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Updated: Jan 27, 2026
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Analysis of Yersinia enterocolitica Effector Translocation into Host Cells Using Beta-lactamase Effector Fusions
Published on: October 13, 2015
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Searching algorithm for Type IV effector proteins (S4TE) 2.0: Improved tools for Type IV effector prediction,
Christophe Noroy1,2,3, Thierry Lefrançois2, Damien F Meyer1,2
1CIRAD, UMR ASTRE, Petit-Bourg, Guadeloupe, France.
Plos Computational Biology
|March 26, 2019
Summary
Researchers developed S4TE 2.0, a tool to predict bacterial Type IV Effectors (T4Es) and compare them across strains. This aids in understanding bacterial virulence and identifying new antibacterial targets.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Bacterial pathogens use Type IV Effectors (T4Es) to manipulate host cells for survival.
- T4Es are delivered via type IV secretion systems and possess specific features like eukaryotic-like domains.
- Predicting T4Es is crucial for understanding bacterial virulence and host-specificity.
Purpose of the Study:
- To develop and present S4TE 2.0, a user-friendly, web-based tool for accurate prediction and comparison of T4Es.
- To enable customized analysis of T4Es across various bacterial genomes.
- To facilitate the identification of T4E orthologs and comparative analysis of effector repertoires.
Main Methods:
- Development of a web-based suite of tools (S4TE 2.0) with a graphical interface.
- Implementation of customizable search parameters and thresholds for T4E prediction.
- Utilizing features like eukaryotic-like domains, localization signals, and C-terminal translocation signals for prediction.
- Comparative analysis of T4E repertoires across multiple bacterial strains using Venn diagrams and gene lists.
Main Results:
- S4TE 2.0 provides accurate prediction and comparison of T4Es.
- The tool allows customized analysis for any genome, including G+C composition and gene density.
- It enables comparison of up to four bacterial strains, identifying orthologs and providing visualizations.
- Interactive features link to NCBI and Pfam databases for enhanced data exploration.
Conclusions:
- S4TE 2.0 is a valuable resource for identifying and analyzing bacterial T4Es.
- The software aids in understanding bacterial host-specificity and virulence factors.
- It supports the discovery of potential targets for novel antibacterial therapies.
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