Metabolic flux balance analysis of an industrially useful microorganism Corynebacerium glutamicum by a genome-scale reconstructed model

Microorganisms have multi-hierarchical networks such as gene, protein and metabolites in the cells. When cells encounter changes in environmental conditions, they try to adapt themselves to new environmental conditions by changing the activities of the intracellular networks. We observed experimentally different patterns of metabolic fluxes (flows) under different conditions. In silico genome-scale metabolic models allow us to analyze characteristics of metabolic systems of organisms. In this study, we newly reconstructed a genome-scale metabolic model of an industrially useful microorganism, Corynebacterium glutamicum, based on genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA). We simulated the metabolic fluxes both under aerobic and oxygen deprivation conditions. The predicted growth rates and production rates of organic acids as lactate and succinate exhibited good agreement with experimental data reported in the literatures. The genome-scale metabolic model provides a better understanding for evaluating metabolic capabilities and predicting metabolic characteristics of C. glutamicum. This can be a basis for in silico analyses of metabolic network.