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Title: Modeling and optimization of a multi-product biosynthesis factory for multiple objectives
Authors: Lee, F.C.
Pandu Rangaiah, G. 
Lee, D.-Y. 
Keywords: Metabolic pathway recipe
Multi-objective optimization
Multi-product biosynthesis factory
Pareto-optimal set
Systems biotechnology
Issue Date: May-2010
Citation: Lee, F.C., Pandu Rangaiah, G., Lee, D.-Y. (2010-05). Modeling and optimization of a multi-product biosynthesis factory for multiple objectives. Metabolic Engineering 12 (3) : 251-267. ScholarBank@NUS Repository.
Abstract: Genetic algorithms and optimization in general, enable us to probe deeper into the metabolic pathway recipe for multi-product biosynthesis. An augmented model for optimizing serine and tryptophan flux ratios simultaneously in Escherichia coli, was developed by linking the dynamic tryptophan operon model and aromatic amino acid-tryptophan biosynthesis pathways to the central carbon metabolism model. Six new kinetic parameters of the augmented model were estimated with considerations of available experimental data and other published works. Major differences between calculated and reference concentrations and fluxes were explained. Sensitivities and underlying competition among fluxes for carbon sources were consistent with intuitive expectations based on metabolic network and previous results. Biosynthesis rates of serine and tryptophan were simultaneously maximized using the augmented model via concurrent gene knockout and manipulation. The optimization results were obtained using the elitist non-dominant sorting genetic algorithm (NSGA-II) supported by pattern recognition heuristics. A range of Pareto-optimal enzyme activities regulating the amino acids biosynthesis was successfully obtained and elucidated wherever possible vis-à-vis fermentation work based on recombinant DNA technology. The predicted potential improvements in various metabolic pathway recipes using the multi-objective optimization strategy were highlighted and discussed in detail. © 2009 Elsevier Inc. All rights reserved.
Source Title: Metabolic Engineering
ISSN: 10967176
DOI: 10.1016/j.ymben.2009.12.003
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