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Genome-Scale Metabolic Systems Design by Flux Transition Theory

Matthew L. Rizk and James C. Liao. Chemical and Biomolecular Engineering, University of California, Los Angeles, 5531 Boelter Hall, 420 Westwood Plaza, Los Angeles, CA 90095

Microbial strain design for a metabolic engineering purpose is usually based on reaction stoichiometry. Although these approaches have been successful in identifying targets for knockouts, they cannot identify enzymes for expression tuning, which often is the key to successful metabolic engineering. This difficulty arises from the lack of detailed kinetic parameters which are impractical to determine. Here, a genome-scale approach is developed for identifying enzyme targets for over or under expression. This approach, termed flux transition theory (FTT), identifies the most effective enzyme targets for fluxes changes without detailed kinetic parameters. This approach was verified using experimentally proven enzymatic targets from published metabolic engineering studies in the production of aromatics, succinate and lysine. FTT is able to capture the most likely kinetic phenomena due to the network structure, and is useful for identifying targets for enzyme expression tuning.