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.

doi:10.15252/msb.20145160

A system-level model for the microbial regulatory genome

Journal Article · Tue Jul 01 00:00:00 EDT 2014 · Molecular Systems Biology

DOI:https://doi.org/10.15252/msb.20145160· OSTI ID:1627935

Brooks, Aaron N. ^[1]; Reiss, David J. ^[2]; Allard, Antoine ^[3]; Wu, Wei‐Ju ^[2]; Salvanha, Diego M. ^[4]; Plaisier, Christopher L. ^[2]; Chandrasekaran, Sriram ^[2]; Pan, Min ^[2]; Kaur, Amardeep ^[2]; Baliga, Nitin S. ^[5]

Inst. for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States). Molecular and Cellular Biology Program; DOE/OSTI
Inst. for Systems Biology, Seattle, WA (United States)
Université Laval, Québec, QC (Canada). Département de Physique de Génie Physique et d'Optique
Inst. for Systems Biology, Seattle, WA (United States); Univ. of Sao Paulo, Ribeirao Preto (Brazil). LabPIB. Dept. of Computing and Mathematics FFCLRP‐USP
Inst. for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States). Molecular and Cellular Biology Program; Univ. of Washington, Seattle, WA (United States). Depts. of Microbiology and Biology; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

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.

View Accepted Manuscript (DOE)

Research Organization:: Institute for Systems Biology, Seattle, WA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge Associated Univ., Oak Ridge, TN (United States); Univ. of Washington, Seattle, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: AC02-05CH11231; AC05-06OR23100; FG02-07ER64327; FG02-08ER64685

OSTI ID:: 1627935

Journal Information:: Molecular Systems Biology, Journal Name: Molecular Systems Biology Journal Issue: 7 Vol. 10; ISSN 1744-4292

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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