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使用牛津纳米孔技术进行严重急性呼吸综合征冠状病毒2全基因组测序以监测废水中的变异株

SARS-CoV-2 Whole-Genome Sequencing Using Oxford Nanopore Technology for Variant Monitoring in Wastewaters.

作者信息

Barbé Laure, Schaeffer Julien, Besnard Alban, Jousse Sarah, Wurtzer Sébastien, Moulin Laurent, Le Guyader Françoise S, Desdouits Marion

机构信息

Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France.

R&D Laboratory, DRDQE, Eau de Paris, Ivry-sur-Seine, France.

出版信息

Front Microbiol. 2022 Jun 9;13:889811. doi: 10.3389/fmicb.2022.889811. eCollection 2022.

DOI:10.3389/fmicb.2022.889811
PMID:35756003
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9218694/
Abstract

Since the beginning of the Coronavirus Disease-19 (COVID-19) pandemic, multiple Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mutations have been reported and led to the emergence of variants of concern (VOC) with increased transmissibility, virulence or immune escape. In parallel, the observation of viral fecal shedding led to the quantification of SARS-CoV-2 genomes in wastewater, providing information about the dynamics of SARS-CoV-2 infections within a population including symptomatic and asymptomatic individuals. Here, we aimed to adapt a sequencing technique initially designed for clinical samples to apply it to the challenging and mixed wastewater matrix, and hence identify the circulation of VOC at the community level. Composite raw sewage sampled over 24 h in two wastewater-treatment plants (WWTPs) from a city in western France were collected weekly and SARS-CoV-2 quantified by RT-PCR. Samples collected between October 2020 and May 2021 were submitted to whole-genome sequencing (WGS) using the primers and protocol published by the ARTIC Network and a MinION Mk1C sequencer (Oxford Nanopore Technologies, Oxford, United Kingdom). The protocol was adapted to allow near-full genome coverage from sewage samples, starting from ∼5% to reach ∼90% at depth 30. This enabled us to detect multiple single-nucleotide variant (SNV) and assess the circulation of the SARS-CoV-2 VOC Alpha, Beta, Gamma, and Delta. Retrospective analysis of sewage samples shed light on the emergence of the Alpha VOC with detection of first co-occurring signature mutations in mid-November 2020 to reach predominance of this variant in early February 2021. In parallel, a mutation-specific qRT-PCR assay confirmed the spread of the Alpha VOC but detected it later than WGS. Altogether, these data show that SARS-CoV-2 sequencing in sewage can be used for early detection of an emerging VOC in a population and confirm its ability to track shifts in variant predominance.

摘要

自新型冠状病毒肺炎(COVID-19)大流行开始以来,已报告了多种严重急性呼吸综合征冠状病毒2(SARS-CoV-2)突变,并导致出现了具有更高传播性、毒力或免疫逃逸能力的关注变异株(VOC)。与此同时,对病毒粪便排毒的观察使得能够对废水中的SARS-CoV-2基因组进行定量,从而提供有关人群中SARS-CoV-2感染动态的信息,包括有症状和无症状个体。在此,我们旨在调整一种最初为临床样本设计的测序技术,以将其应用于具有挑战性的混合废水基质,从而在社区层面识别VOC的传播情况。每周收集法国西部一个城市的两个污水处理厂(WWTP)在24小时内采集的混合原污水,并通过RT-PCR对SARS-CoV-2进行定量。2020年10月至2021年5月期间收集的样本使用ARTIC网络发布的引物和方案以及MinION Mk1C测序仪(英国牛津纳米孔技术公司)进行全基因组测序(WGS)。该方案经过调整,以实现污水样本的近全基因组覆盖,起始覆盖率约为5%,在深度30时达到约90%。这使我们能够检测到多个单核苷酸变异(SNV),并评估SARS-CoV-2 VOC Alpha、Beta、Gamma和Delta的传播情况。对污水样本的回顾性分析揭示了Alpha VOC的出现,2020年11月中旬首次检测到同时出现的标志性突变,到2021年2月初该变异株占主导地位。与此同时,一种针对突变的qRT-PCR检测方法证实了Alpha VOC的传播,但比WGS检测到的时间晚。总之,这些数据表明,污水中的SARS-CoV-2测序可用于早期检测人群中新兴的VOC,并证实其跟踪变异株优势变化的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/95ad3ff08368/fmicb-13-889811-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/a5ffb763b8ff/fmicb-13-889811-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/83c9b606ee75/fmicb-13-889811-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/95ad3ff08368/fmicb-13-889811-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/16298a95cffb/fmicb-13-889811-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/f48ecf771ef0/fmicb-13-889811-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/78afd0599b96/fmicb-13-889811-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/0de1cf604997/fmicb-13-889811-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3725/9218694/95ad3ff08368/fmicb-13-889811-g007.jpg

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