Genetic-Metabolic Coupling for Targeted Metabolic Engineering

Abstract

Production of chemicals in microbes often employs potent biosynthetic enzymes, which can interact with the microbial native metabolism to affect cellfitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic perturbations, thus limiting their relevance to specific conditions. Here, we address this issue by coupling cell fitness to the production of thiamine diphosphate in Escherichia coli using a synthetic RNA biosensor. We use this strategy to interrogate a library of transposon mutants and elucidate the native gene network influencing both cell fitness and thiamine production. Ultimately, we identify effectors of the OxyR-Fur stress response that limit thiamine biosynthesis via alternative regulation of iron storage andFe-S cluster inclusion in enzymes. This study presents a new approach for the reliable high-throughput identification of genetic targets of both known and unknown function that are directly relevant to a specific biosynthetic process.