Cell-Free Expression Systems (CFES) are a promising, modular, in vitro method to produce biologics. They consist of cellular extracts (lysates), a plasmid DNA template, and the necessary amino acids, metabolites, and nucleotides to produce proteins. These systems allow for the production of multiple bioproducts with a single extract, and without the limitations of keeping cells alive, they can also produce toxic proteins. For therapeutic applications, however, large yields of protein are necessary, even in initial testing stages. Currently, transcription-translation (TX-TL) activity stops prematurely with bottlenecks in productivity and lifetime, which halts protein production before sufficiently high yield is achieved. In this project, I am using metabolomics – the study of metabolites – to characterize E. coli-based cell-free expression dynamics, which will enable me to propose methods to induce sustained and consistent protein expression in CFES by manipulation of the lysate proteome with perturbations during the pre-lysis cell growth phase. In preliminary work, I have demonstrated enhanced performance of CFES using a lysate prepared from cells exposed to lowered environmental temperature pre-lysis, suggesting that upstream growth conditions can be engineered to unlock higher productivity over a longer system lifetime. These results will metabolically characterize bottlenecks associated with the lysate’s proteomic composition in productivity and lifetime of CFES for the first time. In addition to identifying universally improved lysate conditions, my work also seeks to evaluate and expand the robust applications of CFES by identifying proteomic modifications that display resilience against environmental stresses. Such lysates could expand the contexts in which CFES can be utilized, including in low-resource settings where temperature control and other aspects of storage stability cannot be easily regulated or in situations where biomanufacturing is required rapidly or on-demand. The successful scaling of CFES would advance the drug development process by enabling the manufacturing of several drug candidates in parallel while reducing costs, time, and infrastructure barriers.
