Recent advances in metabolic reconstructions and availability of fluxomic and metabolomics data has paved the way for large-scale kinetic modeling of metabolism. Challenges still remain in deducing genome-wide reaction mechanisms and elucidating kinetic parameter values. In general, kinetic model prediction quality is determined by the range and scope of genetic and/or environmental perturbations used during parameterization. To this end, we develop a kinetic model of E. coli core metabolism that satisfies the fluxomic data for multiple mutant strains and conditions by making use of recently introduced Ensemble Modeling (EM) concepts. The integrated experimental data includes multiple carbon substrates (glucose, acetate and pyruvate) under aerobic respiration as well as fermentative (anaerobic) conditions. This model includes representations for all relevant reactions from the genome-scale iAF1260 model. Parameterization of the kinetic expressions is performed using a formal optimization approach that minimizes the uncertainty-scaled discrepancies between model predictions and flux measurements. This modeling effort describes a stepwise procedure for construction of large-scale kinetic models with robust parameterization consistent with multiple sets of omics information for E. coli, and provides a guideline for developing large-scale kinetic models for other well studied organisms.

Development of a comprehensive Escherichia coli kinetic metabolic model consistent with multiple genetic and environmental perturbations

249th National Meeting (2015)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.