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Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches

机译:使用计算方法识别细菌病因组学中的病原性岛

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High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms.
机译:高通量测序技术使通过分析细菌的基因组序列来研究细菌成为可能。例如,比较基因组序列分析可以揭示基因组中诸如基因丢失,基因获得或基因交换的现象。通过分析致病细菌基因组,我们可以发现许多致病细菌中的致病基因组区域是从其他细菌水平转移的,这些区域也被称为致病岛(PAIs)。 PAI具有某些可检测的特性,例如具有与其余宿主基因组不同的基因组特征,并且包含迁移性基因,因此它们可以整合到宿主基因组中。在这篇综述中,我们将讨论与病原菌岛相关的各种特征以及用于识别PAI的当前计算方法。还将讨论现有的致病岛数据库和相关的计算资源,以便研究人员可以发现它对于细菌进化和致病机制的研究很有用。

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