Identification of Feasible Metabolic Fluxes and Metabolite Concentrations using Large-scale Kinetic Models

The constraints imposed during modeling must satisfy biologically representative phenotypes of the studied organism. Simultaneously, identification and analysis of these constraints enhances our understanding of the evolution/operational paradigms of the organism. It was postulated by Varma and Palsson[1] that it is possible to define limits on metabolic behavior using flux balance analysis, but in order to accurately capture the metabolic responses, detailed information about enzyme kinetics and their regulation is needed. Since development of mechanistic kinetic models is a difficult task due to uncertainty in kinetic properties of enzymes, a substantial number of recent works consider only the mass action (MA) term in their model formulation. As kinetics is one of crucial factors in governing the metabolic capabilities of a cell, i.e. realizable metabolic flux and concentration states, considering only the mass action term does not necessarily provide a realistic description of the feasible space of fluxes and concentrations. In this work, using the ORACLE[2] framework, we constructed a large-scale mechanistic kinetic model of optimally grown E. coli that considers the enzyme saturations as observed in biological systems. Using this model, we performed an analysis of the complex interplay between stoichiometry, thermodynamics, and kinetics in determining flexibility and capabilities of metabolic networks. Our analysis indicates that enzyme saturation is an important and necessary consideration in modeling metabolic networks. Extended ranges of feasibility, both in the space of metabolic fluxes and metabolite concentrations, of kinetic models involving the enzyme saturation suggests that the enzymes in metabolic networks have evolved to function at different saturation states so as to ensure higher flexibility and robustness of the cell.

Presented at:
Biochemical and Molecular Engineering XVIII, Beijing, China, June 16-20, 2013

 Record created 2013-07-08, last modified 2018-03-17

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