An interesting group of HIV-1-infected individuals, termed HIV-1 controllers, natural HIV-1 suppressors, HIV-1 elite suppressors or elite controllers have spontaneous HIV-1 viral control of replication to <50 copies of HIV-1 RNA per milliliter plasma without antiretroviral therapy. The study of elite controllers provides a unique opportunity to gain knowledge about virological and immunological factors that are crucial for the control of HIV-1 infection.
Regulatory T cells (Tregs) regulate chronic inflammation by suppressing the activation and proliferation of effector lymphocytes.1 Evidence indicates that an imbalance between Tregs and effector lymphocytes is directly associated with the pathogenesis of chronic viral infections.2-4 However, the role of Tregs in HIV-1 pathogenesis is controversial. Some studies conclude that Tregs suppress the host adaptive antiviral immune response and are therefore considered harmful,5-12 Although others hold that Tregs prevent chronic immune activation and are therefore considered beneficial.13-19 To date, Tregs have not been directly correlated to HIV-1 disease progression. However, the role of Tregs to suppress effector lymphocytes together with the fact that T-cell activation is associated with HIV-1 disease progression makes the association between Tregs, T-cell activation and proliferation interesting to study.11,16,20,21-23
T-helper (TH) 17 cells may be an important T-cell population during HIV-1 infection because they enhance host defenses against microbial agents.24 Consequently, a severe lack of TH17 cells could lead to an increase in the susceptibility to opportunistic infections as is characteristic of untreated HIV-1 infection. TH17 cells have been implicated in the immunopathology of multiple chronic inflammatory diseases, but studies of TH17 cells in HIV-1 infection are few and conflicting.24-28
To gain insight into the role of regulatory and effector cells in spontaneous HIV-1 control, we investigated the frequency of Tregs and TH17 cells in peripheral blood mononuclear cells (PBMCs) from 3 different groups of individuals infected with HIV-1: treatment-naive viremic individuals, individuals on highly active antiretroviral therapy (HAART), and elite controllers. We demonstrate that elite controllers have low level of Tregs compared with viremic individuals and that a characteristic of spontaneous HIV-1 control is a maintained balance between regulatory T cells and TH17 cells. This is the first study of TH17 cells within HIV-1 elite controllers. Although Tregs have been considered within spontaneous HIV-1 control, the two previous studies15,23 have conflicting results. This makes Tregs an area of research where attention is needed. Also little is known about Tregs together with TH17 cells in the context of Elite Controllers.
This study included 3 groups of HIV-1-infected individuals with the following inclusion criteria—viremic individuals (viremic, n = 17): (1) never received HAART; individuals on HAART (HAART, n = 19): (1) HAART >1 year, (2) suppressed HIV-1 RNA viral load to <40 copies per milliliter; elite controllers (elite controllers, n = 13): (1) HIV-1 antibody enzyme-linked immunosorbent assay reactive and Western Blot positive, (2) at least 3 HIV-1 RNA test results available without HAART, (3) a span of at least 1 year between the first and the last HIV-1 RNA test result, (4) no HIV-1 RNA tests was >40 HIV-1 RNA copies per milliliter. Additionally, anonymous uninfected individuals were used as healthy controls (uninfected, n = 10). A summary of the clinical characteristics of the different groups is listed in Table 1 and for each individual in Supplemental Digital Content 1 (http://links.lww.com/QAI/A148). Statistical differences in sex were found between viremic individuals and elite controllers and in age between viremic individuals and individuals on HAART. Although still in agreement with the mentioned inclusion criteria and the definition of elite controllers used by others,29,30 two elite controllers had previously received HAART during acute HIV-1 infection for 14 and 15 months, respectively. The protocol was approved by the Capital Region´s Committee on Biomedical Research (H-B-2007-019). Written informed consent was provided by all individuals.
Determination of Plasma HIV-1 RNA Viral Load
Plasma HIV-1 RNA levels were measured with a polymerase chain reaction quantitative kit; COBAS AmpliPrep/COBAS TaqMan HIV-1 Test version 1.5 and version 2.0 (Roche, Branchburg, NJ) according to the manufacturer's instructions. The limit of detection was 40 and 20 copies per milliliter, respectively.
Cell Isolation and CD4 T-Cell Counts
PBMCs were isolated from blood collected in heparin or EDTA by density-gradient centrifugation and cryopreserved until subsequent analyses. CD4 T lymphocytes were routinely quantitated using MultiTEST Four-Color CD3/CD8/CD45/CD4 reagents on a FACSCalibur (BD Bioscience, Franklin Lakes, NJ) according to the manufacturer's instructions.
Cryopreserved PBMCs were thawed and left overnight in RPMI 1640 (Invitrogen, Carlsbad, CA) supplemented with 10% fetal bovine serum (Invitrogen) and 1% Penicllin/Streptomycin (Invitrogen) at 37°C and 5% CO2. Before staining, the PBMCs were washed in RPMI 1640. All data were acquired on a BD LSRII instrument, using FACS Diva software (BD Bioscience) and analyzed with FlowJo software (Tree Star, Ashland, OR).
Identification of CD4+ Regulatory T Cells
For flow cytometric characterization of Tregs, we stained PBMCs with directly conjugated monoclonal antibodies specific for the following surface markers: CD3 PerCP (BD Bioscience), CD4 APC-H7 (BD Bioscience), CD25 PE (Miltenyi Biotec, Auburn, CA), and CD127 FITC (eBioscience, San Diego, CA). Anti-forkhead box protein 3 (FoxP3) APC (Clone PCH101, eBioscience) antibodies and FoxP3 Permeabilization Kit were used for intracellular staining of FoxP3 according to the manufacturers' protocol (eBioscience). Dead cells were identified and excluded from the analysis using Violet LIVE/DEAD Fixable Dead Cell Stain Kit (Invitrogen). The combination of all 3 phenotypic markers, CD25+CD127lowFoxP3+, was used for Treg identification. (Supplemental Digital Content 2, http://links.lww.com/QAI/A149, demonstrates gating strategy). In the following CD25+CD127lowFoxP3+, cells will be referred to as Tregs.
Identification of Activated T Cells
T-cell activation level was determined by staining with antibodies specific for the following surface markers: CD3 PerCP (BD Bioscience), CD4 APC-H7 (BD Bioscience), CD38 PE-Cy7 (Biolegend, San Diego, CA) and HLA-DR Pacific Blue (Biolegend). Anti-Ki67 PE (BD Bioscience), anti-FoxP3 APC (Clone PCH101, eBioscience) antibodies, and FoxP3 Permeabilization kit were used for intracellular staining of proliferation according to the manufacturer's instructions. In these analyses, CD8+ T cells were defined as CD3+CD4− within the lymphocyte gate. (Supplemental Digital Content 3, http://links.lww.com/QAI/A150, demonstrates gating strategy).
Identification of TH17 and TH1 Cells
Flow cytrometric identification of IL17A producing TH17 cells were performed after stimulation of PBMCs with or without phorbol 12-myriate 13-acetate (25 μg/mL; Sigma Aldrich, Saint Louis, MO) and Ionomycin (1 μg/mL; Sigma Aldrich) in the presence of Brefeldin A (12.5 μg/mL; Sigma Aldrich), as previously described.28,31-33 We optimized the period of stimulation to 11 hours (data not shown). To identify TH17 cells, we used antibodies specific for the surface markers CD3 PerCP (BD Bioscience) and CD4 PE (Dako, Glostrup, Denmark) and antibodies specific for IL17A FITC (eBioscience) and interferon γ PE-Cy7 (BD Bioscience). Staining of CD3 and CD4 after permeabilization allowed detection of these markers even when downregulated in response to stimulation. Dead cells were identified and excluded by Violet LIVE/DEAD Fixable Dead Cell Stain Kit (Invitrogen). (Supplemental Digital Content 4, http://links.lww.com/QAI/A151, demonstrates gating strategy). Permeabilization of cells was performed using BD cytofix/cytoperm kit (BD Bioscience) according to the manufacturer's instructions.
Data analysis was performed using GraphPad Prism version 5 (GraphPad Software Inc, La Jolla, CA) and data are expressed as medians with interquartile range (IQR). We determined the statistical significance of differences between groups using nonparametric Mann-Whitney rank sum test followed by Bonferroni correction and contingency of categorical data was analysed with Fisher exact test. Correlations were determined with Spearman rank correlation. For all analyses, P values of less than 0.05 were considered significant.
Individuals With HIV-1 Control Have Lower Frequency and Number of Tregs Than Viremic Individuals
To elucidate the population dynamic of Tregs in HIV-1 infection, we studied Tregs in 3 groups of individuals infected with HIV-1 and a group of uninfected controls. All 3 groups of infected individuals had a significantly higher frequency of Tregs as compared with uninfected controls (Fig. 1A). The frequency of Tregs among elite controllers was significantly lower than among viremic individuals (Fig. 1A). In CD4+ T lymphocytes, the Treg frequencies were as follows: 0.48% (IQR: 0.34-0.63) in uninfected controls, 1.46% (0.42-2.04) in elite controllers, 1.96% (0.95-2.83) in individuals on HAART, and 3.14% (2.43-3.92) in viremic individuals. The absolute numbers of Tregs followed a similar pattern with fewer Tregs in individuals with viral control (HIV-1 RNA viral load <40 copies/mL) than in viremic individuals without viral control: 12 cells/μL (3-14) in elite controllers, 9 cells/μL (4-11) in individuals on HAART, and 15 cells/μL (11-21) in viremic individuals. Absolute CD4 T-cell count was unavailable for the uninfected controls.
HIV-1 infection leads to higher frequencies of Tregs in PBMCs, but in viremic individuals, there was no correlation between the absolute number of Tregs and log viral load nor the frequency of Tregs and log viral load (r = −0.1765, P = 0.5133 and r = 0.1029, P = 0.7044, respectively).
Inverse Correlation Between Frequency of Tregs and Frequency of CD4 T Cells
We found a trend toward a positive association between absolute number of Tregs and CD4 T-cell count (r = 0.2557, P = 0.0794). Interestingly, we found a significant inverse correlation between the frequency of Tregs and the frequency of CD4+ T-lymphocytes in all HIV-1-infected individuals (r = −0.3382, P = 0.0187) (Fig. 1B).
Positive Correlation Between Tregs and Activated and Proliferating CD4+ and CD8+ T Lymphocytes
Within both the CD4+ and the CD8+ T lymphocytes, we found a significantly lower frequency of activated CD38+HLA-DR+ cells and proliferating Ki67+ cells in individuals with HIV-1 viral control compared with viremic individuals (data not shown). However, we did not find any statistically significant differences in activation or proliferation among the groups with no or low viral load (elite controllers, individuals on HAART, and uninfected controls).
Combining all individuals, we found a positive correlation between the frequency of Tregs and both CD38+HLA-DR+ and Ki67+ CD4+ T lymphocytes (r = 0.3817, P = 0.0081 and r = 0.6273, P < 0.0001, respectively) (Figs. 2A, B). Similarly, there was a positive correlation between the absolute number of Tregs and the absolute number of CD38+HLA-DR+ CD4+ T lymphocytes (r = 0.6029, P < 0.0001) and the absolute number of Ki67+ CD4+ T lymphocytes (r = 0.7325, P < 0.0001). This correlation was not seen when analyzing each group individually. Further, there was also a positive correlation between the frequency of Tregs and both CD38+HLA-DR+ and Ki67+ CD8+ T lymphocytes (r = 0.7224, P < 0.0001 and r = 0.4513, P < 0.0015, respectively) (Figs. 2C, D), when combining all individuals. Positive correlation between the frequency of Tregs and CD38+HLA-DR+ CD8+ T lymphocytes was also found when analyzing viremic individuals (r = 0.5500, P = 0.0337) and elite controllers (r = 0.6727, P = 0.0233) separately.
Maintained Balance Between TH17 Cells and Tregs in Elite Controllers
To further elucidate the T-cell dynamic/composition in HIV-1-infected individuals, we studied IL17A-producing TH17 cells. IL17A-producing TH17 cells were confirmed to produce only minimal amounts of interferon γ (data not shown). There was no difference in the frequency of IL17A-producing CD4+ T lymphocytes between the groups: 1.13% (0.93-1.74) in uninfected controls, 0.73% (0.61-2.42) in elite controllers, 0.58% (0.39-1.47) in individuals on HAART, and 1.78% (0.64-2.32) in viremic individuals (Fig. 3A). The frequency of TH17 cells observed in all HIV-1-infected individuals appeared scattered, but no clinical parameters could explain this. Noteworthy, the TH17 proportion in especially elite controllers appeared to be bimodal; however, we were unable to explain this difference by patient characteristics, such as sex, age, estimated time of infection, and CD4 count.
The ratio of TH17 cells and Tregs was significantly lower in viremic individuals 0.48 (0.27-0.65) and individuals on HAART 0.75 (0.33-1.18) compared with uninfected controls 2.87 (1.75-3.76) (Fig. 3B). In elite controllers, the TH17/Treg ratio was 0.92 (0.27-3.04); not significantly different from uninfected controls (Fig. 3B).
HIV-1 infects CD4 T cells resulting in a progressive decline of this cell subset. Within the CD4 T-cell pool, Tregs and TH17 cells are important regulatory and effector cells, respectively, and they are therefore likely to be influenced by HIV-1 infection and play a role in HIV-1 control. Here we show that individuals with HIV-1 control, natural or HAART-mediated, have lower levels of Tregs compared with viremic individuals, but that all groups of HIV-1-infected individuals have higher levels of Tregs than uninfected controls. Further, all groups of HIV-1-infected individuals have levels of TH17 cells comparable to uninfected controls, but unlike viremic individuals and individuals on HAART, elite controllers had TH17/Treg ratios comparable to uninfected controls. Thereby, we show that an interesting attribute of spontaneous HIV-1 control could be a maintained balance between regulatory T cells and TH17 cells.
Accurate identification of Tregs is difficult and as a result inconsistent phenotypes have been used to identify Tregs. Consequently, comparison of results between published studies is complicated. Although phenotypic characterization of Tregs is still incomplete, the specific transcription factor FoxP3 in conjunction with the surface markers CD25 or/and CD127 have recently been used to identify Tregs with suppressive functions.34,35 Both CD25+ and CD25high are used in gating strategies for Tregs, but the definition of the CD25high population is in our opinion subjective. Thus, to accurately identify Tregs with suppressive functions, we selected the most stringent phenotypic identification of Tregs that combined the 3 markers, CD25+CD127lowFoxP3+. Noteworthy, the results remained unchanged when we used the CD25highCD127lowFoxP3+ definition.
Although controversial, Tregs are believed to be important in HIV-1 infection and might play a different role in natural HIV-1 control compared with HAART-induced control of HIV-1 infection. Nonetheless, we did not observe such a difference. For HIV-1-infected individuals with both natural and HAART-mediated viral control, we found a lower frequency and absolute number of Tregs as compared with viremic individuals. We also found an elevated frequency of Tregs in viremic HIV-1-infected individuals compared with uninfected controls, similar to other studies of Tregs in peripheral blood.2,8,11,19,36 The elevated frequency of Tregs in viremic individuals could not be attributed to age, as this group of patients had the lowest median age of the groups tested.37 However, our results contrast the findings in the existing 2 studies of Tregs in elite controllers by Chase et al15 and Owen et al23 who reported a higher and similar, respectively, levels of Tregs in elite controllers than in both viremic individuals and individuals in antiretroviral therapy with fully suppressed infection. These differences may at least in part be explained by means of Treg definition. We identified Tregs as CD25+CD127lowFoxP3+ CD4+ T lymhocytes by means of flow cytometric analysis, whereas Chase et al14,15 determined Tregs by FoxP3 mRNA by quantitative reverse transcriptase—polymerase chain reaction and single positive FoxP3+ CD4+ T-cells in flow cytometry. On the contrary, Owen et al23 did not include FoxP3 in their flow cytometric analysis but instead used CD25+CD127-CD152+ as definition. As Chase et al15 used only FoxP3 as the phenotypic marker in their flow cytometric analysis of Tregs, it is possible that the Treg population studied included other T-cell subsets that express FoxP3, such as TH17 cells.38 Moreover, the individuals studied by Chase et al14,15 are predominantly HLA-B5703 positive39 suggesting that they are of African descent. Individuals of different ethnic background in West Africa have varying levels of Tregs.40 Genetic expression profiling showed that certain ethnic groups had diminished expression of FoxP3 compared with European Caucasians, indicating that ethnic background plays a role in determining Treg levels. Individuals in our cohort of elite controllers are all European Caucasians. An alternative explanation of the different outcome of our study may relate to mode of acquiring HIV-1 infection. Our cohort predominantly acquired HIV-1 through sexual contact. The mode of acquisition in the study by Chase et al14,15 is unknown, but a large proportion of infected individuals in Baltimore acquire HIV-1 infection through injection drug use.41
We found an inverse correlation between the frequency of Tregs and the frequency of CD4+ T lymphocytes in PBMCs. Whether this inverse correlation is a result of fewer Tregs in uninfected controls and individuals with limited disease progression (elite controllers) or whether it is a result of a higher frequency of Tregs in viremic patients with a lower proportion of CD4 T cells is controversial and needs further investigation.9,11 An increase in Treg frequency could be attributed in part by a longer lifespan of Tregs because Tregs seem to have a slower rate of decline than other CD4 T-cell subsets16 or by a redistribution of Tregs from lymphoid tissue to peripheral blood.36 Alternatively, the higher frequency of Tregs in viremic individuals could result from conversion of non-Tregs to Tregs upon activation.11,12,42-44 The high frequency of activation in viremic individuals could explain such a conversion.
T-cell activation and T-cell turnover are predictive values for the rate of disease progression.11,13,21,22 Given that an important function of Tregs is to suppress excessive T-cell activation, we examined the activation and proliferation of CD4+ and CD8+ T lymphocytes.21,22 In elite controllers, we found no difference in activation or proliferation in either CD4+ or CD8+ T lymphocytes as compared with both uninfected controls and individuals on HAART. Activation and proliferation similar to this has previously been reported.2,8,11,19,36,45
Tregs are known to suppress T-cell activation.1,35 Therefore, a negative correlation may be expected between Tregs and activation of CD4 and CD8 T cells. In contrast, we found a strong correlation between Tregs and both the activation and proliferation of CD4+ and CD8+ T lymphocytes. A possible explanation for the positive correlation between Tregs and immune activation may be that Tregs are functionally impaired. HIV-1 infection leads to increased immune activation and if the Tregs that are present fail to exert negative feedback after activation, there would be a positive correlation between Tregs and immune activation. Immune activation can also lead to conversion of non-Tregs to Tregs, resulting in an altered generation rate of Tregs.42,43 Correlation of Tregs and activation has previously been studied with conflicting outcome. Differences could be related to both the phenotypic markers used to identify Tregs and to the differences in study groups.2,11,16,23,45,46
Potentially, TH17 cells could have an important role in the natural control of HIV-1 infection as seen in elite controllers because the main function of TH17 cells is to enhance host defense against microbial agents.24 However, in our study of TH17 cells in PBMCs, we found a large variation in the TH17 frequencies for all groups and no differences in the TH17 frequency between uninfected controls and HIV-1-infected individuals. In particular, we observed a bimodal distribution of TH17 cells in the elite controllers that could not be explained by clinical parameters. These findings agree with Brenchley et al47 who reported no difference in IL17-producing cells in peripheral blood from HIV-1-infected individuals compared with uninfected controls. However, the few other published studies on HIV-1 infection and TH17 cells have reported conflicting results. One study reported an increased frequency of IL-17-producing cells in unstimulated and stimulated peripheral blood from HIV-1-infected individuals compared with uninfected controls.31 In contrast, two other studies reported a decrease in TH17 cells in peripheral blood from HIV-1-infected viremic individuals compared with uninfected controls.33,48
Tregs and TH17 cells have been believed to have antagonistic effects.34 However, a certain plasticity and interplay between Tregs and TH17 cells in addition to simultaneous expression of the cell markers for Tregs (FoxP3) and TH17 cells (RORg(t)) has recently been reported.34,38,49,50 The two cell types also share common chemokine receptor (CCR6 and CCR4) that prompt especially TH17 to migrate to inflamed tissues.51,52 Depending on chemokine expression, we would anticipate that Tregs and TH17 cells maintain a balance in healthy tissue and the interplay of the two cell subsets would be relevant to viral control and subsequently the course of infection.28,53 TH17 cells contribute to maintenance of mucosal barrier integrity in the gut. An extensive loss of TH17 cells has been observed during HIV-1 infection,47 and this loss may lead to increased microbial translocation and sustained inflammation. As recovery of CD4 T cells is slow in the gut compared with the peripheral blood, Tregs and TH17 cells measured in the peripheral blood might not mirror the state in the gut.54,55 Unfortunately, we did not have access to tissue samples and are unable to elaborate of the relationship between TH17 and Tregs in tissue and peripheral blood. Possibly, ex vivo phenotypic labelling cannot directly be translated into in vivo functions.
With the interplay of Tregs and TH17 cells in mind, we found a significant decrease in TH17/Treg ratio for viremic individuals and individuals on HAART compared with uninfected controls. Interestingly, we did not see a significant reduction in the TH17/Treg ratio between elite controllers and uninfected controls, indicating that elite controllers have a close to normal balance between TH17 cells and Tregs. The heterogeneity of elite controllers, which is not explained by patient characteristics and also a feature of controllers in another study,28 may indicate several means of immunological control of infection, a subset of which may rely more heavily on a normal TH17/Treg ratio. The importance of the balance between Tregs and TH17 cells in disease control is shown in the recent studies by Favre et al28,53 who found a loss of balance between TH17 cells and Tregs in progressive HIV and simian immunodeficiency virus infection.
In conclusion, lack of viral control corresponded, in our hands, to excessive activation and proliferation, both undesirable effects for the T cells. Whether the elevated levels of Tregs in HIV-1-infected individuals is detrimental or favourable is yet to be established. We found similar levels of Tregs, activation and proliferations and TH17/Treg ratio in elite controllers and individuals on HAART. Although these factors do not explain natural control of HIV-1 infection, our results support their role in HIV-1 control. The similar TH17/Treg ratio found in uninfected controls and elite controllers might indicate an importance of the balance between regulatory and effector cells in HIV-1 control, although this needs further investigation.
We gratefully acknowledge the patients who made this study possible and Solvej Kolbjørn Jensen, Birgit Knudsen, and Anna-Louise Sørensen for excellent technical assistance.
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