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Philo SE, Zhou NA, Lillis LM, Raghava V, Abraham D, Kumar V, Kumar N, Rigby J, Harrison JC, Fagnant-Sperati CS, Kossik AL, Ong AQW, Swanstrom R, Burnor E, Demeke B, Beck NK, Shirai JH, Libby SJ, Boyle DS, Feasey N, Kang G, Meschke JS. Development, confirmation, and application of a seeded Escherichia coli process control organism to validate Salmonella enterica serovar Typhi environmental surveillance methods. PLoS One 2024; 19:e0301624. [PMID: 38713678 DOI: 10.1371/journal.pone.0301624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 03/19/2024] [Indexed: 05/09/2024] Open
Abstract
Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of Typhoid fever. Blood culture is the gold standard for clinical diagnosis, but this is often difficult to employ in resource limited settings. Environmental surveillance of waste-impacted waters is a promising supplement to clinical surveillance, however validating methods is challenging in regions where S. Typhi concentrations are low. To evaluate existing S. Typhi environmental surveillance methods, a novel process control organism (PCO) was created as a biosafe surrogate. Using a previous described qPCR assay, a modified PCR amplicon for the staG gene was cloned into E. coli. We developed a target region that was recognized by the Typhoid primers in addition to a non-coding internal probe sequence. A multiplex qPCR reaction was developed that differentiates between the typhoid and control targets, with no cross-reactivity or inhibition of the two probes. The PCO was shown to mimic S. Typhi in lab-based experiments with concentration methods using primary wastewater: filter cartridge, recirculating Moore swabs, membrane filtration, and differential centrifugation. Across all methods, the PCO seeded at 10 CFU/mL and 100 CFU/mL was detected in 100% of replicates. The PCO is detected at similar quantification cycle (Cq) values across all methods at 10 CFU/mL (Average = 32.4, STDEV = 1.62). The PCO was also seeded into wastewater at collection sites in Vellore (India) and Blantyre (Malawi) where S. Typhi is endemic. All methods tested in both countries were positive for the seeded PCO. The PCO is an effective way to validate performance of environmental surveillance methods targeting S. Typhi in surface water.
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Affiliation(s)
- Sarah E Philo
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Nicolette A Zhou
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | | | | | | | - Vinoth Kumar
- Christian Medical College Vellore, Vellore, India
| | - Nirmal Kumar
- Christian Medical College Vellore, Vellore, India
| | - Jonathan Rigby
- Malawi Liverpool Wellcome Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Joanna Ciol Harrison
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Christine S Fagnant-Sperati
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Alexandra L Kossik
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Angelo Q W Ong
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Rachael Swanstrom
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Elisabeth Burnor
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Bethel Demeke
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Nicola K Beck
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Jeffry H Shirai
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
| | - Stephen J Libby
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, United States of America
| | | | - Nicholas Feasey
- Malawi Liverpool Wellcome Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | | | - John Scott Meschke
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
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2
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Holm RH, Rempala GA, Choi B, Brick JM, Amraotkar AR, Keith RJ, Rouchka EC, Chariker JH, Palmer KE, Smith T, Bhatnagar A. Dynamic SARS-CoV-2 surveillance model combining seroprevalence and wastewater concentrations for post-vaccine disease burden estimates. COMMUNICATIONS MEDICINE 2024; 4:70. [PMID: 38594350 PMCID: PMC11004132 DOI: 10.1038/s43856-024-00494-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 03/28/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Despite wide scale assessments, it remains unclear how large-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. METHODS We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible ( S ), vaccinated ( V ), variant-specific infected (I 1 andI 2 ), recovered ( R ), and seropositive ( T ) model ( S V I 2 R T ) tracked prevalence longitudinally. This was related to wastewater concentration. RESULTS Here we show the 64% county vaccination rate translate into about a 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence is a 24-fold increase of infection counts, which correspond to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration have the strongest correlation (r = 0.95) at 1 week lag. CONCLUSIONS Our study underscores the importance of continuing environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.
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Grants
- P20 GM103436 NIGMS NIH HHS
- This study was supported by Centers for Disease Control and Prevention (75D30121C10273), Louisville Metro Government, James Graham Brown Foundation, Owsley Brown II Family Foundation, Welch Family, Jewish Heritage Fund for Excellence, the National Institutes of Health, (P20GM103436), the Rockefeller Foundation, the National Sciences Foundation (DMS-2027001), and the Basic Science Research Program National Research Foundation of Korea (NRF) (RS-2023-00245056).
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Affiliation(s)
- Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Grzegorz A Rempala
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA
| | - Boseung Choi
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA
- Division of Big Data Science, Korea University, Sejong, South Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon, South Korea
| | | | - Alok R Amraotkar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Rachel J Keith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Eric C Rouchka
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
- KY INBRE Bioinformatics Core, University of Louisville, Louisville, KY, 40202, USA
| | - Julia H Chariker
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
- KY INBRE Bioinformatics Core, University of Louisville, Louisville, KY, 40202, USA
| | - Kenneth E Palmer
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY, 40202, USA
- Department of Pharmacology and Toxicology, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, 40202, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, 40202, USA.
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3
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Anderson LB, Ness HD, Holm RH, Smith T. Wastewater-Informed Digital Advertising as a COVID-19 Geotargeted Neighborhood Intervention: Jefferson County, Kentucky, 2021-2022. Am J Public Health 2024; 114:34-37. [PMID: 37856730 PMCID: PMC10726935 DOI: 10.2105/ajph.2023.307439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/04/2023] [Indexed: 10/21/2023]
Abstract
We sought to deliver a geotargeted digital health advertising intervention. We assessed risk of community infection through an integrated public health and wastewater rubric and delivered advertisements between November 2021 and April 2022 in Louisville, Kentucky. The average daily click-through rates for the campaigns were 0.19%, 0.15%, and 0.13%. Results show potential for digital public health interventions that are geographically anchored to subcity sewersheds and community interest and willingness to engage with targeted wastewater-themed public health messaging. (Am J Public Health. 2024;114(1):34-37. https://doi.org/10.2105/AJPH.2023.307439).
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Affiliation(s)
- Lauren B Anderson
- Lauren B. Anderson, Heather D. Ness, Rochelle H. Holm, and Ted Smith are with the Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY. L. B. Anderson is also with the Department of Urban and Public Affairs, College of Arts and Sciences, University of Louisville. H. D. Ness is also with the Department of Health Promotion and Behavioral Sciences, School of Public Health and Information Sciences, University of Louisville
| | - Heather D Ness
- Lauren B. Anderson, Heather D. Ness, Rochelle H. Holm, and Ted Smith are with the Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY. L. B. Anderson is also with the Department of Urban and Public Affairs, College of Arts and Sciences, University of Louisville. H. D. Ness is also with the Department of Health Promotion and Behavioral Sciences, School of Public Health and Information Sciences, University of Louisville
| | - Rochelle H Holm
- Lauren B. Anderson, Heather D. Ness, Rochelle H. Holm, and Ted Smith are with the Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY. L. B. Anderson is also with the Department of Urban and Public Affairs, College of Arts and Sciences, University of Louisville. H. D. Ness is also with the Department of Health Promotion and Behavioral Sciences, School of Public Health and Information Sciences, University of Louisville
| | - Ted Smith
- Lauren B. Anderson, Heather D. Ness, Rochelle H. Holm, and Ted Smith are with the Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY. L. B. Anderson is also with the Department of Urban and Public Affairs, College of Arts and Sciences, University of Louisville. H. D. Ness is also with the Department of Health Promotion and Behavioral Sciences, School of Public Health and Information Sciences, University of Louisville
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4
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Klaassen F, Holm RH, Smith T, Cohen T, Bhatnagar A, Menzies NA. Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky. ENVIRONMENTAL RESEARCH 2024; 240:117395. [PMID: 37838198 PMCID: PMC10863376 DOI: 10.1016/j.envres.2023.117395] [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] [Received: 06/15/2023] [Revised: 09/29/2023] [Accepted: 10/11/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. METHODS We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. FINDINGS Adding wastewater data minimally improved the predictive performance of nowcasts compared to a model fitted to case and death data (Weighted Interval Score (WIS) 0.208 versus 0.223), and reduced the predictive performance compared to a model fitted to deaths data (WIS 0.517 versus 0.500). Adding wastewater data to deaths data improved the nowcasts agreement to estimates from models using cases and deaths data. These findings were consistent across individual sewersheds as well as for models fit to the aggregated total data of 5 sewersheds. Retrospective reconstructions of epidemiological dynamics created using different combinations of data were in general agreement (coverage >75%). INTERPRETATION These findings show wastewater data may be valuable for infectious disease nowcasting when clinical surveillance data are absent, such as early in a pandemic or in low-resource settings where systematic collection of epidemiologic data is difficult.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA.
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5
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Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. JOURNAL OF WATER AND HEALTH 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
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Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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6
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Holm RH, Rempala G, Choi B, Brick JM, Amraotkar A, Keith R, Rouchka EC, Chariker JH, Palmer K, Smith TR, Bhatnagar A. Wastewater and seroprevalence for pandemic preparedness: variant analysis, vaccination effect, and hospitalization forecasting for SARS-CoV-2, in Jefferson County, Kentucky. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.06.23284260. [PMID: 36656780 PMCID: PMC9844017 DOI: 10.1101/2023.01.06.23284260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Despite wide scale assessments, it remains unclear how large-scale SARS-CoV-2 vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible (S), vaccinated (V), variant-specific infected (I_1 and I_2), recovered (R), and seropositive (T) model (SVI_2 RT) tracked prevalence longitudinally. This was related to wastewater concentration. The 64% county vaccination rate translated into about 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence was a 24-fold increase of infection counts, which corresponded to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration had the strongest correlation (r = 0.95) at 1 week lag. Our study underscores the importance of continued environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.
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7
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Fontenele RS, Yang Y, Driver EM, Magge A, Kraberger S, Custer JM, Dufault-Thompson K, Cox E, Newell ME, Varsani A, Halden RU, Scotch M, Jiang X. Wastewater surveillance uncovers regional diversity and dynamics of SARS-CoV-2 variants across nine states in the USA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162862. [PMID: 36933724 PMCID: PMC10017378 DOI: 10.1016/j.scitotenv.2023.162862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 05/06/2023]
Abstract
Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.
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Affiliation(s)
- Rafaela S Fontenele
- National Library of Medicine, National Institute of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Yiyan Yang
- National Library of Medicine, National Institute of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Erin M Driver
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA
| | - Arjun Magge
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA
| | - Simona Kraberger
- The Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ 85287, USA
| | - Joy M Custer
- The Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ 85287, USA
| | - Keith Dufault-Thompson
- National Library of Medicine, National Institute of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Erin Cox
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA
| | - Melanie Engstrom Newell
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA
| | - Arvind Varsani
- The Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ 85287, USA; School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA; Center of Evolution and Medicine, Arizona State University, Tempe, AZ 85287, USA
| | - Rolf U Halden
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA; School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, USA; OneWaterOneHealth, Nonprofit Project of the Arizona State University Foundation, Tempe, AZ 85287, USA
| | - Matthew Scotch
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA; College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA
| | - Xiaofang Jiang
- National Library of Medicine, National Institute of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
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Smith T, Holm RH, Keith RJ, Amraotkar AR, Alvarado CR, Banecki K, Choi B, Santisteban IC, Bushau-Sprinkle AM, Kitterman KT, Fuqua J, Hamorsky KT, Palmer KE, Brick JM, Rempala GA, Bhatnagar A. Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158567. [PMID: 36084773 PMCID: PMC9444845 DOI: 10.1016/j.scitotenv.2022.158567] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/07/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.
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Affiliation(s)
- Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Rachel J Keith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Alok R Amraotkar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Chance R Alvarado
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
| | - Krzysztof Banecki
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Boseung Choi
- Division of Big Data Science, Korea University, Sejong, South Korea; Biomedical Mathematics Group, Institute for Basic Science, Daejeon, South Korea
| | - Ian C Santisteban
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA
| | - Adrienne M Bushau-Sprinkle
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Kathleen T Kitterman
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA
| | - Joshua Fuqua
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Pharmacology and Toxicology, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Krystal T Hamorsky
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Kenneth E Palmer
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Pharmacology and Toxicology, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | | | - Grzegorz A Rempala
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA.
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9
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Amman F, Markt R, Endler L, Hupfauf S, Agerer B, Schedl A, Richter L, Zechmeister M, Bicher M, Heiler G, Triska P, Thornton M, Penz T, Senekowitsch M, Laine J, Keszei Z, Klimek P, Nägele F, Mayr M, Daleiden B, Steinlechner M, Niederstätter H, Heidinger P, Rauch W, Scheffknecht C, Vogl G, Weichlinger G, Wagner AO, Slipko K, Masseron A, Radu E, Allerberger F, Popper N, Bock C, Schmid D, Oberacher H, Kreuzinger N, Insam H, Bergthaler A. Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale. Nat Biotechnol 2022; 40:1814-1822. [PMID: 35851376 DOI: 10.1038/s41587-022-01387-y] [Citation(s) in RCA: 74] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 06/07/2022] [Indexed: 01/14/2023]
Abstract
SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.
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Affiliation(s)
- Fabian Amman
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Rudolf Markt
- Department of Microbiology, Universität Innsbruck, Innsbruck, Austria
| | - Lukas Endler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Sebastian Hupfauf
- Department of Microbiology, Universität Innsbruck, Innsbruck, Austria
| | - Benedikt Agerer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Anna Schedl
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Lukas Richter
- Austrian Agency for Health and Food Safety (AGES), Vienna, Austria
| | | | - Martin Bicher
- dwh GmbH, Vienna, Austria.,Institute for Information Systems Engineering, Technische Universität Wien, Vienna, Austria
| | - Georg Heiler
- Complexity Science Hub, Vienna, Austria.,Institute of Information Systems Engineering, Technische Universität Wien, Vienna, Austria
| | - Petr Triska
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Matthew Thornton
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria
| | - Thomas Penz
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Martin Senekowitsch
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Jan Laine
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Zsofia Keszei
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Peter Klimek
- Complexity Science Hub, Vienna, Austria.,Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria
| | - Fabiana Nägele
- Department of Microbiology, Universität Innsbruck, Innsbruck, Austria
| | - Markus Mayr
- Department of Microbiology, Universität Innsbruck, Innsbruck, Austria
| | - Beatrice Daleiden
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria
| | - Martin Steinlechner
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria
| | - Harald Niederstätter
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria
| | - Petra Heidinger
- Austrian Centre of Industrial Biotechnology GmbH, Graz, Austria
| | - Wolfgang Rauch
- Department of Infrastructure, Universität Innsbruck, Innsbruck, Austria
| | | | - Gunther Vogl
- Institut für Lebensmittelsicherheit, Veterinärmedizin und Umwelt des Landes Kärnten, Klagenfurt am Wörthersee, Austria
| | - Günther Weichlinger
- Abteilung 12 - Wasserwirtschaft, Amt der Kärntner Landesregierung, Klagenfurt am Wörthersee, Austria
| | | | - Katarzyna Slipko
- Institute for Water Quality and Resource Management, Technische Universität Wien, Vienna, Austria
| | - Amandine Masseron
- Institute for Water Quality and Resource Management, Technische Universität Wien, Vienna, Austria
| | - Elena Radu
- Institute for Water Quality and Resource Management, Technische Universität Wien, Vienna, Austria.,Ştefan S. Nicolau Institute of Virology, Bucharest, Romania
| | | | - Niki Popper
- dwh GmbH, Vienna, Austria.,Institute for Information Systems Engineering, Technische Universität Wien, Vienna, Austria
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Daniela Schmid
- Austrian Agency for Health and Food Safety (AGES), Vienna, Austria
| | - Herbert Oberacher
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria
| | - Norbert Kreuzinger
- Institute for Water Quality and Resource Management, Technische Universität Wien, Vienna, Austria
| | - Heribert Insam
- Department of Microbiology, Universität Innsbruck, Innsbruck, Austria
| | - Andreas Bergthaler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria.
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10
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Smith T, Holm RH, Yeager R, Moore JB, Rouchka EC, Sokoloski KJ, Elliott EM, Talley D, Arora V, Moyer S, Bhatnagar A. Combining Community Wastewater Genomic Surveillance with State Clinical Surveillance: A Framework for SARS-CoV-2 Public Health Practice. FOOD AND ENVIRONMENTAL VIROLOGY 2022; 14:410-416. [PMID: 35982363 PMCID: PMC9387882 DOI: 10.1007/s12560-022-09531-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 05/31/2022] [Indexed: 05/16/2023]
Abstract
This study aimed to develop a framework for combining community wastewater surveillance with state clinical surveillance for the confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants within the community and to provide recommendations on how to expand on such research and apply the findings in public health responses. Wastewater samples were collected weekly from 17 geographically resolved locations in Louisville/Jefferson County, Kentucky (USA), from February 10 to December 13, 2021. Genomic surveillance and quantitative reverse transcription PCR (RT-qPCR) platforms were used to screen for SARS-CoV-2 in wastewater, and state clinical surveillance was used for confirmation. The study results highlighted an increased epidemiological value of combining community wastewater genomic surveillance and RT-qPCR with conventional case-auditing methods. The spatial scale and temporal frequency of wastewater sampling provided promising sensitivity and specificity for gaining public health screening insights about SARS-CoV-2 emergence, seeding, and spread in communities. Improved national surveillance systems are needed against future pathogens and variants, and wastewater-based genomic surveillance exhibits great potential when coupled with clinical testing. This paper presents evidence that complementary wastewater and clinical testing are cost-effectively enhanced when used in combination, as they provide a strong tool for a joint public health framework. Future pathogens of interest may be examined in either a targeted fashion or using a more global approach where all pathogens are monitored. This study has also provided novel insights developed from evidence-based public health practices.
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Affiliation(s)
- Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA.
| | - Ray Yeager
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA
- Center for Integrative Environmental Health Sciences, School of Medicine, University of Louisville, 500 S. Preston St., Louisville, KY, 40202, USA
| | - Joseph B Moore
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA
- Diabetes and Obesity Center, School of Medicine, University of Louisville, 580 S. Preston St., Louisville, KY, 40202, USA
| | - Eric C Rouchka
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, 319 Abraham Flexner Way, Louisville, KY, 40202, USA
| | - Kevin J Sokoloski
- Department of Microbiology and Immunology, School of Medicine, University of Louisville, 505 S. Hancock St., Louisville, KY, 40202, USA
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, 505 S. Hancock St., Louisville, KY, 40202, USA
| | - Erin M Elliott
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA
- Diabetes and Obesity Center, School of Medicine, University of Louisville, 580 S. Preston St., Louisville, KY, 40202, USA
| | - Daymond Talley
- Morris Forman Water Quality Treatment Center, Louisville/Jefferson County Metropolitan Sewer District, 4522 Algonquin Parkway, Louisville, KY, 40211, USA
| | - Vaneet Arora
- Division of Laboratory Services, Kentucky Department for Public Health, 100 Sower Blvd., Suite 204, Frankfort, KY, 40601, USA
- Department of Pathology and Laboratory Medicine, University of Kentucky, 800 Rose St., Lexington, KY, 40536, USA
| | - Sarah Moyer
- Department of Health Management and System Sciences, School of Public Health and Information Sciences, University of Louisville, 485 E. Gray St., Louisville, KY, 40202, USA
- Department of Public Health and Wellness, Louisville-Jefferson County Metro Government, 400 E. Gray St., Louisville, KY, 40202, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY, 40202, USA
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11
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Sovic MG, Savona F, Bohrerova Z, Faith SA. MixviR: an R Package for Exploring Variation Associated with Genomic Sequence Data from Environmental SARS-CoV-2 and Other Mixed Microbial Samples. Appl Environ Microbiol 2022; 88:e0087422. [PMID: 36286480 PMCID: PMC9680627 DOI: 10.1128/aem.00874-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 09/19/2022] [Indexed: 11/29/2022] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/coronavirus disease 2019 (COVID-19) pandemic has highlighted an important role for efficient surveillance of microbial pathogens. High-throughput sequencing technologies provide valuable surveillance tools, offering opportunities to conduct high-resolution monitoring from diverse sample types, including from environmental sources. However, given their large size and potential to contain mixtures of lineages within samples, such genomic data sets can present challenges for analyzing the data and communicating results with diverse stakeholders. Here, we report MixviR, an R package for exploring, analyzing, and visualizing genomic data from potentially mixed samples of a target microbial group. MixviR characterizes variation at both the nucleotide and amino acid levels and offers the RShiny interactive dashboard for exploring data. We demonstrate MixviR's utility with validation studies using mixtures of known lineages from both SARS-CoV-2 and Mycobacterium tuberculosis and with a case study analyzing lineages of SARS-CoV-2 in wastewater samples over time at a sampling location in Ohio, USA. IMPORTANCE High-throughput sequencing technologies hold great potential for contributing to genomic-based surveillance of microbial diversity from environmental samples. However, the size of the data sets, along with the potential for environmental samples to contain multiple evolutionary lineages of interest, present challenges around analyzing and effectively communicating inferences from these data sets. The software described here provides a novel and valuable tool for exploring such data. Though originally designed and used for monitoring SARS-CoV-2 lineages in wastewater, it can also be applied to analyses of genomic diversity in other microbial groups.
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Affiliation(s)
- Michael G. Sovic
- Center For Applied Plant Sciences, The Ohio State University, Columbus, Ohio, USA
| | - Francesca Savona
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, USA
| | - Zuzana Bohrerova
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA
- Ohio Water Resources Center, The Ohio State University, Columbus, Ohio, USA
| | - Seth A. Faith
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, USA
- Center of Microbiome Science, The Ohio State University, Columbus, Ohio, USA
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12
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The Detection of Periodic Reemergence Events of SARS-CoV-2 Delta Strain in Communities Dominated by Omicron. Pathogens 2022; 11:pathogens11111249. [PMID: 36365000 PMCID: PMC9697103 DOI: 10.3390/pathogens11111249] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/14/2022] [Accepted: 10/24/2022] [Indexed: 12/01/2022] Open
Abstract
Despite entering an endemic phase, SARS-CoV-2 remains a significant burden to public health across the global community. Wastewater sampling has consistently proven utility to understanding SARS-CoV-2 prevalence trends and genetic variation as it represents a less biased assessment of the corresponding communities. Here, we report that ongoing monitoring of SARS-CoV-2 genetic variation in samples obtained from the wastewatersheds of the city of Louisville in Jefferson county Kentucky has revealed the periodic reemergence of the Delta strain in the presence of the presumed dominant Omicron strain. Unlike previous SARS-CoV-2 waves/emergence events, the Delta reemergence events were geographically restricted in the community and failed to spread into other areas as determined by wastewater analyses. Moreover, the reemergence of the Delta strain did not correlate with vaccination rates as communities with lower relative vaccination have been, to date, not affected. Importantly, Delta reemergence events correlate with increased public health burdens, as indicated by increased daily case rates and mortality relative to non-Delta wastewatershed communities. While the underlying reasons for the reemergence of the Delta variant remain unclear, these data reaffirm the ongoing importance of wastewater genomic analyses towards understanding SARS-CoV-2 as it enters the endemic phase.
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13
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Tamáš M, Potocarova A, Konecna B, Klucar Ľ, Mackulak T. Wastewater Sequencing-An Innovative Method for Variant Monitoring of SARS-CoV-2 in Populations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:9749. [PMID: 35955106 PMCID: PMC9367975 DOI: 10.3390/ijerph19159749] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 07/28/2022] [Accepted: 07/29/2022] [Indexed: 05/14/2023]
Abstract
The SARS-CoV-2 outbreak has already affected more than 555 million people, and 6.3 million people have died. Due to its high infectivity, it is crucial to track SARS-CoV-2 outbreaks early to prevent the spread of infection. Wastewater monitoring appears to be a powerful and effective tool for managing epidemiological situations. Due to emerging mutations of SARS-CoV-2, there is a need to monitor mutations in order to control the pandemic. Since the sequencing of randomly chosen individuals is time-consuming and expensive, sequencing of wastewater plays an important role in revealing the dynamics of infection in a population. The sampling method used is a crucial factor and significantly impacts the results. Wastewater can be collected as a grab sample or as a 24 h composite sample. Another essential factor is the sample volume, as is the method of transport used. This review discusses different pretreatment procedures and RNA extraction, which may be performed using various methods, such as column-based extraction, TRIzol, or magnetic extraction. Each of the methods has its advantages and disadvantages, which are described accordingly. RT-qPCR is a procedure that confirms the presence of SARS-CoV-2 genes before sequencing. This review provides an overview of currently used methods for preparing wastewater samples, from sampling to sequencing.
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Affiliation(s)
- Michal Tamáš
- Department of Environmental Engineering, Institute of Chemical and Environmental Engineering, Faculty of Chemical and Food Technology, Slovak University of Technology, Radinského 9, 81237 Bratislava, Slovakia
- Institute of Physiology, Faculty of Medicine, Comenius University in Bratislava, 81372 Bratislava, Slovakia
| | - Alena Potocarova
- Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University in Bratislava, Sasinkova 4, 81108 Bratislava, Slovakia
| | - Barbora Konecna
- Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University in Bratislava, Sasinkova 4, 81108 Bratislava, Slovakia
| | - Ľubos Klucar
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská Cesta 21, 84551 Bratislava, Slovakia
| | - Tomas Mackulak
- Department of Environmental Engineering, Institute of Chemical and Environmental Engineering, Faculty of Chemical and Food Technology, Slovak University of Technology, Radinského 9, 81237 Bratislava, Slovakia
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14
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Barbé L, Schaeffer J, Besnard A, Jousse S, Wurtzer S, Moulin L, Le Guyader FS, Desdouits M. SARS-CoV-2 Whole-Genome Sequencing Using Oxford Nanopore Technology for Variant Monitoring in Wastewaters. Front Microbiol 2022; 13:889811. [PMID: 35756003 PMCID: PMC9218694 DOI: 10.3389/fmicb.2022.889811] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 03/29/2022] [Indexed: 01/21/2023] Open
Abstract
Since the beginning of the Coronavirus Disease-19 (COVID-19) pandemic, multiple Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mutations have been reported and led to the emergence of variants of concern (VOC) with increased transmissibility, virulence or immune escape. In parallel, the observation of viral fecal shedding led to the quantification of SARS-CoV-2 genomes in wastewater, providing information about the dynamics of SARS-CoV-2 infections within a population including symptomatic and asymptomatic individuals. Here, we aimed to adapt a sequencing technique initially designed for clinical samples to apply it to the challenging and mixed wastewater matrix, and hence identify the circulation of VOC at the community level. Composite raw sewage sampled over 24 h in two wastewater-treatment plants (WWTPs) from a city in western France were collected weekly and SARS-CoV-2 quantified by RT-PCR. Samples collected between October 2020 and May 2021 were submitted to whole-genome sequencing (WGS) using the primers and protocol published by the ARTIC Network and a MinION Mk1C sequencer (Oxford Nanopore Technologies, Oxford, United Kingdom). The protocol was adapted to allow near-full genome coverage from sewage samples, starting from ∼5% to reach ∼90% at depth 30. This enabled us to detect multiple single-nucleotide variant (SNV) and assess the circulation of the SARS-CoV-2 VOC Alpha, Beta, Gamma, and Delta. Retrospective analysis of sewage samples shed light on the emergence of the Alpha VOC with detection of first co-occurring signature mutations in mid-November 2020 to reach predominance of this variant in early February 2021. In parallel, a mutation-specific qRT-PCR assay confirmed the spread of the Alpha VOC but detected it later than WGS. Altogether, these data show that SARS-CoV-2 sequencing in sewage can be used for early detection of an emerging VOC in a population and confirm its ability to track shifts in variant predominance.
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Affiliation(s)
- Laure Barbé
- Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France
| | - Julien Schaeffer
- Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France
| | - Alban Besnard
- Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France
| | - Sarah Jousse
- Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France
| | | | - Laurent Moulin
- R&D Laboratory, DRDQE, Eau de Paris, Ivry-sur-Seine, France
| | | | | | - Marion Desdouits
- Laboratoire de Microbiologie (LSEM, Unité MASAE), IFREMER, Nantes, France
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