Collaborative Research: RUI: Broadening the Application of Programmed Evolution for Metabolic Engineering

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Design considerations during metabolic engineering have been based on incomplete understanding of the evolutionary forces acting upon populations of engineered bacteria. This project inverts the metabolic engineering paradigm by harnessing evolution instead of fighting it. The investigators developed an evolutionary approach to metabolic engineering that enables bacteria to integrate their growth environment and their engineered metabolism. The approach is called Programmed Evolution because a population of bacteria is programmed with DNA software to compute solutions to a metabolic pathway optimization problem, and evolution is used to direct the bacterial population toward optimal solutions. The goal of this project is to expand Programmed Evolution by developing a new method for new riboswitch discovery, using the new riboswitches optimally express the enzymes necessary for e the production of new compounds, and developing mathematical models and computational tools to support both processes. These approaches will reduce the cost of producing useful compounds in metabolically engineered bacteria for applications in energy, pharmaceuticals, and bioremediation. This project will increase diversity for science education, contribute to a competitive and scientifically literate workforce, and has the potential to improve American economic competitiveness. This project responds to the call in Vision and Change for more authentic undergraduate research experiences as undergraduates pose research questions, develop testable hypotheses, collect and analyze data, and communicate results. As they learn how to program the evolution of bacteria for metabolic engineering, undergraduate research students will learn how to program the course of their own futures as science literate citizens, educators, and research scientists.Programmed Evolution is a modular system for the optimization of orthogonal metabolic pathways in bacteria. It uses combinatorics, fitness, and biosensor modules that can be developed and tested separately, used in combinations, and shared among research groups. A key component of Programmed Evolution is the riboswitch that transduces metabolic output into fitness gene expression and selective advantage. Most riboswitches used in metabolic engineering incorporate RNA aptamers discovered by the in vitro process of Systematic Evolution of Ligands by Exponential enrichment. However, aptamers discovered in vitro rarely function in vivo. The investigators propose to develop Cell-based Exponential enrichment as a new in vivo method of discovering riboswitches that function predictably in bacterial cells. The new method introduces genetic variation in a riboswitch to produce a library, applies negative and positive selection, and characterizes the phenotype and genotype of new riboswitches. The significance of the new approach derives from its potential to advance knowledge of naturally occurring riboswitches and to discover new riboswitches for applications in energy, pharmaceuticals and bioremediation.