Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism
Saori UematsuiD, Satoshi OhnoiD, Kaori Y. TanakaiD, Atsushi HatanoiD, Toshiya KokajiiD, Yuki ItoiD, Hiroyuki KubotaiD, Ken‐ichi HironakaiD, Yutaka SuzukiiD, Masaki MatsumotoiD, Keiichi I. NakayamaiD, Akiyoshi HirayamaiD, Tomoyoshi SogaiD, Shinya KurodaiD
Abstract
Glucose homeostasis is maintained by modulation of metabolic flux. Enzymes and metabolites regulate the involved metabolic pathways. Dysregulation of glucose homeostasis is a pathological event in obesity. Analyzing metabolic pathways and the mechanisms contributing to obesity-associated dysregulation in vivo is challenging. Here, we introduce OMELET: Omics-Based Metabolic Flux Estimation without Labeling for Extended Trans-omic Analysis. OMELET uses metabolomic, proteomic, and transcriptomic data to identify changes in metabolic flux, and to quantify contributions of metabolites, enzymes, and transcripts to the changes in metabolic flux. By evaluating the livers of fasting ob/ob mice, we found that increased metabolic flux through gluconeogenesis resulted primarily from increased transcripts, whereas that through the pyruvate cycle resulted from both increased transcripts and changes in substrates of metabolic enzymes. With OMELET, we identified mechanisms underlying the obesity-associated dysregulation of metabolic flux in liver. HighlightsO_LIWe created OMELET to infer metabolic flux and its regulation from multi-omic data. C_LIO_LIGluconeogenic and pyruvate cycle fluxes increased in fasting ob/ob mice. C_LIO_LITranscripts increases mediated the increase in gluconeogenic fluxes in ob/ob mice. C_LIO_LIIncreases in transcripts and substrates enhanced pyruvate cycle flux in ob/ob mice. C_LI
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