BMC Infectious Diseases (Feb 2025)
Single-cell transcriptome analysis reveals the dysregulated monocyte state associated with tuberculosis progression
Abstract
Abstract Background In tuberculosis (TB) infection, monocytes play a crucial role in regulating the balance between immune tolerance and immune response through various mechanisms. A deeper understanding of the roles of monocyte subsets in TB immune responses may facilitate the development of novel immunotherapeutic strategies and improve TB prevention and treatment. Methods We retrieved and processed raw single-cell RNA-seq data from SRP247583. Single-cell RNA-seq combined with bioinformatics analysis was employed to investigate the roles of monocytes in TB progression. Results Our findings revealed that classical monocytes expressing inflammatory mediators increased as the disease progressed, whereas non-classical monocytes expressing molecules associated with anti-pathogen infection were progressively depleted. Pseudotime analysis delineated the differentiation trajectory of monocytes from classical to intermediate to non-classical subsets. An abnormal differentiation trajectory to non-classical monocytes may represent a key mechanism underlying TB pathogenesis, with CEBPB and CORO1A identified as genes potentially related to TB development. Analysis of key transcription factors in non-classical monocytes indicated that IRF9 was the only downregulated transcription factor with high AUC activity in this subset. The expression of IRF9 exhibited a decreasing trend in both latent TB infection (LTBI) and active TB groups. Furthermore, dysregulation of transcription factor regulatory networks appeared to impair ferroptosis, with ferroptosis-associated genes MEF2C, MICU1, and PRR5 identified as potential targets of IRF9. Through cell communication analysis, we found that interactions between non-classical monocytes and other subpopulations may mediate TB progression, with MIF and LGALS9 highlighted as potential signaling pathways. Conclusion This study employs bioinformatics analysis in conjunction with single-cell sequencing technology to uncover the crucial role of monocyte subsets in tuberculosis infection.
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