(197a) Genome-Scale Metabolic Network Modeling Results In Minimal Interventions That Cooperatively Force Carbon Flux towards Malonyl-CoA | AIChE

(197a) Genome-Scale Metabolic Network Modeling Results In Minimal Interventions That Cooperatively Force Carbon Flux towards Malonyl-CoA

Authors 

Xu, P. - Presenter, Rensselaer Polytechnic Institute
Ranganathan, S. - Presenter, The Pennsylvania State University
Maranas, C. D. - Presenter, Department of Chemical Engineering
Koffas, M. A. G. - Presenter, Rensselaer Polytechnic Institute


Malonyl-coenzyme A (malonyl-CoA) is an important precursor metabolite for the biosynthesis of polyketides, flavonoids and biofuels. However, malonyl-CoA naturally synthesized in microorganisms is consumed for the production of amino acids, fatty acids and phospholipids leaving only a small amount available for the production of other metabolic targets in recombinant biosynthesis. During the past decade, metabolic pathway modeling has aided various metabolic engineering efforts to design strains of bacteria and yeast that overproduce high-value and commodity chemicals. Here we present an integrated computational and experimental approach aimed at improving the intracellular availability of malonyl-CoA in Escherichia coli. We used a customized version of the recently developed OptForce methodology to predict a minimal set of genetic interventions that guarantee a pre-specified yield of malonyl-CoA in E. coli strain BL21 StarTM. In order to validate the model predictions, we have successfully constructed an E.coli recombinant strain that exhibits a 4-fold increase in the levels of intracellular malonyl-CoA compared to the wild-type strain. Furthermore, we demonstrate the potential of this E. coli strain for the synthesis of plant-specific secondary metabolites (i.e., flavanones) that are the precursors of promising agents in the treatment of chronic diseases such as cardiovascular disorders and diabetes. Specifically, a titer of 474 mg/L of the flavanone naringenin was observed which, so far, is the highest yield achieved in a lab-scale fermentation process. Quantitative analysis of kinetic profiles from these strains highlights the synergistic effect of combining beneficial mutants (ΔfumC and ΔsucC) and overexpression targets (acc, pgk, gapA and pdh) predicted by OptForce. More importantly, the presented strategy can also be readily expanded to the production of other malonyl-CoA-derived compounds like polyketides and fatty acids.