Proteomic profiling of non-obese type 2 diabetic skeletal muscle

Abnormal glucose handling has emerged as a major clinical problem in millions of diabetic patients worldwide. Insulin resistance affects especially one of the main target organs of this hormone, the skeletal musculature, making impaired glucose metabolism in contractile fibres a major feature of type 2 diabetes. High levels of circulating free fatty acids, an increased intramyocellular lipid content, impaired insulin-mediated glucose uptake, diminished mitochondrial functioning and an overall weakened metabolic flexibility are pathobiochemical hallmarks of diabetic skeletal muscles. In order to increase our cellular understanding of the molecular mechanisms that underlie this complex diabetes-associated skeletal muscle pathology, we initiated herein a mass spectrometry-based proteomic analysis of skeletal muscle preparations from the non-obese Goto-Kakizaki rat model of type 2 diabetes. Following staining of high-resolution two-dimensional gels with colloidal Coomassie Blue, 929 protein spots were detected, whereby 21 proteins showed a moderate differential expression pattern. Decreased proteins included carbonic anhydrase, 3-hydroxyisobutyrate dehydrogenase and enolase. Increased proteins were identified as monoglyceride lipase, adenylate kinase, Cu/Zn superoxide dismutase, phosphoglucomutase, aldolase, isocitrate dehydrogenase, cytochrome c oxidase, small heat shock Hsp27/B1, actin and 3-mercaptopyruvate sulfurtransferase. These proteomic findings suggest that the diabetic phenotype is associated with a generally perturbed protein expression pattern, affecting especially glucose, fatty acid, nucleotide and amino acid metabolism, as well as the contractile apparatus, the cellular stress response, the anti-oxidant defense system and detoxification mechanisms. The altered expression levels of distinct skeletal muscle proteins, as documented in this study, might be helpful for the future establishment of a comprehensive biomarker signature of type 2 diabetes. Reliable markers could be used for improving diagnostics, monitoring of disease progression and therapeutic evaluations.