Data-driven research led by computational systems biology methods, encompassing bioinformatics of multiomics datasets and mathematical modeling, are critical for discovery. Herein, we describe a multiomics (metabolomics-fluxomics) approach as applied to heart function in diabetes. The methodology presented has general applicability and enables the quantification of the fluxome or set of metabolic fluxes from cytoplasmic and mitochondrial compartments in central catabolic pathways of glucose and fatty acids. Additionally, we present, for the first time, a general method to reduce the dimension of detailed kinetic, and in general stoichiometric models of metabolic networks at the steady state, to facilitate their optimization and avoid numerical problems. Representative results illustrate the powerful mechanistic insights that can be gained from this integrative and quantitative methodology.
Keywords: Diabetes; Fluxomics; Glucose and fatty acids catabolism; Heart; Kinetic modeling; Metabolomics.
© 2022. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.