Genetic-metabolic coupling for targeted metabolic engineering

• DOI: 10.1101/156927
• Publication Date: 2017-06-29T05:10:12Z
• Authors: Stefano Cardinale; Felipe Gonzalo Tu...; Morten Otto Alexa...
• Keywords: Metabolic Engineering; Synthetic Biology; Metabolic network; Limiting

SUMMARY To produce chemicals, microbes typically employ potent biosynthetic enzymes that interact with native metabolism to affect cell fitness as well chemical production. However, production optimization largely relies on data collected from wild type strains in the absence of metabolic perturbations, thus limiting their relevance specific process scenarios. Here, we address this issue by coupling thiamine diphosphate Escherichia coli using a synthetic RNA biosensor. We apply system interrogate library transposon mutants elucidate gene network influencing both and Specifically, identify uncharacterized effectors OxyR-SoxR stress response limit biosynthesis via alternative regulation iron storage Fe-S-cluster inclusion enzymes. Our study represents new generalizable approach for reliable high-throughput identification genetic targets known unknown function are directly relevant process.