A major challenge for the development of an effective vaccine against tuberculosis (TB) is that the attributes of protective CD4+ T cell responses are still elusive for human TB. Infection with HIV type 1 is a major risk factor for TB, and a better understanding of HIV-induced alterations of Mycobacterium tuberculosis–specific CD4+ T cells that leads to failed host resistance may provide insight into protective T cell immunity to TB. A total of 86 participants from a TB-endemic setting, either HIV-infected or uninfected and with latent or active TB (aTB), were screened using M. tuberculosis–specific MHC class II tetramers. We examined the phenotype as well as function of ex vivo M. tuberculosis–specific tetramer+CD4+ T cells using flow cytometry. The numbers of M. tuberculosis–specific tetramer+CD4+ T cells were relatively well maintained in HIV-infected persons with aTB, despite severe immunodeficiency. However, although HIV-uninfected persons with latent TB infection exhibited ex vivo M. tuberculosis–specific CD4+ T cells predominantly of a CXCR3+CCR6+CCR4 (Th1*) phenotype, aTB or HIV infection was associated with a contraction of this subset. Nevertheless, in individuals with aTB and/or HIV infection, circulating ex vivo M. tuberculosis–specific CD4+ T cells did not display defects in exhaustion or polyfunctionality compared with healthy HIV-uninfected individuals with latent TB infection. Collectively, these data suggest that increased susceptibility to TB disease could be related to a loss of circulating Th1* CD4+ T cells rather than major changes in the number or function of circulating CD4+ T cells.

This article is featured in In This Issue, p.2189

It is estimated that a third of the world’s population is latently infected with Mycobacterium tuberculosis, and in 2015, over 10 million people developed active tuberculosis (aTB), of which 1.2 million (12%) were coinfected with HIV (1). Although in the majority of immunocompetent individuals, the risk of progression from latent to aTB is 2–10% in a lifetime, it increases up to an annual risk of 5–15% in HIV-infected persons (2), making HIV one of the strongest known risk factors for TB (3). Furthermore, in aTB cases, concomitant HIV infection results in accelerated TB disease progression, more severe clinical symptoms in some cases, and increased mortality (4, 5), further emphasizing the detrimental effect of HIV on M. tuberculosis immunity.

The major immune defect induced by HIV is a progressive reduction in absolute CD4+ T cells (6) that correlates with increasing TB disease risk (7), attesting to the critical role of CD4+ T cells for M. tuberculosis immunity. However, TB risk is significantly elevated even in HIV-infected persons with well-preserved CD4+ T cell counts (during the early phase of infection or after immune-restoring antiretroviral therapy), suggesting that HIV may also induce qualitative defects in M. tuberculosis–specific CD4+ T cells. Indeed, alterations in the polyfunctional capacity (8, 9), memory profile (10), and lineage differentiation (11) of M. tuberculosis–specific CD4+ T cells have been previously reported. Moreover, HIV promotes systemic immune activation (12) and cell exhaustion (13). Altogether, these HIV-induced impairments weaken M. tuberculosis immune responses and could facilitate TB reactivation and/or promote excessive TB progression.

To date, the constituents of an effective immune response to TB remain incompletely understood. Indeed, although Th1 responses are the cornerstone of adaptive immunity to TB, they failed to associate with protection from infection or disease in recent clinical trials of a novel TB vaccine (14, 15). Thus, to better understand the impact of HIV on M. tuberculosis–specific responses we assessed the magnitude, phenotype, and functional profile of ex vivo M. tuberculosis–specific CD4+ T cells from individuals with distinct HIV and TB clinical states, employing MHC class II tetramers. This approach allowed us to define TB disease- and HIV-induced alterations specific to M. tuberculosis–specific CD4+ T cells in their resting state. Our findings provide novel insights into cellular mechanisms of failed M. tuberculosis–specific immunity.

Study participants (n = 86) recruited from the Ubuntu Clinic, Khayelitsha in Cape Town, South Africa, were screened for M. tuberculosis–specific MHC class II responses. To assess the qualitative effects of HIV infection on M. tuberculosis–specific CD4+ T cells before profound CD4 depletion, only HIV-infected individuals with latent TB infection (LTBI) with well-maintained CD4+ T cell counts were recruited. Individuals were categorized into four groups based on their TB and HIV status: HIV/LTBI (n = 28), HIV+/LTBI (n = 30), HIV/aTB (n = 14), and HIV+/aTB (n = 14). LTBI was diagnosed based on a positive IFN-γ release assay (QuantiFERON-TB Gold In-Tube; Cellestis), no symptoms of aTB disease, a negative M. tuberculosis sputum (GeneXpert), and a normal chest x-ray. aTB disease was diagnosed based on clinical symptoms, positive chest x-ray, and positive M. tuberculosis sputum. All HIV-infected individuals were antiretroviral treatment-naive and no one had started TB treatment at the time of enrolment. The study was approved by the University of Cape Town Human Research Ethics Committee (Numbers 158/2010 and 896/2014) and the protocol review office of the U.S. National Cancer Institute institutional review board. All participants provided written informed consent.

Absolute blood CD4+ T cell counts were measured using a Flow-CARE PLG CD4 test (Beckman Coulter). For HIV-infected individuals, plasma HIV type 1 RNA levels were quantified using Abbott m2000 RealTime HIV type 1 assay. For HLA typing, DNA was extracted from PBMCs using the QIAamp Mini Blood kit (Qiagen). High-resolution HLA class II genotypes were determined using 454/Fluidigm HLA Typing Kits (Roche) following the manufacturer’s protocols (16).

Four custom-ordered M. tuberculosis–specific MHC class II tetramers conjugated with PE or allophycocyanin were obtained from the National Institutes of Health Tetramer Core Facility (Emory University): CFP-1071–85 (EISTNIRQAGVQYSR) loaded HLA-DRB1*0401 tetramer (DRB1*0401/CFP); CFP-1051–65 (AQAAVVRFQEAANKQ) loaded HLA-DRB5*0101 tetramer (DRB5*0101/CFP); CFP-1071–85 (EISTNIRQAGVQYSR) loaded HLA-DQB1*0602 tetramer (DQB1*0602/CFP); and ESAT-631–45 (EGKQSLTKLAAAWGG) loaded HLA-DQB1*0602 tetramer (DQB1*0602/ESAT). Additionally, the human CLIP (Clip; PVSKMRMATPLLMQA) was complexed to each of the aforementioned tetramers and used as a negative control to validate tetramer-staining specificity (Supplemental Fig. 1A). The performance of PE- and allophycocyanin-conjugated tetramers was compared in a subset of individuals (Supplemental Fig. 1B), showing that comparable frequencies of tetramer+ cells were obtained with both reagents. Moreover, for ex vivo phenotyping, we performed a dual tetramer stain using PE- and allophycocyanin-conjugated tetramers of different specificities simultaneously in a subset of samples (n = 7). To validate this approach, we verified that costaining with two different tetramers did not interfere with the detection of tetramer+ T cells (Supplemental Fig. 1C).

After resting, cryopreserved PBMC were stimulated with 1 μg/ml of cognate peptide (15mers; Peptide Synthetics) from culture filtrate protein of 10 kDa (CFP-10) or early secretory antigenic target of 6 kDa (ESAT-6) proteins. Stimulations were performed in the presence of costimulatory Abs: anti-CD28 and anti-CD49d (1 μg/ml; BD) for 16 h. Brefeldin A (10 μg/ml; Sigma-Aldrich) was added at the onset of stimulation.

Cells were first stained with Fixable Near-IR Dead Cell Stain (Invitrogen), then with PE- and/or allophycocyanin-conjugated class II tetramers (2 and 4 μg/ml, respectively) at 37°C for 30 min, and subsequently surface stained. When intracellular proteins were measured, cells were fixed and permeabilized using Cytofix/Cytoperm buffer (BD Biosciences) and then stained intracellularly. A summary table of the Abs used for each panel is presented in Supplemental Table I. Samples were acquired on an LSR II flow cytometer (BD) using FACSDiva software and analysis was performed using FlowJo (v9.9.4; Tree Star), Pestle (v1.7), and Spice (v5.35) software (17). The gating strategies applied are presented in Supplemental Fig. 2.

Statistical analyses were performed using Prism (GraphPad, v5.0). Nonparametric statistical tests were used for all comparisons. The Mann–Whitney U test and Wilcoxon matched pairs test were used for unmatched and paired samples, respectively, and the Kruskal–Wallis ANOVA using Dunn test for multiple comparisons. Correlations were performed using the Spearman Rank test. A p value <0.05 was considered statistically significant.

Using four different MHC class II tetramers recognizing CFP-10 or ESAT-6 epitopes from M. tuberculosis, we identified tetramer-positive CD4+ T cells in 35 of the 86 participants screened. The clinical characteristics of each individual with M. tuberculosis–specific MHC class II tetramer responses are presented in Table I. The proportion of tetramer responders was similar in each group, representing ∼40% of individuals tested (Supplemental Fig. 3A). The detection rate for each tetramer (∼18% for DRB1*0401, ∼59% for DRB5*0101, ∼67% for DQB1*0602; Supplemental Fig. 3B) was in accordance with the prevalence of these HLA class II types in the South African population (18). Fig. 1A shows representative plots of M. tuberculosis–specific tetramer staining in one donor from each clinical group studied. Whereas the median frequencies of tetramer+CD4+ T cells were comparable between the HIV/LTBI, HIV+/LTBI, and HIV/aTB groups (median: 0.028, 0.024, and 0.035%, respectively), in HIV+/aTB individuals, the median frequency of tetramer+CD4+ cells was significantly higher (0.16%, Fig. 1B). To take into account variation in absolute CD4+ T cell counts between groups, particularly in persons coinfected with HIV and aTB (Fig. 1C), the absolute number of M. tuberculosis–specific tetramer+CD4+ T cells was calculated (Fig. 1D). The absolute number of M. tuberculosis–specific tetramer+CD4+ T cells in HIV+/LTBI individuals (median: 128 cells per cm3) was significantly lower than the HIV/LTBI group (270 cells per cm3), representing a median fold reduction of 52%. By contrast, despite the profound CD4 depletion observed in HIV+/aTB patients, the higher frequency of M. tuberculosis–specific tetramer+CD4+ T cells observed in this group resulted in a relative maintenance of the absolute number of M. tuberculosis–specific tetramer+CD4+ T cells (median: 199 cells per cm3) to similar levels as observed in the HIV-uninfected group (Fig. 1D). This suggests that, notwithstanding profound lymphopenia, active bacterial replication still promotes the expansion of CD4+ T cells targeting M. tuberculosis in HIV-infected persons.

Table I.
Clinical characteristics of the study cohort







Class II HLA Type
Tetramer Frequency (% CD4)a
PIDGenderHIV StatusTB StatusAgeCD4 Count (Cells Per cm3)Log10 HIV Viral Load (Copies Per ml)DRB1DRB5DQB1DRB1 *0401/CFPDRB5 *0101/CFPDQB1*0602/ESATDQB1*0602/ CFP
LTBI            
 0018 — LTBI 40 nd na 0701/1501 0101 0202/0601 — 0.062 — — 
 1035 — LTBI 19 1459 na 0401/1503 0101 0302/0602 0.071 0.025 — nd 
 1029 — LTBI 22 1430 na 0301/1501 0101 0201/0602 — 0.055 0.040 nd 
 1052 — LTBI 25 1412 na 0301/1503 0101 0602/0301 — — 0.017 nd 
 1022 — LTBI 43 1344 na 0701/1503 0101 0202/0602 — 0.046 0.014 nd 
 0100 — LTBI 28 1157 na 1301/1302  0602/0609 — — 0.056 0.063 
 1055 — LTBI 19 932 na 1001/1101  0501/0602 — — 0.025 nd 
 1057 — LTBI 20 871 na 0302/1401  0402/0602 — — 0.034 nd 
 1011 — LTBI 28 801 na 1101/1302  0602/0609 — — — 0.012 
 1038 — LTBI 18 743 na 0301/1101  0201/0602 — — 0.028 0.014 
 1072 — LTBI 24 741 na 0102/1503 0101 0501/0602 — 0.019 0.022 nd 
 1061 — LTBI 21 674 na 0804/1101  0319/0602 — — 0.027 nd 
 1066 — LTBI 39 621 na 0401/0901  0302/0202 0.074 — — nd 
Median [IQR] 24 [20–34] 902 [742–1395]         
 1075 LTBI 31 965 3.77 0901/1503 0101 0202/0602 — 0.025 0.013 nd 
 0113 LTBI 41 803 4.49 1301/1503 0101 0604/0602 — 0.029 — — 
 1080 LTBI 54 774 4.15 0302/1503 0101 0402/0602 — 0.016 0.014 nd 
 1153 LTBI 46 714 3.47 1102/1503 0101 0319/0602 — 0.036 0.024 nd 
 0050 LTBI 30 563 5.06 1302/1503 0101 0609/0602 — 0.039 — 0.019 
 0094 LTBI 35 558 4.99 0302/1503 0101 0402/0602 — 0.037 0.042 0.027 
 1076 LTBI 25 543 2.96 0401/1101  0302/0602 0.018 — 0.015 nd 
 0131 LTBI 35 532 1.30 1302/1503 0101 0604/0602 — 0.024 0.017 — 
 0077 LTBI 38 511 3.35 0401/0701  0302/0202 0.024 — — — 
 1129 LTBI 29 510 3.66 1101/1503 0101 0319/0602 — 0.015 — nd 
 1081 LTBI 37 383 3.51 1303/1503 0101 0202/0602 — 0.037 — nd 
Median [IQR]  35 [30–40] 558 [511–774] 3.66 [3.35–4.49]        
aTB infection            
 0012 — aTB 28 1599 na 1102/1503 0101 0319/0602 — 0.013 0.045 0.010 
 0002 — aTB 35 1100 na 1101/1101  0319/0602 — — 0.017 0.026 
 0014 — aTB 26 865 na 0302/1503 0101 0402/0602 — 0.020 0.038 — 
 0085 — aTB 29 724 na 0404/1454  0402/0602 — — 0.046 0.018 
 0133 — aTB 30 685 na 0302/0401  0402/0302 0.090 — — — 
 0137 — aTB 25 417 na nd nd nd 0.101 — 0.035 0.050 
Median [IQR]  29 [26–31] 795 [618–1225]         
 0144 aTB 30 206 4.69 1101/1101  0319/0602 — — 0.195 0.088 
 0106 aTB 35 157 4.93 1503/1503 0101 0602/0602 — 0.163 0.190 0.098 
 0087 aTB 49 105 4.59 1302/1503 0101 0609/0602 — 0.082 — 0.120 
 0122 aTB 29 90 5.41 0302/1503 0101 0402/0602 — 0.242 0.260 — 
 0132 aTB 26 76 4.63 0302/1503 0101 0402/0602 — 0.160 — — 
Median [IQR]   30 [28–42] 105 [83–182] 4.69 [4.61–5.17]        







Class II HLA Type
Tetramer Frequency (% CD4)a
PIDGenderHIV StatusTB StatusAgeCD4 Count (Cells Per cm3)Log10 HIV Viral Load (Copies Per ml)DRB1DRB5DQB1DRB1 *0401/CFPDRB5 *0101/CFPDQB1*0602/ESATDQB1*0602/ CFP
LTBI            
 0018 — LTBI 40 nd na 0701/1501 0101 0202/0601 — 0.062 — — 
 1035 — LTBI 19 1459 na 0401/1503 0101 0302/0602 0.071 0.025 — nd 
 1029 — LTBI 22 1430 na 0301/1501 0101 0201/0602 — 0.055 0.040 nd 
 1052 — LTBI 25 1412 na 0301/1503 0101 0602/0301 — — 0.017 nd 
 1022 — LTBI 43 1344 na 0701/1503 0101 0202/0602 — 0.046 0.014 nd 
 0100 — LTBI 28 1157 na 1301/1302  0602/0609 — — 0.056 0.063 
 1055 — LTBI 19 932 na 1001/1101  0501/0602 — — 0.025 nd 
 1057 — LTBI 20 871 na 0302/1401  0402/0602 — — 0.034 nd 
 1011 — LTBI 28 801 na 1101/1302  0602/0609 — — — 0.012 
 1038 — LTBI 18 743 na 0301/1101  0201/0602 — — 0.028 0.014 
 1072 — LTBI 24 741 na 0102/1503 0101 0501/0602 — 0.019 0.022 nd 
 1061 — LTBI 21 674 na 0804/1101  0319/0602 — — 0.027 nd 
 1066 — LTBI 39 621 na 0401/0901  0302/0202 0.074 — — nd 
Median [IQR] 24 [20–34] 902 [742–1395]         
 1075 LTBI 31 965 3.77 0901/1503 0101 0202/0602 — 0.025 0.013 nd 
 0113 LTBI 41 803 4.49 1301/1503 0101 0604/0602 — 0.029 — — 
 1080 LTBI 54 774 4.15 0302/1503 0101 0402/0602 — 0.016 0.014 nd 
 1153 LTBI 46 714 3.47 1102/1503 0101 0319/0602 — 0.036 0.024 nd 
 0050 LTBI 30 563 5.06 1302/1503 0101 0609/0602 — 0.039 — 0.019 
 0094 LTBI 35 558 4.99 0302/1503 0101 0402/0602 — 0.037 0.042 0.027 
 1076 LTBI 25 543 2.96 0401/1101  0302/0602 0.018 — 0.015 nd 
 0131 LTBI 35 532 1.30 1302/1503 0101 0604/0602 — 0.024 0.017 — 
 0077 LTBI 38 511 3.35 0401/0701  0302/0202 0.024 — — — 
 1129 LTBI 29 510 3.66 1101/1503 0101 0319/0602 — 0.015 — nd 
 1081 LTBI 37 383 3.51 1303/1503 0101 0202/0602 — 0.037 — nd 
Median [IQR]  35 [30–40] 558 [511–774] 3.66 [3.35–4.49]        
aTB infection            
 0012 — aTB 28 1599 na 1102/1503 0101 0319/0602 — 0.013 0.045 0.010 
 0002 — aTB 35 1100 na 1101/1101  0319/0602 — — 0.017 0.026 
 0014 — aTB 26 865 na 0302/1503 0101 0402/0602 — 0.020 0.038 — 
 0085 — aTB 29 724 na 0404/1454  0402/0602 — — 0.046 0.018 
 0133 — aTB 30 685 na 0302/0401  0402/0302 0.090 — — — 
 0137 — aTB 25 417 na nd nd nd 0.101 — 0.035 0.050 
Median [IQR]  29 [26–31] 795 [618–1225]         
 0144 aTB 30 206 4.69 1101/1101  0319/0602 — — 0.195 0.088 
 0106 aTB 35 157 4.93 1503/1503 0101 0602/0602 — 0.163 0.190 0.098 
 0087 aTB 49 105 4.59 1302/1503 0101 0609/0602 — 0.082 — 0.120 
 0122 aTB 29 90 5.41 0302/1503 0101 0402/0602 — 0.242 0.260 — 
 0132 aTB 26 76 4.63 0302/1503 0101 0402/0602 — 0.160 — — 
Median [IQR]   30 [28–42] 105 [83–182] 4.69 [4.61–5.17]        

Underlining denotes HLA types matching the tested M. tuberculosis–specific tetramers.

a

MHC class II tetramer frequency as a percentage of total CD4+ T cells.

F, female; IQR, interquartile range; M, male; na, not applicable; nd, not done; PID, patient identification number.; —, no detection of M. tuberculosis–specific tetramer+CD4+ T cells.

FIGURE 1.

Identification of M. tuberculosis–specific MHC class II tetramer (TET) responses in individuals with HIV and/or aTB. (A) Representative examples of TET+ responses in each clinical group. The frequency of TET+ cells is expressed as a percentage of total CD4+ T cells. (BD) Frequency of TET+ cells (B), absolute CD4+ T cell count (C), and absolute number of TET+ cells (D) in each clinical group (n = 13 LTBI/HIV, n = 11 LTBI/HIV+, n = 6 aTB/HIV, and n = 5 aTB/HIV+). Bars represent the median and interquartile range. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. *p < 0.05, **p < 0.01, *** p < 0.001.

FIGURE 1.

Identification of M. tuberculosis–specific MHC class II tetramer (TET) responses in individuals with HIV and/or aTB. (A) Representative examples of TET+ responses in each clinical group. The frequency of TET+ cells is expressed as a percentage of total CD4+ T cells. (BD) Frequency of TET+ cells (B), absolute CD4+ T cell count (C), and absolute number of TET+ cells (D) in each clinical group (n = 13 LTBI/HIV, n = 11 LTBI/HIV+, n = 6 aTB/HIV, and n = 5 aTB/HIV+). Bars represent the median and interquartile range. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. *p < 0.05, **p < 0.01, *** p < 0.001.

Close modal

To examine the effect of HIV infection and/or TB disease on ex vivo M. tuberculosis–specific CD4+ T cells, we investigated their phenotype using flow cytometry (Fig. 2A). The memory differentiation, activation status, and homing potential of these cells were examined, as they are likely to be important features relating to the functional potential of T cells upon stimulation (19, 20). Due to sample availability, a subset of 29 participants was phenotyped. Based on the expression of CD27 and CD45RA, we classified four memory populations: naive-like (CD27+CD45RA+), early differentiated (CD27+CD45RA), late differentiated (CD27CD45RA), and terminally differentiated (CD27CD45RA+). In individuals with LTBI, irrespective of HIV status, M. tuberculosis–specific CD4+ T cells were predominately early differentiated (median: 61% for HIV and 63% for HIV+) and approximately a third of the cells exhibited a late-differentiated phenotype. Conversely, aTB individuals (regardless of their HIV status) exhibited a significantly elevated proportion of late differentiated M. tuberculosis–specific CD4+ T cells (median: 60% for HIV and 84% for HIV+) with a concomitant reduction of early-differentiated cells (median: 29% for HIV and 16% for HIV+; Fig. 2B).

FIGURE 2.

Ex vivo phenotype of M. tuberculosis–specific MHC class II tetramer+CD4+ cells in individuals with HIV and/or aTB. Due to the availability of PBMC, a subset of 29 donors (HIV/LTBI: n = 13, HIV+/LTBI: n = 7, HIV/aTB: n = 4, and HIV+/aTB: n = 5) was phenotyped. A total of 10 of these 29 individuals exhibited more than one individual tetramer (TET) response (HIV/LTBI: n = 16, HIV+/LTBI: n = 9, HIV/aTB: n = 8, HIV+/aTB: n = 7, see Supplemental Fig. 3A). (A) Representative examples of memory, homing, and activation profiles of TET+CD4+ T cells (red) and total CD4+ T cells (gray) in one LTBI/HIV, one LTBI/HIV+, and one aTB/HIV+ individual. (B) Comparison of the proportion of distinct memory subsets (naive: CD27+CD45RA+; early differentiated [ED]: CD27+CD45RA; late differentiated [LD]: CD27CD45RA; and terminally differentiated [TD]: CD27CD45RA+) on ex vivo TET+CD4+ T cells from LTBI/HIV (open circles, n = 16), LTBI/HIV+ (black circles, n = 9), aTB/HIV (open triangles, n = 8), and aTB/HIV+ (black triangles, n = 7) individuals. (C) Comparison of the expression of homing markers (CCR4, CCR6, and CXCR3) on ex vivo TET+CD4+ T cells from each clinical group. (D) Comparison of the expression of activation markers (PD-1, KLRG1, and HLA-DR) on ex vivo TET+CD4+ T cells from each clinical group. Bars represent the median and interquartile range. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. *p < 0.05, **p < 0.01, ***p < 0.001. (E) Relationship between the expression of CCR4 on TET+CD4+ T cells and plasma HIV viral load in LTBI individuals. Correlations were tested by a two-tailed nonparametric Spearman Rank test.

FIGURE 2.

Ex vivo phenotype of M. tuberculosis–specific MHC class II tetramer+CD4+ cells in individuals with HIV and/or aTB. Due to the availability of PBMC, a subset of 29 donors (HIV/LTBI: n = 13, HIV+/LTBI: n = 7, HIV/aTB: n = 4, and HIV+/aTB: n = 5) was phenotyped. A total of 10 of these 29 individuals exhibited more than one individual tetramer (TET) response (HIV/LTBI: n = 16, HIV+/LTBI: n = 9, HIV/aTB: n = 8, HIV+/aTB: n = 7, see Supplemental Fig. 3A). (A) Representative examples of memory, homing, and activation profiles of TET+CD4+ T cells (red) and total CD4+ T cells (gray) in one LTBI/HIV, one LTBI/HIV+, and one aTB/HIV+ individual. (B) Comparison of the proportion of distinct memory subsets (naive: CD27+CD45RA+; early differentiated [ED]: CD27+CD45RA; late differentiated [LD]: CD27CD45RA; and terminally differentiated [TD]: CD27CD45RA+) on ex vivo TET+CD4+ T cells from LTBI/HIV (open circles, n = 16), LTBI/HIV+ (black circles, n = 9), aTB/HIV (open triangles, n = 8), and aTB/HIV+ (black triangles, n = 7) individuals. (C) Comparison of the expression of homing markers (CCR4, CCR6, and CXCR3) on ex vivo TET+CD4+ T cells from each clinical group. (D) Comparison of the expression of activation markers (PD-1, KLRG1, and HLA-DR) on ex vivo TET+CD4+ T cells from each clinical group. Bars represent the median and interquartile range. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. *p < 0.05, **p < 0.01, ***p < 0.001. (E) Relationship between the expression of CCR4 on TET+CD4+ T cells and plasma HIV viral load in LTBI individuals. Correlations were tested by a two-tailed nonparametric Spearman Rank test.

Close modal

Next, to examine the activation and exhaustion status of ex vivo M. tuberculosis–specific CD4+ T cells, the expression of PD-1, KLRG1, and HLA-DR were measured. M. tuberculosis–specific CD4+ T cells were characterized by a low expression of PD-1 (median: ∼2%) with no significant differences observed between the four groups studied (Fig. 2C). Similarly, KLRG1 expression on M. tuberculosis–specific CD4+ T cells was comparable among the four clinical groups, with less than a quarter of the cells expressing KLRG1. In persons with aTB disease, HLA-DR expression on M. tuberculosis–specific CD4+ T cells was significantly elevated (median: 58% for HIV and 76% for HIV+) compared with LTBI individuals (7% for HIV and 16% for HIV+, Fig. 2C). Finally, to define whether HIV or aTB alters ex vivo M. tuberculosis–specific CD4+ T cell homing potential, we measured the expression of the chemokine receptors CCR4, CCR6, and CXCR3. In the context of aTB disease (irrespective of HIV infection), M. tuberculosis–specific tetramer+CD4+ T cells were characterized by a significantly lower expression of CXCR3 (median: 44% for HIV and 50% for HIV+) when compared with individuals with LTBI (78% for HIV and 74% for HIV+; Fig. 2D). Additionally, a trend toward lower expression of CCR6 was also observed in TB patients when compared with LTBI individuals. HIV infection per se did not significantly alter the expression of CXCR3 or CCR6 on M. tuberculosis–specific CD4+ T cells. However, specifically in the LTBI group, HIV was associated with a significant increase in the expression of CCR4 on M. tuberculosis–specific tetramer+CD4+ T cells when compared with HIV-uninfected individuals (p = 0.012, median: 61% versus 24%, respectively; Fig. 2D). In addition, CCR4 expression on tetramer+CD4+ T cells from HIV+/LTBI donors positively correlated with plasma HIV viral load (p = 0.03, r = 0.72), suggesting that the increase in CCR4 expression in these cells could be driven by viral replication (Fig. 2E).

The expression pattern of the three chemokine receptors studied has previously been used to delineate Th subsets as follows: CCR4CCR6CXCR3+ (Th1), CCR4+CCR6+CXCR3 (Th17), CCR4+CCR6CXCR3 (Th2), and CCR4CCR6+CXCR3+ (Th1*) (19, 21). This latter subset has been described as a nonconventional Th1 subset endowed with the capacity to produce IFN-γ and low levels of IL-17 (22). Detailed analysis of chemokine receptor combinations expressed by ex vivo M. tuberculosis–specific CD4+ T cells revealed that 1) these cells exhibit a broad and diverse coexpression profile of chemokine receptors; and 2) the overall distribution of these subsets was significantly different between LTBI and aTB in both HIV-uninfected and HIV-infected persons (p = 0.002 and p = 0.018, respectively). Furthermore, in the context of LTBI, HIV infection also significantly perturbs the global distribution of chemokine receptor expression (p = 0.003) (Fig. 3A). In healthy individuals, ex vivo M. tuberculosis–specific CD4+ T cells were predominately CCR4CCR6+CXCR3+ (Th1*, median: 41%) or CCR4CCR6CXCR3+ (Th1, 20.4%, Fig. 3B). aTB disease induced the greatest changes on the expression pattern of chemokine receptors, where the proportion of tetramer+CD4+ T cells expressing CCR4CCR6+CXCR3+ (Th1*) was significantly reduced (median: 5% for HIV/aTB and 7.3% for HIV+/aTB), compared with cells from HIV/LTBI donors (median: 40.6% for HIV/LTBI and 15.6% for HIV+/LTBI, Fig. 3B). These changes were partly counterbalanced by an elevated proportion of cells that did not express any of the tested chemokine receptors. The alterations induced by HIV infection, in LTBI individuals, were of a different nature compared with aTB-induced changes; tetramer+CD4+ T cells exhibited a significantly higher proportion of cells coexpressing CCR4+CCR6+CXCR3+ (median: 26%) and CCR4+CCR6+CXCR3 (Th17, 9%) when compared with the HIV/LTBI group (7% and 2%, respectively) (Fig. 3B). Although not statistically significant, these HIV-induced changes were partly counterbalanced by a contraction of the proportion of CCR4CCR6+CXCR3+ cells in HIV+/LTBI donors (median: 15.6%). Additionally, the proportion of M. tuberculosis–specific CCR4CCR6+CXCR3+ CD4+ T cells negatively correlated with HIV viral load (p = 0.004, r = −0.67), suggesting that HIV replication could preferentially reduce M. tuberculosis–specific Th1* responses (Fig. 3C). Of note, a lower proportion of cells expressing CCR4CCR6+CXCR3+ in the total CD4 compartment from individuals with HIV or aTB was also observed (data not shown), indicating that the alteration of Th1* responses could be a global effect of active viral and/or bacterial replication, and not only restricted to M. tuberculosis–specific CD4+ T cells.

FIGURE 3.

Comparison of the chemokine receptor coexpression profile in ex vivo M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells in individuals with HIV and/or aTB. (A) Pie charts showing the median proportion of each possible chemokine receptor combination within ex vivo TET+CD4+ T cells. Statistical comparisons were performed using the pie statistic tool integrated in the Spice software. Each color corresponds to a different chemokine receptor combination. (B) Proportions of cells expressing each possible chemokine receptor combination in ex vivo TET+CD4+ T cells using a Boolean gating strategy. LTBI/HIV individuals are depicted with blue dots, LTBI/HIV+ individuals with red dots, aTB/HIV individuals with green dots, and aTB/HIV+ individuals with orange dots. Bars and boxes represent medians and interquartile ranges, respectively. Statistical comparisons were performed using the Student t test. *p < 0.05, **p < 0.01. Th subsets assigned to known chemokine receptor combinations are indicated below. (C) Relationship between the proportion of CCR4CCR6+CXCR3+TET+CD4+ T cells and plasma HIV viral load. LTBI/HIV+ individuals are depicted with red dots and aTB/HIV+ individuals with orange dots. Correlation was tested by a two-tailed nonparametric Spearman Rank test.

FIGURE 3.

Comparison of the chemokine receptor coexpression profile in ex vivo M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells in individuals with HIV and/or aTB. (A) Pie charts showing the median proportion of each possible chemokine receptor combination within ex vivo TET+CD4+ T cells. Statistical comparisons were performed using the pie statistic tool integrated in the Spice software. Each color corresponds to a different chemokine receptor combination. (B) Proportions of cells expressing each possible chemokine receptor combination in ex vivo TET+CD4+ T cells using a Boolean gating strategy. LTBI/HIV individuals are depicted with blue dots, LTBI/HIV+ individuals with red dots, aTB/HIV individuals with green dots, and aTB/HIV+ individuals with orange dots. Bars and boxes represent medians and interquartile ranges, respectively. Statistical comparisons were performed using the Student t test. *p < 0.05, **p < 0.01. Th subsets assigned to known chemokine receptor combinations are indicated below. (C) Relationship between the proportion of CCR4CCR6+CXCR3+TET+CD4+ T cells and plasma HIV viral load. LTBI/HIV+ individuals are depicted with red dots and aTB/HIV+ individuals with orange dots. Correlation was tested by a two-tailed nonparametric Spearman Rank test.

Close modal

Overall, these data indicate that active M. tuberculosis replication substantially altered the phenotype of ex vivo M. tuberculosis–specific CD4+ T cells, with skewing of their memory profile toward a late differentiated memory phenotype; they were highly activated and a significantly lower proportion of these cells was identified in the CCR4CCR6+CXCR3+ (Th1*) subset, compared with individuals with LTBI. HIV-induced changes in the ex vivo M. tuberculosis–specific CD4+ T cell phenotype were more subtle, affecting primarily chemokine receptor coexpression, where the CCR4+CCR6+CXCR3+ and CCR4+CCR6+CXCR3 (Th17) subsets were enriched to the detriment of CCR4CCR6+CXCR3+ (Th1*) cells.

Having shown that both HIV and aTB disease impact the phenotype of ex vivo M. tuberculosis–specific CD4+ T cells, we next investigated whether the functional potential of these cells was affected by different disease states. Thus, we compared the ability of cells to secrete IFN-γ, IL-2, and TNF-α in response to CFP-10 or ESAT-6 peptide stimulation in the four clinical groups (Fig. 4A). Of note, as IL-17 expression is rarely detectable in response to peptide stimulation (23, 24), this Ab was not included in our panel. Overall, despite the different phenotype observed in ex vivo M. tuberculosis–specific tetramer+CD4+ T cells in HIV or aTB, the functional capacities of M. tuberculosis–specific CD4+ T cells were comparable between the different clinical groups (Fig. 4B). The majority of M. tuberculosis–responding CD4+ T cells were polyfunctional, coexpressing IFN-γ, IL-2, and TNF-α (median: 69% for HIV/LTBI, 58% for HIV+/LTBI, 43% for HIV/aTB, and 67% for HIV+/aTB).

FIGURE 4.

Polyfunctional profile of M. tuberculosis–specific CD4+ T cells according to HIV and TB disease status. (A) Representative dot plots of IFN-γ, IL-2, and TNF-α production in response to cognate peptide in three individuals with distinct HIV and/or TB disease status. The frequencies of cytokine-producing cells are expressed as a percentage of total CD4+ T cells. (B) Pie charts and graph representing the cytokine secretion profiles of M. tuberculosis–specific CD4+ T cells in response to cognate peptide stimulation. The four clinical groups are depicted as in Fig. 3. Each section of the pie chart represents a specific combination of cytokines, as indicated by the color at the bottom of the graph. Horizontal bars and boxes depict the medians and interquartile ranges, respectively. The black arc on the pies corresponds to IFN-γ–producing cells. Statistical comparisons were performed using a Wilcoxon rank-sum test. NS, no stimulation.

FIGURE 4.

Polyfunctional profile of M. tuberculosis–specific CD4+ T cells according to HIV and TB disease status. (A) Representative dot plots of IFN-γ, IL-2, and TNF-α production in response to cognate peptide in three individuals with distinct HIV and/or TB disease status. The frequencies of cytokine-producing cells are expressed as a percentage of total CD4+ T cells. (B) Pie charts and graph representing the cytokine secretion profiles of M. tuberculosis–specific CD4+ T cells in response to cognate peptide stimulation. The four clinical groups are depicted as in Fig. 3. Each section of the pie chart represents a specific combination of cytokines, as indicated by the color at the bottom of the graph. Horizontal bars and boxes depict the medians and interquartile ranges, respectively. The black arc on the pies corresponds to IFN-γ–producing cells. Statistical comparisons were performed using a Wilcoxon rank-sum test. NS, no stimulation.

Close modal

As it has been shown that M. tuberculosis–specific CD4+ T cells are more permissive to HIV infection (25), we next wished to define whether such preferential targeting of M. tuberculosis–specific cells could alter their functionality by promoting cell exhaustion. Thus, we compared the frequency of ex vivo tetramer+CD4+ T cells to the frequency of M. tuberculosis–responding CD4+ T cells (i.e., cells producing IFN-γ, IL-2, or TNF-α) after cognate peptide stimulation to determine if M. tuberculosis–specific CD4+ T cells detected ex vivo using tetramers are functionally responsive to TCR triggering (Fig. 5A). The median frequency of M. tuberculosis–specific CD4+ T cells detected ex vivo using MHC class II tetramers was comparable to the median frequency of cytokine-responding CD4+ T cells in both the HIV-uninfected and HIV-infected groups (Fig. 5B). In fact, there was a strong positive correlation between the frequencies of ex vivo tetramer+CD4+ T cells and cytokine-producing CD4+ T cells (p < 0.0001, r = 0.71, Fig. 5C). Further analyses assessing the cytokine+/tetramer+ cell ratio in each clinical group revealed that, in some instances, cytokine+CD4+ T cell responses to cognate peptide were higher in magnitude (1.8- to 10-fold higher) compared with the frequency of the corresponding tetramer+CD4+ T cells (Fig. 5D). Such a profile was predominantly observed for DRB5*0101/CFP-1051–65 responses (11 out of 12), suggesting that the CFP-1051–65 peptide is likely to be a promiscuous epitope presented by multiple HLA class II alleles. For non-DRB5*0101 restricted–epitopes, the cytokine+/tetramer+ cell ratio was close to 1 and comparable between all clinical groups (median: 0.8 for HIV/LTBI, 0.78 for HIV+/LTBI, 1.2 for HIV/aTB, and 0.88 for HIV+/aTB, data not shown). Overall, these results suggest that neither HIV infection nor aTB promote M. tuberculosis–specific CD4+ T cell exhaustion, as most peripheral M. tuberculosis–specific CD4+ T cells detected ex vivo appear functional upon restimulation.

FIGURE 5.

Cytokine responsive potential of M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells according to HIV and TB disease status. (A) Representative examples of the frequency of TET+ cells and IFN-γ response to cognate peptide in two LTBI/HIV individuals. NS, no stimulation. (B) Comparison of the frequencies of ex vivo TET+CD4+ T cells and cytokine+ (CK+) cells in response to cognate peptide in HIV and HIV+ individuals (n = 17 and n = 13, respectively). The frequency of M. tuberculosis–specific CK+CD4+ T cells is defined as the frequency of cells expressing IFN-γ, IL-2, or TNF-α in response to cognate peptide after background (NS) subtraction. Bars represent medians. Triangles represent individuals with aTB. (C) Association between the frequency of ex vivo TET+CD4+ T cells and CK+CD4+ T cells in response to cognate peptide. The dotted line represents a slope of 1. Correlations were tested by a two-tailed nonparametric Spearman Rank test. (D) Ratio of the frequency of CK+CD4+ T cells/the frequency ex vivo TET+CD4+ T cells in each clinical group. Black symbols indicate DRB5*0101 CFP-1051–65 responses. The gray area highlights individuals with a CK+/TET+ ratio ≥1.8. Statistical comparisons were performed using a Wilcoxon matched pairs test.

FIGURE 5.

Cytokine responsive potential of M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells according to HIV and TB disease status. (A) Representative examples of the frequency of TET+ cells and IFN-γ response to cognate peptide in two LTBI/HIV individuals. NS, no stimulation. (B) Comparison of the frequencies of ex vivo TET+CD4+ T cells and cytokine+ (CK+) cells in response to cognate peptide in HIV and HIV+ individuals (n = 17 and n = 13, respectively). The frequency of M. tuberculosis–specific CK+CD4+ T cells is defined as the frequency of cells expressing IFN-γ, IL-2, or TNF-α in response to cognate peptide after background (NS) subtraction. Bars represent medians. Triangles represent individuals with aTB. (C) Association between the frequency of ex vivo TET+CD4+ T cells and CK+CD4+ T cells in response to cognate peptide. The dotted line represents a slope of 1. Correlations were tested by a two-tailed nonparametric Spearman Rank test. (D) Ratio of the frequency of CK+CD4+ T cells/the frequency ex vivo TET+CD4+ T cells in each clinical group. Black symbols indicate DRB5*0101 CFP-1051–65 responses. The gray area highlights individuals with a CK+/TET+ ratio ≥1.8. Statistical comparisons were performed using a Wilcoxon matched pairs test.

Close modal

Finally, we compared the phenotypic profile of M. tuberculosis–specific CD4+ T cells in their resting and stimulated states (Fig. 6A). Because IFN-γ expression comprised the predominate proportion of the M. tuberculosis–specific peptide response (Fig. 4B), and little nonspecific background for this cytokine was observed (data not shown), we focused on IFN-γ–producing cells to assess the phenotype of peptide-responding CD4+ T cells. Regardless of TB and HIV disease status, short-term TCR triggering using cognate peptide induced a significant decrease in CCR4 and HLA-DR expression, whereas KLRG1 was significantly elevated compared with tetramer+CD4+ T cells in their resting state (Fig. 6B). Additionally, in individuals with LTBI, M. tuberculosis peptide–stimulated IFN-γ+CD4+ T cells were also characterized by a significant decrease in CCR6 and CXCR3 expression compared with resting cells (p = 0.003 and p = 0.001, respectively, Fig. 6B). These latter changes were not observed in aTB, possibly because their expression was already decreased in resting M. tuberculosis–specific CD4+ T cells (Fig. 2D). Of note, these differences were not attributed to cell culture itself as the phenotypic profile of tetramer+CD4+ T cells observed ex vivo were comparable to unstimulated tetramer+CD4+ T cells after 16 h in culture (data not shown).

FIGURE 6.

Alteration of the phenotypic profile of ex vivo M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells upon short-term stimulation with cognate peptide. (A) Representative dot plots of ex vivo TET+CD4+ T cells (blue) and IFN-γ+CD4+ T cells (red) overlaid on total CD4+ T cell profile (gray) in one LTBI/HIV individual. (B) Expression of homing and activation markers on ex vivo TET+CD4+ T cells and IFN-γ+CD4+ T cells (after stimulation with cognate peptide) in LTBI individuals (n = 11, left panel) and individuals with aTB (n = 13, right panel). Bars represent the medians. Statistical comparisons were performed using a Wilcoxon matched pairs test. (C) Comparison of the phenotypic profile of IFN-γ+CD4+ T cells between clinical groups. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. **p < 0.01.

FIGURE 6.

Alteration of the phenotypic profile of ex vivo M. tuberculosis–specific MHC class II tetramer (TET)+CD4+ T cells upon short-term stimulation with cognate peptide. (A) Representative dot plots of ex vivo TET+CD4+ T cells (blue) and IFN-γ+CD4+ T cells (red) overlaid on total CD4+ T cell profile (gray) in one LTBI/HIV individual. (B) Expression of homing and activation markers on ex vivo TET+CD4+ T cells and IFN-γ+CD4+ T cells (after stimulation with cognate peptide) in LTBI individuals (n = 11, left panel) and individuals with aTB (n = 13, right panel). Bars represent the medians. Statistical comparisons were performed using a Wilcoxon matched pairs test. (C) Comparison of the phenotypic profile of IFN-γ+CD4+ T cells between clinical groups. Statistical comparisons were performed using a one-way ANOVA Kruskal–Wallis test. **p < 0.01.

Close modal

When comparing the phenotypic profile of IFN-γ+CD4+ T cells between clinical groups, Fig. 6C shows that chemokine receptor expression on IFN-γ+CD4+ T cells was comparable. This indicates that TCR triggering–induced changes in M. tuberculosis–specific CD4+ T cells partly masks the differences in chemokine receptor expression in ex vivo tetramer+CD4+ T cells (Fig. 2D). Conversely, despite the downregulation of HLA-DR upon peptide stimulation, HLA-DR on M. tuberculosis–specific IFN-γ+CD4+ T cells remained significantly higher in patients with aTB compared with LTBI (median: ∼35% versus ∼1%, respectively, Fig. 6C).

These data demonstrate that the phenotypic profile of M. tuberculosis–specific CD4+ T cells was considerably altered as a result of TCR triggering, showing that the use of MHC class II tetramers permitted us to define the phenotypic nature of ex vivo M. tuberculosis–specific CD4+ T cells in a resting state, and identified differences in the context of HIV and/or aTB disease that may have been overlooked if these cells were assessed after stimulation.

The use of MHC class II tetramers allows an unbiased quantification and characterization of Ag-specific CD4+ T cells in their resting state. In this study, to our knowledge we report for the first time in HIV coinfection and TB disease, the phenotypic and functional characterization ex vivo of M. tuberculosis–specific human CD4+ T cells using MHC class II tetramers. This allowed us to define the impact of HIV infection on ex vivo M. tuberculosis–specific CD4+ T cells and characterize these cells during aTB disease.

Firstly, we show comparable frequencies of ex vivo M. tuberculosis–specific CD4+ T cells between the HIV/LTBI, HIV+/LTBI, and HIV/aTB groups, and significantly higher frequencies in HIV+/aTB compared with other groups. These results could appear inconsistent with previous reports showing that M. tuberculosis–specific CD4+ T cells are preferentially depleted during HIV infection (25, 26). However, in our study cohort recruited from a highly TB endemic area, recurrent M. tuberculosis exposure and the relatively well-preserved CD4+ T cell count in HIV-infected individuals with LTBI (median: 558 cells per cm3) could account for the conservation of M. tuberculosis–specific CD4+ T cells. Moreover, elevated frequencies of M. tuberculosis–specific IFN-γ+CD4+ T cells have been reported in severely immunocompromised HIV-infected patients with LTBI or aTB (2629). Thus, the maintenance in the absolute number of M. tuberculosis–specific CD4+ T cells in aTB and HIV coinfection with severe lymphopenia demonstrates that bacterial replication induces the expansion of CD4+ T cells targeting M. tuberculosis, showing that memory M. tuberculosis responses are not eradicated in advanced HIV and that the residual M. tuberculosis–specific cells are not exhausted.

Secondly, assessing the phenotype of ex vivo M. tuberculosis–specific CD4+ T cells revealed that whereas aTB disease induced major alterations in cell profiles, HIV-induced changes were of a more subtle nature. During TB disease, ex vivo M. tuberculosis–specific CD4+ T cells were highly activated, and exhibited a mature memory phenotype and decreased expression of CXCR3. These specific cell features are typical of an acute infection, and suggest recent or ongoing cell stimulation (3033). Conversely, HIV infection per se did not induce significant changes in cell maturation or activation profile, but skewed the profile of chemokine receptor expression of ex vivo M. tuberculosis–specific CD4+ T cells. M. tuberculosis–specific cells in LTBI were previously reported to be almost exclusively CCR4CCR6+CXCR3+ (Th1*) (34, 35). In this report, we found their chemokine receptor expression profile to be more diverse, even in the absence of HIV infection. These differences may be explained by frequent exposure to M. tuberculosis in our setting. HIV infection led to a reduction in the CCR4CCR6+CXCR3+ subset, counterbalanced by the accumulation of CCR4+CCR6+CXCR3 cells (Th17) and a subset of cells coexpressing CCR4, CCR6, and CXCR3. This latter subset has been described in M. tuberculosis–specific CD4+ T cell clones generated from healthy individuals (22) and in peripheral blood from HIV-infected individuals on antiretroviral therapy (36). Functionally, these cells shared characteristics with Th17 and Th1/Th17 subsets, producing IFN-γ and low amounts of IL-17 (36). The diversity and complexity in the chemokine receptor expression patterns of CD4 responses specific for a single M. tuberculosis peptide are remarkable. Our data suggest that HIV infection may bias M. tuberculosis–specific CD4+ T cell responses toward a more Th17-like phenotype. However, the manner in which skewed profiles during HIV coinfection may affect M. tuberculosis containment remains to be determined. HIV-induced alteration of chemokine receptor expression has been reported previously (37, 38). These alterations during HIV infection may change the homing potential of M. tuberculosis–specific CD4+ T cells or affect their Th lineage commitment, as we reported previously (11). Moreover, recent reports demonstrate that the homing potential and Th differentiation status of M. tuberculosis–specific cells can dramatically influence immune protection against TB (39, 40).

The use of M. tuberculosis–specific MHC class II tetramers allowed us to accurately probe the functionality of resting M. tuberculosis–specific CD4+ T cells. We reveal that the majority of circulating M. tuberculosis–specific CD4+ T cells appeared functional, as the frequency of cytokine-producing cells reflected the frequency of tetramer+ cells, and was comparable, regardless of HIV infection or aTB disease. We did not observe functional differences between LTBI and aTB, consistent with previous reports (4144). This may be due to a limited number of participants analyzed in this study and CD4 responses to a single peptide not being representative of the response to the whole pathogen. However, these results further challenge the idea that polyfunctional Th1 cell responses to M. tuberculosis are protective (45). In addition, our data demonstrate that short-term TCR triggering induced considerable phenotypic changes in M. tuberculosis–specific CD4+ T cells, including substantial downregulation in chemokine receptor expression and upregulation of the inhibitory receptor KLRG1 (46). These phenomena have previously been reported for T cells of other specificities (30, 47). Such changes in recently activated cells could contribute to the negative regulation of T cell function. Due to the limited number of participants analyzed in this study, there was some disparity in age, gender, and HIV disease severity between the studied groups. Thus, it will be of value to confirm our results in a larger cohort. Moreover, in this study, we report on HIV and aTB-associated phenotypic and functional profiles of M. tuberculosis–specific CD4+ T cells in the circulation, and it remains to be determined whether similar profiles would be observed at the site of disease (i.e., in the lung).

Overall, we describe a broader profile of M. tuberculosis–specific Th cells in individuals from a high burden setting, with major phenotypic changes induced by aTB disease, and more subtle changes during unsuppressed HIV replication. It remains to be seen whether these perturbations are normalized after treatment for HIV and/or TB. MHC class II tetramers for TB represent a useful tool for further ex vivo characterization of M. tuberculosis–specific cells, without the need for in vitro stimulation and potential modulation of expression of markers of interest. Further transcriptomic characterization of tetramer-sorted M. tuberculosis–specific cells is underway, which may identify additional phenotypic or functional differences induced by HIV and aTB.

We thank the National Institutes of Health Tetramer Core Facility (Emory University) for providing the MHC class II tetramers used in this study. We thank Dr. Thomas J. Scriba from the South African Tuberculosis Vaccine Initiative for sharing knowledge and expertise regarding M. tuberculosis–specific MHC class II tetramer technology. We thank the study participants and staff at the Ubuntu HIV-TB clinic for their time and commitment to this project and Mrs. Kathryn Norman for administrative support.

This work was supported by the National Research Foundation of South Africa (92558 to C.R.) and the National Institutes of Health, Office of the Director (R21AI115977 to C.R.). W.A.B. was supported by the European and Developing Countries Clinical Trials Partnership (TA_08_40200_020), National Research Foundation of South Africa (92755), and the Wellcome Trust (089832/Z/09/Z). N.S. is supported by a Clinical Infectious Diseases Research Initiative postdoctoral fellowship. R.J.W. is supported by the Wellcome Trust (104803 and 203135), the European Union (FP7-Health-F3-2012-305578), Horizon 2020 under grant agreement 643381, The Francis Crick Institute, which receives support from Cancer Research U.K. (FC00110218), the U.K. Medical Research Council (FC00110218), the National Institutes of Health (U01AI115940), the Medical Research Council of South Africa via its strategic health innovations partnerships, and National Research Foundation of South Africa (96841). This project has been funded in part with federal funds from the Frederick National Laboratory for Cancer Research, under Contract HHSN261200800001E. The HLA typing of study participants was supported in part by the Intramural Research Program of the National Institutes of Health, Frederick National Lab, Center for Cancer Research.

The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • aTB

    active tuberculosis

  •  
  • LTBI

    latent TB infection

  •  
  • TB

    tuberculosis.

1
WHO
.
2016
.
Global Tuberculosis Report 2016.
WHO
,
Geneva, Switzerland
.
2
Aaron
,
L.
,
D.
Saadoun
,
I.
Calatroni
,
O.
Launay
,
N.
Mémain
,
V.
Vincent
,
G.
Marchal
,
B.
Dupont
,
O.
Bouchaud
,
D.
Valeyre
,
O.
Lortholary
.
2004
.
Tuberculosis in HIV-infected patients: a comprehensive review.
Clin. Microbiol. Infect.
10
:
388
398
.
3
Du Bruyn
,
E.
,
R. J.
Wilkinson
.
2016
.
The immune interaction between HIV-1 infection and Mycobacterium tuberculosis.
Microbiol. Spectr.
4
:
1
29
.
4
Whalen
,
C. C.
,
P.
Nsubuga
,
A.
Okwera
,
J. L.
Johnson
,
D. L.
Hom
,
N. L.
Michael
,
R. D.
Mugerwa
,
J. J.
Ellner
.
2000
.
Impact of pulmonary tuberculosis on survival of HIV-infected adults: a prospective epidemiologic study in Uganda.
AIDS
14
:
1219
1228
.
5
Kwan
,
C. K.
,
J. D.
Ernst
.
2011
.
HIV and tuberculosis: a deadly human syndemic.
Clin. Microbiol. Rev.
24
:
351
376
.
6
Okoye
,
A. A.
,
L. J.
Picker
.
2013
.
CD4(+) T-cell depletion in HIV infection: mechanisms of immunological failure.
Immunol. Rev.
254
:
54
64
.
7
Sonnenberg
,
P.
,
J. R.
Glynn
,
K.
Fielding
,
J.
Murray
,
P.
Godfrey-Faussett
,
S.
Shearer
.
2005
.
How soon after infection with HIV does the risk of tuberculosis start to increase? A retrospective cohort study in South African gold miners.
J. Infect. Dis.
191
:
150
158
.
8
Day
,
C. L.
,
N.
Mkhwanazi
,
S.
Reddy
,
Z.
Mncube
,
M.
van der Stok
,
P.
Klenerman
,
B. D.
Walker
.
2008
.
Detection of polyfunctional Mycobacterium tuberculosis-specific T cells and association with viral load in HIV-1-infected persons.
J. Infect. Dis.
197
:
990
999
.
9
Kalsdorf
,
B.
,
T. J.
Scriba
,
K.
Wood
,
C. L.
Day
,
K.
Dheda
,
R.
Dawson
,
W. A.
Hanekom
,
C.
Lange
,
R. J.
Wilkinson
.
2009
.
HIV-1 infection impairs the bronchoalveolar T-cell response to mycobacteria.
Am. J. Respir. Crit. Care Med.
180
:
1262
1270
.
10
Matthews
,
K.
,
M.
Ntsekhe
,
F.
Syed
,
T.
Scriba
,
J.
Russell
,
K.
Tibazarwa
,
A.
Deffur
,
W.
Hanekom
,
B. M.
Mayosi
,
R. J.
Wilkinson
,
K. A.
Wilkinson
.
2012
.
HIV-1 infection alters CD4+ memory T-cell phenotype at the site of disease in extrapulmonary tuberculosis.
Eur. J. Immunol.
42
:
147
157
.
11
Riou
,
C.
,
N.
Strickland
,
A. P.
Soares
,
B.
Corleis
,
D. S.
Kwon
,
E. J.
Wherry
,
R. J.
Wilkinson
,
W. A.
Burgers
.
2016
.
HIV skews the lineage-defining transcriptional profile of Mycobacterium tuberculosis-specific CD4+ T cells.
J. Immunol.
196
:
3006
3018
.
12
Nasi
,
M.
,
M.
Pinti
,
C.
Mussini
,
A.
Cossarizza
.
2014
.
Persistent inflammation in HIV infection: established concepts, new perspectives.
Immunol. Lett.
161
:
184
188
.
13
Morou
,
A.
,
B. E.
Palmer
,
D. E.
Kaufmann
.
2014
.
Distinctive features of CD4+ T cell dysfunction in chronic viral infections.
Curr. Opin. HIV AIDS
9
:
446
451
.
14
Tameris
,
M. D.
,
M.
Hatherill
,
B. S.
Landry
,
T. J.
Scriba
,
M. A.
Snowden
,
S.
Lockhart
,
J. E.
Shea
,
J. B.
McClain
,
G. D.
Hussey
,
W. A.
Hanekom
, et al
MVA85A 020 Trial Study Team
.
2013
.
Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomised, placebo-controlled phase 2b trial.
Lancet
381
:
1021
1028
.
15
Ndiaye
,
B. P.
,
F.
Thienemann
,
M.
Ota
,
B. S.
Landry
,
M.
Camara
,
S.
Dièye
,
T. N.
Dieye
,
H.
Esmail
,
R.
Goliath
,
K.
Huygen
, et al
MVA85A 030 trial investigators
.
2015
.
Safety, immunogenicity, and efficacy of the candidate tuberculosis vaccine MVA85A in healthy adults infected with HIV-1: a randomised, placebo-controlled, phase 2 trial.
Lancet Respir. Med.
3
:
190
200
.
16
Moonsamy
,
P. V.
,
T.
Williams
,
P.
Bonella
,
C. L.
Holcomb
,
B. N.
Höglund
,
G.
Hillman
,
D.
Goodridge
,
G. S.
Turenchalk
,
L. A.
Blake
,
D. A.
Daigle
, et al
.
2013
.
High throughput HLA genotyping using 454 sequencing and the Fluidigm Access Array™ System for simplified amplicon library preparation.
Tissue Antigens
81
:
141
149
.
17
Roederer
,
M.
,
J. L.
Nozzi
,
M. C.
Nason
.
2011
.
SPICE: exploration and analysis of post-cytometric complex multivariate datasets.
Cytometry A
79
:
167
174
.
18
Tikly
,
M.
,
A.
Rands
,
N.
McHugh
,
P.
Wordsworth
,
K.
Welsh
.
2004
.
Human leukocyte antigen class II associations with systemic sclerosis in South Africans.
Tissue Antigens
63
:
487
490
.
19
Sallusto
,
F.
,
A.
Lanzavecchia
.
2009
.
Heterogeneity of CD4+ memory T cells: functional modules for tailored immunity.
Eur. J. Immunol.
39
:
2076
2082
.
20
Sallusto
,
F.
,
C. R.
Mackay
,
A.
Lanzavecchia
.
2000
.
The role of chemokine receptors in primary, effector, and memory immune responses.
Annu. Rev. Immunol.
18
:
593
620
.
21
Acosta-Rodriguez
,
E. V.
,
L.
Rivino
,
J.
Geginat
,
D.
Jarrossay
,
M.
Gattorno
,
A.
Lanzavecchia
,
F.
Sallusto
,
G.
Napolitani
.
2007
.
Surface phenotype and antigenic specificity of human interleukin 17-producing T helper memory cells.
Nat. Immunol.
8
:
639
646
.
22
Becattini
,
S.
,
D.
Latorre
,
F.
Mele
,
M.
Foglierini
,
C.
De Gregorio
,
A.
Cassotta
,
B.
Fernandez
,
S.
Kelderman
,
T. N.
Schumacher
,
D.
Corti
, et al
.
2015
.
T cell immunity. Functional heterogeneity of human memory CD4+ T cell clones primed by pathogens or vaccines.
Science
347
:
400
406
.
23
Riou
,
C.
,
R.
Bunjun
,
T. L.
Müller
,
A.
Kiravu
,
Z.
Ginbot
,
T.
Oni
,
R.
Goliath
,
R. J.
Wilkinson
,
W. A.
Burgers
.
2016
.
Selective reduction of IFN-γ single positive mycobacteria-specific CD4+ T cells in HIV-1 infected individuals with latent tuberculosis infection.
Tuberculosis
101
:
25
30
.
24
Lindestam Arlehamn
,
C. S.
,
D. M.
McKinney
,
C.
Carpenter
,
S.
Paul
,
V.
Rozot
,
E.
Makgotlho
,
Y.
Gregg
,
M.
van Rooyen
,
J. D.
Ernst
,
M.
Hatherill
, et al
.
2016
.
A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans.
PLoS Pathog.
12
:
e1005760
.
25
Geldmacher
,
C.
,
N.
Ngwenyama
,
A.
Schuetz
,
C.
Petrovas
,
K.
Reither
,
E. J.
Heeregrave
,
J. P.
Casazza
,
D. R.
Ambrozak
,
M.
Louder
,
W.
Ampofo
, et al
.
2010
.
Preferential infection and depletion of Mycobacterium tuberculosis-specific CD4 T cells after HIV-1 infection.
J. Exp. Med.
207
:
2869
2881
.
26
Geldmacher
,
C.
,
A.
Schuetz
,
N.
Ngwenyama
,
J. P.
Casazza
,
E.
Sanga
,
E.
Saathoff
,
C.
Boehme
,
S.
Geis
,
L.
Maboko
,
M.
Singh
, et al
.
2008
.
Early depletion of Mycobacterium tuberculosis-specific T helper 1 cell responses after HIV-1 infection.
J. Infect. Dis.
198
:
1590
1598
.
27
Rangaka
,
M. X.
,
L.
Diwakar
,
R.
Seldon
,
G.
van Cutsem
,
G. A.
Meintjes
,
C.
Morroni
,
P.
Mouton
,
M. S.
Shey
,
G.
Maartens
,
K. A.
Wilkinson
,
R. J.
Wilkinson
.
2007
.
Clinical, immunological, and epidemiological importance of antituberculosis T cell responses in HIV-infected Africans.
Clin. Infect. Dis.
44
:
1639
1646
.
28
Hammond
,
A. S.
,
S. J.
McConkey
,
P. C.
Hill
,
S.
Crozier
,
M. R.
Klein
,
R. A.
Adegbola
,
S.
Rowland-Jones
,
R. H.
Brookes
,
H.
Whittle
,
A.
Jaye
.
2008
.
Mycobacterial T cell responses in HIV-infected patients with advanced immunosuppression.
J. Infect. Dis.
197
:
295
299
.
29
Vignesh
,
R.
,
N.
Kumarasamy
,
A.
Lim
,
S.
Solomon
,
K. G.
Murugavel
,
P.
Balakrishnan
,
S. S.
Solomon
,
K. H.
Mayer
,
C. R.
Swathirajan
,
E.
Chandrasekaran
, et al
.
2013
.
TB-IRIS after initiation of antiretroviral therapy is associated with expansion of preexistent Th1 responses against Mycobacterium tuberculosis antigens.
J. Acquir. Immune Defic. Syndr.
64
:
241
248
.
30
Sallusto
,
F.
,
E.
Kremmer
,
B.
Palermo
,
A.
Hoy
,
P.
Ponath
,
S.
Qin
,
R.
Förster
,
M.
Lipp
,
A.
Lanzavecchia
.
1999
.
Switch in chemokine receptor expression upon TCR stimulation reveals novel homing potential for recently activated T cells.
Eur. J. Immunol.
29
:
2037
2045
.
31
Petruccioli
,
E.
,
L.
Petrone
,
V.
Vanini
,
A.
Sampaolesi
,
G.
Gualano
,
E.
Girardi
,
F.
Palmieri
,
D.
Goletti
.
2013
.
IFNγ/TNFα specific-cells and effector memory phenotype associate with active tuberculosis.
J. Infect.
66
:
475
486
.
32
Adekambi
,
T.
,
C. C.
Ibegbu
,
S.
Cagle
,
A. S.
Kalokhe
,
Y. F.
Wang
,
Y.
Hu
,
C. L.
Day
,
S. M.
Ray
,
J.
Rengarajan
.
2015
.
Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response.
J. Clin. Invest.
125
:
1827
1838
.
33
Wilkinson
,
K. A.
,
T.
Oni
,
H. P.
Gideon
,
R.
Goliath
,
R. J.
Wilkinson
,
C.
Riou
.
2016
.
Activation profile of Mycobacterium tuberculosis-specific CD4(+) T cells reflects disease activity irrespective of HIV status.
Am. J. Respir. Crit. Care Med.
193
:
1307
1310
.
34
Lindestam Arlehamn
,
C. S.
,
A.
Gerasimova
,
F.
Mele
,
R.
Henderson
,
J.
Swann
,
J. A.
Greenbaum
,
Y.
Kim
,
J.
Sidney
,
E. A.
James
,
R.
Taplitz
, et al
.
2013
.
Memory T cells in latent Mycobacterium tuberculosis infection are directed against three antigenic islands and largely contained in a CXCR3+CCR6+ Th1 subset.
PLoS Pathog.
9
:
e1003130
.
35
Arlehamn
,
C. L.
,
G.
Seumois
,
A.
Gerasimova
,
C.
Huang
,
Z.
Fu
,
X.
Yue
,
A.
Sette
,
P.
Vijayanand
,
B.
Peters
.
2014
.
Transcriptional profile of tuberculosis antigen-specific T cells reveals novel multifunctional features.
J. Immunol.
193
:
2931
2940
.
36
Wacleche
,
V. S.
,
J. P.
Goulet
,
A.
Gosselin
,
P.
Monteiro
,
H.
Soudeyns
,
R.
Fromentin
,
M. A.
Jenabian
,
S.
Vartanian
,
S. G.
Deeks
,
N.
Chomont
, et al
.
2016
.
New insights into the heterogeneity of Th17 subsets contributing to HIV-1 persistence during antiretroviral therapy.
Retrovirology
13
:
59
.
37
Wacleche
,
V. S.
,
N.
Chomont
,
A.
Gosselin
,
P.
Monteiro
,
M.
Goupil
,
H.
Kared
,
C.
Tremblay
,
N.
Bernard
,
M. R.
Boulassel
,
J. P.
Routy
,
P.
Ancuta
.
2012
.
The colocalization potential of HIV-specific CD8+ and CD4+ T-cells is mediated by integrin β7 but not CCR6 and regulated by retinoic acid.
PLoS One
7
:
e32964
.
38
Bunders
,
M. J.
,
J. L.
van Hamme
,
M. H.
Jansen
,
K.
Boer
,
N. A.
Kootstra
,
T. W.
Kuijpers
.
2014
.
Fetal exposure to HIV-1 alters chemokine receptor expression by CD4+T cells and increases susceptibility to HIV-1.
Sci. Rep.
4
:
6690
.
39
Sakai
,
S.
,
K. D.
Mayer-Barber
,
D. L.
Barber
.
2014
.
Defining features of protective CD4 T cell responses to Mycobacterium tuberculosis.
Curr. Opin. Immunol.
29
:
137
142
.
40
Sallin
,
M. A.
,
S.
Sakai
,
K. D.
Kauffman
,
H. A.
Young
,
J.
Zhu
,
D. L.
Barber
.
2017
.
Th1 differentiation drives the accumulation of intravascular, non-protective CD4 T cells during tuberculosis.
Cell Reports
18
:
3091
3104
.
41
Harari
,
A.
,
V.
Rozot
,
F.
Bellutti Enders
,
M.
Perreau
,
J. M.
Stalder
,
L. P.
Nicod
,
M.
Cavassini
,
T.
Calandra
,
C. L.
Blanchet
,
K.
Jaton
, et al
.
2011
.
Dominant TNF-α+ Mycobacterium tuberculosis-specific CD4+ T cell responses discriminate between latent infection and active disease.
Nat. Med.
17
:
372
376
.
42
Pollock
,
K. M.
,
H. S.
Whitworth
,
D. J.
Montamat-Sicotte
,
L.
Grass
,
G. S.
Cooke
,
M. S.
Kapembwa
,
O. M.
Kon
,
R. D.
Sampson
,
G. P.
Taylor
,
A.
Lalvani
.
2013
.
T-cell immunophenotyping distinguishes active from latent tuberculosis.
J. Infect. Dis.
208
:
952
968
.
43
Lichtner
,
M.
,
C.
Mascia
,
I.
Sauzullo
,
F.
Mengoni
,
S.
Vita
,
R.
Marocco
,
V.
Belvisi
,
G.
Russo
,
V.
Vullo
,
C. M.
Mastroianni
.
2015
.
Multifunctional analysis of CD4+ T-cell response as immune-based model for tuberculosis detection.
J. Immunol. Res.
2015
:
217287
.
44
Kim
,
K.
,
R.
Perera
,
D. B.
Tan
,
S.
Fernandez
,
N.
Seddiki
,
J.
Waring
,
M. A.
French
.
2014
.
Circulating mycobacterial-reactive CD4+ T cells with an immunosuppressive phenotype are higher in active tuberculosis than latent tuberculosis infection.
Tuberculosis
94
:
494
501
.
45
Wilkinson
,
K. A.
,
R. J.
Wilkinson
.
2010
.
Polyfunctional T cells in human tuberculosis.
Eur. J. Immunol.
40
:
2139
2142
.
46
Voehringer
,
D.
,
M.
Koschella
,
H.
Pircher
.
2002
.
Lack of proliferative capacity of human effector and memory T cells expressing killer cell lectinlike receptor G1 (KLRG1).
Blood
100
:
3698
3702
.
47
McMahon
,
C. W.
,
A. J.
Zajac
,
A. M.
Jamieson
,
L.
Corral
,
G. E.
Hammer
,
R.
Ahmed
,
D. H.
Raulet
.
2002
.
Viral and bacterial infections induce expression of multiple NK cell receptors in responding CD8(+) T cells.
J. Immunol.
169
:
1444
1452
.

The authors have no financial conflicts of interest.

Supplementary data