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Title: Recovering coronavirus from large volumes of water
Author: Cuevas-Ferrando, Enric
Pérez-Cataluña, Alba
Allende, Ana
Guix Arnau, Susana
Randazzo, Walter
Sánchez, Gloria
Keywords: COVID-19
Aigües residuals
Issue Date: 16-Oct-2020
Publisher: Elsevier B.V.
Abstract: The need for monitoring tools to better control the ongoing coronavirus disease (COVID-19) pandemic is extremely urgent and the contamination of water resources by excreted viral particles poses alarming questions to be answered. As a first step to overcome technical limitations in monitoring SARS-CoV-2 along the water cycle, we assessed the analytical performance of a dead end hollow fiber ultrafiltration coupled to different options for secondary concentrations to concentrate viral particles from large volume of spiked tap water, seawater and surface water together with two quantitative RT-qPCR detection kits. Spiking the porcine epidemic diarrhea virus (PEDV), an enveloped virus surrogate for SARS-CoV-2, together with the mengovirus, we demonstrated that PEG-precipitation and SENS-kit better recovered PEDV (13.10 ± 0.66%) from tap water, while centrifugal filtration resulted the best option to recover mengovirus regardless of the detection kit used. No statistical significant differences were found when comparing high (10,000 ×g) and low (3500 ×g) centrifugation speeds for the secondary PEG- based concentration of spiked seawater, while considerable inhibition was observed for both viruses detected by NoInh-kit assay. Similarly, the co-concentration of PCR inhibitors and viral particles was observed in surface waters detected with either SENS-kit or NoInh-kit and RNA dilution was needed to achieve acceptable recoveries at the expenses of the overall sensitivity of the method. These methodologies represent suitable options to investigate SARS-CoV-2 occurrence in different water resources and allow to conduct on site sampling of large volume of water.
Note: Versió postprint del document publicat a:
It is part of: Science of the Total Environment, 2020, vol. 762, p. 143101
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ISSN: 0048-9697
Appears in Collections:Articles publicats en revistes (Genètica, Microbiologia i Estadística)

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