STAT3 inhibition recovers regeneration of aged muscles by restoring autophagy in muscle stem cells.

Age-related reduction in muscle stem cell (MuSC) regenerative capacity is associated with cell-autonomous and non-cell-autonomous changes caused by alterations in systemic and skeletal muscle environments, ultimately leading to a decline in MuSC number and function. Previous studies demonstrated that STAT3 plays a key role in driving MuSC expansion and differentiation after injury-activated regeneration, by regulating autophagy in activated MuSCs. However, autophagy gradually declines in MuSCs during lifespan and contributes to the impairment of MuSC-mediated regeneration of aged muscles. Here, we show that STAT3 inhibition restores the autophagic process in aged MuSCs, thereby recovering MuSC ability to promote muscle regeneration in geriatric mice. We show that STAT3 inhibition could activate autophagy at the nuclear level, by promoting transcription of autophagy-related genes, and at the cytoplasmic level, by targeting STAT3/PKR phosphorylation of eIF2α. These results point to STAT3 inhibition as a potential intervention to reverse the age-related autophagic block that impairs MuSC ability to regenerate aged muscles. They also reveal that STAT3 regulates MuSC function by both transcription-dependent and transcription-independent regulation of autophagy.

Spatially resolved transcriptomics reveals innervation-responsive functional clusters in skeletal muscle.

Striated muscle is a highly organized structure composed of well-defined anatomical domains with integrated but distinct assignments. So far, the lack of a direct correlation between tissue architecture and gene expression has limited our understanding of how each unit responds to physio-pathologic contexts. Here, we show how the combined use of spatially resolved transcriptomics and immunofluorescence can bridge this gap by enabling the unbiased identification of such domains and the characterization of their response to external perturbations. Using a spatiotemporal analysis, we follow changes in the transcriptome of specific domains in muscle in a model of denervation. Furthermore, our approach enables us to identify the spatial distribution and nerve dependence of atrophic signaling pathway and polyamine metabolism to glycolytic fibers. Indeed, we demonstrate that perturbations of polyamine pathway can affect muscle function. Our dataset serves as a resource for future studies of the mechanisms underlying skeletal muscle homeostasis and innervation.