A system‐level model for the microbial regulatory genome
Abstract 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 ty...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2014-07-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.15252/msb.20145160 |
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| _version_ | 1850179272081145856 |
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| author | Aaron N Brooks David J Reiss Antoine Allard Wei‐Ju Wu Diego M Salvanha Christopher L Plaisier Sriram Chandrasekaran Min Pan Amardeep Kaur Nitin S Baliga |
| author_facet | Aaron N Brooks David J Reiss Antoine Allard Wei‐Ju Wu Diego M Salvanha Christopher L Plaisier Sriram Chandrasekaran Min Pan Amardeep Kaur Nitin S Baliga |
| author_sort | Aaron N Brooks |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-af647d93246e4a92a0f9b8b40d778dd7 |
| institution | OA Journals |
| issn | 1744-4292 |
| language | English |
| publishDate | 2014-07-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-af647d93246e4a92a0f9b8b40d778dd72025-08-20T02:18:32ZengSpringer NatureMolecular Systems Biology1744-42922014-07-0110711410.15252/msb.20145160A system‐level model for the microbial regulatory genomeAaron N Brooks0David J Reiss1Antoine Allard2Wei‐Ju Wu3Diego M Salvanha4Christopher L Plaisier5Sriram Chandrasekaran6Min Pan7Amardeep Kaur8Nitin S Baliga9Institute for Systems BiologyInstitute for Systems BiologyDépartement de Physique, de Génie Physique et d'Optique, Université LavalInstitute for Systems BiologyInstitute for Systems BiologyInstitute for Systems BiologyInstitute for Systems BiologyInstitute for Systems BiologyInstitute for Systems BiologyInstitute for Systems BiologyAbstract 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.https://doi.org/10.15252/msb.20145160EGRINgene regulatory networkssystems biologytranscriptional regulation |
| spellingShingle | Aaron N Brooks David J Reiss Antoine Allard Wei‐Ju Wu Diego M Salvanha Christopher L Plaisier Sriram Chandrasekaran Min Pan Amardeep Kaur Nitin S Baliga A system‐level model for the microbial regulatory genome Molecular Systems Biology EGRIN gene regulatory networks systems biology transcriptional regulation |
| 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 | EGRIN gene regulatory networks systems biology transcriptional regulation |
| url | https://doi.org/10.15252/msb.20145160 |
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