These authors contributed equally to this work
A system-level model for the microbial regulatory genome
Version of Record online: 15 JUL 2014
© 2014 The Authors. Published under the terms of the CC BY 4.0 license
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.
Molecular Systems Biology
Volume 10, Issue 7, July 2014
How to Cite
Mol Syst Biol. (2014) 10: 740
- Issue online: 1 JUL 2014
- Version of Record online: 15 JUL 2014
- Manuscript Accepted: 11 JUN 2014
- Manuscript Revised: 6 JUN 2014
- Manuscript Received: 28 JAN 2014
- Office of Science
- Office of Biological and Environmental Research
- U. S. Department of Energy. Grant Numbers: DE-AC02-05CH11231, DE-FG02-04ER64685, DE-FG02-07ER64327, DE-FG02-08ER64685
- U.S. National Science Foundation. Grant Number: EAGER—MSB-1237267
- Interplay. Grant Number: NSF-1330912
- ABI. Grant Number: NSF-1262637
- U.S. National Institutes of Health. Grant Number: 2P50GM076547
- University of Luxembourg-ISB Partnership
- Department of Energy Office of Science Graduate Fellowship Program (DOE SCGF)
- American Recovery and Reinvestment Act of 2009, and administered by ORISE-ORAU. Grant Number: DE-AC05-06OR23100
- São Paulo Research Foundation (FAPESP). Grant Numbers: 2012/05392-1, 2011/08104-4
- 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 (http://egrin2.systemsbiology.net) has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes.
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.