CIRAD, UMR ASTRE, Petit-Bourg, Guadeloupe, France.
ASTRE, Univ Montpellier, CIRAD, INRA, Montpellier, France.
PLoS Comput Biol. 2019 Mar 25;15(3):e1006847. doi: 10.1371/journal.pcbi.1006847. eCollection 2019 Mar.
Bacterial pathogens have evolved numerous strategies to corrupt, hijack or mimic cellular processes in order to survive and proliferate. Among those strategies, Type IV effectors (T4Es) are proteins secreted by pathogenic bacteria to manipulate host cell processes during infection. They are delivered into eukaryotic cells in an ATP-dependent manner via the type IV secretion system, a specialized multiprotein complex. T4Es contain a wide spectrum of features including eukaryotic-like domains, localization signals or a C-terminal translocation signal. A combination of these features enables prediction of T4Es in a given bacterial genome. In this study, we developed a web-based comprehensive suite of tools with a user-friendly graphical interface. This version 2.0 of S4TE (Searching Algorithm for Type IV Effector Proteins; http://sate.cirad.fr) enables accurate prediction and comparison of T4Es. Search parameters and threshold can be customized by the user to work with any genome sequence, whether publicly available or not. Applications range from characterizing effector features and identifying potential T4Es to analyzing the effectors based on the genome G+C composition and local gene density. S4TE 2.0 allows the comparison of putative T4E repertoires of up to four bacterial strains at the same time. The software identifies T4E orthologs among strains and provides a Venn diagram and lists of genes for each intersection. New interactive features offer the best visualization of the location of candidate T4Es and hyperlinks to NCBI and Pfam databases. S4TE 2.0 is designed to evolve rapidly with the publication of new experimentally validated T4Es, which will reinforce the predictive power of the algorithm. The computational methodology can be used to identify a wide spectrum of candidate bacterial effectors that lack sequence conservation but have similar amino acid characteristics. This approach will provide very valuable information about bacterial host-specificity and virulence factors and help identify host targets for the development of new anti-bacterial molecules.
细菌病原体进化出许多策略来破坏、劫持或模拟细胞过程，以生存和增殖。在这些策略中，IV 型效应器（T4E）是由致病菌分泌的蛋白质，用于在感染过程中操纵宿主细胞过程。它们通过 IV 型分泌系统以 ATP 依赖性方式递送至真核细胞，IV 型分泌系统是一种专门的多蛋白复合物。T4E 包含广泛的特征，包括类似真核的结构域、定位信号或 C 端易位信号。这些特征的组合可用于预测给定细菌基因组中的 T4E。在这项研究中，我们开发了一个基于网络的综合工具套件，具有用户友好的图形界面。该版本 2.0 的 S4TE（IV 型效应蛋白搜索算法；http://sate.cirad.fr）能够准确预测和比较 T4E。用户可以根据需要自定义搜索参数和阈值，以处理任何公开或非公开的基因组序列。该应用程序的范围从特征分析到潜在 T4E 的鉴定，再到基于基因组 GC 组成和局部基因密度对效应物进行分析。S4TE 2.0 允许同时比较多达四个细菌菌株的假定 T4E 库。该软件在菌株之间识别 T4E 同源物，并提供每个交集的 Venn 图和基因列表。新的交互功能提供了候选 T4E 位置的最佳可视化，并提供了到 NCBI 和 Pfam 数据库的超链接。S4TE 2.0 的设计目的是随着新的实验验证的 T4E 的发表而快速发展，这将增强算法的预测能力。该计算方法可用于识别广泛的候选细菌效应物，这些效应物缺乏序列保守性，但具有相似的氨基酸特征。这种方法将提供有关细菌宿主特异性和毒力因子的非常有价值的信息，并有助于确定新的抗菌分子的宿主靶标。
