HIV-1 infection induces alterations in multiple components of the immune system, reflected mainly by a decrease in the CD4+ T-cell population, leading to AIDS. However, the natural history of HIV-1 infection is heterogeneous, given the variability in the time required to advance to AIDS. In most HIV-1–infected individuals, the median time is 8–10 years1; nonetheless, a small fraction of HIV-1–infected individuals who despite being infected for more than 10 years remain symptom less, maintaining normal peripheral blood (PB) CD4+ T-cell counts (>500 CD4+ cells/μL), in the absence of antiretroviral therapy; they are known as long-term nonprogressors (LTNPs).2,3 In addition, there are 2 new subgroups of HIV-1–positive individuals who exhibit a spontaneous and sustained control of viral replication, at least for 1 year without antiretroviral therapy: elite controllers maintain undetectable HIV-1 RNA levels (<50 copies/mL), and viremic controllers exhibit detectable but low viral loads (<2000 copies/mL).4 These subgroups have revealed the existence of natural mechanisms of viral control.
Several studies have aimed at determining the mechanisms involved in HIV-1 resistance and viral control; so far, resistance has been associated with host genetic variants and immunological factors that limit viral infection and progression.5 The CCR5-delta 32 mutation has been the most widely investigated, and its association with HIV-1 resistance relies on the inability of R5 viral strains to enter target cells. Other single-nucleotide polymorphisms in HIV-1 coreceptors and their ligands are associated with this phenomenon.6 Also, several reports on cellular immunity indicate that apoptosis of target cells,7 increased production of interferon-γ by natural killer (NK) cells,8 increased expression of NK receptors associated with cellular activity,9,10 and certain human leukocyte antigen (HLA) alleles11,12 are other factors associated with HIV-1 resistance. Finally, humoral response also contributes to HIV-1 resistance; in fact, a higher production of mucosal anti-HIV-1 IgA has been reported in exposed seronegatives (ESNs) compared with healthy controls.13
Regarding soluble factors, RNases, chemokines, and cationic proteins have been associated with HIV-1 protection in ESNs or LTNPs.14–17 The secretion of leukocyte protease inhibitor (SLPI) is induced by HIV-1 gp120 in oral epithelial cells without requiring infection.18 In addition, McNeely et al19,20 showed that SLPI protects against HIV-1 infection, an inhibitory effect that occurs before reverse transcription. Also, a higher production of human α-defensins (HAD-1 to -3) has been associated with inhibition of HIV-1 replication.21,22
However, it is currently accepted that one of the most important pathogenic mechanism during chronic HIV-1 infection that has been correlated to AIDS progression is the hyperactivation of immune cells. Abnormal activation is induced by exposure to viral antigens and then exacerbated by destruction of mucosal lymphoid tissue,23 leading to the translocation of bacteria from the intestinal lumen to systemic circulation.24 As a result, there is an increased number of activated target cells for HIV-1,25 an increased apoptosis of activated CD4+ T cells, anergy, and, in general, a functional alteration of the immune system. As a counteracting mechanism, regulatory T cells (Tregs) control cellular activation levels. However, the potential effect of Tregs on HIV-1 pathogenesis is controversial because several reports suggest that these cells might have a dual role. Their benefic potential comes from their ability to decrease cellular activation, limiting viral replication and new cell targets; in contrast, their accumulation might restrict the specific anti-HIV-1 responses, limiting clearance of infected cells.26
Considering that HIV-1 controllers were recently described and the mechanisms related to viral control are poorly studied, we evaluated the frequency and immune activation phenotype of immune cells and class I HLA alleles and the expression of the soluble factors HAD-1 and SLPI, in a Colombian cohort of HIV controllers, trying to determine their association to viral control.
Population and Samples
Two groups were included: (1) 11 HIV-1 controllers, defined as previously described4; briefly, we selected HIV-infected individuals who exhibit a spontaneous and sustained control of viral replication, at least for 1 year without antiretroviral therapy: elite controllers maintain undetectable HIV-1 RNA levels (<50 copies/mL), and viremic controllers exhibit detectable but low viral loads (<2000 copies/mL); all these 11 individuals were tested negative for alleles with the delta 32 mutation in the CCR5 gene; and (2) 11 chronic HIV-1–infected progressors, who were individuals with a CD4+ T-cell count higher than 250 cells per microliter, HIV viral load higher than 2500 RNA copies per milliliter, and without highly active antiretroviral therapy at the time of sampling.
All individuals signed an informed consent approved by the Bioethical Board from Universidad de Antioquia, prepared according to Colombian Legislation, Resolution 008430 of 1993. This investigation was approved by the Ethical Committee of Universidad de Antioquia (certificate of approval 10-8-298). Twenty milliliters of PB in EDTA or heparin tubes were collected to determine the frequency and phenotype of immune cells and for cell culture, respectively.
Culture of PB Polymorphonuclear Cells
Because HAD-1 and SLPI are produced mainly by neutrophils, this cell subpopulation was isolated and cultured. Briefly, 12 mL of PB was mixed with 6 mL of 6% dextran and 0.9% NaCl; this mixture was incubated for 45 minutes at room temperature (RT), the erythrocytes were lysed with 6 mL of distillated water for 35 seconds, and the osmolarity was restored with 0.6 M KCl. Then, polymorphonuclear cells (PMNs) were isolated by density-gradient centrifugation at 700g for 30 minutes with Ficoll-Hypaque 1077 (Sigma, St Louis, MO). In 24-well plates, 2 × 106 PMNs were incubated in RPMI (Invitrogen, Carlsbad, CA) with 3000 pg/mL of p24 antigen, obtained from H9/HTLV-III cell supernatants (National Institutes of Health AIDS Research & Reference Reagent Program, Bethesda, MD). As a positive control, 10 μg/mL of lipopolysaccharide (LPS; Sigma) was used. For viral or LPS stimulation, the cells were incubated for 2 hours at 37°C in 5% CO2 and then washed and re-incubated for an additional 48 hours at 37°C in 5% CO2. Finally, PMNs were collected for RNA extraction.
Real-Time Reverse Transcriptase–Polymerase Chain Reaction Assay to Quantify HAD-1 and SLPI mRNA
RNA was extracted using TRizol Reagent (Invitrogen) following the manufacturer's instructions. The amount and purity of the RNA were determined by spectrometry at 260/280 nm. Total RNA was treated with DNase I (Fermentas, St Leon-Rot, Germany). DNA was synthesized using SuperScript III (Invitrogen), according to the manufacturer's instructions.
Each 20 μL of real-time polymerase chain reaction (PCR) mixture consisted of 2 μL of cDNA, 10 μL of Maxima SYBR Green/qPCR Master Mix (Fermentas), and primers (0.4 μM each). The primer sequences and product size for HAD-1 and SLPI were previously reported27,28; the sequences and cycling profiles are found in Supplemental Digital Content 1 (see Table,https://links.lww.com/QAI/A260). Ubiquitin RNA was used to normalize the RNA content of HAD-1 and SLPI. We included a melting curve to confirm the specificity of the PCR product. All real-time reverse transcriptase–PCR amplifications were performed using the CFX96 real-time system and data analysis using the software CFX Manager Version 1.5.534.0511 (Bio-Rad, Hercules, CA).
HLA typing was performed by the Histocompatibility and Immunogenetics Clinical Laboratory of University of Utah. The determination of the HLA-A and HLA-B alleles was performed by a DNA hybridization assay (One-Lambda, Canoga Park, CA) using multicolored beads with unique flurophores bound to amplified PCR products. Detection was via a Luminex 100 Flow cytometer.
Flurochrome-labeled mouse monoclonal antibodies against human molecules were from Becton Dickinson (BD, San Jose, CA): CD8, CD86, lineage marker (Lin-1, a mixture of anti-CD3, CD14, CD16, CD19, CD20, and CD56), CD11c, CD123, and the CDR3 region of the invariant T-cell receptor-α chain (clone 6B11); and from eBioscience (San Diego, CA): CD3, CD4, CD16, CD25, CD38, CD56, CD69, CD127, HLA-DR, and FoxP3.
The frequency and phenotype of different subpopulations in PB were determined by flow cytometry. Briefly, 150 μL of PB was incubated with specific monoclonal antibodies for 25 minutes at RT in the dark. Erythrocytes were lysed by incubating for 10 minutes with 2 mL of 1× fluorescence-activated cell sorting lysing solution (BD); the cells were washed twice with 2 mL of cold phosphate-buffered saline at 250g for 5 minutes and fixed with 250 mL of 2% paraformaldehyde.
Lymphocyte's gate, identified by side (SSC) vs. forward (FSC) light scatter, was used to analyze the following cell populations: NK cells (CD3−/CD16+/CD56+), invariant natural killer T cells (iNKT; 6B11+/CD3+), and T cells (CD3+/CD4+ or CD3+/CD8+). The CD4/CD8 lymphocyte ratio was determined based on the percentage of CD4+ and CD8+ T cells. In mononuclear cells' gate, identified by SSC vs. FSC, the dendritic cells were gated as Lin−/HLA-DR+ and then as CD11c+ myeloid dendritic cell (mDC) or CD123+ plasmacytoid dendritic cell (pDC).
The frequency of Tregs (defined in lymphocyte's gate as CD3+/CD4+/FoxP3+/CD25+/CD127low/−) was determined by intracellular flow cytometry. After staining with extracellular markers, the cells were permeabilized and fixed using the anti-human FoxP3 staining set (eBioscience), following manufacturer's instructions. Seven microliters of anti-FoxP3 was then added; the cells were incubated for 25 minutes at 4°C, washed twice with 2 mL of phosphate-buffered saline at 250g for 5 minutes, and fixed with 250 μL of 2% paraformaldehyde.
All preparations were stored at 4°C until acquisition in the cytometer FACS CANTO-II (BD). Acquisition analysis was performed in the BD FACSDiva 6.1.2 version. The analysis of activation molecules was made using the fluorescence minus one method. Dead cells were excluded from the analysis through SSC vs. FSC. Absolute numbers of different leukocyte subpopulations were calculated based on manually determined total and differential PB cell counts.
To compare data from HIV-1 controllers vs. progressors, a nonparametric test (Mann–Whitney U–2-tailed test) was performed. P < 0.05 was considered statistically significant. Correlation analyses were based on Spearman correlation coefficient calculations.
Allelic distribution and frequencies of the haplotypes were determined using the software Genepop 4.0.10, and to evaluate statistically significant differences, Fisher exact test was used. Statistical tests were performed using Graph-Pad Software version 5.00.
HIV-1 Controllers Exhibit Differences in Immune Cells
Demographics and virological and immunological data at the time of sampling are shown in Table 1. Two elite and 9 viremic controllers were included. There were no differences in age and time length after HIV-1 diagnosis in both infected groups; as expected, HIV-1 controllers exhibited significantly lower viral load and higher CD4+ T-cell count and percentage in PB when compared with progressors.
The percentage (median: 40.5%, range min-max: 22.3%–49.3%; vs. 45.2%, 29.5%–68.7; P = 0.1679; Fig. 1A) and absolute numbers (913.3, 564.4–2205 vs. 1168, 740–2776; P = 0.3579) of CD8+ T cells were similar in controllers and progressors, respectively. As expected, HIV-1 progressors exhibited a significant decrease in the CD4+/CD8+ lymphocyte ratio when compared with controllers (0.48, 0.13–0.78 vs. 0.9, 0.5–2.3; P = 0.0058; Fig. 1B).
We did not find significant differences in the frequency of iNKT cells between controllers and progressors (0.09%, 0.03%–0.16% vs. 0.11%, 0.03%–0.25, respectively; P = 0.5543; Fig. 1C). However, the frequency of Tregs, defined as CD4+/FoxP3+/CD127−/low cells, was significantly lower in controllers when compared with progressors (4.95%, 1.8%–10.1% vs. 7.8%, 6%–19.8%, respectively; P = 0.0222; Fig. 1D). Similar results were obtained when the Tregs were defined as CD4+/CD25+/CD127−/low cells.
When comparing controllers and progressors, we found a significant difference in the frequency of circulating NK cells (5.7%, 3.5%–12% vs. 12.6%, 2.4%–24.8%; P = 0.0104; Fig. 1E); the frequency of mDC from controllers was significantly higher when compared with progressors (0.59%, 0.44%–0.96% vs. 0.4%, 0.03%–0.9%; P = 0.0278; Fig. 1F), and we did not find a significant difference in the frequency of pDC (0.15%, 0.07%–0.25% vs. 0.11%, 0.004%–0.24%; P = 0.1779; Fig. 1G).
Decreased Expression of Immune Activation Markers in HIV-1 Controllers
HIV-1 controllers, compared with progressors, expressed a significantly lower percentage of mDC expressing CD86 (0%, 0%–0.5% vs. 0.14%, 0%–38.1%; P = 0.0320; Fig. 2A) and lower mean fluorescence intensity (MFI) of this molecule on mDC (0, 0–10,680 vs. 4281, 0–20,390; P = 0.0320). Regarding pDC, despite a lower level of expression of CD86 on cells from controllers (Fig. 2B), no significant differences in the percentage of pDC CD86+ were detected (0%, 0%–2.4% vs. 0.05%, 0%–16.8%; P = 0.4583; Fig. 2B) or in the MFI of CD86 (0, 0–3527 vs. 2782, 0–4567; P = 0.2664), between both groups of infected patients.
Regarding the activation status of T cells, controllers exhibited a significantly lower percentage of CD4+ T cells co-expressing CD38/HLA-DR when compared with progressors (2.3%, 0.8%–5.4% vs. 5.7%, 3.3%–10.3%; P < 0.0004; Fig. 2C). There was also a negative correlation between the expression of these activation molecules and the frequency of circulating CD4+ T cells in controllers (Spearman r = −0.7; P = 0.0165; Fig. 2D). In contrast, in CD8+ T cells, we did not find significant differences in the expression of activation markers in controllers vs. progressors (4.6%, 1.7%–6.2% vs. 6.1%, 2.5%–15.2%; P = 0.1309; Fig. 2E). Finally, significant differences were found when the results of controllers were compared with progressors for the percentage of NK cells expressing CD69 (1.5%, 0%–5.9% vs. 3.74%, 0.53%–19.5%; P = 0.0417; Fig. 2F) but not for the MFI of CD69 expression (1499, 0–2366 vs.1543, 925–3475; P = 0.7927).
PMNs From HIV-1 Controllers Express Higher SLPI
To determine if HAD-1 and SLPI, factors with anti-HIV-1 activity, were associated with the control of viral replication, we evaluated by real-time PCR the change in HAD-1 and SLPI gene expression when the PMNs were stimulated with HIV-1. SLPI expression in controllers was significantly higher than that in progressors (11.4, −2.3 to 179.9 vs. 0, −6.4 to 9.2; P = 0.0486; Fig. 3A), whereas the expression of HAD-1 was similar in both groups (0, −2.8 to 3.1 vs. −1.5, −2.3 to 13.17; P = 0.6945; Fig. 3B). In contrast, in LPS-stimulated PMNs, used as positive control of stimulation, no significant differences were found between controllers and progressors when the expression of SLPI (11.7, 3.3–40.9 vs. 11.75, 0–42.9; P = 0.9623) and HAD-1 (3.3, 1–7.6 vs. 1.7, 1.39–4.9; P = 0.1381) was measured.
The cellular immune response of HIV-1–specific cytotoxic T lymphocytes is mediated mainly by the type of peptides displayed by class I HLA molecules. When the frequency of class I HLA alleles between controllers and progressors was evaluated, no association was established between the control of viral replication and the frequency of any HLA-A and HLA-B alleles (P-value for each allele was >0.05), previously related to resistance to HIV-1 progression (see Tables, Supplemental Digital Content 2, https://links.lww.com/QAI/A261).
The investigation of the mechanisms involved in natural control of HIV-1 replication is essential to develop therapeutic measures to prevent HIV-1 infection or progression. In 2007, a particular group of infected individuals was described as viral controllers; they spontaneously control HIV-1 replication, at least for 1 year, in the absence of highly active antiretroviral therapy.4 These patients might represent a key group to study mechanisms involved in the control of viral replication. Because controllers are poorly characterized, our study focused on this population of HIV-1–infected individuals.
We evaluated the frequency and phenotype of immune cells among HIV-1–infected persons (controllers versus progressors) and investigated if the presence of particular HLA alleles or the levels of SLPI and HAD-1 expression were associated with the viral control. Despite a longer time of HIV-1 diagnosis in HIV-1 controllers, they exhibited higher CD4+ T-cell counts and lower viral load than progressors. In addition, HIV-1 controllers had a higher frequency of mDC, a lower percentage of Treg cells, and lower expression of activation molecules on CD4+ T cells and mDC compared with progressors. Finally, SLPI expression was higher in stimulated PMN from HIV-1 controllers, compared with progressors.
SLPI is a protein previously associated with HIV-1 resistance29–31; higher salivary SLPI levels were associated with decreased risk of HIV-1 infection among infants exposed to HIV-1 via breastfeeding.29 Similarly, higher SLPI levels were found in vaginal fluids of HIV-1–positive women whose babies were born uninfected than those from transmitting women31; these, together with our findings, suggest that a higher expression of SLPI is related to the control of HIV-1 transmission and replication. Previous, unpublished data from our research group indicated higher expression of SLPI in oral mucosa of ESNs compared with healthy controls. To our knowledge, this is the first report suggesting the importance of this factor in delaying AIDS progression in HIV-1 controllers. However, no correlation was observed between SLPI expression and viral load or CD4+ T-cell counts.
The mechanisms involved in the antiviral effect of SLPI are not well understood. Initially, it was thought that the effect was mediated by interaction of SLPI with viral envelope proteins, but recently it was shown that SLPI binds to annexin-II, at the macrophage membrane, blocking HIV infection.32 In fact, annexin-II binds to phosphatidylserine expressed on the HIV-1 envelope, promoting viral binding and entry into target cells; it was demonstrated that annexin-II–deficient cells are less susceptible to HIV infection in vitro.33
The results indicate a similar fold increase in SLPI expression in response to HIV and LPS in HIV controllers; in contrast, a lower fold increase in SLPI expression in response to HIV-1, compared with LPS stimulation, was observed in HIV progressors. Previous studies have reported the expression of several pattern recognition receptors by neutrophils, including TLR734; although it was demonstrated that HIV RNA can bind to TLR735 and that the signaling through this receptor induces the expression of SLPI,36 previous reported alterations on TLR expression, specifically a significantly higher expression of TLR4 but not of TLR7, associated with increased HIV RNA load in advanced HIV infection could explain these findings.37,38
The production of high amounts of HAD-1 to -3 by mDCs from HIV-1–infected individuals was correlated to the control of viral load, better outcome, and slow disease progression22; in our controllers, this association was not observed. This apparent contradiction could be due to genetic/ethnic differences of the individuals included in the survey or to the fact that different cell populations (mDCs vs. PMNs) were analyzed in these 2 studies.
Class I HLA alleles have been associated with resistance/susceptibility to several infections, including HIV. However, in the present study we did not find a higher frequency of alleles previously reported to be associated with HIV control; small number of patients comprising each cohort or differences in genetic characteristics of the population included in this study could account for the apparent discrepancy with previous reports.
Immune activation is considered as one of the most important mechanisms mediating apoptosis of lymphocytes. Previous studies have indeed shown that in HIV-infected subjects there is a negative and a positive correlation between immune activation and CD4+ T-cell counts and viral load, respectively,39–42 and that immune activation is the main pathogenic mechanism associated with AIDS progression. HIV controllers exhibited a lower expression level of the activation markers on CD4+ and CD8+ T cells and mDCs, indicating that the control of immune activation may lead to the control of viral replication and preservation of CD4+ T-cell counts. Similarly, Owen et al43 reported that LTNPs expressed a lower percentage of CD8+ T cells co-expressing the activation molecules CD38 and HLA-DR.
Although elimination of CD4+ T cells is the hallmark of progressive HIV-1 infection, the frequency and function of other immune subpopulations are altered. iNKT cells are affected at early stages of HIV-1 infection; in progressors, these cells are in low frequency and exhibit a hyperactivated phenotype.44 In our chronically infected patients, independent of viral load, the frequency of these cells was decreased, suggesting that their loss in PB occurred very early.
Studies evaluating the role of Tregs led to contradictory results, making it difficult to interpret their participation during HIV-1 infection. In this study, HIV-1 controllers exhibited a lower frequency of Tregs compared with progressors. However, HIV-1 controllers do not exhibit a hyperactivated immune status, despite lower levels of Tregs. Low viral loads in these individuals could explain this finding; previous studies have indicated that HIV-1 components, including gp120, induce accumulation of Tregs by expansion of preexisting cells or conversion of naive T cells.45 In fact, there are reports indicating a positive correlation between viral load and Treg frequency in lymphoid tissue of HIV-1–infected individuals.46
In agreement with our results, other studies have demonstrated that accumulation of Tregs or the high expression of FoxP3 is directly correlated to immune activation and AIDS progression.26,47 Indeed, lower frequency of Tregs should have a beneficial effect during the chronic phase of HIV-1 infection, allowing the effector function of immune cells to take place. However, in contrast to our results, previous reports indicated that a high frequency of Tregs was inversely correlated with immune activation and apoptosis of CD8+ T cells in LTNPs; in addition, the same study reported that decreased Treg frequency was associated with immune cell exhaustion in HIV-1 progressors.48,49
Based on our results, we propose a model in which HIV-1 controllers have the ability to produce higher amounts of SLPI, limiting viral replication. Therefore, these individuals maintain a normal frequency of CD4+ T cells and mDCs, preventing extensive damage of gastrointestinal physical barriers, limiting translocation of microbial products from intestinal lumen to systemic circulation. As a result, there is minor cell apoptosis mediated by activation and lower expansion of Tregs, thereby allowing the conservation of innate and adaptive immune components to retard or inhibit AIDS progression.
The authors thank Anne-Lise Haenni for all her constructive comments, and the CIHR IID&GH Program of the University of Manitoba. The H9/HTLVIII cell line was obtained through the AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH.
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