Strain Engineering for the Development of Continuous Bioprocesses

The successful implementation of biorefineries could eventually produce renewable resources to replace petroleum-based materials as feedstocks for chemical processing. Such a concept requires the integration of many fermentation units to work in a coordinated fashion, so that continuous operations could be used for large-scale bioprocessing units. However, most biological conversions are carried out in batch mode, primarily due to the high risk of instability when dealing with engineered strains or microorganisms. The challenge is to develop microbial strains which will not undergo significant genetic modification throughout the continuous process. This project will develop such strains along with associated processes, using the 1,4-diacids (succinic, fumaric, and malic) as exemplary products. The approach will make use of a computational framework that identifies gene deletion strategies for coupling biochemical production to cell growth, leading to genetically-stable overproducing microorganisms. Phase I will apply this framework to enumerate sets of multiple gene deletions leading to the growth-coupled production of the 1,4-diacids. The four most promising strategies will be constructed, and the resulting strains will be subjected to adaptive evolution to enhance their rates of growth and diacid production. Finally, the strains will be characterized in continuous culture, and the experimental findings will be reconciled with predictions to gauge the overall success of the combined modeling/experimental platform. In addition, an economic evaluation will be performed. Commercial Applications and Other Benefits as described by the awardee: A set of microbial production strains for commodity chemicals would represent a significant step toward the development of an economically-viable biorefinery. The yield and productivity potential not only would exceed that of current fermentation technology but also would be genetically stable and thus suitable for continuous processing.