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Community-level SARS-CoV-2 sequence diversity revealed by wastewater sampling.
Swift, Candice L; Isanovic, Mirza; Correa Velez, Karlen E; Norman, R Sean.
  • Swift CL; Department of Environmental Health Sciences, University of South Carolina, USA.
  • Isanovic M; Department of Environmental Health Sciences, University of South Carolina, USA.
  • Correa Velez KE; Department of Environmental Health Sciences, University of South Carolina, USA.
  • Norman RS; Department of Environmental Health Sciences, University of South Carolina, USA. Electronic address: rsnorman@sc.edu.
Sci Total Environ ; 801: 149691, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1364458
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis) S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Wastewater / COVID-19 Type of study: Prognostic study Topics: Variants Limits: Humans Language: English Journal: Sci Total Environ Year: 2021 Document Type: Article Affiliation country: J.scitotenv.2021.149691

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Wastewater / COVID-19 Type of study: Prognostic study Topics: Variants Limits: Humans Language: English Journal: Sci Total Environ Year: 2021 Document Type: Article Affiliation country: J.scitotenv.2021.149691