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Reducing the allowable kinetic space by constructing ensemble of dynamic models with the same steady-state flux

Paper ID Volume ID Publish Year Pages File Format Full-Text
31835 44842 2011 16 PDF Available
Title
Reducing the allowable kinetic space by constructing ensemble of dynamic models with the same steady-state flux
Abstract

Dynamic models of metabolism are instrumental for gaining insight and predicting possible outcomes of perturbations. Current approaches start from the selection of lumped enzyme kinetics and determine the parameters within a large parametric space. However, kinetic parameters are often unknown and obtaining these parameters requires detailed characterization of enzyme kinetics. In many cases, only steady-state fluxes are measured or estimated, but these data have not been utilized to construct dynamic models. Here, we extend the previously developed Ensemble Modeling methodology by allowing various kinetic rate expressions and employing a more efficient solution method for steady states. We show that anchoring the dynamic models to the same flux reduces the allowable parameter space significantly such that sampling of high dimensional kinetic parameters becomes meaningful. The methodology enables examination of the properties of the model's structure, including multiple steady states. Screening of models based on limited steady-state fluxes or metabolite profiles reduces the parameter space further and the remaining models become increasingly predictive. We use both succinate overproduction and central carbon metabolism in Escherichia coli as examples to demonstrate these results.

Keywords
Ensemble modeling; Dynamic model; Steady-state flux
First Page Preview
Reducing the allowable kinetic space by constructing ensemble of dynamic models with the same steady-state flux
Publisher
Database: Elsevier - ScienceDirect
Journal: Metabolic Engineering - Volume 13, Issue 1, January 2011, Pages 60–75
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering