The frequency of CD127low expressing CD4+CD25high T regulatory cells is inversely correlated with human T lymphotrophic virus type-1 (HTLV-1) proviral load in HTLV-1-infection and HTLV-1-associated myelopathy/tropical spastic paraparesis

Background CD4+CD25high regulatory T (TReg) cells modulate antigen-specific T cell responses, and can suppress anti-viral immunity. In HTLV-1 infection, a selective decrease in the function of TReg cell mediated HTLV-1-tax inhibition of FOXP3 expression has been described. The purpose of this study was to assess the frequency and phenotype of TReg cells in HTLV-1 asymptomatic carriers and in HTLV-1-associated neurological disease (HAM/TSP) patients, and to correlate with measures of T cell activation. Results We were able to confirm that HTLV-I drives activation, spontaneous IFNγ production, and proliferation of CD4+ T cells. We also observed a significantly lower proportion of CTLA-4+ TReg cells (CD4+CD25high T cells) in subjects with HAM/TSP patients compared to healthy controls. Ki-67 expression was negatively correlated to the frequency of CTLA-4+ TReg cells in HAM/TSP only, although Ki-67 expression was inversely correlated with the percentage of CD127low TReg cells in healthy control subjects. Finally, the proportion of CD127low TReg cells correlated inversely with HTLV-1 proviral load. Conclusion Taken together, the results suggest that TReg cells may be subverted in HAM/TSP patients, which could explain the marked cellular activation, spontaneous cytokine production, and proliferation of CD4+ T cells, in particular those expressing the CD25highCD127low phenotype. TReg cells represent a potential target for therapeutic intervention for patients with HTLV-1-related neurological diseases.


Background
Between 10 and 20 million people are infected with HTLV-1 worldwide [1]. Although most subjects are clinically asymptomatic during their lifetime, a proportion (5 to 10%) develop adult T cell leukemia/lymphoma (ATLL) or HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP) [2]. Epidemiological surveys have identified regions in the world where prevalence rates are considerably higher, including Japan, the Caribbean, South America, Africa, Melanesia and the Middle East [1,3]. It has been estimated that the prevalence of HTLV-1 infection in South America ranges from 2 to 5% [4], with an estimated 1-2 million infected people in Brazil [5]. The prevalence in blood donors ranges from 0.17 to 1.8% in different areas of the country [6,7], with a 0.3% seroprevalence in the city of Sao Paulo blood donors [8].
HTVL-1 is a retrovirus encoding the group specific antigen (gag), protease (pro), polymerase (pol), and envelope (env) genes. Six proteins are encoded by the pX region of the genome, including the Tax protein, which is critical to viral replication and induction of cellular activation and transformation, increasing the expression and production of cytokines and receptors involved in T cell growth and transformation, such as IL-15 [9,10] and IL-2 [11][12][13]. Tax also has the ability of interfering in the expression of several transcription factors and proto-oncogenes, as well as in the nucleic acid repair and apoptosis [14][15][16][17]. These effects combined seem to play a key role in the potential of HTLV-1 to induce cellular transformation and, consequently, trigger the development of ATLL.
It has been previously demonstrated that HTLV-1 proviral load is one of the key factors in the pathogenesis of HAM/ TSP [18,19], although host genetic factors are also independently associated with the development of the diseases, e.g. certain HLA [20,21] and non-HLA [22,23] genes. These invoke the hypothesis that both viral and genetic host factors are implicated in the pathogenesis of HAM/TSP.
The CD8 + T cell response to HTLV-1 can be readily detected [24][25][26][27][28][29][30][31], commonly directed against the HTLV-1tax protein. The contribution of the CD8 + T cell response might be particularly important for viral control in HTLV-1 infection, since infected lymphocytes produce virtually no cell-free infectious HTLV-1 particles. However, it is noteworthy that the magnitude of the HTLV-1-specific T cell response is associated with higher proviral loads, highlighting the fact that T cells frequencies are determined by proviral load, as well as being a determinant of proviral load. CD4 + T cells are the main target for HTLV-1 infection, which induces CD4 + T cell activation, including proliferation and IFNγ production. The HTLV-1-specific CD4 + T cell response is directed mainly against Env, the HTLV-1 envelope surface [32].
T Reg cells are crucial for the control of autoimmune disease and maintenance of peripheral T cell tolerance (reviewed in Sakagushi et al. [33]). In addition, they can suppress pathogen-specific T cell responses, including response to viruses [34][35][36][37]. The mechanisms whereby T Reg cells suppress T cell responses are not yet fully understood, but are likely to include both soluble factors, e.g. IL-10 and TGFβ, as well as cell-cell contact dependent mechanisms, e.g.
through CTLA-4. CTLA-4 (CD152) is expressed by a large fraction of CD4 + CD25 + T cells, and by a majority of CD4 + CD25 high T cells. CTLA-4 has also been shown to be one of mediators of T Reg function [38,39], and is considered a marker for T Reg cells. In addition, it was recently demonstrated that T Reg cells are characterized by low levels of the IL-7Rα (CD127 low ) [40][41][42], which together with CD25 help to distinguish T Reg cells from activated normal CD4 + T cells in healthy individuals. FOXP3 is a key regulator of T Reg cell function, but is not exclusive to T Reg cells; it has been identified in human nonregulatory activated CD4 + FoxP3 + T cells. Humans with mutations in FOXP3 present with a syndrome characterized by severe autoimmune and inflammatory disorders often early in life, denominated IPEX [33]. Interestingly, it was recently shown that HTLV-1 tax can downregulate Foxp3 expression [43,44].
We hypothesized that HTLV-1 compromises T Reg cell function, resulting in higher T cell activation, which contributes to HAM/TSP development. We found a significantly higher frequency of CD4 + Ki-67 + T cells and a lower proportion of CTLA-4 + T Reg cells in subjects with HAM/TSP, compared to healthy controls. Moreover, we found an inverse correlation between HTLV-1 proviral load and frequency of CD127 low /CTLA-4 + T Reg cells. Our data suggest a role for T Reg cells in the pathogenesis of HAM/TSP, and reveal a potential new therapeutic target for patients with HAM/TSP.

Study subjects
Blood samples were collected at the Federal University of Sao Paulo outpatient clinics, after informed consent. PBMC were isolated by Ficoll-Paque PLUS density gradient centrifugation and cryopreserved. The demographics of the study subjects are shown in Table 1, including gender, age, proviral load, CD3, CD4 and CD8 absolute T cell counts. No statistically significant differences were observed in gender and age distribution among groups.

CD4+ T cell activation and IFNγ production in healthy donors, HTLV-1 seropositive asymptomatics, and HAM/ TSP patients
We initially investigated the expression of Ki-67, HLA-DR and CD38 on CD4 + T cells in PBMC from healthy donors (Control), HTLV-1 infected patients who were clinically asymptomatic (HTLV), or had associated neurological disease (HAM/TSP). HAM/TSP had significantly higher frequencies of CD4 + Ki-67 + T cells compared to HTLV or Control subjects (Fig. 1A, 1C). In addition, HAM/TSP patients had an increase in the frequency of CD4 + HLA-DR + T cells compared to Controls (Fig. 1E), whereas no statistically significant difference in frequency of CD4 + CD38 + T cells was noted (data not shown). Furthermore, CD4 + T cells from both HTLV and HAM/TSP groups had an increase in the spontaneous expression of IFNγ (Fig. 1B, 1D).

Decreased frequency of T Reg cells in HAM/TSP patients
In order to assess the frequency of T Reg cells in HTLV-1 infected subjects, we measured the expression of CD25, CTLA-4, CD127 and GITR on CD4 + T cells by flow cytometry. Gating strategies are shown in Fig. 2A-C. The frequency of CD4 + T cells expressing CD25 was very similar between the groups (Fig. 2D). As CD25 is upregulated on activated CD4 + T cells, and thus is not a specific marker for T Reg cells, we sought to determine the frequency of T Reg cells using more specific phenotypes. First, we analyzed the frequency of CD4 + CD25 high T cells, known to be composed mainly of T Reg cells [45], and no significant difference in the frequency of T Reg cells could be found between controls and HTLV-1 subjects (Fig. 2E). We determined the intracellular expression of CTLA-4 in CD4 + CD25 + , and CD4 + CD25 high T cells and observed a decrease in frequency of CTLA-4 + from HAM/TSP patients ( Fig. 2F and 2G). Next, we assessed the expression of CD127. HAM/ TSP patients had a statistically significant increase in the frequency of CD4 + CD25 + CD127 low T cells compared to Controls (Fig. 2H). In contrast, there was a slight decrease in frequency of CD4 + CD25 high CD127 low T cells in HTLV-1 infected groups, although this did not reach statistical significance (Fig. 2I). There were no differences in percent expression of GITR between the groups (Fig. 2J, 2K).

Decreased CTLA-4+ T Reg cells correlate with increased CD4+ T cell proliferation in HAM/TSP patients
Our initial analysis indicated that the frequency of CD4 + CD25 + CD127 low T cells was higher in HAM/TSP patients. However, there were a lower percentage of CTLA-4 + T Reg cells, indicating that HAM/TSP subjects might have  101  Control  Male  34  NA  690  389  1220  102  Control  Male  -NA  1116  525  1649  103  Control  Male  -NA  ---104  Control  Male  -NA  ---105  Control  Female  31  NA  ---106  Control  Female  28  NA  ---107 Control Expression of Ki-67, HLA-DR and spontaneous production of IFNγ by CD4 + T cells from Control, HTLV and HAM/TSP sub-jects

CD4
IFNγ γ γ γ  T Reg cells with a dysfunctional phenotype. Moreover, we showed that HAM/TSP patients had an increased proliferation and T cell activation, as evidenced by higher frequencies of HLA-DR, Ki-67 and INFγ-expressing CD4 + T cells. To test whether the higher frequency of T Reg cells was associated with lower levels of activation or proliferation of CD4 + T cells, we compared the frequency of CTLA-4 + , CD127 low or GITR + T Reg cells with the percentage of CD4 + Ki-67 + T cells. The frequency of CTLA-4 + T Reg was negatively correlated with the frequency of CD4 + Ki-67 + T cells in HAM/TSP patients only (Fig. 3A). In addition, there was a negative correlation between the frequency of CD127 low T Reg cells and the percentage of CD4 + Ki-67 + T cells in controls, whereas no such correlation was found in HTLV-1 infected subjects (Fig. 3B). There was no association between GITR + T Reg cells with the percentage of CD4 + Ki-67 + T cells in any group (Fig. 3C).

The frequency of CD4 + CD25 + CTLA-4 + and CD127 low T Reg cells was negatively correlated to HTLV-1 proviral load
Finally, we wanted to determine whether the frequency of T Reg cells was related to HTLV-1 proviral load. High CD4 + T cells activation and elevated HTLV-1 proviral load are observed in HAM/TSP. We hypothesized that this phenomenon would be related to a lower proportion of T Reg cells. We quantified HTLV-1 proviral load by real-time PCR and correlated it with the frequency of the different CD25-expressing CD4 + T cell subsets. There was no correlation between the frequency of CD4 + CD25 + or CD4 + CD25 high T cells with proviral load (Fig. 4A and 4B). In contrast, there was a negative correlation between the frequency of CD4 + CD25 + CTLA-4 + T cells and proviral load in HTLV only (Fig. 4C). Moreover, there was an inverse correlation between CD127 low T Reg cells and HTLV-1 proviral load (Fig. 4F).

Discussion
Regulatory T cells are important for the maintenance of peripheral T cell tolerance to self antigens, and can also suppress T cell responses to tumors, parasites, viruses and bacteria. In this study we addressed the relationship between T Reg cells, T cell activation, and HTLV-1 proviral load. Infection with HTLV-1 was associated with higher spontaneous IFNγ release by CD4 + T cells, but only in HAM/TSP there was a marked increase in T cell proliferation.
The HTLV-1 derived tax protein can downregulate expression of the FOXP3, which presence is associated with T Reg cell function [43,44]. Increased expression of tax can be expected in patients with HAM/TSP, who have higher proviral loads compared to asymptomatic carries. We observed a higher proportion of CD4 + IFNγ + T cells in HTLV-1 infected subjects, which could also be indicative of a decreased T Reg cell fraction. Interestingly, only the HAM/TSP patients presented with a higher cell proliferation, as measured by Ki-67 staining, which correlated markedly with HTLV-1 proviral load (data not shown). These observations suggest that HTLV-1 directly affects T Reg cell number, and as proviral load increases, not only is the control of IFNγ lost, but controls on cell proliferation as well. Our data, together with the recent findings that HTLV-1 tax downregulates FOXP3 expression, indicate that T Reg cell dysfunction can be a direct consequence of HTLV-1 infection.
In order to better understand the role of T Reg cells in HTLV-I infection and disease, we used CTLA-4 and CD127 staining in CD4 + CD25 high cells as markers for T Reg subsets. CD127 and CTLA-4 have been described as useful markers for T Reg , and facilitate the identification of T Reg cells, even without staining for FOXP3 [40]. In this study, we found that an increased frequency of CD127 low CD4 + CD25 + T Reg in controls correlated negatively with CD4 + T cell proliferation (Ki-67), indicating that these cells indeed have a regulatory immunophenotype. In contrast, increased frequency of these cells correlated with increased CD4 + T cell proliferation in HTLV-1 infected individuals, suggesting that these cells are not regulatory T cells in these individuals. In addiction, the elevated frequency of CTLA-4 + T Reg cells was negatively correlated to CD4 + T cell proliferation only in HAM/TSP patients, which suggest that it is a better immunophenotype of T Reg cells in HAM/TSP patients, but more studies are necessary to confirm this.
We could detect a negative association between the frequency of CTLA-4 + or CD127 low T Reg cells and proviral load, extending recent findings of an association between FOXP3 expression and HTLV-1 infection [44]. We speculate that therapeutic manipulation of regulatory T cells could positively impact disease pathogenesis. Two mechanisms might be involved, the first by suppressing the exuberant anti-HTLV-1 CD8 + T cell mediated immune response, and the second by suppression of CD4 + T cell proliferation, which can result in lower proviral load. However, stimulating an expansion of T Reg cells could also provide additional targets for HTLV-1 replication, so such studies should proceed with great caution.
In this study, there are some limitations. The study was cross sectional, and with a limited number of patients in each group. We hope that future longitudinal studies can assess changes in T Reg cells over time in HTLV-1 infected patients. We, and others, working in the regulatory T cells field, are limited by the lack of definitive phenotypic markers of T Reg , and CD4 + CD25 +/high remains the standard identifiers. In this study we have added other markers, but at the time the study was conducted, the FOXP3 antibody, commonly used to detect a T Reg cell population was not commercially available. However, this may have been Correlation between different immunophenotypes of T reg with expression of Ki-67 Figure 3 Correlation between different immunophenotypes of T reg with expression of Ki-67. Frequency of CTLA-4 + , CD127 low , or GITR + T reg were correlated with proportion of CD4 + Ki67 + T cells in Control (Blue diamond), HTLV (Green triangle) and HAM/TSP (Red circle). A. There was a negative correlation between CTLA-4 + T reg with percentage of CD4 + Ki67 + T cells in HAM/TSP only (r = -0.7833, p = 0.017). B. CD127 low T reg were inversely correlated with proportion of CD4 + Ki67 + T cells in Control group (r = -0.8108, p = 0.034). C. There was no association between GITR + T reg with percentage of CD4 + Ki67 + T cells in any group.

A C B
Correlation between HTLV-1 proviral load of HTLV (Green triangle), and HAM/TSP (Red circle) with expression of CD127 or CTLA-4 in CD25 + or CD25 high CD4 + T cells subsets

A B
C D E F a fortuitous event, as recent reports suggest that FOXP3 is also expressed on non regulatory T cells in humans [46,47]. As we did not have access to tissue samples from these subjects, we cannot exclude redistribution of cells out of the peripheral blood into tissues, and the study of regulatory T cells at secondary lymphoid sites and within CSF will be of interest for a future study of HTLV-1 associated disease.
In conclusion, our data suggest a role of T Reg cells in the pathogenesis of HAM/TSP. Further studies should help delineate the ability of expanded T Reg cells to affect T cell proliferation in HTLV-1 patients and the potential development of therapeutic modulation of regulatory T cells in HTLV-1 patients.

Conclusion
In this study, we showed that HTLV-I drives activation, spontaneous IFNγ production, and proliferation of CD4+ T cells. HAM/TSP patients have a decreased frequency of T Reg cells in peripheral blood, compared to healthy subjects, markedly in the CD4 + CD25 high CTLA + phenotype. The proportion of CD127 low T Reg cells correlated inversely with HTLV-1 proviral load. These results suggest that T Reg cells may be subverted in HAM/TSP patients, and contributes to the identification of novel therapeutic targets for patients with HTLV-1-related disease.

Study subjects
Three groups of volunteers were enrolled. The first consisted of seven HTLV-1-negative control volunteers; the second consisted of ten HTLV-1 seropositive volunteers without clinical and laboratory evidence of HTLV-1-associated disease, and the last group was composed of nine patients with the diagnosis of HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP). After approval by the Institutional Review Board, written informed consent was obtained from all the participants according to the guidelines of Brazilian Ministry of Health. Samples were collected in EDTA-treated vacuum tubes, and PBMC were frozen into liquid nitrogen after separation using a ficoll gradient.

DNA extraction and determination of HTLV-1 proviral load
HTLV-1 proviral DNA was extracted from PBMCs using a commercial kit (Qiagen GmbH, Hilden Germany) following the manufacturer's instructions. The extracted DNA was used as a template to amplify a fragment of 158 bp from the viral tax region using previously published primers [48]. The SYBR green real-time PCR assay was carried out in 25 μl PCR mixture containing 10× Tris (pH 8.3; Invitrogen, Brazil), 1.5 mM MgCl 2 , 0.2 μM of each primer, 0.2 mM of each dNTPs, SYBR Green (18.75 Units/r × n; Cambrex Bio Science, Rockland, ME) and 1 unit of platinum Taq polymerase (Invitrogen, Brazil). The amplification was performed in the Bio-Rad iCycler iQ system using an initial denaturation step at 95°C for 2 minutes, followed by 50 cycles of 95°C for 30 seconds, 57°C for 30 seconds and 72°C for 30 seconds. The human housekeeping β globin gene primers GH20 and PC04 [49] were used as an internal control calibrator. For each run, standard curves for the value of HTLV-1 tax were generated from MT-2 cells of log 10 dilutions (from 10 5 to 10 0 copy). The threshold cycle for each clinical sample was calculated by defining the point at which the fluorescence exceeded a threshold limit. Each sample was assayed in duplicate and the mean of the two values was considered as the copy number of the sample. The amount of HTLV-1 proviral load was calculated as follows: copy number of HTLV-1 (tax) per 1,000 cells = (copy number of HTLV-1 tax)/(copy number of β globin/2) × 1000 cells. The method could detect 1 copy per 10 3 PBMCs cells.

Flow cytometry
PBMCs were thawed and stained with directly conjugated antibodies. Three different panels of antibodies were used to evaluate the expression of proteins associated with T Reg cells and T cell activation. All antibodies were from BD Biosciences, unless otherwise noted. All panels contained PerCP-conjugated anti-CD4 and allophycocyanin-conjugated anti-CD25, and in addition contained (1)  . Cells stained with PerCP-conjugated anti-CD4 alone and allophycocyanin-conjugated CD25 alone were used to establish positive gates for FITC-and PE-conjugated antibodies. For panel 1 and 2, cells were stained with all antibodies in PBS supplemented with 0.5% bovine serum albumin (BSA) and 2 mM EDTA (FACS buffer), followed by two washes in FACS buffer and fixation in 1% paraformaldehyde (PFA). For panel 3, cells were first stained with PerCP-conjugated anti-CD4 and allophycocyanin-conjugated anti-CD25, followed by two washes in FACS buffer and fixation in 1% PFA. The cells were subsequently washed twice with PBS containing 0.1% saponin (perm buffer), prior to staining with PEconjugated anti-CD152 and FITC-conjugated anti-Ki-67 diluted in perm buffer. All samples were analyzed on a FACSCalibur flow cytometer (Becton Dickinson) equipped with a 488 nm argon and a 633 nm red-diode lasers for four color detection. Acquisition and analyses were performed using CellQuest software (Becton Dickinson). Fluorescence voltages and compensation values were determined using unstained cells and cells singlestained with each of the fluorochrome-conjugated antibodies, respectively. The gating strategy used was to gate on lymphocytes using a forward scatter versus side scatter gate, followed by gating on CD4 + cells. The gate for CD4 + CD25 + cells was set using cells cells stained with the PerCP-conjugated anti-CD4 antibody alone. Positive gates for the FITC-and PE-conjugated antibodies were set using cells stained with only PerCP-conjugated anti-CD4 and APC-conjugated anti-CD25 antibodies.

Cytokine flow cytometry
PBMCs were thawed and cultured for 24 hours in 96-well U-bottom plates at a concentration of 4 × 10 5 cells/well. Brefeldin A (BFA) was added at a concentration of 5 μg/ml for the last 5 hours of the culture. After culture, cells were harvested, stained with PE-conjugated anti-CD4, fixed in 4% PFA for 20 min, prior to being washed twice with perm buffer. The cells were subsequently stained with PerCP-conjugated anti-CD3 and allophycocyanin-conjugated anti-IFNγ, washed twice in perm buffer and resuspended in FACS buffer, prior to being analyzed on a FACSCalibur. All antibodies were from BD Biosciences.

Statistical analyses
Data sets were compiled and analyzed in Statistica, release 6.0 (Statsoft, Tulsa, OK) and Prism, release 4.0 (GraphPad Software, San Diego, CA). Groups comparisons were performed using non-parametric Kruskal Wallis ANOVA by ranks test; associations between variables were evaluated by Spearman rank order correlation's test. Critical p values were considered statistically significant if below 0.05.
JM planed and conducted the experiments, performed the statistical analyses, and wrote the manuscript; HMRB wrote the original protocol, collected the samples, prepared the database, helped in the experiments, performed statistical analyses, and wrote the manuscript; KAJ conducted the experiments and helped in the flow cytometry analyses; JMC conducted the experiments and helped in the flow cytometry analyses; MKCB conducted the experiments and helped in the flow cytometry analyses; WKN performed the HTLV-I viral load; YN supported the protocol design and the conduction of HTLV-I viral load; ECS performed the HTLV-I serology, helped in the project design, the molecular biology experiments, and writing the manuscript; MAC selected subjects for the cohort and supervised the blood collection of samples from HAM/ TSP patients; ASBO selected subjects for the cohort and supervised the blood collection of samples from HAM/ TSP patients; DFN participated in the experimental design, obtained funds for the project, discussed the results, and wrote the manuscript; EGK wrote the original protocol, participated in the experimental design, obtained funds for the project, discussed the results, and wrote the manuscript.
Publish with Bio Med Central and every scientist can read your work free of charge