Identification of distributed metabolic objectives in the hypermetabolic liver by flux and energy balance analysis.
A methodology for inferring distributed metabolic objectives from time series flux data is developed by combining metabolic flux analysis, pathway identification, free energy balances, and nested optimization. This methodology is used to investigate the metabolic response of the rat liver to burn injury-induced whole body inflammation. Gibbs free energy changes were computed for stoichiometrically balanced sequences of reactions, or pathways, rather than individual reactions, to account for energetic coupling between reactions. Systematic enumeration of pathways proceeded by elementary flux mode (EFM) analysis. Together with stoichiometric balances and external metabolite flux measurements, the DeltaG(PATH)(o) criterion provided sufficient constraints to solve a series of nested optimization problems on the metabolic goal functions and associated flux distributions of fasted livers during the first-week time course of burn injury. The optimization results suggest that there is a consistent metabolic goal function for the liver that is insensitive to the changing metabolic burdens experienced by the liver during the first-week time course. As defined by the goal function coefficients, the global metabolic objective was to distribute the metabolic resources between amino acid metabolism and ketone body synthesis. These findings point to a role for the time-invariant structure of the metabolic reaction network, expressed as stoichiometric and thermodynamic constraints, in shaping the cellular metabolic objective.
Nolan
Ryan P
RP
Department of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.
Fenley
Andrew P
AP
Lee
Kyongbum
K
D000818:Animals; D002056:Burns / Q000378:metabolism*; D004734:Energy Metabolism; D008099:Liver / Q000378:metabolism*; D008954:Models, Biological; D009924:Organ Culture Techniques; D010101:Oxygen Consumption; D010477:Perfusion / Q000379:methods; D051381:Rats