Computational prediction shines light on type III secretion origins.
Computational prediction shines light on type III secretion origins.
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DOI：
10.1038/srep34516
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发表时间：
2016-10-07
影响因子：
4.6
通讯作者：
Bromberg Y
中科院分区：
文献类型：
--
作者：
Goldberg T;Rost B;Bromberg Y
III型分泌系统是一种关键的细菌共生和致病机制，负责各种传染病，从食源性疾病到腺鼠疫。在许多革兰氏阴性细菌中，III型分泌系统将效应蛋白转运到宿主细胞中，将资源转化为细菌优势。在这里，我们介绍了一种计算方法，通过结合同源性为基础的推理与从头预测，识别III型效应子，达到高达3倍的性能比现有的工具。我们的工作揭示了识别和转运效应子的信号分布在整个蛋白质序列上，而不是像以前认为的那样局限于N-末端。我们扫描了数百个原核生物基因组，发现了以前未知的效应子，这表明III型分泌可能在古细菌/细菌分裂之前就已经进化了。至关重要的是，我们的方法对短序列片段表现良好，有利于微生物群落的评估和细菌致病性的快速鉴定-不需要基因组组装。pEffect及其数据集可在http://services.bromberglab.org/peffect上获得。
Type III secretion system is a key bacterial symbiosis and pathogenicity mechanism responsible for a variety of infectious diseases, ranging from food-borne illnesses to the bubonic plague. In many Gram-negative bacteria, the type III secretion system transports effector proteins into host cells, converting resources to bacterial advantage. Here we introduce a computational method that identifies type III effectors by combining homology-based inference with de novo predictions, reaching up to 3-fold higher performance than existing tools. Our work reveals that signals for recognition and transport of effectors are distributed over the entire protein sequence instead of being confined to the N-terminus, as was previously thought. Our scan of hundreds of prokaryotic genomes identified previously unknown effectors, suggesting that type III secretion may have evolved prior to the archaea/bacteria split. Crucially, our method performs well for short sequence fragments, facilitating evaluation of microbial communities and rapid identification of bacterial pathogenicity – no genome assembly required. pEffect and its data sets are available at http://services.bromberglab.org/peffect.