CAREER: A Framework for Directed Genome Evolution

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0449183Gill The proposed work entails optimizing protoplast fusion and genome-shuffling approaches in the bacterium, E. coli. Additionally, gene chips will be used to identify the genes responsible for antibiotic (aa-hydroxamate) tolerant phenotypes, and small network theory will be employed to understand how connectivity and clustering may affect antibiotic tolerance versus fitness. Improving the understanding of genome evolution and the tradeoffs between the yield from individual metabolic pathways and organism fitness is expected to make a positive impact on the metabolic engineering community. The impact follows from more insights being gleaned on how "global" versus "local" optimization is managed at the molecular level by cellular systems. Such insights, in turn, will allow for improved quantitative prediction of the outcome of different metabolic engineering strategies. Understanding better how genomic evolution can lead to antibiotic resistance and organism fitness should also positively impact work on contending with the medical problem of antibiotic resistant bacteria. The plan to integrate research into education and outreach has two objectives. First, outreach activities will be pursued via Women in Engineering, Multicultural Engineering, and high school honors programs. Secondly, undergraduates will be organized into teams that are charged with developing laboratory demonstration modules. Such teams will integrate prior coursework and learn collaboration skills while producing useful courseware.