| Summary: | Muscle atrophy arises from a multiplicity of physiological or pathological situations (e.g., aging, physical inactivity, diabetes, cancers …) and its consequences are very detrimental at whole-body level. Even though knowledge of the underlying mechanisms keeps growing, there is still no proven treatment to date. To address this major clinical challenge, we selected here an innovative approach that compares muscle adaptations between an original model of natural resistance to muscle atrophy, the hibernating brown bear (Ursus arctos), and a classical model of physical inactivity-induced atrophy, the unloaded mouse. Throughout the hibernation season, the brown bear remains continuously torpid up for 5-7 months, without normothermic interbout arousals, and thus dealing with fasting and prolonged physical inactivity. Remarkably, even facing with these two main atrophic inducers, the bear has the unique ability to withstand muscle loss. Using transcriptomic analysis by RNA sequencing, we identified 2693 differentially expressed genes between the active versus hibernating period in bear muscle. A general downregulation of genes involved in extracellular matrix structure organization was observed in the hibernating brown bear. We then decided to focus on TGF-β superfamily including i) the TGF-β signaling being a master regulator of the extracellular matrix organization, and as well involved in muscle mass loss and ii) the BMP signaling, recently discovered involved in muscle mass maintenance. During hibernation, gene expression of the TGF-β and BMP pathways components was overall downregulated and upregulated, respectively. On the contrary, an increased expression of TGF-β signaling genes and a decreased expression of BMP signaling genes was observed in mice muscles during physical inactivity. We have further substantiated this opposite regulation between atrophied muscles of the unloaded mouse and non-atrophied muscles of the hibernating bear at the protein level. Altogether, our data identified a balance between ...
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