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牛津纳米孔公司 2024 年用于爆发检测和来源归因的测序技术:进展和克隆特异性挑战。

Oxford Nanopore's 2024 sequencing technology for outbreak detection and source attribution: progress and clone-specific challenges.

机构信息

Institute for Food Safety and Hygiene, University of Zurich, Zurich, Switzerland.

National Reference Center for Enteropathogenic Bacteria and Listeria (NENT), Zurich, Switzerland.

出版信息

J Clin Microbiol. 2024 Nov 13;62(11):e0108324. doi: 10.1128/jcm.01083-24. Epub 2024 Oct 4.

Abstract

Whole genome sequencing is an essential cornerstone of pathogen surveillance and outbreak detection. Established sequencing technologies are currently being challenged by Oxford Nanopore Technologies (ONT), which offers an accessible and cost-effective alternative enabling gap-free assemblies of chromosomes and plasmids. Limited accuracy has hindered its use for investigating pathogen transmission, but recent technology updates have brought significant improvements. To evaluate its readiness for outbreak detection, we selected 78 isolates from diverse lineages or known epidemiological clusters for sequencing with ONT's V14 Rapid Barcoding Kit and R10.4.1 flow cells. The most accurate of several tested workflows generated assemblies with a median of one error (SNP or indel) per assembly. For 66 isolates, the cgMLST profiles from ONT-only assemblies were identical to those generated from Illumina data. Eight assemblies were of lower quality, with more than 20 erroneous sites each, primarily caused by methylations at the GAAGAC motif (5'-GAAGC-3'/5'-GTTTC-3'). This led to inaccurate clustering, failing to group isolates from a persistence-associated clone that carried the responsible restriction-modification system. Out of 50 methylation motifs detected among the 78 isolates, only the GAAGAC motif was linked to substantially increased error rates. Our study shows that most genomes assembled from ONT-only data are suitable for high-resolution genotyping, but further improvements of chemistries or basecallers are required for reliable routine use in outbreak and food safety investigations.

摘要

全基因组测序是病原体监测和疫情检测的重要基石。现有的测序技术正受到牛津纳米孔技术(ONT)的挑战,后者提供了一种易于使用且具有成本效益的替代方案,能够实现染色体和质粒的无间隙组装。其有限的准确性阻碍了其在病原体传播研究中的应用,但最近的技术更新带来了显著的改进。为了评估其在疫情检测中的准备情况,我们选择了来自不同谱系或已知流行病学集群的 78 个分离株,使用 ONT 的 V14 快速条形码试剂盒和 R10.4.1 流池进行测序。经过测试的几种工作流程中,最准确的一种生成的组装体平均每个组装体有一个错误(SNP 或插入缺失)。对于 66 个分离株,ONT 仅组装的 cgMLST 图谱与从 Illumina 数据生成的图谱相同。八个组装体的质量较低,每个组装体都有超过 20 个错误位点,主要是由于 GAAGAC 基序(5'-GAAGC-3'/5'-GTTTC-3')的甲基化引起的。这导致聚类不准确,无法将携带相关限制修饰系统的持久性相关克隆的分离株进行分组。在 78 个分离株中检测到的 50 个甲基化基序中,只有 GAAGAC 基序与显著增加的错误率有关。我们的研究表明,大多数仅从 ONT 数据组装的基因组适用于高分辨率基因分型,但需要进一步改进化学物质或碱基调用器,以确保在疫情和食品安全调查中可靠地常规使用。

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