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Deciphering the role of insertion sequences in the evolution of bacterial epidemic pathogens with panISa software

机译:使用panISa软件解读插入序列在细菌流行病原体进化中的作用

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摘要

Next-generation sequencing (NGS) is now widely used in microbiology to explore genome evolution and the structure of pathogen outbreaks. Bioinformatics pipelines readily detect single-nucleotide polymorphisms or short indels. However, bacterial genomes also evolve through the action of small transposable elements called insertion sequences (ISs), which are difficult to detect due to their short length and multiple repetitions throughout the genome. We designed software for the detection of IS insertions in the genomes of prokaryotes. has been released as open source software (GPL3) available from In this study, we assessed the utility of this software for evolutionary studies, by reanalysing five published datasets for outbreaks of human major pathogens in which ISs had not been specifically investigated. We reanalysed the raw data from each study, by aligning the reads against reference genomes and running on the alignments. Each hit was automatically curated and IS-related events were validated on the basis of nucleotide sequence similarity, by comparison with the ISFinder database. In , the pipeline identified IS or IS upstream from the gene, which encodes a cephalosporinase in all third-generation cephalosporin-resistant isolates. In the genomes of isolates, we found that early Haitian isolates had the same ISs as Nepalese isolates, confirming the inferred history of the contamination of this island. In , identified regions of high plasticity, including a pathogenicity island enriched in IS-related events. The overall distribution of ISs deduced with was consistent with SNP-based phylogenic trees, for all species considered. The role of ISs in pathogen evolution has probably been underestimated due to difficulties detecting these transposable elements. We show here that is a useful addition to the bioinformatics toolbox for analyses of the evolution of bacterial genomes. will facilitate explorations of the functional impact of ISs and improve our understanding of prokaryote evolution.
机译:下一代测序(NGS)现在已广泛用于微生物学中,以探索基因组进化和病原体爆发的结构。生物信息学流水线很容易检测到单核苷酸多态性或短插入缺失。但是,细菌基因组也通过称为插入序列(ISs)的小转座因子的作用而进化,由于它们的短长度和在整个基因组中的多次重复,很难检测到。我们设计了用于检测原核生物基因组中IS插入的软件。已作为开放源代码软件(GPL3)发布,可通过以下途径获得。在本研究中,我们通过重新分析五个未专门调查IS的人类主要病原体暴发的数据集,评估了该软件在进化研究中的效用。我们通过将读取的数据与参考基因组进行比对并进行比对,重新分析了每项研究的原始数据。通过与ISFinder数据库进行比较,每个匹配都自动进行整理,并基于核苷酸序列相似性验证与IS相关的事件。在中,管道识别出IS或该基因上游的IS,该基因在所有第三代头孢菌素耐药菌株中均编码头孢菌素酶。在分离株的基因组中,我们发现海地早期分离株与尼泊尔分离株具有相同的IS,从而证实了该岛污染的推断历史。在中,已确定具有高可塑性的区域,包括一个富含IS相关事件的致病岛。对于所考虑的所有物种,推论出的IS的总体分布与基于SNP的系统树相一致。由于难以检测到这些转座因子,因此IS在病原体进化中的作用可能被低估了。我们在这里显示这是对生物信息学工具箱进行细菌基因组进化分析的有用补充。将有助于探索IS的功能影响,并增进我们对原核生物进化的了解。

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