Evidence map›Paper›PMID 23593149›Full record

ArticlePloS one2013

Effective identification of bacterial type III secretion signals using joint element features.

Yejun Wang, Ming'an Sun, Hongxia Bao, Qing Zhang, Dianjing Guo

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Computational prediction of secreted proteins in gram-negative bacteria.Computational and structural biotechnology journal · 2021
    Review
  9. Article
  10. Virulence · 2019
    Review
  11. Article
  12. Chromosomally-EncodedFrontiers in cellular and infection microbiology · 2019
    Article
  13. Article
  14. The TAL Effector AvrBs3 fromFrontiers in microbiology · 2017
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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.

Yejun WangSchool of Life Sciences and the State Key Lab of Agrobiotechnology, the Chinese University of Hong Kong, Shatin, NT, Hong Kong.
Ming'an Sun
Hongxia Bao
Qing Zhang
Dianjing Guo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type III secretion system (T3SS) plays important roles in bacteria and host cell interactions by specifically translocating type III effectors into the cytoplasm of the host cells. The N-terminal amino acid sequences of the bacterial type III effectors determine their specific secretion via type III secretion conduits. It is still unclear as to how the N-terminal sequences guide this specificity. In this work, the amino acid composition, secondary structure, and solvent accessibility in the N-termini of type III and non-type III secreted proteins were compared and contrasted. A high-efficacy mathematical model based on these joint features was developed to distinguish the type III proteins from the non-type III ones. The results indicate that secondary structure and solvent accessibility may make important contribution to the specific recognition of type III secretion signals. Analysis also showed that the joint feature of the N-terminal 6(th)-10(th) amino acids are especially important for guiding specific type III secretion. Furthermore, a genome-wide screening was performed to predict Salmonella type III secreted proteins, and 8 new candidates were experimentally validated. Interestingly, type III secretion signals were also predicted in gram-positive bacteria and yeasts. Experimental validation showed that two candidates from yeast can indeed be secreted through Salmonella type III secretion conduit. This research provides the first line of direct evidence that secondary structure and solvent accessibility contain important features for guiding specific type III secretion. The new software based on these joint features ensures a high accuracy (general cross-validation sensitivity of ∼96% at a specificity of ∼98%) in silico identification of new type III secreted proteins, which may facilitate our understanding about the specificity of type III secretion and the evolution of type III secreted proteins.

Indexed as

Bacterial Secretion SystemsBacteriaBacterial ProteinsCell LineComputational BiologyComputer SimulationGenome, BacterialHumansModels, BiologicalModels, MolecularProtein ConformationProtein TransportSalmonellaSequence DeletionBacterial ProteinsBacterial Secretion Systems

Identifiers

PMID23593149
PMCPMC3617162

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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.