Multi-omics study identifies novel signatures of DNA/RNA, amino acid, peptide, and lipid metabolism by simulated diabetes on coronary endothelial cells.

Coronary artery endothelial cells (CAEC) exert an important role in the development of cardiovascular disease. Dysfunction of CAEC is associated with cardiovascular disease in subjects with type 2 diabetes mellitus (T2DM). However, comprehensive studies of the effects that a diabetic environment exerts on this cellular type are scarce. The present study characterized the molecular perturbations occurring on cultured bovine CAEC subjected to a prolonged diabetic environment (high glucose and high insulin). Changes at the metabolite and peptide level were assessed by Liquid Chromatography-Mass Spectrometry (LC-MS2) and chemoinformatics. The results were integrated with published LC-MS2-based quantitative proteomics on the same in vitro model. Our findings were consistent with reports on other endothelial cell types and identified novel signatures of DNA/RNA, amino acid, peptide, and lipid metabolism in cells under a diabetic environment. Manual data inspection revealed disturbances on tryptophan catabolism and biosynthesis of phenylalanine-based, glutathione-based, and proline-based peptide metabolites. Fluorescence microscopy detected an increase in binucleation in cells under treatment that also occurred when human CAEC were used. This multi-omics study identified particular molecular perturbations in an induced diabetic environment that could help unravel the mechanisms underlying the development of cardiovascular disease in subjects with T2DM.

Towards a systems-level understanding of mitochondrial biology.

Human mitochondria are complex and highly dynamic biological systems, comprised of over a thousand parts and evolved to fully integrate into the specialized intracellular signaling networks and metabolic requirements of each cell and organ. Over the last two decades, several complementary, top-down computational and experimental approaches have been developed to identify, characterize and modulate the human mitochondrial system, demonstrating the power of integrating classical reductionist and discovery-driven analyses in order to de-orphanize hitherto unknown molecular components of mitochondrial machineries and pathways. To this goal, systematic, multiomics-based surveys of proteome composition, protein networks, and phenotype-to-pathway associations at the tissue, cell and organellar level have been largely exploited to predict the full complement of mitochondrial proteins and their functional interactions, therefore catalyzing data-driven hypotheses. Collectively, these multidisciplinary and integrative research approaches hold the potential to propel our understanding of mitochondrial biology and provide a systems-level framework to unraveling mitochondria-mediated and disease-spanning pathomechanisms.