Optimization of Cell Free Protein Synthesis: Development of a Fusion Protein Fitness Strategy

Abstract

Our undergraduate researchers work in the field of metabolic engineering to harness metabolic pathways for the production of useful metabolites with applications in the biofuel, pharmaceutical, or industrial chemical industries. We published a metabolic engineering approach called programmed evolution that introduces variation in regulatory elements for the expression of enzymes that control orthogonal metabolic pathways. Programmed evolution employs a riboswitch‐based fitness module to transduce the production of a desired metabolite into antibiotic resistance. We validated programmed evolution by optimizing the conversion of caffeine to theophylline by caffeine demethylase, but we recognized several limitations to the widespread use of our approach, including crosstalk between orthogonal and native bacterial metabolism, potential toxicity of metabolites, and poor representation of large variation spaces. To avoid these limitations, we are developing an in vitro approach to programmed evolution. For cell‐free protein synthesis (CFPS), we found supercoiled plasmid was a much better template than linear PCR amplicon. We designed, constructed, and have begun testing a novel fitness module that responds to the production of theophylline produced by the action of caffeine demethylase produced by CFPS. The fitness module encodes a fusion protein composed of three functional units. The amino portion contains a Gal4 DNA binding domain that will target binding sites on a library of DNA regulatory elements for the expression of caffeine demethylase. The carboxyl terminus includes streptavidin which will bind to avidin beads for physical separation of selected DNA regulatory elements. Sandwiched in between these two domains is GFP, which serves as a biosensor. Using this in vitro selection strategy, we plan to pursue the optimization of CFPS for the discovery of efficient metabolic pathways of interest.Support or Funding InformationNSF RUI grant MCB‐1613203 to Davidson College and MCB‐1613281 to Missouri Western State University, Davidson College Martin Genomics ProgramThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.