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Improving SARS-CoV-2 analyses from wastewater
University of Skövde, School of Bioscience.
2021 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Wastewater-based epidemiology (WBE) analyzes wastewater for the presence of biological and chemical substances to make public health conclusions. COVID-19 disease is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that infected individuals shed also in their feces, making WBE an alternative way to track SARS-CoV-2 in populations. There are many limitations to the detection and quantification of SARS-CoV-2 from wastewater, such as sample quality, storage conditions or viral concentration. This thesis aims to determine the extent of these limitations and the factors that contribute to them. Other viruses can help the measurements for example Bovine coronavirus (BCoV) can be spiked as a process surrogate, while Pepper mild mottle virus (PMMoV), a fecal biomarker is used to estimate the prevalence of SARS-CoV-2 infection. This study involved two distinct wastewater samples. For method comparison both samples were processed with two methods: virus concentration by electronegative (EN) filtration or direct RNA extraction method. From the RNA extracts RT-qPCR assays were performed to identify and quantify SARS-CoV-2, BCoV, and PMMoV. Based on the obtained cycle threshold (Ct) values, viral gene copy numbers and virus concentration of the original wastewater samples were calculated. Statistical tests were conducted to assess suggested hypothesizes and variations within the data. Results revealed differences in viral contents due to different sample qualities and as a result of freezing and thawing. Furthermore, different sample processing methods led to differences in quantification. In conclusion, improving analysis of SARS-CoV-2 in wastewater using methodologies with better detection efficiency leads to more reliable results.

Place, publisher, year, edition, pages
2021. , p. 42
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-20237OAI: oai:DiVA.org:his-20237DiVA, id: diva2:1579832
Subject / course
Bioscience
Educational program
Molecular Biotechnology - Master’s Programme, 60 ECTS
Supervisors
Examiners
Available from: 2021-07-12 Created: 2021-07-12 Last updated: 2021-07-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
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  • de-DE
  • en-GB
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  • nn-NO
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  • Other locale
More languages
Output format
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