Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance

Xiaoqing Xu, Yu Deng, Jiahui Ding, Xiawan Zheng, Shuxian Li, Lei Liu, Ho kwong Chui, Leo L.M. Poon, Tong Zhang*

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

21 Citationer (Scopus)

Abstract

To effectively control the ongoing outbreaks of fast-spreading SARS-CoV-2 variants, there is an urgent need to add rapid variant detection and discrimination methods to the existing sewage surveillance systems established worldwide. We designed eight assays based on allele-specific RT-qPCR for real-time allelic discrimination of eight SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, Lambda, Mu, and Kappa) in sewage. In silico analysis of the designed assays for identifying SARS-CoV-2 variants using more than four million SARS-CoV-2 variant sequences yielded ∼100% specificity and >90% sensitivity. All assays could sensitively discriminate and quantify target variants at levels as low as 10 viral RNA copy/µL with minimal cross-reactivity to the corresponding nontarget genotypes, even for sewage samples containing mixtures of SARS-CoV-2 variants with differential abundances. Integration of this method into the routine sewage surveillance in Hong Kong successfully identified the Beta variant in a community sewage. Complete concordance was observed between the results of viral whole-genome sequencing and those of our novel assays in sewage samples that contained exclusively the Delta variant discharged by a clinically diagnosed COVID-19 patient living in a quarantine hotel. Our assays in this method also provided real-time discrimination of the newly emerging Omicron variant in sewage two days prior to clinical test results in another quarantine hotel in Hong Kong. These novel allelic discrimination assays offer a rapid, sensitive, and specific way for detecting multiple SARS-CoV-2 variants in sewage and can be directly integrated into the existing sewage surveillance systems.

OriginalsprogEngelsk
Artikelnummer118686
TidsskriftWater Research
Vol/bind220
ISSN0043-1354
DOI
StatusUdgivet - 15 jul. 2022
Udgivet eksterntJa

Bibliografisk note

Copyright © 2022 Elsevier Ltd. All rights reserved.

Fingeraftryk

Dyk ned i forskningsemnerne om 'Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance'. Sammen danner de et unikt fingeraftryk.

Citationsformater