Cell-type distribution of BAL cells
Our study was restricted to PLWH on long-term anti-retroviral therapy (ART) with no history of TB despite long-term exposure to Mtb (Fig. 1a). The 14 participants belonged to two well defined phenotypic groups of equal size: participants classified as “LTBI” who tested IGRA positive and displayed a TST ≥ 10 mm, and participants coined “resisters” who persistently tested IGRA negative with a TST = 0 mm (Fig. 1a and Table 1)12. All participants agreed to undergo a BAL and the recovered cells were kept unstimulated or challenged with Mtb for 6h and 24h. We performed scRNA-seq to investigate the BAL cellular composition, gene expression levels in the absence of Mtb and the transcriptomic responses to Mtb challenge (Fig. 1a). After quality control resulting in exclusion of one resister and data integration, we obtained single-cell transcriptome results for 257,671 BAL cells from six resister and seven LTBI participants (Supplementary Table 1). Based on gene expression we found two main subsets of cells (Fig. 1b). Alveolar macrophages (AM) and dendritic cells (DC) constituted the largest subset corresponding to 89% of the cells while the remaining 11% of BAL cells consisted of lymphocytes (T, B and NK cells) (Fig. 1b-c). However, BAL cells comprised strikingly different proportions of myeloid and lymphoid cells between the two groups, where resisters presented a significantly higher proportion of lymphocytes (P = 0.0023, Fig. 1d-e). While all LTBI subjects had < 5% of lymphocytes in their BAL samples (mean 2.93%), BAL samples from resisters presented a large spread of lymphocyte proportions ranging from 4–62.5% (mean 24.78%, Fig. 1e and Extended Data Fig. 1). None of the clinical or demographic variables collected, correlated with the degree of lymphocytosis. We noted minor peripheral blood contamination in the BAL of three samples from both groups, which had no correlation with lymphocytosis (Supplementary Table 1). We also obtained peripheral blood mononuclear cells (PBMCs) from the same participants and found no significant differences in lymphocyte proportions (P = 0.61, Fig. 1f) or cell subpopulations in PBMC between the two groups (Supplementary Table 2).
Table 1
Demographic and clinical data from the participants.
Subject*
|
Group
|
Sex
|
Age (yrs)
|
ART time (yrs)
|
ART
|
IGRA
|
TST (mm)
|
HIV viral load (cp/mL)
|
2RTB0014
|
LTBI
|
M
|
51
|
14
|
TDF-FTC-EFV
|
Positive
|
10
|
20
|
2RTB0092
|
LTBI
|
F
|
42
|
11
|
TDF-FTC-EFV
|
Positive
|
20
|
20
|
2RTB0113
|
LTBI
|
F
|
51
|
13
|
TDF-FTC-EFV
|
Positive
|
16
|
NA
|
2RTB0148
|
LTBI
|
F
|
47
|
16
|
TDF-FTC-EFV
|
Positive
|
20
|
0
|
2RTB0196
|
LTBI
|
F
|
59
|
11
|
TDF-FTC-EFV
|
Positive
|
17
|
242
|
2RTB0205
|
LTBI
|
F
|
53
|
12
|
TDF-FTC-EFV
|
Positive
|
22
|
0
|
2RTB0215
|
LTBI
|
F
|
43
|
17
|
TDF-FTC-EFV
|
Positive
|
18
|
0
|
2RTB0058
|
Resister
|
F
|
55
|
8
|
TDF-FTC-EFV
|
Negative
|
0
|
0
|
2RTB0062
|
Resister
|
F
|
47
|
16
|
TDF-FTC-EFV
|
Negative
|
0
|
58
|
2RTB0183
|
Resister
|
F
|
41
|
14
|
TDF-3TC-ATV/r
|
Negative
|
0
|
0
|
2RTB0209
|
Resister
|
F
|
40
|
10
|
TDF-FTC-EFV
|
Negative
|
0
|
20
|
2RTB0224¶
|
Resister
|
F
|
49
|
15
|
TDF-FTC-EFV
|
Negative
|
0
|
0
|
2RTB0253
|
Resister
|
F
|
54
|
12
|
ABC-3TC-NVP
|
Negative
|
0
|
22
|
2RTB0269
|
Resister
|
F
|
57
|
11
|
TDF-FTC-EFV
|
Negative
|
0
|
20
|
3TC: Lamivudine; ABC: Abacavir; ATV/r: Atazanavir/ritonavir; cp: copies; EFV: Efavirenz; F: female; FTC: Emtricitabine; LTBI: latent tuberculosis infection; M: male; NA: not available; NVP: Nevirapine; TB: tuberculosis; TDF: tenofovir; yrs: years.
* All participants are non-smokers. Participants are from Xhosa ethnic group, except 2RTB0113 and 2RTB0205 who are from Sotho.
¶ Sample excluded due to high proportion of dead cells in BAL scRNA-seq libraries (> 70%).
|
Characteristics of lymphocyte subpopulations in the absence of Mtb
To better define the differences in BAL cell subpopulations between resister and LTBI samples, we re-integrated and clustered the myeloid and lymphoid cells separately. Re-integration and clustering were done with all the infected and non-infected samples at the two time-points. Among lymphocytes we identified 19 clusters (Fig. 2a, Extended Data Fig. 2 and Supplementary Table 3). The majority of lymphocyte clusters comprised T cells (CD3+), including CD4+ naïve T cells (CCR7, SELL [CD62L]), CD4+ regulatory T cells (FOXP3, CTLA4), CD8+ cytotoxic T cells (GZMs), and CD4+ and CD8+ TRM expressing tissue-resident (TR) markers (ITGA1 [CD49a], ITGAE [CD103], CXCR6 and CD69) (Fig. 2a-c and Extended Data Fig. 2). We also detected one cluster of NK cells (KLRC2, NCAM [CD56]) and one B cell cluster (MS4A1, CD79 and CD19) (Fig. 2a-c and Extended Data Fig. 2). For each participant, we determined the proportion of the lymphocyte subpopulations relative to their total lymphocyte count from the 6h non-infected samples. We compared these proportions between resister and LTBI participants using a Wilcoxon test and failed to detect significant differences (Fig. 2d). Similarly, we found no significant group differences in the ratio of CD4+ to CD8+ T cells in PBMC or BAL samples (median CD4/CD8 of 1.19 vs 1.13 in PBMC, and 0.51 vs 0.52 in BAL from resister vs LTBI, Supplementary Table 2). We also compared the proportions of lymphocyte clusters relative to the whole BAL which showed higher proportions of all resister clusters relative to LBTI BAL samples (Extended Data Fig. 3). Hence, differences in subpopulation proportions and CD4/CD8 ratios were not associated with lymphocytosis in the resister group.
We then compared the transcriptomic profile of BAL lymphocytes from resister to LTBI BAL samples in the absence of ex-vivo Mtb challenge. The low T cell counts in LTBI samples precluded the use of a comprehensive pseudobulk differential expression (DE) analysis of lymphocyte clusters. Hence, on the single cell level we compared the expression by the 6h non-infected lymphocytes from the two groups for the genes that encode IFN-γ and antimicrobial peptides which are key effectors of T cell anti-mycobacterial immunity 26–28. Due to lymphocytosis, we found a significant larger numbers of IFNG-positive cells for the resister group across all clusters (Fig. 2e). Among resisters, the clusters with the largest proportion of IFNG-positive cells were L.3 (GZMBhigh CD8+ T cell) and L.14 (FOShigh CD8+ T cell), with the latter cluster expressing CD69 and various heat shock protein (HSP) genes. The cells in the L.14 cluster not only displayed higher expression levels of IFNG but the proportion of IFNG-positive cells in resisters was significantly larger relative to LTBI (Fig. 2e). Finally, we determined the transcript counts of antimicrobial peptides granulysin (GNLY), granzyme B (GNZB) and perforin (PRF1)27,28. We detected one cluster, L.8, co-expressing the three genes at baseline (Fig. 2f). Since the cells were CD3 and CD8 positive, we annotated the L.8 cluster as CD8+ poly-cytotoxic T cells (Fig. 2b, Extended Data Fig. 2 and Supplementary Table 3). In L.8, GZMB and PRF1 were expressed at approximately the same level in cells from the resister and LTBI participants, while GNLY was detected with higher expression in the resister cells (Fig. 2f). Across all clusters, resister lymphocytes constitutively expressed higher counts of IFNG, GZMB and GNLY transcripts relative to LTBI.
Characteristics of alveolar macrophages in the absence of ex vivo Mtb challenge
Next, we annotated the subpopulations in the AM/DC subset where we identified 12 clusters (Fig. 3a and Supplementary Table 3). Of these, one small cluster (DC.9) consisted of DC, while all remaining clusters were subpopulations of macrophages (Fig. 3a-c). All macrophages expressed markers that were consistent with tissue-resident AM (MARCO, PPARG, FABP4) except for cluster MoAM.4 which we annotated as infiltrating monocyte-derived macrophages (CCL2, CSFR1, MMP9 and CD14) (Fig. 3b and Extended Data Fig. 2). We found no significant differences in the proportions of tissue-resident AM or infiltrating monocyte-derived macrophages between cells from resister and LTBI participants (Fig. 3d).
To analyze the transcriptomic profiles of these myeloid BAL cell populations, we performed pseudobulk DE analysis between cells from resister and LTBI participants in the absence of Mtb challenge. The DE analyses were done for each cluster independently, excluding AM.10, and AM.11 due to their low number of cells per library. For the nine AM clusters and the single DC cluster, we detected a total of 4,275 genes (comprised of 2,167 distinct genes) that were differentially expressed between resister and LTBI cells (Fig. 4a-b, Extended Data Fig. 3 and Supplementary Table 4). Strikingly, only the differentially expressed genes (DEG) with higher expression in resister cells resulted in enrichment of GO-terms/pathways (Fig. 4c and Supplementary Table 5). For example, AM from the resister group presented higher expression of genes for pathways related to oxidative phosphorylation as well as cytokine-, chemokine- and interleukin-mediated signaling, with the most pronounced differential gene expression in AM.3 (ERRFI1high TR-AM) and MoAM.4 cells (Fig. 4c).
Next, we investigated the extent to which differential baseline gene expression reflected changes in transcription factor (TF) activities. TF activity was inferred based on the gene expression of target genes induced or repressed by the TFs. For the TF regulatory network analysis, we calculated TF activity scores using the genes differently expressed between resisters and LTBI samples in the absence of Mtb (Fig. 4d and Supplementary Table 6). In AM, we found significant differences in TF activities between the groups for TFs involved in M1 and M2 macrophage polarization. For example, TFs AP1, NFKB, CEBPG and IRF1 that are linked to an M1-state showed stronger activity in AM from resisters (Fig. 4d). Similarly, we found higher expression of M1 genes such as IL6, CCL3 and IL1B as well as the lower expression of the canonical M2 marker CD163 in AM from resister compared to LTBI samples (Fig. 4e). This showed that alveolar macrophages from resisters were shifted towards an M1 transcriptomic profile in the absence of Mtb.
When we repeated the baseline comparison of resister vs LTBI in AM removing the effect of lymphocyte proportion from the model, we observed that this adjustment differently affected AM/DC clusters (Extended Data Fig. 4). More strikingly, while we still observed DEG between resister and LTBI cells, the number of DEG was small and the genes were enriched only in few GO-terms/pathways (Extended Data Fig. 4). This suggested that the vast majority of the AM/DC functional transcriptomic differences observed between resisters and LTBI were correlated with alveolar lymphocytosis.
Cell-cell communication in the absence of ex vivo Mtb challenge
We then investigated if the resister and LTBI phenotypes were reflected in an altered crosstalk between cell populations during short-term in-vitro culture. For that, we performed a cell-cell communication analysis of the non-infected cells with 6h of incubation by mapping the expression of receptor-ligand pairs across the BAL cell clusters from the resister and LTBI samples. We found that cell subpopulations from the resister group displayed more and stronger cell-cell interactions (Extended Data Fig. 6a). In both the resister and LTBI groups, AM presented a higher number of cell-cell interactions as senders (expressing the ligands) and receivers (expressing the receptors) than DC and lymphocytes (Fig. 5a). However, all AM clusters in the resister samples presented higher numbers of cell-cell communications than in the LTBI, a trend which was observed to a lesser extent in the lymphocyte clusters (Fig. 5a). When we further evaluated the cellular crosstalk, we observed a set of signaling pathways defined by different cell-cell interaction between resister and LTBI samples (Extended Data Fig. 6b). Consistent with the significantly higher number of IFNG-expressing cells in the absence of the ex vivo Mtb challenge (Fig. 4f-g), cell-cell communication for the IFN-γ signaling pathway was exclusively detected in the cells from the resisters (Extended Data Fig. 6b). In resisters, L.3 and L.14 presented significant cell-cell interactions as senders (expressing IFNG) with the myeloid cells as the receiver clusters (expressing IFNGR1 + IFNGR2) (Fig. 5b). TNF was mostly expressed in myeloid cells, but also in cluster L.3 (Fig. 5c-d). TNF receptor 1 (TNFRSF1A) was highly expressed only in AM, while TNF receptor 2 (TNFRSF1B) was found in both myeloid and lymphoid clusters (Fig. 5d). However, expression of TNFRSF1B was most pronounced in the MoAM.4 and DC.9 clusters which are not classical tissue-resident AM. There was a non-significant trend of higher expression of TNFRSF1A among resister macrophages (Fig. 5d). This might explain the higher number of cell-cell interactions within the TNF crosstalk in resister vs LTBI cells, especially the communications mediated by TNFRSF1A (Extended Data Fig. 6c). The crosstalk between TNF and TNFRSF1B was dominated by the higher T cell counts in resister lymphocyte clusters (Fig. 5d and Extended Data Fig. 6d). In summary, there was higher cell-cell crosstalk in resisters for INF-γ and TNF signalling relative to LTBI.
Alveolar macrophage response to ex vivo Mtb challenge
We next investigated the transcriptomic response of BAL cells after 6h and 24h of ex-vivo challenge with Mtb. Given the size of our study sample, we focused the analysis on established mycobactericidal mechanisms of human cells (Supplementary Table 7). In the myeloid cells, these were the antimicrobial peptide cathelicidin (CAMP), the defensins as well as TNF, which can mediate the killing of Mtb via induction of reactive oxygen species (ROS)29–31. Only one defensin gene, Defensin beta 1 (DEFB1), was expressed in the BAL cells. DEFB1 and CAMP were transcribed only by the tissue-resident AM and displayed reduced transcription with time in culture (Extended Data Fig. 7a). CAMP presented no significant change in expression after Mtb infection. In contrast, resister cells of clusters AM.3, AM.7 (Activated TR-AM) and AM.8 (ANXA1high TR-AM) exhibited a small but significant higher expression of DEFB1 over LTBI cluster cells at 24h of Mtb infection (Extended Data Fig. 7a). For TNF transcription, we observed significantly increased transcription at 6h post-infection (p.i.) for resister macrophages over LTBI cells in clusters AM.0 (ASH1Llow TR-AM), AM.2 (PEX14high TR-AM), AM.3, MoAM.4 and AM.11 (proliferating AM) (Fig. 6a). TNF transcription dropped substantially across all clusters at 24h but remained significantly higher in resister-derived cells for cluster AM.3 (Fig. 6a). Hence, while the TNF transcriptional response was consistently stronger for resister AM this superior TNF response was more pronounced at the early phase of Mtb infection.
Alveolar lymphocyte response to ex vivo Mtb challenge
When assessing the transcriptomic IFNG response of alveolar lymphocytes, we noticed a significant response to Mtb in cluster L.3 (GZMBhigh CD8+ cytotoxic T) by LTBI cells with stronger response observed at 6h (Fig. 6b). We did not observe a similar IFNG induction in any of the resister clusters. However, the baseline count of IFNG transcripts in L.3 resister cells was higher than the stimulated IFNG count in LTBI samples at both 6h and 24 h p.i. (Fig. 6b). Across the remaining T cell clusters, at 6h p.i. we observed significantly higher numbers of cells expressing IFNG transcripts in resister vs LTBI samples (Fig. 6b). Notable were L.14 (FOShigh CD8 + T) cells where resisters expressed higher levels of IFNG transcripts and a significantly larger proportion of cells were IFNG-positive compared to LTBI samples (Fig. 6b).
A main interest for our analyses were the expression changes in response to Mtb challenge of the mycobactericidal peptides GNLY, GNZB and PRF1. Irrespective of Mtb challenge, only the CD8+ poly-cytotoxic T cells from cluster L.8 (Poly-cytotoxic CD8 + T [GZMB/GNLY/PRF1high]) co-expressed all three genes (Fig. 2f and Fig. 6c). In L.8 cells from resister and LTBI samples, GNLY was induced to similar levels in both groups by Mtb infection (Fig. 6c). Similarly, GZMB was expressed at approximately the same level at 6h and 24h p.i. in resister and LTBI L.8 cells (Fig. 6c). Perforin showed a trend for higher expression in LTBI samples at 6h after Mtb challenge. However, at 24h PRF1 was expressed at the same level in a larger proportion of resister cells (Fig. 6c). Moreover, we noticed that the poly-cytotoxic CD8+ T cells from L.8 also expressed the genes for the NK activating receptors NKG2D (KLRK1) and NKG2C (KLRC2) as well as for the inhibitory receptor NKG2A (KLRC1) and for CD94 (KLRD1) required for the CD94/NKG2 complex (Fig. 2c and Supplementary Table 3).
KLRD1 was expressed at approximately the same level at 6h and 24h p.i. in both groups. Similarly, the KLRC1 gene encoding the inhibitory NKG2A receptor was expressed at approximately the same low levels at 6h and 24h after Mtb infection in both groups (Fig. 6c). Conversely, the genes encoding the activating receptors, KLRC2 and KLRK1, were expressed at higher levels in a larger proportion of L.8 cells by resisters. This was most pronounced for KLRK1 where at 24h p.i > 60% of L.8 cells in resisters expressed the gene vs only 20% in LTBI cells (3-fold difference, Fig. 6c). Overall, the ratios of activating and inhibitory receptors demonstrated a strong switch in favour of activation of the CD8+ poly-cytotoxic T cells in resisters. Even more striking, the numbers of L.8 cells in BAL samples were significantly different between resisters and LTBI samples (P = 0.0009). The mean ratio of the CD8+ poly-cytotoxic T cells was 0.077% of all BAL cells for the LTBI group and 1.2% for the resister group, presenting an over 15-fold increase in this group over LTBI (Fig. 6c).
The heterodimers NKG2A-CD94 (KLRC1 + KLRD1) and NKG2C-CD94 (KLRC2 + KLRD1) interact with HLA-E, while NKG2D (KLRK1) interacts with the non-classical MHC class I ligands MICA and MICB32,33. In our data, HLA-E was highly expressed in all AM/DC clusters and HLA-E expression was significantly induced by 24h of Mtb challenge to a similar extent in both groups (Extended Data Fig. 6b). MICA and MICB genes were transcribed by macrophages with higher expression at the 24h p.i. time-point (Extended Data Fig. 6c). MICB presented lower expression than MICA with similar levels by both groups. Conversely, at 24h MICA expression was increased in seven AM clusters from resisters over LTBI participants (Fig. 6d). Except cluster AM.10, the remaining six clusters expressed MICA in a higher proportion of resister cells (mean 34% vs 26.5%) at significantly higher levels (Supplementary Table 7). However, differences in expression levels were overall modest with log2FC < 0.1 (Supplementary Table 7). The most pronounced difference was found in AM.3 where a 1.5-fold higher proportion of infected cells expressed MICA transcripts in resister vs LTBI cells with log2FC = 0.125 (Fig. 6d, Supplementary Table 7). Combined, this supported the NKG2D (KLRK1) – MICA receptor ligand interaction as critical feature for recognition of infected AM by poly-cytotoxic CD8+ T cell.