Evidence map›Paper›PMID 21108798›Full record

ArticleBMC microbiology2010

Computational prediction of the Crc regulon identifies genus-wide and species-specific targets of catabolite repression control in Pseudomonas bacteria.

Patrick Browne, Matthieu Barret, Fergal O'Gara, John P Morrissey

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 41 citations in OpenAlex.

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  18. Reverse diauxie phenotype inNPJ biofilms and microbiomes
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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

4 authors at 2 institutions in 2 countries.

Patrick BrowneBIOMERIT Research Centre, Microbiology Department University College Cork, Ireland.
Matthieu Barret
Fergal O'Gara
John P Morrissey
University College Cork · IEInstitut de recherche en horticulture et semences · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCatabolite repression control (CRC) is an important global control system in Pseudomonas that fine tunes metabolism in order optimise growth and metabolism in a range of different environments. The mechanism of CRC in Pseudomonas spp. centres on the binding of a protein, Crc, to an A-rich motif on the 5' end of an mRNA resulting in translational down-regulation of target genes. Despite the identification of several Crc targets in Pseudomonas spp. the Crc regulon has remained largely unexplored.

resultsIn order to predict direct targets of Crc, we used a bioinformatics approach based on detection of A-rich motifs near the initiation of translation of all protein-encoding genes in twelve fully sequenced Pseudomonas genomes. As expected, our data predict that genes related to the utilisation of less preferred nutrients, such as some carbohydrates, nitrogen sources and aromatic carbon compounds are targets of Crc. A general trend in this analysis is that the regulation of transporters is conserved across species whereas regulation of specific enzymatic steps or transcriptional activators are often conserved only within a species. Interestingly, some nucleoid associated proteins (NAPs) such as HU and IHF are predicted to be regulated by Crc. This finding indicates a possible role of Crc in indirect control over a subset of genes that depend on the DNA bending properties of NAPs for expression or repression. Finally, some virulence traits such as alginate and rhamnolipid production also appear to be regulated by Crc, which links nutritional status cues with the regulation of virulence traits.

conclusionsCatabolite repression control regulates a broad spectrum of genes in Pseudomonas. Some targets are genus-wide and are typically related to central metabolism, whereas other targets are species-specific, or even unique to particular strains. Further study of these novel targets will enhance our understanding of how Pseudomonas bacteria integrate nutritional status cues with the regulation of traits that are of ecological, industrial and clinical importance.

Indexed as

Catabolite RepressionComputational BiologyGene Expression Regulation, BacterialRegulonBacterial ProteinsPseudomonasRepressor ProteinsBacterial Proteinscrc protein, PseudomonasRepressor Proteins

Identifiers

PMID21108798
PMCPMC3003667
OpenAlexW2161532174

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.