Proteome- and transcriptome-driven reconstruction of the human myocyte metabolic network and its use for identification of markers for diabetes

Cell Rep. 2015 May 12;11(6):921-933. doi: 10.1016/j.celrep.2015.04.010. Epub 2015 Apr 30.

Abstract

Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers* / metabolism
  • Diabetes Mellitus, Type 2* / genetics
  • Diabetes Mellitus, Type 2* / metabolism
  • Female
  • Gene Expression Regulation
  • Humans
  • Male
  • Metabolic Networks and Pathways* / genetics
  • Middle Aged
  • Models, Biological
  • Muscle Cells* / metabolism
  • Oligonucleotide Array Sequence Analysis
  • Proteome* / metabolism
  • Reproducibility of Results
  • Sequence Analysis, RNA
  • Transcriptome* / genetics

Substances

  • Biomarkers
  • Proteome