Sang Yup Lee (email@example.com)
Soon Ho Hong (firstname.lastname@example.org)
Soo Yun Moon (email@example.com)
Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering and BioProcess Engineering Research Center, Bioinformatics Research Center, Center for Ultramicrochemical Process Systems, Korea Advanced Institute of Science and Technology 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea
The intracellular metabolic fluxes can be calculated by metabolic flux analysis, which uses a stoichiometric model for the intracellular reactions along with mass balances around the intracellular metabolites. In this study, we have constructed in silico metabolic pathway network of Escherichia coli consisting of 301 reactions and 294 metabolites. Metabolic flux analyses were carried out to estimate flux distributions to achieve the maximum in silico yield of succinic acid in E. coli. The maximum in silico yield of succinic acid was only 83\% of its theoretical yield. The lower in silico yield of succinic acid was found to be due to the insufficient reducing power, which could be increased to its theoretical yield by supplying more reducing power. Furthermore, the optimal metabolic pathways for the production of succinic acid could be proposed based on the results of metabolic flux analyses. In the case of succinic acid production, it was found that pyruvate carboxylation pathway should be used rather than phosphoenolpyruvate carboxylation pathway for its optimal production in E. coli. Then, the in silico optimal succinic acid pathway was compared with conventional succinic acid pathway through minimum set of wet experiments. The results of wet experiments indicate that the pathway predicted by in silico analysis is more efficient than conventional pathway.