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Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR
Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303066/ https://www.ncbi.nlm.nih.gov/pubmed/35872187 http://dx.doi.org/10.1016/j.scitotenv.2022.157547 |
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author | West, Nicholas W. Vasquez, Adrian A. Bahmani, Azadeh Khan, Mohammed F. Hartrick, James Turner, Carrie L. Shuster, William Ram, Jeffrey L. |
author_facet | West, Nicholas W. Vasquez, Adrian A. Bahmani, Azadeh Khan, Mohammed F. Hartrick, James Turner, Carrie L. Shuster, William Ram, Jeffrey L. |
author_sort | West, Nicholas W. |
collection | PubMed |
description | Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher. |
format | Online Article Text |
id | pubmed-9303066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93030662022-07-22 Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR West, Nicholas W. Vasquez, Adrian A. Bahmani, Azadeh Khan, Mohammed F. Hartrick, James Turner, Carrie L. Shuster, William Ram, Jeffrey L. Sci Total Environ Article Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher. Elsevier B.V. 2022-11-15 2022-07-22 /pmc/articles/PMC9303066/ /pubmed/35872187 http://dx.doi.org/10.1016/j.scitotenv.2022.157547 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article West, Nicholas W. Vasquez, Adrian A. Bahmani, Azadeh Khan, Mohammed F. Hartrick, James Turner, Carrie L. Shuster, William Ram, Jeffrey L. Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title | Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title_full | Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title_fullStr | Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title_full_unstemmed | Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title_short | Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR |
title_sort | sensitive detection of sars-cov-2 molecular markers in urban community sewersheds using automated viral rna purification and digital droplet pcr |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303066/ https://www.ncbi.nlm.nih.gov/pubmed/35872187 http://dx.doi.org/10.1016/j.scitotenv.2022.157547 |
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