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Get Free AccessWastewater-based epidemiology is now widely used in many countries for the routine monitoring of SARS-CoV-2 and other viruses at a community level. However, efficient sample processing technologies are still under investigation. In this study, we compared the performance of the novel Nanotrap® Microbiome Particles (NMP) concentration method to the commonly used polyethylene glycol (PEG) precipitation method for concentrating viruses from wastewater and their subsequent quantification and sequencing. For this, we first spiked wastewater with SARS-CoV-2, influenza and measles viruses and norovirus and found that the NMP method recovered 0.4%–21% of them depending on virus type, providing consistent and reproducible results. Using the NMP and PEG methods, we monitored SARS-CoV-2, influenza A and B viruses, RSV, enteroviruses and norovirus GI and GII and crAssphage in wastewater using quantitative PCR (qPCR)-based methods and next-generation sequencing. Good viral recoveries were observed for highly abundant viruses using both methods; however, PEG precipitation was more successful in the recovery of low-abundance viruses present in wastewater. Furthermore, samples processed with PEG precipitation were more successfully sequenced for SARS-CoV-2 than those processed with the NMP method. Virus recoveries were enhanced by high sample volumes when PEG precipitation was applied. Overall, our results suggest that the NMP concentration method is a rapid and easy virus concentration method for viral targets that are abundant in wastewater, whereas PEG precipitation may be more suited to the recovery and analysis of low-abundance viruses and for next generation sequencing.
Kata Farkas, Jessica L. Kevill, Rachel C. Williams, Igor Pântea, Nicola Ridding, Kathryn Lambert-Slosarska, Nick Woodhall, Jasmine M. S. Grimsley, Matthew J. Wade, Andrew C. Singer, Andrew J. Weightman, Gareth Cross, Davey L Jones (2024). Comparative assessment of Nanotrap and polyethylene glycol-based virus concentration in wastewater samples. FEMS Microbes, 5, DOI: 10.1093/femsmc/xtae007.
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Type
Article
Year
2024
Authors
13
Datasets
0
Total Files
0
Language
English
Journal
FEMS Microbes
DOI
10.1093/femsmc/xtae007
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