Genetic-Metabolic Coupling for Targeted Metabolic Engineering

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Abstract

Production of chemicals in microbes often employs potent biosynthetic enzymes, which can interact with the microbial native metabolism to affect cell fitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic pertur-bations, 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 and Fe-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.
Original languageEnglish
JournalCell Reports
Volume20
Issue number5
Pages (from-to)1029-1037
ISSN2211-1247
DOIs
Publication statusPublished - 2017

Cite this

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title = "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 cell fitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic pertur-bations, 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 and Fe-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.",
author = "Stefano Cardinale and {Tueros Farfan}, {Felipe Gonzalo} and Sommer, {Morten Otto Alexander}",
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Genetic-Metabolic Coupling for Targeted Metabolic Engineering. / Cardinale, Stefano; Tueros Farfan, Felipe Gonzalo; Sommer, Morten Otto Alexander.

In: Cell Reports, Vol. 20, No. 5, 2017, p. 1029-1037.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Genetic-Metabolic Coupling for Targeted Metabolic Engineering

AU - Cardinale, Stefano

AU - Tueros Farfan, Felipe Gonzalo

AU - Sommer, Morten Otto Alexander

PY - 2017

Y1 - 2017

N2 - Production of chemicals in microbes often employs potent biosynthetic enzymes, which can interact with the microbial native metabolism to affect cell fitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic pertur-bations, 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 and Fe-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.

AB - Production of chemicals in microbes often employs potent biosynthetic enzymes, which can interact with the microbial native metabolism to affect cell fitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic pertur-bations, 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 and Fe-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.

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