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Determining the Control Circuitry of Redox Metabolism at the Genome-Scale

Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regu...

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Autores principales: Federowicz, Stephen, Kim, Donghyuk, Ebrahim, Ali, Lerman, Joshua, Nagarajan, Harish, Cho, Byung-kwan, Zengler, Karsten, Palsson, Bernhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974632/
https://www.ncbi.nlm.nih.gov/pubmed/24699140
http://dx.doi.org/10.1371/journal.pgen.1004264
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author Federowicz, Stephen
Kim, Donghyuk
Ebrahim, Ali
Lerman, Joshua
Nagarajan, Harish
Cho, Byung-kwan
Zengler, Karsten
Palsson, Bernhard
author_facet Federowicz, Stephen
Kim, Donghyuk
Ebrahim, Ali
Lerman, Joshua
Nagarajan, Harish
Cho, Byung-kwan
Zengler, Karsten
Palsson, Bernhard
author_sort Federowicz, Stephen
collection PubMed
description Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs), ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2) (p<1e-6) correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.
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spelling pubmed-39746322014-04-08 Determining the Control Circuitry of Redox Metabolism at the Genome-Scale Federowicz, Stephen Kim, Donghyuk Ebrahim, Ali Lerman, Joshua Nagarajan, Harish Cho, Byung-kwan Zengler, Karsten Palsson, Bernhard PLoS Genet Research Article Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs), ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2) (p<1e-6) correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network. Public Library of Science 2014-04-03 /pmc/articles/PMC3974632/ /pubmed/24699140 http://dx.doi.org/10.1371/journal.pgen.1004264 Text en © 2014 Federowicz et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Federowicz, Stephen
Kim, Donghyuk
Ebrahim, Ali
Lerman, Joshua
Nagarajan, Harish
Cho, Byung-kwan
Zengler, Karsten
Palsson, Bernhard
Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title_full Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title_fullStr Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title_full_unstemmed Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title_short Determining the Control Circuitry of Redox Metabolism at the Genome-Scale
title_sort determining the control circuitry of redox metabolism at the genome-scale
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974632/
https://www.ncbi.nlm.nih.gov/pubmed/24699140
http://dx.doi.org/10.1371/journal.pgen.1004264
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