Identifying synergistically switching pathways for multi-product strain improvement using multiobjective flux balance analysis

The current work involves in silico analysis of metabolic network of E. coli, characterizing its pathways for the production of various industrially important metabolites including pyruvate, acetate, lactate, ethanol and various amino acids. Initially, the correlation among the flux distribution profiles for each objective has been investigated by resorting to a novel multiobjective optimization. Subsequently, we identified the genes which are significant for switching the metabolic pathways from one objective to another. Thus, the present analysis allows us to explore synergism among the metabolic pathways for different combinations of multi-products, providing a new insight into the behavior of the biological system.