Michael D. Lynch, University of Colorado, ECCH 111, Campus Box 424, Boulder, CO 80309, Tirzah Ya'el Mills, Chemical Engineering, West Virginia University, 956 Ashton Place, Morgantown, WV 26508, Amarjeet Singh, Chemical & Biological Engineering, University of Colorado at Boulder, 1111 Engineering Drive, Campus Box 424, Boulder, CO 80309, and Ryan T. Gill, Department of Chemical and Biological Engineering, University of Colorado, ECCH 111 Campus Box 424, Boulder, CO 80309.
Traditional optimization of bacterial strains for biorefining applications is far from a simple task and involves a substantial understanding of the metabolic pathways involved. Population based genomics approaches offer the promise of more quickly identifying and manipulating the genetics behind production, however due to the large screening effort involved, these tools have been largely applied to selectable phenotypes. For example, we have develop a new technique, scalar analysis of library enrichments (SCALES), for identifying genes that may improve the productivity of engineered strains. We have applied this tool in several different contexts, including the production of different organic-acids in E. coli. To expand this approach, we initiated activities on the development of a antibiotic resistance reporter that responds to succinate concentrations. We will report on the use of this reporter in combination with population-based genomics tools to select for succinate overproduction as well as identify the genetic elements involved in production optimization.