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Lou EG, Sapoval N, McCall C, Bauhs L, Carlson-Stadler R, Kalvapalle P, Lai Y, Palmer K, Penn R, Rich W, Wolken M, Brown P, Ensor KB, Hopkins L, Treangen TJ, Stadler LB. Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022. [PMID: 35395314 DOI: 10.2139/ssrn.4022373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.
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Affiliation(s)
- Esther G Lou
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Nicolae Sapoval
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Lauren Bauhs
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Russell Carlson-Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Prashant Kalvapalle
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Yanlai Lai
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Kyle Palmer
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Ryker Penn
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Whitney Rich
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Madeline Wolken
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Pamela Brown
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Katherine B Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX 77005, United States of America
| | - Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America; Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX 77005, United States of America
| | - Todd J Treangen
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America.
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Lou EG, Sapoval N, McCall C, Bauhs L, Carlson-Stadler R, Kalvapalle P, Lai Y, Palmer K, Penn R, Rich W, Wolken M, Brown P, Ensor KB, Hopkins L, Treangen TJ, Stadler LB. Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 833:155059. [PMID: 35395314 PMCID: PMC8983075 DOI: 10.1016/j.scitotenv.2022.155059] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/31/2022] [Accepted: 04/01/2022] [Indexed: 05/14/2023]
Abstract
Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.
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Affiliation(s)
- Esther G Lou
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Nicolae Sapoval
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Lauren Bauhs
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Russell Carlson-Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Prashant Kalvapalle
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Yanlai Lai
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Kyle Palmer
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Ryker Penn
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Whitney Rich
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Madeline Wolken
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America
| | - Pamela Brown
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America
| | - Katherine B Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX 77005, United States of America
| | - Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054, United States of America; Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX 77005, United States of America
| | - Todd J Treangen
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, United States of America
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, MS 519, Houston, TX 77005, United States of America.
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Jahn K, Dreifuss D, Topolsky I, Kull A, Ganesanandamoorthy P, Fernandez-Cassi X, Bänziger C, Devaux AJ, Stachler E, Caduff L, Cariti F, Corzón AT, Fuhrmann L, Chen C, Jablonski KP, Nadeau S, Feldkamp M, Beisel C, Aquino C, Stadler T, Ort C, Kohn T, Julian TR, Beerenwinkel N. Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC. Nat Microbiol 2022. [PMID: 35851854 DOI: 10.1101/2021.01.08.21249379] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.
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Affiliation(s)
- Katharina Jahn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Anina Kull
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | | | - Xavier Fernandez-Cassi
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carola Bänziger
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Alexander J Devaux
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Elyse Stachler
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Lea Caduff
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Federica Cariti
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Alex Tuñas Corzón
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sarah Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mirjam Feldkamp
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Catharine Aquino
- Functional Genomics Center Zurich, ETH Zurich, Zurich, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Christoph Ort
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Tamar Kohn
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Timothy R Julian
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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