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绘制细菌效应因子图谱:通过体内和计算机模拟方法定义决定细菌效应因子分泌的蛋白特征。

Mapping bacterial effector arsenals: in vivo and in silico approaches to defining the protein features dictating effector secretion by bacteria.

机构信息

Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, 3000 Victoria, Australia.

Infection and Immunity Program, Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton, 3800 Victoria, Australia.

出版信息

Curr Opin Microbiol. 2020 Oct;57:13-21. doi: 10.1016/j.mib.2020.04.002. Epub 2020 Jun 5.

DOI:10.1016/j.mib.2020.04.002
PMID:32505919
Abstract

Many bacterial pathogens rely on dedicated secretion systems to translocate virulence proteins termed 'effectors' into host cells. These effectors engage and manipulate host cellular functions to support bacterial colonization and propagation. The secretion systems are molecular machines that recognize targeting 'features' in these effector proteins in vivo to selectively and efficiently secrete them. The joint analysis of whole genome sequencing data and computational predictions of amino acid characteristics of effector proteins has made available extensive lists of candidate effectors for many bacterial pathogens, among which Dot/Icm type IVB secretion system in Legionella pneumophila reigns with the largest number of effectors identified to-date. This system is also used by the causative agent of Q fever, Coxiella burnetii, to secrete a large pool of distinct effectors. By comparing these two pathogens, we provide an understanding of the rationale behind effector repertoire expansion. We will also discuss recent bioinformatic advances facilitating high-throughput discovery of secreted effectors through in silico 'feature' recognition, and the current challenge to substantiate the biological relevance and bona fide nature of effectors identified in silico.

摘要

许多细菌病原体依赖于专门的分泌系统将毒力蛋白(称为“效应物”)易位到宿主细胞中。这些效应物与宿主细胞功能相互作用并操纵宿主细胞功能,以支持细菌的定植和繁殖。分泌系统是分子机器,可在体内识别这些效应蛋白中的靶向“特征”,以选择性和有效地分泌它们。对全基因组测序数据和效应蛋白氨基酸特征的计算预测的联合分析,为许多细菌病原体提供了大量候选效应物的列表,其中军团菌属的 Dot/Icm 型 IVB 分泌系统鉴定出的效应物数量最多。该系统也被 Q 热病原体贝氏柯克斯体用于分泌大量不同的效应物。通过比较这两种病原体,我们了解了效应物库扩张背后的基本原理。我们还将讨论最近的生物信息学进展,这些进展通过计算“特征”识别促进了分泌效应物的高通量发现,并讨论了当前的挑战,即证实通过计算鉴定的效应物的生物学相关性和真实性。

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Mapping bacterial effector arsenals: in vivo and in silico approaches to defining the protein features dictating effector secretion by bacteria.绘制细菌效应因子图谱:通过体内和计算机模拟方法定义决定细菌效应因子分泌的蛋白特征。
Curr Opin Microbiol. 2020 Oct;57:13-21. doi: 10.1016/j.mib.2020.04.002. Epub 2020 Jun 5.
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Legionella pneumophila, armed to the hilt: justifying the largest arsenal of effectors in the bacterial world.军团菌肺炎,全副武装:正当细菌世界中最大的效应器库。
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Use of Bastion for the Identification of Secreted Substrates.利用 Bastion 鉴定分泌底物。
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PncsHub: a platform for annotating and analyzing non-classically secreted proteins in Gram-positive bacteria.
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Nucleic Acids Res. 2022 Jan 7;50(D1):D848-D857. doi: 10.1093/nar/gkab814.
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Proteomic Identification of Coxiella burnetii Effector Proteins Targeted to the Host Cell Mitochondria During Infection.感染过程中靶向宿主细胞线粒体的柯克斯体效应蛋白的蛋白质组学鉴定。
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Nucleic Acids Res. 2021 Jan 8;49(D1):D651-D659. doi: 10.1093/nar/gkaa899.