Journal
BIOTECHNOLOGY AND BIOENGINEERING
Volume 95, Issue 5, Pages 972-983Publisher
JOHN WILEY & SONS INC
DOI: 10.1002/bit.21063
Keywords
cardiac metabolism; mass isotopomer analysis; carbon tracer experiments; constraint-based modeling; nonlinear programming; systems biology
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The increasing accessibility of mass isotopomer data via GC-MS and NMR technology has necessitated the use of a systematic and reliable method to take advantage of such data for flux analysis. Here we applied a nonlinear, optimization-based method to study substrate metabolism in cardiomyocytes using C-13 data from perfused mouse hearts. The myocardial metabolic network used in this study accounts for 257 reactions and 240 metabolites, which are further compartmentalized into extracellular space, cytosol, and mitochondrial matrix. Analysis of the perfused mouse heart showed that the steady-state ATP production rate was 16.6 +/- 2.3 mu mol/ min (.) gww, with 30% of the ATP coming from glycolysis. Of the four substrates available in the perfusate (glucose, pyruvate, lactate, and oleate), exogenous glucose forms the majority of cytosolic pyruvate. Pyruvate decaboxylation is significantly higher than carboxylation, suggesting that anaplerosis is low in the perfused heart. Exchange fluxes were predicted to be high for reversible enzymes in the citric acid cycle (CAC), but low in the glycolytic pathway. Pseudo ketogenesis amounted to approximately 50% of the net ketone body uptake. Sensitivity analysis showed that the estimated flux distributions were relatively insensitive to experimental errors. The application of isotopomer data drastically improved the estimation of reaction fluxes compared to results computed with respect to reaction stoichiometry alone. Further study of 12 commonly used C-13 glucose mixtures showed that the mixtures of 20% [U-(13) C-6] glucose, 80% [3 C-13] glucose and 20% [U-(13) C-6] glucose, 80% [4 C-13] were best for resolving fluxes in the current network. (c) 2006 Wiley Periodicals, Inc.
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