Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

被引:0
|
作者
Smruthi Karthikeyan
Joshua I. Levy
Peter De Hoff
Greg Humphrey
Amanda Birmingham
Kristen Jepsen
Sawyer Farmer
Helena M. Tubb
Tommy Valles
Caitlin E. Tribelhorn
Rebecca Tsai
Stefan Aigner
Shashank Sathe
Niema Moshiri
Benjamin Henson
Adam M. Mark
Abbas Hakim
Nathan A. Baer
Tom Barber
Pedro Belda-Ferre
Marisol Chacón
Willi Cheung
Evelyn S. Cresini
Emily R. Eisner
Alma L. Lastrella
Elijah S. Lawrence
Clarisse A. Marotz
Toan T. Ngo
Tyler Ostrander
Ashley Plascencia
Rodolfo A. Salido
Phoebe Seaver
Elizabeth W. Smoot
Daniel McDonald
Robert M. Neuhard
Angela L. Scioscia
Alysson M. Satterlund
Elizabeth H. Simmons
Dismas B. Abelman
David Brenner
Judith C. Bruner
Anne Buckley
Michael Ellison
Jeffrey Gattas
Steven L. Gonias
Matt Hale
Faith Hawkins
Lydia Ikeda
Hemlata Jhaveri
Ted Johnson
机构
[1] University of California San Diego,Department of Pediatrics
[2] The Scripps Research Institute,Department of Immunology and Microbiology
[3] University of California San Diego,Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics
[4] University of California San Diego,Department of Obstetrics, Gynecology, and Reproductive Sciences
[5] COVID-19 Detection,Center for Computational Biology and Bioinformatics
[6] Investigation,Institute for Genomic Medicine
[7] Surveillance,Department of Computer Science and Engineering
[8] Clinical,Operational Strategic Initiatives
[9] and Outbreak Response,Return to Learn
[10] California Department of Public Health,Student Affairs
[11] University of California San Diego,Academic Affairs
[12] University of California San Diego,Department of Pathology
[13] University of California San Diego,Herbert Wertheim School of Public Health and Human Longevity Science
[14] University of California San Diego,Division of Infectious Disease and Global Public Health
[15] University of California San Diego,Department of Biomedical Informatics
[16] Student Health and Well-Being,Office of the UC San Diego Health CEO
[17] University of California San Diego,Department of Medicine
[18] University of California San Diego,Sanford Consortium of Regenerative Medicine
[19] University of California San Diego,Department of Cellular and Molecular Medicine
[20] University of California San Diego,Department of Bioengineering
[21] Scripps Health,undefined
[22] San Diego,undefined
[23] Rady Children’s Institute for Genomic Medicine,undefined
[24] Sharp Healthcare,undefined
[25] Helix,undefined
[26] County of San Diego Health and Human Services Agency,undefined
[27] University of California San Diego,undefined
[28] University of California San Diego,undefined
[29] Office of Advanced Molecular Detection,undefined
[30] Centers for Disease Control and Prevention,undefined
[31] University of California San Diego,undefined
[32] University of California San Diego,undefined
[33] University of California San Diego,undefined
[34] University of California San Diego,undefined
[35] University of California San Diego,undefined
[36] University of California San Diego,undefined
来源
Nature | 2022年 / 609卷
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学科分类号
摘要
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.
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页码:101 / 108
页数:7
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