CIRAD, UMR CMAEE, F-97170 Petit-Bourg, Guadeloupe, France, INRA, UMR1309 CMAEE, F-34398, Montpellier, France, Université des Antilles et de la Guyane, 97159 Pointe-à-Pitre cedex, Guadeloupe, France, INRA, Laboratoire des Interactions Plantes-Microorganismes, UMR441, Castanet-Tolosan, France and CNRS, Laboratoire des Interactions Plantes-Microorganismes, UMR2594, Castanet-Tolosan, France.
Nucleic Acids Res. 2013 Nov;41(20):9218-29. doi: 10.1093/nar/gkt718. Epub 2013 Aug 13.
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 α- and γ-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.
IV 型效应器（T4Es）是由病原菌产生的蛋白质，用于操纵宿主细胞的基因表达和过程，为自身利益转移细胞机制，并规避免疫反应。已经对一些细菌进行了 T4E 的特征描述，但仍有许多有待发现。为了帮助生物学家从α-和γ-变形菌的完整基因组中识别推定的 T4E，我们开发了一种基于 Perl 的命令行生物信息学工具，称为 S4TE（IV 型分泌系统效应器搜索算法）。该工具通过使用 13 种序列特征的组合来预测和排列 T4E 候选物，包括与已知效应物的同源性、与真核结构域的同源性、亚细胞定位信号或分泌信号的存在等。S4TE 软件是模块化的，在最终组合输出以生成分数并对最强的 T4E 候选物进行排序之前，独立运行特定的模体搜索。用户可以调整各种搜索参数，如每个模块的权重、选择阈值或输入数据库。该算法还提供 GC%和局部基因密度分析，这加强了 T4E 候选物的选择。S4TE 是一种独特的 T4E 预测工具，在实验生物学之前就具有实用性。
