Differential effects of age, cytomegalovirus- seropositivity and end-stage renal disease (ESRD) on circulating T lymphocyte subsets

Nicolle Hr Litjens
Michiel GH Betjes

Elly A De Wit
Michiel GH Betjes

Differential effects of age, cytomegalovirus- seropositivity and end-stage renal disease (ESRD) on circulating T lymphocyte subsets
R E S E A R C H Open Access
The age-and cytomegalovirus (CMV)-seropositivity-related changes in subsets and differentiation of circulating T cells were investigated in end-stage renal disease (ESRD) patients (n = 139) and age-matched healthy individuals. The results show that CMV-seropositivity is associated with expansion of both CD4 + and CD8 + memory T cells which is already observed in young healthy individuals. In addition, CMV-seropositive healthy individuals have a more differentiated memory T cell profile. Only CMV-seropositive healthy individuals showed an age-dependent decrease in CD4 + naïve T cells. The age-related decrease in the number of CD8 + naïve T cells was CMV-independent. In contrast, all ESRD patients showed a profound naïve T-cell lymphopenia at every decade. CMV-seropositivity aggravated the contraction of CD4 + naïve T cells and increased the number of differentiated CD4 + and CD8 + memory T cells. In conclusion, CMV-seropositivity markedly alters the homeostasis of circulating T cells in healthy individuals and aggravates the T cell dysregulation observed in ESRD patients.

Introduction

End-stage renal disease (ESRD) is associated with an immune defect characterized by increased susceptibility for infections and decreased humoral responses to T-cell dependent antigens like HBsAg [1,2]. Circulating T lymphocytes can be dissected into subsets of naïve and memory T lymphocytes using the common leukocyte antigen CD45RO (memory marker) and the chemokine receptor CCR7 which is important for homing of T cells to lymphoid organs. Differential expression of CD45RO and CCR7 allows for further dissection of functionally different T lymphocyte subsets; naïve T cells (Tnaive, expressing CCR7), central-memory T cells (Tcm, expressing CCR7) and effector-memory (Tem, no expression of CCR7) [3]. In addition, within the CD8 + T lymphocyte subset an extra late effector memory population can be distinguished, lacking both CCR7 and CD45RO (Temra) [4,5]. The loss of expression of the co-stimulatory molecule CD28 and increased expression of CD57 on memory T cells is indicative of a later stage of differentiation of T cells with diminished replicative capacity [6].

Progressive loss of renal function is associated with a progressive decrease in the size of the the naïve T cell compartment, a decrease within CD4 + Tcm lymphocytes and a significant increase in CD8 + Temra [7,8]. In addition, we have demonstrated that the severely impaired humoral response of ESRD patients to HBV vaccination can be attributed to a specific deficit in the generation of antigen-specific effector-memory CD4 + T cells [9]. Therefore, the disturbed composition of circulating T cells in ESRD patients seems to underly, at least partly, their immune deficiency.

Cytomegalovirus (CMV) seropositivity is known to have a major impact on the repertoire of antigen specific T cells as an estimated 10% of circulating T cells is CMV-antigen specific in seropositive individuals [10]. In addition, the changes generally observed with an aged immune system, like a decreased CD4/CD8 ratio and expansion of CD28 negative CD8 + positive T cells seem to be related to CMV seropositivity [11][12][13]. The prevalence of CMV seropositivity increases with age and varies with socio-economic and ethnic background from 30 to 100% [14]. Therefore, any analysis of age-related changes of the immune system should take CMV-seropositivity into account. To date few studies have documented the interaction between CMV-seropositivity and ageing on the absolute numbers of circulating T cell subsets in healthy controls [11,15,16]. Although these studies indicated an CMV-related increase in total numbers of CD8 + T cells, they reached dissimilar conclusions with respect to CMV-related changes of T cells at young age which may be due to differences in definition of the various T cell populations.

ESRD patients have increased numbers of circulating CD8 + Temra cells and CD28 negative T cells suggesting a major influence of CMV seropositivity on T cell immunity [17]. However, it is not known how CMV and ageing interact and contribute to the observed ESRDrelated changes in numbers of circulating T cells subsets. A carefull dissection of the influence of these different factors (loss of renal function, age and CMV seropositivity) on circulating T cells is pivotal to understand the ESRD-related immune deficiency.

To examine this question, we have performed a large cross-sectional study including ESRD patients and healthy donors.

Material and methods

Subjects

Patients aged 18 to 78 years were recruited for the study from our outpatient clinic for renal transplantation during a period of 2.5 years. All patients had ESRD, defined as an estimated glomerular filtration rate of less then 15 mL/min with or without renal replacement therapy. Patients with a malignancy, active infection or taking immunosuppressive drugs were excluded. The healthy individuals were recruited from their relatives, thereby matching for socio-economic and ethnical background. All patients and healthy controls included gave informed consent and the local medical ethical committee approved the study. It was conducted according to the principles of Declaration of Helsinki and in compliance with International Conference on Harmonization/Good Clinical Practice regulations. Study population characteristics are depicted in Table 1. We aimed at 5 to 10 CMV-seropositive and -seronegative individuals at each age-decade.

Flowcytometric analysis of the various T lymphocyte subsets

To determine the percentages and absolute numbers of the various T lymphocytes, we performed a whole blood staining as described previously but with some minor adjustments [7]. Briefly, to distinguish the various T lymphocyte subsets, we used AmCyan-labelled CD3 (BD, Erembodegem, Belgium) with either peridinin chlorophyll protein (PerCP)-labelled CD4 or CD8 in combination with allophycocyanin (APC)-labelled CD45RO (BD) or Pacific Blue-labelled CD45RO (Biolegend Europe B.V, Uithoorn, Netherlands), and fluorescein isothiocyanate (FITC)-labelled CCR7 (R&D Systems Europe Ltd, Abingdon, UK). The various subsets are defined as CD4 + or CD8 + and either naive being CCR7 + CD45RO -(Tnaive) or belonging to the memory population (Tmem). The latter can be further dissected in central memory being CCR7 + CD45RO + (Tcm), effector memory being CCR7 -CD45RO + (Tem) and for the CD8 + T lymphocytes, Temra being CCR7 -CD45RO -. In addition, percentages of CD28 -(CD28null) and CD57 + for CD4 + and CD8 + T lymphocytes were determined using phycoerythrin (PE)-labelled CD28 (BD) and APClabelled CD57 (Biolegend), respectively. For each measurement, we acquired 50000 lymphocytes to ensure reliable results. Analysis was performed using the FACS Canto™ II (BD) and FACSDIVA software (BD).

CMV serology

Serum IgG antibodies to CMV were measured with an enzyme immuno assay (Biomerieux, VIDAS, Lyon, France) and expressed as arbitrary units/ml (AU/mL). Following the manufacturers guidelines, a test result exceeding 6 AU/mL was considered positive for the presence of CMV-specific IgG antibodies.

Statistical analysis

The non-parametric Spearman's rank correlation (Rs) test was performed to analyze correlations between age and the various T lymphocytes subsets in the group of healthy individuals and ESRD patients. ESRD patients and their age-matched healthy controls were divided into two groups; 20-40 years (young) and 60-80 years (old), to evaluate the effect of CMV seropositivity on the composition of the T lymphocyte compartment. The Mann-Whitney U-test was used to compare values between CMV-seronegative and seropositive individuals as well as to compare ESRD patients to healthy donors. Distribution of gender and CMV-seropositivity was tested using the Chi-square test. P-values less than 0.05 were considered significant. The SPSS software version 17 was used for all statistical tests.

Results

CMV-seropositivity is associated with increased T cell numbers and differentiation to a memory-effector phenotype in healthy young individuals At young age, the absolute number of CD4 + and CD8 + T cells was increased in CMV-seropositive healthy individuals by 76% and 83%, respectively when compared to CMV-seronegative healthy individuals (Table 2). Both the naïve and memory T cells showed increased cell numbers, although the memory compartment contributed for the largest part (48% for CD4 + and 64% for CD8 + T lymphocytes). In both CD4 + and CD8 + T memory cells a significant increase in differentiation towards the effector-memory phenotype was observed. Within the memory compartment, the CD4 Tem increased by 2.1-fold and the CD8 Tem by 1.5-fold. The memory CD8 + T cells showed the highest degree of differentiation to an effector phenotype as the Temra cells were on average 2.3-fold increased in CMV-seropositive healthy donors (Table 2).

CMV-seropositivity selectively influences T cell subsets with increasing age

With increasing age, the CD4 + T lymphocyte population and the different subsets remained remarkably unaffected in CMV-seronegative persons over a period of 4 to 5 decades ( Figure 1B and Figure 2A-D, straight line). However, in CMV-seropositive healthy individuals the elevated CD4 T cell numbers at young age, specifically the Tnaive, decreased to values similar to seronegative persons at old age ( Table 2 Figure 1B and Figure 2A, dotted line).

The findings were very different for age-related changes of CD8 + T cells. Most notably, a steep decrease (> 80%) was observed in Tnaive cell numbers which was unaffected by CMV-seropositivity. In CMV-seronegative individuals this resulted in a modest decrease of the total CD8 + T cell population, as the Tmem remained unchanged with increasing age ( Table 2). In CMVseropositive individuals the CD8 + Tmem increased significantly (P = 0.02) with increasing age ( Figure 3E), an effect which could be observed in all memory subpopulations although statistical significance was not reached ( Figure 3B-D). This resulted in a significantly age-related decrease in the CD4/CD8 ratio (P < 0.01) in CMV-seropositive healthy individuals, but not in CMV seronegative individuals (data not shown).

Impact of CMV-seropositivity on composition of T lymphocytes subsets in ESRD patients

Compared to CMV-seropositive healthy individuals, ESRD patients have a significantly (P < 0.01) lower number of T lymphocytes which is related to a relative CD4 + T cell lymphopenia at all ages. The decreased CD4 + T cell numbers are caused by a significant decrease in Tnaive and Tcm as has been described before [7]. The CD4 + Tnaive decreased with increasing age but this association was only statistically significant (P < 0.01) in CMVseropositive patients ( Figure 2E), and resulted in a significantly (P = 0.03) lower number of Tnaive at old age in CMV-seropositive patients (Table 3). Similar as observed in healthy individuals, the CD4 + T memory compartment ( Figure 1E) and its subsets ( Figure  2E-H) remained stable with age, irrespective of CMV-serostatus. The influence of CMV-seropositivity on differentiation to an effector memory phenotype was less clear in ESRD patients, compared to healthy individuals.

The CD8 + Tnaive population showed a very significant age-related decrease, irrespective of CMV-serostatus and with a similar slope as healthy individuals. At all ages, CD8 + T lymphocytes of CMV-seropositive ESRD patients are significantly higher due to an increased Tmem when compared to their seronegative counterparts similar to healthy donors. The Tmem does not increase with age ( Figure 3J) as was observed for CMVseropositive healthy individuals. At young age, CD8 + Temra and Tmem are approximately 6-and 1.6-fold increased whereas at old age the values are 5.5-and 1.7fold ( Table 3). The decrease of Tnaive cell numbers but unchanged Tmem subsets led to a significant age-related decrease of total CD8 + T cell numbers in ESRD patients ( Figure 1F).

CMV seropositivity and ESRD increase CD57 expression and loss of CD28 on memory T cells

Markers specific for terminal differentiation of T lymphocytes, i.e. loss of CD28 expression (CD28null) and percentages CD57 + T lymphocytes are specifically higher within CD4 + Tmem of CMV-seropositive healthy individuals. Similar results were obtained for percentages of CD28null, but not CD57 + , Tmem cells within the CD8 + T lymphocyte compartment. With increasing age, these markers remained stable (Table 2).

Similar to the healthy counterparts, significantly higher percentages of CD28null and CD57 + in both CD4 + and CD8 + Tmem lymphocytes were observed in CMV-seropositive ESRD patients (Table 3). Moreover in contrast to healthy donors, a significant increase in percentages of CD28null CD4 + Tmem was observed when old ESRD patients were compared to young ones ( Table  3, 11.9% to 4.0%, p < 0.001). Also, the percentage of CD57 positive CD4 + Tmem was significantly higher in CMV-seropositive ESRD patients as compared to healthy controls (at young age 34.0% versus 18.1% and at old age 35.7% versus 13.2% for CMV-seropositive ESRD patients and CMV-seropositive healthy donors, respectively, p < 0.01.)

Discussion

In this study we have analyzed the differential and combined effects of age, CMV latency and loss of renal function on numbers and composition of the various T lymphocytes. The results show that CMV latency, defined by CMV seropositivity, has a major impact on circulating T cell numbers, composition and age-related effects of the immune system. Moreover, CMV aggravates some pre-existing changes in the T cell compartment of ESRD patients. A remarkably stable composition of the CD4 + T cell compartment was noted in CMV-seronegative healthy donors over an age span of at least 5 decades. Both total number of CD4 + T cells and relative distribution remained unchanged in the elderly population. In contrast, the CD8 + naive T cell subset showed a major age-related decline while the memory compartment remained stable with respect to differentiation and expressing of ageing markers CD28null and CD57. The preferential age-related decrease of CD8 Tnaive cells is in accordance with previous studies [18] and, although speculative, may be caused by a higher antigen driven turnover of these cells as compared to CD4 + T naive cells.

CMV-seropositivity has a large effect on CD4 + and CD8 + T cell subsets at all ages in healthy individuals. It is associated with increased numbers of all CD4 + T cells  at young age and smaller numbers at old age, in particular within the Tnaive cell subset.

CMV-seropositivity was associated with a different effect on CD8 + T cells, as only the memory T cell compartement was significantly and stably expanded. The slope of the age-related decline of CD8 Tnaive was not affected by CMV-seropositivity. Confirming previous results, the appearance of CD28null cells within the CD4 + Tmem cell compartment seemed pathognomonic for CMV-seropositivity, but was unaffected by increasing age [15,17,19]. Overall, the results indicated that loss of CD28 expression and increased expression of CD57 on CD4 + and CD8 + T cells was highly associated with CMV-seropositivity. These markers should therefore be interpretated with care in clinical studies that study the ageing of T cells, taking into account the potential confounder of increasing prevalence of CMV-seropositivity with age. Hypothetical extrapolation of the regression lines of the total CD4 + and CD8 + T cell (sub) populations beyond 80 years results in a lowered CD4/CD8 T cell ratio, lowered Tnaive cell numbers and an increased percentage of memory T cells with a higher percentage of CD28null cells. These findings have indeed been described in the healthy very old and specifically in relation with CMV-seropositivity [11,20,21]. Therefore, it seems likely that the changes seen in the age span from 20 to 80 years continue within the ninth and tenth decade. The CMV-seropositivity related changes of the T cell immune system at old age are associated with an increased risk for mortality and therefore seem to be of clinical significance. Destabilization of atherosclerotic plaques by CD4 + CD28null T cells [17] or immune suppressor activity of CD8 + CD28null T cells [22,23] may explain this increased risk for mortality in elderly CMVseropositive individuals.

The age-related decrease in the number of CD4 + and CD8 + Tnaive cells with CMV-seropositivity explains the reported age-related increased of memory T cells when percentages and not absolute numbers of cells are used [24]. However, studies involving human subjects that have reported absolute numbers of circulating T cell subsets in relation to age and CMV seropositivity are scarce [15,16]. As our results clearly show, latency for CMV is associated with a stable increase of memory CD8 + T cells and an increase of memory CD4 + T cells at young age. This is in sharp contrast to the results from the study by Chidrawar [16], which may be explained by the relative low number of young CMVseropositive individuals in this study, but similar to data obtained by Looney et al. [15].

It is known that CMV antigen-specific T cells may be present at a high frequency within the pool of circulating CD4 + and CD8 + T cells [25,26], but our results are not in support of a limited immunological space [24,27]  but actually show expansion of the T cell population under influence of CMV latency. The relative large CMV-related increase in total T cell numbers (> 30%) indicate a bystander effect on other T cells [10] which is in accordance with the discrepancy noted between e.g. the percentage of CMV-specific CD4 + T cells and the higher percentage of CD4 + CD28null cells [17,28]. In addition to the pleiotropic effects of CMV-seropositivity on T cell subsets in relation with age, the effects in ESRD patients are again different. ESRD patients have a remarkable contracted population of naive CD4 + and CD8 + T cells at all ages. The causes of this Tnaive lymphopenia are not certain but may involve reduced thymic output, lack of IL-7 and increased activationinduced apoptosis in ESRD patients [7,8]. Most strikingly, the association between CMV-seropositivity and increased expansion of CD4 + T cells at young age was not observed in ESRD patients. In addition, independent of CMV-seropositivity an age-related progressive decline of an already contracted naive CD4 + T cell at young age was observed. However, CMV-seropositivity showed an add-on effect on CD4 + Tnaive lymphopenia and was associated with the development of terminally differentiated effector-memory T cells in both the CD4 + and CD8 + compartment. Similar to healthy individuals, the appearance of CD28null T cells and increased CD57 expression was highly associated with CMV seropositivity. In CMV-seropositive ESRD patients, the percentage of CD57 positive cells was significantly higher and the percentage of CD4 + CD28null T cells increased with age. Overall, CMV-seropositivity aggravates the ESRD-related changes of the T cell immune system.

A unifying hypothesis may be that frequent CMV reactivation [29], [30,31] causes a lifetime activation of the immune system with an initial increase of CD4 + T cells at young age but over the years exhaustion of replicative capacity with progressive decrease of naive T cells [32][33][34]. In ESRD a similar process occurs with continuous T cell activation possibly by the pro-inflammatory state of uremia and increased susceptibility for activation induced cell death. The net effect is severe Tnaive cell depletion and increased numbers of terminally differentiated CD4 + and CD8 + memory T cells which is aggravated by CMV reactivation. CMV reactivation is triggered by inflammatory stimuli creating the possibility that the pro-inflammatory condition of ESRD patients leads to more frequent subclinical CMV reactivation and even CMV disease [14,35].

The negative association of an CMV associated immune risk profile with survival in the very old is known and is likely also of clinical importance, but at a much earlier age, in ESRD patients. Understanding the combined effects of age, CMV seropositivity and ESRD on T cell immunity may help to identify patients at risk for a decreased vaccination response [36,37], at risk for cardiovascular events [17], and may guide patient-tailored immune suppression after kidney transplantation [38].

Figure 1
1Age-related effects of CMV on composition of T lymphocytes. The lines of the best fits are shown for absolute numbers of T lymphocytes (A, D), CD4 + (B, E) and CD8 + T lymphocytes (C, F) of healthy volunteers (A, B, C) and ESRD patients (D, E, F) against age on X-axis and CMV serostatus (dotted line = CMV seropositive and closed line = CMV seronegative).

Figure 2 Figure 3
23Age-related effects of CMV on CD4 + T cell subsets. The lines of the best fits are shown for absolute numbers of CD4 + Tnaive (A, E), Tcm (B, F), Tem (C, G) and Tmem (D, H) of healthy volunteers (A, B, C, D) and ESRD patients (E, F, G, H) against age on X-axis and CMV serostatus (dotted line = CMV seropositive and closed line = CMV seronegative). Age-related effects of CMV on CD8 + T cell subsets. The lines of the best fits are shown for absolute numbers of CD8 + Tnaive (A, F), Tcm (B, G), Tem (C, H), Temra (D, I) and Tmem (E, J) of healthy volunteers (A, B, C, D, E) and ESRD patients (F, G, H, I, J) against age on X-axis and CMV serostatus (dotted line = CMV seropositive and closed line = CMV seronegative).

Table 1
1Study population characteristics * values are median (range), percentages are means. Distribution of gender and CMV-seropositivity within the healthy donor and ESRD patients was tested using the Chi-square test. Gender did not significantly alter the composition of T lymphocyte subsets. Comparison between the healthy donors and ESRD patients with respect to age, CMV-serology was tested using the Mann-Whitney U-test.ESRD patients
healthy controls
P-value

Table 2
2The effect of age and cytomegalovirus (CMV) serostatus on the various T lymphocytes for healthy donors absolute values are 10 6 /mL, Tmem is sum of Tcm+Tem or sum of Tcm+Tem+Temra for CD4 and CD8 T lymphocytes, respectively. * are percentages of CD4+ and CD8+ Tmem lymphocytes, respectively. P-values represent the comparison between CMV-and CMV+.young (20-40 yrs)
elderly (> 60 yrs)

CMV-(N = 15)
CMV+ (N = 17)
CMV-(N = 21)
CMV+ (N = 23)
mean ± SEM
mean ± SEM
P-value
mean ± SEM
mean ± SEM
P-value

T lymphocytes
0.77 ± 0.07
1.39 ± 0.13
<0.01
0.91 ± 0.1
1.03 ± 0.09
0.19

CD4 + T lymphocytes
0.49 ± 0.06
0.86 ± 0.09
<0.01
0.63 ± 0.08
0.63 ± 0.06
0.74

Tnaive
0.17 ± 0.02
0.36 ± 0.05
0.01
0.25 ± 0.05
0.21 ± 0.03
0.61

Tcm
0.2 ± 0.03
0.26 ± 0.02
0.08
0.21 ± 0.02
0.23 ± 0.03
0.91

Tem
0.07 ± 0.01
0.15 ± 0.02
<0.01
0.08 ± 0.01
0.11 ± 0.01
0.05
Tmem
0.27 ± 0.04
0.4 ± 0.04
0.02
0.29 ± 0.03
0.34 ± 0.04
0.38

*CD28null
0.11 ± 0.02
4.21 ± 0.98
<0.01
0.34 ± 0.17
4.73 ± 1.36
<0.01

*CD57 +
5.23 ± 0.71
18.11 ± 3.88
0.04
6.46 ± 0.69
13.18 ± 3.77
0.34

CD8 + T lymphocytes
0.23 ± 0.02
0.42 ± 0.04
<0.01
0.22 ± 0.03
0.34 ± 0.03
<0.01

Tnaive
0.15 ± 0.03
0.22 ± 0.04
0.28
0.06 ± 0.01
0.06 ± 0.01
0.54

Tcm
0.04 ± 0.01
0.04 ± 0.01
0.77
0.05 ± 0.01
0.08 ± 0.02
0.55

Tem
0.06 ± 0.01
0.09 ± 0.02
0.08
0.07 ± 0.01
0.11 ± 0.02
0.05

Temra
0.04 ± 0.01
0.09 ± 0.02
0.01
0.06 ± 0.02
0.11 ± 0.02
0.01
Tmem
0.14 ± 0.01
0.23 ± 0.03
0.01
0.18 ± 0.03
0.3 ± 0.03
<0.01

*CD28null
31.89 ± 5.12
47.82 ± 4.13
0.04
27.78 ± 3.52
43.28 ± 4.47
0.02

*CD57 +
38.39 ± 8.67
49.63 ± 6.14
0.34
29.21 ± 2.79
49.65 ± 9.38
0.03

CD4/CD8 ratio
2.06 ± 0.35
2.13 ± 0.18
0.571
3.58 ± 0.38
2.05 ± 0.20
<0.01

Litjens et al. Immunity & Ageing 2011, 8:2
http://www.immunityageing.com/content/8/1/2

Table 3
3The effect of age and cytomegalovirus (CMV) serostatus on the various T lymphocytes for ESRD patients absolute values are 10 6 /mL, Tmem is sum of Tcm+Tem or sum of Tcm+Tem+Temra for CD4 and CD8 T lymphocytes, respectively. * are percentages of CD4+ and CD8+ Tmem lymphocytes, respectively. P-values represent the comparison between CMV-and CMV+young (20-40 yrs)
elderly (> 60 yrs)

CMV-(N = 27)
CMV+ (N = 23)
CMV-(N = 15)
CMV+ (N = 25)
mean ± SEM
mean ± SEM
P-value
mean ± SEM
mean ± SEM
P-value

T lymphocytes
0.72 ± 0.08
0.86 ± 0.1
0.47
0.48 ± 0.04
0.6 ± 0.04
0.09

CD4 + T lymphocytes
0.46 ± 0.05
0.46 ± 0.06
0.90
0.35 ± 0.03
0.36 ± 0.03
0.87

Tnaive
0.2 ± 0.03
0.17 ± 0.04
0.73
0.13 ± 0.02
0.08 ± 0.01
0.03

Tcm
0.15 ± 0.02
0.14 ± 0.02
0.61
0.13 ± 0.02
0.13 ± 0.02
0.85

Tem
0.07 ± 0.01
0.09 ± 0.02
0.52
0.06 ± 0.01
0.09 ± 0.01
0.01
Tmem
0.21 ± 0.02
0.23 ± 0.03
0.93
0.18 ± 0.03
0.22 ± 0.02
0.28

*CD28null
0.05 ± 0.01
4.05 ± 0.83
<0.01
0.82 ± 0.69
11.91 ± 2.79
<0.01

*CD57 +
9.93 ± 1.24
34.02 ± 7.09
<0.01
7.61 ± 1.77
35.71 ± 7.15
<0.01

CD8 + T lymphocytes
0.23 ± 0.03
0.34 ± 0.04
0.02
0.17 ± 0.02
0.22 ± 0.03
<0.01

Tnaive
0.13 ± 0.02
0.11 ± 0.01
0.64
0.03 ± 0.01
0.03 ± 0.01
0.51

Tcm
0.04 ± 0.01
0.03 ± 0.01
0.59
0.04 ± 0.01
0.03 ± 0.01
0.64

Tem
0.07 ± 0.02
0.07 ± 0.02
0.73
0.06 ± 0.01
0.06 ± 0.01
0.76

Temra
0.02 ± 0.01
0.12 ± 0.02
<0.01
0.02 ± 0.01
0.11 ± 0.02
<0.01
Tmem
0.13 ± 0.03
0.22 ± 0.04
0.03
0.12 ± 0.02
0.19 ± 0.03
0.02

*CD28null
26.73 ± 2.82
50.95 ± 5.55
<0.01
24.92 ± 3.51
50.45 ± 4.44
<0.01

*CD57 +
26.71 ± 5.11
68.12 ± 6.7
<0.01
34.09 ± 4.83
55.22 ± 7.26
0.06

CD4/CD8 ratio
2.32 ± 0.27
1.62 ± 0.18
<0.01
4.37 ± 0.90
2.0 ± 0.20
<0.01

Litjens et al. Immunity & Ageing 2011, 8:2 http://www.immunityageing.com/content/8/1/2
Conflict of interest statementThe authors declare that they have no competing interests.Authors' contributions NL designed the study, performed the experiments, statistical analyses and drafted the manuscript, EdW performed the experiments and MB designed the study and drafted the manuscript. All authors read and approved the final manuscript.
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Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution. Litjens, Immunity & Ageing. 82Differential effects of age, cytomegalovirus-seropositivity and end-stage renal disease (ESRD) on circulating T lymphocyte subsets. Submit your manuscript at www.biomedcentral.com/submitCite this article as: Litjens et al.: Differential effects of age, cytomegalovirus-seropositivity and end-stage renal disease (ESRD) on circulating T lymphocyte subsets. Immunity & Ageing 2011 8:2. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit


Removal of SDS from biological protein digests for proteomic analysis by mass spectrometry

Soundharrajan Ilavenil
Naif†
Abdullah Al-Dhabi
†
Srisesharam Srigopalram
Young Ock Kim
Paul Agastian
Rajasekhar Baaru
Ki Choon Choi
Mariadhas Valan Arasu
Chun Geon Park
Kyung Hun Park
Removal of SDS from biological protein digests for proteomic analysis by mass spectrometry
10.1186/s12953-016-0098-5R E S E A R C H Open Access
Background: Metal-organic frameworks (MOFs -MIL-101) are the most exciting, high profiled developments in nanotechnology in the last ten years, and it attracted considerable attention owing to their uniform nanoporosity, large surface area, outer-surface modification and in-pore functionality for tailoring the chemical properties of the material for anchoring specific guest moieties. MOF's have been particularly highlighted for their excellent gas storage and separation properties. Recently biomolecules-based MOF's were used as nanoencapsulators for antitumor and antiretroviral controlled drug delivery studies. However, usage of MOF material for removal of ionic detergent-SDS from biological samples has not been reported to date. Here, first time we demonstrate its novel applications in biological sample preparation for mass spectrometry analysis. Methods: SDS removal using MIL-101 was assessed for proteomic analysis by mass spectrometry. We analysed removal of SDS from 0.5 % SDS solution alone, BSA mixture and HMEC cells lysate protein mixture. The removal of SDS by MIL-101 was confirmed by MALDI-TOF-MS and LC-MS techniques. Results: In an initial demonstration, SDS has removed effectively from 0.5 % SDS solution by MIL-101via its binding attraction with SDS. Further, the experiment also confirmed that MIL-101 strongly removed the SDS from BSA and cell lysate mixtures. Conclusions: These results suggest that SDS removal by the MIL-101 method is a practical, simple and broad applicable in proteomic sample processing for MALDI-TOF-MS and LC-MS analysis.

Background Metals organic frameworks (MOF) are nano-porous compounds that contain metal ions or clusters that are connected by organic ligands to forms two or three dimensional structures. Last 10 years, MOFs are most potential compounds in hydrogen storage [1,2], CO 2 capture [3,4], catalysis [5,6], sensing [7], and others [8]. It has highly porous nature that makes very attractive for catalysis applications. In addition, MOFs have large diversity in nature as compared to Zeolites due to the use of SiO4/AlO4 tetrahedral building units in the later materials. The catalytic applications of zeolites are more restricted to relatively small organic molecules (typically no larger than xylene) because due to its microporous in nature. Whereas, the size of pore, shape, dimensionality and chemical natures in MOFs have been controlled by the suitable selection of their building blocks (metal and organic linker). Apart from these features, the lower acidity of the active centers in MOFs makes these materials even very attractive compared Zeolites (highly acidic centers). Also, MOFs may be changing the interactions of adsorbing reactants and the transition states or intermediaries formed inside the framework cavity between the host and guest.

The fundamental step of global proteomics experiments, particularly involving sensitive MS technique is efficient sample preparation. Extraction of total proteins from various biological sources including tissues and cultured cells using SDS-Sodium Dodecyl Sulfate, CHAPS, and Triton is well known in several biochemical studies. SDS is widely used and considered to be very beneficial due to complete cell lysis, disaggregation and efficient solubilization of the global proteome primarily hydrophobic membrane-bound components. SDS interacted with proteins by ionic and hydrophobic bonds and dissolves proteins by changing their secondary and tertiary structures [9]. Further, it plays an important role in studies of membrane proteins or aggregated proteins, because of these proteins are not soluble in other agents. In addition, SDS continuously used in protein separations from biological samples by sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) method. Unfortunately, SDS in the samples can be unfavourable due to its unwanted effects in liquid chromatography and it produces large DS − related signals and ion suppression effects [10,11]. Therefore, SDS removal is an essential prerequisite for achieving higher peptide/protein coverage in the mass-spectrometric analysis. It can be accomplished by numerous techniques such as precipitation, strong cation exchange, protein and peptide level purification with pierce detergent removal cartridges and FASP II etc. [12]. Gu et al. 2011 [13] reported that the MOFs based material is very useful for biological applications. But, usage of MOFs material for removal of ionic detergent-SDS from biological samples has not been reported to date. Therefore, we tried to find out a novel method for removal of ionic detergent-SDS from biological samples by microdevices based MOFs material for proteomic analysis.

Results and discussion

Standard sample cleans up with different solid phase extraction (SPE) or desalting methods have not been much effective in SDS depletion to date; prompting the investigation of various methods for SDS removal will make several commercial products [14], Filter aided sample preparation (FASP) [15], high salt precipitation kits [16], and SDS specific binding spin cartridges are very famous methods for depletion of detergent from protein mixtures for proteomic sample preparation. However, a majority of techniques are hindered by low protein recovery, labour intensiveness, irreproducibility and incomplete SDS removal. To these address, we tried to find out a novel and efficient method for SDS removal.

Here we used MOFs (MIL-101) as a binding material for SDS removal from the biological samples by micro-device based method. Our preliminary results were highly encouraged and demonstrated a novel biological application of MOF materials which could have significant value in sample processing i.e SDS depletion for MALDI-TOF and LC-MS analysis.

SDS removal from 0.5 % SDS solution using MIL-101

First, we tried to remove the SDS from 0.5 % SDS solution using MIL-101 as a binding material. Presently, this method has not been applied for removing SDS during proteomic analysis by the mass spectroscopy. Thus, we designed and used this method for SDS removable from biological protein mixture before MALDI-TOF-MS analysis. Initially, we removed the SDS from 0.5 % SDS solution with the help of MIL-101 material by centrifugation at 3000 rpm and the results exhibited that maximum concentration of SDS was removed as evidence the peak intensity of SDS at 287.89[M + H] was differed and clear in after removal of SDS ( Fig. 1a & b). This result suggests that for the solution containing SDS can be removed by MIL-101 material.

SDS removal from BSA mixtures using MIL-101

Further, we analysed capability of MIL-101 for removal of SDS from bovine serum albumin. Different concentration of BSA was mixed with 0.5 % of SDS. Then BSA in SDS mixture was treated with MIL-101 for overnight and then centrifuged at 3000 rpm prior to MALDI-TOF-MS analysis. Generally, SDS acts as a potent surfactant that could be denatured the trypsin activity when digestion process. But, we observed good signalling intensity for BSA tryptic peptides. It indicated that MIL-101 has an ability to remove the SDS from single protein mixture with robust trypsin activity (Fig. 2a).

SDS removal from cell lysate protein mixture using MIL-101

Further, we planned to assess the weather MIL-101 have an ability to remove the SDS from cell lysate protein mixtures or not, because it is very complicated and little difficult to separate SDS from the biological samples as compared with single protein mixtures. So, we prepared protein extract from HMEC cells and mixed with 0.5 % boiling SDS. This mixture was incubated with 30 mg of MIL-101 slurry with end-over-end rotation overnight. Proteins were further separated from MIL-101 by centrifugation at 3000 rpm for 5 min. Supernatant containing protein mixture was processed for MALDI-TOF-MS analysis. This result suggests that MIL-101 has effectively removed SDS from cell lysate protein mixtures (Fig. 2b).

LC-MS analysis of tryptic peptides

Finally, the processed sample was subjected to LC-MS analysis. The result indicates that MIL-101 processed sample shows little ion suppression effect only. It may be due to trace amount of SDS was found in the samples. Overall MIL-101 effectively removed SDS from cell lysate by its binding efficiency (Fig. 3a). Figure 3b demonstrated the number of proteins with 1 or 2 unique peptide matches, Totally 750 protein were identified; among them 438 proteins having two peptide matches and 319 proteins having one peptide hits. Figure 3c demonstrated the GO (Gene Ontology) based annotations and cellular distribution of identified proteins. From our preliminary analysis, we hypothesize that MIL-101 is an attractive MOFs candidate for SDS removal from biological proteins before MS analyses.

Conclusions

The MIL-101 is an attractive MOFs candidate for removing SDS from biological samples through its electrostatic interactions. All the experimental results suggested that MIL-101 method could be a very useful method to prepare biological sample preparations for spectroscopy based proteomic analysis.  Then, the sample was centrifuged at 3000 rpm for 5 min and then subjected to MALDI-TOF analysis.

Methods

Chemical

SDS removal from BSA mixture

Different concentrations of BSA (5, 10, 25 μg) were mixed with the freshly prepared SDS (0.5 % SDS w/v) and was further incubated overnight with the slurry prepared using 100 μg MIL-101 with one ml of freshly prepared ice cold phosphate buffer and reduced with 10 mM DTT. Later, the sample was subjected to in-solution digestion using trypsin and peptides were desalted and then loaded into MALDI-TOF analysis.

SDS removal from cell lysate mixture HMEC cells were lysed using 0.5 % boiling SDS and sonicated to clear the chromatin. Lysate protein was estimated by BCA method and incubated with MIL-101 matrix (100 μg slurry) at room temperature for overnight to SDS attraction by the MOF and then separated by centrifugation. Protein mixture was in-solution digested, desalted and then subjected into MALDI-TOF and LCMS analysis. An outline of the work flow was illustrated in Fig. 4a-b.

MALDI-TOF analysis

Peptide mass fingerprinting (PMF) was conducted using MALDI-TOF-MS equipped with linear mode 20 KvA, laser shots 150 (337 nm, 50 H, N2 laser (Bruker Daltonics, Germany). For, each sample spectra required in the positive linear mode, and an average of 200 spectra that passed the accepted criteria of peak intensity was automatically selected and accumulated. Spectrum processing and data base searches were conducted b automatic mode with internal calibration using trypsin autolysis peaks (m/z 842.509 and m/z 2211.104). The fragmentation of selected peptide was measured using the PSD mode for MS analysis [17].

LC-MS analysis

The peptides were analysed using a reverse phase capillary column (LC system -LTQ; Thermo Scientific, San Jose, CA) prepared by slurry packing 3-μM Jupiter C18 bonded particles into a 65 cm long and 75 μM inner  diameter fused silica capillary. 2.5 μg of peptides were loaded onto the column; the mobile phase was held at 100 % buffer A (0.1 % formic acid) for 20 min, followed by a linear gradient from 0 to 70 % buffer B(0.1 % formic acid in 90 % acetonitrile) for more than 85 min. Each full MS scan (m/z 400-2000) was followed by collision induced MS/MS spectra. The dynamic exclusion duration was set to 1 min; the heated capillary was maintained at 200°C and the ESI voltage was held at 2.2 kV [18].

Abbreviations: SDS, Sodium dodecyl sulfate; MOFs, Metal organic frameworks; HMEC, Human mammary epithelial cells; MALDI-TOF, Matrix assisted laser desorption/ionization-time of flight; BSA, Bovine serum albumin; DTT, Dithiothreitol; GO, Gene ontology; LC-MS, Liquid chromatography-mass spectrometry; FASP, Filter aided sample preparation); SPE, Solid phase extraction; CHAPS, 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate

BCA kit and HMEC cells were purchased from Thermo Fisher Scientific and American Type Culture Collection[Rockwille, MD, USA] respectively. SDS, Trypsin, BSA and DTT obtained from Sigma-Aldrich, USA. MIL-101 was from sigma product # 185361[Final concentration 100 μg/ml] and Microdevices obtained from Mobitec; product code: MobiSpin Column F (1.5 ml tubes). SDS removal from 0.5 % SDS solution MIL-101 (100 μg slurry) was mixed with 0.5 % SDS solution and incubated at room temperature for overnight.

Fig. 1 a
1-b SDS m/z intensity, before and After SDS removal by MIL-101, data acquired on MALDI-TOF MS

Fig. 2 a
2PMF profile of SDS removed BSA tryptic digest mixture using MALDI-TOF. b PMF profile of SDS depleted tryptic digest mixture using MALDI-TOF

Fig. 3 a
3Liquid Chromatogram separations of SDS removed tryptic. b Number of proteins with 1 or 2 unique peptide matches. c GO based annotations and cellular distribution

Fig. 4 a
4Work flow of SDS removal from a complex lysate mixture. Microdevices based b SDS removal using MIL-101, SDS was bound to MOF and proteins were separated by Centrifugation for downstream analysis
Availability of data and materialsAll data and materials were given in the manuscript. We don't have further data and materials.Authors' contributions NAA-D, YOK and MVA were planned and executed the laboratory experiments. SI, MVA, PA, RB, KCC CGP, SS, and KHP participated in data analysis, results interpretation, and chemicals arrangement. All listed authors were contributed to this research work and accepted the final manuscript for publications. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participate Not applicable. • We accept pre-submission inquiries • Our selector tool helps you to find the most relevant journal Submit your next manuscript to BioMed Central and we will help you at every step:
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