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Title:Evaluation of methods and processes for robust monitoring of SARS-CoV-2 in wastewater
Authors:ID Maksimović, Olivera (Author)
ID Lengar, Živa (Author)
ID Kogej Zwitter, Zala (Author)
ID Bačnik, Katarina (Author)
ID Bajde, Irena (Author)
ID Milavec, Mojca (Author)
ID Županič, Anže (Author)
ID Mehle, Nataša (Author)
ID Kutnjak, Denis (Author)
ID Ravnikar, Maja (Author)
ID Gutiérrez-Aguirre, Ion (Author)
Files:URL URL - Source URL, visit https://link.springer.com/article/10.1007/s12560-022-09533-0
 
.pdf PDF - Presentation file, download (1,32 MB)
MD5: DE49AA11C9A1134C49C9787FF19F93D4
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo NIB - National Institute of Biology
Abstract:The SARS-CoV-2 pandemic has accelerated the development of virus concentration and molecular-based virus detection methods, monitoring systems and overall approach to epidemiology. Early into the pandemic, wastewater-based epidemiology started to be employed as a tool for tracking the virus transmission dynamics in a given area. The complexity of wastewater coupled with a lack of standardized methods led us to evaluate each step of the analysis individually and see which approach gave the most robust results for SARS-CoV-2 monitoring in wastewater. In this article, we present a step-by-step, retrospective view on the method development and implementation for the case of a pilot monitoring performed in Slovenia. We specifically address points regarding the thermal stability of the samples during storage, screening for the appropriate sample concentration and RNA extraction procedures and real-time PCR assay selection. Here, we show that the temperature and duration of the storage of the wastewater sample can have a varying impact on the detection depending on the structural form in which the SARS-CoV-2 target is present. We found that concentration and RNA extraction using Centricon filtration units coupled with Qiagen RNA extraction kit or direct RNA capture and extraction using semi-automated kit from Promega give the most optimal results out of the seven methods tested. Lastly, we confirm the use of N1 and N2 assays developed by the CDC (USA) as the best performing assays among four tested in combination with Fast Virus 1-mastermix. Data show a realistic overall process for method implementation as well as provide valuable information in regards to how different approaches in the analysis compare to one another under the specific conditions present in Slovenia during a pilot monitoring running from the beginning of the pandemic.
Keywords:waste water, method evolution, virus detection, SARS-CoV-2
Publication status:Published
Publication version:Version of Record
Publication date:23.08.2022
Year of publishing:2022
Number of pages:str. 384-400
Numbering:Vol. 14
PID:20.500.12556/DiRROS-19431 New window
UDC:579
ISSN on article:1867-0334
DOI:10.1007/s12560-022-09533-0 New window
COBISS.SI-ID:119616515 New window
Publication date in DiRROS:17.07.2024
Views:124
Downloads:107
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Record is a part of a journal

Title:Food and environmental virology
Shortened title:Food environ. virol.
Publisher:Springer
ISSN:1867-0334
COBISS.SI-ID:4144248 New window

Document is financed by a project

Funder:EC - European Commission
Project number:813542
Name:Innovative Network for Next Generation Training and Sequencing of Virome
Acronym:INEXTVIR

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P4-0407-2019
Name:Okoljska in aplikativna virologija: virusi, prijatelji in sovražniki

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:L4-3179-2021
Name:Odkrivanje in z vodo povezana epidemiologija porajajočih se tobamovirusov, ki okužujejo kmetijske rastline

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:odpadna voda, SARS-Cov-2, razvoj metode, zaznavanje virusa


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