Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and l-DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5–5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a l-DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.