Government of Asturias (FICYT-PCTI, FC-GRUPIN-IDI/2018/000182) to M.L., and by a Leverhulme Trust research grant to D.M.D. (ID/RPG-2014-342). We thank Begoña Díaz for technical support and the care of experimental animals. The current protocol is derived from our previous work (Dwyer et al., 2017).
Competing interests
The authors declare no competing financial and non-financial interests.
Ethics
This experimental protocol followed the current guidelines of the European Council Directive (210/63/UE) and Spanish regulation RD53/2013 regarding the care and use of laboratory animals.
References
Arthurs, J., Lin, J. Y., Amodeo, L. R., and Reilly, S. (2012). Reduced palatability in drug-induced taste aversion: II. Aversive and rewarding unconditioned stimuli.Behav Neurosci 126(3): 433-444.
Berridge, K. C. (2000). Measuring hedonic impact in animals and infants: Microstructure of affective taste reactivity patterns. Neurosci Biobehav Rev 24: 173-198.
Cagniard, B., and Murphy, N. P. (2009). Taste reactivity and its modulation by morphine and methamphetamine in C57BL/6 and DBA/2 mice. Physiol Behav 96(3): 412-420.
Davis, J. D. (1989). The microstructure of ingestive behavior. Ann NY Acad Sci 575(1): 106-119.
Dwyer, D. M. (2012). Licking and liking: The assessment of hedonic responses in rodents. Q J Exp Psychol 65(3): 371-394.
Dwyer, D. M., Gasalla, P., Bura, S., and López, M. (2017). Flavors paired with internal pain or with nausea elicit divergent types of hedonic responses.Behav Neurosci 131(3): 235-248.
Garcia, J., Kimeldorf, D. J., and Koelling, R. A. (1955). Conditioned aversion to saccharin resulting from exposure to gamma radiation. Science 122: 157-158.
Gasalla, P., Begega, A., Soto, A., Dwyer, D. M., and López, M. (2016). Functional brain networks underlying latent inhibition of conditioned disgust in rats.Behav Brain Res 315: 36-44.
Gasalla, P., Soto, A., Dwyer, D. M., and López, M. (2017). Blocking of flavor-nausea learning by non-flavor cues: Assessment through orofacial reactivity responses.J Exp Psychol Animal Learn Cogn 43(2): 171-182.
Grill, H. J., and Norgren, R. (1978). Taste reactivity test: I. Mimetic responses to gustatory stimuli in neurologically normal rats.Brain Res 143(2): 263-279.
Inui, T., and Shimura, T. (2017). Activation of mu-opioid receptors in the ventral pallidum decreases the negative hedonic evaluation of a conditioned aversive taste in rats. Behav Brain Res 320: 391-399.
Kiefer, S. W., Hill, K. G., and Kaczmarek, H. J. (1998). Taste reactivity to alcohol and basic tastes in outbred mice.Alcohol Clin Exp Res 22(5):1146-1151.
Parker, L. A. (1995). Rewarding drugs produce taste avoidance, but not taste-aversion. Neurosci Biobehav Rev 19(1): 143-151.
Parker, L. A. (2003). Taste avoidance and taste aversion: evidence for two different processes.Anim Learn Behav 31(2): 165-172.
Parker, L. A. (2006). The role of nausea in taste avoidance learning in rats and shrews. Auton Neurosci 125: 34-41.
Parker, L. A. (2014). Conditioned flavor avoidance and conditioned gaping: Rat models of conditioned nausea.Eur J Pharmacol 722: 122-133.
Pelchat, M. L., Grill, H. J., Rozin, P., and Jacobs, J. (1983). Quality of acquired responses to tastes by Rattus norvegicus depends on type of associated discomfort.J Comp Psychol 97(2): 140-153.
Reilly, S., and Schachtman, T. R. (2009). Conditioned taste aversion: Behavioral and neural processes. Oxford University Press, UK: Oxford.
Travers, J. B., Herman, K., Yoo, J., and Travers, S. P. (2007). Taste Reactivity and Fos Expression in GAD1-EGFP Transgenic Mice. Chem Senses 32 (2):129-137.
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Tissue-Specific, Genome-wide Mapping of R-loops in Drosophila Using MapR
JJ Juan Jauregui-Lozano
KC Kendall Cottingham
HH Hana Hall
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4516 Views: 1128
Reviewed by: Giusy TornilloMario RuizNingfei An
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Original Research Article:
The authors used this protocol in Aging Cell Feb 2022
Abstract
R-loops, or RNA:DNA hybrids, are structures that arise co-transcriptionally when a nascent RNA hybridizes back with the template ssDNA, leading to a displaced ssDNA. Because accumulation of R-loops can lead to genomic instability and loss of cellular homeostasis, it is important to determine the genome-wide distribution of R-loops in different physiological conditions. Current R-loop mapping strategies are based on R-loop enrichment—mediated by the S9.6 antibody, such as DRIP-seq, or by the exonuclease RNase H1, such as MapR—or the latest R-loop CUT&Tag, based on an artificial R-loop sensor derived from an RNase H1 sub-domain. Because some of these techniques often require high input material or expensive reagents, we sought to apply MapR, which does not require expensive reagents and has been shown to be compatible with low input samples. Importantly, we demonstrate that incorporation of improved CUT&RUN steps into the MapR protocol yields R-loop-enriched DNA when using low input Drosophila nuclei.
Graphical abstract:
Workflow for mapping tissue-specific, genome-wide R-loops in Drosophila. Purify GST-tagged and catalytically inactive RNase H1 tethered MapR enzymes, GST-ΔRH-MNase, and GST-MNase, from transformed E. coli. Perform tissue-specific nuclei immuno-enrichment from UAS-EGFP.KASH-Msp300 Drosophila using magnetic bead–bound green fluorescent protein (GFP) antibody. Incubate isolated nuclei with MapR enzymes and activate MNase DNA cleavage with low salt/high calcium buffers. Purify released, R-loopenriched DNA fragments and generate sequencing-ready libraries. Align MapR data to reference genome and compare R-loop enrichment peaks in genome browser.
Keywords: R-loop Drosophila Bioinformatics MapR Neurons
Background
R-loops are RNA:DNA hybrids that mostly form during transcription as a result of a nascent RNA strand annealing to a template DNA strand while misplacing a single-stranded DNA. R-loops play an important role in biological processes such as class switch recombination and mitochondrial replication. However, persistent or un-scheduled R-loop formation is a major source of spontaneous DNA damage that can lead to genome instability, one of the key hallmarks of aging (García-Muse and Aguilera, 2019). R-loop resolution is particularly important for neuronal function, as mutations in the R-loop processing factors are associated with neurodegenerative disorders such as Aicardi–Goutières syndrome, ataxia with oculomotor apraxia, and amyotrophic lateral sclerosis (Becherel et al., 2015; Lim et al., 2015; Salvi and Mekhail, 2015). Strategies to map R-loops are based on using either the S9.6 antibody, the RNase H1 enzyme, or more recently, the RNase H1–derived N-terminal hybrid-binding domain (HBD) fused to a Tn5 (Wang et al., 2021). However, the majority of these methods can require high amounts of starting material, or extensive and expensive protocols.
Here, we modified a recently published method, called MapR, that uses the catalytically inactive ribonuclease H1 (RNase H1) enzyme to enrich for R-loops. MapR, which is based on CUT&RUN, utilizes an RNase H1 tethered to a micrococcal nuclease (MNase) for cleavage and release of R-loop-enriched DNA (Yan and Sarma, 2020). Because using the traditional MapR protocol with low input Drosophila samples led to over-digested DNA (Jauregui-Lozano et al., 2022), we adapted the MapR protocol with steps from an improved published CUT&RUN protocol, which incorporates low salt, high calcium buffers to decrease MNase activation time, as well as background binding (Meers et al., 2019). The main advantage of this approach is the ability to map R-loops where starting material is very limited, such as specific tissues or cells from the whole animal. Using this method, we show that Drosophila melanogaster photoreceptor (PR) neurons accumulate R-loops during aging, which correlates with decreased expression of genes with neuronal function and decreased visual function (Jauregui-Lozano et al., 2022). Thus, studies that combine cell-specific approaches provide us with a unique and powerful tool to map R-loops genome-wide and study R-loop-associated toxicity in the context of neuronal aging.
Materials and Reagents
5 or 15 mL conical tube
40 µm cell strainer (Corning, catalog number: 431750)
Slide-A-LyzerTM G2 dialysis cassettes, 10K MWCO, 3 mL (Thermo Fisher, catalog number: 87730)
PierceTM glutathione magnetic agarose beads (Thermo Fisher, catalog number: 78601). Keep at 4 °C
One Shot BL21 (DE3) chemically competent E. coli (Thermo Fisher, catalog number: C600003). Keep unused E. coli pellets at -80 °C
L-Glutathione reduced (Millipore Sigma, catalog number: G4251-300MG)
HyperPAGE II pre-stained protein marker (Bioline, catalog number: BIO-33066). Keep aliquots at -20 °C
DynabeadsTM protein G for immunoprecipitation (Invitrogen, catalog number: 10003D). Keep at 4 °C
Anti-GFP antibody (Sigma-Aldrich, catalog number: 11814460001). Keep at -20 °C upon resuspension
UAS-EGFP.KASH-Msp300 flies (Bloomington Drosophila Stock Center, BDSC#92580)
Digitonin 5% (Thermo Fisher, catalog number: BN2006)
UltraPureTM dithiothreitol (DTT) 0.1 M solution (Thermo Scientific, catalog number 707265ML)
UltraPureTM ethylenediaminetetraacetic acid, disodium salt, dihydrate (EDTA) (Thermo Fisher, catalog number: 15576028)
UltraPureTM 1 M Tris-HCl, pH 8.0 (Invitrogen, catalog number 15568025)
EGTA, molecular biology grade (Millipore, catalog number: 324626)
cOmpleteTM, mini, EDTA-free protease inhibitor cocktail tablets (Roche, catalog number: 04693159001)
Corning® 100 mL HEPES, liquid 1 M solution (238.3 mg/mL) (Corning, catalog number: 25-060-CI)
IGEPAL® CA-630 (Supelco, catalog number: 56741-50ML-F)
TWEEN® 20 (Sigma-Aldrich, catalog number: P1379)
Coomassie Brilliant Blue R-250 dye (Thermo Scientific, catalog number: 20278)
Acetic acid glacial, ReagentPlus® (Sigma-Aldrich, catalog number A6283)
Methanol, ACS reagent (Sigma-Aldrich, catalog number 179337)
Spermidine (Sigma-Aldrich, catalog number: S022-1G)
RNase A (Thermo Fisher, catalog number: 12091021)
Linear acrylamide (Thermo Fisher, catalog number: AM9520)
RNase H (New England BioLabs, catalog number M0297S). Keep at -20 °C
ChIP DNA Clean & Concentrator (Zymo, catalog number D5205)
QubitTM 1× dsDNA high sensitivity (HS) (Thermo Fisher, catalog number: Q33230)
Note: We recommend using high sensitivity assays since obtained DNA can be low-input and difficult to quantify using traditional reagents.
Ovation® ultralow V2 DNA-Seq library preparation kit (Tecan, catalog number: 0344NB-08)
GST-wash/equilibration buffer (see Recipes)
GST-elution buffer (see Recipes)
Coomassie fixing solution (see Recipes)
Coomassie staining solution (see Recipes)
Coomassie destaining solution (see Recipes)
Homogenization/wash buffer (see Recipes)
Dilution buffer (see Recipes)
Bead washing buffer (see Recipes)
PBST (1×, pH 7.4) (see Recipes)
Dig-wash buffer (see Recipes)
Low salt rinse buffer (see Recipes)
Activation buffer (see Recipes)
EGTA-STOP buffer (1×) (see Recipes)
Equipment
Branson sound amplifier
Agilent TapeStation 4200
WHEATON® Dounce tissue grinder, 1 mL
37 °C incubator with shaking platform (such as Thomas Scientific SCO2W benchtop water jacketed CO2 incubator, catalog number: 1229P58)
Cold (4 °C) centrifuge (such as EppendorfTM, model: Centrifuge 5424 R)
Cold (4 °C) incubator (such as FisherbrandTM mini low temperature refrigerated incubator, catalog number: 15-015-2632)
Tube revolver rotator (such as Thermo ScientificTM tube revolver rotator, catalog number: 88881001)
Magnetic rack (such as Millipore PureProteomeTM magnetic stand, catalog number: LSKMAGS08)
Gel electrophoresis chamber (such as Bio-Rad Mini-PROTEAN® tetra vertical electrophoresis cell, catalog number: 1658025FC)
Software
Genomic alignment of sequencing reads: Bowtie2 (Langmead and Salzberg, 2012)
BAM file processing: Samtools (Li et al., 2009)
Bigwig generation/processing: Deeptools (Ramírez et al., 2014)
Integrative genome browser (Thorvaldsdóttir et al., 2013)
Procedure
E. coli transformation and protein purification
For this protocol, we performed the E. coli transformation and protein overexpression induction as described in the original MapR method paper (Yan and Sarma, 2020). We also described these steps in Jauregui-Lozano et al. (2022).
Transform BL21 DE3 cells using 10 ng of plasmid and following manufacturer’s instructions from New England Biolabs.
Plate transformed cells in LB media plates overnight at 37 °C.
Pick a single colony and grow in liquid LB media supplemented with carbenicillin (1 μg/mL), at 37 °C and 225 rpm overnight.
The next day, add 4.5 mL of liquid culture into 495 mL of liquid LB media supplemented with carbenicillin and incubate for 2–4 h at 37 °C and 225 rpm. After 2 h of incubation, check optical density of an aliquot of liquid culture until it reaches 0.6 as measured with a spectrophotometer.
Induce protein expression by adding IPTG to a final concentration of 0.5 mM.
Incubate IPTG-containing liquid culture for 3 h at 37 °C and 225 rpm.
Prepare fresh GST-wash/equilibration buffer and GST-elution buffer.
Centrifuge bacterial lysate for 10 min at 8,000 × g in a cold centrifuge.
Remove supernatant and resuspend bacterial pellet in 5 mL of cold PBS buffer with cOmpleteTM protease inhibitor.
Sonicate using Branson sound amplifier with amplitude 20% and 5 cycles of 15 s on–45 s off. Make sure that the conical tube containing the bacterial lysate is on ice during sonication.
Centrifuge for 20 min at 4 °C and 13,000 × g.
Transfer soluble lysate to a new 5 or 15 mL conical tube.
Equilibrate 1 mL of PierceTM glutathione magnetic agarose beads GST by adding 1 mL of wash/equilibration buffer.
Vortex for 10 s, place on magnet, remove supernatant, and add 1 mL of wash/equilibration buffer.
Add DTT and EDTA to soluble lysate (final 1 mM for each).
Remove supernatant from beads and transfer the beads to soluble lysate.
Incubate for 1–2 h at 4 °C with constant rotation.
Using magnet, remove supernatant and add 1 mL of wash buffer. Save 20–50 μL of supernatant as “flowthrough” sample, to later use when running the SDS-page.
Incubate at 4 °C with constant rotation.
Remove wash buffer using magnet and repeat wash step two more times.
Remove wash buffer and add 250 μL of GST-elution buffer.
Incubate for 10 min at 4 °C with constant rotation.
Collect eluate #1 [e#1] and repeat elution step two more times.
To each 250 μL eluate, add 41 μL of 7× cOmpleteTM protease inhibitor previously resuspended in GST-elution buffer.
Run SDS-page with flowthrough and eluates to assess purification efficiency (Figure 1).
Figure 1. Coomassie-stained SDS page evaluating purification efficiency. Efficiency of GST protein purification was assessed using SDS-page followed by staining with Coomassie Blue. For flowthrough (FT), 20 μg of protein were loaded; for the elution fractions, 2 μg of protein were loaded. GST-ΔRH-MNase will have a size of ~60 kDa, while GST-MNase will have a size of ~40 kDa.
After running SDS-page, transfer gel into Coomassie fixing solution for 30 min, and place in a rocker.
Transfer fixed gel into Coomassie staining solution for 1 h and place in a rocker.
Transfer stained gel into Coomassie destaining solution for 20 min and place in a rocker.
Replace Coomassie destaining solution, and place in a rocker.
Repeat steps 28 and 29 two more times (for a total of 1 h 20 min destaining). GST-MNase will have a molecular weight close to 40 kDa, and GST-ΔRH-MNase close to 60 kDa.
Dialyze protein, add glycerol for storing at -20 °C, and quantify protein according to original MapR method (Yan and Sarma, 2020).
Sample preparation
If purifying tissue-specific nuclei from Drosophila, perform nuclei immuno-enrichment as follows: for this protocol, we performed tissue-specific nuclei immunoprecipitation from UAS-EGFP.KASH-Msp300 flies (available at the Bloomington Drosophila Stock Center, see Methods). These flies, when crossed with a Gal4 fly line, will express a GFP anchored to the outer nuclear membrane in a specific tissue. Then, magnetic beads and GFP antibody can be used to purify these nuclei. We have also described these steps (Jauregui-Lozano et al., 2021), and this approach is compatible with different chromatin profiling techniques.
Prepare fresh bead washing buffer, homogenization/wash buffer, and dilution buffer and keep on ice.
Incubate 40 µL of DynabeadsTM in 1 mL of bead washing buffer for 10 min at room temperature (RT) with constant rotation.
Transfer tube to magnetic rack. Invert rack several times to ensure all beads are bound to the magnet. Remove supernatant with pipettor.
Resuspend beads in 1 mL bead washing buffer with 4 µg of anti-GFP antibody.
Incubate beads for 30 min at RT with constant rotation to couple with GFP antibody.
Using magnet, remove supernatant.
Wash beads with 1 mL bead washing buffer for 5 min at RT with constant rotation.
Using magnet, remove supernatant.
Resuspend beads in 0.1% NP-40 homogenization/wash buffer. Mix three parts dilution buffer with one part homogenization/wash buffer to a final concentration of 0.1% NP-40.
Load Dounce homogenizer with 1 mL of homogenization/wash buffer. Keep homogenizer on ice.
Transfer Drosophila samples to homogenizer.
400 fly heads (flash frozen in liquid nitrogen and stored at -80 °C) can be used with 1 mL of homogenization/wash buffer to isolate nuclei from neuronal tissue in the adult head.
Fresh samples such as larval tissue or whole embryos can also be used.
Grind samples with 5 “loose” pestle strokes.
Incubate samples on ice for 5 min.
Grind samples with an additional 5 “loose” pestle strokes followed by 10 “tight” pestle strokes.
Filter fly homogenate using a 40 µm cell strainer.
Add 3 mL of dilution buffer to filtered 1 mL homogenate to a final concentration of 0.1% NP-40.
Evenly split 4 mL of homogenate into four 1.5 mL tubes (1 mL per tube).
Add 50 µL of bead/antibody solution to each tube.
Incubate fly homogenate with bead/antibody solution for 30 min at RT with constant rotation to couple nuclei with the anti-GFP beads.
Using magnet, remove supernatant.
Combine bead-bound nuclei from all four tubes in 1 mL of 0.1% NP-40 homogenization/wash buffer.
Incubate for 5 min at 4 °C with constant rotation.
Using magnet, remove supernatant.
Resuspend bead-bound nuclei in 1 mL of 0.1% NP-40 homogenization/wash buffer and transfer to a fresh 1.5 mL tube.
Incubate for 5 min at 4 °C with constant rotation.
Using magnet, remove supernatant.
Wash bead-bound nuclei in 1 mL of 0.1% NP-40 homogenization/wash buffer for 5 min at 4 °C with constant rotation.
Note: As previously described (Jauregui-Lozano et al., 2021), this method will yield bead-bound nuclei, which is suitable with MapR. Otherwise, purify nuclei using Concanavalin A-coated beads, as described in the original MapR method (Yan and Sarma, 2020).
Modified MapR
Wash bead-bound nuclei with 1 mL of dig-wash buffer.
For every wash step, incubate bead-bound nuclei at 4 °C for 5 min with constant rotation.
Using magnet, remove dig-wash buffer, and repeat wash step two more times.
Resuspend bead-bound nuclei in 150 μL of dig-wash buffer.
Add GST-ΔRH-MNase or GST-MNase to a final concentration of 1 μM.
To calculate protein molarity based on protein concentration, use the formula:
where,
μg/mL is the concentration of protein obtained with traditional protein quantification reagents, such as Bradford Assay or QubitTM protein assay kits (Thermo Fisher).
MW (kDa) is the molecular weight of the protein. GST-MNase has a MW of 44 kDa, and GST-dRH-MNase has a MW of 61.5 kDa.
The Bioline website has an online calculator that performs this calculation: https://www.bioline.com/media/calculator/01_04.html.
Incubate at 4 °C with constant rotation for 1 h.
Wash bead-bound nuclei three times with 500 μL of dig-wash buffer.
Wash bead-bound nuclei one time with low salt rinse buffer.
Resuspend bead-bound nuclei in 200 μL of ice-cold calcium-containing activation buffer, and place on wet ice for 60 s.
Using magnet, remove supernatant and immediately add 150 μL of EGTA-STOP buffer.
Incubate for 30 min at 37 °C.
Using magnet, transfer supernatant to a new tube and extract DNA from the supernatant using ChIP DNA clean & concentrator. The supernatant contains the released R-loop-enriched DNA; make sure you purify DNA from supernatant.
Quantify DNA using Nanodrop or QubitTM DNA reagent.
Use 100 pg–10 ng of purified DNA to make sequencing-ready MapR libraries using Ovation® Ultralow V2 DNA-Seq library preparation kit.
Data analysis
Notes:
In this example, we use the D. melanogaster reference genome “BDGP Release 6 + ISO1 MT/dm6”, or dm6, available at https://hgdownload.soe.ucsc.edu/goldenPath/dm6/bigZips/.
Code that is run in command line starts with $.
Alignment to reference genome
Index reference genome using Bowtie2
$ bowtie2-build --threads [# of threads/cores] [reference genome fasta file] [file name used to name the index files]
Find below a screenshot of what the first 20 lines will look like after running the bowtie2-build command using 64 threads and using a reference genome fasta file named “dm6.fa”. dm6 will be used as file name for index files.
Align raw/clean sequencing reads to reference genome (code is piped to directly generate BAM file rather than SAM).
$ bowtie2 -p [# of threads/cores] --sensitive -x [index specified in step 1] -1 CleanReads_1.fq -2 CleanReads_2.fq | samtools view -@ [# of threads/cores] -bSo Output.bam
Sort BAM file by genomic coordinates (this step is required to generate bigwig files using deepTools)
$ samtools sort -@ [# of threads/cores] -o Output_sorted.bam Output.bam
Bigwig generation for data visualization
-Using deepTools
$ bamCoverage -b BAMfile.bam -o output_file.bw -bs [bin size] -p [# of threads/cores] --normalizeUsing CPM
Genome browser inspection
Figure 2. Genome browser inspection of MapR data with or without pre-treatment with RNAse H1. Data was visualized in a genome browser (such as Integrative Genomics Browser, or IGV) using counts-per-million (CPM) normalized bigwig files. In order to compare enrichment, both tracks were scaled to the same values.
Notes
Traditional MapR contains a control for R-loop enrichment, where a fraction of bead-bound nuclei is incubated with GST-MNase. In this experimental condition, the researcher can control for random MNase binding to chromatin or background. Unexpectedly, we were not able to get the MNase control to work. We did not obtain purifiable DNA upon performing the experiment. For quantification of purified DNA, we used the High Sensitivity QubitTM, which allows quantification of small amounts of DNA (picograms). Thus, we performed an additional control, where we treated a fraction of bead-bound nuclei with catalytically active RNAse H1 for three hours, prior to performing MapR.
Analyzed bigwig files used for data visualization were downloaded from Gene Expression Omnibus (GEO), accession code GSE174488. They correspond to MapR from D. melanogaster photoreceptor neurons, as originally described in Jauregui-Lozano et al. (2022).
Recipes
GST-wash/equilibration buffer
Reagent Final concentration Amount
Tris (1 M pH 7.5) 125 mM 1,250 µL
NaCl (5 M) 150 mM 300 µL
DTT (100 mM) 1 mM 100 µL
EDTA (500 mM) 1 mM 20 µL
H2O
Total
n/a
mL
10 mL
GST-elution buffer
Reagent Final concentration Amount
Glutathione (reduced) (1 M) 50 mM 500 µL
GST-wash/equilibration buffer
Total
n/a
9.5 mL
10 mL
Coomassie fixing solution
Reagent Final concentration Amount
Methanol 50% 50 mL
Acetic acid, glacial
H2O
Total
10%
10 mL
40 mL
100 mL
Coomassie staining solution
Reagent Final concentration Amount
Coomassie Brilliant Blue 0.1 0.1 g
Methanol
Acetic acid, glacial
H2O
Total
50%
10%
50 mL
10 mL
40 mL
100 mL
Alternatively, you can make a 10% Coomassie Blue stock solution (1 g Coomassie reagent + 10 mL H2O) and add 1 mL of 10% stock solution into Coomassie staining solution.
Coomassie destaining solution
Reagent Final concentration Amount
Methanol 40% 40 mL
Acetic acid, glacial
H2O
Total
10%
10 mL
50 mL
100 mL
Homogenization/wash buffer
Reagent Final concentration Amount
HEPES (1M, pH 7.5) 40 mM 400 µL
KCl (1M) 120 mM 1.2 mL
NP-40 (10%) 0.4% 400 µL
H2O n/a 8 mL
Total 10 mL
Dilution buffer
Reagent Final concentration Amount
HEPES (1 M, pH 7.5) 40 mM 400 µL
KCl (1 M) 120 mM 1.2 mL
H2O n/a 8.4 mL
Total 10 mL
Bead washing buffer
Reagent Final concentration Amount
MgCl2 2.5 mM 25 µL
PBST (1×) n/a 9.975 mL
Total 10 mL
PBST (1×, pH 7.4)
Reagent Final concentration Amount
PBS (10×) 1× 5 mL
Tween 0.1% 50 µL
H2O n/a 44.950 mL
Total 50 mL
Dig-wash buffer
Reagent Final concentration Amount
HEPES (1 M, pH 7.5) 20 mM 1 mL
Spermidine (6.4 M, pH 7.0) 0.5 mM 3.9 µL
NaCl (5 M) 150 mM 1.5 mL
H2O
Total
n/a
47.5 mL
50 mL
Low salt rinse buffer
Reagent Final concentration Amount
HEPES (1 M, pH 7.5) 20 mM 200 µL
Spermidine (6.4 M) 0.5 mM 0.8 µL
Digitonin (5%) 0.05% 100 µL
H2O n/a 9.62 mL
Total n/a 10 mL
Activation buffer
Reagent Final concentration Amount
HEPES (1 M, pH 7.5) 3.5 mM 14 µL
CaCl (100 mM) 10 mM 400 µL
Digitonin (5%) 0.05% 40 µL
H2O n/a 3.46 mL
Total n/a 4 mL
EGTA-STOP buffer (1×)
Reagent Final concentration Amount
NaCl (5M) 170 mM 34 µL
EGTA (100 mM) 20 mM 200 µL
Digitonin (5%) 0.05% 10 µL
RNase A (10 µg/µL) 0.05% 5 µL
Linear acrylamide (5 µg/µL) 0.025% 5 µL
H2O n/a 746 µL
Total n/a 1 mL
Acknowledgments
This research was supported by the National Institute of Health – National Eye Institute grant R21EY031024. This protocol describes a methodology used in the research paper (DOI: 10.1111/acel.13554) by Jauregui-Lozano et al. (2022).
Competing interests
The authors declare no competing financial interests.
References
Becherel, O. J., Sun, J., Yeo, A. J., Nayler, S., Fogel, B. L., Gao, F., Coppola, G., Criscuolo, C., De Michele, G., Wolvetang, E. et al. (2015). A new model to study neurodegeneration in ataxia oculomotor apraxia type 2. Hum Mol Genet 24(20): 5759-5774.
García-Muse, T. and Aguilera, A. (2019). R Loops: From Physiological to Pathological Roles. Cell 179(3): 604-618.
Jauregui-Lozano, J., Bakhle, K. and Weake, V. M. (2021). In vivo tissue-specific chromatin profiling in Drosophila melanogaster using GFP-tagged nuclei. Genetics 218(3).
Jauregui-Lozano, J., Escobedo, S., Easton, A., Lanman, N. A., Weake, V. M. and Hall, H. (2022). Proper control of R-loop homeostasis is required for maintenance of gene expression and neuronal function during aging. Aging Cell 21(2): e13554.
Langmead, B. and Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nat Methods 9(4): 357-359.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R. and Genome Project Data Processing, S. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16): 2078-2079.
Lim, Y. W., Sanz, L. A., Xu, X., Hartono, S. R. and Chedin, F. (2015). Genome-wide DNA hypomethylation and RNA:DNA hybrid accumulation in Aicardi-Goutieres syndrome. Elife 4: e08007.
Meers, M. P., Bryson, T. D., Henikoff, J. G. and Henikoff, S. (2019). Improved CUT&RUN chromatin profiling tools. Elife 8: e46314.
Ramírez, F., Dundar, F., Diehl, S., Gruning, B. A. and Manke, T. (2014). deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res 42(Web Server issue): W187-191.
Salvi, J. S. and Mekhail, K. (2015). R-loops highlight the nucleus in ALS. Nucleus 6(1): 23-29.
Thorvaldsdóttir, H., Robinson, J. T. and Mesirov, J. P. (2013). Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14(2): 178-192.
Wang, K., Wang, H., Li, C., Yin, Z., Xiao, R., Li, Q., Xiang, Y., Wang, W., Huang, J., Chen, L., et al. (2021). Genomic profiling of native R loops with a DNA-RNA hybrid recognition sensor. Sci Adv 7(8): eabe3516.
Yan, Q. and Sarma, K. (2020). MapR: A Method for Identifying Native R-Loops Genome Wide. Curr Protoc Mol Biol 130(1): e113.
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4,517 | https://bio-protocol.org/en/bpdetail?id=4517&type=0 | # Bio-Protocol Content
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A Novel Imaging Technique for The On-site Assessment of Renal Biopsy Specimens
TT Tomoaki Takata *
HI Hajime Isomoto *
TI Takuji Iyama
KY Kentaro Yamada
(*contributed equally to this work)
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4517 Views: 694
Reviewed by: Alessandro Didonna Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Scientific Reports Jul 2020
Abstract
When performing renal biopsy, it is necessary to identify the cortex, where glomeruli are exclusively distributed, to ensure the quality of the specimen for histological diagnosis. However, conventional methods using a stereomicroscope or magnifying lens often fail to clarify the quality of the specimen. We have established a fluorescent-based imaging technique for the on-site assessment of renal biopsy specimens. The fluorescent images can be easily obtained by adding an optical filter to the microscope and with a short incubation of an activatable fluorescent probe. This novel imaging technique can be applied to renal biopsy specimens for distinguishing the renal cortex.
Keywords: Activatable fluorescent probe Gamma-glutamyl transpeptidase gGlu-HMRG Fluorescence Biopsy Renal cortex
Background
Renal biopsy is one of the most important procedures for the assessment of kidney diseases. Upon performing renal biopsy, it is necessary to obtain a sufficient number of glomeruli, which are exclusively distributed in the renal cortex. A stereomicroscope or magnifying lens are usually used for this purpose; however, it is often difficult to clearly identify the cortex. Therefore, novel methods for the on-site assessment of renal biopsy specimens need to be established.
Gamma-glutamyl hydroxymethyl rhodamine green (gGlu-HMRG) is a recently developed activatable fluorescent probe (Urano et al., 2011). This probe is characterized by immediate fluorescence emission upon enzymatic catalysis by gamma-glutamyl transpeptidase (GGTP). gGlu-HMRG was originally developed for the detection of several types of cancer that express high levels of GGTP (Mitsunaga et al., 2013), and has not been applied to renal biopsy specimens.
Our recent work has focused on investigating the feasibility of gGlu-HMRG for the on-site assessment of renal biopsy specimens (Iyama et al., 2020). Renal cortex, in which most of the glomeruli are contained, showed rapid induction of fluorescence upon the incubation of gGlu-HMRG and could be clearly distinguished from renal medulla. We herein present a protocol for the induction of fluorescence by gGlu-HMRG with some modifications for better clarity of the images.
Materials and Reagents
Pipettes (M&S Instruments, catalog numbers: F144059M, F144058, and F144055M)
Pipette tips (Violamo, catalog numbers: V-1000, V-200, and V-10)
Eppendorf centrifuge tubes, 1.5 mL
6 cm dishes (AS ONE, catalog number: 2-8590-02)
Phosphate buffer saline (PBS) (FUJIFILM, catalog number: 166-23555)
Dimethyl sulfoxide (FUJIFILM, catalog number: 041-29351)
Normal saline (Otsuka Pharmaceutical Factory, catalog number: 035081517)
ProteoGREENTM-gGlu (GORYO Chemical, catalog number: GC801). Dissolve in dimethyl sulfoxide at 1 mM and store at -20 °C before use (unnecessary to filter)
Equipment
Stereomicroscope (BioTools, catalog number: BS-3048BT)
Fluorescent unit (BioTools, catalog number: BT-ExSM)
Band pass filter (FUJIFILM, catalog number: BPB-45). This filter should be set at the light source of the fluorescent unit
Sharp cut filter (FUJIFILM, catalog number: SC-52). This filter should be set at the lens side of the fluorescent unit (Figure 1)
Figure 1. Setup of the fluorescent unit for the imaging. Band pass filter and sharp cut filter should be set as illustrated.
Procedure
Preparation of the fluorescent probe
Thaw ProteoGREENTM-gGlu stock solution on ice (protect from light).
Dilute ProteoGREENTM-gGlu stock solution into PBS to prepare fluorescent solution (concentration of 50 μM).
Handling of renal biopsy specimen
Perform renal biopsy (Donovan et al., 1991).
Briefly rinse biopsy specimen with 10 mL of normal saline in 6 cm dish. Protect the specimen from drying.
Apply 100 μL of the fluorescent solution to the biopsy specimen. Incubate for 3 min under dark conditions at room temperature.
Illuminate and observe the specimen. Excitation wavelength of 450 nm passes through the band pass filter; the fluorescent solution is excited and emits fluorescence. Sharp cut filter eliminates redundant wavelengths except for fluorescence.
Capture images of the renal biopsy specimen at 2.0× magnification ratio. The corticomedullary junction of the specimen can be easily identified (Figure 2).
Figure 2. Fluorescent image of the renal biopsy specimen incubated with gGlu-HMRG. Cortex emits stronger fluorescence than the medulla. Scale bar = 1 mm.
Notes
Prepare fluorescent solution each time just before use.
Fluorescent solution should be applied to the specimen before fixation.
Renal carcinoma deriving from the renal proximal tubular epithelial cells might influence the fluorescence.
Acknowledgments
This protocol is based on “A novel method for assessing the renal biopsy specimens using an activatable fluorescent probe,” published in Scientific Reports (Iyama et al., 2020).
Competing interests
The authors declare that they have no financial or non-financial conflicts of interest.
Ethics
This study was conducted in accordance with the Declaration of Helsinki and approved by the ethical committee of Tottori University Hospital (approval number: 18A135). Informed consent was obtained from all subjects.
References
Iyama, T., Takata, T., Yamada, K., Mae, Y., Taniguchi, S., Ida, A., Ogawa, M., Yamamoto, M., Hamada, S., Fukuda, S., et al. (2020). A novel method for assessing the renal biopsy specimens using an activatable fluorescent probe. Sci Rep 10(1): 12094.
Mitsunaga, M., Kosaka, N., Choyke, P. L., Young, M. R., Dextras, C. R., Saud, S. M., Colburn, N. H., Sakabe, M., Nagano, T., Asanuma, D., et al. (2013). Fluorescence endoscopic detection of murine colitis-associated colon cancer by topically applied enzymatically rapid-activatable probe. Gut 62(8): 1179-1186.
Urano, Y., Sakabe, M., Kosaka, N., Ogawa, M., Mitsunaga, M., Asanuma, D., Kamiya, M., Young, M. R., Nagano, T., Choyke, P. L., et al. (2011). Rapid cancer detection by topically spraying a gamma-glutamyltranspeptidase-activated fluorescent probe. Sci Transl Med 3(110): 110ra119.
Donovan, K. L., Thomas, D. M., Wheeler, D. C., Macdougall, I. C. and Williams, J. D. (1991). Experience with a new method for percutaneous renal biopsy. Nephrol Dial Transplant 6(10): 731-733.
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Biophysics > Bioengineering > Medical biomaterials
Molecular Biology > Protein > Activity
Biochemistry > Other compound > Peptide
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4,518 | https://bio-protocol.org/en/bpdetail?id=4518&type=0 | # Bio-Protocol Content
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In vitro Fluorescence Imaging–based Actin Bundling Assay
AG Anjelika Gasilina
PR Paul A. Randazzo
Published: Vol 12, Iss 18, Sep 20, 2022
DOI: 10.21769/BioProtoc.4518 Views: 1409
Reviewed by: David PaulSeham EbrahimMoriah R Beck
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Mar 2022
Abstract
Understanding the molecular and structural mechanisms that govern the assembly and organization of higher-order actin architecture requires the use of in vitro actin binding and bundling assays. Crosslinking of actin filaments into bundles can be monitored in vitro via several techniques, including negative staining/electron microscopy, low-speed co-sedimentation assay/SDS-PAGE, and fluorescence staining/confocal microscopy. We and others have previously characterized the N-BAR domain of ASAP1, an ADP-ribosylation factor GTPase-activating protein, as an actin-bundling module; we further identified key lysine residues responsible for actin cross-linking. Here, we use the ASAP1 BAR domain as an example and describe a detailed procedure for observing the actin bundle formation by confocal microscopy. This protocol requires small reaction volumes and takes advantage of bright commercially available fluorescent phalloidins, making it an ideal choice for medium-throughput screening of mutants or domain truncations in their ability to bundle actin.
Graphical abstract:
Keywords: Actin bundles Actin-bundling protein Phalloidin Fluorescence microscopy Protein–protein interactions
Background
Actin function in normal physiology and pathology depends on the assembly of actin filaments into higher-order structures. The regulation of higher-order actin structures is still being discovered. Advances in our understanding of these dynamics are facilitated by information-dense assays with quantifiable results. ASAP1 is an ADP-ribosylation factor GTPase-activating protein (GAP) that regulates the dynamics of filamentous actin–based structures, including stress fibers, focal adhesions, and circular dorsal ruffles (Randazzo et al., 2000; Oda et al., 2003; Bharti et al., 2007). We and others have previously found that the N-BAR domain of ASAP1 binds and bundles actin filaments and that its actin bundling activity is under auto-inhibitory regulation by its GAP and SH3 domains (Gasilina et al., 2019; Chen et al., 2020). We then set out to identify structural determinants on ASAP1 BAR domain that control actin bundling activity (Gasilina et al., 2022), which required careful quantification. Here, we detail a method to analyze the actin bundling activity of ASAP1 BAR-PH, which is applicable to other proteins with hypothesized actin-bundling activity. Unlike low-speed sedimentation assay, this method requires small quantities of actin filaments and test proteins and allows for simultaneous processing of several samples, which facilitates the evaluation of several concentrations, point mutants, domain truncations, or ionic strengths in a relatively short amount of time. In addition, because the filaments are directly visualized, information such as bundle width and length can be determined, which is not possible with the sedimentation assays; quantification is robust with methods that have been developed for analysis of images.
Materials and Reagents
Circular coverslips, German glass, 12 mm diameter, #1.5 thickness (Electron Microscopy Sciences, catalog number: 72291-02)
24-well flat bottom cell culture plate (Corning Costar, Corning, catalog number: 3526, or similar)
1.5–1.7 mL microcentrifuge tubes (Thomas Scientific, catalog number: 1138W14)
0.5 mL open-top thickwall polycarbonate tube (Beckman Coulter, catalog number: 343776)
50 mL conical tubes (Corning, catalog number: 352070)
0.22 µm syringe filters (Millex, Millipore-Sigma, catalog number: SLGPR33RS)
50 mL Luer tip syringes (BD Luer-Lok Tip, Fisher Scientific, catalog number: 14-820-11)
10 µL pipette tips, ends cut off to make a larger orifice
Frosted microscope slides (Fisherbrand, Fisher Scientific, catalog number: 12-550-343)
Ethanol/dry ice bath or liquid nitrogen for snap-freezing protein
Phosphate buffered saline (PBS) (Gibco, ThermoFisher Scientific, catalog number: 20012027)
Poly-L-lysine, 0.01% solution (Sigma-Aldrich, MilliporeSigma, catalog number: P4707-50ML)
Rabbit muscle G-actin, >99% pure (Cytoskeleton, Inc., catalog number: AKL99)
Note: Using actin prepared in-house from rabbit skeletal acetone powder is also fine, but care needs to be taken to verify that all bundling protein contaminants have been removed.
ASAP1 N-BAR recombinant protein, expressed and purified as described previously (Gasilina et al., 2019, 2022)
α-actinin (Cytoskeleton, Inc., catalog number: AT01)
Note: It is highly recommended to use a bona fide actin bundling protein, such as α-actinin or vinculin tail, as a positive control.
Bovine serum albumin (BSA) (Sigma-Aldrich, Millipore Sigma, catalog number: B8667). Aliquot into 100 µL volumes and snap freeze. Store at -80 °C.
Methanol ≥99.9% (J.T. Baker, VWR International, catalog number: 9093-02)
Fluorescently labeled phalloidin [rhodamine phalloidin (Invitrogen, ThermoFisher Scientific, catalog number: R415), or Alexa Fluor 488 phalloidin (Invitrogen, ThermoFisher Scientific, catalog number: A12379)]. Reconstitute in 1.5 mL of 100% methanol and store at -20 °C.
Note: Although any bright and photostable fluorescent phalloidin conjugate can be used to stain and visualize bundles, the use of fluorophores in the visible spectra will facilitate finding and focusing on the sample during data acquisition.
Adenosine 5’-triphosphate disodium salt (ATP) (Cytoskeleton, Inc., catalog number: BSA04). Reconstitute with 1 mL of cold 100 mM Tris, pH 7.5 (Recipe 7), for a 100 mM stock, aliquot into 5–100 µL portions and 10–50 µL portions, snap freeze, and store at -80 °C. Note that the ATP from cytoskeleton is lyophilized from a solution buffered to pH 7, and, consequently, the solutions do not require additional adjusting of the pH.
Paraformaldehyde, 16%, methanol-free (Electron Microscopy Sciences, catalog number: 15710)
Dako fluorescence mounting medium (Agilent, catalog number: S302380-2)
Calcium chloride (CaCl2) (Sigma-Aldrich, Millipore Sigma, catalog number: 223506)
Potassium chloride (KCl) (Sigma-Aldrich, Millipore Sigma, catalog number: P3911)
Magnesium chloride (MgCl2) (Sigma-Aldrich, Millipore Sigma, catalog number: M9272)
Tris-HCl, 1 M, pH 7.5 (KD Medical, catalog number: RGF-3350)
Dithiothreitol (DTT) Cleland’s reagent (MP Biomedicals, VWR International, catalog number: 0219482101)
1× G-actin buffer (see Recipes)
10× actin polymerization buffer (see Recipes)
1× F-actin buffer (see Recipes)
1 M CaCl2 (see Recipes)
1 M KCl (see Recipes)
1 M MgCl2 (see Recipes)
Tris-HCl, 1 M, pH 7.5 (see Recipes)
1 M DTT (see Recipes)
Equipment
P10, P20, and P200 micropipettes
Benchtop microcentrifuge for 1.5/2 mL tubes
Small volume ultra-centrifuge (e.g., Thermo Scientific Sorvall MTX with S120-AT3 rotor)
Confocal microscope equipped with oil-immersion objective, preferably with a tile scanning option (we use a 63× objective, but given the size of the bundles, any objective between 40× and 100× is suitable.)
Software
Fiji/ImageJ (National Institutes of Health, imagej.nih.gov)
Procedure
Preparation of poly-L-lysine-coated coverslips
Note: This procedure assumes that four technical replicates are made for each bundling assay, and four bundling assays are made in total—F-actin alone, F-actin with ASAP1 BAR-PH, F-actin with BSA as a negative control, and F-actin with α-actinin as a positive control—all at a single concentration. If additional proteins or concentrations are to be tested, scale up the number of coverslips accordingly.
To examine four conditions in quadruplicate, place 16 coverslips into a 24-well plate, one in each well (Figure 1A–B). We use the 24-well plate because the size of the wells is ideal for the 12 mm coverslips.
Add 500 µL of 0.01% poly-L-lysine solution to each well, ensuring the coverslips are fully submerged. If coverslips float up, gently lower them back into solution with a pipette tip (Figure 1C–D).
Replace the lid and incubate at room temperature (RT) for 2 h (Figure 1E).
Aspirate poly-L-lysine solution and wash the coverslips three times with 500 µL of distilled water (Figure 1F).
Place the lid on the plate slightly askew and let coverslips dry overnight (Figure 1G). Alternatively, dry the coverslips in a 65 °C oven for 15 min.
Preparation of globular actin (G-actin) stock
Briefly centrifuge a tube containing 250 µg of lyophilized actin to bring powder to the bottom of the tube.
Add 250 µl of cold G-actin buffer, freshly supplemented with 0.2 mM ATP and 0.5 mM DTT (see Recipes). Pipette gently five to six times to resuspend the powder, taking care to avoid bubbles. Do not vortex.
Incubate on ice for 1 h.
This is a 1 mg/mL (~23 µM) stock of G-actin.
Notes:
Actin is not stable in its globular form. Promptly proceed to Step C or aliquot into smaller quantities and store at -80 °C.
We found that high-purity actin from cytoskeleton has very few aggregates and thus does not require high-speed centrifugation post resuspension. If other sources of actin are used, it may be necessary to centrifuge the G-actin stock at 100,000–150,000 × g to remove aggregates and subsequently calculate the protein concentration of the remaining G-actin fraction.
Preparation of actin filaments (F-actin)
Prepare 10× actin polymerization buffer (see Recipes).
Add 25 µL of the 10× actin polymerization buffer (1/10th of the volume) to 250 µL of 1 mg/mL stock of G-actin. Mix well, taking care to avoid bubbles. Do not vortex.
Incubate at RT for 1 h.
Note: F-actin is stable at 4 °C for up to one month. Do not freeze.
Preparation of potential bundling proteins such as ASAP1 and BAR-PH, the negative control BSA, and the positive control α-actinin for bundling assay (optional but highly recommended)
Pre-cool the tabletop ultracentrifuge and rotor to 4 °C.
Rapidly thaw ASAP1 BAR-PH, BSA, and α-actinin in RT water bath. We typically store the proteins in 100 μL aliquots at protein concentrations of approximately 1 mg/mL. For ASAP1 and recombinant proteins derived from ASAP1, the storage buffer is typically 20 mM HEPES, pH 8.0, and 150 mM NaCl.
Distribute proteins into polycarbonate ultracentrifuge tubes.
Place tubes, appropriately balanced with tubes filled with “blank” solution (e.g., protein buffer or water), into the ultracentrifuge rotor. Secure the lid.
Spin at 150,000 × g and 4 °C for 1 h to sediment particulates and aggregates.
Post-centrifugation, open the rotor lid and mark the sides of the tubes facing outward with a dot to indicate the side with the pellet and debris.
Transfer the spun protein into a new pre-labeled microcentrifuge tube, taking care not to disturb the pellet.
Determine the protein concentration using a protein assay, e.g., BCA or Bradford, or other spectrophotometric method.
Note: If the protein concentration is low, it is advisable to purify the protein into the F-actin buffer or exchange the protein into F-actin buffer using PD-10 (Cytiva) or Zeba columns (ThermoFisher).
Actin bundling assay
Label four microcentrifuge tubes, one for each reaction: F-actin alone, F-actin + BSA, F-actin + α-actinin, and F-actin + ASAP1 BAR-PH (Figure 1H–I).
Set up a 15 µL reaction in each tube using F-actin buffer (see Recipes) to compensate for volume differences (Figure 1J–K). Reactions typically contain 1–3 µM actin and 1–3 µM of the test or control proteins. Use 3 µM actin and 3 µM test proteins and respective positive and negative controls for initial estimation of bundling efficiency.
Note: The reactions should be set up within 10 min of each other and promptly transferred to the coverslips to allow for comparable incubation times for each reaction.
Using a 10 µL pipette held vertically and a tip with the end cut off, pipette 3 µL of the reaction directly into the center of each coverslip (Figure 1L–M). Avoid introducing bubbles—this may require depressing the pipette plunger only to the first stop. Repeat for all replicates and reactions.
Note: Placing the reaction spot directly into the center of the coverslip will greatly facilitate the image acquisition process.
Replace the lid of the 24-well plate and incubate the reaction drops at RT for 1 h.
During this time, prepare 20 mL of 4% paraformaldehyde (PFA) in PBS from the 16% stock and chill on ice. Unused 16% PFA can be stored sealed in parafilm for up to two weeks at 4 °C. Alternatively, dilute the entire 10 mL ampule to 4% in PBS (40 mL total) and store unused portion for up to one week at 4 °C.
Gently place the plate on ice and add 500 µL of ice-cold 4% PFA to each well (pipette on the side of the wells to avoid breaking the reaction drops) (Figure 1N). If any coverslips float up, gently lower them back with a pipette tip. Fix for 30 min (fixing adheres the actin bundles to the coverslips, so they are not lost during the staining process).
Rinse the coverslips gently in cold PBS twice for 5 min each. Gently aspirate.
Stain each coverslip in 500 µL of 1:500 dilution of fluorescent phalloidin in PBS for 30 min on ice. Cover the plate with foil during staining (Figure 1O).
In the meantime, pre-label 12 microscope slides (if placing two coverslips per slide) with identifying information (e.g., date, initials, reaction name, and phalloidin conjugate). Gently wipe the slide with a Kimwipe sprayed with 70% alcohol, if necessary (Figure 1P).
After 30 min, gently aspirate the staining solution and add PBS. Incubate for 5 min. Repeat. After the final PBS wash, aspirate and add 500 µL of ddH2O to each well.
Mount two coverslips on each slide using Dako fluorescent medium. Gently aspirate excess mounting medium from the edges of coverslips (see Figure 1Q–T). Allow to dry for at least 1 h at RT in the dark. Samples can be stored at 4 °C or transferred to -20 °C for long-term storage after imaging.
Figure 1. Pictographic Summary of the Procedure. For details and descriptions, refer to the main text.
Image acquisition and image analysis
Image the coverslips using a confocal microscope. For Alexa 488 phalloidin, use an argon 488 laser; for rhodamine phalloidin, use a krypton 564 laser. Using the tile scanning option (optional) allows for acquisition of a large area of the reaction spot. Typical results are shown in Figure 2. Examples of technically failed assays are shown in Figure 3.
Post-acquisition, images can be further analyzed using ImageJ. Bundle length and number or fluorescence intensity can be measured using freely available plugins; use thereof is described in Gasilina et al. (2019, 2022).
Overview of possible analyses
Examining the efficiency of actin bundling by comparing fluorescent intensities of bundles
Plotting line scan intensities of bundles made by different actin bundling proteins can be a quick way to estimate bundling efficiencies. This method can serve as a straightforward tool for initial characterization of mutants or domain truncations, among others.
Please note that direct comparisons of fluorescence intensities among different microscopy images require acquisition using identical settings (objective, light path, laser power, gain, frame size, zoom, and scan speed).
Download and Install Fiji/ImageJ.
Open the microscopy image of an actin bundling assay.
Select line tool and draw a line across the bundle.
Click “Analyze” → “Plot Profile.”
When the graph of the line scan appears, click “List” and copy the contents of the resulting window into a spreadsheet.
Repeat for other regions of interest and images.
Plot line scans in a single graph to visualize differences in fluorescence intensities of the bundles.
Quantifying the number and length of actin bundles using Ridge Detection Plugin (ImageJ/Fiji)
Download and Install Fiji/ImageJ.
Follow the instructions on https://imagej.net/plugins/ridge-detection to download the Ridge Detection Plugin.
Open an Experiment file in Fiji/ImageJ and convert to 8 bit by clicking Image → Type → 8-bit.
Initialize the Ridge Detection Plugin by clicking Plugins → Ridge Detection.
Set “Mandatory_parameters.” To help with accurate determination of mandatory parameter cut-offs, check “Preview” window and modify high and low contrast in “Optional_parameters” to view bundle detection in real time.
Click “OK” to initiate calculation of bundle length and the number of bundles.
The summary window provides the length and a unique identification number for each identified bundle.
Figure 2. Representative results. (A) “F-actin-only” control sample was stained with fluorescent phalloidin. Note uniform distribution of filaments on the image tile. The negative control protein, e.g., BSA, should appear nearly identical to the F-actin-only control. (B) “F-actin with ASAP1 BAR-PH” sample was stained with fluorescent phalloidin. Note the appearance of thick bundles. (C) “F-actin with α-actinin” positive control sample. α-actinin is a bona fide actin-bundling protein, which robustly cross-links actin filaments into thick bundles. Scale bar = 10 µm.
Figure 3. Examples of failed assays. (A) “F-actin-only” control sample was stained with fluorescent phalloidin. Note “clumps” of actin in the upper left and lower right corners. Improper storage of F-actin leads to aggregation of filaments and their subsequent appearance as clumps. Therefore, the rest of the coverslips in this set were discarded. (B) In this particular example, the test protein was not pre-spun before setting up the assay, resulting in debris and particulates being carried through the fixation and staining, which appeared as auto-fluorescent artifacts (upper right). Presence of these strongly fluorescent spots impedes image analysis. Scale bar = 10 µm.
Recipes
1× G-actin buffer (store at 4 °C)
CaCl2 (1 M), 0.2 mM, 10 µL
Tris-HCl (1 M, pH 8.0), 20 mM, 1 mL
ddH2O, 49 mL
Total: 50 mL
Supplement with 0.2 mM ATP and 0.5 mM DTT (final) immediately before use. For each milliliter of G-actin buffer working solution, add 2 µL of the 100 mM ATP stock and 5 µL of the 100 mM DTT stock. Keep on ice. Discard unused stock after 4–5 h.
10× actin polymerization buffer (store at RT)
MgCl2 (1 M), 20 mM, 200 µL
KCl (5 M), 1 M, 2 mL
ddH2O, 7.8 mL
Total: 10 mL
To prepare 100 µL of working solution, mix 10 µL of freshly thawed 100 mM ATP stock with 90 µL of 10× polymerization buffer on ice. Discard unused stock after 4–5 h.
1× F-actin buffer (prepare and use immediately. Keep on ice and discard after 4–5 h)
G-actin buffer + ATP/DTT, 450 µL
10× actin polymerization buffer + ATP, 50 µL
Total: 500 µL
Use the following as a guide (volumes account for pipetting errors): to make G-actin buffer + ATP/DTT, combine 500 µL of G-actin buffer, 1 µL of the 100 mM ATP stock, and 2.5 µL of the 100 mM DTT stock. To make actin polymerization buffer + ATP, combine 10 µL of freshly thawed 100 mM ATP stock and 90 µL of polymerization buffer. To make F-actin buffer, combine 450 µL of G-actin buffer with ATP and DTT and 50 µL of actin polymerization buffer with ATP.
1 M CaCl2
Add 7.35 g CaCl2 to 50 mL of ultra-pure water for a 1 M stock solution. Store in a conical tube at RT.
1 M KCl
Add 18.6 g KCl to 50 mL of ultra-pure water for a 5 M stock solution. Store in a conical tube at RT.
1 M MgCl2
Add 10.2 g MgCl2 to 50 mL of ultra-pure water for a 1 M stock solution. Store in a conical tube at RT.
Tris-HCl, 100 mM, pH 7.5
Add 10 mL of the 1 M Tris-HCl stock to 90 mL of ultra-pure water and filter sterilize, to prepare 100 mL of a 100 mM working solution. Store in two 50 mL sterile conical tubes; keep one tube at RT and store the other at 4 °C.
1 M DTT
Add 1.54 g to 10 mL of ultra-pure water for a 1 M stock. Aliquot 9 mL into nine 1 mL aliquots. Take 1 mL of the 1 M stock and further dilute to 100 mM with 9 mL of ultra-pure water. Aliquot the 100 mM stocks in 500 µL volumes. Store at -20 °C.
Acknowledgments
This work was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services (project number BC007365 to P.A.R.). This protocol was adapted from Lin-Jones and Burnside (2007) and our previous work (Gasilina et al., 2019, 2022). The authors thank Natalie M. Badillo for assistance with photography.
Competing interests
The authors declare no competing interests.
References
Bharti, S., Inoue, H., Bharti, K., Hirsch, D. S., Nie, Z., Yoon, H. Y., Artym, V., Yamada, K. M., Mueller, S. C., Barr, V. A., et al. (2007). Src-dependent phosphorylation of ASAP1 regulates podosomes. Mol Cell Biol 27(23): 8271-8283.
Chen, P. W., Billington, N., Maron, B. Y., Sload, J. A., Chinthalapudi, K. and Heissler, S. M. (2020). The BAR domain of the Arf GTPase-activating protein ASAP1 directly binds actin filaments. J Biol Chem 295(32): 11303-11315.
Gasilina, A., Vitali, T., Luo, R., Jian, X. and Randazzo, P. A. (2019). The ArfGAP ASAP1 Controls Actin Stress Fiber Organization via Its N-BAR Domain. iScience 22: 166-180.
Gasilina, A., Yoon, H. Y., Jian, X., Luo, R. and Randazzo, P. A. (2022). A lysine-rich cluster in the N-BAR domain of ARF GTPase-activating protein ASAP1 is necessary for binding and bundling actin filaments. J Biol Chem 298(3): 101700.
Lin-Jones, J. and Burnside, B. (2007). Retina-specific protein fascin 2 is an actin cross-linker associated with actin bundles in photoreceptor inner segments and calycal processes. Invest Ophthalmol Vis Sci 48(3): 1380-1388.
Oda, A., Wada, I., Miura, K., Okawa, K., Kadoya, T., Kato, T., Nishihara, H., Maeda, M., Tanaka, S., Nagashima, K., et al. (2003). CrkL directs ASAP1 to peripheral focal adhesions. J Biol Chem 278(8): 6456-6460.
Randazzo, P. A., Andrade, J., Miura, K., Brown, M. T., Long, Y. Q., Stauffer, S., Roller, P. and Cooper, J. A. (2000). The Arf GTPase-activating protein ASAP1 regulates the actin cytoskeleton. Proc Natl Acad Sci U S A 97(8): 4011-4016.
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A Simplified Paradigm of Late Gestation Transient Prenatal Hypoxia to Investigate Functional and Structural Outcomes from a Developmental Hypoxic Insult
EG Elyse C. Gadra
AC Ana G. Cristancho
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4519 Views: 762
Reviewed by: Oneil Girish BhalalaHélène Léger Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Developmental Neuroscience Mar 2022
Abstract
Late-gestation transient intrauterine hypoxia is a common cause of birth injury. It can lead to long-term neurodevelopmental disabilities even in the absence of gross anatomic injury. Currently, postnatal models of hypoxia–ischemia are most commonly used to study the effect of oxygen deprivation in the fetal brain. These models, however, are unable to take into account placental factors that influence the response to hypoxia, exhibit levels of cell death not seen in many human patients, and are unable to model preterm hypoxia. To address this gap in research, we have developed a protocol to induce transient hypoxia in fetal mice. A pregnant dam at gestational day 17.5 is placed into a hypoxia chamber. Over 30 min, the inspired oxygen is titrated from 21% (ambient air) to 5%. The dam remains in the chamber for up to 8 h, after which fetal brains can be collected or pups delivered for postnatal studies. This protocol recapitulates phenotypes seen in human patients exposed to transient in utero hypoxia and is readily reproducible by researchers.
Graphical abstract:
Keywords: Prenatal hypoxia Animal model Behavior Imaging Developing brain
Background
Each year, millions of neonates are affected by intrauterine hypoxia, of which the most recognized form is hypoxic ischemic encephalopathy (HIE) in full-term infants (Lee et al., 2013; Stanaway et al., 2018). Prenatal hypoxia is one of the leading worldwide causes of long-term brain injury (Lee et al., 2013; Stanaway et al., 2018), and HIE is characterized by an intrapartum loss of oxygen and nutrients. Approximately 40% of affected children develop a neurodevelopmental disability (NDD), such as autism or epilepsy (Ferriero, 2004; Lee et al., 2013; Stanaway et al., 2018). Therapeutic hypothermia is the mainstay of current therapy but is only available to a fraction of children who have moderate to severe acute HIE and are near a facility capable of initiating it in the immediate perinatal period (Ahearne et al., 2016). Children initially classified as having mild HIE may still experience adverse outcomes (de Haan et al., 2006; van Kooij et al., 2010; Eunson, 2015; Reiss et al., 2019; Schreglmann et al., 2020; Finder et al., 2020). These mildly affected children do not qualify for therapeutic hypothermia. In addition to term infant HIE, HIE in preterm infants is a poorly understood entity that predisposes children to NDDs (Schmidt and Walsh, 2010; Gopagondanahalli et al., 2016). Preterm infants with HIE are also not eligible for therapeutic hypothermia. Given the need for targeted therapies, we must develop animal models that can recapitulate the full spectrum of phenotypes exhibited by children affected by prenatal hypoxia.
Existing models of transient hypoxia in rodents have focused primarily on its effect on the postnatal brain (postnatal day 7–10) (Rice et al., 1981; Sun et al., 2016) because this postnatal period is considered to correlate neuroanatomically to term human infants (Semple et al., 2013). Models such as the Vannucci model involve unilateral ligation of the carotid artery with subsequent exposure to hypoxia (Rice et al., 1981; Sun et al., 2016). In addition to recapitulating human neuroanatomy, this postnatal method makes studying the combined effects of hypoxia and ischemia more technically feasible.
While there are benefits to postnatal rodent models of transient hypoxia, these have limitations. Importantly, postnatal models do not account for maternal and placental factors that may modulate the fetal response to hypoxia. The in utero environment is hypoxic at baseline (Trollmann et al., 2008), and many studies investigating the hypoxic response have revealed complex interactions between oxygen control and injury outcome (Tomita et al., 2003; Chen et al., 2008; Sheldon et al., 2009; Sheldon et al., 2014; Arthuis et al., 2017; Xu et al., 2019; Peebles et al., 2020; Zhang et al., 2021). Additionally, postnatal models involving carotid artery ligation followed by hypoxia result in severe injury, characterized by significant levels of cell death (Rice et al., 1981), and not the milder injury seen in many human patients (Lee et al., 2013). Finally, while the postnatal rodent brain correlates anatomically with term human infants, some functional networks mature faster in postnatal rodents than in term infants (Feather-Schussler and Ferguson, 2016). At birth, mice exhibit neuroanatomy analogous to infants born at 23–26 weeks gestation (Semple et al., 2013). However, they do not display respiratory or feeding issues common in children born before 34 weeks gestation (Zhao et al., 2019). Additionally, mice are ambulatory around postnatal day 10, a milestone human children do not achieve until approximately 12 months old (Feather-Schussler and Ferguson, 2016; Aziz et al., 2018).
Although previous mouse models of prenatal hypoxia have been described (Baud et al., 2004; Mallard and Vexler, 2015), many are primarily used to study the effects of chronic hypoxia throughout gestation. Other prenatal models of transient injury are more challenging to execute (such as late gestation uterine artery ligation) (Kubo et al., 2017). Sheep models of transient and mild hypoxia-only injury require specialized equipment, ample resources, and are not amenable to genetic manipulation (McClendon et al., 2017; McClendon et al., 2019). Here, we characterize a protocol to induce transient, mild, hypoxic injury in prenatal mice.
Previously, we have used this model to characterize the effect of late gestation (embryonic day 17.5) transient prenatal hypoxia (5% FiO2) on long-term neurodevelopmental and anatomical features in mice (Cristancho et al., 2022). Our studies showed increased levels of hypoxia-inducible factor 1 alpha (a marker of hypoxic exposure) in the brains of fetal mice exposed to prenatal hypoxia. Mice exposed to hypoxia had decreased weights at postnatal day 2. Hypoxic exposure also led to decreased seizure threshold in mice. In addition, both male and female hypoxic mice showed abnormalities in grip strength and repetitive behaviors. Finally, male hypoxic mice had increased anxiety-like behaviors, while female hypoxic mice showed abnormalities in social interaction. We hope that future researchers may use this model to investigate the mechanisms underlying mild and preterm HIE and elucidate the maternal–placental–fetal factors underlying neurodevelopmental outcomes in preterm children exposed to transient hypoxia.
Materials and Reagents
Medical NF grade nitrogen, size 200 cylinder, CGA-580 (Airgas, NI NF200). Protect from light and store in a well-ventilated space; indefinite shelf life.
Soda lime, indicating (Thermo Fisher Scientific, catalog number: AA4478636). Store at room temperature; stored indefinitely in an airtight container (at least 3 years). Use fresh soda lime for each exposure.
Hydrogel (clear H2O, 70-01-5022). Store at room temperature; once opened, store in a sealed plastic bag and discard after one week or when dried out.
Laboratory rodent diet 5015 pellets (Lab Diet, catalog number: 001328). Store at room temperature in climate-controlled conditions; shelf life is at least nine months.
Nalgene VERSI-DRY lab table soakers (VWR, catalog number: 52857-104). Store at room temperature; indefinite shelf life.
VWR disposable Petri dishes, 10 cm, semi-stackable (VWR, catalog number: 25384-088). Store at room temperature; indefinite shelf life.
Alcohol 70% (ethyl alcohol), 4 L (Millipore Sigma, catalog number: 65350-85). Store at room temperature in flammables cabinet; will last multiple years if kept sealed away from light.
C57BL/6NCrl mice at embryonic day 17.5 were used for this protocol (Charles River)
We have also successfully used C57BL6/J (Jackson Laboratories) animals.
We have not tested other gestational time points of exposure but believe the protocol could be adapted depending on the experimental needs.
Equipment
ProOx 360 versatile high infusion rate O2 controller with oxygen sensor (Biospherix, model: E702)
Harris model 425-200-580 heavy duty argon, helium, and nitrogen single stage regulator, CGA-580 (Airgas, model: HCL3000773)
Animal cage enclosures with riser platform (Biospherix, A-Chamber)
Translucent plastic bins (to house animals during hypoxic exposures) [e.g., BINO plastic storage bins, deep large, The Handler Collection (Amazon, 12093-CLR)]
Cutting board or similar divider (to visually separate animals when performing two hypoxic exposures in one chamber) [e.g., Dexas superboard pastry board, 14 in. × 17 in. (Amazon, B000063SRL)]
Procedure
Oxygen Sensor Calibration
Calibrate the oxygen sensor once a month according to the manufacturer’s instructions (using parameters for low oxygen control).
Replace oxygen sensor as necessary (i.e., if calibration is unsuccessful, per manufacturer).
Mouse Enclosure Set up
Retrieve one plastic bin and clean it with 70% ethanol.
Wipe down with water on cloth and then with a dry cloth.
Line the bottom of the plastic bin with lab table soakers (shiny side down).
Place 10–15 Lab Diet 5015 pellets and ¼ contents of a Hydrogel cup in a 10 cm Petri dish.
Place the Petri dish in the back right corner of the plastic bin (see Figure 1).
Figure 1. Mouse enclosure setup. Shows appropriate setup of mouse enclosure for hypoxic chamber. Plastic bin previously cleaned with 70% ethanol is lined with VERSI-DRY lab table soaker. A 10 cm Petri dish is filled with several food pellets and ¼ contents of a Hydrogel cup and placed in the back right corner.
Chamber Set up
Place the mouse enclosure in the back right corner of the hypoxia chamber (see Figure 2A).
If performing two exposures in the same chamber, place a cutting board to the left of the first mouse enclosure, then place the second mouse closure to the left of the cutting board to prevent mice from visualizing each other.
Fill a 10 cm Petri dish with a liberal amount of fresh soda lime (around 15 g).
Use fresh soda lime in each exposure to maximize its absorptive ability.
Soda lime is added to scavenge for expired carbon dioxide (CO2) that may accumulate in the sealed chamber.
We have used this same amount of soda lime for two mice in the same chamber.
Figure 2. Hypoxia chamber setup. A. Appropriate setup for hypoxia chamber when one exposure is being performed. The enclosure setup is placed in the back right corner of the chamber. A liberal amount of soda lime is added to a Petri dish, which is placed on the floor of the chamber (indicated by red arrow). B. Appropriate setup for hypoxia chamber when two exposures are being performed. The enclosure setups are placed against the back wall of the chamber, side by side. A large cutting board is placed between chambers to prevent mice from visualizing each other. A liberal amount of soda lime is added to a Petri dish, which is placed on the floor of the chamber. C. Zoomed out view of appropriate setup for hypoxia chamber when two exposures are being performed, with oxygen controller on top of chamber. D. Oxygen controller. Highlighted are the buttons (1) for adjusting the inspired oxygen levels and the switch (2) for turning on the flow to the chambers. As pictured, the chamber is currently set to room air, 21%.
Acclimation
Place the mouse in the prepared enclosure within the hypoxia chamber.
Close and seal the door to the hypoxia chamber.
Allow the mouse to roam freely within the enclosure for 1 min.
Normoxic Control (if performing hypoxia, jump to Section F)
Ensure the hypoxia chamber is closed and sealed correctly.
Ensure the ProOx 360 controller is powered on. If so, it will display the current percentage of inspired oxygen, also known as fraction of inspired oxygen (FiO2), in the chamber (it should be approximately 21%).
Ensure the switch on the right side of the sensor is set to “OFF,” not “GAS.”
If performing only normoxia, there is no need to open the gas canister; if performing both normoxia and hypoxia at once, the gas canister will be open. If “OFF” is selected, no nitrogen will flow to the chamber.
Start a timer for the desired normoxic exposure duration.
After the desired exposure time, continue to section L.
Starting the Hypoxic Exposure
Open the nitrogen canister and visualize the kPa nitrogen remaining using the meter on the right side of the regulator (see Figure 3).
Approximately 3,000 kPa is necessary for 8 h of 5% FiO2 in one chamber; if performing hypoxia in two chambers, approximately 6,000 kPa is necessary.
Figure 3. Gas regulator dials. The right dial (1) is the inlet pressure gauge and shows the amount of nitrogen left in the canister in kPa. The left dial (2) is the delivery pressure gauge and shows the flow rate, which should stay between 15 and 20 psi during an exposure.
Ensure the ProOx 360 controller is on (if so, it will display the current FiO2 percentage in the chamber; it should be approximately 21%).
Ensure the switch on the right side of the sensor is set to “OFF,” not “GAS.”
Set initial FiO2 value by holding down the leftmost button labeled “*” under FiO2 reading, using the “▼” and “▲” buttons to navigate to the desired value, and then releasing all buttons.
Before turning the switch from “OFF” to “GAS,” change FiO2 setpoint to 19%.
Current FiO2 setpoint can be checked at any point by holding the “*” button.
Simultaneously start a timer (counting up) and turn the switch from “OFF” to “GAS.”
Nitrogen gas will start flowing:
If a loud, high-pitched, whining noise is heard, tighten the connection between the regulator and the nitrogen canister.
If the tubing is well connected to the canister, there will be a low, intermittent hissing noise when the controller is using nitrogen to regulate O2 levels.
Within the first 2 min, check the flow rate on the left meter of the regulator; it should be between 15 and 20 psi (see Figure 3).
If the flow rate is too high, decrease it by turning the gold lever counterclockwise.
If the flow rate is too low, increase it by turning the gold lever clockwise.
Titrating Oxygen from 21% to 5%
At the time points given in Table 1, change the FiO2 setpoint to the corresponding value by holding down the leftmost button labeled “*” under the FiO2 reading, using the “▼” to navigate to the desired value, and then releasing both buttons.
Regarding differing FiO2 setpoints and actual FiO2 readings, see Notes.
Table 1. Setpoints by time with expected FiO2.
Time after start (min) FiO2 setpoint (%) Actual FiO2 reading (%)
0 19 20–21
2 17.5 18.5–19
5 Keep at 17.5 17–17.5
7 15 16.5–17
10 Keep at 15 14.5–15
12 12.5 14–14.5
15 Keep at 12.5 12–12.5
17 10 12–12.5
20 Keep at 10 10.5–11
22 7.5 9.5–10
25 Keep at 7.5 or change to 5 if not at 7.5 8–8.5
26 5 7.5–8
30 Keep at 5 5–5.5
Reaching Steady State FiO2 at 5%
After the first 30 min of exposure, the FiO2 in the chamber will be around 5%.
The FiO2 reading typically fluctuates approximately 0.2% in any direction, i.e., from 4.8% to 5.2%; any fluctuation greater than 0.2% from the setpoint means the ProOx 360 controller should be recalibrated, or the hypoxia chamber should be inspected per manufacturer instructions.
Visualize the mouse inside the chamber, ensuring it is breathing.
Breaths will appear shallow and quick.
The mouse will often choose to sleep near or in the Petri dish for the duration of the exposure, exhibiting minimal movement.
Stay for an additional 10 min, ensuring that the equipment is working correctly, the flow rate is between 15 and 20 psi, and the FiO2 value remains constant (within 0.2% of the setpoint).
Checking on the Mouse During Exposure
Approximately 4 h into the exposure, check on the mouse, ensuring it is still breathing.
Check that the flow rate is between 15 and 20 psi (see Figure 3) and that the FiO2 reading remains constant (within 0.2% of the setpoint).
Changing the Nitrogen Canister During Exposure
If necessary, the nitrogen canister can be swapped for a new one during the exposure.
Avoid, if possible. Replace the canister before the exposure when the tank is at or below 3,000 kPa for one chamber and 6,000 kPa for two.
If changing the canister during the exposure, do not open the hypoxia chamber; the FiO2 value will remain relatively constant if the canister is changed quickly.
Change the nitrogen canister out quickly, moving the regulator to a new canister.
The process should not take more than 3–4 min.
After changing the canister, wait for nitrogen to flow into the chamber.
Adjust the flow rate as necessary, so it lies between 15 and 20 psi (see Figure 3).
Ending the Hypoxic Exposure
When the desired exposure time is reached, immediately open the door to the hypoxia chamber, allowing air to rush in.
Remove the mouse enclosure from the chamber and set it on a nearby surface.
Turn off the ProOx 360 controller and close the nitrogen canister completely.
Cleaning Up
Remove the mouse from the enclosure and place it into a clean new cage.
Visualize the mouse periodically while cleaning to ensure it is recovering well.
A normoxic mouse will be alert and moving around.
A hypoxic mouse will be cold and move slowly and sluggishly; it will recover within 5 min.
Remove all the materials from the mouse enclosure and discard.
Clean the mouse enclosure with 70% ethanol.
Throw out the soda lime.
If the soda lime is excessively purple, it is scavenging a lot of CO2; inspect the hypoxia chamber for issues and add more soda lime when performing the next exposure.
Notes
The oxygen sensor is calibrated for low oxygen control, as detailed by the ProOx 360 manual. Therefore, at higher FiO2 setpoints near the beginning of the exposure, it is normal and expected for actual FiO2 readings to be lower than the setpoint as one approaches the next setpoint. This discrepancy in setpoint and actual O2 reading will normalize as the setpoint is lowered; the actual FiO2 reading approaches the setpoint at lower values. Therefore, at a setpoint of 5% inspired oxygen, the actual oxygen reading will remain steady from a range of approximately 4.8%–5.2%.
Acknowledgments
The development of this protocol was supported by the National Institutes of Health (Grant: K08NS119797-01A1, 5K12HD043245-18, R01MH092535, R01MH092535-S1, and U54HD086984), and institutional grants from the Children’s Hospital of Philadelphia, including Neurology Black Tie Tailgate Fund, Foerderer Grant, and K-readiness Pilot award.
Competing interests
The authors have no competing interests to disclose.
Ethics
Studies involving animals were approved by the Institutional Animal Care and Use Committee (IACUC) at the Children’s Hospital of Philadelphia (Approved Number: IAC 22-000547).
References
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High-throughput Method for Determination of Seed Paternity by Microsatellite Markers
Samik Bhattacharya
IB Ian T. Baldwin
Published: Vol 3, Iss 8, Apr 20, 2013
DOI: 10.21769/BioProtoc.452 Views: 12810
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Original Research Article:
The authors used this protocol in The Plant Journal Aug 2012
Abstract
In this protocol, determination of seed paternity by microsatellite markers in Nicotiana attenuata is described. However, this does not include a protocol for the novel marker selection/identification, but rather exploits the markers generated for a closely related species N. tabacum (Bindler et al., 2007). This is a high-throughput protocol optimized and streamlined for one skilled person to process 384 (96 x 4) seeds in 5 days, from DNA isolation (from seedlings) to paternity assessment by microsatellite genotype data.
Keywords: Microsatellite genotyping Multiplex PCR High-throughput seed paternity test Nicotiana attenuata
Materials and Reagents
Agencourt Chloropure Kit (this kit is discontinued by Beckman Coulter but can be ordered) or Quiagen MagAttract 96 DNA plant core kit (QIAGEN, catalog number: 67163 )
Qiagen Type-it Multiplex PCR kit (QIAGEN, catalog number: 206243 )
QIAquick PCR purification kit (QIAGEN, catalog number: 28106 )
Liquid nitrogen
100% Isopropanol, ultrapure
Freshly prepared 70% ethanol made with nuclease free water
Note: 70% ethanol is hygroscopic, always make fresh for optimal result.
Agarose
Ethydium bromide solution
Nuclease free water
Pure molecular biology grade ethanol (96– 100%)
Note: Calculate the volume of ethanol needed before you start. A new kit of 24 plates needs about 5 L of ethanol.
GENSCAN 500 ROX (Applied Biosystems, catalog number: 401734 )
1x TAE (Tris-Acetate-EDTA) buffer (see Recipes)
Equipment
2.2 ml Ritter Deep-well plates (ABGene, catalog number: AB-6661 )
Adhesive plate film (ABGene, catalog number: AB-0558 , AB-626 , AB-662 )
4 mm steel balls (SPEX SamplePrep, catalog number: 2150 )
Pipette tips
Processsing Plate: Deep-well titer plate with a 96-well format (SPEX SamplePrep, catalog number: 2210 )
Destination Plate: 300 μl round bottom microtiter plate (96 well, 300 μl well capacity, round bottom) (Corning, Costar®, catalog number: 07-200-105 )
Desktop centrifuge for 96 well plates
Reagent reservoir
Genogrinder (SPEX SamplePrep, catalog number: 2010 )
Cooling block (SPEX SamplePrep, catalog number: 2665 )
Steel ball dispenser (SPEX SamplePrep, catalog number: 2100 )
Multi-channel pipettes (0.1-10, 10-100, 30-300 μl)
Agencourt Supermagnet magnetic Plate (Agencourt SPRIPlate 96R-Ring Magnet Plate, catalog number: A29164 )
BioRad Gel casting tray, running tray, power pack etc (Bio-Rad Laboratories)
Nanodrop spectrophotometer (Nanodrop)
Pipette (0.2-2 μl), pipette tips, soft tissue paper
ABI 3100 Genetic Analyzer (Applied Biosysyems)
Procedure
Sample grinding (Day 1)
Take up to 40 mg fresh tissue sample (leaf punches/seedling) in 2.2 ml plate. Take care to group similar samples/treatments/experimental designs together for easier data handling during sequencing and genotype analysis.
Dispense 2 steel balls in each well with dispenser.
Balance two plates exactly for grinding in Genogrinder.
Seal the plate(s) with adhesive plate film.
Cool the plate(s) in liquid nitrogen.
Cool the cooling racks along with the plates.
Grind in Genogrinder at Speed 250, 1x, for 1 min. If not crushed completely, again for 1 min.
DNA isolation (Day 1)
Assembly in step B-1 is performed once for each new Agencourt Chloropure kit. If you have already made the following preparations for a previous experiment, please skip ahead to step B-2. Standard RNase treatment can be included either at the step B-5 with the homogenized lysate (requires large amount of enzyme, but convenient for high-throughput) or selectively after determination of the degree of RNA contamination at "quality check".
Add 80 ml of 100% Isopropanol to the wash buffer bottle provided with the kit. After addition of Isopropanol invert the bottle to mix. Once the solution has been thoroughly mixed, store at room temperature.
Prepare bind buffer: Combine 6 μl bind buffer with 150 μl of 100% isopropanol for each individual isolation in a nuclease free vessel of suitable size (for example: for 10 isolations, add 60 μl of bind buffer to 1.5 ml of 100% isopropanol in a 15 ml conical tube). Vortex bind buffer bottle thoroughly before combining. Unused combined solution should be discarded.
Homogenize each sample in 300 μl of lysis buffer, provided with the kit. (sample input should not exceed three 6 mm lyophilized leaf punches or 40 mg ground seeds or fresh leaf material.)
Centrifuge lysate for 10 min at 1,100 RCF at room temp to pellet debris.
Transfer 150 μl of homogenized lysate to 1.2 ml processing plate.
Pipette 150 μl bind buffer (prepared in step B-2), mix by slowly pipetting 5 times and incubate at room temperature for 5 min.
Move the plate onto the Agencourt Supermagnet and separate for 2-4 min. Wait for the solution to clear before proceeding to the next step.
Slowly aspirate the cleared solution from the plate and discard.
Note: Aspirate from the top down to avoid disturbing the pellet. This step must be performed while the plate is situated on the magnet. Do not disturb the separated magnetic beads. If beads are drawn out, leave a few microliters of supernatant behind.
Remove the plate from the magnet and add 300 μl of Wash buffer. Pipette mix 10 times and incubate for 1 min at RT.
Return plate to the magnet and separate for 2-4 min. Wait for the solution to clear before proceeding to the next step.
Slowly aspirate the cleared solution from the plate and discard. This step must be performed while the plate is situated on the magnet.
Remove the plate from the magnet and add 300 μl of 70% ethanol. Pipette mix 10 times to re-suspend the beads.
Return plate to the magnet and separate for 2 min. Wait for the solution to clear before proceeding to the next step.
Slowly aspirate the cleared solution from the plate and discard.
Repeat steps l-n for a total of 2 ethanol washes.
Let the plate air dry for 5 min at room temperature. The plate should air-dry until the last visible traces of ethanol evaporate. Over-drying the sample may result in a lower recovery.
Remove the plate from the magnet and add 50 μl of nuclease-free water. Re-suspend the beads by pipette mixing 10 times.
Note: Smaller or larger elution volumes can be used for more or less concentrated product; however the minimum elution volume should be 40 μl to ensure complete elution. Optimal elution volumes need to be experimentally determined.
DNA quality/quantity check
1) Quality
a) Prepare 0.8% agarose gel with 1x TAE buffer. Add 2 μl Ethydium Bromide before casting.
b) Load 2 μl DNA+1 μl loading dye
c) Add 1 kb or 100 bp ladder for reference
d) Run at constant 100 V for 30 min
e) Check DNA for quality, presence of RNA and quantity in gel doc system and record.
Figure 1. DNA quality check on 0.8% agarose gel. Lane 1-6, 8-13 represent extracted DNA samples, lane 7 represents DNA marker.
2) Quantity
a) Follow the procedure to measure concentration of DNA in Nanodrop.
b) Export to excel file for reference.
Dilution of DNA sample
a) Dilute the samples to 50 ng/μl as working stock.
b) Dispense them in 3 PCR plates (for 3 multiplex PCR reactions) similarly and maintaining the sample organization of working DNA plate. Make a record of the samples.
PCR amplification (Day 2)
Multiplex groups
Primer groups are selected based on primer sequences using software MultiPLX version 2.0 (available at http://bioinfo.ut.ee/?page_id=167, Ref: doi: 10.1093/bioinformatics/bti219) to select multiplex grouping. Medium stringency was chosen to select groups.
Example of 3 multiplex groups of 8 primer pairs:
Table 1. Example of 3 multiplex groups of 8 primer pairs:
10x Primer mix
First make 100 μM primer stock (if using 50 μM primer stock, adjust the volume of the table below accordingly).
Mix all primers according to the table below to get 3 primer-mix groups (sufficient for 1x PCR plate i.e. 96 samples).
Table 2. Schematic representation of preparation of 3 primer mix groups:
PCR reaction mix
Thaw the 2x Type-it Multiplex PCR Master Mix (MM) (if stored at -20 °C), template DNA (already dispensed in PCR plates), RNase-free water, and the primer mix. Mix the solutions completely before use.
Note: It is important to mix the solutions completely before use to avoid localized concentrations of salts.
Prepare a reaction mix according to the table below. Note: The reaction mix typically contains all the components required for multiplex PCR except the template DNA. Prepare a volume of reaction mix 10% greater than that required for the total number of reactions to be performed. For reaction volumes less than 25 μl, the 1:1 ratio of Type-it Multiplex PCR Master Mix to primer mix and template should be maintained.
Note: Starting with an initial Mg2+ concentration of 3 mM is recommended as provided by the 2x Type-it Multiplex PCR MM.
Table 3. Reaction Mix preparation for one 96 well plate samples
(modified after manufacturer's instruction)
Mix the reaction mix thoroughly and dispense appropriate volumes into PCR tubes or plates. Note: Mix gently, for example, by pipetting the reaction mix up and down a few times. Due to the hot start, it is not necessary to keep samples on ice during reaction setup.
PCR condition
Table 4. PCR condition (according to manufacturer's instruction)
PCR programme:
Ctrl. Tube
Lid- 105 °C
(1)95 °C-05:00 min
(2)95 °C-00:30 min
(3)60°C- 01:30 min
(4)72 °C-00:30 min
(5)Go to step (2), repeat 29
(6)60°C-30:00 min
(7)20 °C- ∞
(8)End
(9)Store PCR products in -20 °C, till further processing.
PCR check
Check PCR products randomly on 1.8% agarose gel (this is just to check if everything is working before proceeding to next steps. So choose random samples). Load 4 μl product and 100 bp ladder.
Note: Use only Xylene Cyanol loading dye as Bromophenol Blue dye interfere with the amplified band range.
PCR purification (Day 3)
Add 75 μl nuclease free water to each well of PCR plate (containing 25 μl PCR product) to make it 100 μl.
In a 96 well plate (at-least 1 ml capacity) dispense 300 μl Buffer PM. Add 100 μl PCR sample and mix by pipetteing.
Apply the samples to the wells of the QIAquick plate while it is fitted with the collecting deepwell plate.
Centrifuge at 1,100 RCF (g) for 2 min.
Discard flow-through.
Note: If the sample volume is more than 600 μl apply the remaining samples to the wells of the QIAquick plate and repeat step 4.
Wash wells of QIAquick plate by adding 900 μl of Buffer PE to each well and centrifuge at 1,100 RCF (g) for 2 min.
Repeat step 4-f.
Discard flow-through and gently soak any buffer remaining on the tip of column with soft tissue.
Centrifuge at 1,500 RCF (g) for 4 min.
Important: This step removes residual Buffer PE from the membrane.
Let the plate dry for 5 min or until all the ethanol (of Buffer PE) evaporates. Place it under fume hood for 10 min is sufficient.
To elute, place the plate on collection tubes (provided), add 50 μl of RNase-free water (provided) to the center of each well of the QIAquick 96 plate, incubate for 2 min, and centrifuge at 1,500 RCF (g) for 2 min.
Important: Ensure that the elution buffer is dispensed directly onto the center of QIAquick membrane for complete elution of bound DNA. Please note that the average eluate volume is 60 μl from 80 μl elution buffer volume, and 40 μl from 60 μl elution buffer volume.
Quality check
Check Purified PCR product by nanodrop or 1.8% agarose gel.
Note: For nanodrop analysis, centrifuge the samples at 1,500 RCF for 2 min and estimate from the upper layer (to precipitate any remaining silica particles from the column, which sometimes interfere with sensitive nanodrop estimation). Imporant: It is better to check randomly the purified product on 1.8% agarose gel to be sure of quality. As this is a multiplex PCR, do not expect a clear band. The gel will appear as smear of many bands.
Figure 2. PCR amplification check on 1.8% agarose gel. Lanes 1-15 represent PCR products (with a couple of failed amplification on lane 7 and 14), lane 16 represents 100bp DNA marker.
Dilution
It is not needed to further dilute the samples if you start with 50 ng DNA sample and followed the procedure exactly. At this step the concentration of samples should be around 250 ng/μl.
For the size sequencing set up, it is recommended to dilute samples in this step to facilitate sample handling.
Add 200 μl nuclease free water to each purified sample tube (1/5th dilution). So the concentration becomes 50 ng/μl.
Size sequencing (Day 4)
Sequencing mix
The size sequence mix for each sample contains
5 μl purified PCR product (250 ng total)
4.5 μl nuclease free water
0.5 μl GENSCAN 500 ROX marker
For a single sequence plate (prepare for 105 samples), set up MM as below:
Mix 472.5 μl nuclease free water with 52.5 μl of ROX marker.
Dispense 5 μl of above MM to each of sequencing plate.
Mix in 5 μl purified PCR samples.
Do not leave any sample well blank. Fill it with Nuclease free water.
Cover the plate with adhesive seal mat.
Centrifuge the plates briefly at 1,500 RCF.
Prepare sequencing table of samples.
Prepare the sample list conveniently for recognition later. e.g. Sample name_primer mix group_Sample number_any other info.
Table 5. Sample list example
Analysis (Day 5)
Before starting analysis, import the data files generated by the sequencer to the computer with GeneMapper software. It is recommended to read the manual if you want to modify and fine-tune the marker settings and allele size binning for genotyping.
Genotype table
Genotyping in GeneMapper
1) Go to 'file' menu and create new project. Name it conveniently.
2) Import your samples that belong to one primer mix group.
3) Create marker panel and bin set for each multiplex primer groups.
Refer to the manual for modifying or creating a new marker panel for new set of markers/primer mix in microsatellite. This involves:a) Marker set creation
b) Autobinning of alleles
c) Manual binning of alleles
d) Create new marker panel and bin set.
4) Use predefined marker panel for respective samples
Go to 'file' menu and create new project. Name it conveniently.
Import your samples that belong to one primer mix group.
Create marker panel and bin set for each multiplex primer groups
Refer to the manual for modifying or creating a new marker panel for new set of markers/primer mix in microsatellite. This involves:
Marker set creation
Autobinning of alleles
Manual binning of alleles
Create new marker panel and bin set.
Use predefined marker panel for respective samples
Analysis parameters
1) Select the table setting as ‘Microsatellite default’
2) Select the analysis method as ‘Microsatellite analysis method’
3) Set the predefined panel as EV1 for primer mix 1 and so on.
4) Set size standard as GEN500.
5) Analyze
6) If some samples fail to match size standards, go to edit size standards and override size. If it does not improve the sizing, then there was some problem with the sample.
a) Open the genotype Tab. Do not bother about the GQ (genotype quality) column as it is set to a very high stringency.
b) Go to tools-panel manager-microsatellite kit-attenuata panel-EV1 binset. Select ‘show project alleles’. If you see any ‘*’ out of the grey bars (defines the range of allele bins), then either modify the range of existing bins (click on the grey bar and you’ll get handles for modification), or add a new bin (click on the blank space near your odd allele (that is not binned) and name it. Save the panel. Again analyze the samples with the modified binset.
c) If you want to see data for only two alleles and want to modify the way you want your data, modify the table output style. However, manual inspection of allele size, height etc is sometimes necessary to ensure optimal result than automation.
d) Go to file and export the genotype table in .csv or other excel compatible format.
Paternity analysis in COLONY
For paternity/maternity analysis, i.e. to determine the parent of an offspring the software COLONY (http://www.zsl.org/science/research/software/colony,1154,AR.html).
COLONY is a Fortran program written by Jinliang Wang . It implements a maximum likelihood method to assign sibship and parentage jointly, using individual multilocus genotypes at a number of codominant or dominant marker loci. (Jones and Wang, 2010).
Formatting of genotype table.
1) Keep only the sample name, two allele sizes for each marker for all the marker.
2) Compile data for all the marker sets into a single datasheet for all offspring and all marker.
Marker table (save as tab delimited .txt file and rename 'marker').
Table 6. Marker details
Parent table (save as tab delimited .txt file and rename 'father/mother')
Table 7. Paternal allele list
Table 8. Maternal allele list
Offspring table (save as tab delimited .txt file and rename 'offspring')
Table 9. Offspring allele list
Analysis parameters
Feed all the information step by step as asked by the software and brose for the files to upload.
A typical parameter is as follows:
Number of loci:16
Number of offspring in the sample:
Number of male candidates:0
Number of female candidates:
Number of known paternal sibships:0
Number of known maternal sibships:0
Number of offspring with excluded fathers:0
Number of offspring with excluded mothers:0
Male mating system:Polygamy/monogamy
Female mating system:Polygamy/monogamy
Number of threads : 1
Number of Excluded Paternal Sibships:0
Number of Excluded Maternal Sibships:0
Seed for random number generator:1,234
Allele frequency:No updating by accounting for the inferred relationship
Species:Diploid/haploid
Sibship size prior:No
Known population allele frequency:No
Number of run:1
Length of run : short/medium/long
Monitor intermiediate results by:Every 1 second
Prob. a mum is included in the female candidates:0.5
Project data input produced:
NOTE to the Project:
Analysis outputs
1) Select Show result-'best configuration'.
2) Copy the table of assigned father ID/mother ID to each sample.
3) Sort parents and count offsprings sired by them in excel.
Population analysis in GenAlEx
Population analysis in GenAlEx
When comparing populations for genotypes, or simply want to look at the genotypic diversity within a population, apart from parental analysis, it is better to use the excel addon 'GenAlEx' (http://biology.anu.edu.au/GenAlEx/Welcome.html). (Ref: Peakall R. and Smouse P.E. 2006. Genalex 6: Genetic analysis in Excel. Population genetic software for teaching and research, Molecular Ecology Notes, Volume 6, Issue 1, pages 288–295).
This can analyze:
Heterozygosity, F-statistics and Polymorphism
Allelic Patterns
Allele List
Allele Frequencies and Principal Component Analysis (PCA).
Recipes
1x TAE (Tris-Acetate-EDTA) buffer
Prepare a stock solution of EDTA (ethylenediamine tetraacetic acid)
For a 500 ml stock solution of 0.5 M EDTA, dissolve 93.05 g EDTA disodium salt (FW = 372.2) in 400 ml deionized water and adjust the pH with NaOH to 8.0. Make up the final volume to 500 ml.
Prepare a 50x Stock Solution of TAE
Dissolve 242 g Tris base (FW = 121.14) in approximately 750 ml deionized water. Add 57.1 ml glacial acid and 100 ml of 0.5 M EDTA (pH 8.0) and adjust the solution to a final volume of 1 L. This stock solution can be stored at room temperature for a long time. The pH of this buffer needs no further re-adjustment and remains about 8.5.
Prepare a Working Solution of 1x TAE
Dilute the 50X stock solution by 1:50 with deionized water. Final solute concentrations are 40 mM Tris acetate and 1mM EDTA.
Acknowledgments
This work was supported by the Max Planck Gesellschaft. The protocol was adapted from the publication: Kessler et al. (2012).
References
Bindler, G., van der Hoeven, R., Gunduz, I., Plieske, J., Ganal, M., Rossi, L., Gadani, F. and Donini, P. (2007). A microsatellite marker based linkage map of tobacco. Theor Appl Genet 114(2): 341-349.
Jones, O. R. and Wang, J. (2010). COLONY: a program for parentage and sibship inference from multilocus genotype data. Mol Ecol Resour 10(3): 551-555.
Kessler, D., Bhattacharya, S., Diezel, C., Rothe, E., Gase, K., Schöttner, M. and Baldwin, I. T. (2012) Unpredictability of nectar nicotine promotes outcrossing by hummingbirds in Nicotiana attenuata. Plant J 71(4): 529-538.
Article Information
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© 2013 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Bhattacharya, S. and Baldwin, I. T. (2013). High-throughput Method for Determination of Seed Paternity by Microsatellite Markers. Bio-protocol 3(8): e452. DOI: 10.21769/BioProtoc.452.
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Plant Science > Plant molecular biology > DNA > Genotyping
Plant Science > Plant physiology > Tissue analysis
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Collection of Xylem Exudates from the Model Plant Arabidopsis and the Crop Plant Soybean
SO Satoru Okamoto
AK Azusa Kawasaki
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4520 Views: 1566
Reviewed by: Ashish RanjanPooja VermaMalgorzata Lichocka
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Original Research Article:
The authors used this protocol in Plant Physiology Aug 2022
Abstract
A number of molecules, such as secreted peptides, have been shown to mediate root-to-shoot signaling in response to various conditions. The xylem is a pathway for water and molecules that are translocated from roots to shoots. Therefore, collecting and analyzing xylem exudates is an efficient approach to study root-to-shoot long-distance signaling. Here, we describe a step-by-step protocol for the collection of xylem exudate from the model plant Arabidopsis and the crop plant soybean (Glycine max). In this protocol, we can collect xylem exudate from plants cultured under normal growth conditions without using special equipment.
Graphical abstract:
Xylem exudates on the cut surfaces of an Arabidopsis hypocotyl and a soybean internode.
Keywords: Arabidopsis (Arabidopsis thaliana) Soybean (Glycine max) Xylem sap Long-distance signaling Proteomics
Background
Plants consist of multiple organs that play distinctive roles during plant life. Hence, organ-to-organ communication is indispensable for plants to adapt to environmental stresses and maintain homeostasis at the whole-plant level. It is known that various types of macromolecules, such as phytohormones, RNAs, proteins, and peptides mediate long-distance signaling (Okamoto et al., 2015, 2016; Lu et al., 2020). The xylem plays an important role in the translocation of water and micronutrients from roots to shoots. In addition, long-distance signaling molecules, including small secreted peptides and phytohormones, are translocated from roots to shoots through the xylem. Therefore, collecting and analyzing xylem exudates is an effective approach to identify novel long-distance mobile molecules.
To date, several methods have been developed to collect xylem exudates (Buhtz, 2004, Goodger et al., 2005; Dafoe and Constabel, 2009), and the appropriateness of a given method is dependent on plant species and conditions. One method uses a pressure chamber to obtain xylem exudate from woody plants. In this method, roots are placed inside a sealed chamber, and pressurized gas is added to the chamber. This method can be applied to woody plants that have mechanically stronger tissues than herbaceous plants, and a precise protocol was written by Flajšman et al. (2017). Another method depends on root pressure and is usually applied to herbaceous plants whose tissues are soft. Root pressure is one of the driving forces of xylem sap. Accumulation of solutes in root xylem results in low water potential and generates positive hydrostatic pressure in the xylem (Taiz et al., 2015). Although the quantity of xylem exudates obtained with this method depends on plant species and conditions, this method requires no special equipment and has been applied to many herbaceous plants, including Arabidopsis thaliana (Iwai et al., 2003; Buhtz et al., 2004; Kehr et al., 2005; Alvarez et al., 2006; Djordjevic et al., 2007; Ligat et al., 2011; Ko et al., 2014; Tabata et al., 2014; Okamoto et al., 2015; Luo and Zhang, 2019). However, the collection of xylem exudates is likely not familiar to many researchers, and it is difficult to find a step-by-step protocol for this method.
Previously, we collected xylem exudate from soybean to conduct peptidome analysis and identified various endogenous root-to-shoot mobile peptides (Okamoto et al., 2015). In addition, we analyzed xylem exudate from the model plant Arabidopsis thaliana and detected mature CLAVATA3/ESR-related 2 peptides (Okamoto et al., 2022a). In this protocol, we describe step-by-step procedures for the collection of xylem exudates from both the model plant Arabidopsis and the crop plant soybean.
Part I. Collection of xylem exudates from Arabidopsis
Materials and Reagents
1.5 mL tube (BIO-BIK, catalog number: ST-0150F)
Plastic square dish (140 mm × 100 mm, height 18 mm/EIKEN, catalog number: AW2000)
Plastic Petri dish (ø 85 mm, height 20 mm/EIKEN, catalog number: AP2310)
Razor blade (FEATHER, FA-10)
Micropipette [Nichiryo, catalog number: 00-NPX2-2 (0.1–2 µL)]
Arabidopsis seeds
Ethanol (FUJIFILM Wako, catalog number: 057-00451)
Tween 20 (MP Biomedicals, catalog number: 194841)
Sodium hypochlorite solution (FUJIFILM Wako, catalog number: 197-02206)
Murashige and Skoog (MS) plant salt mixture (FUJIFILM Wako, catalog number: 392-00591)
Gamborg’s vitamin solution 1,000× (Sigma-Aldrich, catalog number: G1019)
Sucrose (FUJIFILM Wako, catalog number: 196-00015)
Agar (FUJIFILM Wako, catalog number: 016-11875)
Culture media (100 mL) (see Recipes)
Equipment
Growth chamber (Nippon Medical & Chemical Instruments, model: LH-241S)
Procedure
Place Arabidopsis seeds in 1.5 mL tubes.
Add 1 mL of 70% ethanol and wash the seeds for 1 min.
Remove the ethanol solution.
Add 1 mL of H2O, 10 µL of 10% Tween 20, and 50 µL of sodium hypochlorite solution and mix using a vortex mixer.
Wash the seeds for 15 min by gently inverting the tubes.
Remove the solution and rinse the seeds five times with sterilized water.
Sow the seeds in plastic Petri dishes with culture media (see Recipes).
Incubate at 4 °C for three days.
Cover the dishes with aluminum foil to grow seedlings in darkness and incubate at 23 °C for five days.
Remove the aluminum foil. At this stage, the seedlings are etiolated with elongated hypocotyls (Figure 1A). Note that further darkness affects seedling viability.
Grow the seedlings under a 10 h light/14 h dark cycle at 23 °C for five days. The cotyledons will become green (Figure 1B).
Transfer the Arabidopsis seedlings to plastic square dishes with culture media [with or without 1% sucrose (see Notes 1)] on a clean bench.
Place the dishes vertically and incubate the plants under a 10 h light [100 µmol/m2s photosynthetic photon flux density (PPFD)]/14 h dark cycle at 23 °C for 14 days (Figure 1C).
Cut the hypocotyls with a razor blade (Figure 1D). Within 20–40 min, xylem exudates will form droplets on the cut surface of the cotyledon (Figure 1E).
Wipe the first droplets with soft paper to avoid contamination of phloem sap and then collect the droplets with a micropipette. The droplets can be sampled at approximately 30 min intervals.
Store the collected exudates at -80 °C.
Figure 1. Collection of xylem exudates from Arabidopsis. (A) Arabidopsis seedlings at five days after germination (DAG), grown under dark conditions. (B) Arabidopsis seedlings at 10 DAG, incubated under a light/dark cycle for five days. (C) Arabidopsis plants at 24 DAG. (D) Arabidopsis hypocotyls are cut with a razor blade. (E) and (F) Xylem exudates form droplets on the cut surface of hypocotyls, and these droplets are collected with a micropipette. Each droplet is indicated by a triangle.
Notes
In our study (Okamoto et al., 2022a), because the target peptide gene responds to low-carbon conditions, Arabidopsis was cultured without sucrose from 10–24 DAG. The exudate was collected for 4 h, and approximately 320 µL of exudate was obtained from 360 plants. Application of sucrose to the culture medium increases the yield of xylem exudates.
The amount of xylem exudates obtained from Arabidopsis is too small to conduct proteomics analysis (approximately 1 µL/plant), so the purpose of analyzing Arabidopsis xylem exudate should be the detection of interesting (target) molecule(s).
To conduct a comprehensive analysis, a larger amount of xylem exudates must be collected from larger plants (see Part II).
Recipes
Culture media (100 mL)
Reagent Final concentration Amount
Murashige and Skoog (MS) salt mixture 1/2× 0.23 g
Sucrose 1 or 0% (w/v) 1 or 0 g
Gamborg’s vitamin solution 1,000× 1× 100 µL
Adjust the pH to 5.7 and add 0.8 g agar; then, autoclave the solution for 20 min at 121 °C.
Part II. Collection of xylem exudates from soybean
Materials and Reagents
Soybean seeds
50 mL centrifuge tubes (Labcon, catalog number: 3181-345)
Plastic square dish (140 mm × 100 mm, height 18 mm/EIKEN, catalog number: AW2000)
Silicon tube [select a tube whose inner diameter is fitted to or slightly larger than (less than 1 mm larger) the cut stems. In the case of soybean, the diameter of the lower internodes is 4–7 mm approximately seven weeks after germination. The length of the tube depends on the length of the flat needle or micropipette tip. When the flat needle described below was used, we cut the tube into approximately 8 cm lengths [AsOne, catalog number: 6-586-12 (4 mm i.d.), 6-586-17 (5 mm i.d.), 6-586-20 (6 mm i.d.), and 6-586-25 (7 mm i.d.)]
Plastic pot (ø 150 mm, height 127 mm)
Garden shears
Flat needle (AsOne, catalog number: 1-2752-01)
5 mL syringe (TERUMO, catalog number: SS-05SZ)
Ethanol (FUJIFILM Wako, catalog number: 057-00451)
Vermiculite
Clay
Nutrition solution for soybean (1 L) (see Recipes)
Equipment
Greenhouse or growth chamber (Nippon Medical & Chemical Instruments, model: LH-411PFQDT-SP)
Centrifuge (Kubota, model: 2410)
Procedure
Place seeds (less than 25 mL to facilitate washes) in 50 mL centrifuge tubes and add approximately 40 mL of 70% ethanol to wash the seeds by inverting gently for 1 min.
Rinse the seeds with distilled water five times.
Place soft wet paper on plastic square dishes and arrange the seeds on the paper (approximately 25 seeds/dish) (Figure 2A).
Cover the seeds with wet, soft paper and place a lid on the dishes to maintain higher humidity (Figure 2B).
Incubate the seeds in the square dishes under a 16 h light (200 µmol/m2s PPFD)/8 h dark cycle at 23 °C for two days.
Select healthy seedlings (e.g., relatively long roots, greening cotyledon) and transplant them into vermiculite in plastic pots.
Place the pots in a growth chamber [16 h light (900 µmol/m2s PPFD)/8 h dark, 23 °C, and humidity not controlled] or greenhouse and supply a sufficient amount of nutrition solution. The frequency of solution application depends on the plant age, conditions, and weather (in the case of a greenhouse).
Approximately seven weeks after germination, cut the hypocotyls or lower internodes (first or second internodes from hypocotyls) with garden shears (Figure 2C, D). The hypocotyls and the lower internodes are too hard to cut with a razor blade.
Wash the cut surface with distilled water by dripping water on the surface.
Allow the cut stem to leak exudates for 20 min to avoid contamination from phloem sap.
Wipe the cut surface and the side of the stem with soft paper and wrap the stem just beneath the cut surface with clay (make a clay ring around the stem) (Figure 2E). Note that the droplets on the side of the stem prevent clay from sticking to the stem; therefore, the droplets need to be completely wiped off.
Place and press a silicon tube into the clay to avoid leakage of xylem exudates (Figure 2F). The gap between the stem and tube should be sealed with clay.
Collect xylem exudates using a syringe with a flat needle or micropipette. The exudates can be sampled at 20–30 min intervals.
Clay particles sometimes contaminate the exudates. To remove them from the xylem exudates, centrifuge at 2,600 × g for 10 min (and optimally at 4 °C) and transfer the supernatant to a new tube.
Store the xylem exudates at -80 °C.
Figure 2. Collection of xylem exudates from soybean. (A) Soybean seeds were arranged on soft wet paper in a plastic square dish. (B) The seeds were covered with wet paper, and a lid was placed on the dishes. (C) Lower internodes (1st or 2nd internodes from the bottom) of soybean. The plants were grown in a growth chamber (PPFD = 900 µmol/m2s). (D) Hypocotyl or lower internodes were cut with garden shears. (E) The stem just beneath the cut surface was wrapped with clay. (F) A silicon tube is pressed onto the cut stem, and xylem exudates accumulate in the tube. (G) From cutting the internodes to the fitting of a tube (C–F), it takes less than 1 min per plant, so this method is applicable to collecting xylem exudates from a large number of plants for comprehensive analysis.
Notes
A larger quantity of exudates will be obtained when plants are cultured in a greenhouse rather than in a growth chamber.
Under greenhouse conditions, approximately 60 mL of xylem exudate was obtained from 12 soybean plants (45 DAG) during the five hours after cutting the stems (approximately 5 mL/plant).
The yield of xylem exudates can decrease under stressed conditions, such as low-N and salt stress conditions. In our case, when soybean plants were cultured under a low-N (1.2 mM NH4NO3) condition for the last five days, approximately 20 mL of xylem exudate was obtained from 11 soybean plants in five hours. When soybean plants were cultured with the nutrition solution containing 50 mM NaCl for the last five days, no xylem exudates were obtained.
This method can be applied to various dicot plants. Under greenhouse conditions, approximately 120 mL of xylem exudate was obtained from 14 tomato (Solanum lycopersicum) plants (45 DAG) during the five hours after cutting the stems (approximately 8.6 mL/plant), and seven endogenous peptides were identified (Okamoto et al., 2022b).
Recipes
Nutrition solution for soybean (1 L)
Reagent Final concentration Amount
NH4NO3 6.0 mM 480 mg
CaCl2·2H2O 1.8 mM 262 mg
MgSO4·7H2O 1.0 mM 245 mg
KH2PO4 0.8 mM 108.8 mg
K2SO4 0.28 mM 49.6 mg
Fe(III)-EDTA 0.1 mM 43.9 mg
MnSO4·5H2O 5.9 µM 1.43 mg
H3BO3 4.0 µM 0.25 mg
CuSO4·5H2O 1.0 µM 0.25 mg
ZnSO4·7H2O 0.87 µM 0.25 mg
Na2MoO4·2H2O 0.21 µM 0.05 mg
CoCl2·6H2O 0.13 µM 0.03 mg
The reagents are dissolved in desalted water, and total volume is adjusted to 1 L.
The pH is adjusted to 6.0.
Acknowledgments
These procedures are based on Okamoto et al. (2022a) and Okamoto et al. (2015). This work was supported by JST PRESTO (JPMJPR17Q2 to S.O.) and the MEXT Leading Initiative for Excellent Young Researchers (to S.O.).
Competing interests
The authors declare no competing interests.
References
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Okamoto, S., Suzuki, T., Kawaguchi, M., Higashiyama, T., and Matsubayashi, Y. (2015). A comprehensive strategy for identifying long-distance mobile peptides in xylem sap. Plant J 84: 611-620.
Okamoto, S., Tabata, R., and Matsubayashi, Y. (2016). Long-distance peptide signaling essential for nutrient homeostasis in plants. Curr Opin Plant Biol 34: 35-40.
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Taiz, L., Zeiger, E., Moller I. M. and Murphy A. (2015). Plant Physiology and Development, Sixth Edition. Sinauer Associates.
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4,521 | https://bio-protocol.org/en/bpdetail?id=4521&type=0 | # Bio-Protocol Content
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Peer-reviewed
CRISPR/Cas9-mediated LRP10 Knockout in HuTu-80 and HEK 293T Cell Lines
MG Martyna M. Grochowska
VB Vincenzo Bonifati
WM Wim Mandemakers
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4521 Views: 2234
Reviewed by: Xi Feng Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Acta Neuropathologica Jul 2021
Abstract
Loss-of-function (LoF) variants in the low-density lipoprotein receptor–related protein 10 gene (LRP10) have been recently implicated in the development of neurodegenerative diseases, including Parkinson's disease (PD), PD dementia (PDD), and dementia with Lewy bodies (DLB). However, despite the genetic evidence, little is known about the LRP10 protein function in health and disease. Here, we describe a detailed protocol to efficiently generate a LRP10 LoF model in two independent LRP10-expressing cell lines, HuTu-80 and HEK 293T, using the CRISPR/Cas9 genome-editing tool. Our method efficiently generates bi-allelic LRP10 knockout (KO), which can be further utilized to elucidate the physiological LRP10 protein function and to model some aspects of neurodegenerative disorders.
Graphical abstract:
CRISPR/Cas9 workflow for the generation of the LRP10 KO. (1) Designed single guide RNA (sgRNA) is cloned into CRISPR/Cas9 px458 plasmid. (2) Cells are transfected with the CRISPR/Cas9 plasmid containing sgRNA. (3) Two days post transfection, cells are dissociated and sorted as single cells by fluorescence-activated cell sorting (FACS). (4) After several weeks, expanded clonal lines are (5) verified with Sanger sequencing for the presence of INDELs (insertions or deletions), RT-qPCR for the amounts of LRP10 mRNA transcript, and Western blotting for the analysis of the LRP10 protein levels.
Keywords: LRP10 HuTu-80 HEK 293T CRISPR/Cas9 Gene editing Knockout
Background
Rare, pathogenic variants in the low–density lipoprotein–related protein 10 gene (LRP10) have been identified in patients with familial Parkinson’s disease (PD), PD dementia (PDD), and dementia with Lewy bodies (DLB) (Quadri et al., 2018). Moreover, postmortem analysis of patients carrying distinct LRP10 variants showed a severe burden of alpha-synuclein–associated pathology in the form of Lewy bodies (LB) and Lewy neurites (LN) in the brain stem, limbic, and cortical regions (Quadri et al., 2018). Importantly, functional studies revealed that initially identified LRP10 pathogenic variants affected either LRP10 transcript expression and stability, protein stability, or protein localization, pointing to loss-of-function (LoF) as a shared pathogenic mechanism (Quadri et al., 2018). In addition, earlier studies using LRP10 overexpression models reported that LRP10 participates in intracellular trafficking pathways (Boucher et al., 2008; Brodeur et al., 2009, 2012; Doray et al., 2008). Despite these data, little is known about the endogenous LRP10 function in health and disease, partly due to the lack of in vitro LRP10 knockout (KO) models.
The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 system is a powerful and precise method for editing the genome in various cell types (Jinek et al., 2012; Cong et al., 2013; Adli, 2018). Gene KO models are often critical for identifying the function of the protein that a particular gene encodes. In the CRISPR/Cas9 system, the endonuclease Cas9 is guided to a specific site in the genome by a single guide RNA (sgRNA) to generate a double-strand break (Adli, 2018). The break is fixed in a process called non-homologous end-joining (NHEJ), which results in INDELs (insertion or deletion) (Sander and Joung, 2014). The introduction of INDELs leads to changes in the reading frame, which disrupts mRNA and protein expression (Sander and Joung, 2014).
Here, we show a step-by-step protocol to efficiently generate a LRP10 KO in the epithelial human cell lines HuTu-80 and HEK 293T using the CRISPR/Cas9 genome-editing tool. Our approach efficiently targeted the first exon of the LRP10 gene using a sgRNA cloned into a plasmid containing Cas9 from Streptococcus pyogenes. We obtained homozygous and compound heterozygous independent LRP10 KO clones carrying INDEL mutations leading to a frameshift and a premature stop codon. These models were used to test the specificity of commercially available and in-house developed antibodies against the endogenously expressed LRP10 protein (Grochowska et al., 2021). Interestingly, HuTu-80 cells highly express both LRP10 and alpha-synuclein, making the LRP10 KO in HuTu-80 cells a suitable model for studying the potential link between LRP10 LoF and alpha-synuclein accumulation in PD, PDD, and DLB. Lastly, given the high targeting efficiency of the LRP10 locus in both cell lines, this protocol holds promise for the generation of LRP10 KO in more relevant in vitro models of neurodegeneration, such as human stem cell–derived neural progenitors that can be differentiated into neurons and glia.
Materials and Reagents
6-well cell culture plates (TC-plate, standard F, Sarstedt, catalog number: 83.3920.005)
48-well cell culture plates (TC-treated, F-bottom, CorningTM CostarTM, catalog number: 3548)
96-well cell culture plates (F-bottom with lid, Greiner Bio-One, catalog number: 655180)
FalconTM round-bottom polystyrene test tubes with cell strainer snap cap, 5 mL (FalconTM, catalog number: 352235)
10 cm Petri dishes (sterile, VWR)
Parafilm® M (Sigma-Aldrich, catalog number: P7793)
DMEM (Sigma-Aldrich, catalog number: D6429), store at 4 °C
DMEM/F-12 (GibcoTM, catalog number: 11320033), store at 4 °C
Fetal bovine serum (FBS, GibcoTM, catalog number: A5256701), aliquot and store at -20 °C
Trypsin–EDTA (0.05%), phenol red (GibcoTM, catalog number: 25300054), aliquot and store at -20 °C
Penicillin–streptomycin (10,000 U/mL, GibcoTM, catalog number: 15140122), aliquot and store at -20°C
DPBS, no calcium and no magnesium (DPBS-/-, GibcoTM, catalog number: 14190144), store at room temperature
pSpCas9-(BB)-2A-GFP (Addgene plasmid #48138; http://n2t.net/addgene:48138; RRID: Addgene_48138)
BbsI (10,000 units/mL; NEB, catalog number: R0539S), aliquot and store at -80 °C
NEBufferTM r2.1 (NEB, catalog number: B7030S), store at 4 °C
T4 DNA ligase (400,000 units/mL, NEB, catalog number: M0202S), store at -20 °C
T4 DNA ligase reaction buffer (NEB, catalog number: B0202S), store at -20 °C
TE buffer solution 1× (TRIS–EDTA buffer) pH 8,0 (VWR, J75793.AE), store at room temperature
Ampicillin (Sigma-Aldrich, 69-52-3)
BD BACTOTM agar (BD, catalog number: 214010)
Tryptone (Millipore, catalog number: T7293)
Yeast extract (Sigma-Aldrich, catalog number: Y1625)
NaCl (Sigma-Aldrich, catalog number: S7653)
Trizma® base (Sigma-Aldrich, catalog number: TRIS-RO)
cOmpleteTM (Roche, catalog number: 11836145001)
Pefabloc® SC (Roche, catalog number: 11585916001)
IGEPAL® CA-630 (Sigma-Aldrich, catalog number: 18896)
SDS (Sigma-Aldrich, catalog number: 71729)
Bromophenol blue (Thermo Fisher Scientific, catalog number: A18469.18)
Glycerol (Sigma-Aldrich, catalog number: G5516)
DTT (Dithiothreitol, Thermo Fisher Scientific, catalog number: R0862)
TWEEN® 20 (Sigma-Aldrich, catalog number: P1379)
Agarose powder (Sigma, catalog number: A9539)
GeneJuice® transfection reagent (Merck Millipore, catalog number: 70967), store at 4 °C
Hoechst 33342, trihydrochloride, trihydrate, 10 mg/mL solution in water (InvitrogenTM, catalog number: H3570)
One ShotTM TOP10 chemically competent E. coli (InvitrogenTM, catalog number: C404010), store at -80 °C
HuTu-80 cells (CLS, catalog number: 330218), expand and cryopreserve cell stocks in liquid nitrogen
HEK 293T (ATCC® CRL-3216TM), expand and cryopreserve cell stocks in liquid nitrogen
DMSO (Sigma-Aldrich, catalog number: W387509), aliquot and store at -20 °C
Sanger sequencing kit (BigDye Terminator v3.1 Cycle Sequencing Kit and ExoSAP-IT, A38073), store the components according to the manufacturer’s specifications
NucleoBond PC, mini kit for transfection-grade plasmid DNA (MACHEREY-NAGEL, REF 740571.100), store the components according to the manufacturer’s specifications
Blood & cell culture DNA mini kit (QIAGEN, catalog number: 13323), store the components according to the manufacturer’s specifications
RNeasy mini kit (QIAGEN, catalog number: 74004), store the components according to the manufacturer’s specifications
SuperScript® III first-strand synthesis system for RT-PCR (Invitrogen, catalog number: 18080-051), store the components according to the manufacturer’s specifications
iTaqTM Universal SYBR® green supermix (Bio-Rad, catalog number: 172-5121), store the components according to the manufacturer’s specifications
4–15% Criterion TGX precast midi protein gel (Bio-Rad, catalog number: 5671085), store at 4 °C
Trans-blot turbo midi 0.2 µm nitrocellulose membranes (Bio-Rad, catalog number: 1704159), store at 4 °C
Blotto, non-fat dry milk (Santa Cruz, catalog number: sc-2325), store at room temperature
Donkey anti-rabbit IgG (H+L), Alexa FluorTM Plus 800 (Thermo Fisher Scientific, catalog number: A32808)
Alexa Fluor® 680 AffiniPure donkey anti-sheep IgG (H+L) (Jackson ImmunoResearch, catalog number: 713-625-147)
1× PBS, store at room temperature
Growth media for HuTu-80 cells (see Recipes), store at 4 °C
Growth media for HEK 293T cells (see Recipes), store at 4 °C
Lysogeny broth (LB; Miller formulation, see Recipes), store at 4 °C
LB agar plates (see Recipes), store at 4 °C
10× Tris-buffered saline (TBS) solution (see Recipes)
Protein lysis buffer, store at 4 °C (see Recipes)
4× sample buffer, store at 4 °C (see Recipes)
Equipment
Thermal cycler (Bio-Rad, model: C1000TouchTM)
Horizontal gel electrophoresis system
Molecular Imager® GelDoc XR System (Bio-Rad)
3790 series genetic analyzer (Thermo Fisher Scientific)
Benchtop orbital incubator shaker (New Brunswick Scientific, model: Innova® 40/40R)
Eppendorf centrifuge 5810 equipped with the A-4-81 rotor (Eppendorf)
Cell culture CO2 incubator (Sanyo, model: MCO-19AIC)
Benchtop EVOS M5000 imaging system (AMF5000) equipped with a GFP light cube (AMEP4951)
Water bath (Precision – CIR 35, Fisher Scientific)
High sensitivity flow cytometer BD FACSAriaTM III (BD Biosciences)
CFX Opus 96 Real-Time PCR (Bio-Rad)
Heraeus FrescoTM 17 microcentrifuge equipped with 24 × 1.5/2.0 mL rotor with ClickSealTM biocontainment lid (Thermo Scientific)
Trans-Blot® TurboTM transfer system (Bio-Rad)
Odyssey CLx imaging system (LI-COR Biosciences)
Software
CHOPCHOP (version 3, https://chopchop.cbu.uib.no/)
TIDE: Tracking of Indels by Decomposition (http://shinyapps.datacurators.nl/tide/)
CFX Maestro Software for CFX Real-Time PCR Instruments (Bio-Rad)
Image StudioTM Lite Ver 5.2 (LI-COR Biosciences)
Procedure
sgRNA in silico design for the LRP10 locus
Determine the optimal CRISPR/Cas9 target sites using the CHOPCHOP web tool (http://chopchop.cbu.uib.no) (Labun et al., 2019) or another preferable CRISPR/Cas9 design tool. Pick sgRNA (20 bp) with the highest predicted efficiency and the lowest predicted off-targets. The sequence of the optimal sgRNA is used to design sense and antisense oligonucleotides to clone the sgRNA into pSpCas9-(BB)-2A-GFP (see step 2). We recommend testing the targeting efficiency of several sgRNA designed against different exons of the gene of interest.
To clone sgRNA into pSpCas9-(BB)-2A-GFP (Ran et al., 2013), order sense and antisense oligonucleotides (Integrated DNA Technologies) with proper BbsI overhangs. These oligonucleotides need to be phosphorylated at the 5’ ends. Importantly, the pSpCas9-(BB)-2A-GFP allows the expression of the sgRNA under the control of the human U6 promoter, which requires a “G” base at the transcription start site. Therefore, add “G” at the start of the sgRNA sequence. For the LRP10 KO, we used sgRNA targeting the first exon of the LRP10 gene (ordered oligonucleotides: 5′-P-CACCGCGTTTCGGTTCTTACCAAGG and 5′-P-AAACCCTTGGTAAGAACCGAAACGC). The target genomic sequence for the generation of the LRP10 KO was chosen based on the score of the online CHOPCHOP tool and the prior testing of multiple sgRNA targeting different exons of the LRP10 gene.
Oligo design template:
sgRNA-oligo-FW: 5’-P-CACC(G)NNNNNNNNNNNNNNNNNNNN-3’
sgRNA-oligo-RV: 5’-P-AAACNNNNNNNNNNNNNNNNNNNN(C)-3’
P, phosphorylated
Cloning of sgRNA into pSpCas9-(BB)-2A-GFP plasmid
Oligonucleotide annealing. Adjust the concentration of the oligonucleotides to 100 µM using sterile demineralized water (dH2O) or TE buffer and combine in the annealing reaction (Table 1). Incubate the reaction in the thermal cycler at 95 °C for 5 min. Next, ramp down to 25 °C at 5 °C/min. The annealed product can be stored at -20 °C for several months.
Table 1. Components of oligonucleotide annealing reaction
Reagent Amount (µL) Final concentration
sgRNA-oligo-FW 1 10 µM
sgRNA-oligo-RV 1 10 µM
10× T4 ligation buffer 1 1×
dH2O 7 -
Total volume 10
Set up the restriction enzyme digestion for pSpCas9-(BB)-2A-GFP plasmid with BbsI enzyme (Table 2). Incubate for 90 min at 37 °C. Inactivate the restriction enzyme for 20 min at 65 °C. Load 3 µL of the digested vector on 0.8% agarose gel to check the restriction reaction efficiency. BbsI enzyme cuts the plasmid at two positions, removing 22 base pairs from the plasmid. The uncut plasmid DNA on the agarose gel has a multiple-band pattern (three bands running above 7 kbp) due to several plasmid conformations. The BbsI-digested plasmid DNA shows a single-band pattern running around 9 kbp.
Note: Typically, high cutting efficiency of BbsI is achieved and, therefore, purification of the linearized vector from the gel is not required.
Table 2. pSpCas9-(BB)-2A-GFP digestion setup
Reagent Amount (µL) Final concentration
1 µg pSpCas9-(BB)-2A-GFP 1 50 ng/µL
BbsI 1 1,000 units
NEBufferTM r2.1 2 1×
dH2O 16 -
Total volume 20
Set up the ligation reaction (Table 3). Before the ligation, dilute annealed oligonucleotides 1:250 in sterile dH2O to a final concentration of 40 nM. Incubate the ligation reaction at 16 °C overnight or at room temperature for 10 min. Heat inactivate at 65 °C for 10 min. Chill on ice and transform 1–5 μL of the reaction into 50 μL competent cells according to your in-house bacterial transformation protocol. Plate the transformed bacteria on LB agar plates containing 50 µg/mL of ampicillin (see Recipes). Place plates overnight in a 37 °C incubator.
Table 3. Ligation reaction setup
Reagent Amount (µL) Final concentration
Linearized pSpCas9-(BB)-2A-GFP X ~50 ng
Annealed oligonucleotides (1:250 dilution) 2 8 nM
T4 DNA ligase 0.5 20,000 units
10× T4 ligation buffer 1 1×
dH2O Fill with dH2O to the total volume of 10 µL -
Total volume 10
Next day, pick the colonies (at least six) and inoculate them in a 3 mL bacterial growth medium (LB) containing 50 µg/mL of ampicillin at 37 °C and 200 rpm overnight. Next, perform plasmid mini preparations using a NucleoBond PC mini kit following the manufacturer’s specifications or an in-house protocol. Verify correct clones by Sanger sequencing using a hU6-FW primer (5’- GAGGGCCTATTTCCCATGATT) with BigDye Terminator v3.1 Cycle Sequencing Kit or an in-house protocol. Select one correct clone to proceed to the next step.
Note: Make sure that your plasmid DNA is transfection-grade. DNA preparations obtained from the NucleoBond PC mini kit are suited for molecular-grade experiments and can be directly used for cell transfections.
Cell culture and transfection
Maintain HuTu-80 cells in growth medium (see Recipes) at 37 °C and 5% CO2. Split the cells when 80% confluent. Maintain HEK 293T cells in growth medium (see Recipes) at 37 °C and 5% CO2. Split the cells when 80% confluent.
The day before transfection, seed the following quantities of cells in one well of a 6-well plate: 0.5 million HEK 293T cells and 0.3 million HuTu-80 cells. The next day, cells will reach 30%–40% confluence and are ready for transfection.
Transfect the cells in one well of a 6-well plate. Perform the transfection with pSpCas9-(BB)-2A-GFP containing sgRNA using GeneJuice® transfection reagent according to the manufacturer’s specifications.
Forty-eight hours later, check the transfection efficiency using a benchtop imaging system equipped with the appropriate light cube to visualize GFP-positive cells. Transfected cells express GFP. Transfection efficiency in HuTu-80 cells is low to moderate (10%–30%). Transfection efficiency in HEK 293T cells is high (approximately 80%).
Prepare the transfected cells for fluorescence-activated cell sorting (FACS) 48 h post-transfection.
96-well plate preparation
On the day of FACS, prepare three 96-well plates (flat bottom) by adding 150 µL of HuTu-80 or HEK 293T growth medium to each well.
Incubate the plates before FACS at 37 °C and 5% CO2 for at least 30 min to equilibrate the medium.
FACS
For single-cell sorting, aspirate the medium from the well of the 6-well plate and wash it once with DPBS-/-.
Add 1 mL of trypsin–EDTA to the well and incubate it at 37 °C and 5% CO2 for 5 min.
Add 1 mL of growth medium to the well, gently resuspend to dislodge the cells from the plate, and transfer the cells to a 15 mL Falcon tube.
Spin the cells at 1,000 rpm (198 × g) for 5 min.
Aspirate and discard the supernatant. Next, resuspend the cell pellet in 1 mL of DPBS-/- containing 4% FBS.
Transfer 1 mL of the cell solution to a FalconTM round-bottom polystyrene test tube with a cell strainer snap cap.
Add 1 µL of sterile Hoechst 33342 solution to label dead cells and mix gently by inverting the tube.
Sort GFP-positive cells into three 96-well plates (1 cell per well) by gating out doublets (forward and sideward scatter-based) and dead cells (Hoechst 33342 positive cells). Select the population of cells with high GFP expression. Figure 1 represents the FACS settings on BD FACSAriaTM III for CRISPR/Cas9-mediated LRP10 KO in HuTu-80 cells. Optionally, include a negative control sample (non-transfected and non-Hoechst–stained cells) to optimally determine the gating of the positive cell population.
Figure 1. Example of FACS sorting gating settings for CRISPR/Cas9-mediated KO in HuTu-80 cell line.
Expansion of single cells post-sorting
Immediately after sorting, incubate plates at 37 °C and 5% CO2 for 72 h.
Perform the first medium change with 150 µL of growth medium.
Perform subsequent media changes every 72 h until colonies are observed under the light microscope.
The colonies start to emerge 14 days after sorting. You can expect a minimum of 10 clones from one 96-well plate for the HuTu-80 cells. You can expect a minimum of 30 clones from one 96-well plate for the HEK 293T cells.
When colonies reach 80% confluence, aspirate the media from the 96-well plates, wash with DPBS-/-, add 50 µL of trypsin–EDTA per well, and incubate at 37 °C and 5% CO2 for 5 min.
Next, add 150 µL of growth media per well, resuspend to dislodge the cells, and transfer each clone to separate 15 mL Falcon tubes. Spin at 1,000 rpm (198 × g).
Discard the supernatant and resuspend the cell pellet of each clone in fresh 150 µL of growth media. Add one-half (75 µL) of the cell suspension to a new well of a 48-well plate (PCR processing plate) and fill that well with an additional 225 µL of growth media. Add another half (75 µL) of the cell suspension to a new 48-well plate (propagation plate) and fill that well with an additional 225 µL of growth media.
Processing of plates and verification of positive clones
PCR processing plate. Grow clones until they reach 80% confluence. When ready, extract genomic DNA with an in-house protocol or using a blood & cell culture DNA mini kit. Amplify the DNA fragment of interest by PCR using primers flanking LRP10 exon 1 (FW: CAAAGTTTGGCCCGAAGAGG, RV: GGGCAGGCAGGATAGAGTGC), and perform Sanger sequencing following your in-house protocols. Perform INDEL tracking manually or with a freely available web tool (TIDE, http://shinyapps.datacurators.nl/tide/) to identify targeted clones (Brinkman et al., 2014).
Propagation plate. Grow clones until they reach 80% confluence and then cryopreserve as follows: aspirate the media, wash with DPBS-/-, add 50 µL of trypsin–EDTA per well, and incubate at 37 °C and 5% CO2 for 5 min. To each well, add 300 µL of growth media containing 10% DMSO. Wrap the plates with ParafilmTM wrapper and store them in a zippered plastic bag in the freezer at -80 °C. The cells will stay frozen during the screening. As you identify positive clones, thaw and expand the desired clones according to your in-house protocol. Additionally, thaw and expand three unedited clones (LRP10 WT) that underwent the same genome-editing procedure. These clones can be used as a control condition for the downstream experiments. The amount of LRP10 at the transcript and protein level for each clone can be further characterized by RT-qPCR and Western blotting. Below, we briefly describe the recommendations and kits used for the RT-qPCR and Western blotting experiments.
RT-qPCR
Recommendations
For RT-qPCR, we recommend the following primer sets for the LRP10:
Set 1 (LRP10-N-terminal): FW: ACTGCACCTGGCTCATCC and RV: GAGATCAGTGGCTGGAGAGG
Set 2 (LRP10-C-terminal): FW: CCAGGAGTACAGCATCTTTGC and RV: TAGCAGAGAACGCAGGTTGC
Relative LRP10 mRNA levels can be determined after normalization to the geometric mean of the following housekeeping genes:
CLK2 (FW: TCGTTAGCACCTTAGGAGAGG, RV: TGATCTTCAGGGCAACTCG)
COPS5 (FW: CCAGGAACCATTTGTAGCAG, RV: GTAGCCCTTTGGGTATGTCC)
RNF10 (FW:GCATCTGTGAACTGGCTTTG, RV: CTGACGTTTCCTCTTCTCAATG)
Procedure
Extract RNA from cells using RNeasy mini kit following the manufacturer’s specifications.
For each sample (clonal line), perform first-strand cDNA synthesis with random hexamers using SuperScript® III first-strand synthesis system, followed by RNase H digestion. Follow the manufacturer’s specifications. Use 1 µg of RNA per cDNA reaction.
Next, use iTaqTM Universal SYBR® green supermix to prepare RT-qPCR reactions. Follow the manufacturer’s specifications. For each cDNA sample, prepare five separate reactions (five different primer sets). Each reaction contains iTaqTM Universal SYBR® green supermix, a primer set, and 100 ng of cDNA. Each reaction should be performed in triplicate (technical replicates for the RT-qPCR).
Load the PCR tubes or plate into the RT-PCR instrument and start the PCR run. Our thermal cycling protocol is optimized for CFX Opus 96 Real-Time PCR with the following conditions: 3 min at 95 °C (initial denaturation), 40 cycles of 5 s at 95 °C, and 30 s at 60 °C.
The relative normalized LRP10 mRNA expression can be quantified using CFX Maestro Software for CFX Real-Time PCR Instruments.
Western blotting
Recommendations
For Western blotting, we recommend using the LRP10-NT (1-440 aa) (Sino Biological, 13228-T16) and LRP10-CT (463-713 aa) (MRC PPU Reagents, DA058) antibodies at the concentration of 1:500 (Grochowska et al., 2021). We recommend the following fluorescently conjugated secondary antibodies: donkey anti-rabbit IgG (H+L) highly cross-adsorbed secondary antibody, Alexa FluorTM Plus 800 (Thermo Fisher Scientific, A32808), and Alexa Fluor® 680 AffiniPure donkey anti-sheep IgG (H+L) (Jackson ImmunoResearch, 713-625-147) at the concentration of 1:1,000.
Procedure
Before protein lysis, wash the cells once with 1× TBS (see Recipes). Subsequently, add the protein lysis buffer (see Recipes) that contains freshly added protease inhibitors, 1× cOmpleteTM, and 1 mM Pefabloc® SC.
Snap-freeze the lysates. Next, thaw the lysates and clear them by centrifugation at 13,000 rpm (1,628 × g) and 4 °C for 10 min.
Mix the lysates with 4× sample buffer supplemented with 100 mM DTT and incubate for 10 min at 95 °C.
Separate the proteins on 4%–15% Criterion TGX precast gel. Transfer the proteins to the trans-blot turbo midi 0.2 µm nitrocellulose membrane using the Trans-Blot® TurboTM transfer system.
Block the membrane for 1 h at room temperature using the blocking buffer [5% non-fat dry milk (Blotto) and 0.1% v/v TWEEN® 20 in 1× TBS].
Perform primary antibody incubation overnight at 4 °C in blocking buffer.
Wash the membrane three times for 5 min with 1× TBS containing 0.1% v/v TWEEN® 20.
Perform secondary antibody incubation for 1 h at room temperature with fluorescently conjugated secondary antibodies in blocking buffer.
Wash the membrane three times for 5 min with 1× TBS containing 0.1% v/v TWEEN® 20.
Image the blots with Odyssey CLx imaging system. Images can be analyzed with Image StudioTM Lite Ver 5.2.
Notes
After CRISPR/Cas9 genome editing, we extracted DNA from 43 clonally expanded HEK 293T lines, performed PCR using primers flanking LRP10 exon 1, and Sanger-sequenced the obtained PCR products. Using the TIDE web tool (Brinkman et al., 2014), we decomposed electropherograms of individual clones to track INDELs located at the expected double-stranded break site and subsequently genotyped all clonal lines. We demonstrate that our CRISPR/Cas9 approach targeted both alleles in 58.1% of the clonally expanded HEK 293T lines (Figure 2A; homozygous and compound heterozygous clones combined). From all analyzed clones, 4.7% were not targeted, 2.3% were targeted on one of the alleles, and 34.9% were predicted to carry more than two INDELs (Figure 2A). One base pair insertion was the most common mutation introduced after the double-stranded break repair with NHEJ (Figure 2B). Importantly, the insertion of one base pair leads to a frameshift and often creates a premature stop codon. The designed sgRNA also strongly prefers to insert thymidine over other DNA nucleotides (Figure 2C, D, E). The 1 bp homozygous insertion in HEK 293T (KO-1 and KO-2, Figure 2D) and HuTu-80 (KO-1 and KO-2, Figure 2E) was predicted to lead to a frameshift and a premature stop codon at the position p.Gly12Trp fs*18. Similarly, the compound heterozygous mutation with a 1 bp insertion on one DNA strand and 2 bp deletion on the other DNA strand in HEK 293T and HuTu-80 clones was predicted to lead to a frameshift and a premature stop codon at the positions p.Gly12Trp fs*18/p.Gly12Arg fs*17 (KO-3, Figure 2D and E).
Figure 2. CRISPR/Cas9-mediated LRP10 KO is highly efficient in HEK 293T and HuTu-80 cell lines. (A) LRP10 targeting efficiencies in clonally expanded HEK 293T lines. Genotypes derived from 43 clonal lines were analyzed. WT, unedited LRP10 sequence. (B) Percentage of each mutation type (DEL: deletion; IN: insertion; bp: base pair) from the total number of targeted alleles. (C) Frequency of A, T, G, and C insertions analyzed in all “1 bp insertion” (IN 1 bp) alleles. (D), (E) Electropherograms of LRP10 DNA sequences from three independent clones showing bi-allelic targeting in HEK 293T (D) and HuTu-80 (E) cell lines. Sanger sequencing analysis confirms on-target mutagenesis with alleles containing INDELs. Clone 1 (KO-1) and 2 (KO-2) carry an insertion of a thymidine (c.33dupT) and clone 3 (KO-3) carries an insertion and deletion on two different alleles (c.33dupT and c.32_33insG). All three genotypes are predicted to induce frameshifts leading to a premature stop codon (p.Gly12Trp fs*18 or p.Gly12Arg fs*17).
Recipes
Growth media for HuTu-80 cells
DMEM/F-12, 445 mL
FBS 10%, 50 mL
Penicillin–streptomycin 1%, 5 mL
Total: 500 mL
Growth media for HEK 293T cells
DMEM, 445 mL
FBS 10%, 50 mL
Penicillin-streptomycin 1%, 5 mL
Total: 500 mL
LB (Miller formulation)
Tryptone 1% (w/v), 10 g
Yeast extract 0.5% (w/v), 5 g
NaCl 1% (w/v), 10 g
dH2O, add up to 1 L
Prepare liquid LB medium, followed by autoclaving (120 °C) and cooling down to room temperature.
LB agar plates
BD BACTOTM agar, 7.5 g
LB (Miller formulation), 400 mL
Mix and autoclave at 120 °C. When cooled down to approximately 55 °C, add 50 µg/mL of ampicillin. Prepare Petri dishes on a sterile bench. Carefully pour a thin layer of solution into the Petri dishes (approximately 15 mL per plate). Avoid creating bubbles. Leave the plates to set before storage in the fridge. Plates can be kept in the fridge for a maximum of two weeks.
10× Tris-buffered saline (TBS) solution
Trizma® base, 24 g
NaCl, 88 g
Dissolve in 900 mL dH2O
Adjust pH to 7.6 with HCl
Adjust the final volume to 1 L with dH2O
Protein lysis buffer
1 M Tris-Cl (pH 7.4, stock made from Trizma® base) 50 mM, 25 mL
NaCl 100 mM, 2.92 g
IGEPAL® CA-630 1.0%, 5 mL
Add dH2O up to 500 mL
Store in the fridge. Before use, add 1× cOmplete and 1 mM Pefabloc® SC from the stocks. To prepare a 25× cOmpleteTM stock, dissolve one cOmpleteTM tablet in 2 mL of deionized water or 10 mM phosphate buffer, pH 7.0. The stock solution is stable for at least 12 weeks at -15 to -25 °C. To prepare 100 mM Pefabloc® SC, dissolve 100 mg of Pefabloc® SC in 4.18 mL of deionized water. The concentrated 100 mM stock solution prepared in deionized water is acidic and stable for 1–2 months at -15 to -25 °C if stored in aliquots.
4× sample buffer
1 M Tris-Cl (pH 6.8, stock made from Trizma® base), 3.125 mL
20% SDS solution, 20 mL
Glycerol (v/v), 10 mL
Bromophenol blue, 2 mg
Make 800 µL aliquots and store them in the fridge. Before use, add 200 µL of 1 M DTT to obtain 4× sample buffer. To prepare a 1 M DTT solution, dissolve 1.55 g of DTT powder in 10 mL of deionized water.
Acknowledgments
This work was supported by research grants from the Stichting ParkinsonFonds (Netherlands) and Alzheimer Nederland. pSpCas9(BB)-2A-GFP (PX458) was a gift from Feng Zhang (Addgene plasmid # 48138; http://n2t.net/addgene:48138; RRID:Addgene_48138).
Competing interests
The authors declare no conflicts of interest or competing interests.
References
Adli, M. (2018). The CRISPR tool kit for genome editing and beyond. Nat Commun 9(1): 1911.
Boucher, R., Larkin, H., Brodeur, J., Gagnon, H., Thériault, C. and Lavoie, C. (2008). Intracellular trafficking of LRP9 is dependent on two acidic cluster/dileucine motifs.Histochem Cell Biol 130(2): 315-327.
Brodeur, J., Larkin, H., Boucher, R., Theriault, C., St-Louis, S. C., Gagnon, H. and Lavoie, C. (2009). Calnuc binds to LRP9 and affects its endosomal sorting. Traffic 10(8): 1098-1114.
Brodeur, J., Theriault, C., Lessard-Beaudoin, M., Marcil, A., Dahan, S. and Lavoie, C. (2012). LDLR-related protein 10 (LRP10) regulates amyloid precursor protein (APP) trafficking and processing: evidence for a role in Alzheimer's disease. Mol Neurodegener 7: 31.
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A. and Zhang, F. (2013). Multiplex genome engineering using CRISPR/Cas systems. Science 339(6121): 819-823.
Doray, B., Knisely, J. M., Wartman, L., Bu, G. and Kornfeld, S. (2008). Identification of acidic dileucine signals in LRP9 that interact with both GGAs and AP-1/AP-2.Traffic 9(9): 1551-1562.
Grochowska, M. M., Carreras Mascaro, A., Boumeester, V., Natale, D., Breedveld, G. J., Geut, H., van Cappellen, W. A., Boon, A. J. W., Kievit, A. J. A., Sammler, E., et al. (2021). LRP10 interacts with SORL1 in the intracellular vesicle trafficking pathway in non-neuronal brain cells and localises to Lewy bodies in Parkinson's disease and dementia with Lewy bodies. Acta Neuropathol 142(1): 117-137.
Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A. and Charpentier, E. (2012). A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337(6096): 816-821.
Labun, K., Montague, T. G., Krause, M., Torres Cleuren, Y. N., Tjeldnes, H. and Valen, E. (2019). CHOPCHOP v3: expanding the CRISPR web toolbox beyond genome editing. Nucleic Acids Res 47(W1): W171-W174.
Quadri, M., Mandemakers, W., Grochowska, M. M., Masius, R., Geut, H., Fabrizio, E., Breedveld, G. J., Kuipers, D., Minneboo, M., Vergouw, L. J. M., et al. (2018). LRP10 genetic variants in familial Parkinson's disease and dementia with Lewy bodies: a genome-wide linkage and sequencing study. Lancet Neurol 17(7): 597-608.
Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A. and Zhang, F. (2013). Genome engineering using the CRISPR-Cas9 system. Nat Protoc 8(11): 2281-2308.
Sander, J. D. and Joung, J. K. (2014). CRISPR-Cas systems for editing, regulating and targeting genomes. Nat Biotechnol 32(4): 347-355.
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4,522 | https://bio-protocol.org/en/bpdetail?id=4522&type=0 | # Bio-Protocol Content
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Peer-reviewed
Dual-target Bridging ELISA for Bispecific Antibodies
MP Min Pei
YW Yao Wang
LT Lei Tang
WW Weitao Wu
CW Chunhe Wang
YC Yi-Li Chen
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4522 Views: 1915
Reviewed by: Chiara AmbrogioMigla Miskinyte Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Dec 2021
Abstract
Bispecific antibodies (BsAbs) are typically monoclonal antibody (mAb)–derived molecular entities engineered to bind to two distinct targets, including two antigens or two epitopes on the same antigen. When compared to parental monoclonal antibodies or combinational therapies, the generated BsAbs have the ability to bridge the two targets and thus may offer additional clinical benefits. Characterizing BsAbs’ ability to bind to both targets simultaneously is critical for their biotherapeutic development. A range of bi-functional quantitative bridging assays to enable target-specific capture and detection of binding properties include enzyme-linked immunosorbent assay (ELISA), surface plasmon resonance (SPR), and cell-based flow cytometry. Developing suitable and robust cell-based bioassays is more challenging than non-cell-based binding assays because cell-based assays with complex matrices can be inherently variable and often lack precision. Compared to SPR, ELISA has a rapid setup and readily available method, being widely and extensively applied in almost every laboratory. Here, we describe a dual-target bridging ELISA assay that characterizes the ability of a HER2(human epidermal growth factor receptor 2)/PD-L1(programmed cell death ligand 1) BsAb in binding to both HER2 and PD-L1 simultaneously, a prerequisite for its envisioned mode of action.
Graphical abstract:
Keywords: Bridging ELISA Dual-target Bispecific Antibody Binding assay Affinity
Background
Engineered bispecific antibodies (BsAbs) that recognize two separate antigens or epitopes are an emerging class of next-generation biological therapeutics. Such antibodies, capable of engaging multiple targets, shed new light on clinical treatments with the prospect of additive or synergistic mechanisms of action (MoA) and/or superior potency compared to monoclonal antibody (mAb) or combination therapies (Kontermann, 2012; Register et al., 2021). Many BsAbs are currently marketed as therapeutics in several disease areas, and more than 100 BsAbs have progressed into clinical pipelines (Kaplon et al., 2022; Register et al., 2021).
The binding assays are necessary components of in vitro BsAb characterization (Saldanha et al., 2018). They must be readily conducted during initial product development phases for the candidate screening and stability assessments and can therefore potentially be used as MoA-reflective potency assays (Lee et al., 2017). The bioassay strategy is outlined to characterize the independent or simultaneous binding affinities of a BsAb to their dual-antigen targets and demonstrate the full biological binding activity, which is the prerequisite of the envisioned MoA (Register et al., 2021).
Bridging ELISA is a type of sandwich ELISA that has been widely used in bi-functional quantitative assays that cover both binding events simultaneously. This assay is based on a bridging format and utilizes an immobilized capture recombinant antigen 1 in a solid phase (usually polystyrene microplates), followed by the addition of a biotinylated version of the antigen 2, to form the antigen 1–BsAb–antigen 2 bridging complex. The horseradish peroxidase (HRP)–labeled streptavidin is used as the detector. Major advantages of this method are the rapid setup, easy preparation of reagents, and effortless handling when compared to other bridging bioassays [e.g., surface plasmon resonance (SPR) or cell-based flow cytometry]. By applying this bridging approach, several BsAbs, including PD-L1/TIGIT (T-cell immunoreceptor with immunoglobulin and ITIM domain), HER2/PD-1(programmed death protein 1), 4-1BB(CD137) (tumor necrosis factor receptor superfamily 9)/HER2, and OX40(CD134) (tumor necrosis factor receptor superfamily 4)/4-1BB (Hinner et al., 2019; Ljungars et al., 2020; Chu et al., 2022; Mu et al., 2022), have been determined to being capable of binding to both targets simultaneously. The bridging ELISA assay should be viewed as a potential new standard and well-established procedure for measuring dual-target binding. Here, we focus on HER2(human epidermal growth factor receptor 2)/PD-L1(programmed cell death ligand 1) BsAb and describe an effective dual-target binding ELISA protocol that allows the measurement of a bispecific drug binding to both targets in a single assay format.
Materials and Reagents
96-well microplate (Greiner Bio-One, catalog number: 650061)
HER2/PD-L1 BsAb protein (Chen et al., 2021)
Recombinant extracellular domain of human programmed cell death ligand 1 (C-6His）(PD-L1-ECD) Novoprotein, catalog number: CM06)
Recombinant human epidermal growth factor receptor 2 (C-6His) (HER2) (Novoprotein, catalog number: CP69)
1% casein in PBS (Thermo Fisher Scientific, catalog number: 37582)
TMB substrate kit (Thermo Fisher Scientific, catalog number: 34021)
High sensitivity streptavidin-HRP (Thermo Fisher Scientific, catalog number: 21130)
EZ-Link Sulfo-NHS-LC-LC-Biotin kit (Thermo Fisher Scientific, catalog number: 21338)
Sulfuric acid (Sinopharm Chemical Reagent Co., Ltd, catalog number: 100216008)
PBS (Hyclone, catalog number: 16777-249)
Tween-20 (Sigma-Aldrich, catalog number: P1379)
0.05% PBST (v/v) (see Recipes)
2 M sulfuric acid solution (H2SO4) (see Recipes)
Trastuzumab (Selleck, catalog number: A2007)
Equipment
SpectraMax M5e microplate reader (Molecular Devices, catalog number: 89212-400)
Software
GraphPad Prism 9.0 (GraphPad Software, www.graphpad.com)
Procedure
Antigens preparation
Prepare the biotin-antigen—biotinylated-HER2 protein—used for detection. First, conjugate the HER2 protein using the EZ-Link Sulfo-NHS-LC-LC-Biotin kit, according to manufacturer’s instructions.
Prepare human PD-L1-ECD protein (capture antigen) at a final concentration of 2 μg/mL in PBS buffer.
Coating plate with PD-L1-ECD antigen
Coat each well of a 96-well microplate with 50 µL of 2 µg/mL PD-L1-ECD protein. Cover the plate with a lid and incubate at 4 °C overnight without agitation.
Blocking and addition of HER2/PD-L1 BsAb
The next day, remove the coating solution and wash the plate three times with 200 µL of PBS per well.
Block the coated microplate by adding 200 µL of 1% casein in PBS buffer to each well using a multichannel pipette. Incubate for 1 h at 37 °C.
Discard the blocking solution and wash the microplate three times with 200 µL of 0.05% PBST per well.
Prepare three-fold serial dilutions of HER2/PD-L1 BsAb and control antibody (e.g., trastuzumab) in 1% casein in PBS buffer (e.g., 200 nM, 66.7 nM, 22.2 nM, 7.4 nM, 2.5 nM, 0.823 nM, 0.274 nM, 0.091 nM, 0.030 nM, 0.010 nM, 0.003 nM, and 0.001 nM).
Add 50 μL of each diluted antibody to each well in triplicate and incubate for 1 h at 37 °C.
Incubation with HER2/PD-L1 BsAb and addition of biotinylated-HER2 antigen
After incubation with the HER2/PD-L1 BsAb and control antibody, wash the microplates three times with 200 µL of 0.05% PBST to each well.
Pipette 50 µL of pre-prepared biotinylated-HER2 protein at 2 µg/mL in 1% casein in PBS buffer to each well and incubate for 1 h at 37 °C.
Discard the biotinylated-HER2 protein solution and wash the microplates three times with 200 µL of 0.05% PBST to each well.
Add 50 μL of 1:1,000 diluted streptavidin-HRP in 1% casein in PBS buffer to each well for detection, and incubate for 1 h at 37 °C.
Discard the detection solution and wash the microplates three times with 200 µL of 0.05% PBST to each well.
Addition of substrate and development
Prepare TMB substrate solution A and B at 1:1 ratio according to manufacturer’s instructions. Add 50 μL of freshly prepared substrate to each well and incubate for 10 min at room temperature.
After sufficient color development, add 50 μL of stop solution with 2 M sulfuric acid (H2SO4) to each well and measure the absorbance (optical density, OD) at 450 nm using a SpectraMax M5e microplate reader.
Data analysis
Subtract the background signal from the measured OD450nm values and normalize them. Transform all values of the HER2/PD-L1 BsAb concentration or control antibody to logarithmic scale (base 10, log10).
Plot the background corrected and normalized OD450nm values (Y-axis, corresponding to the fraction of occupied HER2/PD-L1 BsAb binding to both HER2 and PD-L1 sites simultaneously) against the logarithm of the HER2/PD-L1 BsAb or control antibody concentrations (X-axis, log10 scale).
Fit the concentration-response data using a 4 parameter logistic model by non-linear regression, with GraphPad Prism 9.0 software (Figure 1).
Figure 1. Binding curves of the dual-target bridging ELISA. HER2/PD-L1 BsAb could simultaneously bind to human PD-L1-ECD and HER2, as determined by the bridging ELISA, in which PD-L1-ECD proteins were coated onto the plates, and biotinylated-HER2 proteins were used as detection agent. Trastuzumab was used as control antibody. Data are shown as mean ± SEM (n = 3).
Notes
In this ELISA method, use a multichannel pipette in each step to add solutions to the wells of a 96-well microplate. In solution removal and washing steps, throw out the solutions directly into the sink. None of the plate incubation steps require agitation.
Recipes
0.05% PBST (v/v)
Tween-20, 0.05%, 500 μL
PBS, 999.5 mL
Total, 1,000 mL
2 M sulfuric acid solution (H2SO4)
Sulfuric acid (98%), 2 M, 3 mL
ddH2O, 897 mL
Total, 1,000 mL
Acknowledgments
This work was supported by the China National Major Scientific and Technological Special Project for “Significant New Drugs Innovation and Development” (2019ZX09732002-006) and the National Natural Science Foundation of China (81872785 and 81673347). The protocol described here was adapted from previously published work (Chen et al., 2021).
Competing interests
M. P. and Y.-L. C received stipends from Shanghai Mabstone Biotechnology, Ltd. Y. W., L. T., W. W., and C. W. are employed by Dartsbio Pharmaceuticals, Ltd.
References
Chen, Y. L., Cui, Y., Liu, X., Liu, G., Dong, X., Tang, L., Hung, Y., Wang, C. and Feng, M. Q. (2021). A bispecific antibody targeting HER2 and PD-L1 inhibits tumor growth with superior efficacy. J Biol Chem 297(6): 101420.
Chu, W., Xu, H., Wang, Y., Xie, Y., Chen, Y. L., Tan, X., Huang, C., Wang, G., Wang, Q., Luo, W., et al. (2022). HER2/PD1 bispecific antibody in IgG4 subclass with superior anti-tumour activities. Clin Transl Med 12(4): e791.
Hinner, M. J., Aiba, R. S. B., Jaquin, T. J., Berger, S., Durr, M. C., Schlosser, C., Allersdorfer, A., Wiedenmann, A., Matschiner, G., Schuler, J., et al. (2019). Tumor-Localized Costimulatory T-Cell Engagement by the 4-1BB/HER2 Bispecific Antibody-Anticalin Fusion PRS-343. Clin Cancer Res 25(19): 5878-5889.
Kaplon, H., Chenoweth, A., Crescioli, S. and Reichert, J. M. (2022). Antibodies to watch in 2022. MAbs 14(1): 2014296.
Kontermann, R. E. (2012). Dual targeting strategies with bispecific antibodies. MAbs 4(2): 182-197.
Lee, H. Y., Schaefer, G., Lesaca, I., Lee, C. V., Wong, P. Y. and Jiang, G. (2017). “Two-in-One” approach for bioassay selection for dual specificity antibodies. J Immunol Methods 448: 74-79.
Ljungars, A., Schiott, T., Mattson, U., Steppa, J., Hambe, B., Semmrich, M., Ohlin, M., Tornberg, U. C. and Mattsson, M. (2020). A bispecific IgG format containing four independent antigen binding sites. Sci Rep 10(1): 1546.
Mu, S., Liang, Z., Wang, Y., Chu, W., Chen, Y. L., Wang, Q., Wang, G. and Wang, C. (2022). PD-L1/TIGIT bispecific antibody showed survival advantage in animal model. Clin Transl Med 12(5): e754.
Register, A. C., Tarighat, S. S. and Lee, H. Y. (2021). Bioassay Development for Bispecific Antibodies-Challenges and Opportunities. Int J Mol Sci 22(10): 5350.
Saldanha, M., Dandekar, P. and Jain, R. (2018). A Regulatory Perspective on Testing of Biological Activity of Complex Biologics. Trends Biotechnol 36(3): 231-234.
Article Information
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Biological Engineering > Biomedical engineering
Drug Discovery > Drug Screening
Biochemistry > Protein
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4,523 | https://bio-protocol.org/en/bpdetail?id=4523&type=0 | # Bio-Protocol Content
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Flow Cytometry Analysis of SIRT6 Expression in Peritoneal Macrophages
VP Valentina Pérez-Torrado
JR Jorge Rodríguez-Duarte
CE Carlos Escande
MB Mariana Bresque
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4523 Views: 2101
Reviewed by: Chiara AmbrogioHemant Giri Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Mar 2022
Abstract
The sirtuin 6 has emerged as a regulator of acute and chronic immune responses. Recent findings show that SIRT6 is necessary for mounting an active inflammatory response in macrophages. In vitro studies revealed that SIRT6 is stabilized in the cytoplasm to promote tumor necrosis factor (TNFα) secretion. Notably, SIRT6 also promotes TNFα secretion by resident peritoneal macrophages upon lipopolysaccharide (LPS) stimulation in vivo. Although many studies have investigated SIRT6 function in the immune response through different genetic and pharmacological approaches, direct measurements of in vivo SIRT6 expression in immune cells by flow cytometry have not yet been performed. Here, we describe a step-by-step protocol for peritoneal fluid extraction, isolation, and preparation of peritoneal cavity cells, intracellular SIRT6 staining, and flow cytometry analysis to measure SIRT6 levels in mice peritoneal macrophages. By providing a robust method to quantify SIRT6 levels in different populations of macrophages, this method will contribute to deepening our understanding of the role of SIRT6 in immunity, as well as in other cellular processes regulated by SIRT6.
Graphical abstract:
Keywords: SIRT6 Inflammation Macrophages Peritoneal cavity cells Flow cytometry
Background
Sirtuins, NAD+-dependent deacetylases, have been implicated in many biological processes, including inflammation. In the context of the inflammatory response, SIRT6 in particular has attracted attention due to its apparently coexisting and opposite pro- and anti-inflammatory activities (Kawahara et al., 2009; Xiao et al., 2012; Jiang et al., 2013; 2016). Initially, and similarly to other sirtuins, SIRT6 was proposed to inhibit inflammation by silencing NFκB and c-Jun–dependent transcription. Through its deacetylating enzymatic activity on Ac-H3K9, SIRT6 indirectly regulates cytokine expression (Kawahara et al., 2009; Bauer et al., 2012; Xiao et al., 2012). Recently, it has been reported that SIRT6 exerts pro-inflammatory functions through its ability to remove fatty acid groups from proteins in the cytoplasmic compartment. In particular, SIRT6 promotes tumor necrosis factor (TNFα) secretion by the demyristoylation of pro-TNFα in fibroblasts and macrophages during lipopolysaccharide(LPS)-mediated acute inflammatory response (Jiang et al., 2013; Jiang et al., 2016; Bresque et al., 2022). In addition, SIRT6 is actively regulated during acute inflammation in vivo, and its inhibition dampens TNFα secretion, reducing LPS-induced septic shock, obesity-induced systemic inflammation, and progression of experimental autoimmune encephalomyelitis (EAE) (Sociali et al., 2017; Ferrara et al., 2020; Bresque et al., 2022).
Most studies focusing on the role of SIRT6 in inflammation have been performed in vitro and have not measured changes in its localization and expression during the inflammatory response. Recently, studies regarding conditions for SIRT6 ablation have been developed to assess SIRT6 relevance in chronic inflammation and its consequences on immune cell populations in vivo (Lee et al., 2017; Ferrara et al., 2020). The peritoneal cavity provides a large number of differentiated macrophages and is a useful tool for studying in vivo immune responses. Recently, we demonstrated, by using flow cytometry and immunofluorescence, that there was an increase in both SIRT6-positive cells and SIRT6 fluorescence intensity in CD11b+F4/80hi peritoneal macrophages stimulated by LPS. Our work is the first to apply flow cytometry to quantify SIRT6 levels in vivo in macrophages isolated from LPS-stimulated mice peritoneum (Bresque et al., 2022). Thus, this protocol sheds light on this issue, providing a new tool to study SIRT6 expression in immune and potentially other cells. This flow cytometry protocol, which employs a commercially available anti-SIRT6 antibody, offers a robust method to quantify the levels of an intracellular protein and may be applied to a wide variety of samples, including macrophages from adipose tissue.
Materials and Reagents
Male C57BL/6 mice (bred and maintained at Institut Pasteur Montevideo animal facility-UBAL)
Falcon® 50 mL conical centrifuge tubes (Corning, catalog number: 352070)
1.5 mL Eppendorf microcentrifuge tubes (CNWTC, catalog number: TYA10)
96-well plates, V-bottom (Deltalab, catalog number: 900012.1)
1 mL syringes with 26 G needle (BD, catalog number: 303176)
5 mL syringes with 24 G needle (BD, catalog number: 302187)
Ketamine (Pharmaservice, Ripoll Vet, Montevideo, Uruguay)
Xylazine (Unimedical, Montevideo, Uruguay)
95% ethanol (Drogueria Industrial Uruguaya, catalog number: 12702)
RPMI (GIBCO, catalog number: 61870-010)
FBS (GIBCO, catalog number: 10437-028)
BSA (Capricorn, catalog number: BSA-1U)
EDTA (Fluka, catalog number: 03620)
PBS (Sigma, catalog number: D1408)
0.4% trypan blue solution (GIBCO, catalog number: 15250061)
Normal rat serum (NRS) (provided by URBE - Facultad de Medicina - UdelaR)
eBioscienceTM FoxP3/Transcription Factor Staining Buffer set (Invitrogen, catalog number: 00-5523-00)
LIVE/DEAD fixable Far-Red dead cell stain kit (Thermo Fisher Scientific, catalog number: L10120)
APC anti-CD11b antibody (Millipore, catalog number: MABF520)
APCCy7 anti-CD19 antibody (BioLegend, catalog number: 115530)
APCCy7 anti-TCRβ chain antibody (BioLegend, catalog number: 109220)
APCCy7 anti-Ly-6G antibody (BioLegend, catalog number: 127624)
Brilliant VioletTM 510 anti-CD11b antibody (BioLegend, catalog number: 101245)
PE anti-F4/80 antibody (Millipore, catalog number: MABF1530)
Anti-SIRT6 antibody (Abcam, catalog number: ab191385)
Alexa FluorTM 488 goat anti-rabbit IgG antibody (Invitrogen, catalog number: A11034)
Ketamine/xylazine anesthesia (see Recipes)
70% ethanol (see Recipes)
RPMI supplemented with 0.2% FBS (see Recipes)
FACS buffer (see Recipes)
15% normal rat serum (15% NRS) (see Recipes)
Equipment
Surgical instruments (mayo and iris scissors straight and mosquito hemostatic and dissecting forceps)
Refrigerated centrifuge (Eppendorf, model: 5804R), Rotor A-2-DWP
Inverted microscope (Nikon, model: Eclipse TS100)
Hemacytometer (Bright-LineTM, catalog number: Z359629)
AttuneTM NxT flow cytometer (Invitrogen, catalog number: A24858)
Software
AttuneTM NxT Software (Invitrogen)
FlowJo (LLC, FlowJo_Vx.0.7)
Procedure
Isolation and preparation of peritoneal cavity cells (refer to explicative video to follow steps 5–10)
Anesthetize the mouse via subcutaneous injection of 500 µL of ketamine/xylazine (see Recipes) using a 1 mL syringe with a 26 G needle.
Euthanize the mice by cervical dislocation.
Place the mouse on its back on the Styrofoam block.
Spray the mouse with 70% ethanol (see Recipes). Using dissecting forceps and mayo scissors, grab and cut the external skin of the peritoneum.
Separate the skin until approximately 3 cm of the peritoneum is exposed.
Pull up the peritoneum skin with dissecting forceps and elevate it (see Video 1).
Inject 4 mL of RPMI supplemented with 0.2% FBS in the peritoneal cavity using a 5 mL syringe with a 24 G needle. Insert the needle gently in the area held with dissecting forceps.
After injection, clamp the area with hemostatic forceps and gently massage the peritoneum to release cells.
Using iris scissors, perform an incision in the peritoneum wall in the area above the clamp. Holding the hemostatic forceps, flip the mouse face down in a 50 mL Falcon tube. Alternatively, peritoneal lavage collection could be performed using a plastic Pasteur pipette.
Once there, open the clamp, release, and collect peritoneal fluid.
Centrifuge the peritoneal fluid collected at 500 × g for 10 min at 4 °C.
Discard the supernatant and resuspend cells in 1 mL of RPMI supplemented with 0.2% FBS.
Count viable cells using trypan blue (1:2 dilution) and a hemacytometer.
Video 1. Peritoneal Lavage.
Note: Intraperitoneal anesthesia is not recommended due to its inflammatory effect on peritoneal cells. It is important to anesthetize mice before cervical dislocation to facilitate precise manipulation and avoid blood infiltration in the peritoneal cavity. To prevent damage on peritoneal cavity organs and avoid collection of blood or other fluids with peritoneal fluid, it is important to be very careful when injecting, clamping, and cutting the peritoneum. The use of a 24 G needle for the peritoneal lavage is crucial. A bigger needle will damage the peritoneum and the organs in the cavity. At least 1 min of peritoneal mice massage is required to recover as many cells as possible from the peritoneal cavity. The technique used for the peritoneal lavage ensures the complete recovery of the volume injected in the peritoneal cavity and, therefore, maximum cell recovery. With this protocol, at least 5 × 106 cells per animal will be recovered. After animal sacrifice, all procedures should not exceed 5 min to maximize cell viability. After collection, it is important to maintain peritoneal cavity cells on ice. For optimal peritoneal cell counting, it is recommended to use a final 1:20 dilution. Dilute the cells 1:10 in RPMI supplemented with 0.2% FBS and then dilute 1:2 with trypan blue.
Flow cytometry staining protocol
Use three wells for each sample to be analyzed: one for SIRT6 staining and the others for SIRT6 antibody control and secondary antibody control (see detailed control information in Table 1). For Single Stain (SS) and No Stain (NS), mix the remaining cells from all samples and plate them. In all cases, plate 2 × 105 cells in each well.
Centrifuge the cells at 500 × g for 2 min.
Aspirate and discard supernatant with a multichannel pipette and wash with 100 µL of PBS. Alternatively, the supernatant could be decanted by inversion of the plate.
Centrifuge cells at 500 × g for 2 min.
Discard supernatant and resuspend all sample wells in 10 µL of fixable viability dye (see Table 2). For SS and NS wells, resuspend in 10 µL of PBS.
Incubate the plate 10 min at room temperature, protected from light.
Add 15 µL of 15% NRS (see Recipes) to each well (including SS and NS) and resuspend the cells.
Incubate 20 min on ice protected from light.
Add 25 µL of surface staining mix (see Table 2) to each sample well and resuspend cells. For SS wells, add the antibody selected for each fluorophore [e.g., for PE SS, use PE Anti-F4/80 (see Table 2 for each SS)]. For NS wells, add and resuspend in 25 µL of FACS buffer (see Recipes).
Incubate 30 min on ice protected from light.
Centrifuge cells at 500 × g for 2 min.
Discard supernatant and wash with 100 µL of FACS buffer.
Repeat steps 11 and 12.
Discard supernatant and resuspend all cells in 100 µL of transcription factor staining fixation/permeabilization reagent (prepared as described by manufacturer).
Incubate overnight at 4 °C protected from light.
Centrifuge cells at 500 × g for 2 min.
Discard supernatant and wash with 100 µL of transcription factor staining permeabilization buffer (prepared as described by manufacturer).
Repeat steps 16 and 17.
Discard supernatant and resuspend cells in 20 µL of anti-SIRT6 antibody to each SIRT6 staining and secondary antibody control wells. For SIRT6 antibody control, SS, and NS, resuspend in 20 µL of transcription factor staining permeabilization Buffer.
Incubate 30 min on ice protected from light.
Centrifuge cells at 500 × g for 2 min.
Discard supernatant and wash with 100 µL of transcription factor staining permeabilization buffer (prepared as described by manufacturer).
Centrifuge cells at 500 × g for 2 min.
Discard supernatant and resuspend in 20 µL of conjugated secondary antibody to SIRT6 staining wells and SIRT6 control wells of each sample. For secondary antibody control, SS, and NS, add 20 µL of transcription factor staining permeabilization buffer.
Incubate 1 h on ice protected from light.
Discard supernatant and wash with 100 µL of transcription factor staining permeabilization buffer.
Centrifuge cells at 500 × g for 2 min.
Repeat steps 26 and 27.
Discard supernatant and resuspend all wells in 100 µL of FACS buffer.
Transfer the content of each well to Eppendorf tubes.
Add up to 400 µL of additional FACS buffer to each tube.
Acquire between 2 × 104 and 5 × 104 events per sample in the flow cytometer.
Note: For SS and NS, one well per fluorophore used in staining (SS conditions) and one additional well for NS condition are necessary. The transfer of the content of each well to appropriate tubes is only necessary if using a flow cytometer without a plate handler. The additional FACS buffer volume needed in each tube depends on the flow cytometer used. For AttuneTM NxT flow cytometer ,
Table 1. Antibody controls description.
Summary of the used staining and utility of SIRT6 antibody and secondary antibody controls. If wanted, an isotype control for SIRT6 antibody can be added.
Antibody Control Viability staining
Surface staining
mix
Anti-SIRT6 antibody staining Secondary antibody staining Utility
SIRT6 antibody control Yes Yes No Yes Identification of conjugated secondary antibody signals for non-specific binding targets.
Secondary
antibody control
Yes Yes Yes No Identification of SIRT6 antibody noise signal without addition of conjugated secondary antibody. Visualization of possible spectral overlap.
Table 2. Reagent preparations for each staining step.
Detailed information to prepare all the reagents used. For each staining step, the table shows the antibody used, the initial dilution at which the antibody was prepared, the final dilution once added to the wells, and the diluent used. Note that for the surface staining mix there are two alternatives for the dump gate composition [1) or 2)], depending on the inflammatory conditions of the assay.
Initial dilution
(prepared)
Final dilution
(added to wells)
Fixable viability dye staining
LIVE/DEAD Far-Red
1:500 1:500
Diluted in PBS 1×
Surface staining
Surface mix:
Brilliant Violet 510 anti-CD11b
1:150
1:300
PE anti-F4/80
1:100 1:200
APCCy7 Dump Gate:
1) with inflammatory stimuli:
APCCy7 anti-CD19
APCCy7 anti-TCRβ
APCCy7 anti-Ly6G
2) without inflammatory stimuli:
APCCy7 anti-CD19
Diluted in FACS buffer
Single Stain (SS):
APC anti-CD11b (for Far-Red SS)
Brilliant Violet 510 anti-CD11b
PE anti-F4/80
APCCy7 anti-CD19
FITC anti-CD11c (for Alexa Fluor 488 SS)
Diluted individually in FACS buffer
1:200
1:200
1:200
1:200
1:100
1:150
1:100
1:200
1:100
1:400
1:400
1:400
1:400
1:200
1:300
1:200
1:400
1:200
Intracellular/intranuclear SIRT6 staining
Anti-SIRT6
1:200 1:200
Conjugated secondary antibody (Alexa Fluor 488 goat anti-rabbit)
1:200 1:200
* Diluted individually in the transcription factor staining permeabilization buffer.
Data analysis
Perform fluorophore compensation using SS acquisition data.
Apply compensation matrix to all samples.
Select population of interest by morphology (Figure 1A). In this step, exclude events corresponding to cellular debris from the gate.
Select single cells events (Figure 1B).
Select live cells (negative cells for viability dye staining) (Figure 1C). Cell viability should be around 80%–90%.
Select the negative population for the staining used for the dump gating (Figure 1D).
Select CD11b positive cells (Figure 1E).
Within CD11b positive cells, there are three populations defined by the expression of F4/80: negative (F4/80-), low (F4/80lo), and high (F4/80hi) (Figure 1F). In our case, F4/80lo and F4/80hi populations were analyzed, since these are considered different macrophage populations (Bain et al., 2016).
Figure 1. Gating strategy for definition of macrophage populations. Figure shows the definition of the population of interest by morphology (A), selection of single cells (B) and live cells (C), exclusion of different lineages with dump gating (D), posterior selection of CD11b positive cells (E), and identification of two macrophage populations (F4/80lo and F4/80hi) within these cells (F). SIRT6 expression was analyzed in these two populations. Arrows indicate the population selected for the next step of the gating strategy. The percentage of the selected population is shown in each graph.
Image was extracted and modified from the original research article (Bresque et al., 2022). In this experiment, mice were injected with LPS or PBS (control), and SIRT6 expression in the peritoneal cells was assessed using the protocol described previously.
Select the population of macrophages of interest (CD11b+F4/80lo and CD11b+F4/80hi) in control samples. Define SIRT6 positive population as the gate above all cells observed in SIRT6 antibody and secondary antibody controls; this gate must be the same in both controls. For each control, you may allow up to 1% of cells inside the SIRT6 positive cells gate (Figure 2A). Repeat this step individually for all samples, since the fluorescence of the controls may vary between samples and/or conditions.
Apply the SIRT6 positive gate defined in SIRT6 stained replicates for each sample (Figure 2B).
Repeat steps 9 and 10 for all the populations of macrophages analyzed.
For data analysis, use a percentage of SIRT6 positive cells and SIRT6 geometric mean fluorescence intensity (GMFI) within SIRT6 positive cells. Use GMFI as a measurement of SIRT6 expression levels within this population.
Statistical analysis is made as described in the original research article (Bresque et al., 2022).
Figure 2. Gating strategy for definition of SIRT6 positive cells. (A) Definition of SIRT6 positive cells using antibody controls (SIRT6 antibody and secondary antibody) in macrophage populations (F4/80lo and F4/80hi). SIRT6 positive gate is above all events in both antibody controls; up to 1% of events in this gate are allowed for antibody controls. (B) SIRT6 positive gate applied to SIRT6 stained samples (application of gate represented by black arrow). The percentage of SIRT6 positive cells is shown inside the SIRT6 positive gate. Image was extracted and modified from the original research article (Bresque et al., 2022). In this experiment, mice were treated with LPS or PBS (control), and SIRT6 expression was assessed using the protocol described previously.
Recipes
Ketamine/xylazine anesthesia (calculated based on 30 g mice)
Ketamine (50 mg/mL), 200 mg/kg, 120 µL
Xylazine (20 mg/mL), 24 mg/kg, 40 µL
ddH2O, 340 µL
Total: 500 µL
70% ethanol
95% ethanol, 737 mL
ddH2O, 263 mL
Total: 1,000 mL
RPMI supplemented with 0.2% FBS
FBS 0.2%, 2 mL
RPMI, 998 mL
Total: 1,000 mL
FACS buffer
BSA 0.1%, 1 g
2 mM EDTA, 20 mL (prepared for 100 mM EDTA)
ddH2O, 980 mL
Total: 1,000 mL
15% normal rat serum (15% NRS)
Normal rat serum (NRS), 2.25 mL
FACS buffer, 12.75 mL
Total: 15 mL
Acknowledgments
This work was supported by grants by ANII (FCE_1_2014_1_104002 and INNOVA II to CE) and FOCEM - Fondo para la Convergencia Estructural del Mercosur (COF 03/11). MB was supported by scholarships from ANII (POS_NAC_2015_1_109950) and CAP (UdelaR). VPT was supported by scholarships from CAP (UdelaR). The AttuneTM NxT cytometer was purchased and upgraded by an institutional grant by ANII (PEC_3_2019_1_158811). The authors would like to thank all the people at the Animal Facility Unit (UBAL) and the Cell Biology Unit at the Institut Pasteur Montevideo for their support and assistance in the present work. The authors would like to thank Dr. Mercedes Segovia (LIRI, Institut Pasteur Montevideo) and Alvaro Díaz (Facultad de Química, Universidad de la República), for helpful advice and discussions for the flow cytometry analysis. The original research that originated this protocol publication was published in Bresque et al. (2022).
Competing interests
CE and MB declare on behalf of all the authors that there are no conflicts of interest related to this manuscript.
Ethics
All mice used in this study (male C57BL/6) were bred and maintained at the Institut Pasteur de Montevideo Animal Facility Unit (UBAL). The experimental protocol was approved by the Institutional Animal Care and Use Committee of the Institut Pasteur de Montevideo (CEUA, protocol numbers 70153-000839-17, 003-19, and 006-19). All the studies described were performed according to the methods approved in the protocol and following all international guidelines and legal regulations.
References
Bain, C. C., Hawley, C. A., Garner, H., Scott, C. L., Schridde, A., Steers, N. J., Mack, M., Joshi, A., Guilliams, M., Mowat, A. M., et al. (2016). Long-lived self-renewing bone marrow-derived macrophages displace embryo-derived cells to inhabit adult serous cavities. Nat Commun 7: ncomms11852.
Bauer, I., Grozio, A., Lasiglie, D., Basile, G., Sturla, L., Magnone, M., Sociali, G., Soncini, D., Caffa, I., Poggi, A., et al. (2012). The NAD+-dependent histone deacetylase SIRT6 promotes cytokine production and migration in pancreatic cancer cells by regulating Ca2+ responses. J Biol Chem 287(49): 40924-40937.
Bresque, M., Cal, K., Perez-Torrado, V., Colman, L., Rodriguez-Duarte, J., Vilaseca, C., Santos, L., Garat, M. P., Ruiz, S., Evans, F., et al. (2022). SIRT6 stabilization and cytoplasmic localization in macrophages regulates acute and chronic inflammation in mice. J Biol Chem 298(3): 101711.
Ferrara, G., Benzi, A., Sturla, L., Marubbi, D., Frumento, D., Spinelli, S., Abbotto, E., Ivaldi, F., von Holtey, M., Murone, M., et al. (2020). Sirt6 inhibition delays the onset of experimental autoimmune encephalomyelitis by reducing dendritic cell migration. J Neuroinflammation 17(1): 228.
Jiang, H., Khan, S., Wang, Y., Charron, G., He, B., Sebastian, C., Du, J., Kim, R., Ge, E., Mostoslavsky, R., et al. (2013). SIRT6 regulates TNF-α secretion through hydrolysis of long-chain fatty acyl lysine.Nature 496(7443): 110-113.
Jiang, H., Zhang, X. and Lin, H. (2016). Lysine fatty acylation promotes lysosomal targeting of TNF-α. Sci Rep 6(1): 24371.
Kawahara, T. L., Michishita, E., Adler, A. S., Damian, M., Berber, E., Lin, M., McCord, R. A., Ongaigui, K. C., Boxer, L. D., Chang, H. Y., et al. (2009). SIRT6 links histone H3 lysine 9 deacetylation to NF-kappaB-dependent gene expression and organismal life span. Cell 136(1): 62-74.
Lee, Y., Ka, S. O., Cha, H. N., Chae, Y. N., Kim, M. K., Park, S. Y., Bae, E. J. and Park, B. H. (2017). Myeloid Sirtuin 6 Deficiency Causes Insulin Resistance in High-Fat Diet-Fed Mice by Eliciting Macrophage Polarization Toward an M1 Phenotype. Diabetes 66(10): 2659-2668.
Sociali, G., Magnone, M., Ravera, S., Damonte, P., Vigliarolo, T., Von Holtey, M., Vellone, V. G., Millo, E., Caffa, I., Cea, M., et al. (2017). Pharmacological Sirt6 inhibition improves glucose tolerance in a type 2 diabetes mouse model. FASEB J 31(7): 3138-3149.
Xiao, C., Wang, R. H., Lahusen, T. J., Park, O., Bertola, A., Maruyama, T., Reynolds, D., Chen, Q., Xu, X., Young, H. A., et al. (2012). Progression of chronic liver inflammation and fibrosis driven by activation of c-JUN signaling in Sirt6 mutant mice. J Biol Chem 287(50): 41903-41913.
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Peer-reviewed
Extraction and Quantification of Plant Hormones and RNA from Pea Axillary Buds
DC Da Cao
FB Francois Barbier
KY Kaori Yoneyama
CB Christine A. Beveridge
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4524 Views: 1488
Reviewed by: Ansul Lokdarshi Anonymous reviewer(s)
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Cited by
Original Research Article:
The authors used this protocol in Frontiers in Plant Science Nov 2020
Abstract
The quantification of plant hormones and related gene expression is essential to improve the understanding of the molecular regulation of plant growth and development. However, plant hormone quantification is still challenging due to extremely low endogenous levels and high chemical diversity. In this study, we present a convenient extraction protocol that enables the simultaneous extraction of both phytohormones and RNA from the same sample in a small quantity (approximately 10 mg). Using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC–MS/MS), this protocol provides a method to quantify 13 phytohormones and their derivatives from four classes (cytokinin, auxin, abscisic acid, and gibberellin) at the speed of 14 min per sample.
Keywords: Phytohormone and RNA extraction Phytohormone quantification Cytokinin Gibberellin Auxin Abscisic acid UPLC–MS/MS Pea axillary buds
Background
Phytohormones are endogenous signaling molecules that are involved in an immensely diverse range of plant physiological and developmental processes, which makes them critical for plant growth, development, and responses to biotic and abiotic stresses. Axillary bud outgrowth is a perfect example of a developmental process involving multiple phytohormones. Auxin, cytokinin, and strigolactone have been found to play major roles in triggering axillary bud dormancy (Barbier et al., 2019b). Abscisic acid and gibberellic acid are also involved in axillary bud outgrowth regulation (Yao and Finlayson, 2015; Charnikhova et al., 2017).
Despite their importance for plant growth regulation, not all phytohormones can yet be easily detected and quantified, which significantly limits the progression of phytohormone-related research (Cao et al., 2017; Liu et al., 2019). Due to various chemical classes and ultra-trace amounts of phytohormones in plant tissues, it is also difficult to measure a variety of phytohormone classes using a single separation method and analytical platform (Novák et al., 2017). Moreover, phytohormone levels vary between different plant tissues (Novák et al., 2017). Thus, it is important to select appropriate pre-treatment and quantification methods to boost the measurement sensitivity of targeted phytohormones (Yu et al., 2018). Ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC–MS/MS) has become the most efficient method for boosting measurement sensitivity, as it provides high selectivity and sensitivity for phytohormone profiling (Pan et al., 2010; Schäfer et al., 2016; Šimura et al., 2018). However, mass spectrometry sensitivity is strongly influenced by other compounds in plant materials, which suppress the ionization of target compounds (Trapp et al., 2014). Thus, a specific cleanup extraction method for phytohormones is needed. To quantify multiple phytohormone classes, many studies have used a time-consuming parallel extraction method for different classes of phytohormones (Cao et al., 2016; Xin et al., 2020). In addition to phytohormone profiling, monitoring gene expression is a key requirement for understanding the involvement of phytohormones in plant physiology and development (Šimura et al., 2018; Barbier et al., 2019b). However, a simultaneous extraction method for a wide range of phytohormones and RNA using one simple extraction method had not been previously reported.
Materials and Reagents
Phytohormone standards and internal standards (Table 1).
Table 1. Phytohormone standards and internal standards.
Reagent Supplier Classification Catalog number Storage temperature (°C)
tZEATIN OlChemim STD 001 0301 -20
DHZ OlChemim STD 001 0601 -20
tZR OlChemim STD 001 0311 -20
DHZR OlChemim STD 001 0611 -20
tZMP OlChemim STD 001 5141 -20
iP OlChemim STD 001 0161 -20
iPR OlChemim STD 001 0171 -20
iPAMP OlChemim STD 001 5041 -20
IAA OlChemim STD 003 1531 -20
GA1 OlChemim STD 012 2491 -20
ABA OlChemim STD 013 2701 -20
D5-tZ OlChemim ISTD 030 0301 -20
D3-DZ OlChemim ISTD 030 0601 -20
d5-tZR OlChemim ISTD 030 0311 -20
d3-DZR OlChemim ISTD 030 0611 -20
d5-tZRP OlChemim ISTD 030 0311 -20
d6-iP OlChemim ISTD 030 0161 -20
d6-iPR OlChemim ISTD 030 0171 -20
d6-iPAMP OlChemim ISTD 030 5041 -20
d5-IAA OlChemim ISTD 031 1531 -20
d2-GA1* OlChemim ISTD 032 2491 -20
d2-GA20 OlChemim ISTD 032 2481 -20
d2-GA29 OlChemim ISTD 032 2471 -20
d6-ABA OlChemim ISTD 034 2721 -20
Tzeatin: trans-zeatin; DHZ: dihydrozeatin; tZR: trans-zeatin riboside; DHZR: dihydrozeatin ribodide; tZMP: trans-zeatin riboside-5'-monophosphate; iP: isopentenyladenine; iPR: isopentenyladenosine; iPAMP: isopentenyladenosine-5'-monophosphate; IAA: indole-3-acetic acid; ABA: abscisic acid; GA1, 20, and 29: gibberellin A1, A20, and A29; STD: phytohormone standard; ISTD: phytohormone internal standard.
*Can be replaced with d4-GA1 (product number: 032 2491) due to d2-GA1 not being commercially available anymore.
Acetonitrile (Merck, catalog number: 1.00030)
Methanol (Merck, catalog number: 1.06007)
Milli-Q water (Merk Milli-Q)
Acetic acid (Merck, catalog number: 5.33001)
Formic acid (Merck, catalog number: 5.33002)
Liquid nitrogen
Node 2 axillary buds from garden pea plants with five fully expanded leaves
Internal standard working solution (see Recipes)
Extraction solvent (see Recipes)
1% acetic acid (see Recipes)
Plant hormone standard solutions (see Recipes)
Equipment
2010 Geno Grinder (SPEX SamplePrep, model: 2010)
3 mm diameter 440C stainless steel balls for Geno/Grinder 2010 (SPEX SamplePrep, product number: 2151)
Refrigerated centrifuge (Eppendorf, model: 5425R)
Solid phase extraction manifold (Chromabond, model: 730150)
Rotational vacuum concentrator with cold trap (Christ, model: RVC 2-33)
Ultra-high pressure liquid chromatograph system (Shimadzu Corporation, model: Nexera X2)
Triple quadrupole linear ion trap mass spectrometry system (AB Sciex, model: 5500)
Laboratory scale (accuracy: 0.0001 g)
Sep-Pak tC18 cartridge (Waters, catalog number: WAT036820)
1.5 mL Eppendorf tube (Eppendorf, catalog number: 0030121872)
HPLC vial (Agilent, catalog number: 5188-6591)
HPLC cap (Agilent, catalog number: 5190-7024)
Kinetex C18 reversed phase UPLC column (2.1 mm ×100 mm, 1.7 μm) (Phenomenex, catalog number: 00A-4475-AN)
Vertex low-retention non-filtered pipette tip (SSIbio, catalog number: 4337N00)
15 mL Falcon tube (Corning, catalog number: 352096)
4 °C refrigerator and -20 °C and -80 °C freezer
Procedure
Homogenization and extraction of samples
Weigh a 1.5 mL Eppendorf tube with two grinding beads (3 mm stainless steel metal balls) inside.
Sample 20 pea axillary buds (approximately 2 mm each) into one Eppendorf tube and snap freeze in liquid nitrogen.
Weigh the Eppendorf tube again after sampling and calculate the weight of axillary buds.
Homogenize the frozen plant tissues with 2010 Geno Grinder at 4 °C (1,500 stroke/min, 2×1 min).
Two outputs: RNA pellet and supernatant
Add 1 mL of freshly prepared extraction solvent (80% acetonitrile containing 1% acetic acid and 5 µL internal standard working solution) to the homogenized sample and vortex for 10 s at room temperature.
Leave the extract at -20 °C for 5 min and then centrifuge at 15,900 × g and 4 °C for 10 min.
Transfer 950 μL of supernatant to a new Eppendorf tube for hormone extraction. The remaining pellet can be used for RNA extraction (see Note 1).
Evaporate supernatant using a rotational vacuum concentrator with cold trap at room temperature until pellet is completely dry.
Sample cleaning with solid phase extraction (SPE) column
Add 1 mL of 1% acetic acid to the dried sample and pipette up and down three times for redissolution.
Store the sample at 4 °C until loading on Sep-Pak tC18 cartridge at step 14.
Set up the solid phase extraction manifold with Sep-Pak tC18 cartridge (Figure 1).
Figure 1. The setup of solid phase extraction manifold with Sep-Pak tC18 cartridge.
Wash Sep-Pak tC18 cartridge with 1 mL of 100% methanol.
Activate tC18 cartridge with 1 mL of 1% acetic acid.
Load the sample (from step 10) on the activated cartridge.
Wash the loaded cartridge with 1 mL of 1% acetic acid.
Elute the sample with 1 mL of 80% acetonitrile containing 1% acetic acid.
Evaporate the eluted sample using the rotational vacuum concentrator with cold trap at room temperature until completely dry.
Add 50 µL of 1% acetic acid to the dried sample, pipette up and down three times for redissolution, and vortex for 30 s.
Centrifuge the dissolved sample at 15,900 × g and 4 °C for 10 min and transfer the supernatant into a HPLC vial.
Store the sample at -80 °C before loading on the UPLC–MS/MS.
UPLC–MS/MS setup
The UPLC–MS/MS system used for this protocol is a Nexera X2 ultra-high pressure liquid chromatograph system coupled with a 5500 triple quadrupole linear ion trap mass spectrometry system equipped with an electrospray ionization source (ESI). The UPLC method is as follows:
Mobile phase A: 0.5% formic acid in Milli-Q water (v/v).
Mobile phase B: 0.5% formic acid in acetonitrile (v/v).
Flow rate: 0.5 mL min-1.
UPLC gradient: 4% B over 0.5 min, 4%–15% B over 7 min, and 15%–95% B over 3.5 min.
Cleanup step: 95%–95% B over 2 min, 95%–4% B over 0.1 min, and column wash for 1 min.
ESI parameters (for positive and negative modes, respectively): curtain gas, 20 psi; collision gas, medium; ion source temperature, 500 °C; ion source gas 1 and 2, 80 psi; and IonSpary voltage, +4,500 V or -4,500 V.
The scheduled multiple reaction monitoring (sMRM) parameters are listed in Table 2.
Table 2. sMRM parameters for phytohormone standards and their corresponding internal standards. CE, DP, and EP are the same between PH and ISTD.
PH Q1 Q3 RT SM ISTD Q1 Q3 RT SM CE DP EP
tZEATIN 220 136 2.3 + d5-tZ 225 136 2.2 + 25 75 10
DHZ 222 136 2.5 + d3-DZ 225 136 2.4 + 25 100 8
tZR 352 220 3.5 + d5-tZR 357 225 3.3 + 25 80 10
DHZR 354 222 3.6 + d3-DZR 357 225 3.4 + 30 80 10
tZMP 432 220 1.9 + d5-tZRP 437 225 1.8 + 25 100 10
IP 204 136 5.4 + d6-IP 210 136 5 + 20 70 10
IPR 336 136 6.9 + d6-IPR 342 136 6.5 + 40 80 10
IPAMP 416 136 4 + d6-IPRP 422 136 3.5 + 42 100 10
IAA 176 130 8.1 + d5-IAA 181 135 8.1 + 25 120 15
GA1 347 229 7.6 - d2-GA1 349 231 7.6 - -40 -80 -15
GA20 331 287 9.5 - d2-GA20 333 289 9.5 - -30 -80 -15
GA29 347 303 4.8 - d2-GA29 349 305 4.8 - -30 -80 -15
ABA 263 153 9.4 - d6-ABA 269 159 9.4 - -20 -80 -15
PH: phytohormone; Q1: precursor ion selected in Q1; Q3: product ion selected in Q3; RT: retention time; ISTD: internal standard; SM: scan mode; CE: collision energy; DP: declustering potential; EP: entrance potential.
Data analysis
MultiQuant software (AB Sciex, USA) is used to analyze raw mass spectrometry data. The concentration of each hormone is further calculated using Microsoft Excel by comparing with the internal standard concentration added in the sample.
Notes
The RNA from the plant debris pellet should be able to be extracted using most available RNA extraction methods. Two established RNA extraction methods have been tested: the first is a commercial RNA extraction kit, and the second is a cetyltrimethylammonium bromide (CTAB)-based method (Barbier et al., 2019a; Cao et al., 2020). The RNA from the pellet is extracted immediately, and the preservation condition for the pellet has not been tested in this protocol.
The validation of the UPLC–MS/MS method has been detailed in our previous publication (Cao et al., 2020).
Plant material should always be kept frozen until adding the extraction solvent, to prevent degradation of plant hormones or possible metabolic reactions in the plant cell.
Sep-Pak tC18 cartridge should be kept wet after activation until the elution of the sample.
The maintenance of the UPLC–MS/MS system should be strictly followed as per the requirement of the manufacturer, to prevent sensitivity decrease and environmental contamination.
All solvents and consumables that directly contact the sample have been tested and are free of environmental contamination. If any consumables need to be replaced with different brands, environmental contamination needs to be tested.
If the UPLC–MS/MS system needs to be replaced with other types of models or brands (e.g., Agilent, Thermos, or Waters), the settings of the UPLC–MS/MS need to be reoptimized with plant hormone standards and internal standards.
If the plant hormone extraction process cannot be finished in one working day, the process can be paused after step 8, and the dried sample can be stored at -20 °C for 24 h before continuing the extraction.
A summarized flow chart for the phytohormone and RNA extraction can be found at https://www.frontiersin.org/files/Articles/605069/fpls-11-605069-HTML/image_m/fpls-11-605069-g001.jpg.
Recipes
Internal standard working solution
10 ng mL-1 d5-tZEATIN
20 ng mL-1 d3-DHZ
40 ng mL-1 d5-tZR
100 ng mL-1 d3-DHZR
120 ng mL-1 d5-tZMP
40 ng mL-1 d6-iP
60 ng mL-1 d6-iPA
10 ng mL-1 d6-iPRMP
200 ng mL-1 d5-IAA
200 ng mL-1 d2-GA20
200 ng mL-1 d2-GA29
200 ng mL-1 d6-ABA
Dissolved in 100% methanol.
Store at -80 °C for up to one month.
Extraction solvent
Dilute acetonitrile and acetic acid with Milli-Q water, to 80% acetonitrile containing 1% acetic acid. Store at 4 °C for up to one month.
1% acetic acid
Dilute acetic acid with Milli-Q water to 1% acetic acid. Store at 4 °C for up to one month.
Plant hormone standard solutions
Plant hormone standard and internal standard solutions were diluted with methanol to 100 µg mL-1 (stock solution) and 1 µg mL-1 (working solution). Store at -80 °C for up to one year.
Acknowledgments
This method has been published as a methodology article in Frontiers of Plant Science (Cao et al., 2020). This research was funded by The University of Queensland and the Australian Research Council Georgina Sweet Fellowship (FL180100139) and supported during the establishment phase of the ARC Centre of Excellence for Plant Success in Nature and Agriculture (CE200100015). We thank Dr. Lindsay Shaw for reviewing the manuscript.
Competing interests
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.
References
Barbier, F. F., Chabikwa, T. G., Ahsan, M. U., Cook, S. E., Powell, R., Tanurdzic, M. and Beveridge, C. (2019a). A phenol/chloroform-free method to extract nucleic acids from recalcitrant, woody tropical species for gene expression and sequencing. Plant Methods 15(1): 62.
Barbier, F. F., Dun, E. A., Kerr, S. C., Chabikwa, T. G. and Beveridge, C. A. (2019b). An update on the signals controlling shoot branching. Trends Plant Sci 24(3): 220-236.
Cao, D., Barbier, F., Yoneyama, K. and Beveridge, C. A. (2020). A rapid method for quantifying RNA and phytohormones from a small amount of plant tissue. Front Plant Sci 11(1832).
Cao, D., Lutz, A., Hill, C. B., Callahan, D. L. and Roessner, U. (2017). A quantitative profiling method of phytohormones and other metabolites applied to barley roots subjected to salinity stress. Front Plant Sci 7: 2070.
Cao, Z.-Y., Sun, L. H., Mou, R. X., Zhang, L. P., Lin, X. Y., Zhu, Z. W. and Chen, M. X. (2016). Profiling of phytohormones and their major metabolites in rice using binary solid-phase extraction and liquid chromatography-triple quadrupole mass spectrometry. J Chromatogr A 1451: 67-74.
Charnikhova, T. V., Gaus, K., Lumbroso, A., Sanders, M., Vincken, J. P., De Mesmaeker, A., Ruyter-Spira, C. P., Screpanti, C. and Bouwmeester, H. J. (2017). Zealactones. Novel natural strigolactones from maize. Phytochemistry 137: 123-131.
Liu, Y., Fang, X. a., Chen, G., Ye, Y., Xu, J., Ouyang, G. and Zhu, F. (2019). Recent development in sample preparation techniques for plant hormone analysis. TrAC Trends in Analyt Chem 113: 224-233.
Novák, O., Napier, R. and Ljung, K. (2017). Zooming in on plant hormone analysis: tissue-and cell-specific approaches. Annu Rev Plant Biol 68: 323-348.
Pan, X., Welti, R. and Wang, X. (2010). Quantitative analysis of major plant hormones in crude plant extracts by high-performance liquid chromatography–mass spectrometry. Nat Protoc 5(6): 986.
Schäfer, M., Brütting, C., Baldwin, I. T. and Kallenbach, M. (2016). High-throughput quantification of more than 100 primary-and secondary-metabolites, and phytohormones by a single solid-phase extraction based sample preparation with analysis by UHPLC–HESI–MS/MS. Plant Methods 12(1): 30.
Šimura, J., Antoniadi, I., Široká, J., Tarkowská, D., Strnad, M., Ljung, K. and Novák, O. (2018). Plant hormonomics: Multiple phytohormone profiling by targeted metabolomics. Plant Physiol 177(2): 476-489.
Trapp, M. A., De Souza, G. D., Rodrigues-Filho, E., Boland, W. and Mithöfer, A. (2014). Validated method for phytohormone quantification in plants. Front Plant Sci 5(1-11).
Xin, P., Guo, Q., Li, B., Cheng, S., Yan, J. and Chu, J. (2020). A Tailored High-efficiency Sample Pretreatment Method for Simultaneous Quantification of 10 Classes of Known Endogenous Phytohormones. Plant Commun 1(3): 100047.
Yao, C. and Finlayson, S. (2015). Abscisic acid is a general negative regulator of Arabidopsis axillary bud growth. Plant Physiol 169(1): 611-626.
Yu, D., Rupasinghe, T. W., Boughton, B. A., Natera, S. H., Hill, C. B., Tarazona, P., Feussner, I. and Roessner, U. (2018). A high-resolution HPLC-QqTOF platform using parallel reaction monitoring for in-depth lipid discovery and rapid profiling. Anal Chim Acta 1026: 87-100.
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Gastrulation Screening to Identify Anti-metastasis Drugs in Zebrafish Embryos
JN Joji Nakayama
HM Hideki Makinoshima
ZG Zhiyuan Gong
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4525 Views: 1042
Reviewed by: Xi FengQin TangSalim Gasmi
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Original Research Article:
The authors used this protocol in eLIFE Dec 2021
Abstract
Few models exist that allow for rapid and effective screening of anti-metastasis drugs. Here, we present a drug screening protocol utilizing gastrulation of zebrafish embryos for identification of anti-metastasis drugs. Based on the evidence that metastasis proceeds through utilizing the molecular mechanisms of gastrulation, we hypothesized that chemicals interrupting zebrafish gastrulation might suppress the metastasis of cancer cells. Thus, we developed a phenotype-based chemical screen that uses epiboly, the first morphogenetic movement in gastrulation, as a marker. The screen only needs zebrafish embryos and enables hundreds of chemicals to be tested in five hours by observing the epiboly progression of chemical-treated embryos. In the screen, embryos at the two-cell stage are firstly corrected and then developed to the sphere stage. The embryos are treated with a test chemical and incubated in the presence of the chemical until vehicle-treated embryos develop to the 90% epiboly stage. Finally, positive ‘hit’ chemicals that interrupt epiboly progression are selected by comparing epiboly progression of the chemical-treated and vehicle-treated embryos under a stereoscopic microscope. A previous study subjected 1,280 FDA-approved drugs to the screen and identified adrenosterone and pizotifen as epiboly-interrupting drugs. These were validated to suppress metastasis of breast cancer cells in mice models of metastasis. Furthermore, 11β-hydroxysteroid dehydrogenase 1 (HSD11β1) and serotonin receptor 2C (HTR2C), the primary targets of adrenosterone and pizotifen, respectively, promoted metastasis through induction of epithelial-mesenchymal transition (EMT). Therefore, this screen could be converted into a chemical genetic screening platform for identification of metastasis-promoting genes.
Graphical abstract:
Keywords: Anti-metastasis drugs Metastasis Gastrulation EMT Phenotyping screening Zebrafish
Background
Cancer research using zebrafish as a model has attracted attention because it offers many unique advantages that are not readily provided by other animal models. Furthermore, the zebrafish system has also been increasingly recognized as a chemical screening platform because it provides the advantage of high-throughput screening in an in vivo vertebrate setting with physiologic relevance to humans (Zon and Peterson, 2005; MacRae and Peterson, 2015; Nakayama et al., 2020; Nakayama and Makinoshima, 2020; Nakayama and Gong, 2020).
Metastasis is responsible for approximately 90% of cancer-associated mortality. It proceeds through multiple steps: invasion, intravasation, survival in the circulatory system, extravasation, colonization, and metastatic tumor formation in secondary organs with angiogenesis (Nguyen et al., 2009; Chaffer and Weinberg, 2011; Welch and Hurst, 2019). Dissemination of cancer cells is an initial step of metastasis, and its molecular mechanism involves local breakdown of basement membrane, loss of cell polarity, and induction of epithelial-mesenchymal transition (EMT) (Tsai, J. H. and Yang, 2013; Lu, W. and Kang, 2019). These cellular and biological phenomena are also observed during vertebrate gastrulation in that evolutionarily conserved morphogenetic movements of epiboly, internalization, convergence, and extension cooperate to generate germ layers and sculpt the body plan (Solnica-Krezel, 2005). In zebrafish, the first morphogenetic movement, epiboly, is initiated at approximately four hours post fertilization (hpf) to move cells from the animal pole to eventually engulf the entire yolk cell by 10 hpf. These movements are governed by molecular mechanisms that are induced by temporally and spatially regulated gene expression; these mechanisms and changes in gene expression are partially observed in metastatic progression (White et al., 2017).
At least 50 common genes are involved in both gastrulation and metastasis progression (Table 1) (Yang, J. and Weinberg, 2008; Thiery et al., 2009; Nieto et al., 2016; Dongre and Weinberg, 2019; Yang, J. et al., 2020). These genes are expressed in Xenopus or zebrafish embryos, and genetic inhibition of each gene in these embryos interferes with gastrulation progression. Conversely, the same 50 genes are ectopically expressed in metastatic cancer cells and confer metastatic properties to cancer cells; genetic inhibition of each of these genes suppresses metastasis progression. This evidence led us to hypothesize that chemicals that interfere with zebrafish gastrulation might suppress metastasis progression of cancer cells. Based on the hypothesis, we developed a phenotype-based chemical screen that uses epiboly, the first morphogenetic movement in gastrulation, as a marker. This screen measures the suppressor effect of each test chemical by observing epiboly progression of chemical-treated embryos (Figures 1 and 2).
Table 1. A list of the 50 common genes that are involved in gastrulation and metastasis progression.
Genes Gastrulation Defects Reference Effects in Metastasis Reference
BMP Convergence and extension (Kondo, 2007) EMT (Katsuno et al., 2008)
WNT Convergence and extension (Tada and Smith, 2000) Migration and invasion (Vincan and Barker, 2008)
FGF Convergence and extension (Yang, X. et al., 2002) Invasion (Nomura et al., 2008)
EGF Epiboly (Song et al., 2013) Migration (Lu, Z. et al., 2001)
PDGF Convergence and extension (Damm and Winklbauer, 2011) EMT (Jechlinger et al., 2006)
CXCL12 Migration of endodermal cells (Mizoguchi et al., 2008) Migration and invasion (Shen et al., 2013)
CXCR4 Migration of endodermal cells (Mizoguchi et al., 2008) Migration and invasion (Shen et al., 2013)
PIK3CA Convergence and extension (Montero et al., 2003) Migration and invasion (Wander et al., 2013)
YES Epiboly (Tsai, W. B. et al., 2005) Migration (Barraclough et al., 2007)
FYN Epiboly (Sharma et al., 2005) Migration and invasion (Yadav and Denning, 2011)
MAPK1 Epiboly (Krens et al., 2008) Migration (Radtke et al., 2013)
SHP2 Convergence and extension (Jopling et al., 2007) Migration (Wang, F. M. et al., 2005)
SNAI1 Convergence and extension (Ip and Gridley, 2002) EMT (Batlle et al., 2000)
SNAI2 Mesoderm and neural crest formation (Shi, J. et al., 2011) EMT (Medici et al., 2008)
TWIST1 Mesoderm formation (Castanon and Baylies, 2002) EMT (Yang, J. et al., 2004)
TBXT Convergence and extension (Tada and Smith, 2000) EMT (Fernando et al., 2010)
ZEB1 Epiboly (Vannier et al., 2013) EMT (Spaderna et al., 2008)
GSC Mesodermal patterning (Sander et al., 2007) EMT (Hartwell et al., 2006)
FOXC2 Unclear, defects in gastrulation (Wilm et al., 2004) EMT (Mani et al., 2007)
STAT3 Convergence and extension (Miyagi et al., 2004) Migration (Abdulghani et al., 2008)
POU5F1 Epiboly (Lachnit et al., 2008) EMT (Dai et al., 2013)
EZH2 Unclear, defects in gastrulation (O'Carroll et al., 2001) Invasion (Ren et al., 2012)
EHMT2 Defects in neurogenesis (Lin, F. et al., 2005) Migration and invasion (Chen et al., 2010)
BMI1 Defects in skeleton formation (van der Lugt et al., 1994) EMT (Guo et al., 2011)
RHOA Convergence and extension (Zhu, S. et al., 2006) Migration and invasion (Yoshioka et al., 1999)
CDC42 Convergence and extension (Choi and Han, 2002) Migration and invasion (Reymond et al., 2012)
RAC1 Convergence and extension (Habas et al., 2003) Migration and invasion (Vega and Ridley, 2008)
ROCK2 Convergence and extension (Marlow et al., 2002) Migration and invasion (Itoh et al., 1999)
PAR1 Convergence and extension (Kusakabe and Nishida, 2004) Migration (Shi, X. et al., 2004)
PRKCI Convergence and extension (Kusakabe and Nishida, 2004) EMT (Gunaratne et al., 2013)
CAP1 Convergence and extension (Seifert et al., 2009) Migration (Yamazaki et al., 2009)
EZR Epiboly (Link et al., 2006) Migration (Khanna et al., 2004)
EPCAM Epiboly (Slanchev et al., 2009) Migration and invasion (Ni et al., 2012)
ITGB1/ITA5 Mesodermal migration (Skalski et al., 1998) Migration and invasion (Felding-Habermann, 2003)
FN1 Convergence and extension (Marsden and DeSimone, 2003) Invasion (Malik et al., 2010)
HAS2 Dorsal migration of lateral cells (Bakkers et al., 2004) Invasion (Kim et al., 2004)
MMP14 Convergence and extension (Coyle et al., 2008) Invasion (Perentes et al., 2011)
COX1 Epiboly (Cha et al., 2006) Invasion (Kundu and Fulton, 2002)
PTGES Convergence and extension (Speirs et al., 2010) Invasion (Wang, D. and Dubois, 2006)
SLC39A6 Anterior migration (Yamashita et al., 2004) EMT (Lue et al., 2011)
GNA12/13 Convergence and extension (Lin, F. et al., 2005) Migration and invasion (Yagi et al., 2011)
OGT Epiboly (Webster et al., 2009) Migration and invasion (Lynch et al., 2012)
CCN1 Cell movement (Latinkic, 2003) Migration and invasion (Lin, J. et al., 2012)
TRPM7 Convergence and extension (Liu et al., 2011) Migration (Middelbeek et al., 2012)
MAPKAPK2 Epiboly (Holloway et al., 2009) Migration (Kumar et al., 2010)
B4GALT1 Convergence and extension (Machingo et al., 2006) Invasion (Zhu, X. et al., 2005)
IER2 Convergence and extension (Hong et al., 2011) Migration (Neeb et al., 2012)
TIP1 Convergence and extension (Besser et al., 2007) Migration and invasion (Han et al., 2012)
PAK5 Convergence and extension (Faure et al., 2005) Migration (Gong et al., 2009)
MARCKS Convergence and extension (Iioka et al., 2004) Migration and invasion (Rombouts et al., 2013)
Figure 1. Schematic diagram of a phenotype-based chemical screen using zebrafish embryos. Pairs of adult zebrafish are crossed, and their embryos are collected at the two-cell stage and arrayed into individual wells of a 24-well plate. Different chemicals are added to each well when the embryos develop to the sphere stage. Epiboly progression of each chemical-treated embryo is compared to DMSO-treated embryos under a stereoscopic microscope when DMSO-treated embryos develop to the 90% epiboly stage.
Figure 2. Representative samples of chemical-treated embryos. Embryos at the sphere stage were treated with 10 μM of each indicated chemical. Niclosamide-treated embryos served as positive controls, while DMSO-treated embryos served as negative controls. Epiboly progression of each chemical-treated embryo was compared with that of DMSO-treated embryos under a stereoscopic microscope, when DMSO-treated embryos developed to the 90% epiboly stage.
This screen enables hundreds of chemicals to be tested in only five hours. Our study subjected 1,280 FDA-approved drugs to this screen and identified adrenosterone and pizotifen as epiboly-interfering drugs. These were further validated to suppress metastasis of breast cancer cells in mouse models of metastasis (Figure 3) (Nakayama et al., 2021a, 2021b). This screen can also measure suppressor effect of crude drugs. We subjected 120 herbal medicines to this screen and identified cinnamon bark extract as an epiboly-interfering drug. Cinnamon bark extract was validated to suppress metastatic dissemination of breast cancer cells in a zebrafish xenograft model (Nakayama et al., 2022). Moreover, this screen can be converted into a chemical genetic screening platform for identification of metastasis-promoting genes. We demonstrated that 11β-hydroxysteroid dehydrogenase 1 (HSD11β1) and serotonin receptor 2C (HTR2C), the primary targets of adrenosterone and pizotifen, respectively, induced EMT and promoted metastasis of breast cancer cells (Nakayama et al., 2021a, 2021b) (Figure 4).
Figure 3. Pizotifen, one of the epiboly-interrupting drugs, suppresses metastatic progression of breast cancer cells in vitro and in vivo. (A) Effect of pizotifen on cell motility and invasion of MBA-MB-231, MDA-MB-435, and PC9 cells. Either vehicle- or pizotifen-treated cells were subjected to Boyden chamber assays. Fetal bovine serum (1% v/v) was used as the chemoattractant in both assays. Each experiment was performed at least twice. (B) Representative images of primary tumors on day 10 post-injection (top panels) and metastatic burden on day 70 post-injection (bottom panels) taken using an IVIS Imaging System. (C) Number of metastatic nodules in the lungs of vehicle- and pizotifen-treated mice.
Figure 4. HTR2C, a primary target of pizotifen, induces EMT-mediated metastatic dissemination of human cancer cells. (A) Immunofluorescence staining of E-cadherin and vimentin expressions in the MCF7 cells. (B) Expression of E-cadherin, vimentin, and HTR2C were examined by Western blotting in the MCF7 and HaCaT cells; GAPDH loading control is also shown (bottom). (C) Representative images of dissemination patterns of MCF7 cells expressing either the control vector (top left) or HTR2C (lower left) in a zebrafish xenotransplantation model. White arrowheads indicate disseminated MCF7 cells. (D) Mean frequencies of the fish showing head, trunk, or end-tail dissemination (right). Each value is indicated as the mean ± SEM of two independent experiments. Statistical analysis was determined by Student’s t-test.
Materials and Reagents
150 mm dish (Corning, catalog number: 430599)
24-well flat bottom plastic plates (Corning, catalog number: CLS3473)
Wild-type zebrafish strain (AB line)
Tg (kdrl:eGFP) zebrafish (Provided by Dr. Stainier)
FDA-, EMA-, and other agencies-approved chemical libraries (Prestwick Chemical, Illkirch, France)
Niclosamide (Sigma-Aldrich, catalog number: N3510)
DMSO (Sigma-Aldrich, catalog number: D8418)
Anti-E-cadherin antibody (Cell Signaling Technology, catalog number: 14472)
Anti-vimentin antibody (Cell Signaling Technology, catalog number: 5741)
Anti-HTR2C antibody (Abcam, catalog number: ab133570)
Anti-GAPDH antibody (Cell Signaling Technology, catalog number: 2118)
Human breast cancer cell line MCF7 (ATCC, catalog number: HTB-22)
NaCl (Sigma-Aldrich, catalog number: S3014)
KCl (Sigma-Aldrich, catalog number: P9541)
MgSO4·7H2O (Sigma-Aldrich, catalog number: M2773)
E3 medium (see Recipes)
Equipment
External tank, a part of zebrafish breeding tank (Tecniplast, catalog number: ZB10BTE)
Perforated internal tank, a part of zebrafish breeding tank (Tecniplast, catalog number: ZB10BTI)
Polycarbonate divider, a part of zebrafish breeding tank (Tecniplast, catalog number: ZB10BTD)
Polycarbonate lid (Tecniplast, catalog number: ZB10BTL)
Incubator (AQUALYTIC, catalog number: 2418210)
Stereomicroscope (Leica, catalog number: MZ75)
Procedure
Zebrafish mating setup (Day 0); 10 min
At the night before collecting embryos, arrange pairs of male and female zebrafish separated by a divider (Figure 5).
Figure 5. Zebrafish breeding tank with a divider. Male and female zebrafish are separated by a divider which prevents contact for mating. The images are viewed from overhead angle (left) and from the side (right). The divider is then removed, which allows male zebrafish to contact female zebrafish for mating.
Note: Young adult zebrafish (3–9 months old) should be used for the crossing. The quality of zebrafish embryos affects screening efficiency (critical step). Water temperature is 27 °C. Duration of sunshine is set from 7:00 to 19:00.
Embryo collection and distribution (Day 1); 80 min
Remove the divider to allow the fish to spawn in the morning (7:00–10:00).
Allow crossing for 10 min to obtain zebrafish embryos of the same developmental stage. For example, if more than 20 chemicals are tested, the crossing might be performed three times at three different time points (Group A: 8:30, Group B: 9:00, and Group C: 9:30).
For example, a 60-drug screening would require approximately 1,300 embryos if each drug needs to be tested at one concentration:
Group A: 20 (embryos) × 1 (concentration) × 30 (drugs) + 20 (vehicle control) + 20 (positive control).
Group B: 20 (embryos) × 1 (concentration) × 30 (drugs) + 20 (vehicle control) + 20 (positive control).
Similarly, if each drug needs to be tested at two concentrations, approximately 2,600 embryos would be required:
Group A: 20 (embryos) × 2 (concentrations) × 30 (drugs) + 40 (vehicle controls) + 20 (positive control).
Group B: 20 (embryos) × 2 (concentrations) × 30 (drugs) + 40 (vehicle controls) + 20 (positive control).
After 10 min, replace the divider to prevent the zebrafish from spawning.
Note: This screen measures the suppressor effect of each chemical on the progression of epiboly in live zebrafish embryos. Therefore, epiboly proceeds while the researcher is measuring the effect under a stereoscopic microscope. If more than 20 chemicals need to be tested, the screening should be divided into more than two sessions, and each of the sessions should start at a different time point. For example, if 60 chemicals need to be tested, zebrafish should be crossed at three different time points that are over 30 min apart. That allows 30 min for measuring the effects (critical step).
Collect the embryos in 150 mm dishes containing E3 medium and remove dead embryos.
Incubate the embryos at 27 °C for 20 min.
Collect two-cell stage embryos under the stereoscopic microscope.
Note: This step has limited throughput. The collection of zebrafish embryos should be completed during the two-cell stage. Thus, 900–1,200 embryos at the two-cell stage would be the upper limit for one researcher.
Array approximately 20 embryos into each well of a 24-well plate.
Remove E3 medium from each well by using a pipet.
Add 900 µL of E3 medium to each well.
Embryo development to the sphere stage; 4 h
Incubate the embryos at 27 °C until they develop to the sphere stage
Note: The temperature of the E3 medium affects the development rate of zebrafish embryos. Higher temperatures accelerate the development rate; conversely, lower temperatures slow it down (Urushibata et al., 2021). Therefore, a non-uniform temperature in each well of a 24-well plate can cause false positives (critical step).
Addition of chemicals; 30 min
Prepare a 10-fold concentration of each chemical in E3 medium 30 min before adding the chemicals to the embryos.
Note: After preparing the respective 10-fold concentration of the media, the medium should be stored at 27 °C.
When the embryos develop to the sphere stage, add 100 µL of the respective 10-fold media to the wells.
For example, a 60-drug screening is divided into three groups:
The first set of 20 test chemicals, as well as niclosamide and DMSO as positive and negative controls, are added into group A when embryos from group A develop to the sphere stage.
The second set of 20 test chemicals, niclosamide, and DMSO are added into group B when embryos from group B develop to the sphere stage.
The last set of 20 test chemicals, niclosamide, and DMSO are added into group C when embryos from group C develop to the sphere stage.
Development of DMSO-treated embryos to the 90% epiboly stage; 5 h
After adding the test chemicals, incubate the embryos at 27 °C for approximately 5 h.
Note: The temperature of the E3 medium affects the development rate of zebrafish embryos. Non-uniform temperature in each well of a 24-well plate would cause false positives (critical step).
Measuring the inhibition effects of each chemical; 30 min
Compare the epiboly progression of chemical-treated embryos from group A and DMSO-treated embryos under the stereoscopic microscope, when the DMSO-treated embryos develop to the 90% epiboly stage.
Note: This step has limited throughput. Comparisons should be completed before DMSO-treated embryos at the 90% epiboly stage develop to the next development stage. Thus, 20–30 chemicals would be the upper limit for one researcher.
Compare the epiboly progression of chemical-treated embryos from group B and DMSO-treated embryos under the stereoscopic microscope, when the DMSO-treated embryos develop to the 90% epiboly stage.
Compare the epiboly progression of chemical-treated embryos from group C and DMSO-treated embryos under the stereoscopic microscope, when the DMSO-treated embryos develop to the 90% epiboly stage.
Note: Epiboly proceeds while a researcher is comparing the epiboly progression of chemical-treated and DMSO-treated embryos under the stereoscopic microscope. Therefore, measuring the effect should be completed in 30 mins (critical step). To confirm the reproducibility of whether 'hit' chemicals could interrupt the epiboly progression of zebrafish embryos, further testing on subsequent day is advised (critical step).
Data analysis
This screen measures the suppressor effect of chemicals based on the epiboly progression of zebrafish embryos. Niclosamide and DMSO can be used as positive and negative controls, respectively. Epiboly progression of chemical-treated embryos is compared with that of DMSO-treated embryos under a stereoscopic microscope, allowing positive ‘hit’ chemicals that interrupt epiboly progression to be selected (Figure 2) (Nakayama et al., 2021b, 2022).
Limitations
Throughput in steps 7 and 15, determine how many chemicals can be tested in one screening session. In step 7, the collection of zebrafish embryos should be completed during the two-cell stage and before the four-cell stage. Thus, 900–1,200 embryos at the two-cell stage would be the upper limit for one researcher. In step 15, comparing epiboly progression of each chemical-treated embryo with DMSO-treated embryos under the stereoscopic microscope should be completed before DMSO-treated embryos at the 90% epiboly stage develop to the next stage. Thus, 20–30 chemicals would be the upper limit for one researcher.
In addition, there are some limitations regarding chemical deliverance to zebrafish embryos. These are surrounded by the acellular chorion, which is known to be approximately 1.5–2.5 µm thick and to consist of three layers pierced by pore canals. The pore allows passage of water, ions, and chemicals. A study reported that molecules larger than 3–4 KDa fail to pass through the chorion. Therefore, this screen may not be able to measure the suppressor effect of molecules larger than 3–4 KDa (Pelka et al., 2017).
Troubleshooting
The quality of zebrafish embryos affects screening efficiency. For example, low-quality embryos show high frequencies of asymmetric cell cleavage, and their development is arrested at early cleavage stages (Yilmaz et al., 2017). If a screen used low-quality zebrafish embryos, it would generate false ‘hit’ chemicals since the suppressor effect of a test chemical is measured by observing the epiboly progression of chemical-treated embryos. If the number of zebrafish embryos showing morphological abnormalities correlate with the final concentration of a test chemical, those embryo abnormalities may result from the effect of the test chemical.
Anticipated results
Suppressor effects of a tested chemical on the epiboly progression of zebrafish embryos are significantly affected by the final concentration of the chemical. A previous study subjected 1,280 FDA-approved drugs to this screen and showed that 6% (78/1,280) of the tested drugs affected epiboly progression of the embryos treated with 10 μM. Out of these 78 epiboly-interrupting drugs, 25% of the drugs succeeded in suppressing cell motility and invasion of highly metastatic human cancer cells in a Boyden chamber assay. In contrast, epiboly progression was affected more severely when the embryos were treated at 50 μM, by 10.3% (132/1,280) of the tested drugs. From these, 85% (112/132) failed to suppress cell motility and invasion of highly metastatic human cancer cells in a Boyden chamber assay (Nakayama et al., 2021b).
Recipes
E3 medium
5.0 mM NaCl, 0.17 mM KCl, 0.33 mM MgSO4
Reagent Final concentration Amount
NaCl 5.0 mM
KCl 0.17 mM
MgSO4 0.33 mM
H2O n/a 1,000 mL
Acknowledgments
Figure 1 was drawn by Ami Inoue (Kyoto University of the Arts). Pictures of zebrafish mating tank with a divider were taken by Dr. Li Yan (National University of Singapore). This study was funded by grants from National Medical Research Council of Singapore (R-154000547511) and Ministry of Education of Singapore (R-154000A23112 and R154000B88112) to ZG. Experiments using mice were supported in part by research funds from the Yamagata prefectural government and the City of Tsuruoka. This screen protocol was used in previous research (Nakayama et al., 2021a, 2021b, 2022).
Competing interests
J.N., H.M., and Z.G. declare no conflict of interest.
Ethics
The study protocol using zebrafish was approved by the Institutional Animal Care and Use Committee of the National University of Singapore (protocol number: R16-1068). The study protocol using mice (protocol number: BRC IACUC #110612) was approved by A*STAR (Agency for Science, Technology and Research, Singapore).
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4,526 | https://bio-protocol.org/en/bpdetail?id=4526&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
Enhanced Ribonucleoprotein Immunoprecipitation (RIP) Technique for the Identification of mRNA Species in Ribonucleoprotein Complexes
SF Saja A. Fakhraldeen
SB Scott M. Berry
DB David J. Beebe
CA Caroline M. Alexander
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4526 Views: 1162
Reviewed by: Chiara AmbrogioDavide Botta Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in The Journal of Biological Chemistry Mar 2022
Abstract
RNA binding proteins (RBPs) are critical regulators of cellular phenotypes, and dysregulated RBP expression is implicated in various diseases including cancer. A single RBP can bind to and regulate the expression of many RNA molecules via a variety of mechanisms, including translational suppression, prevention of RNA degradation, and alteration in subcellular localization. To elucidate the role of a specific RBP within a given cellular context, it is essential to first identify the group of RNA molecules to which it binds. This has traditionally been achieved using cross-linking-based assays in which cells are first exposed to agents that cross-link RBPs to nucleic acids and then lysed to extract and purify the RBP-nucleic acid complexes. The nucleic acids within the mixture are then released and analyzed via conventional means (e.g., microarray analysis, qRT-PCR, RNA sequencing, or Northern blot). While cross-linking-based ribonucleoprotein immunoprecipitation (RIP) has proven its utility within some contexts, it is technically challenging, inefficient, and suboptimal given the amount of time and resources (e.g., cells and antibodies) required. Additionally, these types of studies often require the use of over-expressed versions of proteins, which can introduce artifacts. Here, we describe a streamlined version of RIP that utilizes exclusion-based purification technologies. This approach requires significantly less starting material and resources compared to traditional RIP approaches, takes less time, which is tantamount given the labile nature of RNA, and can be used with endogenously expressed proteins. The method described here can be used to study RNA-protein interactions in a variety of cellular contexts.
Graphical abstract:
Keywords: RNA binding protein RNA-protein interaction Ribonucleoprotein complex Post-transcriptional regulation Breast cancer Cancer biology
Background
Post-transcriptional regulation of gene expression enables rapid systematic cellular responses to various stimuli and stressors (Chua et al., 2020; Weskamp et al., 2021). Post-transcriptional regulation can be mediated by various cis- and trans-acting elements, including regulatory elements on the mRNA itself as well as microRNAs and RNA-binding proteins (RBPs) (Theil et al., 2018; Furlan et al., 2021; Ma et al., 2022). In cells, RBPs often exist within large complexes, known as ribonucleoprotein (RNP) complexes, that include the RBPs themselves alongside their mRNA binding partner(s) and other proteins/molecules. Through these interactions in RNP complexes, RBPs can regulate the expression, translation, and/or localization of the mRNA species to which they bind (Dvir et al., 2018; Formicola et al., 2019).
Importantly, a single RBP can bind to and regulate the expression of many mRNAs (Hentze et al., 2018). Thus, deregulation of RBP expression has wide-ranging consequences for cellular health and survival. Notably, deregulation of RBP activity has been implicated in numerous human pathologies, including neurological disorders, kidney disease, and various types of cancer (Chatterji and Rustgi, 2018; Wang et al., 2018; Shi et al., 2020; Kinoshita et al., 2021; Weskamp et al., 2021). In order to begin probing the mechanism via which deregulation of RBP expression leads to disease, it is essential to first identify the group of mRNA binding partners to which the RBP binds. By identifying a list of mRNA binding partners for a given RBP, researchers can begin identifying candidate mRNA partner(s) from the list with potential links to the observed phenotype(s) and can thus begin elucidating the mechanism via which deregulated RBP expression leads to a diseased state (Fakhraldeen et al., 2022).
Given the importance of identifying mRNA binding partners of RBPs, research efforts have focused on developing methodologies that can reproducibly purify and identify mRNAs from RNP complexes (Zhao et al., 2022). The most common methodologies developed thus far rely upon cross-linking of often over-expressed RBPs prior to immunoprecipitation (IP). Once the RNP complexes are purified via manual IP, the cross-links are reversed, and the RNA is extracted and then analyzed via the researchers’ preferred method (e.g., qRT-PCR, microarray analysis, Northern blot, or RNA-Seq). Multiple versions of this so-called ribonucleoprotein immunoprecipitation (RIP) procedure have been developed, including RIP-Chip (manual RIP followed by microarray analysis), CLIP (cross-linking and immunoprecipitation), iCLIP (individual nucleotide resolution CLIP), PAR-CLIP (photoactivatable ribonucleoside-enhanced CLIP), HiTS-RAP (high throughput sequencing–RNA affinity profiling), and various adaptations therefrom (Galgano and Gerber, 2011; Jain et al., 2011; Danan et al., 2016, 2022; Haecker and Renne, 2014; Spitzer et al., 2014; Guerreiro et al., 2014; Ozer et al., 2015; Sutandy et al., 2016; Diaz-Munoz et al., 2017; George et al., 2017; Perconti et al., 2019; Lewinski et al., 2020; Benhalevy and Hafner, 2020; Baldini and Labialle, 2021). These approaches to RIP have several drawbacks. First, introduction of exogenously expressed RBPs can affect the mRNA binding profile of the RBP. Second, the processes of cross-linking and reverse cross-linking themselves can introduce artifacts by inducing interactions that were previously absent/not physiologically relevant, or by not capturing all interactions. Third, performing the IP procedure manually is time consuming and may promote irreproducibility based on the handler. Finally, any added benefits of potentially being able to identify specific binding sites of RBPs with their mRNA binding partners using these techniques are overshadowed by the complex computational approaches required in order to perform such analyses (Jens, 2016; Huessler et al., 2019; Busch et al., 2020; Zhao et al., 2022).
The method described here relies on exclusion-based sample preparation (ESP) technologies to perform RIP (Berry et al., 2015; Pezzi et al., 2018; Fakhraldeen et al., 2022). Specifically, we describe a procedure for performing RIP using the EXTRACTMAN device, which is an adaptation of the ESP-based Sliding Lid for Immobilized Droplet Extraction (SLIDE) technology. Not only does this method require less starting material, but it also offers significantly faster processing times, which is of particular relevance to RIP given the labile nature of RNA. Finally, the use of this sensitive method precludes the need to over-express the RBP of interest or to cross-link the lysate and instead allows for purification of the endogenous RBP in its native state. We describe the successful application of this method to identify mRNA binding partners of the RBP IGF2BP1 in the human embryonic kidney cell line HEK293T as well as in the human breast cancer cell lines MCF7 and MDA-MB-231 (Fakhraldeen et al., 2022). The extracted RNA was analyzed by qRT-PCR, but it can be analyzed using microarray analysis, RNA-Seq, or any endpoint of interest for RNA identification/profiling.
Materials and Reagents
293T human embryonic kidney cells (ATCC, catalog number: CRL-3216)
MCF7 cells (ATCC, catalog number: HTB-22)
MDA-MB-231 cells (ATCC, catalog number: CRM-HTB-26)
10 cm dishes (Fisherbrand, catalog number: FB0875712)
Cell scrapers (Fisherbrand, catalog number: 08-100-241)
DMEM, high glucose, HEPES (Thermo Fisher Scientific, Gibco, catalog number: 12430104)
DMEM, low glucose, pyruvate, HEPES (Thermo Fisher Scientific, Gibco, catalog number: 12320032)
Fetal bovine serum (FBS) [various vendors; pre-screened on mammary epithelial cells to identify lots that promoted cell growth without cell death (floating cells) over the course of four passages]
Penicillin/streptomycin (Thermo Fisher Scientific, Gibco, catalog number: 15070063)
1× phosphate buffered saline (PBS), pH 7.4 (Thermo Fisher Scientific, Gibco, catalog number: 10010023)
HEPES (1 M) (Gibco, Thermo Fisher Scientific, catalog number: 15630080)
MgCl2 (Merck/Sigma-Aldrich, catalog number: 208337)
KCl (Merck/Sigma-Aldrich, catalog number: P9541)
NonidetTM P 40 substitute (Fluka Biochemika, catalog number: 74385)
DTT (1,4-dithiothreitol; MilliporeSigma, catalog number: 111474)
RNaseOUTTM recombinant ribonuclease inhibitor (Thermo Fisher Scientific, Invitrogen, catalog number: 10777-019). Store at -20 °C and thaw on ice prior to use
Halt protease and phosphatase inhibitor single-use cocktail (Thermo Fisher Scientific, catalog number: 78442)
Dynabeads® Protein G (Novex by Life Technologies, catalog number: 10003D). Store at 4°C
Tween-20 (Merck/Sigma-Aldrich, catalog number: P9416)
RNeasy® mini kit (Qiagen, catalog number: 74104)
QuantiTect reverse transcription kit (Qiagen, catalog number: 205311)
Bradford reagent (Thermo Fisher Scientific, catalog number: 23238)
Transfer membrane Immobilon-P polyvinylidene difluoride (PVDF) (Merck/Millipore, catalog number: IPVH00010)
PreciseTM 4%–20% Tris-HEPES-SDS protein gels, 4.5 mm (Thermo Fisher Scientific, catalog number: 25244) or any pre-cast gel of choice
Anti-IMP-1 (D33A2) rabbit monoclonal primary antibody (Cell Signaling, catalog number: 8482)
Anti-vinculin mouse primary antibody, clone V284 (MilliporeSigma, catalog number: 05-386)
Anti-GAPDH (14C10) rabbit monoclonal primary antibody (Cell Signaling, catalog number: 2118)
Horseradish peroxidase (HRP) donkey anti-mouse polyclonal secondary antibody (Jackson ImmunoResearch, catalog number: 715-035-151)
HRP goat anti-rabbit polyclonal secondary antibody (Invitrogen, catalog number: G-21234)
HRP mouse anti-rabbit IgG (conformation-specific) (L27A9) secondary antibody (Cell Signaling, catalog number: 5127)
Non-immune rabbit IgG whole molecule control (Jackson ImmunoResearch, catalog number: 011-000-003)
Milk non-fat, dry milk powder (Kroger or equivalent)
Polysome lysis buffer (see Recipes)
RIP wash/elution buffer (see Recipes)
5% milk in TBS-Tween (see Recipes)
Equipment
EXTRACTMAN device (Gilson)
Spectrophotometer (Thermo Fisher Scientific, model: NanoDrop 2000)
Gel documentation system (Bio-Rad, Gel Doc XR+ Gel Documentation System)
Refrigerated centrifuge that can reach speeds of ≥12,000 rpm (must accommodate 50 mL tubes spun at 3,000 × g and 1.5 mL tubes spun at 12,000 rpm)
Plate centrifuge (Beckman, model: Allegra X15R)
Sonicator (Fisher Scientific 100)
Tube rotator that can hold 1.5 mL tubes; a standard rotisserie tube rotator with adaptors for Eppendorf tubes was used
qPCR machine (Applied Biosystems, ABI7900HT Fast Real-Time PCR System)
Procedure
Cell culture
Plate cells in 10 cm dishes at ≥50% confluence in appropriate media. For 293T cells, plating 1.5 × 106 cells in a 10 cm dish and harvesting within 48 h should yield approximately 2 mg of protein, which should suffice for the endpoint(s) of interest.
Note: One 10 cm dish yields 500 µL of lysate, or the equivalent of two samples for RIP (200 µL of lysate are needed per RIP reaction). If cells express high endogenous levels of RBP of interest, one 10 cm dish should provide sufficient material for RIP; if cells express low endogenous levels of RBP of interest, plan on combining two 10 cm dishes into 500 µL of lysate; if endogenous expression levels of RBP are unknown, we recommend starting with the more concentrated lysate (i.e., two 10 cm dishes combined into 500 µL of lysate). Take into account the need for 2× 200 µL of lysates for each RIP: one lysate to be used for purification with an antibody targeting the RBP of interest and one lysate to be used for purification with an anti-IgG control antibody. The purified eluate from each RIP reaction should provide sufficient material for both protein and RNA analyses.
Incubate cells at 37 °C.
Proceed to the next step 24–48 h post plating.
Cell lysis for RNP lysate preparation
Note: Perform all these steps on ice.
Remove media from dish by aspiration.
Rinse cells with 5 mL of ice-cold PBS twice.
Add 5 mL of fresh ice-cold PBS.
Scrape cells from dish using scraper.
Transfer scraped material to 50 mL conical tubes.
Pellet cells by centrifugation at 3,000 × g and 4 °C for 5 min.
Aspirate and discard the supernatant.
Add polysome lysis buffer (PLB) to pellet (500 µL of PLB per 10 cm dish or 500 µL of PLB per two 10 cm dishes for more concentrated lysate) and pipette up and down to resuspend the pellet completely.
Transfer lysate to 1.5 mL Eppendorf tubes.
Store lysate in PLB at -80 °C or proceed directly to step 11.
Sonicate lysates (10 pulses at 4–5 W) in a cold room.
Spin lysates at approximately 12,000 rpm for 30 min at 4 °C.
Transfer supernatant into new Eppendorf tubes and spin two more times using the same conditions (three total centrifugation cycles with identical conditions).
Aliquot approximately 200 µL of lysate per Eppendorf tube and store at -80 °C until ready to perform RIP procedure or proceed immediately to the next step.
RNP immunoprecipitation (RIP)/EXTRACTMAN
Thaw lysates on ice (if frozen).
Add approximately 1.2 µg of primary antibody to 200 µL of RIP lysate (containing approximately 0.8 mg of protein) and add matched IgG control to another 200 µL of RIP lysate.
Note: The quantity of antibody will vary depending on the antibody affinity or endogenous cellular RBP levels and will need to be optimized (1–10 µg of antibody is a typical range).
Add 5 µL of washed protein G–bound paramagnetic Dynabeads to the same tube(s) containing RIP lysate + primary antibody.
Note: Dynabead washing procedure is described in manufacturer’s specification sheet.
Incubate mixture on rotator at low speed (approximately 30 rotations per minute) and 4 °C for preferred amount of time.
Note: Approximately 25% of protein was pulled through with 30 min incubation; however, pull-through efficiency will vary depending on the antibody affinity or RBP levels and will need to be optimized (30 min–16 h should be a reasonable range for incubation times).
Prepare EXTRACTMAN device.
Note: EXTRACTMAN device setup is presented in video form at the following link: https://www.gilson.com/extractman-starter-kit.html.
Set up new disposable microplate and bead collection strip on the device.
Note: Each plate contains four “columns” labeled A–D, with each column accommodating one RIP reaction. Thus, each plate can be used to run up to four RIP reactions simultaneously.
Place the magnet locator at the correct starting position as specified in the EXTRACTMAN manual.
For each RIP reaction that will be run, add 100 µL of wash/elution buffer to each of the five small wells per column in the microplate (this will include the wash wells as well as the bound elution well).
Note: Add less volume to the elution well if a more concentrated lysate is required.
Add 200 µL of the RIP mixture (lysate + primary antibody + paramagnetic Dynabeads) to the large well(s) in the microplate.
Proceed with device operation as described in the EXTRACTMAN manual. Briefly, alternatively proceed with shifting the handle and then the magnet locator to each successive stop on the device sequentially with a brief (< 5 s) pause at each stop.
Collect the remaining volume in each input well following the procedure and put in tube(s) (approximately 200 µL volume; this is what is labeled as the “unbound” fraction).
Collect the volume in the last well per column in the microplate and put in tube(s) (approximately 100 µL volume; this is what is labeled as the “bound” fraction).
Collect the volumes in the middle wash wells and put in tubes (approximately 100 µL per well).
Note: This step is not required, but the collected volume can be used to check for any losses associated with the washing procedure if deemed necessary.
Store the unbound, bound, and wash fractions (if applicable) at -20 °C for downstream analyses or proceed directly to steps D or F for RNA and/or protein analysis, respectively.
RNA isolation
Note: Prior to beginning work, all benchtops, pipettes, handlers’ gloves, etc. should be wiped down carefully with RNase Away or an equivalent solution containing RNase inhibitor(s). Additionally, all tubes, tips, and other consumables should be certified RNase/nuclease-free. Cell culture media, PBS, and other solutions (e.g., lysis buffer components) should be dedicated for RIP and kept separately from the same solutions used for other experimental purposes. This is to avoid compromising the RNA analysis endpoints by preventing degradation of the RNAs within the RNP complexes being purified.
Add 350 µL of lysis buffer provided in the Qiagen RNeasy mini kit directly into the unbound/bound/wash fraction volumes.
Follow manufacturer’s instructions for remainder of processing steps.
Note: The Qiagen RNeasy mini kit was used for the work described here, but other RNA extraction kits/methods will likely yield similar results if procedures for RNA isolation from cells are followed as per manufacturer’s instructions.
qRT-PCR
Determine RNA concentration and quality using approach of choice [e.g., load approximately 1–2 µL of unbound/bound fractions onto NanoDrop device and record RNA concentration and 260/280 (ideal range: 1.7–2.0) and 260/230 ratios (ideal range: 1.8–2.2)].
Set up RT-PCR using kit of choice (e.g., QuantiTect reverse transcription kit) and appropriate thermal cycler settings.
Note: Run each reaction at least in duplicates.
Run qPCR using cDNA generated in previous step and primers of choice with appropriate temperature and time settings for each cycle.
Note: Other endpoints such as Northern blot, microarray, or RNA-Seq analysis can also be applied here.
Western blotting
Determine protein concentration in each of the unbound, bound, and wash fractions (if applicable) using approach of choice (e.g., addition of Bradford reagent followed by colorimetric reading)
Load equal quantities of protein lysate from each of the unbound fractions onto polyacrylamide gel to enable quantitative visualization of the protein of interest. Load appropriate quantities of bound fractions assuming 20%–100% recovery of the RBP of interest (depending on antibody affinity). This loaded fraction should be recorded and then used to calculate the pull-through efficiency.
Perform Western blotting using apparatus, run/transfer settings, and primary and secondary antibodies of choice.
Data analysis
RIP procedures can be used to identify mRNA binding partners of RBPs. Here, we describe the fast and efficient purification of RNPs containing the RBP IGF2BP1 from human cells using the EXTRACTMAN device. RNA can then be extracted from the purified RNPs and subjected to qRT-PCR analysis. Note that qRT-PCR analysis could be used in the context of the work described here because some mRNA binding partners of IGF2BP1 were already identified in previous analyses. If no mRNA binding partners of the RBP of interest are known, then more exploratory RNA identification approaches such as microarray analysis or RNA-Seq should be applied.
Assessment of RBP enrichment efficiency during the purification procedure is performed using Western blot analysis of the purified fraction (bound), and on a portion of the input lysate following the purification procedure (unbound). Analysis of the protein content in the wash fractions might also be useful. The approximate protein yield in lysates from 293T cells was on the order of 4 µg/µL (approximately 2 mg total protein) from one 10 cm dish. The intensity of the bands observed on the Western blot was quantified using the Image Lab software provided with the Bio-Rad gel documentation system. Band intensity values were used for assessment of pull-through efficiency, knowing the linear range of response for the signals. Specifically, dividing the band intensity of the bound fraction by that of the unbound fraction generates a “% pull-through” readout, which can be used as a proxy for purification efficiency (Figure 1).
Importantly, purification efficiency analysis must be performed on blots of both the RBP of interest as well as control proteins (vinculin or GAPDH were used here). While the % pull-through efficiency may vary for the RBP of interest depending on various factors such as antibody affinity, the % pull-through for the control protein should be negligible. Significant % pull-through of the control protein may indicate non-specific immunoprecipitation conditions, which could be modified by increasing the stringency of the buffer binding conditions by altering the salt or detergent concentrations.
The same analysis should also be performed on the unbound and bound fractions of RIP reactions using an IgG control antibody, with the expectation that this will show minimal pull-through of either the RBP or control protein (e.g., GAPDH and vinculin).
In the analysis performed here, the % pull-through efficiency of the RBP CRD-BP following overnight incubation with primary CRD-BP antibody and standard RIP procedures was 37%, compared to a 60% pull-through efficiency when using the EXTRACTMAN-based RIP technique (Figure 1A). Importantly, no measurable amount of either CRD-BP or the control protein vinculin was detected following incubation with IgG control antibody when using either the standard or EXTRACTMAN-based RIP techniques.
The image lab software from Bio-Rad was used to quantify the relative band intensities, which were then used to calculate the % pull-through efficiency. The software instructs the user to select a reference band (in this case, the band in the unbound fraction for each respective RIP reaction). The reference band intensity is then set to 1, and the band intensity of the test/experimental condition (in this case, the band in the bound fraction for each respective RIP reaction) is quantitated relative to the reference band. Thus, the relative band intensity values for the unbound fraction are shown in Table 1 (the band intensity values for the bound fraction are always set to 1). The % pull-through efficiency is then calculated as the band intensity of the unbound fraction divided by the sum of the band intensities for both the bound and unbound fractions multiplied by 100.
Table 1. Relative Western blot band intensity values.
The relative band intensity values for the bands observed on the Western blots shown in Figure 1 were quantified using the Bio-Rad Image Lab software. O/N: overnight.
Antibody RIP fraction O/N 2 h 30 min
CRD-BP Unbound 1 1 1
Bound 1.47 0.49 0.31
IgG Unbound 1 1 1
Bound 0.59 0.24 0.15
Figure 1. Western blot analysis of pull-through efficiency following RIP of IGF2BP1 in (A–B) 293T cells and (C) MCF7 and MDA-MB-231 cells. (A) Analysis of pull-through efficiency following RIP procedures performed with varying IGF2BP1 primary antibody incubation times [30 min, 2 h, and overnight (O/N)]. (A–B) IGF2BP1 RIP was performed in 293T cells using both standard procedures and EXTRACTMAN, and efficiencies (expressed as percentages) were compared between the two techniques. (C) Analysis of pull-through efficiency following IGF2BP1 RIP procedures performed on human breast cancer cells using EXTRACTMAN.
Once the specificity of the RIP procedure has been confirmed by Western blot of the proteins of interest, analysis of the RNA content within the purified material can be performed. Specifically, similar to protein analysis, RNA is extracted from both the unbound and bound RIP fractions. The extracted RNA is first assessed for quality and quantity, for example, using a NanoDrop device. Then, equal quantities of RNA from each fraction are reverse transcribed for analysis by qPCR. RNA yields from 293T cells were on the order of 400 ng/µL (approximately 12 µg of RNA total) from a single confluent 10 cm dish. Yields varied between cell types but generally fell within the range of 7–15 µg per confluent 10 cm dish. Following the RIP procedure with an antibody targeting the protein of interest using the EXTRACTMAN device, RNA yields in the output fraction ranged approximately from 0.2 to 0.6 µg (or the equivalent of approximately 2%–10% pull-through) (Figure 2).
Reactions are set up using primers for target mRNAs as well as control mRNAs (housekeeping genes and/or genes known to not being associated with your RBP of interest). Reactions are run at least in duplicate. Following the qPCR run, cycle threshold (Ct) values are recorded for each of the unbound and bound fractions from the duplicate set of lysates for each set of primers/gene being investigated. The delta_Ct (∆Ct=Ctbound-Ctunbound) is then calculated for each replicate for each set of primers/gene. The fold change is then calculated as 2-∆Ct. For a given set of primers, if the fold change between the unbound and bound fractions of the RBP pull-through is significantly different from that of the IgG control pull-through complex, this RNA is designated as enriched. To obtain a % mRNA pull-through value, the fold change is divided by a value equivalent to the fold change + 1, i.e.,
Figure 2. qPCR validation of RNA species pulled through following IGF2BP1 RIP procedures in (A) 293T cells and (B) MCF7 cells. qPCR was performed on RNA isolated from IGF2BP1- and IgG-enriched RIP lysates using primers targeting specific mRNA species that were previously identified in IGF2BP1-containing ribonucleoprotein complexes.
Total % RNA pull-through can be calculated by dividing the total amount of RNA in the bound fraction by the sum of the total amount of RNA in the bound and unbound fractions and multiplying by 100. The total amounts of RNA can be obtained by multiplying the concentration of RNA in each respective fraction by the total volume of that fraction.
Recipes
Polysome lysis buffer
KCl powder (m.w.: 74.5 g/mol) 100 mM, 0.7 g (745 mg)
HEPES solution 10 mM, pH 7.0, 1 mL of 1 M HEPES solution (pH 7.0)
MgCl2 powder (m.w.: 95.2 g/mol) 5 mM, 0.05 g (47.6 mg)
Nonidet P-40 0.5%, 0.5 mL
*Halt protease and phosphatase inhibitor single-use cocktail (100× stock) 1×
*RNaseOUTTM (40 U/µL) 2 U/µL
*DTT 1 mM
Total: 100 mL
* Add fresh prior to each use (only prepare volume required for specific number of lysates needed per experiment; therefore, volume will vary); remaining ingredients can be mixed and prepared as a stock solution in an RNase/nuclease-free tube and stored at 4 °C for up to one month.
5% milk in Tris-buffered saline (TBS)-Tween
Milk 5%, 5 mL
TBS-Tween (0.01%), 95 mL
Total: 100 mL
RIP wash/elution buffer (0.01% Tween)
Tween-20 0.01%, 1 mL
PBS, 99 mL
Total: 100 mL
Acknowledgments
Ildiko Kasza and Joshua Martin offered technical assistance. Gilson, Inc (Madison, WI) kindly shared the EXTRACTMAN device. The work was jointly supported by the Kuwait Foundation for the Advancement of Sciences (project number 2013-6302-03, awarded to SAF), Department of Defense Scholar Award (grant number W81XWH-06-1-0491, awarded to CMA), National Cancer Institute (grant number RO1CA186134, to DJB), and by pilot funding from the National Institutes of Health/National Cancer Institute (grant number P30 CA014520–University of Wisconsin Comprehensive Cancer Center Support). This protocol was originally described in Fakhraldeen et al. (2022).
Competing interests
S. M. B. holds equity in and is employed by Salus Discovery LLC, which has licensed technology described in this paper. D. J. B. holds equity in BellBrook Labs LLC, Tasso Inc, Stacks to the Future LLC, Lynx Biosciences LLC, Onexion Bio-systems LLC, and Salus Discovery LLC. All other authors declare that they have no competing interests with the content of this article.
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4,527 | https://bio-protocol.org/en/bpdetail?id=4527&type=0 | # Bio-Protocol Content
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Peer-reviewed
LIST: A Newly Developed Laser-assisted Cell Bioprinting Technology
KR Katiane Roversi *
HO Hamid Ebrahimi Orimi *
ME Mahyar Erfanian
ST Sebastien Talbot
CB Christos Boutopoulos
(*contributed equally to this work)
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4527 Views: 860
Reviewed by: Alessandro Didonna Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in Micromachines (Basel) Jul 2021
Abstract
Cell bioprinting technologies aim to fabricate tissue-like constructs by delivering biomaterials layer-by-layer. Bioprinted constructs can reduce the use of animals in drug development and hold promise for addressing the shortage of organs for transplants. We recently introduced a laser-assisted drop-on-demand bioprinting technology termed Laser Induced Side Transfer (LIST). This technology can print delicate cell types, including primary neurons. This bioprinting protocol includes the following key steps: cell harvesting, bio-ink preparation, laser setup priming, printing, and post-printing analysis. This protocol includes a detailed description of the laser setup, which is a rather unusual setup for a biology lab. This should allow easy reproduction by readers with basic knowledge of optics. Although we have focused on neuron bioprinting, interested readers will be able to adapt the protocol to bioprint virtually any cell type.
Graphical abstract:
Keywords: Laser-assisted bioprinting 3D bio-printing Laser-induced side transfer Nociceptor neurons Drop-on-demand Tissue engineering
Background
Bioprinting technologies employ precise delivery of bio-inks for the fabrication of living constructs. Such constructs serve as drug screening models and can potentially address the organ donation shortage (Knowlton et al., 2018). Bioprinting technologies can be categorized into four main classes: material jetting, vat photopolymerization (e.g., stereolithography), pneumatic or mechanical material extrusion, and free-form spatial printing. Depending on the printing mechanism, these technologies present partial compatibility with available bio-ink formulations, with the bio-ink viscosity being the limiting factor (Kang et al., 2016).
Laser Induced Side Transfer (LIST) is a drop-on-demand bioprinting technology that was recently developed by our group (Ebrahimi Orimi et al., 2020; Roversi et al., 2021). This technology uses low-energy nanosecond laser pulses to generate a transient microbubble at the distal end of a glass microcapillary supplied with bio-ink. Microbubble expansion results in the ejection of a cell-laden microjet perpendicular to the irradiation axis. We have previously used LIST to print delicate cell types such as human umbilical vein endothelial cells (Ebrahimi Orimi et al., 2020) and adult mouse dorsal root ganglion (DRG) neurons (Roversi et al., 2021). Bioprinted cells maintained high viability and functionality. Compared to the first report on LIST (Ebrahimi Orimi et al., 2020), this protocol provides a detailed technical description of all steps, including the assembling of the laser setup, which is a rather unusual setup for a biology lab. This should allow easy reproduction by readers with basic knowledge of optics.
The LIST technology can be used to print virtually any cell type. As such, it holds promise to fill a technological gap in the drop-on-demand bioprinting field: the lack of technologies for printing large scale constructs using bio-inks of both high and low viscosity.
Materials and Reagents
0.45 μm filter (VWR, catalog number: CA28145-497)
15 mL Falcon tube (VWR, catalog number:62406-200)
100 μm filter (pluriSelect, catalog number: 43-40100-00)
Hollow square capillaries, ID 0.30 mm × 0.30 mm, 0.15 mm wall thickness, 50 mm long (Vitrocom, catalog number: 8330-050)
Tube for connecting the capillary to the pump (VWR, catalog number: 89404-042)
12-wells plate (VWR, catalog number: 10062-894)
18 mm microscope round cover glasses (VWR, catalog number: 48380-046)
35 mm high glass bottom dish (ibidi, catalog number: 81158)
60 mm Petri dishes (VWR, catalog number: 25384-092)
Homozygote lox-stop-lox-GCaMP6f (GCaMP6ffl/fl;) mice (Jackson Lab, catalog number: 028865)
TRPV1cre mice (Jackson Lab, catalog number: 017769)
Potassium chloride (KCl) (Sigma, catalog number: P3911), store in room temperature
Dulbecco's modified eagle medium (DMEM) (Thermo Scientific, Gibco, catalog number: 11965118), store at 4 °C
Fetal bovine (FB) essence (VWR/Avantor Seradigm, catalog number: 10803-034), store at -20 °C
Penicillin–streptomycin (Corning, catalog number: 30-002-CI), store at -20 °C
Collagenase A (Sigma, catalog number: 1108879300), store at -20 °C
Dispase® II (neutral protease, grade II) (Sigma, catalog number: 4942078001), store at 4 °C
Bovine serum albumin (BSA) culture grade (Fisher Scientific/Hyclone, catalog number: SH30574.02), store at 4 °C
Phosphate buffered saline (PBS) (Thermo Scientific, Gibco, catalog number: 10010023), store at room temperature
Neurobasal medium (Thermo Scientific, Gibco, catalog number: 21103049), store at 4 °C
XenoFree B-27TM supplement (Thermo Scientific, Gibco, catalog number: A1486701), store at -20 °C
Nerve growth factor (NGF) 2.5S subunit (Thermo Scientific, Gibco, catalog number: 13257019), store at -20 °C
Glial cell line–derived neurotrophic factor (GDNF) (Peprotech, catalog number: 450-51-10), store at -20 °C
Cytosine-beta-D-arabinofuranose hydrochloride (AraC) (Alfa Aesar, catalog number: J55671), store at -20 °C
Glass Pasteur pipette (Fisher Scientific, catalog number: 13-678-20B)
DNase (Sigma, catalog number: DN25), store at -20 °C
L-glutamine (VWR, catalog number: 02-0131), store at -20 °C
Basal medium (Millipore, catalog number: SCME001), store at -20 °C
Fibrinogen (Sigma-Aldrich, catalog number: F8630-5G), store at -20 °C
Allura red AC (Sigma-Aldrich, catalog number: 458848-100G), store at room temperature
Standard extracellular solution (Boston BioProducts, catalog number: C-3030F-4L), store at 4 °C
Capsaicin (Tocris, catalog number: 0462), store at room temperature
Thrombin (Sigma-Aldrich, catalog number: T7513-100UN), store at -20 °C
Supplemented DMEM (see Recipes), store at 4 °C
Collagenase/dispase II (see Recipes), store at -20 °C
BSA 15% (see Recipes), store at -20 °C
Supplemented neurobasal (see Recipes), store at 4 °C
Supplemented neurobasal with growth factors and AraC (see Recipes)
Equipment
Protective laser goggles for 532 nm (e.g., Thorlabs, catalog number: LG3)
Laser viewing card (Thorlabs, catalog number: VRC2)
Laser (Litron Lasers, Nano S 60-30, 532 nm)
Concave lens, f = -50 mm (Thorlabs, catalog number: LC1715-A-ML)
Convex lens, f = 100 mm (Thorlabs, catalog number: LA1509-A)
Half-wave plate (Thorlabs, catalog number: WPMH05M-633). For optimal performance, use a half-wave plate tailored for 532 nm (e.g., Thorlabs, catalog number: WPH05M-532)
Rotating stage (Thorlabs, catalog number: PRM1Z8)
DC servo motor controller (Thorlabs, catalog number: TDC001)
Polarizing beam splitter (e.g., Thorlabs, catalog number: PBS25-532)
Broadband dielectric mirrors (Thorlabs, catalog number: BB1-E02)
Mechanical shutter (Thorlabs, catalog number: SH05)
K-cube solenoid controller (Thorlabs, catalog number: KSC101)
Beam splitter, 10:90 (R:T) (Thorlabs, catalog number: BSN10)
Si detector (photodiode) (Thorlabs, catalog number: DET10A)
Pyroelectric sensor (Gentec-eo, catalog number: QE12LP-S-MB)
Concave lens, f = −50 mm (Thorlabs, catalog number: LC1715-A-ML)
Convex lens, f = 150 mm (Thorlabs, catalog number: LA1433-A-ML)
UVFS beam splitter, 70:30 (R:T) (Thorlabs, catalog number: BST10R)
4× objective lens, plan achromat-NA = 0.1 (Olympus, catalog number: RMS4X)
XYZ motorized translational stage (Thorlabs, catalog numbers: PT1-Z8+MAX 201)
Two-channel APTTM stepper motor controller (Thorlabs, catalog number: BSC102)
K-cube brushed DC servo motor controller (Thorlabs, catalog number: KDC101)
Syringe pump (New Era Pump Systems Inc., catalog number: NE-1000)
High speed camera (Kron Technologies, Chronos 1.4)
LED illumination (Thorlabs, catalog number: MCWHL5)
T-cube LED driver (Thorlabs, catalog number: LEDD1B)
UVFS beam splitter, 50:50 (R:T) (Thorlabs, catalog number: BSW10R)
3D printed capillary holder (see the CAD file as Supplementary material 1) and 6.8 mm × 1.9 mm securing O ring.
Colored glass filter, 570 nm longpass (Thorlabs, catalog number: FGL570)
Achromatic lens, f = 150 mm (Thorlabs, catalog number: AC254-150-A-ML)
Kinematic fluorescence filter cube, left turning (Thorlabs, catalog number: DFM1L)
Kinematic fluorescence filter cube, light turning (Thorlabs, catalog number: DFM1)
Kinematic mirror mount for Ø1" optics (Thorlabs, catalog number: KM100)
Lens mount with retaining ring for Ø1" optics (Thorlabs, catalog number: LMR1)
Incubator, air jacketed CO2 incubator (VWR, catalog number: 10810-888)
Centrifuge, 5810R (Eppendorf, catalog number: 022628089)
Water bath (PolyScience, catalog number: WBE20A11B)
Hemocytometer (VWR, catalog number: 76299-416)
Stereomicroscope (Nikon, catalog number: SMZ-745T)
P1000 pipette (VWR, catalog number: 89079-974)
Tweezers and dissection tools (World Precision Instruments, catalog number: 504167)
Figure 1. Schematic of laser-induced side transfer (LIST). The numbering of the items corresponds to that of the Equipment section.
Software
MATLAB 2020a (MathWorks, https://www.mathworks.com/)
Procedure
Neurons harvesting and dissociation
Notes:
This procedure is used exclusively for the extraction of mouse dorsal root ganglions.
Steps 4–18 should be performed in a tissue culture hood.
Anesthetize the mouse with isoflurane (2.5%–3%) and proceed to its euthanasia by decapitation using a scissor.
Turn the mouse to the ventral side and dissect the vertebral column. See Perner and Sokol (2021) for a detailed video.
Using a stereomicroscope, harvest all the dorsal root ganglia to a 15 mL Falcon tube filled with 10 mL of ice-cold supplemented DMEM.
Centrifuge (200 × g, 5 min, room temperature) and remove the supernatant.
Add 1 mL of the prepared solution of collagenase/dispase II and incubate the cell suspension (80 min, 37 °C, mix gently every 20 min).
During the incubation, prepare the BSA gradient by first adding 2 mL of sterile PBS to a 15 mL Falcon tube and then 1 mL of 15% BSA on top dropwise.
During the incubation, prepare the glass pipettes for trituration by heating them on a flame until reaching the following diameters: first pipette: 0.8 mm; second pipette: 0.3 mm; third pipette: 0.15 mm.
Centrifuge (200 × g, 5 min) the tube containing the cells and the collagenase/dispase II solution and gently remove the supernatant using a 1 mL pipette.
Add 10 mL of supplemented DMEM (room temperature) and centrifuge (200 × g, 5 min)
Add 1 mL of supplemented DMEM and 25 μL of DNase.
Using a pipette gun, triturate the cell solution by aspirating and ejecting slowly the DRG neurons in solution 15 times up and down for each pipette size, starting with the larger. Avoid bubbling by ejecting the solution into the wall of the tube.
Pipette the triturated ganglia suspension on the side of the tube with the BSA gradient.
Centrifuge (200 × g, 12 min, room temperature) the neuron-containing BSA gradient.
Note: Set the acceleration and deceleration of the centrifuge to the minimum speed.
After centrifugation, the neurons will be at the bottom of the tube, while the cell debris will be in the BSA gradient.
Gently remove all the supernatant using a P1000 pipette, starting with the debris.
Resuspend the cells in 500 µL of supplemented neurobasal with growth factors and AraC.
Filter the suspension with a 100 µm filter to remove the remaining cell debris, washing the filter with 1 mL of supplemented neurobasal medium.
Count round cell bodies that are approximately 10 µm in diameter using a hemocytometer. You should get >40,000–60,000 cell bodies per one adult mouse.
Centrifuge the cells and resuspend in the bio-ink keeping a concentration of approximately 106 DRG neurons per milliliter.
Bio-ink preparation
Note: The concentration of the cells in the bio-ink can be adjusted to accommodate the desired number of cells per deposited drop. Bio-ink preparation is performed under sterile conditions.
For 40,000 DRG neurons, resuspend in 20 µL of supplemented neurobasal with growth factors (NGF, GDNF) and AraC, add 16 µL of fibrinogen 5 mg/mL (final concentration 2 mg/mL), and 4 µL of Allura red AC (laser absorber) 100 mM (final concentration 10 mM).
Pipette the bio-ink to uniformly distribute the cells.
Printing substrate preparation
Note: Printing substrate preparation is performed under sterile conditions.
Dissolve 5 mg/mL of fibrinogen from bovine plasma in warm basal medium at 37 °C.
Shake very gently by hand until the fibrinogen is dissolved.
Filter the solution (0.45 µm filter).
Place a round cover glass on a microscope slide. Place the assembly in a 60 mm Petri dish.
Spread uniformly 5 µL of thrombin (final concentration 4.8 U/mL) on the round cover glass.
Spread uniformly 100 µL of fibrinogen solution on the thrombin-coated cover glass.
Note: Spreading the solution on a 13 mm disk will result in an approximately 0.75 mm thick fibrin layer.
Keep the samples at room temperature for 20–25 min to allow gelation.
Prepare the laser setup for bio-printing
Wear protective laser goggles.
Turn on the laser and set the repetition rate to 20 Hz and the energy to approximately 85% of its maximum power.
Rotate the half-wave plate to adjust the power of the laser beam so that it is clearly visible on the laser viewing card.
Use the viewing card to verify that the laser beam passes through the central part of the optical elements of the setup (i.e., indicated with numbers 4, 5, 6, 7, 9, 10, 11, 13, 14, 15, 16, 17, 18 and in Figure 1).
If the setup is misaligned, proceed with laser alignment correction maneuvers. This step requires prior experience on laser alignment. Basic instructions can be found here: https://www.youtube.com/watch?v=qzxILY6nOmA
Measure the laser energy at the sample level by placing the pyroelectric sensor after the objective lens.
Note: Ensure that the beam covers at least 80% of the sensor. To avoid any damage to the sensor, do not place it at the focal point of the objective lens or close to it.
Measure the laser energy of the sampled beam (see element 15 in Figure 1).
Use the measurements obtained in steps 6 and 7 to calculate a correlation coefficient between the sampled laser beam energy and laser beam energy at the sample (capillary). You may assume this correlation coefficient constant for a single experimental session.
Capillary positioning and alignment
Connect the glass square capillary to the tube and secure it at the holder using the O-ring (Figure 2a).
Position the capillary in front of the objective (Figure 2b).
Use the translation stage and the camera to position the capillary at the focal point of the imaging system.
Fine tune the position of the capillary to focus on its front outer wall (i.e., the side facing the objective lens).
Note: The imaging and laser focusing components of the setup shown in Figure 1 must be set to confocality.
Identify the laser spot in the camera view (Figure 2c).
Adjust the position of the capillary holder in the y and z axes so that the laser spot is located 500 μm far from the capillary distal end and at the center of the capillary wall.
Displace the capillary 300 μm in the x axis towards the objective lens.
Note: After completing steps 4–7, the focal point of the laser beam is set at the center of the capillary and at 500 μm from its distal end (Figure 2d).
Figure 2. Overview of capillary filling, positioning, and alignment procedures. (A) Picture showing a capillary mounted on a capillary holder and connected to a syringe via a tube. (B) Picture showing the placement of the capillary in reference to the objective. (C) Side view of the capillary and substrate. (D) Schematic showing the desired alignment of the capillary in reference to the laser beam.
Printing protocol
Turn on the laser, the computer, the syringe pump, the mechanical shutter, and the translation stage controller.
Run the laser at 20 Hz repetition rate at >90% of its maximum power for at least 5 min.
Considering the correlation coefficient (see step 8 in section D), set the laser energy to 120 μJ at the sample level (capillary) by rotating the half wave plate.
Run the MATLAB algorithm that controls the different components of the bioprinting setup (see Supplementary material 2).
Use the graphical user interface (GUI) to
Set the shutter opening time to 50 ms.
Set the speed and acceleration of the translation stage to 10 mm/s and 5 mm/s2, respectively.
Define a printing pattern (e.g., an array of individual droplets separated by a 500 μm gap).
Load approximately 40–100 μL of freshly prepared bio-ink (see section B) to the tube using a pipette (Figure 3a).
Connect the tube to a syringe pump (Figure 3b) and pump gently to move the bio-ink up to the capillary distal end.
Stop the pump when the bio-ink level has reached the distal end of the capillary.
Note: This step requires some practice to avoid overflow because the bio-ink advances rapidly once transitioning from the tube to the capillary.
Place the cover glass containing the printing substrate on the XYZ translation stage (see Figure 4).
Use the sample translation stage to set the distance between the capillary tip and the top of the gel at 500–700 μm (see Figure 4).
Run the GUI to start the printing.
Videos 1 and 2 show the LIST bioprinter setup and the bioprinting process.
Figure 3. Bio-ink loading steps (A) Injection of the bio-ink to the tube and (B) connection to a syringe pump.
Figure 4. Close-up photo of a ready-to-print experimental setup.
Video 1. The LIFT bioprinting setup.
Video 2. The LIFT bioprinting process.
Once the printing process is completed, remove the capillary holder, capillary, and tubing.
Rinse the tube and capillary with 70% ethanol (approximately 6 mL) and water (approximately 6 mL) and dry them with filtered compressed air.
Store the capillary and tube in a sterile environment.
Post printing processing
Place the cover glass on a 12-well plate and place in an incubator for 20 min.
Rinse the cover glass twice with 1 mL of pre-warmed (37 °C) neurobasal medium.
Add 2 mL of supplemented neurobasal with growth factors and AraC (37 °C) and put back in the incubator for 48 h.
Use a microscope to observe the samples and to verify successful printing of individual DRG-containing drops (see Figure 5).
Figure 5. Low (A) and high (B) magnification microscopy images of printed droplets containing DRG neurons (1 h after printing).
Calcium imaging in printed DRG neurons
Calcium influx imaging can be used to test DRG neurons for responsiveness to ligands of ion channel receptors.
Print dissociated DRG neurons from TRPV1cre::GCaMP6ffl/wt mice [using the methodology described above, mice were generated by crossing homozygote lox-stop-lox-GCaMP6f (GCaMP6ffl/fl;) with TRPV1cre].
After 48 h in culture, transfer the coverslips containing the printed neurons to a 35 mm glass bottom dish.
Wash the cells three times with 1 mL of standard extracellular solution (SES, 145 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 10 mM glucose, 10 mM HEPES, pH 7.5).
Keep the cells in 2 mL of SES.
Transfer the dish to a microscope.
Identify a neuron-containing drop and record the baseline fluorescence intensity (GFP channel) (see Figure 6a).
Using barrels, flow (30 s) a solution of 1 µM capsaicin (TRPV1 channel agonist) and wash (210 s) with SES (see Figure 6b for typical response).
Flow (30 s) a solution of 50 mM KCl (positive control) and wash (210 s) with SES.
Figure 6. Representative imaging of calcium influx in printed DRG neurons from TRPV1cre::GCaMP6ffl/wt mice (A) before and (B) after exposure to capsaicin (1 μM; 30 s).
Notes
The cell type and density, as well as the type and concentration of the biological active components of the bio-ink, can affect the printing process. LIST printing of bio-ink compositions different from the one used in this protocol may require additional investigation to determine the optimal printing energy (120 μJ for the bio-ink composition used here). Printing of high viscosity bio-inks will require higher energy. One should experiment by gradually increasing the energy until printing is achieved.
Creating bubbles in the capillary requires sufficient absorption of the laser energy by the bio-ink. For this purpose, a food dye (Allura Red AC) is added to the bio-ink before printing. The dye absorbs the laser energy resulting in cavitation. After printing, the food dye is rinsed. Yet, cells are exposed to the dye, and this is one of the limitations of LIST. One should always verify that the dye is not cytotoxic if a new cell type is used. Alternative dyes or light-absorbing additives can be used to replace Allura Red AC if they present strong absorption at 532 nm. The optimal printing energy will decrease with the increase of the absorption coefficient of those materials.
Before loading the cell in the tube, this must be inspected for residual liquid drops. Those drops cause discontinuity in the bio-ink flow and thus irregular printing.
In the capillary alignment process, one should image its front wall (i.e., the wall facing the objective lens). This is a quite challenging step. One can add a mark at the front wall of the capillary using a pen to facilitate focusing.
With time, cells tend to accumulate in the capillary opening due to gravity. This causes non-uniform distribution of cells in the printed pattern. To mitigate this effect, use the pump to apply a few withdraw/infuse cycles to mix the bio-ink.
Recipes
Supplemented DMEM
Sterile DMEM supplemented with FB essence (10%), penicillin (100 I.U.), and streptomycin (100 µg/mL). Store at 4 °C for up to one week.
Collagenase/dispase II
Sterile PBS supplemented with collagenase A (1 mg/mL) and dispase II (2.4 U/mL). Aliquot and store at -20 °C for up to three months.
BSA 15%
Dilute BSA in sterile PBS to a final concentration of 15%. Store 1 mL aliquots at -20 °C for up to six months.
Supplemented neurobasal
Sterile neurobasal supplemented with penicillin (100 I.U.), streptomycin (100 µg/mL), XenoFree B-27TM (1×), and L-glutamine (200 μM). Store at 4 °C for up to two weeks.
Supplemented neurobasal with growth factors and AraC
Add NGF (50 ng/mL), GDNF (2 ng/mL) and AraC (10 μM) to supplemented neurobasal (recipe 4). Prepare fresh.
Acknowledgments
This research was funded by the Natural Sciences and Engineering Research Council of Canada (Discovery grant RGPIN-2018-06767; CB), the Canadian Foundation for Innovation (ST, #37439), and the Canada Research Chair program (ST, #950-231859). CB is the recipient of a Junior II salary award from the Fonds de la Recherche en Santé du Québec (#312263). KR holds postdoctoral fellowships from the Fonds de Recherche du Québec Nature et technologies (FRQNT), the Fonds de recherche en ophtalmologie de l’Université de Montréal and the Centre Interdisciplinaire de Rcherche sur le Cerveau et L’apprentissage (CIRCA). HEO was the recipient of a PhD scholarship from the FRQNT. This protocol is derived from two recent publications from our group (Ebrahimi Orimi et al., 2020; Roversi et al., 2021).
Competing interests
The authors declare no conflict of interest.
Ethics
The Institutional Animal Care and Use Committees of Université de Montréal (CDEA #22-054, #22-053) approved all animal procedures.
References
Ebrahimi Orimi, H., Hosseini Kolkooh, S. S., Hooker, E., Narayanswamy, S., Larrivee, B. and Boutopoulos, C. (2020). Drop-on-demand cell bioprinting via Laser Induced Side Transfer (LIST). Sci Rep 10(1): 9730.
Kang, H. W., Lee, S. J., Ko, I. K., Kengla, C., Yoo, J. J. and Atala, A. (2016). A 3D bioprinting system to produce human-scale tissue constructs with structural integrity. Nat Biotechnol 34(3): 312-319.
Knowlton, S., Anand, S., Shah, T. and Tasoglu, S. (2018). Bioprinting for Neural Tissue Engineering. Trends Neurosci 41(1): 31-46.
Perner, C. and Sokol, C. L. (2021). Protocol for dissection and culture of murine dorsal root ganglia neurons to study neuropeptide release. STAR Protoc 2(1): 100333.
Roversi, K., Ebrahimi Orimi, H., Falchetti, M., Lummertz da Rocha, E., Talbot, S. and Boutopoulos, C. (2021). Bioprinting of Adult Dorsal Root Ganglion (DRG) Neurons Using Laser-Induced Side Transfer (LIST). Micromachines (Basel) 12(8).
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4,528 | https://bio-protocol.org/en/bpdetail?id=4528&type=0 | # Bio-Protocol Content
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Peer-reviewed
Assay for Protealysin-like Protease Inhibitor Activity
IB Igor M. Berdyshev
MK Maria A. Karaseva
ID Ilya V. Demidyuk
Published: Vol 12, Iss 19, Oct 5, 2022
DOI: 10.21769/BioProtoc.4528 Views: 845
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Original Research Article:
The authors used this protocol in International Journal of Biological Macromolecules Feb 2021
Abstract
Here, we present the first quantitative method for the activity analysis of protealysin-like protease (PLP) inhibitors. This approach is based on a previously developed method for protealysin activity determination by hydrolysis of internally quenched fluorescent peptide substrate 2-aminobenzoyl-L-arginyl-L-seryl-L-valyl-L-isoleucyl-L-(ϵ-2,4-dinitrophenyl)lysine. In this protocol, we significantly reduced enzyme concentration and introduced some minor modifications to decrease variation between replicates. The protocol was validated using emfourin, a novel proteinaceous metalloprotease inhibitor. Data obtained demonstrates that the developed assay method is an affordable approach for characterizing and screening various PLP inhibitors.
Graphical abstract:
Keywords: Internally quenched fluorescent peptide substrate Metalloprotease activity Proteinaceous protease inhibitor Emfourin Protealysin
Background
Protealysin-like proteases (PLPs) are a large group of zinc-containing metalloproteases belonging to the M4 family, according to the MEROPS database (www.ebi.ac.uk/merops) (Demidyuk et al., 2008, 2013). The interest in PLPs is primarily due to their possible involvement in bacterial pathogenesis, as they seem to be involved in bacterial invasion into eukaryotic cells, suppression of immune defense of some animals, and destruction of plant cell walls (Tsaplina et al., 2012, 2020; Demidyuk et al., 2013; Feng et al., 2014; Eshwar et al., 2018; Khaitlina et al., 2020).
We have previously developed a method for activity determination of protealysin (PLN), the prototype of PLP, from Serratia proteamaculans based on the hydrolysis of internally quenched fluorescent peptide substrate 2-aminobenzoyl-L-arginyl-L-seryl-L-valyl-L-isoleucyl-L-(ϵ-2,4-dinitrophenyl)lysine [Abz-RSVIK(Dnp)]. The proposed substrate was advantageous for quantitative activity analysis of PLN, as well as other M4 peptidases (Karaseva et al., 2019). Recently, we discovered emfourin (M4in) from S. proteamaculans, a novel potent slow-binding competitive proteinaceous inhibitor of PLN. To characterize the inhibition activity of M4in, we had to modify the PLN activity assay. Firstly, we significantly reduced the enzyme concentration and, in addition, introduced some minor modifications to decrease variation between replicates (Chukhontseva et al., 2021). Using the modernized protocol in the M4in study has shown that this approach is suitable for screening and characterizing PLP inhibitors.
Since Abz-RSVIK(Dnp) can be used to determine the activity of not only PLN but also other M4 family proteases (Karaseva et al., 2019), the proposed method can be adapted to determine the activity of inhibitors of various representatives of this family. Metalloproteases belonging to the M4 family are produced by significant human pathogens, such as Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis, Burkholderia cenocepacia, Enterococcus faecalis, Legionella pneumophila, Clostridium perfringens, and several pathogenic Vibrio species; their inhibitors, in the face of growing antibiotic resistance in bacteria, are considered as potential drug targets (Adekoya and Sylte, 2009). Thus, this method can be useful in the search for new antibacterial agents.
Materials and Reagents
Microcentrifuge tubes (1.5 mL) for reagent dilutions (SSI, catalog number: 1260)
Black 96-well polystyrene flat bottom microwell plate (Corning, catalog number: 3915)
0.20 μm membrane filter (Corning, catalog number: 431219)
Protealysin (PLN) was produced in E. coli and purified as described in Gromova et al. (2009). Although PLN was used in the development of the protocol, other M4 family proteases can also be used. In particular, we successfully implemented the protocol without any modification with thermolysin from Bacillus thermoproteolyticus (Serva, catalog number: 36015)
Emfourin (M4in) was produced in E. coli and purified as described in Chukhontseva et al. (2021). The activity of other proteinaceous or low-molecular-weight inhibitors of M4 family peptidases can also be determined using the protocol
Substrate: 2-aminobenzoyl-L-arginyl-L-seryl-L-valyl-L-isoleucyl-L-(ϵ-2,4-dinitrophenyl)lysine [Abz-RSVIK(Dnp)] (Peptide 2.0)
Tris(hydroxymethyl)aminomethane (Tris) (Sigma-Aldrich, catalog number: T1503)
Tris(hydroxymethyl)aminomethane hydrochloride (Tris-HCl) (Sigma-Aldrich, catalog number: T3253)
Dimethyl sulfoxide (DMSO) (MP Biomedicals, catalog number: 0219605525)
Assay buffer (see Recipes)
Substrate stock solution in DMSO (see Recipes). Can be stored at -20 °C without any loss in substrate properties; however, it is necessary to minimize freeze-thaw cycles
Protease (PLN) solution (see Recipes). Prepare immediately before analysis; do not store
Inhibitor (M4in) solution (see Recipes). Prepare immediately before analysis; do not store
Equipment
Desktop microcentrifuge (Eppendorf, Micro Centrifuge 5415)
Solid state laboratory thermostat for microcentrifuge tubes (DNA-technology, Thermit)
Temperature-controlled microplate reader capable of measuring fluorescence kinetics (BMG, CLARIOstar Plus)
Software
GraphPad Prism 8.0 (GraphPad Software)
Procedure
Prepare assay buffer and substrate and protein (PLN and M4in) stock solutions.
Add 120 μL of the substrate solution into the wells of a black 96-well plate (see Note 1).
Incubate the plate in a microplate reader at 37 °C for 10 min (see Note 2).
Remove 30 µL of the substrate solution from each well.
Preheat the assay buffer and protein stock solutions in a thermostat at 37 °C.
Add inhibitor solution or assay buffer into the wells according to Table 1:
15 μL of inhibitor solution for inhibition test.
15 μL of assay buffer for enzyme activity control (see Note 3).
30 μL of assay buffer for substrate control (see Note 4).
Incubate the mixtures in the reader at 37 °C for 1 min.
Start the reaction in inhibition test and enzyme activity control with 15 μL of PLN solution (Table 1). Immediately after adding the enzyme, mix the solutions once with a micropipette set at 80 μL. This operation reduces possible signal distortions in the beginning of the reaction.
Place the plate into the reader at 37 °C and record time-related fluorescence changes every 10 s for 15 min, at the excitation and emission wavelengths of 320 and 420 nm, respectively (see Note 5).
Transfer the substrate solution from the substrate control well into a spectrophotometer cell to measure the optical density at 365 nm. Use the concentration calculated from the obtained optical density as the initial substrate concentration in the hydrolysis reactions (see Note 6).
Table 1. Composition of the assay mixtures
Sample Reagent Concentration Volume (μL)
In the reaction mixture In the added solution
Substrate control Substrate 30 or 90 μM 40 or 120 μM 90
Assay buffer 30
Total: 120
Enzyme activity control Substrate 30 or 90 μM 40 or 120 μM 90
Assay buffer 15
Protease 50 pM 400 pM 15
Total: 120
Inhibition test Substrate 30 or 90 μM 40 or 120 μM 90
Inhibitor 0.5–3.5 nM 4–28 nM 15
Protease 50 pM 400 pM 15
Total: 120
Data analysis
Several independent measurements were made for each pair of substrate and M4in concentrations. The progress curves were plotted and analyzed using GraphPad Prism 8.0 software. Detailed information of curve analyses can be found in the original research article (Chukhontseva et al., 2021). Characteristic progress curves are represented as an example (Figure 1).
Figure 1. Emfourin-mediated inhibition of the Abz-RSVIK(Dnp) hydrolysis catalyzed by protealysin. The Abz-RSVIK(Dnp) concentrations are 30 (A) and 90 (B) μM; the emfourin concentrations are 0, 0.5, 1, 1.5, 2, 2.5, and 3.5 nM; the protealysin concentration is 50 pM. The reactions were performed at 37 °C. Abz-RS (2-aminobenzoyl-L-arginyl-L-serin) is the product of the substrate hydrolysis. Conversion of the relative fluorescence units into the product concentration was made using calibration curves, as described previously (Karaseva et al., 2019).
Notes
As in the previously described PLN activity assay, in the inhibition assay the reactions were started by the enzyme addition (Chukhontseva et al., 2021). However, here we manage to significantly lower the enzyme concentration in the assay by adjusting the photomultiplier tube gain. The gain setting controls the amplification of the photomultiplier when converting fluorescent light into electrical current. We were able to conduct measurements using even lower enzyme concentrations (Figure 2). However, decreased concentrations lead to low signal and, consequently, decreased signal/noise ratio.
Figure 2. Kinetics of Abz-RSVIK(Dnp) hydrolysis by protealysin at different concentrations. The protealysin concentrations are 0, 25, 50, 100, 250, 500, and 2,500 pM; the Abz-RSVIK(Dnp) concentration is 30 μM. The reactions were performed at 37 °C. Abz-RS (2-aminobenzoyl-L-arginyl-L-serin) is the product of the substrate hydrolysis. Conversion of the relative fluorescence units into the product concentration was made using calibration curves, as described previously (Karaseva et al., 2019).
The substrate adsorption on microplates is the main reason for this operation. We previously studied the kinetics of substrate adsorption on microplates and observed that after 10 min of incubation the substrate concentration did not change during the reaction time (Karaseva et al., 2019).
Enzyme activity control was carried out to check the protease activity. This control was made every time a new solution was prepared and between independent measurements.
The main aim of the substrate control was to determine the substrate concentration in the reaction mixture. The substrate control was also necessary to prove that background noise was low and that there was no spontaneous substrate hydrolysis in the absence of the enzyme. Our further attempts to lower enzyme concentration failed because of high background noise of the substrate, which resulted in signal variations.
Here, the delay between enzyme addition and the start of the measurement was approximately 20 s.
Substrate stock solution preparation and further dilution were done in a way that DMSO concentration did not exceed 2.5% in the final reaction mixture. In this concentration range, DMSO has no significant effect on the hydrolysis of Abz-RSVIK(Dnp) by protealysin (Figure 3). Substrate concentrations up to 130 μM could be used in the reaction mixture, as described previously (Karaseva et al., 2019). Substrate concentration dependency on the reaction rate at 50 pM of enzyme is shown in Figure 4.
Figure 3. Effect of DMSO on Abz-RSVIK(Dnp) hydrolysis rate by protealysin. The Abz-RSVIK(Dnp) concentration is 16 μM; the protealysin concentration is 50 pM. The reactions were performed at 37 °C.
Figure 4. Michaelis–Menten saturation curve showing the relation between Abz-RSVIK(Dnp) concentration and the protealysin catalyzed reaction rate. The protealysin concentration is 50 pM. The reactions were performed at 37 °C.
Recipes
Assay buffer
50 mM Tris-HCl, pH 7.4
Mix 1.653 g of Tris-HCl and 0.242 g of Tris with 240 mL dH2O
Adjust pH to 7.4 with HCl
Add dH2O to 250 mL
Filter through a 0.20 μm membrane filter
Substrate stock solution
Dissolve 2 mg of substrate in 400 μL of DMSO. To obtain the required substrate concentrations, dilute the stock solution in the assay buffer. Centrifuge the resulting substrate solution at 10,000 × g for 10 min but do not transfer it to a new tube since substrate can absorb on plastic (Karaseva et al., 2019). Determine the substrate concentration by the absorbance of 2,4-dinitrophenyl at 365 nm using the extinction coefficient ϵ365nm = 1,7300 M1 cm-1 (Johanning et al., 1998). Keep substrate solution at room temperature during handling, prepare immediately before analysis, and do not store.
PLN and M4in solution
Take a small quantity of lyophilized protein (PLN or M4in) on the end of a pipette tip and dissolve in 200 μL of the assay buffer. Centrifuge the solution at 10,000 × g for 10 min and transfer to a new tube to remove undissolved fraction. Determine the concentration of the resulting solution by absorbance at 280 nm using the extinction coefficients for PLN (ϵ280nm = 52,370 M1cm1) and M4in (ϵ280nm = 10,810 M1cm1) (Chukhontseva et al., 2021; Karaseva et al., 2019). To obtain the required protein concentrations, dilute the solution in the assay buffer. Keep protein solutions at room temperature during handling.
Acknowledgments
The work was carried out using the equipment of the Center of Cellular and Gene Technology of the Institute of Molecular Genetics of the National Research Centre “Kurchatov Institute.” This work was supported by the Russian Science Foundation (project no. 22-24-00135). This protocol was adapted from previous work (Chukhontseva et al., 2021).
Competing interests
The authors declare no conflict of interest.
References
Adekoya, O. A. and Sylte, I. (2009). The thermolysin family (M4) of enzymes: therapeutic and biotechnological potential.Chem Biol Drug Des 73(1): 7-16.
Chukhontseva, K. N., Berdyshev, I. M., Safina, D. R., Karaseva, M. A., Bozin, T. N., Salnikov, V. V., Konarev, P. V., Volkov, V. V., Grishin, A. V., Kozlovskiy, V. I., et al. (2021). The protealysin operon encodes emfourin, a prototype of a novel family of protein metalloprotease inhibitors. Int J Biol Macromol 169: 583-596.
Demidyuk, I. V., Gasanov, E. V., Safina, D. R. and Kostrov, S. V. (2008). Structural organization of precursors of thermolysin-like proteinases.Protein J 27(6): 343-354.
Demidyuk, I. V., Gromova, T. Y. and Kostrov, S. V. (2013). Protealysin. Rawlings, N. D. and Salvesen, G. (Eds.) Handbook of Proteolytic Enzymes. 3rd edition. Academic Press, 507-602.
Eshwar, A. K., Wolfrum, N., Stephan, R., Fanning, S. and Lehner, A. (2018). Interaction of matrix metalloproteinase-9 and Zpx in Cronobacter turicensis LMG 23827(T) mediated infections in the zebrafish model. Cell Microbiol 20(11): e12888.
Feng, T., Nyffenegger, C., Hojrup, P., Vidal-Melgosa, S., Yan, K. P., Fangel, J. U., Meyer, A. S., Kirpekar, F., Willats, W. G. and Mikkelsen, J. D. (2014). Characterization of an extensin-modifying metalloprotease: N-terminal processing and substrate cleavage pattern of Pectobacterium carotovorum Prt1.Appl Microbiol Biotechnol 98(24): 10077-10089.
Gromova, T. Y., Demidyuk, I. V., Kozlovskiy, V. I., Kuranova, I. P. and Kostrov, S. V. (2009). Processing of protealysin precursor.Biochimie 91(5): 639-645.
Johanning, K., Juliano, M. A., Juliano, L., Lazure, C., Lamango, N. S., Steiner, D. F. and Lindberg, I. (1998). Specificity of prohormone convertase 2 on proenkephalin and proenkephalin-related substrates.J Biol Chem 273(35): 22672-22680.
Karaseva, M. A., Chukhontseva, K. N., Lemeskina, I. S., Pridatchenko, M. L., Kostrov, S. V. and Demidyuk, I. V. (2019). An Internally Quenched Fluorescent Peptide Substrate for Protealysin. Sci Rep 9(1): 14352.
Khaitlina, S., Bozhokina, E., Tsaplina, O. and Efremova, T. (2020). Bacterial Actin-Specific Endoproteases Grimelysin and Protealysin as Virulence Factors Contributing to the Invasive Activities of Serratia.Int J Mol Sci 21(11): 4025.
Tsaplina, O. A., Demidyuk, I., Artamonova, T., Khodorkovsky, M. and Khaitlina, S. (2020). Cleavage of the outer membrane protein OmpX by protealysin regulates Serratia proteamaculans invasion. FEBS Lett 594(19): 3095-3107.
Tsaplina, O. A., Efremova, T., Demidyuk, I. and Khaitlina, S. (2012). Filamentous actin is a substrate for protealysin, a metalloprotease of invasive Serratia proteamaculans. FEBS J 279(2): 264-274.
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Drug Discovery > Drug Screening
Biochemistry > Protein > Activity
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4,529 | https://bio-protocol.org/en/bpdetail?id=4529&type=0 | # Bio-Protocol Content
Improve Research Reproducibility
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Peer-reviewed
First-line Evaluation of Sperm Parameters in Mice (Mus musculus)
GM Guillaume Martinez
Published: Vol 12, Iss 20, Oct 20, 2022
DOI: 10.21769/BioProtoc.4529 Views: 1566
Reviewed by: Chiara Ambrogio Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in eLIFE Apr 2022
Abstract
Infertility has become a major public health problem, with a male factor involved in about half the cases. Mice are the most widely used animal model in reproductive biology research laboratories, but changes in sperm parameters in mice can be subtle and, in the absence of official guidelines, it is important that analyses are carried out in a strict and reproductive manner. This protocol successively details the different steps required to obtain spermatozoa under good conditions, the measurement of sperm motility using a Computer Assisted Sperm Analysis System (CASA) device, the calculation of sperm concentration in the epididymides using a sperm counting cell, and the examination of sperm morphology. The combination of these assays provides an overview of the basic sperm parameters in mice. This is both a diagnostic and a decision-making tool for researchers to orient their scientific strategy according to the observed abnormalities.
Keywords: Sperm Mouse CASA Sperm morphology Sperm motility Sperm count
Background
Mice are the most widely used model organism in laboratories around the world because of their relatively simple breeding conditions, short reproduction cycles, and physiology close to humans. Several fields of science use mice as model organisms, and the advent of genetically manipulated mouse breeding has further expanded the possibilities of this model (Olson et al., 2018; Ito et al., 2018; Gill et al., 2020). For example, CRISPR technology now allows the efficient generation of mouse knock-out models to functionally validate newly identified genetic mutations in a wide range of diseases (Abbasi et al., 2017; Hochheiser et al., 2018; Zhao et al., 2020), including infertility (Beurois et al., 2020; Touré et al., 2021).
Medically assisted reproduction techniques are implemented in the murine model (Stein et al., 2010), establishing it as a model of choice for reproductive biologists (Giritharan et al., 2010), for whom the analysis of sperm parameters became essential a long time ago (Osterloh et al., 1983; Tessler et al., 1985). These techniques have since been adopted by a large portion of scientists who use them for different purposes, such as the evaluation of the impact of diseases and/or toxic substances on reproduction (Sampannang et al., 2020; Abdollahi et al., 2021) and the curative and/or protective effects of molecules against induced deleterious effects (Feyli et al., 2017; Moghadam et al., 2021; Shahedi et al., 2021). Other noteworthy examples include the analysis of nutrition influence on sperm parameters (Zhao et al., 2017; Gómez-Elías et al., 2019) and their heritability (Crisóstomo et al., 2021), or the potential of cryobiology for reproduction (Sztein et al., 2018).
However, this model suffers from limitations in its transfer to humans. One of the drawbacks of the mouse model is that mice have a much more efficient spermatogenesis and much higher fertility than humans—already the primate with the worst known sperm parameters (Martinez and Garcia, 2020). This implies that even subtle defects in mouse sperm parameters may eventually translate into a much more deleterious impact in humans (Martinez et al., 2022). That is why descriptions of animal reproductive phenotypes are becoming increasingly sophisticated and standardized, with each specialty creating its own phenotyping framework (Houston et al., 2021). Here, we propose a rapid, accessible, and reproducible protocol for the first-line assessment of sperm parameters in mice, which provides the researcher with a first diagnosis to guide their scientific strategy and the framework of their future experiments.
This protocol sequentially describes the surgical steps of sperm recovery, sperm motility measurement using a Computer Assisted Sperm Analysis System (CASA) device, sperm concentration measurement, and the examination of sperm morphology.
Materials and Reagents
Petri dish polystyrene (Falcon, catalog number: 351008)
Box with instruments for minor surgery (LD Medical, catalog number: 01748)
Needles, MicrolanceTM 3, 18 G (Beckton Dickinson, catalog number: 304622)
Microtube safety lock 2 mL Clearline (Dutscher, catalog number: 2519649)
SureOne specialty tips (Fisherbrand, catalog number: 02-707-464)
Counting chamber Leja 100 μm (Leja Products B.V., Gynemed, catalog number: SC100-01-02-A)
Thoma Cell Counting chamber (VWR, catalog number: HECH40447702)
Tubes 15 mL (Falcon, catalog number: 352096)
SuperFrost PlusTM adhesion slides (Epredia, catalog number: J7800AMNZ)
Soda lime glass staining troughs with lid (Brand, catalog number: 472200)
EUKITT® classic 100 mL flask (Dutscher, catalog number: 124103)
Mice (Charles River Laboratories)
M2 medium (Sigma-Aldrich, catalog number: M7167-50ML)
Ethanol 96% (Carlo Erba, Labelians, catalog number: CE529141)
Sterile water (Versylene, Fresenius)
Dulbecco′s phosphate buffered saline (PBS) (Sigma-Aldrich, catalog number: D8537-500ML)
Papanicolaou′s solution 1a Harris′ hematoxylin solution (Sigma-Aldrich, catalog number: 1092530500)
Shorr staining solution stain for histology (Sigma-Aldrich, catalog number: 1092750500)
Ammonia solution 25% (Sigma-Aldrich, catalog number: 105432)
Immersion oil for microscopy type N (Nikon, MXA22166)
75% ethanol (see Recipes)
50% ethanol (see Recipes)
Ethanol ammoniacal (see Recipes)
Equipment
Surgical scissors
Incubator binder model CB56 (Binder, catalog number: 9640-0006)
Binocular loupe (Nikon, catalog number: SM2800N)
IKA dry block heater 3 (IKA, catalog number: 0004025300)
Computer Assisted Sperm Analysis System (CASA) CEROS II (Hamilton Thorne Research, IMV Technologies, catalog number: 024905) with its heated blade holder
Centrifuge Sorvall ST 16R (ThermoFisher, catalog number: 10688725)
Nikon Eclipse 80i microscope equipped with a Nikon DS-Ri1 camera with NIS-Elements software and 40× and 100× objectives
Procedure
Notes:
The first two steps of this protocol (sperm recovery and motility analysis) are performed under time and temperature constraints. Sperm motility is a physiological phenomenon that evolves over time and is impacted by the temperature of the environment. To obtain reproducible motility data, the time between sperm extraction and motility measurement has to be the same for all individuals in the study (optimal time would be between 15 and 20 min), and a temperature of 37 °C has to be maintained throughout. As concentration and morphology measurements are not impacted by these factors, they can then be carried out comfortably afterwards, without restrictions.
When handling sperm, always use a cut or wide-opening pipette tip (see Figure 1). The use of normal tips induces deleterious effects on the motility and morphology of spermatozoa.
Figure 1. Use wide-opening pipette tips
Before beginning the procedure
Prepare Petri dishes (two per individual, one per epididymis) with 1 mL of M2 medium and one tube with 5 mL of M2 medium. Heat them to 37 °C for at least 2 h before starting the experiment.
Prepare the dissection field.
Preheat the heating block to 37 °C and place 2 mL microtubes in it (see Figure 2).
Figure 2. Suggested organization of the heating block
Connect the heated blade holder of the CASA.
Turn on the computer, start the CASA software (Figure 3), and enter the sample numbers if appropriate.
Note: The sperm analysis software must have the animal analysis module and be configured according to its user manual. We provide the parameters to be used for mice sperm analysis in Table 1, but we will not go over all the basic configuration elements. For this, please refer to the CEROS II manual.
Table 1. Settings for CASA analysis
Parameters Value Parameters Value
acquisition rate 60 Hz low static–intensity gate 0.5
number of frames 45 high static–intensity gate 1.3
minimum contrast 50 minimum elongation gate 0
minimum cell size 5 maximum elongation gate 87
low static-size gate 0.3 magnification factor 0.7
high static-size gate 1.95
motile sperm VAP >1 progressive motility VAP >30 + STR >70
Figure 3. Screenshot of the software window
Sperm recovery
Sacrifice the animal according to the procedures established in your country and validated by your local ethics committees.
Note: To obtain reproducible and exploitable data, all animals in the same study should be sacrificed at the same age (we recommend between 10 and 12 weeks for an evaluation of the reproductive function in the mature male).
Immediately put the animal on its back on a sterile surgical field and disinfect the abdominal and genital area with ethanol.
Note: Simply spray or apply ethanol with a sterile compress.
Use surgical scissors to make a horizontal skin incision from one lumbar region to the other (Figure 4A), and a large vertical incision through the hypogastric region to the pelvis region (Figure 4B).
Expose the organs by incising vertically through the abdominal muscle wall (Figure 4C).
Note: A quick check will allow you to spot unexpected flagrant anomalies such as a situs invertus.
Locate (Figure 4D) and pull upward with surgical clamps the fat deposits located on each side of the pelvic fossae to elevate and expose the testicles (Figure 4E).
Note: Be careful not to puncture the bladder.
Figure 4. Sequence of surgical procedures for exposure of reproductive organs
Locate the different structures of the reproductive tract from the testis (Figure 5A). Start with the head of the epididymis visible on the testicle and then proceed to the body, tail, and then the efferent canal.
Isolate the tail of the epididymis by incising at one millimeter past the tail-canal junction distally (Figure 5B) and at the body-tail junction proximally (Figure 5C), and place it immediately in the pre-warmed M2 medium in Petri dish.
Note: Optimal time for steps 1–7 is less than 10 min.
Figure 5. Sequence of surgical procedures for epididymal tail isolation with indication of testis (asterisk), epididymal head (cross), and tail (arrow)
Dissect the epididymis with two needles under a binocular loupe with a preheated plate at 37 °C (Figure 6).
Note: It is important to completely drain the tail of the epididymis to obtain the correct concentration of spermatozoa. The dissection must be done very quickly, which can be challenging for a beginner. In this case, always take the same amount of time to dilate the epididymes of the different individuals of the same study. Optimal time for step 8 is less than 10 min (for both epididymis).
Figure 6. Place the tail of the epididymis so that the incisions are clearly visible. (A) Apply pressure to the tail of the epididymis with a needle to remove the sperm through the vas deferens. (B) The spermatozoa will come out as a jelly that will disintegrate in the medium. (C) Empty the epididymis completely by applying repeated pressure. (D) It may be necessary to pierce the organ in several places to empty it completely.
Place the Petri dishes in an incubator at 37 °C for 10 min to allow the sperm to gain motility.
Note: These ten minutes can be used to adjust the CASA settings and fill in the sample identification in the software, if not already done beforehand.
Sperm motility assessment
Transfer the sperm in M2 medium from the Petri dish to the 2 mL microtube preheated in a 37 °C heating block.
Note: You can pool the two epididymides of the same individual or treat them separately according to your needs.
Take 20 µL of suspended semen, place it in a second Eppendorf, then dilute it with preheated M2 medium.
Note: The dilution performed depends on the mice strain used. Perform an experiment beforehand on a control individual to identify the dilution to be used for the rest of the study. For example, we use a standard 1:50 dilution for our Black 6 mice but a 1:100 dilution for our OF1 mice.
Homogenize and then transfer the sample to a Leja slide. Put the slide in the heated blade holder under the microscope.
Note: Wait a few moments for the flow to stabilize in the chamber to prevent the sperm trajectories from being affected by any residual Brownian motion.
Confirm that the sperm density is in the acceptable range of the software and check that the sample identification is correct.
Note: The software acceptability cut-off is relatively high. We advise to use a concentration that does not lead to a systematic crossing of the trajectories to allow an easier analysis afterwards.
Acquire with the software as much field as you may need.
Note: For a statistically robust analysis, we recommend acquiring a minimum of 200 motile spermatozoa. Use a “forward walk” reading during the acquisition to avoid taking the same field several times (Figure 7).
Figure 7. “Forward walk” reading path on a Leja slide
Process all samples successively in the same way.
Note: The purpose here is to acquire the data (the videos) to being able to interpret them later. Do not waste time interpreting now and focus on acquiring all the samples sequentially.
Sperm concentration assessment
Note: We describe here the method used for a Thoma chamber; however, you can use any other type of counting chamber (e.g., Mallassez or Makler) as long as you follow the associated instructions.
Take 10 µL of suspended semen, place it in a third Eppendorf, and add 90 µL of sterile H2O to immobilize the spermatozoa.
Note: You can use another dilution, but you will have to take it into account when calculating the final concentration.
Homogenize and transfer 10 µL to the Thoma counting chamber.
Count the number of sperm present on two lines to obtain the sperm concentration expressed in millions per milliliter (Figure 8).
Note: Count the sperm heads; single flagella are not counted or counted separately. This is also an opportunity to calculate the concentration of any round cells in the ejaculate (germline or immune cells). If you have pooled epididymides, do not forget to multiply by two. You can count more lines and average the results for more accuracy.
Figure 8. Count two full lines of a 1:10 diluted sample to obtain the cell concentration in millions per milliliter
Sperm morphology assessment
Transfer the remaining samples to 15 mL tubes. Add 3 mL of 1× PBS. Homogenize by gentle pipetting.
Centrifuge at 400 × g for 5 min. Discard the supernatant.
Add another 3 mL of 1× PBS to the pellet.
Homogenize by gentle pipetting.
Centrifuge at 400 × g for 5 min. Discard the supernatant.
Add another 200 µL of 1× PBS to the pellet.
Homogenize by gentle pipetting.
Put 10 µL (this volume can be adjusted according to the desired concentration of cells on the slide) at the base of a clean slide and make a smear with a second slide.
Note: The drop must be "pulled" and not "pushed" by the second blade, which would break the sperm flagella (see Figure 9).
Figure 9. The smearing blade should be placed in front of the drop and pull it forward. It must not push or cut through the drop.
Let dry at room temperature.
Immerse in a 75% ethanol bath for at least 1 h.
Let dry at room temperature.
Perform a Harris-Schorr staining by carrying out the following sequence of baths (one immersion corresponds to a duration of approximately 1 s):
Tap water—15 immersions
Hematoxylin—2 min
Tap water—15 immersions
Ethanol ammoniacal—10 immersions
Tap water—15 immersions
Ethanol 50%—5 min
Shorr—5 min
Ethanol 50%—5 min
Ethanol 75%—5 min
Ethanol 95%—5 min
Allow the stained slides to dry completely.
Note: Any alcohol residue will interfere with the interpretation.
Mount the slides with Eukitt and a 24 mm × 60 mm cover slide.
Note: Avoid trapping air bubbles and remove them by applying gentle pressure to the cover slide if necessary.
Let the mounted smear dry horizontally on absorbent paper for 24 h before interpretation.
Data analysis
Concentration analysis
Data can be presented as cell concentration in million cells per milliliter, number of cells per epididymis, or total numeration of cells per individual.
Motility analysis
Review each acquired video (Figure 10) to ensure that the selected sperm paths are correct, i.e., eliminate possible experiment artifacts (air bubble, residue, aggregates) and intersecting sperm paths.
Note: For more details, please refer to the CEROS II user manual.
Figure 10. Screenshot of pattern analysis from the software. Motile sperm pathways are highlighted in green.
The software will provide you with all the information about sperm motility (Figure 11): a first part with the percentages of motile and progressive motile sperm, a second part (if necessary) with the main parameters—the curvilinear velocity (VCL) or average path velocity (VAP), straight-line velocity (VSL), and amplitude lateral of the head (ALH)—and then if necessary the subsequent findings (e.g., the percentage of capacitated sperm).
Note: Be careful with how you handle the results given by the software, as they are in the form of mean/median ± standard error/deviation. Depending on the analysis you want to do, it could be wiser, statistically speaking, to start directly from the raw data of each trajectory extractable from the software.
Figure 11. Screenshot of results provided by the software post-analysis
Morphology analysis
Analyze the slides using a brightfield light microscope with the 100× objective and immersion oil.
The head is stained pale blue in the acrosome region and dark blue in the post-acrosomal region. The intermediate piece is stained red and the flagellum blue or red. The cytoplasmic residues are colored red–orange.
Differentiate spermatozoa according to their typical/atypical morphology (Figure 12) on a minimum of 100 cells (200 for more precise analysis).
Note: It is possible to limit the analysis to the typical/atypical character of the spermatozoa, but it is interesting to carry out an in-depth analysis by separating the abnormalities of the head and the flagellum, or even going into the details of the abnormalities. For this purpose, it is necessary to distinguish abnormalities of the head [elongated, thinned, microcephalic, macrocephalic, multiple, with an abnormal or absent acrosome, or with an abnormal base (post-acrosomal region], the intermediate piece (which may be small, angular, or with cytoplasmic remains), and the flagellum (which may be absent, shortened, of irregular caliber, coiled, and/or multiple).
Figure 12. Light microscopy pictures of Harris-Schorr stained spermatozoa (from Martinez et al., 2022). (A) Typical morphology. (B) Head abnormalities. (C) Flagellum abnormalities. (D) Head and flagellum abnormalities. Defects are pointed by white arrows.
Notes
In an effort to refine and reduce the number of animals used in the studies, always consider additional analyses whenever possible: fix the testicles to make histological sections or the remaining spermatozoa pellets to make immunofluorescence slides, freeze for proteomics, extract DNA from other organs, and run toxicology analyses. Whatever your field of study, try to plan for simultaneous manipulations.
Recipes
75% ethanol
100 mL of 96% ethanol + 31 mL of sterile water
50% ethanol
100 mL of 96% ethanol + 98 mL of sterile water
Ethanol ammoniacal
95 mL of 75% ethanol + 5 mL of ammonia solution at 25%
Acknowledgments
This protocol is derived from the original research paper “Oligogenic heterozygous inheritance of sperm abnormalities in mouse” from Martinez et al. published in eLife on April 22, 2022 (Martinez et al., 2022; doi:10.7554/eLife.75373) and funded by Agence Nationale de la Recherche ANR-19-CE17-0014 and ANR-21-CE17-0007.
Competing interests
The authors declare that no competing interests exist.
Ethics
All animal procedures presented in the original paper were conducted according to a protocol approved by the local Ethics Committee (ComEth Grenoble No. 318), by the French government (ministry agreement number #7128 UHTA-U1209-CA), and by the Direction Générale de la Santé (DGS) for the State of Geneva.
References
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Abdollahi, M. B., Dehghan, S. F., Balochkhaneh, F. A., Moghadam, M. A. and Mohammadi, H. (2021). Comparison of mice' sperm parameters exposed to some hazardous physical agents. Environ Anal Health Toxicol 36(3): e2021013-2021010.
Beurois, J., Cazin, C., Kherraf, Z. E., Martinez, G., Celse, T., Toure, A., Arnoult, C., Ray, P. F. and Coutton, C. (2020). Genetics of teratozoospermia: Back to the head. Best Pract Res Clin Endocrinol Metab 34(6): 101473.
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4,530 | https://bio-protocol.org/en/bpdetail?id=4530&type=0 | # Bio-Protocol Content
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Peer-reviewed
Single Protein Detection and Imaging with Evanescent Scattering Microscopy
PZ Pengfei Zhang *
LZ Lei Zhou *
RW Rui Wang
XZ Xinyu Zhou
JJ Jiapei Jiang
ZW Zijian Wan
SW Shaopeng Wang
(*contributed equally to this work)
Published: Vol 12, Iss 20, Oct 20, 2022
DOI: 10.21769/BioProtoc.4530 Views: 906
Reviewed by: Zinan ZhouAli Asghar KermaniArif Md. Rashedul Kabir
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Cited by
Original Research Article:
The authors used this protocol in Nature Communications Apr 2022
Abstract
Single-molecule measurements provide statistical distributions of molecular properties, in addition to the ensemble averages. Evanescent detection approaches have been widely used for single-molecule detection because the evanescent field can significantly enhance the light-analyte interaction and reduce the background noise. However, current evanescent single-molecule detection systems mostly require specially designed sensing components. Here, we show that single proteins can be imaged on a plain cover glass surface by detecting the evanescent waves scattered by the target molecules. This allows us to quantify the protein–antibody interactions at the single-molecule level. This protocol describes a label-free single-molecule imaging approach with conventional consumables and may pave the road for detecting single molecules with commercial optical microscopy.
Keywords: Single-molecule imaging Single protein Scattering microscopy Evanescent field Total internal reflection Cover glass
Background
Label-free single-molecule imaging allows the statistical analysis of intrinsic molecular properties such as size, mass, and binding kinetics. Evanescent field can notably increase the light-analyte interaction and suppress the background light by reducing the illumination volume. Traditional evanescent detection approaches, such as surface plasmon resonance (SPR), usually measure the ensemble properties of analytes diffusing into the evanescent field by monitoring the variations of incident light exciting the evanescent field (Homola, 2008; Zhang et al., 2018). In recent years, it has been demonstrated that directly measuring the evanescent waves scattered by the analytes can significantly improve the detection sensitivity and even push the detection limit down to the single-molecule level (Mauranyapin et al., 2017). Plasmonic scattering microscopy (PSM) has further advanced this field by providing wide-field single-molecule imaging capabilities (Zhang et al., 2020). However, PSM employs the surface plasmonic field as the illumination, and the gold film supporting the plasmonic field will generate massive heat at high-incident light intensity, which is required to achieve enough signal-to-noise ratio for single-molecule detection. This thus limits its application in the detection of fragile biological macromolecules, as well as long-term monitoring of molecular binding processes (Zhang et al., 2021).
To further push the evanescent scattering detection approaches forward, we recently developed the evanescent scattering microscopy (ESM), which can perform label-free evanescent scattering imaging of single proteins on plain cover glass surfaces (Zhang et al., 2022). The ESM utilizes total internal reflection to replace the surface plasmon resonance to excite the evanescent field, thus avoiding the heating effect by removing the gold film, and making it suitable for detecting most molecules with conventional consumables. In the following protocol, we describe in detail the construction of an ESM system with commercially available components and its single-molecule imaging operations.
Materials and Reagents
Syringe (BD, catalog number: 302830) with needle (Weller, catalog number: KDS2312P) with the flexible plastic tubing (Tygon, catalog number: AAD04103)
Microfluidic ball valves (Cole-Parmer, catalog number: EW-30600-00)
Cover glasses No. 1, 22 × 22 mm (VWR, catalog number: 48366-067)
Cover glasses No. 1, 18 × 18 mm (VWR, catalog number: 48366-045)
Petri dish (Sigma-Aldrich, catalog number: P5731)
0.22 µm filter (Sigma-Aldrich, catalog number: SLGSM33SS)
Isopropyl alcohol (IPA, VWR, catalog number: BDH2032-1GLP)
Hydrogen peroxide (H2O2, 30%) (Sigma-Aldrich, catalog number: H1009)
(3-aminopropyl) triethoxysilane (APTES) (Sigma-Aldrich, catalog number: 440140)
Succinic anhydride (Sigma-Aldrich, catalog number: 239690)
Bovine serum albumin (BSA) (Sigma-Aldrich, catalog number: A7638)
Sodium hydroxide (NaOH) (Sigma-Aldrich, catalog number: S5881)
Ammonium hydroxide (NH3·H2O, 28.0%–30.0%) (Mallinckrodt Reagents, catalog number: C5103500-2.5D)
1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) (Thermo Scientific, catalog number: 22980)
Sulfo-NHS (N-hydroxysulfosuccinimide) (Thermo Scientific, catalog number: 24510)
Phosphate-buffered saline (PBS) (Corning, catalog number: 21-040-CV)
Anti-IgA (IgG) (Bio-Rad, catalog number: STAR141)
Human colostrum IgA (Athens Research and Technology, catalog number: 16-13-090701)
Human IgM (Athens Research and Technology, catalog number: 16-16-090713)
Office tape (3MTM ScotchTM, 810, 3/4 in × 108 ft, 1 in Tape Core Dia, Transparent, Matte)
10 g L−1 succinic anhydride (see Recipes)
NH3·H2O, H2O2, and water (see Recipes)
EDC–NHS solution (see Recipes)
Equipment
Optical breadboard (Newport, model: SG-23-4-ML)
Active vibration isolation stage (Accurion, model: Vario Basic 60-300)
80 mW laser diode (Thorlabs, model: PL450B)
Temperature-controlled mount (Thorlabs, model: LDM38)
Benchtop diode current controller (Thorlabs, model: LDC205C)
Temperature controller (Thorlabs, model: TED200C)
Manual translation stage (Thorlabs, model: XR25P-K2)
Posts and Accessories essentials kit (Thorlabs, model: ESK16)
Bases and Post Holders essentials kit (Thorlabs, model: ESK01)
SM1 Lens Tube essentials kit (Thorlabs, model: ESK25)
Ø 2" Optic Mounts essentials kit (Thorlabs, model: ESK19)
Pillar Post essentials kit (Thorlabs, model: ESK15)
Lens Mount essentials kit (Thorlabs, model: ESK22)
C-Mount Extension Tube kit (Thorlabs, model: CML-KIT)
SM2 Lens Tube essentials kit (Thorlabs, model: ESK26)
Cage Assemblies and Lens Tubes essentials kit (Thorlabs, model: ESK07A)
Cage Assemblies and Lens Tubes essentials kit Set B (Thorlabs, model: ESK07B)
Mounted Ø 1" Achromatic Lens kit (Thorlabs, model: LSB08-A)
Cage cube–mounted protected silver turning mirror (Thorlabs, model: CCM1-P01)
Camera (XIMEA, model: MQ003MG-CM and MQ013MG-CM)
25 mm × 36 mm protected silver mirror (Thorlabs, model: PFR10-P01)
Kinematic fluorescence filter cube (Thorlabs, model: DFM1)
SM1A2 adapter (Thorlabs, model: SM1A2)
60 mm cage system translating lens mount (Thorlabs, model: CXY2)
Brass microscope adapter (Thorlabs, model: M2M34S)
Cage plate (Thorlabs, model: LCP08)
Thermally insulating adapter (Thorlabs, model: SM1A3TS)
Zoom housing (Thorlabs, model: SM1ZM)
Reflective ND filter (Thorlabs, model: ND40A)
30–60 mm cage plate adapter (Thorlabs, model: LCP33)
Cage assembly rods (Thorlabs, model: ER18)
Plate (Thorlabs, model: CPVMP)
Kinematic beam-turning cage cube (Thorlabs, model: DFM1-P01)
Dovetail optical rail (Thorlabs, model: RLA1800)
60× objective (Olympus APO N 60× Oil TIRF, NA 1.49)
50× objective (Motic ULWD 50×, NA 0.42)
Achromatic doublet lens (Thorlabs, model: AC508-180-A-ML, AC254-100-AB-ML, and AC254-030-AB-ML)
Ø 1.5" Posts (Thorlabs, model: P6, P8, P10, P12, P14)
Robbins biopsy punch (Robbins Instruments, catalog number: 18271P)
Sylgard 184 silicone elastomer (Dow Silicones Corporation, catalog number: 04019862)
Potomac laser (1450 South Rolling Road Baltimore MD, 21227, USA)
BD-20AC laboratory corona treater (Electro-Technic Products, catalog number: 12051A)
Oven (Thermo Scientific, model: PR305225M)
Double-coated tape (3M, catalog number: 9628B)
Devcon epoxy (Euro Tool, catalog number: GLU-735.90)
Software
XIMEA CamTool (XIMEA)
MATLAB (MathWorks)
Fiji (https://imagej.net/Fiji)
Origin 2019 (OriginLab)
Office 365 (Microsoft)
Procedure
Setting the optical arrangement
Put the optical breadboard onto an active vibration isolation stage.
Arrange the optical components in the order shown in Figure 1. The details for each component are listed below. All components are fixed onto the breadboard with TR075 or TR1 optical posts (Posts and Accessories essentials kit), and PH1 or PH1.5 post holders and BA1 mounting bases (Bases and Post Holders essentials kit), depending on their sizes.
An 80 mW laser diode is fixed at a temperature-controlled mount as the light source. The laser diode is driven by a benchtop diode current controller and a temperature controller. The mount is fixed onto the breadboard with two TR075 optical posts and two PH1 post holders. The post holders are fixed on the breadboard using a ¼”–20 × ½” screw set.
Figure 1. Optical arrangement of the ESM. Light from the laser diode is conditioned by an achromatic doublet lens group and then focused on the back focal plane of a 60× objective by a tube lens. The incident angle is adjusted by a manual translation stage to reach total internal reflection condition at 65°. Reflection light is also collected by a camera to help finding the objective focus position. Scattered light from the protein and glass surface is collected by a 50× objective to form an ESM image by a second camera.
Fix one SM1L20C slotted lens tube (SM1 Lens Tube essentials kit) into the temperature-controlled mount. Put one AC254-030-A achromatic doublet lens (Mounted Ø 1” Achromatic Lens kit) into the slotted lens tube, and fix its position with two SM1 retaining rings to achieve collimation laser light.
Fix one AC254-100-A-ML achromatic doublet lens (Mounted Ø 1" Achromatic Lens kit) at the end of the slotted lens tube.
Fix one AC254-030-A-ML achromatic doublet lens (Mounted Ø 1" Achromatic Lens kit) with one SMR1 lens mount. Connect the lens mount to one TR3 optical post (Posts and Accessories essentials kit), and then fix it with another two TR3 optical posts and two RA90 right-angle post clamps (Posts and Accessories essentials kit) onto one XR25P-K2 manual translation stage. Figure 2A shows the picture of the assembled parts.
Fix one RLA1800 dovetail optical rail onto the breadboard with cap screws.
Fix one DFM1-P01 kinematic beam-turning cage cube onto the dovetail optical rail using one TR075 optical post, one PH1 post holder, and one RC2 dovetail rail carrier.
Fix one CPVMP plate with cap screws at the end of the dovetail optical rail.
Fix four ER18 cage assembly rods onto the CPVMP plate to construct the structure for one 60 mm vertical cage system.
Fix one LCP33 30–60 mm cage plate adapter onto the cage assembly rods.
Fix one cage cube–mounted protected silver turning mirror at the bottom of the cage plate adapter with four ER025 cage assembly rods.
Fix one AC508-180-A-ML achromatic doublet lens onto the turning mirror as the imaging tube lens with one SM1A2 adapter.
Fix one camera (MQ013MG-CM) equipped with one ND40A reflective ND filter at the focal point of the achromatic doublet lens to monitor the position of the reflection beam.
Fix one kinematic fluorescence filter cube at the top of the cage plate adapter with four ER025 cage assembly rods. One half reflector is set in the cube to allow the transmission of both incident and reflection beams. One half reflector (25 mm x 18 mm) is prepared by cutting the 25 mm x 36 mm protected silver mirror in two equal parts, which can be customized by the Thorlabs technique support team.
Fix another cage plate adapter onto the cage assembly rods at the top of the kinematic fluorescence filter cube. Fix one SM1ZM zoom housing onto the plate adaptor.
Fix one 60× objective onto the zoom housing with a Thorlabs SM1A3TS thermally insulating adapter.
Rotate and paste the office tape in the middle of the 60× objective to reach the final diameter of approximately 34 mm. Fix one LCP08 cage plate with one M2M34S brass microscope adapter onto the cage assembly rods. Ensure the tape circles attach to the adaptor surface to suppress the drift.
Fix one CXY2 60 mm cage system translating lens mount on the top of the objective to place the sensor chip.
Fix another CXY2 60 mm cage system translating lens mount onto the cage assembly rods and fix the SM2A6 adapter with external SM2 threads and internal SM1 threads onto the translating lens mount. Then, fix one SM1ZM zoom housing onto the adaptor.
Fix one 50× objective (working distance 20.5 mm) onto the zoom housing.
Fix another cage plate adapter onto the cage assembly rods. Fix one cage cube–mounted protected silver turning mirror onto the adaptor with four ER025 cage assembly rods.
Fix one AC508-180-A-ML achromatic doublet lens onto the turning mirror as the imaging tube lens with one SM1A2 adapter.
Fix one camera (MQ003MG-CM) at the focal point of the achromatic doublet lens to achieve the ESM image.
Preparing the sensor chip
Employ a 22 × 22 mm cover glass as the sensing substrate.
Clean the cover glasses in a boiling NH3·H2O, H2O2, and water solution for 1 h to obtain clean hydroxylated glass surfaces, where dropping water becomes a layer.
Wash the cover glasses and container twice with water, ultrasonically clean two times with water, and blow dry with nitrogen.
Incubate the hydroxylated cover glasses in boiling 1% APTES diluted with IPA for 3 h to functionalize the surface with the primary amine group. If drying in Step B2 was performed correctly, both the solution and cover glass should be clear after processing.
Wash the cover glass and container twice with IPA, ultrasonically clean twice with IPA, and blow dry with nitrogen.
Incubate the amino group–modified cover glasses in 10 g L−1 succinic anhydride for 1 h to obtain carboxylic group–functionalized cover glass chips. Adjust the pH of succinic anhydride solution to 7.5–8 with 1 M NaOH solution. Wash the cover glass and container twice with water, ultrasonically clean twice with water, and then store in water until use. Prior to the experiment, dry the cover glasses with nitrogen for fabricating the flow cell.
To fabricate the flow cell, prepare one 18 × 18 mm cover glass with two 1 mm holes, which can be drilled by laser.
Note: We asked the Potomac Laser for help to do this.
Use Sylgard 184 silicone elastomer to prepare the PDMS (Polydimethylsiloxane) plate with 3 mm thickness. Put 24 mL silicone elastomer solution into a Petri dish with 100 mm diameter, and then heat it at 60 °C in the oven to achieve a 3 mm thickness PDMS plate. Then, cut a PDMS part with 6 mm length, 3 mm width, and 3 mm thickness. Create a hole with approximately 1 mm at the middle of each PDMS part with the Robbins biopsy punch.
Use a laboratory corona treater to process the surfaces of the 18 × 18 mm cover glass and PDMS part. Then, attach the PDMS parts to the cover glass and place them into the oven at 90 °C for 1 h.
Use the knife to cut the double-coated tape into a small piece (18 × 18 mm) and create one channel (8 × 15 mm) in the middle of the tape piece. Attach the tape piece to the 22 × 22 mm cover glasses, and then attach the 18 × 18 mm cover glass with PDMS parts onto the tape piece. Seal the edges with Devcon epoxy. The final picture of the sensor chip is shown in Figure 2B.
Fix the sensor chip onto the CXY2 60 mm cage system translating lens mount with customized parts (Figure 2C).
Connect the sensor chip to one syringe with a needle with the flexible plastic tubing. On the sensor chip, 304 stainless steel capillary cubes can connect the tubing and PDMS part. The microfluidic ball valves are used to start and stop the waterflow. Place the syringe higher than the sensor chip and gravity will push the sample to flow onto the sensor surface.
In the experiment, the surface was incubated in 40 g L−1 EDC mixed with 11 g L−1 sulfo-NHS for 15 min to activate the carboxyl groups for connecting proteins. The EDC/NHS solution was filtered using a 0.22 µm filter before use.
Reinforcing the system structure
Apart from the lens fixed on the manual translation stage as shown in Figure 2A, all components should be connected with SM1 or SM2 optical tubes.
Use SM1TC or SM2TC clamps to fix each optical component by connecting it to another optical post fixed on the breadboard.
Connect the optical posts to each other with RA90 right-angle clamps and Ø 1/2" stainless steel optical posts (Figure 2D).
Data analysis
The raw image sequence captured at a high frame rate (approximately 200 fps) was converted to an averaged-image sequence, by averaging images over every 20 ms using the real-time averaging function of the camera recording software (XIMEA CamTool), to suppress shot noise. To remove the background, a differential image sequence was obtained by subtracting the previous frame from the present frame of the averaged-image sequence, using the Image Calculator plugin in Fiji. The TrackMate plugin in Fiji was employed to find and count molecules and achieve the ESM intensity of a molecule by averaging the powers of all pixels within the Airy disk. Following the operation instruction of TrackMate and selecting the “Export all spots statistics” at the final step, the mean intensity item is the result of averaging the powers of all pixels within the Airy disk. Origin 2019 was used to create data plots and histograms (Figure 3) and fit the histograms with Gaussian function using the Multiple Peak Fit tool.
Figure 2. Picture of systems. (A) Lens on the manual translation stage. (B) Sensor chip. (C) Mechanical parts fixing the sensor chip onto the system. (D) Optical system.
Figure 3. Image intensity histograms and calibration. Evanescent scattering microscopy image intensity histograms of BSA (A), IgG (B), IgA (C), and IgM (D) proteins, where the solid red curves are Gaussian fittings. (E) Box plots of image intensities measured on different proteins from A–D. (F) Evanescent scattering microscopy image intensity versus protein diameter, measured by dynamic light scattering in logarithmic scale.
Recipes
10 g L−1 succinic anhydride
Reagent Final concentration Amount
Succinic anhydride 10 g L−1 n/a
H2O n/a 100 mL
Total n/a 100 mL
NH3·H2O, H2O2, and water (volume ratio of 1:1:5)
Reagent Final concentration Amount
NH3·H2O 15% 15 mL
H2O2 15% 15 mL
H2O
Total
70%
n/a
70 mL
100 mL
EDC–NHS solution
Reagent Final concentration Amount
EDC 40 g L−1 n/a
NHS
PBS buffer
11 g L−1
n/a
n/a
1 mL
Total n/a 1 mL
Acknowledgments
We thank the financial support from the National Institute of General Medical Sciences of the National Institutes of Health grant R01GM107165. This protocol was adapted from our previously published work (Zhang et al., 2022).
Competing interests
The authors declare no competing financial interest.
References
Homola, J. (2008). Surface plasmon resonance sensors for detection of chemical and biological species. Chem Rev 108(2): 462-493.
Mauranyapin, N. P., Madsen, L. S., Taylor, M. A., Waleed, M. and Bowen, W. P. (2017). Evanescent single-molecule biosensing with quantum-limited precision. Nature Photonics 11(8): 477-481.
Zhang, P., Liu, L., He, Y., Chen, X., Ma, K., Wei, D., Wang, H. and Shao, Q. (2018). Composite layer based plasmon waveguide resonance for label-free biosensing with high figure of merit. Sensors and Actuators B: Chemical 272: 69-78.
Zhang, P., Ma, G., Dong, W., Wan, Z., Wang, S. and Tao, N. (2020). Plasmonic scattering imaging of single proteins and binding kinetics. Nat Methods 17(10): 1010-1017.
Zhang, P., Ma, G., Wan, Z. and Wang, S. (2021). Quantification of Single-Molecule Protein Binding Kinetics in Complex Media with Prism-Coupled Plasmonic Scattering Imaging. ACS Sens 6(3): 1357-1366.
Zhang, P., Zhou, L., Wang, R., Zhou, X., Jiang, J., Wan, Z. and Wang, S. (2022). Evanescent scattering imaging of single protein binding kinetics and DNA conformation changes. Nat Commun 13(1): 2298.
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4,531 | https://bio-protocol.org/en/bpdetail?id=4531&type=0 | # Bio-Protocol Content
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Measurement of Ascorbate Peroxidase Activity in Sorghum
PK Praveen Kumar
Published: Vol 12, Iss 20, Oct 20, 2022
DOI: 10.21769/BioProtoc.4531 Views: 1995
Reviewed by: Khyati Hitesh ShahPrasad S. Dalvi Anonymous reviewer(s)
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Original Research Article:
The authors used this protocol in PLOS ONE Jul 2021
Abstract
The ascorbate peroxidase (APX) is a widely distributed antioxidant enzyme. It differs from catalase and other peroxidases in that it scavenges/reduces reactive oxygen species (ROS) such as hydrogen peroxide (H2O2) to water using reduced ascorbate as the electron donor. It is advantageous over other similar antioxidant enzymes in scavenging ROS since ascorbate may react with superoxide, singlet oxygen, and hydroxyl radical, in addition to reacting with H2O2. The estimation of its activity is helpful to analyze the level of oxidative stress in living systems under stressful conditions. The present protocol was performed to analyze the impact of heavy metal chromium (Cr) toxicity on sorghum plants in the form of APX enzyme activity under the application of glycine betaine (GB) and arbuscular mycorrhizal fungi (AMF) as stress ameliorators. Plant defense strategies against heavy metals toxicity involve the utilization of APX and the instigation of AMF symbiotic system, as well as their possible collaboration with one another or with the plant antioxidant system; this has been examined and discussed in literature. In this protocol, an increased APX activity was observed on underlying functions and detoxification capabilities of GB and AMF that are typically used by plants to enhance tolerance to Cr toxicity.
Graphical abstract:
Flow chart of standardized or calibrated enzyme assay with leaf samples of sorghum
Keywords: Ascorbate peroxidase Hydrogen peroxide Ascorbate Antioxidants Antioxidant enzymes Oxidative stress
Background
Ascorbate peroxidase (APX) is an antioxidant enzyme, involved in the removal of toxic components such as reactive oxygen species (ROS) produced during physiologic and metabolic activities of the cell. Cells need to detoxify ROS efficiently as a consequence of abiotic stresses. A complex enzymatic antioxidative system could be developed by cells, which controls the production of ROS and ultimately protects the plant against oxidative damage (Ashraf et al., 2015). This metal-induced plant anti-oxidative defense mechanism is differential and largely based on the types of heavy metals and plant species. Elevated anti-oxidative enzyme activities attenuate abiotic oxidative stress and play a pivotal role in plants adapting against various environmental stresses (Singh et al., 2008). Furthermore, a decline in APX activity suggests that higher Cr toxicity might be inhibiting its ROS-eliminating role in plants. Decreased APX activity with increased metal toxicity was previously reported in Indian mustard (Mobin and Khan, 2007), oilseed rape (B. Ali, et al., 2014), and wheat (S. Ali, et al., 2015). Overall, increasing Cr toxicity triggers antioxidant production (mainly responsible for ROS quenching), representing plants’ potential to withstand Cr-polluted soils up to a certain level, which is further dependent on plant species and environmental conditions. Anjum et al. (2017) reported that at lower heavy metals concentrations the activity of antioxidant enzymes increased, whereas at higher concentrations the activity did not further increase. Samantaray et al. (1999) used peroxidase and catalase activities as enzyme markers for Cr-tolerant mung bean cultivars. The observed increase in antioxidant enzyme activity might have been in direct response to the generation of superoxide radicals by Cr-induced blockage of the electron transport chain in the mitochondria. Higher increases observed due to Cr(VI) indicated that its addition probably generated more singlet oxygen than Cr(III). The decrease in enzyme activity, as the concentration of external Cr increases, might be due to the inhibitory effect of Cr ions on the enzyme system itself.
In the present study, a comprehensive account of past developments and current trends using glycine betaine (GB) and arbuscular mycorrhizal fungi (AMF) in the research on Cr toxicity and its amelioration in sorghum plants has been attempted. Moreover, another line of plant defense strategy against heavy metals toxicity, which involves the utilization of APX and the instigation of AMF symbiotic system, as well as their possible collaboration with one another or with the plant antioxidant system, has been examined and discussed (Kumar, 2021). The study focuses on the underlying functions and detoxification capabilities of GB and AMF that are typically used by plants to enhance tolerance to Cr toxicity.
Materials and Reagents
Aluminum foil
Hydrogen peroxide, 35% in water (H2O2) (TCI, catalog number: H1222, CAS RN: 7722-84-1)
L(+)-ascorbic acid (CAS 50-81-7) (Merck Millipore, catalog number:100468)
0.1 M potassium phosphate buffer (pH 7.0) (see Recipes)
Reaction mixture (see Recipes)
Equipment
Scale
Pipettes
Stirrer
Mortar and pestle
Centrifuge machine
Double beam UV-VIS spectrophotometer with Graphic LCD – Typr 2205
Glassware: test tubes, beakers, conical flask, measuring cylinder, and a volumetric flask (Slisco scientific and Ace Glass Incorporated)
Procedure
Sample extraction
Note: The complete extraction procedure must be carried out at 0–4 °C. The ascorbate peroxidase activity was measured in leaf tissues of sorghum plants.
Completely homogenize 2 g of fresh and cleaned tissue sample in 10 mL of fresh 0.1 M potassium phosphate buffer (pH 7.0) by using a previously chilled mortar and pestle.
Centrifuge the homogenate at 11,180 × g for 15 min in a temperature-controlled centrifuge machine.
Collect the supernatant as crude extract and discard the pellet completely.
Use this enzyme extract immediately for enzyme assay and preserve the remaining extract in the refrigerator for total soluble protein estimation, which is required for enzyme specific activity calculation.
Enzyme assay
Note: APX is assayed by the method of Nakano and Asada (1981). For estimating APX activity use freshly prepared reagents and extracts only.
Add 3 mL of reaction mixture (see Recipes) and initiate the reaction by adding 50 µL of enzyme extract (from step A4) at the end.
The blank can be simultaneously prepared for each sample by taking 50 µL of boiled enzyme extract instead of enzyme extract.
Record the decrease in absorbance at 290 nm using the spectrophotometer for 2 min against a suitable blank.
The enzyme activity can be calculated using the molar extinction coefficient (absorbance of one molar solution) of 2.8 mM-1 cm-1 for ascorbate in the standard equation given below. Enzyme activity will be given in enzyme units, with one enzyme unit corresponding to the amount of enzyme required to oxidize 1 nmol of ascorbic acid per minute.
Standard equation for absorbance: A = ϵ × l × с
Where A is the amount of light absorbed by the sample at a given wavelength, ϵ is the molar extinction coefficient, l is the distance that the light travels through the solution, and с is the concentration of the absorbing species.
Note: To get better and more accurate results according to your samples and instruments, calibration between L-ascorbate, H2O2, and enzyme extract should be performed before starting the final procedure.
Calculations:
The enzyme activity and specific activity can be calculated as explained in Table 1 for a supposed sample size. The total protein content of the sample is required to calculate the specific activity, which can be determined by Lowry’s method.
Table 1. Ascorbate peroxidase activity (units or nmol of ascorbate/minute)
Supposed sample used: extract was made from a 2 g sample of fresh leaves in 10 mL of potassium phosphate buffer; from this, 0.05 mL of extract was used for assay. Assume P mg/mL of protein was found per sample for the present case from Lowry’s method.
Absorbance at 290 nm Enzyme activity and Specific activity
Replicate Time 0 s 15 s 30 s 45 s 60 s Decrease in absorbance Average decrease in absorbance Enzyme activity/minute (units) = activity/0.05 mL Dilution factor (activity/mL of extract) Total protein content (mg/mL) Specific activity (µmol/min/mg)
1st a b c d e a - e = F (F + O + X) / 3 = Y Y / 2.8 = Z (Z / 0.05) × 1 = G P G / P = Q
2nd j k l m n j - n = O
3rd s t u v w s - w = X
Recipes
0.1 M potassium phosphate buffer (pH 7.0)
0.5 L of 1 M K2HPO4 at 174.18 g mol-1 = 87.09 g
0.5 L of 1 M KH2PO4 at 136.09 g mol-1 = 68.045 g
Mix 61.5 mL of 1 M K2HPO4 with 38.5 mL 1 M KH2PO4 for the preparation of 0.1 M potassium phosphate buffer pH 7.0 at 25 °C
Reaction mixture
2.7 mL of 100 mM potassium phosphate buffer (pH 7.0)
0.1 mL of L(+)-ascorbic acid
0.15 mL of H2O2
Acknowledgments
This research was financially supported by CCS Haryana Agricultural University authority. The corresponding author deeply appreciates the CCSHA University and its staff members for their valuable assistance in experimental conductance and data analysis. My gratitude also goes to Dr. H. R. Singal for encouraging me to write this research article.
Competing interests
The authors declare that they have no conflicts of interest.
References
Ali, B., Xu, X., Gill, R. A., Yang, S., Ali, S., Tahir, M. and Zhou, W. (2014). Promotive role of 5-aminolevulinic acid on mineral nutrients and antioxidative defense system under lead toxicity in Brassica napus. Ind Crops Prod 52: 617-626.
Ali, S., Chaudhary, A., Rizwan, M., Anwar, H. T., Adrees, M., Farid, M., Irshad, M. K., Hayat, T. and Anjum, S. A. (2015). Alleviation of chromium toxicity by glycinebetaine is related to elevated antioxidant enzymes and suppressed chromium uptake and oxidative stress in wheat (Triticum aestivum L.). Environ Sci Pollut Res Int 22(14): 10669-10678.
Anjum, S. A., Ashraf, U., Imran, K. H. A. N., Tanveer, M., Shahid, M., Shakoor, A. and Longchang, W. A. N. G. (2017). Phyto-toxicity of chromium in maize: oxidative damage, osmolyte accumulation, anti-oxidative defense and chromium uptake. Pedosphere 27(2): 262-273.
Ashraf, U., Kanu, A. S., Mo, Z., Hussain, S., Anjum, S. A., Khan, I., Abbas, R. N. and Tang, X. (2015). Lead toxicity in rice: effects, mechanisms, and mitigation strategies--a mini review. Environ Sci Pollut Res Int 22(23): 18318-18332.
Kumar, P. (2021). Soil applied glycine betaine with Arbuscular mycorrhizal fungi reduces chromium uptake and ameliorates chromium toxicity by suppressing the oxidative stress in three genetically different Sorghum (Sorghum bicolor L.) cultivars. BMC Plant Biology 21(1): 1-16.
Mobin, M. and Khan, N. A. (2007). Photosynthetic activity, pigment composition and antioxidative response of two mustard (Brassica juncea) cultivars differing in photosynthetic capacity subjected to cadmium stress. J Plant Physiol 164(5): 601-610.
Nakano, Y. and Asada, K. (1981). Hydrogen Peroxide is Scavenged by Ascorbate-specific Peroxidase in Spinach Chloroplasts. Plant Cell Physiol 22(5): 867-880.
Samantaray, S., Rout, G. R. and Das, P. (1999). Studies on differential tolerance of mungbean cultivars to metalliferous minewastes. Agribiol Res 52(3-4):193-201.
Singh, S., Khan, N. A., Nazar, R. and Anjum, N. A. (2008). Photosynthetic traits and activities of antioxidant enzymes in blackgram (Vigna mungo L. Hepper) under cadmium stress. Am J Plant Physiol 3(1): 25-32.
Article Information
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© 2022 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Category
Plant Science > Plant biochemistry > Metabolite
Plant Science > Plant physiology > Abiotic stress
Biochemistry > Other compound
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How much Molar of Ascarbic acid should be used to prepare the reaction mixture ?
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