ArticlePloS one2013
Effective identification of bacterial type III secretion signals using joint element features.
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.
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Who cites it
19 citing papers in PubMed.
- Type III secretion system chaperones: a helping hand for secretion.Microbiology (Reading, England) · 2026Review
- Machine learning for the prediction of gram-negative bacterial secreted effectors: advances and challenges.Frontiers in chemistry · 2026Review
- Type III secretion by Yersinia pseudotuberculosis is reliant upon an authentic N-terminal YscX secretor domain.Molecular microbiology · 2022Article
- Recent Advancements in Tracking Bacterial Effector Protein Translocation.Microorganisms · 2022Review
- Natural language processing approach to model the secretion signal of type III effectors.Frontiers in plant science · 2022Article
- DeepT3 2.0: improving type III secreted effector predictions by an integrative deep learning framework.NAR genomics and bioinformatics · 2021Article
- iT3SE-PX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection.Computational and mathematical methods in medicine · 2021Article
- Computational prediction of secreted proteins in gram-negative bacteria.Computational and structural biotechnology journal · 2021Review
- Article
- Review
- Bastion3: a two-layer ensemble predictor of type III secreted effectors.Bioinformatics (Oxford, England) · 2019Article
- Chromosomally-EncodedFrontiers in cellular and infection microbiology · 2019Article
- A conserved motif promotes HpaB-regulated export of type III effectors from Xanthomonas.Molecular plant pathology · 2018Article
- The TAL Effector AvrBs3 fromFrontiers in microbiology · 2017Article
- Computational approach to predict species-specific type III secretion system (T3SS) effectors using single and multiple genomes.BMC genomics · 2016Article
- YscU/FlhB of Yersinia pseudotuberculosis Harbors a C-terminal Type III Secretion Signal.The Journal of biological chemistry · 2015Article
- Comparative analysis of the secretion capability of early and late flagellar type III secretion substrates.Molecular microbiology · 2014Article
- Prediction of bacterial type IV secreted effectors by C-terminal features.BMC genomics · 2014Article
- The SPI-1-like Type III secretion system: more roles than you think.Frontiers in plant science · 2014Review
Corrections and comments
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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