Integrating quantitative proteomics and metabolomics in a cellular model of diabetic retinopathy

Abstract

Diabetic retinopathy is the leading cause of visual loss in individuals under the age of 55. Most investigations into the pathogenesis of diabetic retinopathy have been concentrated on the neural retina since this is where clinical lesions are manifested. Recently, however, various abnormalities in the structural and secretory functions of retinal pigment epithelium that are essential for neuroretina survival, have been found in diabetic retinopathy. In this context, here we study the effect of hyperglycemic and hypoxic conditions on the metabolism of a human retinal pigment epithelial cell line (ARPE-19) by integrating quantitative proteomics using tandem mass tagging (TMT), untargeted metabolomics using MS and NMR, and 13C-glucose isotopic labeling for metabolic tracking. We observed a remarkable metabolic diversification under our simulated in vitro hyperglycemic conditions of diabetes, characterized increased flux through polyol pathways and inhibition of the Krebs cycle and oxidative phosphorylation. Importantly, under low oxygen supply RPE cells seem to consume rapidly glycogen storages and stimulate anaerobic glycolysis. Our results therefore pave the way to future scenarios involving new therapeutic strategies addressed to modulating RPE metabolic impairment, with the aim of regulating structural and secretory alterations of RPE. Finally, this study shows the importance of tackling biomedical problems by integrating metabolomic and proteomics results.