Searching algorithm for type IV secretion system effectors 1.0: A tool for predicting type IV effectors and exploring their genomic context

Meyer Damien, Noroy Christophe, Moumène Amal, Raffaele Sylvain, Albina Emmanuel, Vachiery Nathalie. 2013. Searching algorithm for type IV secretion system effectors 1.0: A tool for predicting type IV effectors and exploring their genomic context. Nucleic Acids Research, 41 (20) : 9218-9229.

Quartile : Outlier, Sujet : BIOCHEMISTRY & MOLECULAR BIOLOGY

Résumé : Type IV effectors (T4Es) are proteins produced by pathogenic bacteria to manipulate host cell gene expression and processes, divert the cell machinery for their own profit and circumvent the immune responses. T4Es have been characterized for some bacteria but many remain to be discovered. To help biologists identify putative T4Es from the complete genome of ?- and ?-proteobacteria, we developed a Perl-based command line bioinformatics tool called S4TE (searching algorithm for type-IV secretion system effectors). The tool predicts and ranks T4E candidates by using a combination of 13 sequence characteristics, including homology to known effectors, homology to eukaryotic domains, presence of subcellular localization signals or secretion signals, etc. S4TE software is modular, and specific motif searches are run independently before ultimate combination of the outputs to generate a score and sort the strongest T4Es candidates. The user keeps the possibility to adjust various searching parameters such as the weight of each module, the selection threshold or the input databases. The algorithm also provides a GC% and local gene density analysis, which strengthen the selection of T4E candidates. S4TE is a unique predicting tool for T4Es, finding its utility upstream from experimental biology.

Classification Agris : U10 - Informatique, mathématiques et statistiques
S50 - Santé humaine

Champ stratégique Cirad : Axe 4 (2005-2013) - Santé animale et maladies émergentes

Auteurs et affiliations

• Meyer Damien, CIRAD-BIOS-UMR CMAEE (GLP) ORCID: 0000-0003-2735-176X
• Noroy Christophe, INRA (FRA)
• Moumène Amal, CIRAD-BIOS-UMR CMAEE (GLP)
• Raffaele Sylvain, INRA (FRA)
• Albina Emmanuel, CIRAD-BIOS-UMR CMAEE (GLP)
• Vachiery Nathalie, CIRAD-BIOS-UMR CMAEE (GLP)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/571647/)

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