In silico screening of triple reaction knockout Escherichia coli strains for overproduction of useful metabolites.

For efficient production of industrially useful metabolites by microorganisms, it is important to design metabolic networks suitable for production. For this purpose, constraint-based metabolic flux simulation is a powerful tool to predict the effect of reaction knockouts on target productivity. In this study, using constraint-based metabolic simulation, in silico screening was performed to identify knockout candidate sets that increase the productivity of 1-butanol, 1-propanol, and 1,3-propanediol by engineered Escherichia coli. Metabolic changes caused by all possible sets of triple reaction knockouts were evaluated using a reduced metabolic model, which was constructed to significantly reduce the computational cost. The results demonstrated the strategies to improve target productivity by gene disruption; some of them could not be achieved by previous screening methods. Such knockout strategies can support further improvements of the target productivity.