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Novel Type III Effectors in Pseudomonas aeruginosa

机译:铜绿假单胞菌中的新型III型效应子

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ABSTRACT Pseudomonas aeruginosa is a Gram-negative, opportunistic pathogen that causes chronic and acute infections in immunocompromised patients. Most P.?aeruginosa strains encode an active type III secretion system (T3SS), utilized by the bacteria to deliver effector proteins from the bacterial cell directly into the cytoplasm of the host cell. Four T3SS effectors have been discovered and extensively studied in P.?aeruginosa : ExoT, ExoS, ExoU, and ExoY. This is especially intriguing in light of P.?aeruginosa ’s ability to infect a wide range of hosts. We therefore hypothesized that additional T3SS effectors that have not yet been discovered are encoded in the genome of P.?aeruginosa . Here, we applied a machine learning classification algorithm to identify novel P.?aeruginosa effectors. In this approach, various types of data are integrated to differentiate effectors from the rest of the open reading frames of the bacterial genome. Due to the lack of a sufficient learning set of positive effectors, our machine learning algorithm integrated genomic information from another Pseudomonas species and utilized dozens of features accounting for various aspects of the effector coding genes and their products. Twelve top-ranking predictions were experimentally tested for T3SS-specific translocation, leading to the discovery of two novel T3SS effectors. We demonstrate that these effectors are not part of the injection structural complex and report initial efforts toward their characterization. IMPORTANCE Pseudomonas aeruginosa uses a type III secretion system (T3SS) to secrete toxic proteins, termed effectors, directly into the cytoplasm of the host cell. The activation of this secretion system is correlated with disease severity and patient death. Compared with many other T3SS-utilizing pathogenic bacteria, P.?aeruginosa has a fairly limited arsenal of effectors that have been identified. This is in sharp contrast with the wide range of hosts that this bacterium can infect. The discovery of two novel effectors described here is an important step toward better understanding of the virulence and host evasion mechanisms adopted by this versatile pathogen and may provide novel approaches to treat P.?aeruginosa infections.
机译:摘要铜绿假单胞菌是革兰氏阴性的机会病原体,可在免疫功能低下的患者中引起慢性和急性感染。大部分的绿脓杆菌菌株编码一种活性的III型分泌系统(T3SS),细菌利用该系统将效应蛋白从细菌细胞直接传递到宿主细胞的细胞质中。在铜绿假单胞菌中已经发现并广泛研究了四种T3SS效应子:ExoT,ExoS,ExoU和ExoY。鉴于绿脓杆菌感染多种宿主的能力,这尤其令人着迷。因此我们假设尚未发现的其他T3SS效应子在铜绿假单胞菌的基因组中编码。在这里,我们应用了机器学习分类算法来识别新颖的铜绿假单胞菌效应子。通过这种方法,可以整合各种类型的数据,以将效应子与细菌基因组的其余开放阅读框区分开。由于缺乏足够的阳性效应子学习集,我们的机器学习算法整合了另一种假单胞菌属物种的基因组信息,并利用了数十种特征来解释效应子编码基因及其产物的各个方面。对T3SS特异的易位性通过实验测试了十二个排名最高的预测,从而发现了两个新颖的T3SS效应子。我们证明这些效应器不是注射结构复杂的一部分,并报告了对其表征的初步努力。重要事项铜绿假单胞菌使用III型分泌系统(T3SS)将有毒的蛋白(称为效应子)直接分泌到宿主细胞的细胞质中。该分泌系统的激活与疾病严重程度和患者死亡相关。与许多其他利用T3SS的致病细菌相比,铜绿假单胞菌的效应子库已经被确定。这与该细菌可以感染的多种宿主形成鲜明对比。此处描述的两种新型效应子的发现是迈向更好地理解这种多功能病原体采用的毒力和宿主逃逸机制的重要一步,并且可能为治疗绿脓杆菌感染提供新的方法。

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