(227a) Targeted Proteomics for the Optimization of Biofuel Pathways in E. Coli

Targeted Proteomics for the Optimization of Biofuel Pathways in E. coli

Christopher J. Petzold, Pragya Singh, Vikram R. Ramakrishnan, Mirta Mittelstedt L. de Sousa, Tanveer S. Batth, Taek Soon Lee, Jay D. Keasling, Paul D. Adams

Joint BioEnergy Institute, 5885 Hollis St., 4^th floor, Emeryville, California 94608, USA

Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 USA

Successful metabolic engineering of microbes for biofuel production depends on the speed at which biological circuits can be conceived, constructed, and optimized. To this end, metabolic engineers utilize a variety of analytical methods to identify pathway bottlenecks. Protein quantification by using targeted proteomics compliments metabolite and transcript analysis for rapid optimization of engineered pathways. Traditionally, selective protein detection and quantification have been accomplished via immunoblot analysis, which is fast, convenient, and, for a specific protein, easily multiplexed. However, when assaying full pathways custom antibodies must be obtained for every pathway protein resulting in increased development time and experimental costs. Furthermore, obtaining accurate quantitative information can be challenging. Recently, we applied targeted proteomics to metabolically engineered E. coli by using selected-reaction monitoring (SRM) mass spectrometry. This sensitive method is based on two points of selection (linked peptide and a MS/MS fragment masses) to eliminate background signal and noise. With this method entire biofuel pathways can be monitored in one LC-MS/MS run.  Our initial efforts were directed at optimizing the mevalonate pathway proteins to produce precursors to isoprenoid-based biofuels led to balanced protein levels and over 3-fold improved final isoprenoid titer. Targeted proteomics of native E. coli pathway proteins complements analysis of the heterologous pathway and can reveal more subtle perturbations of metabolic engineering. Consequently, we have developed a rapid targeted proteomics method for over twenty metabolic pathways commonly impacted by metabolic engineering and built a library of peptide standards for absolute quantification. With these methods, we have characterized a variety of pathways and protein expression parameters to improve biofuel production. Overall, our results underscore the importance of targeted proteomics for rapid biofuel pathway optimization.