Secretome Analysis of Lipid-Induced Insulin Resistance in Skeletal Muscle Cells by a Combined Experimental and Bioinformatics Workflow

Skeletal
muscle has emerged as an important secretory organ that
produces so-called myokines, regulating energy metabolism via autocrine,
paracrine, and endocrine actions; however, the nature and extent of
the muscle secretome has not been fully elucidated. Mass spectrometry
(MS)-based proteomics, in principle, allows an unbiased and comprehensive
analysis of cellular secretomes; however, the distinction of bona
fide secreted proteins from proteins released upon lysis of a small
fraction of dying cells remains challenging. Here we applied highly
sensitive MS and streamlined bioinformatics to analyze the secretome
of lipid-induced insulin-resistant skeletal muscle cells. Our workflow
identified 1073 putative secreted proteins including 32 growth factors,
25 cytokines, and 29 metalloproteinases. In addition to previously
reported proteins, we report hundreds of novel ones. Intriguingly,
∼40% of the secreted proteins were regulated under insulin-resistant
conditions, including a protein family with signal peptide and EGF-like
domain structure that had not yet been associated with insulin resistance.
Finally, we report that secretion of IGF and IGF-binding proteins
was down-regulated under insulin-resistant conditions. Our study demonstrates
an efficient combined experimental and bioinformatics workflow to
identify putative secreted proteins from insulin-resistant skeletal
muscle cells, which could easily be adapted to other cellular models.