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Veneri C, Brandtner D, Mancini P, Bonanno Ferraro G, Iaconelli M, Suffredini E, Petrillo M, Leoni G, Paracchini V, Gawlik BM, Marchini A, La Rosa G. Tracking the Spread of the BA.2.86 Lineage in Italy Through Wastewater Analysis. FOOD AND ENVIRONMENTAL VIROLOGY 2024:10.1007/s12560-024-09607-1. [PMID: 38918335 DOI: 10.1007/s12560-024-09607-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 05/29/2024] [Indexed: 06/27/2024]
Abstract
The emergence of new SARS-CoV-2 variants poses challenges to global surveillance efforts, necessitating swift actions in their detection, evaluation, and management. Among the most recent variants, Omicron BA.2.86 and its sub-lineages have gained attention due to their potential immune evasion properties. This study describes the development of a digital PCR assay for the rapid detection of BA.2.86 and its descendant lineages, in wastewater samples. By using this assay, we analyzed wastewater samples collected in Italy from September 2023 to January 2024. Our analysis revealed the presence of BA.2.86 lineages already in October 2023 with a minimal detection rate of 2% which then rapidly increased, becoming dominant by January 2024, accounting for a prevalence of 62%. The findings emphasize the significance of wastewater-based surveillance in tracking emerging variants and underscore the efficacy of targeted digital PCR assays for environmental monitoring.
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Affiliation(s)
- C Veneri
- National Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - D Brandtner
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - P Mancini
- National Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - G Bonanno Ferraro
- National Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - M Iaconelli
- National Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - E Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - M Petrillo
- Seidor Italy S.r.l., 20129, Milan, Italy
| | - G Leoni
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - V Paracchini
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - B M Gawlik
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - A Marchini
- European Commission, Joint Research Centre (JRC), Geel, Belgium
| | - G La Rosa
- National Center for Water Safety (CeNSiA), Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy.
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Donker T, Papathanassopoulos A, Ghosh H, Kociurzynski R, Felder M, Grundmann H, Reuter S. Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification. Proc Natl Acad Sci U S A 2024; 121:e2314262121. [PMID: 38861609 PMCID: PMC11194495 DOI: 10.1073/pnas.2314262121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 05/01/2024] [Indexed: 06/13/2024] Open
Abstract
The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a priori assigning isolates to lineages from phylogenies, based solely on the abundance of single nucleotide polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a priori assigning isolates to lineages.
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Affiliation(s)
- Tjibbe Donker
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Alexis Papathanassopoulos
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Hiren Ghosh
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Raisa Kociurzynski
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Marius Felder
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Hajo Grundmann
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
| | - Sandra Reuter
- Institute for Infection Prevention and Control, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau79106, Germany
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Li L, Haak L, Carine M, Pagilla KR. Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics. Heliyon 2024; 10:e29462. [PMID: 38638959 PMCID: PMC11024598 DOI: 10.1016/j.heliyon.2024.e29462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/20/2024] Open
Abstract
This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends.
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Affiliation(s)
- Lin Li
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Krishna R. Pagilla
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
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Quek ZBR, Ng SH. Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology. Pathogens 2024; 13:275. [PMID: 38668230 PMCID: PMC11054155 DOI: 10.3390/pathogens13040275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 04/29/2024] Open
Abstract
High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.
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Affiliation(s)
- Z. B. Randolph Quek
- Defence Medical & Environmental Research Institute, DSO National Laboratories, Singapore 117510, Singapore
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Srikrishna D. Pentagon Found Daily, Metagenomic Detection of Novel Bioaerosol Threats to Be Cost-Prohibitive: Can Virtualization and AI Make It Cost-Effective? Health Secur 2024; 22:108-129. [PMID: 38625036 DOI: 10.1089/hs.2023.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024] Open
Abstract
In 2022, the Pentagon Force Protection Agency found threat agnostic detection of novel bioaerosol threats to be "not feasible for daily operations" due to the cost of reagents used for metagenomics, cost of sequencing instruments, and cost of labor for subject matter experts to analyze bioinformatics. Similar operational difficulties might extend to many of the 280,000 buildings (totaling 2.3 billion square feet) at 5,000 secure US Department of Defense military sites, 250 Navy ships, as well as many civilian buildings. These economic barriers can still be addressed in a threat agnostic manner by dynamically pooling samples from dry filter units, called spike-triggered virtualization, whereby pooling and sequencing depth are automatically modulated based on novel biothreats in the sequencing output. By running at a high average pooling factor, the daily and annual cost per dry filter unit can be reduced by 10 to 100 times depending on the chosen trigger thresholds. Artificial intelligence can further enhance the sensitivity of spike-triggered virtualization. The risk of infection during the 12- to 24-hour window between a bioaerosol incident and its detection remains, but in some cases it can be reduced by 80% or more with high-speed indoor air cleaning exceeding 12 air changes per hour, which is similar to the rate of air cleaning in passenger airplanes in flight. That level of air changes per hour or higher is likely to be cost-prohibitive using central heating ventilation and air conditioning systems, but it can be achieved economically by using portable air filtration in rooms with typical ceiling heights (less than 10 feet) for a cost of approximately $0.50 to $1 per square foot for do-it-yourself units and $2 to $5 per square foot for high-efficiency particulate air filters.
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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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Wadford DA, Baumrind N, Baylis EF, Bell JM, Bouchard EL, Crumpler M, Foote EM, Gilliam S, Glaser CA, Hacker JK, Ledin K, Messenger SL, Morales C, Smith EA, Sevinsky JR, Corbett-Detig RB, DeRisi J, Jacobson K. Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance. Front Public Health 2023; 11:1249614. [PMID: 37937074 PMCID: PMC10627185 DOI: 10.3389/fpubh.2023.1249614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/27/2023] [Indexed: 11/09/2023] Open
Abstract
Introduction The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or "California COVIDNet". This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. Methods California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. Results Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. Discussion Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.
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Affiliation(s)
- Debra A. Wadford
- California Department of Public Health, Richmond, CA, United States
| | - Nikki Baumrind
- California Department of Public Health, Richmond, CA, United States
| | | | - John M. Bell
- California Department of Public Health, Richmond, CA, United States
| | | | - Megan Crumpler
- Orange County Public Health Laboratory, Santa Ana, CA, United States
| | - Eric M. Foote
- California Department of Public Health, Richmond, CA, United States
| | - Sabrina Gilliam
- California Department of Public Health, Richmond, CA, United States
| | - Carol A. Glaser
- California Department of Public Health, Richmond, CA, United States
| | - Jill K. Hacker
- California Department of Public Health, Richmond, CA, United States
| | - Katya Ledin
- California Department of Public Health, Richmond, CA, United States
| | | | | | | | | | | | - Joseph DeRisi
- University of California, San Francisco, San Francisco, CA, United States
- Chan Zuckerberg Biohub, San Francisco, CA, United States
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Haver A, Theijn R, Grift ID, Raaijmakers G, Poorter E, Laros JFJ, van Dissel JT, Lodder WJ. Regional reemergence of a SARS-CoV-2 Delta lineage amid an Omicron wave detected by wastewater sequencing. Sci Rep 2023; 13:17870. [PMID: 37857658 PMCID: PMC10587120 DOI: 10.1038/s41598-023-44500-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 10/09/2023] [Indexed: 10/21/2023] Open
Abstract
The implementation and integration of wastewater-based epidemiology constitutes a valuable addition to existing pathogen surveillance systems, such as clinical surveillance for SARS-CoV-2. In the Netherlands, SARS-CoV-2 variant circulation is monitored by performing whole-genome sequencing on wastewater samples. In this manuscript, we describe the detection of an AY.43 lineage (Delta variant) amid a period of BA.5 (Omicron variant) dominance in wastewater samples from two wastewater treatment plants (WWTPs) during the months of August and September of 2022. Our results describe a temporary emergence, which was absent in samples from other WWTPs, and which coincided with peaks in viral load. We show how these lineage estimates can be traced back to lineage-specific substitution patterns. The absence of this variant from reported clinical data, but high associated viral loads suggest cryptic transmission. Our findings highlight the additional value of wastewater surveillance for generating insights into circulating pathogens.
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Affiliation(s)
- Auke Haver
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Human Genetics (HG), Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Rick Theijn
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Ivo D Grift
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Gino Raaijmakers
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Elsa Poorter
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Jeroen F J Laros
- Department of Human Genetics (HG), Leiden University Medical Center (LUMC), Leiden, The Netherlands
- Department of BioInformatics and Computational Services (BIR), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Jaap T van Dissel
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Infectious Diseases, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Willemijn J Lodder
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
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Khan M, Li L, Haak L, Payen SH, Carine M, Adhikari K, Uppal T, Hartley PD, Vasquez-Gross H, Petereit J, Verma SC, Pagilla K. Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation. One Health 2023; 16:100536. [PMID: 37041760 PMCID: PMC10074727 DOI: 10.1016/j.onehlt.2023.100536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/13/2023] Open
Abstract
Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.
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Affiliation(s)
- Majid Khan
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Lin Li
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Shannon Harger Payen
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Kabita Adhikari
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Timsy Uppal
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Paul D. Hartley
- Nevada Genomics Center, University of Nevada, Reno, NV 89557, USA
| | - Hans Vasquez-Gross
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Juli Petereit
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Subhash C. Verma
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Krishna Pagilla
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
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