ICAT-MS-MS time course analysis of atrophying mouse skeletal muscle cytosolic subproteome

Abstract

Skeletal muscle atrophy is a process in which protein degradation exceeds protein synthesis, resulting in a decrease of the muscle's physiological cross-sectional area and mass, and is often a serious consequence of numerous health problems. We used the isotope-coded affinity tag (ICAT) labelling approach and MS-MS to protein profile cytosolic subcellular fractions from mouse tibialis anterior skeletal muscle undergoing 0, 4, 8, or 16 days of immobilisation-induced atrophy. For the validation of peptide and protein identifications statistical algorithms were applied to the sequence database search results in order to obtain consistent sensitivity/error rates for protein and peptide identifications at each immobilisation time point. In this study, we identified and quantified a large number of mouse skeletal muscle proteins. At a protein probability (P) of P ≥ 0.9 (corresponding to a false positive error rate of less than 1%) 807 proteins were identified (231, 226, 217 for 4, 8, 16 days of immobilisation and 133 for the control sample, respectively), from which 51 displayed altered protein abundance with atrophy. Due to randomness of data acquisition, a full time course could be generated only for 62 proteins, most of which displayed unchanged protein abundance. In spite of this, useful information about dataset characteristics and underlying biological processes could be obtained through gene over-representation analysis. 20 gene categories—mainly but not exclusively encoded by the subset of overlapping proteins—were consistently found to be significantly (p < 0.05) over-represented in all 4 sub-datasets.