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Digital PCR: A Partitioning-Based Application for Detection and Surveillance of SARS-CoV-2 from Sewage Samples

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2967))

Abstract

The wastewater-based surveillance of SARS-CoV-2 has emerged as a potential tool for cost-effective, simple, and long-term monitoring of the pandemic. Since the COVID-19 pandemic, several developed countries have incorporated the national wastewater surveillance program into their national policies related to pandemic management. Various research groups have utilized the approach of real-time quantitative reverse transcription PCR (RT-qPCR) for the quantification of SARS-CoV-2 from environmental samples like sewage water. However, detection and quantification using RT-qPCR relies on standards and is known to have lesser tolerance to inhibitors present in the sample. Unlike RT-qPCR, digital PCR (dPCR) offers an absolute and sensitive quantification without a need reference and offers higher tolerance to inhibitors present in the wastewater samples. Additionally, the accuracy of detection increases with the presence of rare target copies in the sample. The methodology herein presented comprises the detection and quantification of SARS-CoV-2 from sewer shed samples using the dPCR approach. The main features of the process include virus concentration and absolute quantification of the virus surpassing the substantial presence of inhibitors in the sample. This chapter presents the optimized PEG and NaCl-based protocol for virus concentration followed by nucleic acid extraction and quantification using CDC-approved N1 + N2 assay. The protocol uses MS2 bacteriophage as a process recovery or internal control.

The methodology herein described highlights the importance of digital PCR technologies for environmental surveillance of important emerging pathogens or pandemics.

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Acknowledgments

The authors are grateful to Ahmedabad Municipal Corporation (AMC) for providing the permission for sample collection from different sewage treatment plants. We acknowledge SERB, DST, GOI and DST, GoG for financial support for research study.

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Correspondence to Madhvi Joshi .

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Prajapati, B., Rathore, D., Joshi, C., Joshi, M. (2023). Digital PCR: A Partitioning-Based Application for Detection and Surveillance of SARS-CoV-2 from Sewage Samples. In: Domingues, L. (eds) PCR. Methods in Molecular Biology, vol 2967. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3358-8_1

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  • DOI: https://doi.org/10.1007/978-1-0716-3358-8_1

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3357-1

  • Online ISBN: 978-1-0716-3358-8

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