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A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron

The rapid emergence of SARS-CoV-2 variants raised public health questions concerning the capability of diagnostic tests to detect new strains, the efficacy of vaccines, and how to map the geographical distribution of variants to understand transmission patterns and loads on healthcare resources. Nex...

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Autores principales: Lai, Eric, Kennedy, Emily B., Lozach, Jean, Hayashibara, Kathleen, Davis-Turak, Jeremy, Becker, David, Brzoska, Pius, Cassens, Tyler, Diamond, Evan, Gandhi, Manoj, Greninger, Alexander L., Hajian, Pooneh, Leonetti, Nicole A., Nguyen, Jason M., O’Donovan, K. M. Clair, Peck, Troy, Ramirez, Jimmy M., Roychoudhury, Pavitra, Sandoval, Efren, Wesselman, Cassandra, Wesselman, Timothy, White, Simon, Williams, Stephen, Wong, David, Yu, Yufei, Creager, Richard S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297815/
https://www.ncbi.nlm.nih.gov/pubmed/35766514
http://dx.doi.org/10.1128/jcm.00342-22
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author Lai, Eric
Kennedy, Emily B.
Lozach, Jean
Hayashibara, Kathleen
Davis-Turak, Jeremy
Becker, David
Brzoska, Pius
Cassens, Tyler
Diamond, Evan
Gandhi, Manoj
Greninger, Alexander L.
Hajian, Pooneh
Leonetti, Nicole A.
Nguyen, Jason M.
O’Donovan, K. M. Clair
Peck, Troy
Ramirez, Jimmy M.
Roychoudhury, Pavitra
Sandoval, Efren
Wesselman, Cassandra
Wesselman, Timothy
White, Simon
Williams, Stephen
Wong, David
Yu, Yufei
Creager, Richard S.
author_facet Lai, Eric
Kennedy, Emily B.
Lozach, Jean
Hayashibara, Kathleen
Davis-Turak, Jeremy
Becker, David
Brzoska, Pius
Cassens, Tyler
Diamond, Evan
Gandhi, Manoj
Greninger, Alexander L.
Hajian, Pooneh
Leonetti, Nicole A.
Nguyen, Jason M.
O’Donovan, K. M. Clair
Peck, Troy
Ramirez, Jimmy M.
Roychoudhury, Pavitra
Sandoval, Efren
Wesselman, Cassandra
Wesselman, Timothy
White, Simon
Williams, Stephen
Wong, David
Yu, Yufei
Creager, Richard S.
author_sort Lai, Eric
collection PubMed
description The rapid emergence of SARS-CoV-2 variants raised public health questions concerning the capability of diagnostic tests to detect new strains, the efficacy of vaccines, and how to map the geographical distribution of variants to understand transmission patterns and loads on healthcare resources. Next-generation sequencing (NGS) is the primary method for detecting and tracing new variants, but it is expensive, and it can take weeks before sequence data are available in public repositories. This article describes a customizable reverse transcription PCR (RT-PCR)-based genotyping approach which is significantly less expensive, accelerates reporting, and can be implemented in any lab that performs RT-PCR. Specific single-nucleotide polymorphisms (SNPs) and indels were identified which had high positive-percent agreement (PPA) and negative-percent agreement (NPA) compared to NGS for the major genotypes that circulated through September 11, 2021. Using a 48-marker panel, testing on 1,031 retrospective SARS-CoV-2 positive samples yielded a PPA and NPA ranging from 96.3 to 100% and 99.2 to 100%, respectively, for the top 10 most prevalent World Health Organization (WHO) lineages during that time. The effect of reducing the quantity of panel markers was explored, and a 16-marker panel was determined to be nearly as effective as the 48-marker panel at lineage assignment. Responding to the emergence of Omicron, a genotyping panel was developed which distinguishes Delta and Omicron using four highly specific SNPs. The results demonstrate the utility of the condensed panel to rapidly track the growing prevalence of Omicron across the US in December 2021 and January 2022.
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spelling pubmed-92978152022-07-21 A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron Lai, Eric Kennedy, Emily B. Lozach, Jean Hayashibara, Kathleen Davis-Turak, Jeremy Becker, David Brzoska, Pius Cassens, Tyler Diamond, Evan Gandhi, Manoj Greninger, Alexander L. Hajian, Pooneh Leonetti, Nicole A. Nguyen, Jason M. O’Donovan, K. M. Clair Peck, Troy Ramirez, Jimmy M. Roychoudhury, Pavitra Sandoval, Efren Wesselman, Cassandra Wesselman, Timothy White, Simon Williams, Stephen Wong, David Yu, Yufei Creager, Richard S. J Clin Microbiol Virology The rapid emergence of SARS-CoV-2 variants raised public health questions concerning the capability of diagnostic tests to detect new strains, the efficacy of vaccines, and how to map the geographical distribution of variants to understand transmission patterns and loads on healthcare resources. Next-generation sequencing (NGS) is the primary method for detecting and tracing new variants, but it is expensive, and it can take weeks before sequence data are available in public repositories. This article describes a customizable reverse transcription PCR (RT-PCR)-based genotyping approach which is significantly less expensive, accelerates reporting, and can be implemented in any lab that performs RT-PCR. Specific single-nucleotide polymorphisms (SNPs) and indels were identified which had high positive-percent agreement (PPA) and negative-percent agreement (NPA) compared to NGS for the major genotypes that circulated through September 11, 2021. Using a 48-marker panel, testing on 1,031 retrospective SARS-CoV-2 positive samples yielded a PPA and NPA ranging from 96.3 to 100% and 99.2 to 100%, respectively, for the top 10 most prevalent World Health Organization (WHO) lineages during that time. The effect of reducing the quantity of panel markers was explored, and a 16-marker panel was determined to be nearly as effective as the 48-marker panel at lineage assignment. Responding to the emergence of Omicron, a genotyping panel was developed which distinguishes Delta and Omicron using four highly specific SNPs. The results demonstrate the utility of the condensed panel to rapidly track the growing prevalence of Omicron across the US in December 2021 and January 2022. American Society for Microbiology 2022-06-29 /pmc/articles/PMC9297815/ /pubmed/35766514 http://dx.doi.org/10.1128/jcm.00342-22 Text en Copyright © 2022 Lai et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Virology
Lai, Eric
Kennedy, Emily B.
Lozach, Jean
Hayashibara, Kathleen
Davis-Turak, Jeremy
Becker, David
Brzoska, Pius
Cassens, Tyler
Diamond, Evan
Gandhi, Manoj
Greninger, Alexander L.
Hajian, Pooneh
Leonetti, Nicole A.
Nguyen, Jason M.
O’Donovan, K. M. Clair
Peck, Troy
Ramirez, Jimmy M.
Roychoudhury, Pavitra
Sandoval, Efren
Wesselman, Cassandra
Wesselman, Timothy
White, Simon
Williams, Stephen
Wong, David
Yu, Yufei
Creager, Richard S.
A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title_full A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title_fullStr A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title_full_unstemmed A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title_short A Method for Variant Agnostic Detection of SARS-CoV-2, Rapid Monitoring of Circulating Variants, and Early Detection of Emergent Variants Such as Omicron
title_sort method for variant agnostic detection of sars-cov-2, rapid monitoring of circulating variants, and early detection of emergent variants such as omicron
topic Virology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297815/
https://www.ncbi.nlm.nih.gov/pubmed/35766514
http://dx.doi.org/10.1128/jcm.00342-22
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