A model for determining cardiac mitochondrial substrate utilisation using stable 13C-labelled metabolites View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-11-26

AUTHORS

Ross T. Lindsay, Demetris Demetriou, Dominic Manetta-Jones, James A. West, Andrew J. Murray, Julian L. Griffin

ABSTRACT

IntroductionRelative oxidation of different metabolic substrates in the heart varies both physiologically and pathologically, in order to meet metabolic demands under different circumstances. 13C labelled substrates have become a key tool for studying substrate use—yet an accurate model is required to analyse the complex data produced as these substrates become incorporated into the Krebs cycle.ObjectivesWe aimed to generate a network model for the quantitative analysis of Krebs cycle intermediate isotopologue distributions measured by mass spectrometry, to determine the 13C labelled proportion of acetyl-CoA entering the Krebs cycle.MethodsA model was generated, and validated ex vivo using isotopic distributions measured from isolated hearts perfused with buffer containing 11 mM glucose in total, with varying fractions of universally labelled with 13C. The model was then employed to determine the relative oxidation of glucose and triacylglycerol by hearts perfused with 11 mM glucose and 0.4 mM equivalent Intralipid (a triacylglycerol mixture).ResultsThe contribution of glucose to Krebs cycle oxidation was measured to be 79.1 ± 0.9%, independent of the fraction of buffer glucose which was U-13C labelled, or of which Krebs cycle intermediate was assessed. In the presence of Intralipid, glucose and triglyceride were determined to contribute 58 ± 3.6% and 35.6 ± 0.8% of acetyl-CoA entering the Krebs cycle, respectively.ConclusionThese results demonstrate the accuracy of a functional model of Krebs cycle metabolism, which can allow quantitative determination of the effects of therapeutics and pathology on cardiac substrate metabolism. More... »

PAGES

154

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11306-019-1618-y

DOI

http://dx.doi.org/10.1007/s11306-019-1618-y

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https://app.dimensions.ai/details/publication/pub.1122925751

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31773381


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