Tumor necrosis factor alpha and insulin-like growth factor 1 induced modifications of the gene expression kinetics of differentiating skeletal muscle cells

Introduction TNF-α levels are increased during muscle wasting and chronic muscle degeneration and regeneration processes, which are characteristic for primary muscle disorders. Pathologically increased TNF-α levels have a negative effect on muscle cell differentiation efficiency, while IGF1 can have a positive effect; therefore, we intended to elucidate the impact of TNF-α and IGF1 on gene expression during the early stages of skeletal muscle cell differentiation. Methodology/Principal Findings This study presents gene expression data of the murine skeletal muscle cells PMI28 during myogenic differentiation or differentiation with TNF-α or IGF1 exposure at 0 h, 4 h, 12 h, 24 h, and 72 h after induction. Our study detected significant coregulation of gene sets involved in myoblast differentiation or in the response to TNF-α. Gene expression data revealed a time- and treatment-dependent regulation of signaling pathways, which are prominent in myogenic differentiation. We identified enrichment of pathways, which have not been specifically linked to myoblast differentiation such as doublecortin-like kinase pathway associations as well as enrichment of specific semaphorin isoforms. Moreover to the best of our knowledge, this is the first description of a specific inverse regulation of the following genes in myoblast differentiation and response to TNF-α: Aknad1, Cmbl, Sepp1, Ndst4, Tecrl, Unc13c, Spats2l, Lix1, Csdc2, Cpa1, Parm1, Serpinb2, Aspn, Fibin, Slc40a1, Nrk, and Mybpc1. We identified a gene subset (Nfkbia, Nfkb2, Mmp9, Mef2c, Gpx, and Pgam2), which is robustly regulated by TNF-α across independent myogenic differentiation studies. Conclusions This is the largest dataset revealing the impact of TNF-α or IGF1 treatment on gene expression kinetics of early in vitro skeletal myoblast differentiation. We identified novel mRNAs, which have not yet been associated with skeletal muscle differentiation or response to TNF- α. Results of this study may facilitate the understanding of transcriptomic networks underlying inhibited muscle differentiation in inflammatory diseases.