Suppr超能文献

用于对比比利时嗜肺军团菌疫情分离株分型的全基因组测序分型工具

Comparison of whole genome sequencing typing tools for the typing of Belgian Legionella pneumophila outbreaks isolates.

作者信息

Echahidi Fedoua, Park Subin, Meghraoui Alaeddine, Crombé Florence, Soetens Oriane, Piérard Denis, Prevost Benoit, Wybo Ingrid, Michel Charlotte

机构信息

Department of Microbiology and Infection Control, National Reference Centre for Legionella Pneumophila, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090, Brussels, Belgium.

Association of Public Health Laboratories (APHL), Silver Spring, MD, 20910, USA.

出版信息

Eur J Clin Microbiol Infect Dis. 2025 Mar;44(3):597-607. doi: 10.1007/s10096-024-05013-4. Epub 2024 Dec 21.

Abstract

Whole genome sequencing (WGS) marks a turning point for outbreak investigations for microorganisms related to public health matters, like Legionella pneumophila (Lp). Here, we evaluated the available Lp WGS typing tools for isolates of previously documented Belgian outbreaks, as well as small groups of related and non-related isolates. One reference strain and 77 clinical and environmental isolates were evaluated. Seven isolates belong to a Sequence Type (ST) 36 outbreak in 1999 and sixteen (ten clinical, two matching environmental and four non-related controls) belong to another ST1 outbreak in 1985-1987. The remaining isolates belong to small groups of related and non-related isolates of diverse ST's. WGS was performed and data were analysed using whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) with "Ridom SeqSphere + " (cgMLST), "Applied Maths-Bionumerics" (wgMLST) and the 50 loci cgMLST (CDC/ESGLI_ESCMID). Results of the three tools were concordant with the traditional Sequence Based Typing (SBT). The known outbreaks and small clusters could be detected and clear discrimination of ST1 non-related isolates was obtained. In addition, the 50 loci cgMLST allowed to classify the isolates into subtypes because almost all the 50 genes could be called in all the analysed isolates, which was not achieved by the other tools. This is a big advantage in terms of standardisation and comparison between laboratories for future epidemiological investigations. WGS allowed to analyse a large volume of samples and generated more accurate conclusions for outbreak investigations compared to other typing methods due to its higher discriminatory power and throughput.

摘要

全基因组测序(WGS)标志着与公共卫生事务相关的微生物(如嗜肺军团菌(Lp))爆发调查的一个转折点。在此,我们评估了现有的Lp WGS分型工具,用于之前记录的比利时疫情分离株,以及一小群相关和不相关的分离株。评估了1株参考菌株和77株临床及环境分离株。7株分离株属于1999年的序列型(ST)36疫情,16株(10株临床、2株匹配的环境和4株不相关对照)属于1985 - 1987年的另一次ST1疫情。其余分离株属于不同ST的相关和不相关分离株的小群体。进行了全基因组测序,并使用“Ridom SeqSphere + ”(cgMLST)、“Applied Maths - Bionumerics”(wgMLST)和50个位点的cgMLST(CDC/ESGLI_ESCMID)通过全基因组(wg)和核心基因组(cg)多位点序列分型(MLST)对数据进行分析。三种工具的结果与传统的基于序列的分型(SBT)一致。可以检测到已知的疫情和小簇,并对ST1不相关分离株进行清晰区分。此外,50个位点的cgMLST能够将分离株分类为亚型,因为几乎所有50个基因都可以在所有分析的分离株中检测到,而其他工具无法做到这一点。这在未来流行病学调查的实验室标准化和比较方面是一个很大的优势。与其他分型方法相比,WGS能够分析大量样本,并因其更高的鉴别力和通量为爆发调查得出更准确的结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/041b/11880184/b0a89fcafa27/10096_2024_5013_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验