David W. Schryer



This dissertation applies dynamic tracer-based MFA to study the recycling fluxes of energy metabolites in the mammalian heart and the TCA cycle flux of Saccharomyces uvarum. Compartmentation of metabolites in these systems complicates their analysis, so methods are discussed to reveal compartmentation using dynamic isotopologue simulation coupled with isotopic transient data measured in biological systems operating at pseudo metabolic steady state. A routine was developed to compose dynamic isotopologue models from systems of chemical transformations and, in the case of Saccharomyces uvarum, optimization techniques were applied to find flux distributions that best fit with measurements of the isotopic labeling state. To make the optimization process more efficient for application in large metabolic networks, a sparse symbolic Gauss-Jordan elimination routine was developed to express all steady state metabolic solutions in terms of a flux coordinate system suggested by the analyst. Properties of flux coordinate systems were found to be useful in studying systems of chemical transformations in general and genome-scale metabolic networks in particular. Dynamic isotopologue modeling was applied to study the recycling fluxes of energy metabolites in the mammalian heart. A sensitivity analysis of the dynamic isotopologue model revealed that the fluxes found using 18 O–assisted 31 P–NMR, 31 P–NMR saturation transfer, and 31 P–NMR inversion and saturation transfer all predict a very similar 18 O labeling state of key metabolites, in contrast to statements in the literature. This modeling work shows that the 18 O–assisted 31 P–NMR method provides a measure of the combined net and exchange fluxes in the creatine kinase and adenylate kinase shuttles, and not net flux as previously stated, thus resolving a long-standing debate in the heart energetics community. Overall, this doctoral work highlights the importance of considering compartmentation while analyzing the metabolic fluxes within eukaryotic systems, and provides techniques to reveal previously unknown manifestations of compartmental biology using dynamic isotopologue modeling.

SUPERVISOR: Marko Vendelin

CO-SUPERVISORS: Pearu Peterson, Toomas Paalme


  • Katharina Nöh, Institute of Bio- and Geosciences IBG-1, Forschungszentrum Jülich GmbH
  • Tanel Tenson, Head of the Antibiotics Group in the Molecular Microbiology Laboratory, Institute of Technology at the University of Tartu, Estonia


April 12th, 2012 at 14:00 in the Institute of Cybernetics, room B101

THESIS PDF: Metabolic Flux Analysis of Compartmentalized Systems using Dynamic Isotopologue Modeling