Strain optimization through theoretical and experimental tools.

Abstract

In this dissertation, metabolic network analysis based on elementary mode analysis (EMA), metabolic control analysis (MCA) and thermodynamic analysis of pathways are applied to quantitatively analyze cell metabolism and to engineer a cell for improved performance. By applying EMA, we acquire knowledge of all the pathways of a cell's metabolism. The pathway information permits the systematic implementation of cell manipulation to develop a strain with a desired phenotype. The rational strain improvement is achieved by limiting the cell's functionality to only efficient pathways through gene knockout mutations. This way, the functional space of the designed strain is minimized to a set of pathways that only support the efficient production of the desired product. The EMA approach has been implemented for enhanced synthesis of carotenoid in E. coli and ethanol in T. saccharolyticum. Metabolic control analysis and thermodynamic analysis of pathways are employed to examine changes in metabolic pathways within a cell during metabolic evolution. The evolution approach is utilized to select for a mutant of the designed strain that shows a further improvement in product synthesis or strain robustness. The approach is demonstrated in E. coli for enhanced carotenoid production, improved ethanol production in the presence of inhibitors, and in T. saccharolyticum for increased ethanol productivity. MCA is used as a guiding tool to identify a controlling step in the pathways, while thermodynamic analysis is used to determine changes in the distribution of pathway flux during evolution. The fermentation process is optimized to enhance production efficiency of the products. A controlled fed-batch fermentation process is designed and conducted to produce a high titer of carotenoid. The process of immobilized mixed cells of two substrate-selective strains of E. coli that allow for an efficient conversion of mixed sugars into ethanol at a high yield and a high productivity is also designed and implemented.