Evidence map›Paper›PMID 22139924›Full record

ArticleNucleic acids research2012

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains.

Christophe Pichon, Laurence du Merle, Marie Elise Caliot, Patrick Trieu-Cuot, Chantal Le Bouguénec

Open access · goldAbstract readValidation Study
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

27 citing papers in PubMed, 42 citations in OpenAlex.

  1. Role of Metabolic Adaptation ofPathogens (Basel, Switzerland) · 2023
    Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Small RNA Regulation of Virulence in PathogenicFrontiers in cellular and infection microbiology · 2020
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Editorial: Small Non-coding RNAs inFrontiers in genetics · 2016
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

5 authors at 1 institution in 1 country.

Christophe PichonInstitut Pasteur, Unité de Biologie des Bactéries Pathogènes à Gram Positif, 25-28 Rue du Docteur Roux, F-75724 Paris, France.
Laurence du Merle
Marie Elise Caliot
Patrick Trieu-Cuot
Chantal Le Bouguénec
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

Indexed as

Computer SimulationGenome, BacterialAntigens, BacterialBase PairingBiofilmsEscherichia coliEscherichia coli ProteinsFimbriae ProteinsGene Expression Regulation, BacterialGenomic IslandsHost Factor 1 ProteinRegulonRNA, AntisenseRNA, MessengerStreptococcus agalactiaeAntigens, BacterialEscherichia coli ProteinsFimbriae ProteinsfimD protein, E coliHfq protein, E coliHost Factor 1 ProteinRNA, AntisenseRNA, MessengerSIP protein, Streptococcus group B

Identifiers

PMID22139924
PMCPMC3326304
OpenAlexW2102230713

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.