? Metabolic engineering has gained significance in both industrial and medical biotechnology for the synthesis of a wide variety of products including small metabolites and other antibiotics. However, due to the lack of rational and systematic approaches to metabolic engineering the timelines and cost for strain development can be large and at times prohibitive for many products. This proposal addresses this need for more rational approaches through the implementation of modeling and simulation technologies to design cellular metabolic networks for practical objectives. The bilevel programming framework OptKnock, in particular, focuses on identifying multiple gene deletion strategies for forcing growth-coupled biochemical production following laboratory adaptive evolution. Specifically, knockouts are selected in such a way that the drain towards necessary growth resources (i.e., biomass components, redox potential and energy) must be accompanied, due to stoichiometry, by the production of the desired chemical product. The overall goal of this Phase I SBIR is the completion of an integrated computational and experimental study aimed at demonstrating the technical feasibility of utilizing the OptKnock approach to drive strain engineering efforts. The production of succinate in Escherichia coli will serve as an exemplary case study towards this end. The initial aims of this application are to enumerate sets of multiple gene deletions leading to growth-coupled succinate production and incorporate the three most promising into E. coli. The three unique designed strains will then be subjected to adaptive evolution to enhance their rates of growth, and thus the coupled objective of succinate production will be indirectly optimized. Finally, we will reconcile the experimental findings with the original predictions to gauge the overall success of the combined modeling/experimental platform. In subsequent phases of the project, we will target several compounds of biotechnological and biomedical importance with the goal of generating at least one industrially competitive production strain. This program will lead to the development of a systematic approach to metabolic engineering that leverages genomic information and a host of experimental data for the rational design of production hosts. The developed technology will significantly expedite and lesson the cost of strain development for the production of a plethora of compounds with therapeutic value. ? ? ?
