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


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 ( has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes.


Thumbnail image of graphical abstract

Genome-scale reconstruction of microbial gene regulatory networks using genome sequence and transcriptional profiles reveals condition-dependent co-regulated modules (corems) and predicts the underlying cis-regulatory mechanisms.

  • Genome-wide map of gene regulatory elements (GREs) and their condition-specific activities
  • Model predicts which mechanisms mediate responses to specific environments
  • Operons and regulons are conditionally partitioned and re-associated into co-regulated modules or “corems”.
  • Corems group together genes from different operons and regulons that have highly similar fitness consequences.