Mining the secretome of C2C12 muscle cells

Secretome analysis faces several challenges, including detection of low abundant proteins and the discrimination of bona fide secreted proteins from false-positive identifications stemming from cell leakage or serum. Here, we developed a two-step secretomics approach and applied it for the analysis of secreted proteins of C2C12 skeletal muscle cells as the skeletal muscle has been identified as an important endocrine organ secreting myokines as active signaling molecules. First, we compared culture supernatants and corresponding cell lysates by high-resolution MS-based proteomics and label-free quantification. We found 672 protein groups as candidate secreted proteins, as they showed a higher abundance in the secretome. By Brefeldin A mediated blocking of classical secretory processes, we estimate a sensitivity of > 80% for the detection of classical secreted proteins by our experimental approach. In the second step, peptide level information was integrated with UniProt based protein information by the bioinformatics tool “lysate and secretome peptide feature plotter” (LSPFP) to detect proteolytic protein processing events which might occur during secretion e.g. As a proof on concept, we identified truncations of the cytoplasmic part of the protein Plexin-B2. Our workflow provides an efficient combination of experimental workflow and data analysis to identify putative secreted and proteolytic processed proteins.