(317e) Cell-Free Prototyping Tools for Rapid Biosynthetic Pathway Engineering

To help meet societal needs in energy, medicine, materials, and more, engineers seek to design enzymatic reaction schemes in model microorganisms to produce biochemical and meet manufacturing criteria. Unfortunately, this is difficult because design-build-test (DBT) cycles—iterations of re-engineering organisms to test new sets of enzymes—are detrimentally slow due to the constraints of cell growth. As a result, a typical project today might only explore dozens of variants of an enzymatic reaction pathway. To speed up these DBT cycles,we develop an in vitro prototyping and rapid optimization of biosynthetic enzymes approach (termed iPROBE) to inform cellular metabolic engineering. In our approach, cell-free cocktails for synthesizing target small molecules are assembled in a mix-and-match fashion from crude cell lysates selectively enriched with pathway enzymes. This approach reconstructs pathways in two steps where the first step is enzyme synthesis via cell-free protein synthesis and the second step is enzyme utilization via substrate and cofactor addition to activate small molecule synthesis. We demonstrate that iPROBE can quickly study pathway enzyme ratios, tune individual enzymes in the context of a multi-step pathway, screen enzyme variants for high-performance enzymes, and discover enzyme functionalities. The rapid ability to build pathways in vitro using iPROBE allows us to generate large amounts of data describing pathway operation under several operating conditions. However, to date no easy method of analysis provides informative bridging of cell-free data to cellular metabolic engineering. In this work, we address this limitation by developing a quantitative metric that combines titer at reaction completion, rate during the most productive phase of pathway operation, and enzyme expression as measured by protein solubility (TREE score). By reducing the complexity of available cell-free data to one value we can now quickly screen and rank pathways in the cell-free environment and provide useful information for cellular metabolic engineering. We demonstrate iPROBE and the use of the TREE score for the production of 3-hydroxybutyrate and n-butanol in Clostridium, an industrially relevant non-model organism. We anticipate that iPROBE will facilitate efforts to define, manipulate, and understand metabolic pathways for accelerated DBT cycles in the cell-free environment before engineering organisms. In tandem in with high-end metabolomics, iPROBE will offer a high degree of flexibility to model the kinetics and stability of individual enzymes, measure metabolite fluxes in multistep pathways, and experimentally isolate many other parameters confounded in living organisms.