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- Publisher Website: 10.1016/j.scitotenv.2022.153687
- WOS: WOS:000764890800018
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Article: Comparison of virus concentration methods and RNA extraction methods for SARS-CoV-2 wastewater surveillance
Title | Comparison of virus concentration methods and RNA extraction methods for SARS-CoV-2 wastewater surveillance |
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Authors | |
Issue Date | 2022 |
Citation | Science of The Total Environment, 2022, v. 824, p. 153687 How to Cite? |
Abstract | Wastewater surveillance is a promising tool for population-level monitoring of the spread of infectious diseases, such as the coronavirus disease 2019 (COVID-19). Different from clinical specimens, viruses in community-scale wastewater samples need to be concentrated before detection because viral RNA is highly diluted. The present study evaluated eleven different virus concentration methods for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. First, eight concentration methods of different principles were compared using spiked wastewater at a starting volume of 30 mL. Ultracentrifugation was the most effective method with a viral recovery efficiency of 25 ± 6%. The second-best option, AlCl3 precipitation method, yielded a lower recovery efficiency, only approximately half that of the ultracentrifugation method. Second, the potential of increasing method sensitivity was explored using three concentration methods starting with a larger volume of 1000 mL. Although ultracentrifugation using a large volume outperformed the other two large-volume methods, it only yielded a comparable method sensitivity as the ultracentrifugation using a small volume (30 mL). Thus, ultracentrifugation using less volume of wastewater is more preferable considering the sample processing throughput. Third, a comparison of two viral RNA extraction methods showed that the lysis-buffer-based extraction method resulted in higher viral recovery efficiencies, with cycle threshold (Ct) values 0.9-4.2 lower than those obtained for the acid-guanidinium-phenol-based method using spiked samples. These results were further confirmed by using positive wastewater samples concentrated by ultracentrifugation and extracted separately by the two viral RNA extraction methods. In summary, concentration using ultracentrifugation followed by the lysis buffer-based extraction method enables sensitive and robust detection of SARS-CoV-2 for wastewater surveillance. |
Persistent Identifier | http://hdl.handle.net/10722/314237 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zheng, X | - |
dc.contributor.author | Deng, Y | - |
dc.contributor.author | Xu, X | - |
dc.contributor.author | Li, S | - |
dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Ding, J | - |
dc.contributor.author | On, HY | - |
dc.contributor.author | Lai, JCC | - |
dc.contributor.author | Yau, CY | - |
dc.contributor.author | Chin, WH | - |
dc.contributor.author | Poon, LML | - |
dc.contributor.author | Tun, HM | - |
dc.contributor.author | Zhang, T | - |
dc.date.accessioned | 2022-07-18T06:14:18Z | - |
dc.date.available | 2022-07-18T06:14:18Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Science of The Total Environment, 2022, v. 824, p. 153687 | - |
dc.identifier.uri | http://hdl.handle.net/10722/314237 | - |
dc.description.abstract | Wastewater surveillance is a promising tool for population-level monitoring of the spread of infectious diseases, such as the coronavirus disease 2019 (COVID-19). Different from clinical specimens, viruses in community-scale wastewater samples need to be concentrated before detection because viral RNA is highly diluted. The present study evaluated eleven different virus concentration methods for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. First, eight concentration methods of different principles were compared using spiked wastewater at a starting volume of 30 mL. Ultracentrifugation was the most effective method with a viral recovery efficiency of 25 ± 6%. The second-best option, AlCl3 precipitation method, yielded a lower recovery efficiency, only approximately half that of the ultracentrifugation method. Second, the potential of increasing method sensitivity was explored using three concentration methods starting with a larger volume of 1000 mL. Although ultracentrifugation using a large volume outperformed the other two large-volume methods, it only yielded a comparable method sensitivity as the ultracentrifugation using a small volume (30 mL). Thus, ultracentrifugation using less volume of wastewater is more preferable considering the sample processing throughput. Third, a comparison of two viral RNA extraction methods showed that the lysis-buffer-based extraction method resulted in higher viral recovery efficiencies, with cycle threshold (Ct) values 0.9-4.2 lower than those obtained for the acid-guanidinium-phenol-based method using spiked samples. These results were further confirmed by using positive wastewater samples concentrated by ultracentrifugation and extracted separately by the two viral RNA extraction methods. In summary, concentration using ultracentrifugation followed by the lysis buffer-based extraction method enables sensitive and robust detection of SARS-CoV-2 for wastewater surveillance. | - |
dc.language | eng | - |
dc.relation.ispartof | Science of The Total Environment | - |
dc.title | Comparison of virus concentration methods and RNA extraction methods for SARS-CoV-2 wastewater surveillance | - |
dc.type | Article | - |
dc.identifier.email | Deng, Y: dengyu@hku.hk | - |
dc.identifier.email | Zhang, Y: zhangsia@hku.hk | - |
dc.identifier.email | Yau, CY: tansyy@hku.hk | - |
dc.identifier.email | Chin, WH: alexchin@hku.hk | - |
dc.identifier.email | Poon, LML: llmpoon@hkucc.hku.hk | - |
dc.identifier.email | Tun, HM: heinmtun@hku.hk | - |
dc.identifier.email | Zhang, T: zhangt@hkucc.hku.hk | - |
dc.identifier.authority | Deng, Y=rp02795 | - |
dc.identifier.authority | Chin, WH=rp02345 | - |
dc.identifier.authority | Poon, LML=rp00484 | - |
dc.identifier.authority | Tun, HM=rp02389 | - |
dc.identifier.authority | Zhang, T=rp00211 | - |
dc.identifier.doi | 10.1016/j.scitotenv.2022.153687 | - |
dc.identifier.hkuros | 334263 | - |
dc.identifier.volume | 824 | - |
dc.identifier.spage | 153687 | - |
dc.identifier.epage | 153687 | - |
dc.identifier.isi | WOS:000764890800018 | - |