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Estimating optimal profiles of genetic alterations using constraint-based models.

Kapil G Gadkar·Francis J Doyle Iii·Jeremy S Edwards·Radhakrishnan Mahadevan
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Abstract

Metabolic engineering involves application of recombinant DNA methods to manipulate metabolic networks to improve cellular properties. It is critical that the genetic alterations be performed in an optimal manner to maximize profit. In addition to the product yield, productivity consideration is also critical, especially for the production of bulk chemicals such as 1,3-propanediol. In this work, we demonstrate that it is suboptimal from the standpoint of productivity to induce genetic alteration at the start of the production process. A bi-level optimization scheme is formulated to determine the optimal temporal flux profile for the manipulated reaction. In the first case study, an optimal flux in the reaction catalyzed by glycerol kinase is determined to maximize the glycerol production at the end of a 6-h batch cultivation of Escherichia coli under aerobic conditions. The final glycerol concentration is 30% higher for the optimal flux profile compared with having an active flux during the entire batch. The effect of the mass transfer coefficient on the optimal profile and the glycerol concentration is also determined. In the second case study, the anaerobic batch fermentation of the ldh(-) strain of Escherichia coli is considered. The optimal flux in the acetate pathway is determined to maximize the final ethanol concentration. The optimal flux results in higher ethanol concentration (11.92 mmol L(-1)) compared to strains with no acetate flux (8.36 mmol L(-1)) and fully active acetate flux (6.22 mmol L(-1)). We also examine the effects of growth inhibition due to high ethanol concentrations and variations in final batch time on ethanol production.

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AlgorithmsComputer SimulationEscherichia coliEscherichia coli ProteinsEthanolGene Expression Regulation, BacterialGenetic EngineeringGenetic EnhancementGlycerolModels, GeneticSignal TransductionComparative StudyEvaluation StudyJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.

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Kapil G Gadkar, Francis J Doyle Iii, Jeremy S Edwards, Radhakrishnan Mahadevan. 2005-01-20. Estimating optimal profiles of genetic alterations using constraint-based models.. https://doi.org/10.1002/bit.20349

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