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Ahmed W, Smith WJM, Metcalfe S, Jackson G, Choi PM, Morrison M, Field D, Gyawali P, Bivins A, Bibby K, Simpson SL. Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater. ACS ES&T WATER 2022; 2:1871-1880. [PMID: 36380768 PMCID: PMC8848507 DOI: 10.1021/acsestwater.1c00387] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.
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Affiliation(s)
- Warish Ahmed
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Wendy J. M. Smith
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Suzanne Metcalfe
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Greg Jackson
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Phil M. Choi
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Mary Morrison
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Daniel Field
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Pradip Gyawali
- Institute
of Environmental Science and Research Ltd. (ESR), Porirua 5240, New Zealand
| | - Aaron Bivins
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Kyle Bibby
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
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Krivoňáková N, Šoltýsová A, Tamáš M, Takáč Z, Krahulec J, Ficek A, Gál M, Gall M, Fehér M, Krivjanská A, Horáková I, Belišová N, Bímová P, Škulcová AB, Mackuľak T. Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology. Sci Rep 2021; 11:19456. [PMID: 34593871 PMCID: PMC8484274 DOI: 10.1038/s41598-021-98653-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 09/09/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerges to scientific research and monitoring of wastewaters to predict the spread of the virus in the community. Our study investigated the COVID-19 disease in Bratislava, based on wastewater monitoring from September 2020 until March 2021. Samples were analyzed from two wastewater treatment plants of the city with reaching 0.6 million monitored inhabitants. Obtained results from the wastewater analysis suggest significant statistical dependence. High correlations between the number of viral particles in wastewater and the number of reported positive nasopharyngeal RT-qPCR tests of infected individuals with a time lag of 2 weeks/12 days (R2 = 83.78%/R2 = 52.65%) as well as with a reported number of death cases with a time lag of 4 weeks/27 days (R2 = 83.21%/R2 = 61.89%) was observed. The obtained results and subsequent mathematical modeling will serve in the future as an early warning system for the occurrence of a local site of infection and, at the same time, predict the load on the health system up to two weeks in advance.
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Affiliation(s)
- Naďa Krivoňáková
- Institute of Information Engineering, Automation, and Mathematics, Department of Mathematics, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovakia
| | - Andrea Šoltýsová
- Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Ilkovičova 6, 842 15, Bratislava, Slovakia
- Institute for Clinical and Translational Research, Biomedical Research Center, Slovak Academy of Sciences, Dúbravska Cesta 9, 84505, Bratislava, Slovakia
| | - Michal Tamáš
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic.
| | - Zdenko Takáč
- Institute of Information Engineering, Automation, and Mathematics, Department of Mathematics, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovakia
| | - Ján Krahulec
- Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Ilkovičova 6, 842 15, Bratislava, Slovakia
| | - Andrej Ficek
- Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Ilkovičova 6, 842 15, Bratislava, Slovakia
| | - Miroslav Gál
- Department of Inorganic Technology, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovakia
| | - Marián Gall
- Institute of Information Engineering, Automation, and Mathematics, Department of Mathematics, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovakia
| | - Miroslav Fehér
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Anna Krivjanská
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Ivana Horáková
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Noemi Belišová
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Paula Bímová
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Andrea Butor Škulcová
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
| | - Tomáš Mackuľak
- Department of Environmental Engineering, Faculty of Chemistry and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37, Bratislava, Slovak Republic
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