Expression-level optimization of a multi-enzyme pathway in the absence of a high-throughput assay

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Michael Lee, Anil Aswani, Audrey S. Han, Claire J. Tomlin, John E. Dueber

University of California, United States

Synthetic biology strives to enable reprogramming and repurposing of biological elements ranging from molecules to ecosystems. In engineering organisms, we manipulate gene expression to alter or redirect cell metabolism, and due to the interconnected nature of the cell, it is often multiple genes that we must target to produce a desired effect. To that end, we have developed a system of combinatorial assembly of well-characterized parts, followed by a rapid and inexpensive genotyping assay that enables us to construct and analyze large libraries of heterologous pathways in Saccharomyces cerevisiae. By having genotypic information to associate with phenotypic differences, we use regression modeling to explore and understand the expression landscapes of these pathways. This strategy accelerates the process of building and testing multi-gene systems, to allow for the investigation of more pathways and the inclusion of–and control over–more genes than has previously been possible.