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- Publisher Website: 10.1016/j.watres.2022.118686
- WOS: WOS:000810317900001
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Article: Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance
Title | Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance |
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Authors | |
Issue Date | 2022 |
Citation | Water Research, 2022, v. 220, p. 118686 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/314246 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Xu, X | - |
dc.contributor.author | Deng, Y | - |
dc.contributor.author | Ding, J | - |
dc.contributor.author | Zheng, X | - |
dc.contributor.author | Li, S | - |
dc.contributor.author | Liu, L | - |
dc.contributor.author | Chui, HO-KWONG | - |
dc.contributor.author | Poon, LML | - |
dc.contributor.author | Zhang, T | - |
dc.date.accessioned | 2022-07-18T06:14:29Z | - |
dc.date.available | 2022-07-18T06:14:29Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Water Research, 2022, v. 220, p. 118686 | - |
dc.identifier.uri | http://hdl.handle.net/10722/314246 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Water Research | - |
dc.title | Real-time allelic assays of SARS-CoV-2 variants to enhance sewage surveillance | - |
dc.type | Article | - |
dc.identifier.email | Deng, Y: dengyu@hku.hk | - |
dc.identifier.email | Liu, L: liuleice@hku.hk | - |
dc.identifier.email | Poon, LML: llmpoon@hkucc.hku.hk | - |
dc.identifier.email | Zhang, T: zhangt@hkucc.hku.hk | - |
dc.identifier.authority | Deng, Y=rp02795 | - |
dc.identifier.authority | Poon, LML=rp00484 | - |
dc.identifier.authority | Zhang, T=rp00211 | - |
dc.identifier.doi | 10.1016/j.watres.2022.118686 | - |
dc.identifier.hkuros | 334335 | - |
dc.identifier.volume | 220 | - |
dc.identifier.spage | 118686 | - |
dc.identifier.epage | 118686 | - |
dc.identifier.isi | WOS:000810317900001 | - |