A single-nucleus atlas of skeletal muscle regeneration identifies distinct macrophage populations and their cytokine environments 2257143
Skeletal muscle possesses a remarkable capacity for regeneration, a process tightly regulated by interactions between resident stem cells and the immune system. Following injury, a complex cascade of events is initiated, involving the infiltration of immune cells that clear debris and create a pro-regenerative environment. Among these, macrophages are critical mediators, exhibiting significant plasticity that allows them to switch from a pro-inflammatory to a pro-reparative phenotype. However, the full spectrum of macrophage heterogeneity and their precise communication with muscle cells remains elusive. Here, we present the first single-nucleus RNA sequencing (snRNA-seq) analysis of regenerating skeletal muscle, providing an unprecedented high-resolution view of the nuclear transcriptional landscape during tissue repair. This approach overcomes the limitations of single-cell RNA sequencing (scRNA-seq) by capturing transcripts from multinucleated myofibers and minimizing cellular stress artifacts. Our analysis identified three distinct macrophage subpopulations with unique transcriptional and spatial profiles. We uncovered a differential regulation axis linked to CSF-1 and IL-34, where IL-34 is expressed by smooth muscle cells in proximity to resting macrophages in the perimysium and epimysium, while CSF-1 expression is transiently upregulated by fibroblasts during inflammation. Comparative analysis of aged and dystrophic (mdx and BLA/J) mouse models demonstrated a direct correlation between the degree of inflammation, the abundance of macrophage and fibroblast populations, and the expression levels of CSF-1 and IL-34. These findings provide novel insights into macrophage heterogeneity in muscle physiology and pathology, suggesting that selectively targeting CSF-1 is a superior strategy for depleting pro-inflammatory macrophages in muscular dystrophies and age-related muscle decline. 2021R1I1A3059820 (National Research Foundation of Korea) Computational and Systems Immunology (COMP)