bioRxivImmunologyPreprint
Shared and distinct immunometabolic states link to divergent pathology in cutaneous mycobacterial infections
Huangtao Guo, Rui ZengiD, Qin Wei, Jingshu XiongiD, Haiqin Jiang, Ying Shi, Wenyue Zhang, Chun Pan, Chaojiang ChengiD, Hongsheng Wang, Yetao WangiD
Abstract
Cutaneous mycobacterial infections provide a common tissue setting in which related intracellular pathogens elicit distinct pathological responses, but the innate immune basis of this divergence remains incompletely understood. Here, we combined single-cell profiling from 33 individuals with histological and functional analyses, examining healthy skin and lesions from multibacillary leprosy (MB), paucibacillary leprosy (PB), cutaneous tuberculosis (CTB) and Mycobacterium marinum infection (Mari). All infections showed lower mononuclear phagocyte and higher natural killer (NK) cell proportions within the CD45 compartment, alongside shared and infection-associated dendritic cell, macrophage and NK cell programs. CTB and Mari displayed broader macrophage antimicrobial signatures, whereas MB showed lipid-associated programs and attenuated interferon-associated effector expression across multiple macrophage subsets. Reduced expression of fructose-1,6-bisphosphatase 1 (FBP1) was associated with the absence of Langhans giant cells in MB, and pharmacological FBP1 inhibition nearly abolished fusion of macrophages. Compared with NK cells from Mari, MB NK cells showed reduced central carbon and oxidative metabolism signatures alongside increased lipid-associated programs. Functional experiments showed that inhibition of glucose utilization, disruption of mitochondrial function, or co-culture with foamy macrophages abundant in MB lesions reduced NK cell IFN-{gamma} production. These findings identify shared and distinct innate immune programs and suggest that their interplay with local metabolic environments shapes divergent pathology across cutaneous mycobacterial infections.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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