Conceived and designed the experiments: JS. Performed the experiments: JY. Analyzed the data: JY JS. Wrote the paper: JS. Recruited all subjects with epidemiological data: IMA. Intellectual input for design of experiments and manuscript preparation: MOO.
Current address: The University of Manchester, Manchester, United Kingdom
The authors have declared that no competing interests exist.
T cells producing multiple factors have been shown to be required for protection from disease progression in HIV but we have recently shown this not to be the case in TB. Subjects with active disease had a greater proportion of polyfunctional cells responding to ESAT-6/CFP-10 stimulation than their infected but non-diseased household contacts (HHC). We therefore wanted to assess this profile in subjects who had successfully completed standard TB chemotherapy.
We performed a cross-sectional study using PBMC from TB cases (pre- and post-treatment) and HHC. Samples were stimulated overnight with TB antigens (ESAT-6/CFP-10 and PPD) and their CD4+ and CD8+ T cells were assessed for production of CD107a, IFN-γ, IL-2 and TNF-α and the complexity of the responses was determined using SPICE and PESTLE software.
We found that an increase in complexity (i.e., production of more than 1 factor simultaneously) of the T cell profile was associated with TB disease and that this was significantly reduced following TB treatment. This implies that T cells are able to respond adequately to TB antigens with active disease (at least initially) but the ability of this response to protect the host from disease progression is hampered, presumably due to immune evasion strategies by the bacteria. These findings have implications for the development of new diagnostics and vaccine strategies.
Tuberculosis (TB) is a global health problem with 2 billion people infected with the causative agent
MTb is an intracellular pathogen that infects macrophages and triggers a cascade of cell-mediated immune responses. IFN-γ producing CD4+ T cells provide the major effector response to TB but while IFN-γ is required for protection against disease progression in TB it is not sufficient on its own
For a particular immune profile to be associated with TB disease, abrogation or reversal needs to be shown following standard treatment regimes for TB. As such, we compared the PFT cell profiles of TB cases before and after treatment to that seen in latently infected household contacts (HHC) following stimulation with MTb antigens. We found a significant increase in the proportion of both CD4+ and CD8+ T cells expressing CD107a, IFN-γ and TNF-α but not IL-2 in patients with active TB disease prior to treatment compared to post-treatment responses. Following successful TB treatment, the proportion of cytokine positive cells was reduced to levels equivalent to that seen in HHC. Furthermore, subjects with active TB disease had significantly higher levels of T cells producing 2 or more factors which were again reduced following treatment. These findings have implications for development of new diagnostics and vaccine strategies.
We analysed production of total IFN-γ, IL-2, TNF-α and CD107a following overnight stimulation with ESAT-6/CFP-10 (EC), PPD-T and PHA as a positive control (
%CD4 | %CD8 | |||||
Cases | Cases | Contacts | Cases | Cases | Contacts | |
Stimulation | pre-treatment | post-treatment | TST+ | pre-treatment | post-treatment | TST+ |
PHA | 10.5[6.6–13.4] | 4.1[2.1–8.5] |
4.2[2.7–6.2] |
17.3[15–24.2] | 6.4[1.6–11.9] |
5.4[3.5–7.4] |
PPD | 3.7[2.2–6.3] | 2.4[1.1–3.4] | 2.8[0.7–4.2] | 12[6.5–14.4] | 2.1[1.8–3.7] |
2[0.7–4.5] |
EC | 7.6 |
2[1.2–3.4] |
2.3[0.7–4] |
12[5.5–13] | 2.5[1.9–3.6] |
2.7[1.1–5.4] |
Data expressed as median [interquartile range (IQR)]-positive cells per subset.
* = p≤0.05;
** = p≤0.01,
*** = p≤0.001 compared to TB cases pre-treatment.
The proportion of CD4+ or CD8+ cells positive for any one factor following PHA stimulation was significantly increased in TB cases before treatment compared to both HHC and cases following treatment (p<0.01 and p<0.05 respectively;
All our results following analysis of 4 factors were consistent with our previous findings analysing 3-factors
Bar indicates median of TB cases pre-treatment (n = 12, filled circles), TB cases post-treatment (n = 10, open circles) and 17 HHC (triangles). Data were analysed using a Kruskal-Wallis ANOVA followed by Dunn's post-test comparison and p-values indicated.
We next assessed the combination of CD107a, IFN-γ, IL-2 and TNF-α produced by both CD4+ and CD8+ T cells in TB cases pre and post-treatment compared to HHC following overnight stimulation with ESAT-6/CFP-10. Prior to treatment, TB cases had significantly higher levels of CD4+ T cells producing 2 or more factors simultaneously compared to TB cases following treatment and HHC (p = 0.048 and p = 0.018 respectively;
PBMC were stimulated overnight using ESAT-6/CFP-10 and CD4+ and CD8+ cells were analysed by flow cytometry for different combinations of IFN-γ, IL-2, TNF-α and CD107a. Responses are grouped and colour coded according to the number of factors: White = 1 function, black = any 2 factors, blue = any 3 factors and red = all 4 factors. The pie charts summarise the results shown in the dot plots indicating the combination of cytokines as a percent of total responding cells for CD4+ (A) and CD8+ (B). Significant differences are indicated and were determined using a Kruskal-Wallis ANOVA followed by Dunn's post-test comparison. Pie chart segments were analysed using a permutation test and p-values indicated.
This study assessed the functional differences in T cell responses to Mycobacterial antigens depending on the infection status of the individual. We found that the complexity of the T cell response to TB antigenic stimulation was much higher in subjects with active TB disease than in latently infected household contacts and that this response was contracted following successful TB treatment. This indicates that the initial progression of TB disease is not due to impaired T cell function but most likely is determined by pathogen related factors which hamper the ability of the T cells to provide protective immune responses.
Production of multiple cytokines has been associated with protection from disease progression in HIV
There are other potential contributing factors to this anomaly of the immune system: why an observed increase in T cell function in TB disease does not equate to protection from disease progression. These include an increase in T regulatory cells in active TB disease
Few studies have assessed the contribution of degranulation in the immune response to TB antigens. We wanted to analyse this factor in our study as it is mainly produced by CD8+ T cells, which have been shown to preferentially recognise heavily infected cells
In conclusion, this study has shown that the response of T cells to TB-specific antigens is increased and more complex in patients with active TB disease compared to their latently infected HHC and that these responses are contracted following successful TB treatment. This suggests that loss of T cell function is not the initial factor in development of active TB disease and supports the requirement for biomarkers of TB disease to account for the stage of disease and bacterial load.
This study was conducted according to the principles expressed in the Declaration of Helsinki. Ethical approval was obtained from the Gambia Government/Medical Research Council Joint Ethics Committee. All patients provided written informed consent for the collection of samples and subsequent analysis.
This was a cross-sectional study involving 12 treatment-naive patients with active TB, 10 patients after TB treatment and 17
Peripheral blood mononuclear cells (PBMC) were isolated using density gradient centrifugation according to the Leucosep® tube protocol (Greiner Bio-one, USA). After two washes, cells were resuspended in RPMI+10% AB serum (Sigma, USA), supplemented with penicillin/streptomycin and L-glutamine and counted using a hemocytometer and trypan blue exclusion.
2 million PBMC resuspended in 1 mL of complete medium were added to single wells of a 24-well plate (Nunc, Germany). Each subject had five different stimulation set-ups: negative (media alone), positive (PHA; 5 µg/mL), PPD-T (10 µg/mL) and ESAT-6/CFP-10 peptides (EC; 10 µg/mL). In addition, CD107a-FITC (20 µL per well; Ebioscience, UK) was added for detection of degranulation. Brefeldin A (10 µg/mL; Sigma USA) and Monensin (0.7 µL/mL; Becton-Dickinson USA) were added after 2 hours and plates incubated overnight at 37°C, 5% CO2.
Following overnight stimulation, cells were transferred to tubes for flow cytometric acquisition (Dako, USA). Following centrifugation (600gmax), supernatant was carefully removed and 20 µL of previously titrated surface marker cocktail was added (CD4-APC-Cy7, CD8-PerCP; BDPharmingen). In addition a live-dead fixable stain was included to enable gating out of any non-viable cells (Invitrogen, USA) Tubes were vortexed and incubated for 15 min. at 4°C. Following washing, 150 µL of Fix/Lyse solution (BDPharmingen) was added per tube, vortexed and incubated at 4°C for 15 min. Cells were washed again and 500 µL of 1× Perm/wash solution (BDpharmingen) was then added; tubes vortexed and incubated for 20 min. at RT in the dark. Following centrifugation the supernatant was carefully removed and 20 µl of cytokine cocktail added (IFN-γ-APC, TNF-α-PECy7 and IL-2-PE; BDPharmingen). Tubes were again vortexed and incubated for 30 min. at RT in the dark, then washed, and cells resuspended in 1% paraformaldehyde (PFA) prior to acquisition.
At least 200,000 lymphocytes were acquired with a CyAn ADP™ (Beckman Coulter, USA) flow cytometer following gating according to 90° forward and side scatter plots. FACS plots were analysed using FlowJo software (version 6.1.1; Treestar, OR). Combinatorial cytokine data were analysed with PESTLE (version 1.5.4) and SPICE (version 4.1.5) software obtained from M. Roederer (National Institutes of Health, Bethesda, MD). Percent frequencies of the different combinations of CD107a, IL-2, TNF-α and IFN-γ+ cells following antigenic stimulation were calculated within the total population of CD4+ or CD8+ T cells and background subtracted (as determined from the medium alone control). Non-specific background was extremely low when more than one cytokine was examined. A cut-off of 0.01% was used as described previously
Group medians and distributions for TB cases pre- and post-treatment and household contacts (HHC) were compared using the Kruskal-Wallis ANOVA with Dunn's post-test comparison using GraphPad Prism software version 5 (Software MacKiev). Comparison of cytokine combinations was assessed using ANOVA and pie graphs analysed using an in-built permutation test (SPICE version 4.1.5).
We thank all study participants, Mr. Simon Donkor for data management, field workers for sample collection, the TB Immunology laboratory staff, and the Gambian National Tuberculosis and Leprosy Control programme for continuing collaboration.