Evidence map›Paper›PMID 25028489›Full record

ArticleMolecular systems biology2014

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

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 73 citations in OpenAlex.

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  12. Genes · 2021
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  15. Identifying Components of aFrontiers in microbiology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 3 countries.

Aaron N BrooksInstitute for Systems Biology, Seattle, WA, USA Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.
David J ReissInstitute for Systems Biology, Seattle, WA, USA dreiss@systemsbiology.org nbaliga@systemsbiology.org.
Antoine AllardDépartement de Physique, de Génie Physique et d'Optique, Université Laval, Québec, QC, Canada.
Wei-Ju WuInstitute for Systems Biology, Seattle, WA, USA.
Diego M SalvanhaInstitute for Systems Biology, Seattle, WA, USA LabPIB, Department of Computing and Mathematics FFCLRP-USP, University of Sao Paulo, Ribeirao Preto, Brazil.
Christopher L PlaisierInstitute for Systems Biology, Seattle, WA, USA.
Sriram ChandrasekaranInstitute for Systems Biology, Seattle, WA, USA.
Min PanInstitute for Systems Biology, Seattle, WA, USA.
Amardeep KaurInstitute for Systems Biology, Seattle, WA, USA.
Nitin S BaligaInstitute for Systems Biology, Seattle, WA, USA Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA Departments of Microbiology and Biology, University of Washington, Seattle, WA, USA Lawrence Berkeley National Laboratories, Berkeley, CA, USA dreiss@systemsbiology.org nbaliga@systemsbiology.org.
Institute for Systems Biology · USUniversité Laval · CA

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DUDLEY, AIMEE M · 2006 to 2016
$30.6M
NIGMS NIH HHS 2P50GM076547NIGMS NIH HHS P50 GM076547
6 · The paper itself

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.

Indexed as

Gene Regulatory NetworksGenome, MicrobialModels, GeneticAlgorithmsEscherichia coliGene Expression RegulationGenetic FitnessHalobacterium salinarumOperonRegulatory Elements, TranscriptionalRegulonEGRINgene regulatory networkssystems biologytranscriptional regulation

Identifiers

PMID25028489
PMCPMC4299497
OpenAlexW2150072274

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.