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A system-level model for the microbial regulatory genome

  • 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

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number740
JournalMolecular Systems Biology
Volume10
Issue number7
DOIs
StatePublished - Jul 2014
Externally publishedYes

Keywords

  • EGRIN
  • gene regulatory networks
  • systems biology
  • transcriptional regulation

ASJC Scopus subject areas

  • Information Systems
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Computational Theory and Mathematics
  • Applied Mathematics

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