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利用隐马尔可夫模型揭示细菌基因组中核酸酶细菌素的多样性和分布

Diversity and distribution of nuclease bacteriocins in bacterial genomes revealed using Hidden Markov Models.

作者信息

Sharp Connor, Bray James, Housden Nicholas G, Maiden Martin C J, Kleanthous Colin

机构信息

Department of Biochemistry, University of Oxford, Oxford, United Kingdom.

Department of Zoology, University of Oxford, Oxford, United Kingdom.

出版信息

PLoS Comput Biol. 2017 Jul 17;13(7):e1005652. doi: 10.1371/journal.pcbi.1005652. eCollection 2017 Jul.

Abstract

Bacteria exploit an arsenal of antimicrobial peptides and proteins to compete with each other. Three main competition systems have been described: type six secretion systems (T6SS); contact dependent inhibition (CDI); and bacteriocins. Unlike T6SS and CDI systems, bacteriocins do not require contact between bacteria but are diffusible toxins released into the environment. Identified almost a century ago, our understanding of bacteriocin distribution and prevalence in bacterial populations remains poor. In the case of protein bacteriocins, this is because of high levels of sequence diversity and difficulties in distinguishing their killing domains from those of other competition systems. Here, we develop a robust bioinformatics pipeline exploiting Hidden Markov Models for the identification of nuclease bacteriocins (NBs) in bacteria of which, to-date, only a handful are known. NBs are large (>60 kDa) toxins that target nucleic acids (DNA, tRNA or rRNA) in the cytoplasm of susceptible bacteria, usually closely related to the producing organism. We identified >3000 NB genes located on plasmids or on the chromosome from 53 bacterial species distributed across different ecological niches, including human, animals, plants, and the environment. A newly identified NB predicted to be specific for Pseudomonas aeruginosa (pyocin Sn) was produced and shown to kill P. aeruginosa thereby validating our pipeline. Intriguingly, while the genes encoding the machinery needed for NB translocation across the cell envelope are widespread in Gram-negative bacteria, NBs are found exclusively in γ-proteobacteria. Similarity network analysis demonstrated that NBs fall into eight groups each with a distinct arrangement of protein domains involved in import. The only structural feature conserved across all groups was a sequence motif critical for cell-killing that is generally not found in bacteriocins targeting the periplasm, implying a specific role in translocating the nuclease to the cytoplasm. Finally, we demonstrate a significant association between nuclease colicins, NBs specific for Escherichia coli, and virulence factors, suggesting NBs play a role in infection processes, most likely by enabling pathogens to outcompete commensal bacteria.

摘要

细菌利用一系列抗菌肽和蛋白质相互竞争。已描述了三种主要的竞争系统:VI型分泌系统(T6SS);接触依赖性抑制(CDI);以及细菌素。与T6SS和CDI系统不同,细菌素不需要细菌之间的接触,而是释放到环境中的可扩散毒素。大约一个世纪前就已发现细菌素,但我们对其在细菌群体中的分布和流行情况仍了解不足。就蛋白质细菌素而言,这是因为其序列多样性水平高,且难以将其杀伤结构域与其他竞争系统的杀伤结构域区分开来。在此,我们开发了一种强大的生物信息学流程,利用隐马尔可夫模型来鉴定细菌中的核酸酶细菌素(NBs),迄今为止,已知的此类细菌素只有少数几种。NBs是大型(>60 kDa)毒素,靶向易感细菌细胞质中的核酸(DNA、tRNA或rRNA),通常与产生菌密切相关。我们从分布于不同生态位(包括人类、动物、植物和环境)的53种细菌物种中,鉴定出位于质粒或染色体上的3000多个NB基因。一种新鉴定的预计对铜绿假单胞菌具有特异性的NB(pyocin Sn)被生产出来,并显示能杀死铜绿假单胞菌,从而验证了我们的流程。有趣的是,虽然编码NB跨细胞膜转运所需机制的基因在革兰氏阴性菌中广泛存在,但NB仅在γ-变形菌中发现。相似性网络分析表明,NBs分为八组,每组在参与导入的蛋白质结构域排列上都有明显差异。所有组中唯一保守的结构特征是对细胞杀伤至关重要的序列基序,而在靶向周质的细菌素中通常不存在,这意味着其在将核酸酶转运到细胞质中具有特定作用。最后,我们证明核酸酶大肠杆菌素(对大肠杆菌具有特异性的NBs)与毒力因子之间存在显著关联,表明NBs在感染过程中发挥作用,很可能是通过使病原体胜过共生细菌来实现的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ff2/5536347/62e4027cd14c/pcbi.1005652.g001.jpg

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