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Sutcliffe SG, Kraemer SA, Ellmen I, Knapp JJ, Overton AK, Nash D, Nissimov JI, Charles TC, Dreifuss D, Topolsky I, Baykal PI, Fuhrmann L, Jablonski KP, Beerenwinkel N, Levy JI, Olabode AS, Becker DG, Gugan G, Brintnell E, Poon AF, Valieris R, Drummond RD, Defelicibus A, Dias-Neto E, Rosales RA, Tojal da Silva I, Orfanou A, Psomopoulos F, Pechlivanis N, Pipes L, Chen Z, Baaijens JA, Baym M, Shapiro BJ. Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data. Microb Genom 2024; 10:001249. [PMID: 38785221 PMCID: PMC11165662 DOI: 10.1099/mgen.0.001249] [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: 02/21/2024] [Accepted: 04/18/2024] [Indexed: 05/25/2024] Open
Abstract
Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.
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Affiliation(s)
- Steven G. Sutcliffe
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Susanne A. Kraemer
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
- Environment and Climate Change Canada, Montreal, QC, Canada
| | - Isaac Ellmen
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | | | | | - Delaney Nash
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | | | | | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Pelin I. Baykal
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Kim P. Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Joshua I. Levy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Abayomi S. Olabode
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Devan G. Becker
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Gopi Gugan
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Erin Brintnell
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Art F.Y. Poon
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Renan Valieris
- Computational Biology, A.C. Camargo Cancer Center, São Paulo, SP, Brazil
| | | | | | | | | | | | - Aspasia Orfanou
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Fotis Psomopoulos
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Nikolaos Pechlivanis
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Lenore Pipes
- Department of Integrative Biology, University of California, Berkeley, CA, USA
| | - Zihao Chen
- School of Mathematical Sciences, Peking University, Beijing, BJ, PR China
| | - Jasmijn A. Baaijens
- Delft University of Technology, Delft, ZH, Netherlands
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Michael Baym
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - B. Jesse Shapiro
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
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Zhuang X, Vo V, Moshi MA, Dhede K, Ghani N, Akbar S, Chang CL, Young AK, Buttery E, Bendik W, Zhang H, Afzal S, Moser D, Cordes D, Lockett C, Gerrity D, Kan HY, Oh EC. Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.18.24306052. [PMID: 38699326 PMCID: PMC11065002 DOI: 10.1101/2024.04.18.24306052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.
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Lataretu M, Drechsel O, Kmiecinski R, Trappe K, Hölzer M, Fuchs S. Lessons learned: overcoming common challenges in reconstructing the SARS-CoV-2 genome from short-read sequencing data via CoVpipe2. F1000Res 2024; 12:1091. [PMID: 38716230 PMCID: PMC11074694 DOI: 10.12688/f1000research.136683.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Background Accurate genome sequences form the basis for genomic surveillance programs, the added value of which was impressively demonstrated during the COVID-19 pandemic by tracing transmission chains, discovering new viral lineages and mutations, and assessing them for infectiousness and resistance to available treatments. Amplicon strategies employing Illumina sequencing have become widely established for variant detection and reference-based reconstruction of SARS-CoV-2 genomes, and are routine bioinformatics tasks. Yet, specific challenges arise when analyzing amplicon data, for example, when crucial and even lineage-determining mutations occur near primer sites. Methods We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. Besides fundamental tasks like quality control, mapping, variant calling, and consensus generation, we also implemented additional features to ease the detection of mixed samples and recombinants. Results We highlight common pitfalls in primer clipping, detecting heterozygote variants, and dealing with low-coverage regions and deletions. We introduce CoVpipe2 to address the above challenges and have compared and successfully validated the pipeline against selected publicly available benchmark datasets. CoVpipe2 features high usability, reproducibility, and a modular design that specifically addresses the characteristics of short-read amplicon protocols but can also be used for whole-genome short-read sequencing data. Conclusions CoVpipe2 has seen multiple improvement cycles and is continuously maintained alongside frequently updated primer schemes and new developments in the scientific community. Our pipeline is easy to set up and use and can serve as a blueprint for other pathogens in the future due to its flexibility and modularity, providing a long-term perspective for continuous support. CoVpipe2 is written in Nextflow and is freely accessible from \href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2} under the GPL3 license.
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Affiliation(s)
- Marie Lataretu
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Oliver Drechsel
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - René Kmiecinski
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Kathrin Trappe
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Martin Hölzer
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Stephan Fuchs
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
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4
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Reis AC, Pinto D, Monteiro S, Santos R, Martins JV, Sousa A, Páscoa R, Lourinho R, Cunha MV. Systematic SARS-CoV-2 S-gene sequencing in wastewater samples enables early lineage detection and uncovers rare mutations in Portugal. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 921:170961. [PMID: 38367735 DOI: 10.1016/j.scitotenv.2024.170961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/23/2023] [Accepted: 02/11/2024] [Indexed: 02/19/2024]
Abstract
As the COVID-19 pandemic reached its peak, many countries implemented genomic surveillance systems to track the evolution and transmission of SARS-CoV-2. Transition from the pandemic to the endemic phase prioritized alternative testing strategies to maintain effective epidemic surveillance at the population level, with less intensive sequencing efforts. One such promising approach was Wastewater-Based Surveillance (WBS), which offers non-invasive, cost-effective means for analysing virus trends at the sewershed level. From 2020 onwards, wastewater has been recognized as an instrumental source of information for public health, with national and international authorities exploring options to implement national wastewater surveillance systems and increasingly relying on WBS as early warning of potential pathogen outbreaks. In Portugal, several pioneer projects joined the academia, water utilities and Public Administration around WBS. To validate WBS as an effective genomic surveillance strategy, it is crucial to collect long term performance data. In this work, we present one year of systematic SARS-CoV-2 wastewater surveillance in Portugal, representing 35 % of the mainland population. We employed two complementary methods for lineage determination - allelic discrimination by RT-PCR and S-gene sequencing. This combination allowed us to monitor variant evolution in near-real-time and identify low-frequency mutations. Over the course of this year-long study, spanning from May 2022 to April 2023, we successfully tracked the dominant Omicron sub-lineages, their progression and evolution, which aligned with concurrent clinical surveillance data. Our results underscore the effectiveness of WBS as a tracking system for virus variants, with the ability to unveil mutations undetected via massive sequencing of clinical samples from Portugal, demonstrating the ability of WBS to uncover new mutations and detect rare genetic variants. Our findings emphasize that knowledge of the genetic diversity of SARS-CoV-2 at the population level can be extended far beyond via the combination of routine clinical genomic surveillance with wastewater sequencing and genotyping.
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Affiliation(s)
- Ana C Reis
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Daniela Pinto
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Sílvia Monteiro
- Laboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; CERIS - Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; DECN - Department of Nuclear Sciences and Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | - Ricardo Santos
- Laboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; CERIS - Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; DECN - Department of Nuclear Sciences and Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | | | | | | | | | - Mónica V Cunha
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
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5
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Álvarez-Herrera M, Sevilla J, Ruiz-Rodriguez P, Vergara A, Vila J, Cano-Jiménez P, González-Candelas F, Comas I, Coscollá M. VIPERA: Viral Intra-Patient Evolution Reporting and Analysis. Virus Evol 2024; 10:veae018. [PMID: 38510921 PMCID: PMC10953798 DOI: 10.1093/ve/veae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/02/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024] Open
Abstract
Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.
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Affiliation(s)
- Miguel Álvarez-Herrera
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Jordi Sevilla
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Paula Ruiz-Rodriguez
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Andrea Vergara
- Department of Clinical Microbiology, CDB, Hospital Clínic of Barcelona; University of Barcelona; ISGlobal, C. de Villarroel, 170, Barcelona 08007, Spain
- CIBER of Infectious Diseases (CIBERINFEC), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Jordi Vila
- Department of Clinical Microbiology, CDB, Hospital Clínic of Barcelona; University of Barcelona; ISGlobal, C. de Villarroel, 170, Barcelona 08007, Spain
- CIBER of Infectious Diseases (CIBERINFEC), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Pablo Cano-Jiménez
- Institute of Biomedicine of Valencia (IBV-CSIC), C/ Jaime Roig, 11, Valencia 46010, Spain
| | - Fernando González-Candelas
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Iñaki Comas
- Institute of Biomedicine of Valencia (IBV-CSIC), C/ Jaime Roig, 11, Valencia 46010, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Mireia Coscollá
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
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Pipek OA, Medgyes-Horváth A, Stéger J, Papp K, Visontai D, Koopmans M, Nieuwenhuijse D, Oude Munnink BB, Csabai I. Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples. Nat Commun 2024; 15:517. [PMID: 38225254 PMCID: PMC10789779 DOI: 10.1038/s41467-023-43391-z] [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: 07/11/2023] [Accepted: 11/06/2023] [Indexed: 01/17/2024] Open
Abstract
Systematic monitoring of SARS-CoV-2 co-infections between different lineages and assessing the risk of intra-host recombinant emergence are crucial for forecasting viral evolution. Here we present a comprehensive analysis of more than 2 million SARS-CoV-2 raw read datasets submitted to the European COVID-19 Data Portal to identify co-infections and intra-host recombination. Co-infection was observed in 0.35% of the investigated cases. Two independent procedures were implemented to detect intra-host recombination. We show that sensitivity is predominantly determined by the density of lineage-defining mutations along the genome, thus we used an expanded list of mutually exclusive defining mutations of specific variant combinations to increase statistical power. We call attention to multiple challenges rendering recombinant detection difficult and provide guidelines for the reduction of false positives arising from chimeric sequences produced during PCR amplification. Additionally, we identify three recombination hotspots of Delta - Omicron BA.1 intra-host recombinants.
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Affiliation(s)
- Orsolya Anna Pipek
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary
| | - Anna Medgyes-Horváth
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary.
| | - József Stéger
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary
| | - Krisztián Papp
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary
| | - Dávid Visontai
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary
| | - Marion Koopmans
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, Netherlands
| | - David Nieuwenhuijse
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Bas B Oude Munnink
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, Netherlands
| | - István Csabai
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány P. s. 1A, Budapest, 1117, Hungary
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7
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Anand A, Long C, Chandran K. NYC metropolitan wastewater reveals links between SARS-CoV-2 amino acid mutations and disease outcomes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:167971. [PMID: 37914132 DOI: 10.1016/j.scitotenv.2023.167971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 10/01/2023] [Accepted: 10/18/2023] [Indexed: 11/03/2023]
Abstract
Since late 2020, diverse SARS-CoV-2 variants with enhanced infectivity and transmissibility have emerged. In contrast to the focus on amino acid mutations in the spike protein, mutations in non-spike proteins and their associated impacts remain relatively understudied. New York City metropolitan wastewater revealed over 60 % of the most frequently occurring amino acid mutations in regions outside the spike protein. Strikingly, ~50 % of the mutations detected herein remain uncharacterized for functional impacts. Our results suggest that there are several understudied mutations within non-spike proteins N, ORF1a, ORF1b, ORF9b, and ORF9c, that could increase transmissibility, and infectivity among human populations. We also demonstrate significant correlations of P314L, D614G, T95I, G50E, G50R, G204R, R203K, G662S, P10S, and P13L with documented mortality rates, hospitalization rates, and percent positivity suggesting that amino acid mutations are likely to be indicators of COVID-19 infection outcomes.
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Affiliation(s)
- Archana Anand
- Department of Earth and Environmental Engineering, Columbia University, 500 West 120th Street, New York, NY 10027, United States of America
| | - Chenghua Long
- Department of Earth and Environmental Engineering, Columbia University, 500 W. 120th Street, New York, NY 10027, United States of America
| | - Kartik Chandran
- Department of Earth and Environmental Engineering, Columbia University, 500 W. 120th Street, New York, NY 10027, United States of America.
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8
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Rajput V, Pramanik R, Malik V, Yadav R, Samson R, Kadam P, Bhalerao U, Tupekar M, Deshpande D, Shah P, Shashidhara LS, Boargaonkar R, Patil D, Kale S, Bhalerao A, Jain N, Kamble S, Dastager S, Karmodiya K, Dharne M. Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:118976-118988. [PMID: 37922087 DOI: 10.1007/s11356-023-30709-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/23/2023] [Indexed: 11/05/2023]
Abstract
The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (~28%), BA.1.X (1.0-72%), BA.2 (1.0-18%), BA.2.X (1.0-97.4%) BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-21.83%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.
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Affiliation(s)
- Vinay Rajput
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India
| | - Rinka Pramanik
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India
| | - Vinita Malik
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
| | - Rakeshkumar Yadav
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India
| | - Rachel Samson
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India
| | - Pradnya Kadam
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
| | - Unnati Bhalerao
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
| | - Manisha Tupekar
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
| | - Dipti Deshpande
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
| | - Priyanki Shah
- The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University (SPPU), Pune, Maharashtra, India
| | - L S Shashidhara
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
- The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University (SPPU), Pune, Maharashtra, India
| | | | - Dhawal Patil
- Ecosan Services Foundation (ESF), Pune, Maharashtra, 411030, India
| | - Saurabh Kale
- Ecosan Services Foundation (ESF), Pune, Maharashtra, 411030, India
| | - Asim Bhalerao
- Fluid Robotics Private Limited (FRPL), Pune, Maharashtra, 411052, India
| | - Nidhi Jain
- Fluid Robotics Private Limited (FRPL), Pune, Maharashtra, 411052, India
| | - Sanjay Kamble
- Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune, Maharashtra, 411008, India
| | - Syed Dastager
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India
| | - Krishanpal Karmodiya
- Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, Maharashtra, 41108, India
| | - Mahesh Dharne
- National Collection of Industrial Microorganisms (NCIM), Biochemical Sciences Division, CSIR-National Chemical Laboratory (NCL), Pune, Maharashtra, 411008, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India.
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9
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Trigo-Tasende N, Vallejo JA, Rumbo-Feal S, Conde-Pérez K, Vaamonde M, López-Oriona Á, Barbeito I, Nasser-Ali M, Reif R, Rodiño-Janeiro BK, Fernández-Álvarez E, Iglesias-Corrás I, Freire B, Tarrío-Saavedra J, Tomás L, Gallego-García P, Posada D, Bou G, López-de-Ullibarri I, Cao R, Ladra S, Poza M. Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27877-3. [PMID: 37286834 DOI: 10.1007/s11356-023-27877-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023]
Abstract
Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.
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Affiliation(s)
- Noelia Trigo-Tasende
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Juan A Vallejo
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Soraya Rumbo-Feal
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Kelly Conde-Pérez
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Manuel Vaamonde
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ángel López-Oriona
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Inés Barbeito
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Mohammed Nasser-Ali
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Rubén Reif
- Center for Research in Biological Chemistry and Molecular Materials (CiQUS), University of Santiago de Compostela (USC), 15782, Santiago de Compostela, Spain
| | - Bruno K Rodiño-Janeiro
- BFlow, University of Santiago de Compostela (USC) and Health Research Institute of Santiago de Compostela (IDIS), Campus Vida, 15706, Santiago de Compostela, A Coruña, Spain
| | - Elisa Fernández-Álvarez
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Iago Iglesias-Corrás
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Borja Freire
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Javier Tarrío-Saavedra
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Laura Tomás
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - Pilar Gallego-García
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - David Posada
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, 36310, Vigo, Spain
| | - Germán Bou
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Ignacio López-de-Ullibarri
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ricardo Cao
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Susana Ladra
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Margarita Poza
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain.
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10
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Segelhurst E, Bard JE, Pillsbury AN, Alam MM, Lamb NA, Zhu C, Pohlman A, Boccolucci A, Emerson J, Marzullo BJ, Yergeau DA, Nowak NJ, Bradley IM, Surtees JA, Ye Y. Robust Performance of SARS-CoV-2 Whole-Genome Sequencing from Wastewater with a Nonselective Virus Concentration Method. ACS ES&T WATER 2023; 3:954-962. [PMID: 37406038 PMCID: PMC10005814 DOI: 10.1021/acsestwater.2c00456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/01/2023] [Accepted: 02/21/2023] [Indexed: 07/07/2023]
Abstract
The sequencing of human virus genomes from wastewater samples is an efficient method for tracking viral transmission and evolution at the community level. However, this requires the recovery of viral nucleic acids of high quality. We developed a reusable tangential-flow filtration system to concentrate and purify viruses from wastewater for genome sequencing. A pilot study was conducted with 94 wastewater samples from four local sewersheds, from which viral nucleic acids were extracted, and the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was sequenced using the ARTIC V4.0 primers. Our method yielded a high probability (0.9) of recovering complete or near-complete SARS-CoV-2 genomes (>90% coverage at 10× depth) from wastewater when the COVID-19 incidence rate exceeded 33 cases per 100 000 people. The relative abundances of sequenced SARS-CoV-2 variants followed the trends observed from patient-derived samples. We also identified SARS-CoV-2 lineages in wastewater that were underrepresented or not present in the clinical whole-genome sequencing data. The developed tangential-flow filtration system can be easily adopted for the sequencing of other viruses in wastewater, particularly those at low concentrations.
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Affiliation(s)
- Emily Segelhurst
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
| | - Jonathan E. Bard
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
- Department of Biochemistry, Jacobs School of Medicine
and Biomedical Sciences, University at Buffalo, Buffalo, New
York 14203, United States
- Genetics, Genomics and Bioinformatics Graduate Program,
Jacobs School of Medicine and Biomedical Sciences, University at
Buffalo, Buffalo, New York 14203, United States
| | - Annemarie N. Pillsbury
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
| | - Md Mahbubul Alam
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
| | - Natalie A. Lamb
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
| | - Chonglin Zhu
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
| | - Alyssa Pohlman
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
| | - Amanda Boccolucci
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
| | - Jamaal Emerson
- Department of Microbiology and Immunology, Jacobs
School of Medicine and Biomedical Sciences, University at
Buffalo, Buffalo, New York 14203, United States
| | - Brandon J. Marzullo
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
- Department of Biochemistry, Jacobs School of Medicine
and Biomedical Sciences, University at Buffalo, Buffalo, New
York 14203, United States
| | - Donald A. Yergeau
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
| | - Norma J. Nowak
- UB Genomics and Bioinformatics Core,
University at Buffalo, Buffalo, New York 14203,
United States
- Department of Biochemistry, Jacobs School of Medicine
and Biomedical Sciences, University at Buffalo, Buffalo, New
York 14203, United States
| | - Ian M. Bradley
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
- Research and Education in Energy, Environmental and
Water (RENEW) Institute, University at Buffalo, Buffalo, New
York 14260, United States
| | - Jennifer A. Surtees
- Department of Biochemistry, Jacobs School of Medicine
and Biomedical Sciences, University at Buffalo, Buffalo, New
York 14203, United States
- Department of Microbiology and Immunology, Jacobs
School of Medicine and Biomedical Sciences, University at
Buffalo, Buffalo, New York 14203, United States
- Genetics, Genomics and Bioinformatics Graduate Program,
Jacobs School of Medicine and Biomedical Sciences, University at
Buffalo, Buffalo, New York 14203, United States
| | - Yinyin Ye
- Department of Civil, Structural and Environmental
Engineering, University at Buffalo, Buffalo, New York 14260,
United States
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11
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Vo V, Harrington A, Afzal S, Papp K, Chang CL, Baker H, Aguilar P, Buttery E, Picker MA, Lockett C, Gerrity D, Kan HY, Oh EC. Identification of a rare SARS-CoV-2 XL hybrid variant in wastewater and the subsequent discovery of two infected individuals in Nevada. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:160024. [PMID: 36356728 PMCID: PMC9640213 DOI: 10.1016/j.scitotenv.2022.160024] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/29/2022] [Accepted: 11/03/2022] [Indexed: 05/31/2023]
Abstract
The identification of novel SARS-CoV-2 variants can predict new patterns of COVID-19 community transmission and lead to the deployment of public health resources. However, increased access to at-home antigen tests and reduced free PCR tests have recently led to data gaps for the surveillance of evolving SARS-CoV-2 variants. To overcome such limitations, we asked whether wastewater surveillance could be leveraged to detect rare variants circulating in a community before local detection in human cases. Here, we performed whole genome sequencing (WGS) of SARS-CoV-2 from a wastewater treatment plant serving Las Vegas, Nevada in April 2022. Using metrics that exceeded 100× depth at a coverage of >90 % of the viral genome, we identified a variant profile similar to the XL recombinant lineage containing 26 mutations found in BA.1 and BA.2 and three private mutations. Prompted by the discovery of this rare lineage in wastewater, we analyzed clinical COVID-19 sequencing data from Southern Nevada and identified two cases infected with the XL lineage. Taken together, our data highlight how wastewater genome sequencing data can be used to discover rare SARS-CoV-2 lineages in a community and complement local public health surveillance.
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Affiliation(s)
- Van Vo
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Anthony Harrington
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Salman Afzal
- Southern Nevada Health District, Las Vegas, NV 89106, USA
| | - Katerina Papp
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Hayley Baker
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | | | - Erin Buttery
- Southern Nevada Health District, Las Vegas, NV 89106, USA
| | | | | | - Daniel Gerrity
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA.
| | - Horng-Yuan Kan
- Southern Nevada Health District, Las Vegas, NV 89106, USA.
| | - Edwin C Oh
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Department of Internal Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
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12
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Kayikcioglu T, Amirzadegan J, Rand H, Tesfaldet B, Timme RE, Pettengill JB. Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples. PeerJ 2023; 11:e14596. [PMID: 36721781 PMCID: PMC9884472 DOI: 10.7717/peerj.14596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 11/29/2022] [Indexed: 01/27/2023] Open
Abstract
Background The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). Methods We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Results Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). Conclusion This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.
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Affiliation(s)
- Tunc Kayikcioglu
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, United States of America,Joint Institute for Food Safety and Applied Nutrition, University of Maryland College Park, College Park, MD, United States of America
| | - Jasmine Amirzadegan
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, United States of America,Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States of America
| | - Hugh Rand
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, United States of America
| | - Bereket Tesfaldet
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, United States of America
| | - Ruth E. Timme
- Division of Microbiology, Office of Regulatory Science, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, College Park, MD, United States of America
| | - James B. Pettengill
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, United States of America
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13
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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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14
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Karthikeyan S, Levy JI, De Hoff P, Humphrey G, Birmingham A, Jepsen K, Farmer S, Tubb HM, Valles T, Tribelhorn CE, Tsai R, Aigner S, Sathe S, Moshiri N, Henson B, Mark AM, Hakim A, Baer NA, Barber T, Belda-Ferre P, Chacón M, Cheung W, Cresini ES, Eisner ER, Lastrella AL, Lawrence ES, Marotz CA, Ngo TT, Ostrander T, Plascencia A, Salido RA, Seaver P, Smoot EW, McDonald D, Neuhard RM, Scioscia AL, Satterlund AM, Simmons EH, Abelman DB, Brenner D, Bruner JC, Buckley A, Ellison M, Gattas J, Gonias SL, Hale M, Hawkins F, Ikeda L, Jhaveri H, Johnson T, Kellen V, Kremer B, Matthews G, McLawhon RW, Ouillet P, Park D, Pradenas A, Reed S, Riggs L, Sanders A, Sollenberger B, Song A, White B, Winbush T, Aceves CM, Anderson C, Gangavarapu K, Hufbauer E, Kurzban E, Lee J, Matteson NL, Parker E, Perkins SA, Ramesh KS, Robles-Sikisaka R, Schwab MA, Spencer E, Wohl S, Nicholson L, Mchardy IH, Dimmock DP, Hobbs CA, Bakhtar O, Harding A, Mendoza A, Bolze A, Becker D, Cirulli ET, Isaksson M, Schiabor Barrett KM, Washington NL, Malone JD, Schafer AM, Gurfield N, Stous S, Fielding-Miller R, Garfein RS, Gaines T, Anderson C, Martin NK, Schooley R, Austin B, MacCannell DR, Kingsmore SF, Lee W, Shah S, McDonald E, Yu AT, Zeller M, Fisch KM, Longhurst C, Maysent P, Pride D, Khosla PK, Laurent LC, Yeo GW, Andersen KG, Knight R. Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission. Nature 2022; 609:101-108. [PMID: 35798029 PMCID: PMC9433318 DOI: 10.1038/s41586-022-05049-6] [Citation(s) in RCA: 160] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 06/29/2022] [Indexed: 11/23/2022]
Abstract
As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission. Emerging SARS-CoV-2 variants of concern were detected early and multiple cases of virus spread not captured by clinical genomic surveillance were identified using high-resolution wastewater and clinical sequencing.
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Affiliation(s)
- Smruthi Karthikeyan
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Joshua I Levy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Peter De Hoff
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Greg Humphrey
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Amanda Birmingham
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Kristen Jepsen
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sawyer Farmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Helena M Tubb
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tommy Valles
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | | | - Rebecca Tsai
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Stefan Aigner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Shashank Sathe
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Niema Moshiri
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Benjamin Henson
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Adam M Mark
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Abbas Hakim
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Nathan A Baer
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tom Barber
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Pedro Belda-Ferre
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Marisol Chacón
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Willi Cheung
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Evelyn S Cresini
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Emily R Eisner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Alma L Lastrella
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elijah S Lawrence
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Clarisse A Marotz
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Toan T Ngo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tyler Ostrander
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Ashley Plascencia
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Rodolfo A Salido
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Phoebe Seaver
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elizabeth W Smoot
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Robert M Neuhard
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA.,Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Angela L Scioscia
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,Student Health and Well-Being, University of California San Diego, La Jolla, CA, USA
| | | | | | - Dismas B Abelman
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - David Brenner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Judith C Bruner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Anne Buckley
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Michael Ellison
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Jeffrey Gattas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Steven L Gonias
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Matt Hale
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Faith Hawkins
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lydia Ikeda
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Hemlata Jhaveri
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Ted Johnson
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Vince Kellen
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Brendan Kremer
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Gary Matthews
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Ronald W McLawhon
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Pierre Ouillet
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Daniel Park
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Allorah Pradenas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Sharon Reed
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lindsay Riggs
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Alison Sanders
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | | | - Angela Song
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA.,Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Benjamin White
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Terri Winbush
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Christine M Aceves
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Catelyn Anderson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emory Hufbauer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ezra Kurzban
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Justin Lee
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nathaniel L Matteson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Edyth Parker
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Sarah A Perkins
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik S Ramesh
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Refugio Robles-Sikisaka
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Madison A Schwab
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emily Spencer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Shirlee Wohl
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | | | | | - David P Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | - John D Malone
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | | | - Nikos Gurfield
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Rebecca Fielding-Miller
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA.,Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Richard S Garfein
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Tommi Gaines
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Cheryl Anderson
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Natasha K Martin
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Robert Schooley
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | | | - Duncan R MacCannell
- Office of Advanced Molecular Detection, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Seema Shah
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Eric McDonald
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Alexander T Yu
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Kathleen M Fisch
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Christopher Longhurst
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA
| | - Patty Maysent
- Office of the UC San Diego Health CEO, University of California, San Diego, USA
| | - David Pride
- Departments of Pathology and Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Pradeep K Khosla
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Louise C Laurent
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.,Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA, USA
| | - Gene W Yeo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.,Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA, USA.,Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA. .,Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA. .,Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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15
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Karthikeyan S, Levy JI, De Hoff P, Humphrey G, Birmingham A, Jepsen K, Farmer S, Tubb HM, Valles T, Tribelhorn CE, Tsai R, Aigner S, Sathe S, Moshiri N, Henson B, Mark AM, Hakim A, Baer NA, Barber T, Belda-Ferre P, Chacón M, Cheung W, Cresini ES, Eisner ER, Lastrella AL, Lawrence ES, Marotz CA, Ngo TT, Ostrander T, Plascencia A, Salido RA, Seaver P, Smoot EW, McDonald D, Neuhard RM, Scioscia AL, Satterlund AM, Simmons EH, Abelman DB, Brenner D, Bruner JC, Buckley A, Ellison M, Gattas J, Gonias SL, Hale M, Hawkins F, Ikeda L, Jhaveri H, Johnson T, Kellen V, Kremer B, Matthews G, McLawhon RW, Ouillet P, Park D, Pradenas A, Reed S, Riggs L, Sanders A, Sollenberger B, Song A, White B, Winbush T, Aceves CM, Anderson C, Gangavarapu K, Hufbauer E, Kurzban E, Lee J, Matteson NL, Parker E, Perkins SA, Ramesh KS, Robles-Sikisaka R, Schwab MA, Spencer E, Wohl S, Nicholson L, Mchardy IH, Dimmock DP, Hobbs CA, Bakhtar O, Harding A, Mendoza A, Bolze A, Becker D, Cirulli ET, Isaksson M, Barrett KMS, Washington NL, Malone JD, Schafer AM, Gurfield N, Stous S, Fielding-Miller R, Garfein RS, Gaines T, Anderson C, Martin NK, Schooley R, Austin B, MacCannell DR, Kingsmore SF, Lee W, Shah S, McDonald E, Yu AT, Zeller M, Fisch KM, Longhurst C, Maysent P, Pride D, Khosla PK, Laurent LC, Yeo GW, Andersen KG, Knight R. Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022. [PMID: 35411350 DOI: 10.1101/2022.01.27.22269965] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.
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Affiliation(s)
- Smruthi Karthikeyan
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Joshua I Levy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Peter De Hoff
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Greg Humphrey
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Amanda Birmingham
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Kristen Jepsen
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sawyer Farmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Helena M Tubb
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tommy Valles
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | | | - Rebecca Tsai
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Stefan Aigner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Shashank Sathe
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Niema Moshiri
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Benjamin Henson
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Adam M Mark
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Abbas Hakim
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Nathan A Baer
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tom Barber
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Pedro Belda-Ferre
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Marisol Chacón
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Willi Cheung
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Evelyn S Cresini
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Emily R Eisner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Alma L Lastrella
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elijah S Lawrence
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Clarisse A Marotz
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Toan T Ngo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tyler Ostrander
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Ashley Plascencia
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Rodolfo A Salido
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Phoebe Seaver
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elizabeth W Smoot
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Robert M Neuhard
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Angela L Scioscia
- Student Health and Well-Being, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | | | | | - Dismas B Abelman
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - David Brenner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Judith C Bruner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Anne Buckley
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Michael Ellison
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Jeffrey Gattas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Steven L Gonias
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Matt Hale
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Faith Hawkins
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lydia Ikeda
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Hemlata Jhaveri
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Ted Johnson
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Vince Kellen
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Brendan Kremer
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Gary Matthews
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Ronald W McLawhon
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Pierre Ouillet
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Daniel Park
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Allorah Pradenas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Sharon Reed
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lindsay Riggs
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Alison Sanders
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | | | - Angela Song
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Benjamin White
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Terri Winbush
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Christine M Aceves
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Catelyn Anderson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emory Hufbauer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ezra Kurzban
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Justin Lee
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nathaniel L Matteson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Edyth Parker
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Sarah A Perkins
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik S Ramesh
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Refugio Robles-Sikisaka
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Madison A Schwab
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emily Spencer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Shirlee Wohl
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Laura Nicholson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ian H Mchardy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - David P Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | - John D Malone
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | | | - Nikos Gurfield
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Rebecca Fielding-Miller
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Richard S Garfein
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Tommi Gaines
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Cheryl Anderson
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Natasha K Martin
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Robert Schooley
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | | | - Duncan R MacCannell
- Office of Advanced Molecular Detection, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Seema Shah
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Eric McDonald
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Alexander T Yu
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Kathleen M Fisch
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | - Christopher Longhurst
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA
| | - Patty Maysent
- Office of the UC San Diego Health CEO, University of California, San Diego
| | - David Pride
- Departments of Pathology and Medicine, University of California, San Diego, La Jolla, CA
| | - Pradeep K Khosla
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Louise C Laurent
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA
| | - Gene W Yeo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
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Karthikeyan S, Levy JI, De Hoff P, Humphrey G, Birmingham A, Jepsen K, Farmer S, Tubb HM, Valles T, Tribelhorn CE, Tsai R, Aigner S, Sathe S, Moshiri N, Henson B, Mark AM, Hakim A, Baer NA, Barber T, Belda-Ferre P, Chacón M, Cheung W, Cresini ES, Eisner ER, Lastrella AL, Lawrence ES, Marotz CA, Ngo TT, Ostrander T, Plascencia A, Salido RA, Seaver P, Smoot EW, McDonald D, Neuhard RM, Scioscia AL, Satterlund AM, Simmons EH, Abelman DB, Brenner D, Bruner JC, Buckley A, Ellison M, Gattas J, Gonias SL, Hale M, Hawkins F, Ikeda L, Jhaveri H, Johnson T, Kellen V, Kremer B, Matthews G, McLawhon RW, Ouillet P, Park D, Pradenas A, Reed S, Riggs L, Sanders A, Sollenberger B, Song A, White B, Winbush T, Aceves CM, Anderson C, Gangavarapu K, Hufbauer E, Kurzban E, Lee J, Matteson NL, Parker E, Perkins SA, Ramesh KS, Robles-Sikisaka R, Schwab MA, Spencer E, Wohl S, Nicholson L, Mchardy IH, Dimmock DP, Hobbs CA, Bakhtar O, Harding A, Mendoza A, Bolze A, Becker D, Cirulli ET, Isaksson M, Barrett KMS, Washington NL, Malone JD, Schafer AM, Gurfield N, Stous S, Fielding-Miller R, Garfein RS, Gaines T, Anderson C, Martin NK, Schooley R, Austin B, MacCannell DR, Kingsmore SF, Lee W, Shah S, McDonald E, Yu AT, Zeller M, Fisch KM, Longhurst C, Maysent P, Pride D, Khosla PK, Laurent LC, Yeo GW, Andersen KG, Knight R. Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2021.12.21.21268143. [PMID: 35411350 PMCID: PMC8996633 DOI: 10.1101/2021.12.21.21268143] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.
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Affiliation(s)
- Smruthi Karthikeyan
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Joshua I Levy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Peter De Hoff
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Greg Humphrey
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Amanda Birmingham
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Kristen Jepsen
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sawyer Farmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Helena M. Tubb
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tommy Valles
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | | | - Rebecca Tsai
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Stefan Aigner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Shashank Sathe
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Niema Moshiri
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Benjamin Henson
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Adam M. Mark
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
| | - Abbas Hakim
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Nathan A Baer
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tom Barber
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Pedro Belda-Ferre
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Marisol Chacón
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Willi Cheung
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Evelyn S Cresini
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Emily R Eisner
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Alma L Lastrella
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elijah S Lawrence
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Clarisse A Marotz
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Toan T Ngo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Tyler Ostrander
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Ashley Plascencia
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Rodolfo A Salido
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Phoebe Seaver
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elizabeth W Smoot
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Robert M Neuhard
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Angela L Scioscia
- Student Health and Well-Being, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | | | | | - Dismas B. Abelman
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - David Brenner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Judith C. Bruner
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Anne Buckley
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Michael Ellison
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Jeffrey Gattas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Steven L. Gonias
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Matt Hale
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Faith Hawkins
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lydia Ikeda
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Hemlata Jhaveri
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Ted Johnson
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Vince Kellen
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Brendan Kremer
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Gary Matthews
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | | | - Pierre Ouillet
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Daniel Park
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Allorah Pradenas
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Sharon Reed
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Lindsay Riggs
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Alison Sanders
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | | | - Angela Song
- Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Benjamin White
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Terri Winbush
- Return to Learn, University of California San Diego, La Jolla, CA, USA
| | - Christine M Aceves
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Catelyn Anderson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emory Hufbauer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ezra Kurzban
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Justin Lee
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Nathaniel L Matteson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Edyth Parker
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Sarah A Perkins
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik S Ramesh
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Refugio Robles-Sikisaka
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Madison A Schwab
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emily Spencer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Shirlee Wohl
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Laura Nicholson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Ian H Mchardy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - David P Dimmock
- Rady Children’s Institute for Genomic Medicine, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | - John D Malone
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | | | - Nikos Gurfield
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Sarah Stous
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Rebecca Fielding-Miller
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Richard S. Garfein
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Tommi Gaines
- Division of Infectious Disease and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Cheryl Anderson
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Natasha K. Martin
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Robert Schooley
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | | | - Duncan R. MacCannell
- Office of Advanced Molecular Detection, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Seema Shah
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Eric McDonald
- County of San Diego Health and Human Services Agency, San Diego, CA, USA
| | - Alexander T. Yu
- COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Kathleen M Fisch
- Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
| | - Christopher Longhurst
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA
| | - Patty Maysent
- Office of the UC San Diego Health CEO, University of California, San Diego
| | - David Pride
- Departments of Pathology and Medicine, University of California, San Diego, La Jolla, CA
| | - Pradeep K. Khosla
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Louise C. Laurent
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA
- Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA
| | - Gene W Yeo
- Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
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