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Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program

BACKGROUND: The Centers for Disease Control and Prevention contracted with laboratories to sequence the SARS-CoV-2 genome from positive samples across the United States to enable public health officials to investigate the impact of variants on disease severity as well as the effectiveness of vaccine...

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Autores principales: Goswami, Chirayu, Sheldon, Michael, Bixby, Christian, Keddache, Mehdi, Bogdanowicz, Alexander, Wang, Yihe, Schultz, Jonathan, McDevitt, Jessica, LaPorta, James, Kwon, Elaine, Buyske, Steven, Garbolino, Dana, Biloholowski, Glenys, Pastuszak, Alex, Storella, Mary, Bhalla, Amit, Charlier-Rodriguez, Florence, Hager, Russ, Grimwood, Robin, Nahas, Shareef A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035976/
https://www.ncbi.nlm.nih.gov/pubmed/35468749
http://dx.doi.org/10.1186/s12879-022-07374-7
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author Goswami, Chirayu
Sheldon, Michael
Bixby, Christian
Keddache, Mehdi
Bogdanowicz, Alexander
Wang, Yihe
Schultz, Jonathan
McDevitt, Jessica
LaPorta, James
Kwon, Elaine
Buyske, Steven
Garbolino, Dana
Biloholowski, Glenys
Pastuszak, Alex
Storella, Mary
Bhalla, Amit
Charlier-Rodriguez, Florence
Hager, Russ
Grimwood, Robin
Nahas, Shareef A.
author_facet Goswami, Chirayu
Sheldon, Michael
Bixby, Christian
Keddache, Mehdi
Bogdanowicz, Alexander
Wang, Yihe
Schultz, Jonathan
McDevitt, Jessica
LaPorta, James
Kwon, Elaine
Buyske, Steven
Garbolino, Dana
Biloholowski, Glenys
Pastuszak, Alex
Storella, Mary
Bhalla, Amit
Charlier-Rodriguez, Florence
Hager, Russ
Grimwood, Robin
Nahas, Shareef A.
author_sort Goswami, Chirayu
collection PubMed
description BACKGROUND: The Centers for Disease Control and Prevention contracted with laboratories to sequence the SARS-CoV-2 genome from positive samples across the United States to enable public health officials to investigate the impact of variants on disease severity as well as the effectiveness of vaccines and treatment. Herein we present the initial results correlating RT-PCR quality control metrics with sample collection and sequencing methods from full SARS-CoV-2 viral genomic sequencing of 24,441 positive patient samples between April and June 2021. METHODS: RT-PCR confirmed (N Gene Ct value < 30) positive patient samples, with nucleic acid extracted from saliva, nasopharyngeal and oropharyngeal swabs were selected for viral whole genome SARS-CoV-2 sequencing. Sequencing was performed using Illumina COVIDSeq™ protocol on either the NextSeq550 or NovaSeq6000 systems. Informatic variant calling, and lineage analysis were performed using DRAGEN COVID Lineage applications on Illumina’s Basespace cloud analytical system. All sequence data and variant calls were uploaded to NCBI and GISAID. RESULTS: An association was observed between higher sequencing coverage, quality, and samples with a lower Ct value, with < 27 being optimal, across both sequencing platforms and sample collection methods. Both nasopharyngeal swabs and saliva samples were found to be optimal samples of choice for SARS-CoV-2 surveillance sequencing studies, both in terms of strain identification and sequencing depth of coverage, with NovaSeq 6000 providing higher coverage than the NextSeq 550. The most frequent variants identified were the B.1.617.2 Delta (India) and P.1 Gamma (Brazil) variants in the samples sequenced between April 2021 and June 2021. At the time of submission, the most common variant > 99% of positives sequenced was Omicron. CONCLUSION: These initial analyses highlight the importance of sequencing platform, sample collection methods, and RT-PCR Ct values in guiding surveillance efforts. These surveillance studies evaluating genetic changes of SARS-CoV-2 have been identified as critical by the CDC that can affect many aspects of public health including transmission, disease severity, diagnostics, therapeutics, and vaccines. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07374-7.
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spelling pubmed-90359762022-04-25 Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program Goswami, Chirayu Sheldon, Michael Bixby, Christian Keddache, Mehdi Bogdanowicz, Alexander Wang, Yihe Schultz, Jonathan McDevitt, Jessica LaPorta, James Kwon, Elaine Buyske, Steven Garbolino, Dana Biloholowski, Glenys Pastuszak, Alex Storella, Mary Bhalla, Amit Charlier-Rodriguez, Florence Hager, Russ Grimwood, Robin Nahas, Shareef A. BMC Infect Dis Research Article BACKGROUND: The Centers for Disease Control and Prevention contracted with laboratories to sequence the SARS-CoV-2 genome from positive samples across the United States to enable public health officials to investigate the impact of variants on disease severity as well as the effectiveness of vaccines and treatment. Herein we present the initial results correlating RT-PCR quality control metrics with sample collection and sequencing methods from full SARS-CoV-2 viral genomic sequencing of 24,441 positive patient samples between April and June 2021. METHODS: RT-PCR confirmed (N Gene Ct value < 30) positive patient samples, with nucleic acid extracted from saliva, nasopharyngeal and oropharyngeal swabs were selected for viral whole genome SARS-CoV-2 sequencing. Sequencing was performed using Illumina COVIDSeq™ protocol on either the NextSeq550 or NovaSeq6000 systems. Informatic variant calling, and lineage analysis were performed using DRAGEN COVID Lineage applications on Illumina’s Basespace cloud analytical system. All sequence data and variant calls were uploaded to NCBI and GISAID. RESULTS: An association was observed between higher sequencing coverage, quality, and samples with a lower Ct value, with < 27 being optimal, across both sequencing platforms and sample collection methods. Both nasopharyngeal swabs and saliva samples were found to be optimal samples of choice for SARS-CoV-2 surveillance sequencing studies, both in terms of strain identification and sequencing depth of coverage, with NovaSeq 6000 providing higher coverage than the NextSeq 550. The most frequent variants identified were the B.1.617.2 Delta (India) and P.1 Gamma (Brazil) variants in the samples sequenced between April 2021 and June 2021. At the time of submission, the most common variant > 99% of positives sequenced was Omicron. CONCLUSION: These initial analyses highlight the importance of sequencing platform, sample collection methods, and RT-PCR Ct values in guiding surveillance efforts. These surveillance studies evaluating genetic changes of SARS-CoV-2 have been identified as critical by the CDC that can affect many aspects of public health including transmission, disease severity, diagnostics, therapeutics, and vaccines. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07374-7. BioMed Central 2022-04-25 /pmc/articles/PMC9035976/ /pubmed/35468749 http://dx.doi.org/10.1186/s12879-022-07374-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Goswami, Chirayu
Sheldon, Michael
Bixby, Christian
Keddache, Mehdi
Bogdanowicz, Alexander
Wang, Yihe
Schultz, Jonathan
McDevitt, Jessica
LaPorta, James
Kwon, Elaine
Buyske, Steven
Garbolino, Dana
Biloholowski, Glenys
Pastuszak, Alex
Storella, Mary
Bhalla, Amit
Charlier-Rodriguez, Florence
Hager, Russ
Grimwood, Robin
Nahas, Shareef A.
Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title_full Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title_fullStr Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title_full_unstemmed Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title_short Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program
title_sort identification of sars-cov-2 variants using viral sequencing for the centers for disease control and prevention genomic surveillance program
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035976/
https://www.ncbi.nlm.nih.gov/pubmed/35468749
http://dx.doi.org/10.1186/s12879-022-07374-7
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