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对加拿大机场废水样本进行基因组监测可实现对 SARS-CoV-2 新出现变异株的早期检测。

Genomic surveillance of Canadian airport wastewater samples allows early detection of emerging SARS-CoV-2 lineages.

机构信息

University of Waterloo, Waterloo, ON, Canada.

University of Guelph, Guelph, ON, Canada.

出版信息

Sci Rep. 2024 Nov 3;14(1):26534. doi: 10.1038/s41598-024-76925-6.

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has shown wastewater (WW) surveillance to be an effective means of tracking the emergence of viral lineages which arrive by many routes of transmission including via transportation hubs. In the Canadian province of Ontario, numerous municipal wastewater treatment plants (WWTPs) participate in WW surveillance of infectious disease targets such as SARS-CoV-2 by qPCR and whole genome sequencing (WGS). The Greater Toronto Airports Authority (GTAA), operator of Toronto Pearson International Airport (Toronto Pearson), has been participating in WW surveillance since January 2022. As a major international airport in Canada and the largest national hub, this airport is an ideal location for tracking globally emerging SARS-CoV-2 variants of concern (VOCs). In this study, WW collected from Toronto Pearson's two terminals and pooled aircraft sewage was processed for WGS using a tiled-amplicon approach targeting the SARS-CoV-2 virus genome. Data generated was analyzed to monitor trends of SARS-CoV-2 lineage frequencies. Initial detections of emerging lineages were compared between Toronto Pearson WW samples, municipal WW samples collected from the surrounding regions, and Ontario clinical data as published by Public Health Ontario. Results enabled the early detection of VOCs and individual mutations emerging in Ontario. On average, the emergence of novel lineages at the airport preceded clinical detections by 1-4 weeks, and up to 16 weeks in one case. This project illustrates the efficacy of WW surveillance at transitory transportation hubs and sets an example that could be applied to other viruses as part of a pandemic preparedness strategy and to provide monitoring on a mass scale.

摘要

严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)大流行表明,废水(WW)监测是一种有效的追踪病毒谱系出现的方法,这些病毒谱系通过多种传播途径到达,包括通过交通枢纽。在加拿大安大略省,许多城市污水处理厂(WWTP)通过 qPCR 和全基因组测序(WGS)参与对 SARS-CoV-2 等传染病目标的 WW 监测。大多伦多机场管理局(GTAA),即多伦多皮尔逊国际机场(多伦多皮尔逊)的运营商,自 2022 年 1 月以来一直参与 WW 监测。作为加拿大的主要国际机场和最大的国家枢纽,该机场是追踪全球新兴 SARS-CoV-2 关注变体(VOC)的理想地点。在这项研究中,从多伦多皮尔逊的两个航站楼收集的 WW 和飞机污水被合并,使用针对 SARS-CoV-2 病毒基因组的平铺扩增子方法进行 WGS 处理。生成的数据用于分析监测 SARS-CoV-2 谱系频率的趋势。将多伦多皮尔逊 WW 样本、从周边地区收集的市政 WW 样本以及安大略省临床数据(由安大略省公共卫生局发布)之间的新兴谱系的初始检测结果进行了比较。结果能够早期检测到在安大略省出现的 VOC 和个体突变。平均而言,机场出现新谱系的时间比临床检测提前 1-4 周,在一个案例中提前了 16 周。该项目说明了在过渡性交通枢纽进行 WW 监测的效果,并为作为大流行准备策略的一部分,对其他病毒进行大规模监测提供了范例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b92b/11532424/ce5231329d77/41598_2024_76925_Fig1_HTML.jpg

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