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, 200 (9), 3283-3290

Transcriptomic Analysis of CD4 + T Cells Reveals Novel Immune Signatures of Latent Tuberculosis

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Transcriptomic Analysis of CD4 + T Cells Reveals Novel Immune Signatures of Latent Tuberculosis

Julie G Burel et al. J Immunol.

Abstract

In the context of infectious diseases, cell population transcriptomics are useful to gain mechanistic insight into protective immune responses, which is not possible using traditional whole-blood approaches. In this study, we applied a cell population transcriptomics strategy to sorted memory CD4 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and gain insight into the phenotype of tuberculosis (TB)-specific CD4 T cells. We found a 74-gene signature that could discriminate between memory CD4 T cells from healthy latently Mycobacterium tuberculosis-infected subjects and noninfected controls. The gene signature presented a significant overlap with the gene signature of the Th1* (CCR6+CXCR3+CCR4-) subset of CD4 T cells, which contains the majority of TB-specific reactivity and is expanded in LTBI. In particular, three Th1* genes (ABCB1, c-KIT, and GPA33) were differentially expressed at the RNA and protein levels in memory CD4 T cells of LTBI subjects compared with controls. The 74-gene signature also highlighted novel phenotypic markers that further defined the CD4 T cell subset containing TB specificity. We found the majority of TB-specific epitope reactivity in the CD62L-GPA33- Th1* subset. Thus, by combining cell population transcriptomics and single-cell protein-profiling techniques, we identified a CD4 T cell immune signature of LTBI that provided novel insights into the phenotype of TB-specific CD4 T cells.

Conflict of interest statement

Disclosures

The authors have no financial conflicts of interest.

Figures

FIGURE 1
FIGURE 1
LTBI subjects can be discriminated from uninfected controls based on the transcriptomic profile of memory CD4 T cells. Memory CD4 T cells from 30 LTBI subjects and 29 uninfected controls were sorted by FACS, and RNA content was sequenced with the Illumina platform. (A) Volcano plot obtained from the DESeq2 analysis. The 74 differentially expressed genes are represented in red (adjusted p value < 0.05, absolute log2 fold change > 0.5). (B) Predictive value of gene signatures to discriminate between LTBI and uninfected subjects. The initial cohort was split into five random sets; a gene signature was identified for each combination of four sets (adjusted p value < 0.05, absolute log2 fold change > 0.5 from the DESeq2 analysis), and the PC1 component of the signature was used to predict the LTBI status within the remaining fifth set. (C) Heat map displaying rlog-transformed raw counts of the 74 differentially expressed genes from (A), with genes ordered with hierarchical clustering and subjects ordered based on PC1 component. (D) Pathway enrichment analysis (based on Ingenuity Pathway Analysis; QIAGEN). (E) Bcl2 expression in memory CD4 T cells, as measured by flow cytometry, from 20 LTBI subjects and 20 controls. ***p < 0.001, nonparametric Wilcoxon test.
FIGURE 2
FIGURE 2
The transcriptomic signature of LTBI in memory CD4 T cells has a significant overlap with the TB-specific Th1* subset. (A) Memory CD4 T cell subset composition in LTBI subjects compared with uninfected controls, as determined by flow cytometry. (B) TB-specific peptide reactivity (OX40+ PDL1+) among memory CD4 T cell subsets, as determined by flow cytometry, after PBMC stimulation for 24 h with MTB300 (22). Plots are from one representative subject (left panel). Line graph shows combined data from three LTBI subjects (right panel). (C) Overlap between the 74-gene signature identified in Fig. 1 and the previously described Th1* gene signature (34), based on the hypergeometric distribution test (considering the 21,992 transcripts detected within memory CD4 T cells as the total number of genes). (D) Heat map displaying rlog-transformed raw counts of the nine genes overlapping between the 74-gene signature and the Th1* gene signature, with genes ordered with hierarchical clustering and subjects ordered based on PC1 component. (E) Correlation between the PC1 component of the combined expression of the nine Th1* overlapping genes, identified in (C), in memory CD4 T cells and the frequency of Th1* in corresponding subjects, as determined by linear regression analysis. Data were derived from 20 LTBI subjects and 20 controls (A), (C), and (E) or from 3 LTBI subjects (B). **p < 0.01, ***p < 0.001, nonparametric Wilcoxon test.
FIGURE 3
FIGURE 3
Validation of the presence of the Th1* gene signature in memory CD4 T cells of LTBI subjects at the protein level. (A) ABCB1, c-KIT, and GPA33 expression at the mRNA (upper panels) and protein (lower panels) levels in memory CD4 T cells of LTBI subjects compared with uninfected controls. Gene-expression data were derived from 30 LTBI subjects and 29 uninfected controls using an Illumina sequencing platform. Protein-expression data were derived from 13 LTBI subjects and 15 uninfected controls using CyTOF. (B) ABCB1 activity in memory CD4 T cells of LTBI subjects (n = 12) compared with controls (n = 14), defined as the ratio of Rhodamine 123 mean fluorescence intensity between inhibitor and noninhibitor conditions (lower panel). Representative line graph (upper panel). (C) Frequency of ABCB1+, c-KIT+, and GPA33 cells among each memory CD4 T cell subset in LTBI subjects (n = 13) compared with controls (n = 15), as determined by CyTOF. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, nonparametric Wilcoxon test.
FIGURE 4
FIGURE 4
The Th1* subset with the CD62LGPA33 phenotype is expanded in LTBI and contains the majority of TB-reactive cells. (A) Representative staining plot of ABCB1, c-KIT, and GPA33 expression in the Th1* subset of one LTBI subject. (B) Top 10 genes with the highest correlation between GPA33 gene expression and the 65 genes differentially expressed in memory CD4 T cells of LTBI subjects (n = 30) versus controls (n = 29), but not overlapping with Th1*. CCR7 and CD62L protein expression of memory CD4 T cells (C) and frequencies of Th1* subsets (based on CD62L and GPA33 Boolean gating) (D) in LTBI subjects (n = 13) compared with controls (n = 15), as determined by CyTOF. Boolean gating was determined with FlowJo and analyzed with SPICE (version 5.3). (E) TB-specific peptide reactivity (OX40+PDL1+) among Th1* subsets, as determined by flow cytometry, after PBMC stimulation for 24 h with MTB300 (22) (left panel). Plots are from one representative subject. Line graph shows combined data from three LTBI subjects (right panel). The p value in (D) was determined using a permutation test. *p < 0.05, ***p < 0.001, nonparametric Wilcoxon test.

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