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首页> 外文期刊>Eurosurveillance >Epidemiological information is key when interpreting whole genome sequence data – lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013
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Epidemiological information is key when interpreting whole genome sequence data – lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013

机译:流行病学信息是解释整个基因组序列数据的关键-从2013年在德国沃斯坦的一次肺炎军团菌暴发中吸取的教训

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Introduction Whole genome sequencing (WGS) is increasingly used in Legionnaires’ disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella?pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L.?pneumophila . Methods : We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results : Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion : The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26?kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak.
机译:简介全基因组测序(WGS)在军团菌病(LD)暴发调查中被越来越多地使用,这是由于其分辨率比基于序列的类型分析法(嗜肺军团菌的金标准方法)在地方性菌株分析中的分辨率更高。最近,描述了一种基于1,521个核心基因的逐基因分型方法,称为核心基因组多基因座序列分型(cgMLST),可以实现嗜肺乳杆菌的可靠和标准化分型。方法:我们将这种cgMLST方案应用于迄今为止在德国报道的最大的LD爆发期间获得的分离株。在这次疫情中,已从患者和四个不同的环境源中分离出流行性克隆ST345。回顾性分类了总共42种临床和环境分离株。结果:与流行病学无关的ST345分离株与流行病克隆明显区别开。值得注意的是,流行病分离株分为两个不同的簇,即ST345-A和ST345-B,每个簇分别包含临床和流行病学相关环境样品的混合物。讨论/结论:因此,爆发可能是由环境库中预先存在的单个序列类型的两个变体引起的。这两个簇在位于ca 42和26?kb的两个相邻基因组区域中的40个等位基因不同。额外的分析支持两个区域的水平基因转移,这是造成变体之间差异的原因。两个区域均包含毒力基因,并且先前已报道其参与重组事件。这证实了在进行推断时,基因组爆发调查应始终考虑流行病学信息的观点。总体而言,事实证明,cgMLST有助于区分爆发的复杂基因组流行病学。

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