Clustering Mycobacterium tuberculosis-specific CD154+CD4+ T cells for distinguishing tuberculosis disease from infection based on single-cell RNA-seq analysis

Background

Distinguishing between active tuberculosis disease (TBD) and latent tuberculosis infection (TBI) is crucial for TB control but remains challenging.

Methods

Single-cell RNA sequencing was conducted on purified Mycobacterium tuberculosis (MTB)-specific CD154⁺CD4⁺ T cells.

Results

We observe a superior role of CD154 in detecting MTB infection, whereas its ability in distinguishing TBD from TBI is still limited due to patient heterogeneity. Single-cell RNA sequencing of MTB-specific CD154⁺CD4⁺ T cells identifies 10 distinct clusters, including Treg, T_act, Th1_pex, Th1_eff, Tfh, T_na, Th17_ex, Th2, NKT, and Th1_cyt. Notably, effector and apoptotic Th1 cells are predominant in CD154⁺CD4⁺ T cells of TBD. However, Tfh cells are the primary component in TBI. Most Th1_pex cells are positioned at the end of the developmental trajectory and are regulated by key genes associated with apoptosis and early exhaustion, such as GADD45B, FOS, and EZH2. Oxidative stress-induced metabolic disorder, marked by increased metabolism of nitrogen, cysteine, and glutathione, also contributes to the apoptosis of Th1_pex cells. Using seven features including NA, CM, EM, EMRA, CXCR3⁺ Th1, IFN-γ⁺ Th1, and Tfh of CD154⁺CD4⁺ T cells, both TBD and TBI can be classified into different subtypes, and a further established random forest model can accurately differentiate TBD from TBI. Additionally, the key checkpoints of exhausted MTB-specific Th1 cells are identified and blocking ADORA2A efficiently restores their function.

Conclusions

We depict the cellular compositions, transcriptional characteristics, and developmental trajectories of MTB-specific CD154⁺CD4⁺ T cells from TBI to TBD, putting forward a new direction in the diagnosis and prognosis of disease.