Identificação de moléculas de comunicação e interação celular no músculo esquelético em resposta ao exercício, condições catabólicas e envelhecimento utilizando dados transcriptômicos

Abstract

Skeletal muscle is responsive to various stimuli and plays a crucial role in various aspects of human health. Physical exercise elicits beneficial adaptive responses in the muscle, such as maintenance and increase of muscle mass, enhanced capacity, and release of myokines. Catabolic conditions like tumor cachexia, diabetes, disuse, aging, and sarcopenia negatively affect skeletal muscle, reducing protein synthesis, increasing protein degradation, impairing muscle cell function, and diminishing regenerative capacity. The aim of this study was to investigate the role of muscle secretome and interactome in physical exercise and catabolic conditions. Bulk RNA-Seq of human skeletal muscle datasets was utilized to identify and predict differentially expressed genes (DEGs) present in the human secretome. We characterized cell communication in human and mouse skeletal muscle datasets by predicting interactions between ligands and receptors. We used single-cell sequencing datasets (scRNA-Seq) of skeletal muscle to identify cell types involved in respective ligand-receptor interactions (LxR). The results demonstrate differences in the secretome of physical exercise, aging, and sarcopenia. Muscle cell communication highlights interactions between extracellular matrix components, endothelial components, and the immune system. Exercise enhances the expression of molecules involved in muscle growth and repair, while aging reduces the expression of these molecules. Under conditions leading to muscle atrophy, cell communication points to the role of immune system components in muscle regeneration. This study provides new insights into potential therapies targeting the muscle secretome and interactome to prevent and treat muscle atrophy.