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A system-level model for the microbial regulatory genome

Microbes can tailor transcriptional responses to diverse environmental challenges despite having streamlined genomes and a limited number of regulators. Here, we present data-driven models that capture the dynamic interplay of the environment and genome-encoded regulatory programs of two types of pr...

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Autores principales: Brooks, Aaron N, Reiss, David J, Allard, Antoine, Wu, Wei-Ju, Salvanha, Diego M, Plaisier, Christopher L, Chandrasekaran, Sriram, Pan, Min, Kaur, Amardeep, Baliga, Nitin S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299497/
https://www.ncbi.nlm.nih.gov/pubmed/25028489
http://dx.doi.org/10.15252/msb.20145160
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author Brooks, Aaron N
Reiss, David J
Allard, Antoine
Wu, Wei-Ju
Salvanha, Diego M
Plaisier, Christopher L
Chandrasekaran, Sriram
Pan, Min
Kaur, Amardeep
Baliga, Nitin S
author_facet Brooks, Aaron N
Reiss, David J
Allard, Antoine
Wu, Wei-Ju
Salvanha, Diego M
Plaisier, Christopher L
Chandrasekaran, Sriram
Pan, Min
Kaur, Amardeep
Baliga, Nitin S
author_sort Brooks, Aaron N
collection PubMed
description Microbes can tailor transcriptional responses to diverse environmental challenges despite having streamlined genomes and a limited number of regulators. Here, we present data-driven models that capture the dynamic interplay of the environment and genome-encoded regulatory programs of two types of prokaryotes: Escherichia coli (a bacterium) and Halobacterium salinarum (an archaeon). The models reveal how the genome-wide distributions of cis-acting gene regulatory elements and the conditional influences of transcription factors at each of those elements encode programs for eliciting a wide array of environment-specific responses. We demonstrate how these programs partition transcriptional regulation of genes within regulons and operons to re-organize gene–gene functional associations in each environment. The models capture fitness-relevant co-regulation by different transcriptional control mechanisms acting across the entire genome, to define a generalized, system-level organizing principle for prokaryotic gene regulatory networks that goes well beyond existing paradigms of gene regulation. An online resource (http://egrin2.systemsbiology.net) has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes.
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spelling pubmed-42994972015-01-20 A system-level model for the microbial regulatory genome Brooks, Aaron N Reiss, David J Allard, Antoine Wu, Wei-Ju Salvanha, Diego M Plaisier, Christopher L Chandrasekaran, Sriram Pan, Min Kaur, Amardeep Baliga, Nitin S Mol Syst Biol Articles Microbes can tailor transcriptional responses to diverse environmental challenges despite having streamlined genomes and a limited number of regulators. Here, we present data-driven models that capture the dynamic interplay of the environment and genome-encoded regulatory programs of two types of prokaryotes: Escherichia coli (a bacterium) and Halobacterium salinarum (an archaeon). The models reveal how the genome-wide distributions of cis-acting gene regulatory elements and the conditional influences of transcription factors at each of those elements encode programs for eliciting a wide array of environment-specific responses. We demonstrate how these programs partition transcriptional regulation of genes within regulons and operons to re-organize gene–gene functional associations in each environment. The models capture fitness-relevant co-regulation by different transcriptional control mechanisms acting across the entire genome, to define a generalized, system-level organizing principle for prokaryotic gene regulatory networks that goes well beyond existing paradigms of gene regulation. An online resource (http://egrin2.systemsbiology.net) has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes. Blackwell Publishing Ltd 2014-07-15 /pmc/articles/PMC4299497/ /pubmed/25028489 http://dx.doi.org/10.15252/msb.20145160 Text en © 2014 The Authors. Published under the terms of the CC BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Brooks, Aaron N
Reiss, David J
Allard, Antoine
Wu, Wei-Ju
Salvanha, Diego M
Plaisier, Christopher L
Chandrasekaran, Sriram
Pan, Min
Kaur, Amardeep
Baliga, Nitin S
A system-level model for the microbial regulatory genome
title A system-level model for the microbial regulatory genome
title_full A system-level model for the microbial regulatory genome
title_fullStr A system-level model for the microbial regulatory genome
title_full_unstemmed A system-level model for the microbial regulatory genome
title_short A system-level model for the microbial regulatory genome
title_sort system-level model for the microbial regulatory genome
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299497/
https://www.ncbi.nlm.nih.gov/pubmed/25028489
http://dx.doi.org/10.15252/msb.20145160
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