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Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the...

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Autores principales: Page, Andrew J., Mather, Alison E., Le-Viet, Thanh, Meader, Emma J., Alikhan, Nabil-Fareed, Kay, Gemma L., de Oliveira Martins, Leonardo, Aydin, Alp, Baker, David J., Trotter, Alexander J., Rudder, Steven, Tedim, Ana P., Kolyva, Anastasia, Stanley, Rachael, Yasir, Muhammad, Diaz, Maria, Potter, Will, Stuart, Claire, Meadows, Lizzie, Bell, Andrew, Gutierrez, Ana Victoria, Thomson, Nicholas M., Adriaenssens, Evelien M., Swingler, Tracey, Gilroy, Rachel A. J., Griffith, Luke, Sethi, Dheeraj K., Aggarwal, Dinesh, Brown, Colin S., Davidson, Rose K., Kingsley, Robert A., Bedford, Luke, Coupland, Lindsay J., Charles, Ian G., Elumogo, Ngozi, Wain, John, Prakash, Reenesh, Webber, Mark A., Smith, S. J. Louise, Chand, Meera, Dervisevic, Samir, O’Grady, Justin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461472/
https://www.ncbi.nlm.nih.gov/pubmed/34184982
http://dx.doi.org/10.1099/mgen.0.000589
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author Page, Andrew J.
Mather, Alison E.
Le-Viet, Thanh
Meader, Emma J.
Alikhan, Nabil-Fareed
Kay, Gemma L.
de Oliveira Martins, Leonardo
Aydin, Alp
Baker, David J.
Trotter, Alexander J.
Rudder, Steven
Tedim, Ana P.
Kolyva, Anastasia
Stanley, Rachael
Yasir, Muhammad
Diaz, Maria
Potter, Will
Stuart, Claire
Meadows, Lizzie
Bell, Andrew
Gutierrez, Ana Victoria
Thomson, Nicholas M.
Adriaenssens, Evelien M.
Swingler, Tracey
Gilroy, Rachel A. J.
Griffith, Luke
Sethi, Dheeraj K.
Aggarwal, Dinesh
Brown, Colin S.
Davidson, Rose K.
Kingsley, Robert A.
Bedford, Luke
Coupland, Lindsay J.
Charles, Ian G.
Elumogo, Ngozi
Wain, John
Prakash, Reenesh
Webber, Mark A.
Smith, S. J. Louise
Chand, Meera
Dervisevic, Samir
O’Grady, Justin
author_facet Page, Andrew J.
Mather, Alison E.
Le-Viet, Thanh
Meader, Emma J.
Alikhan, Nabil-Fareed
Kay, Gemma L.
de Oliveira Martins, Leonardo
Aydin, Alp
Baker, David J.
Trotter, Alexander J.
Rudder, Steven
Tedim, Ana P.
Kolyva, Anastasia
Stanley, Rachael
Yasir, Muhammad
Diaz, Maria
Potter, Will
Stuart, Claire
Meadows, Lizzie
Bell, Andrew
Gutierrez, Ana Victoria
Thomson, Nicholas M.
Adriaenssens, Evelien M.
Swingler, Tracey
Gilroy, Rachel A. J.
Griffith, Luke
Sethi, Dheeraj K.
Aggarwal, Dinesh
Brown, Colin S.
Davidson, Rose K.
Kingsley, Robert A.
Bedford, Luke
Coupland, Lindsay J.
Charles, Ian G.
Elumogo, Ngozi
Wain, John
Prakash, Reenesh
Webber, Mark A.
Smith, S. J. Louise
Chand, Meera
Dervisevic, Samir
O’Grady, Justin
author_sort Page, Andrew J.
collection PubMed
description The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organizations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1565 positive samples (172 per 100 000 population) from 1376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6 % of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. In total, 1035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a discrete sublineage associated with six care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients, indicating infection control measures were effective; and found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.
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spelling pubmed-84614722021-09-24 Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management Page, Andrew J. Mather, Alison E. Le-Viet, Thanh Meader, Emma J. Alikhan, Nabil-Fareed Kay, Gemma L. de Oliveira Martins, Leonardo Aydin, Alp Baker, David J. Trotter, Alexander J. Rudder, Steven Tedim, Ana P. Kolyva, Anastasia Stanley, Rachael Yasir, Muhammad Diaz, Maria Potter, Will Stuart, Claire Meadows, Lizzie Bell, Andrew Gutierrez, Ana Victoria Thomson, Nicholas M. Adriaenssens, Evelien M. Swingler, Tracey Gilroy, Rachel A. J. Griffith, Luke Sethi, Dheeraj K. Aggarwal, Dinesh Brown, Colin S. Davidson, Rose K. Kingsley, Robert A. Bedford, Luke Coupland, Lindsay J. Charles, Ian G. Elumogo, Ngozi Wain, John Prakash, Reenesh Webber, Mark A. Smith, S. J. Louise Chand, Meera Dervisevic, Samir O’Grady, Justin Microb Genom Research Articles The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organizations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1565 positive samples (172 per 100 000 population) from 1376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6 % of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. In total, 1035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a discrete sublineage associated with six care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients, indicating infection control measures were effective; and found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves. Microbiology Society 2021-06-29 /pmc/articles/PMC8461472/ /pubmed/34184982 http://dx.doi.org/10.1099/mgen.0.000589 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. The Microbiology Society waived the open access fees for this article.
spellingShingle Research Articles
Page, Andrew J.
Mather, Alison E.
Le-Viet, Thanh
Meader, Emma J.
Alikhan, Nabil-Fareed
Kay, Gemma L.
de Oliveira Martins, Leonardo
Aydin, Alp
Baker, David J.
Trotter, Alexander J.
Rudder, Steven
Tedim, Ana P.
Kolyva, Anastasia
Stanley, Rachael
Yasir, Muhammad
Diaz, Maria
Potter, Will
Stuart, Claire
Meadows, Lizzie
Bell, Andrew
Gutierrez, Ana Victoria
Thomson, Nicholas M.
Adriaenssens, Evelien M.
Swingler, Tracey
Gilroy, Rachel A. J.
Griffith, Luke
Sethi, Dheeraj K.
Aggarwal, Dinesh
Brown, Colin S.
Davidson, Rose K.
Kingsley, Robert A.
Bedford, Luke
Coupland, Lindsay J.
Charles, Ian G.
Elumogo, Ngozi
Wain, John
Prakash, Reenesh
Webber, Mark A.
Smith, S. J. Louise
Chand, Meera
Dervisevic, Samir
O’Grady, Justin
Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title_full Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title_fullStr Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title_full_unstemmed Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title_short Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
title_sort large-scale sequencing of sars-cov-2 genomes from one region allows detailed epidemiology and enables local outbreak management
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461472/
https://www.ncbi.nlm.nih.gov/pubmed/34184982
http://dx.doi.org/10.1099/mgen.0.000589
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