S92: EMILiO: a faster algorithm for genome-scale strain design

As competition in industrial fermentation becomes increasingly fierce, rapid development of highly efficient strains is becoming vital. Computer-aided design of cell metabolism is a promising tool as it can systematically improve strain performance subject to stringent design criteria. While the continued development in mathematical models of cell metabolism will improve their predictive capabilities, this growth also presents a problem for computer-aided design: algorithms must cope with increasingly complex models and design criteria. Existing algorithms typically do not scale well to an increasing number and complexity of genetic manipulations--an important challenge as strains get closer to their theoretical yields. Here, we present EMILiO, a new algorithm that increases the scope of strain design to include reactions with individually optimized fluxes. Unlike existing approaches that would experience an explosion in complexity to solve this problem, we efficiently generated numerous alternate strain designs producing succinate, L-glutamate and L-serine. This was enabled by successive linear programming, a technique used extensively in the petroleum industry but new to the area of strain design.