S46: A strategy for genome design, redesign, and optimization of ethylene production in E. coli

Monday, August 12, 2013: 2:30 PM
Nautilus 1-2 (Sheraton San Diego)
Sean Lynch1, Carrie A. Eckert2, Jianping Yu2, PinChing Maness2 and Ryan T. Gill3, (1)Chemical and Biological Engineering, University of Colorado, Renewable and Sustainable Energy Institute, Boulder, CO, (2)Biosciences Center, National Renewable Energy Laboratory, Golden, CO, (3)Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO
Ethylene is the most highly utilized organic compound used in the production of plastics and chemicals and can be utilized as a precursor for high-energy biofuels. Most ethylene is derived from fossil fuels by steam cracking, resulting in the highest CO2 emissions in the chemical industry. Ethylene is produced in some bacteria and fungi via an ethylene-forming enzyme (Efe) that uses alpha-ketoglutarate (AKG) and arginine as substrates. Heterologous expression of efe alone is sufficient for ethylene production in a variety of organisms, but the reported productivity is less than impressive. In order to improve the often low titers of ethylene produced, an in-depth understanding of optimal expression levels, solubility/stability of Efe, the Efe reaction mechanism, and interactions between the Efe reaction and other metabolic pathways are needed. In collaboration with the University of Colorado-Boulder and LBNL/University of California, Berkeley, we are developing a high-throughput platform approach for prediction and selection to systematically improve ethylene production in E. coli. This project combines implementation and testing of predicted modifications based on pathway modeling followed by high-throughput screening of genome scale (TRMR)/combinatorial pathway (MAGE) libraries to create strains with improved ethylene production. Our current work is focused on investigation of optimal levels of Efe enzyme for maximal solubility and activity, testing substrate-feeding and/or targeted genetic modifications based on pathway modeling to improve flux to AKG and arginine, and development of high-throughput screening methods to select for increased production of key intermediates and/or ethylene to allow for selection from pooled libraries.