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, The COVID-19 Genomics UK (COG-UK) consortium, , Bashton, Matthew, Smith, Darren, Nelson, Andrew, Young, Greg and McCann, Clare (2021) Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management. Microbial Genomics, 7 (6). 000589. ISSN 2057-5858

Full text not available from this repository. (Request a copy)

Abstract

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.

Item Type:	Article
Additional Information:	Matthew Bashton, Darren L. Smith, Gregory R. Young, Clare McCann and Andrew Nelson are member of the COVID-19 Genomics UK (COG-UK) Consortium. Funding information: The authors gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC); this research was funded by the BBSRC Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent projects BBS/E/ F/000PR10348, BBS/E/F/000PR10349, BBS/E/F/000PR10351 and BBS/E/F/000PR10352. D.J.B., N.F.A., T.L.V. and A.J.P. were supported by the Quadram Institute Bioscience BBSRC-funded Core Capability Grant (project number BB/CCG1860/1). E.M.A. was funded by the BBSRC Institute Strategic Programme Gut Microbes and Health BB/R012490/1 and its constituent project(s) BBS/E/F/000PR10353 and BBS/E/ F/000PR10356. The sequencing costs were funded by the COVID-19 Genomics UK (COG-UK) Consortium which is supported by funding from the Medical Research Council (MRC) part of UK Research and Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. The author(s) gratefully acknowledge the UKRI Biotechnology and Biological Sciences Research Council’s (BBSRC) support of The Norwich Research Park Biorepository. L.G. was supported by a DART MRC iCASE and Roche Diagnostics. A.P.T. was funded by Sara Borrell Research Grant CD018/0123 from ISCIII and co-financed by the European Development Regional Fund (A Way to Achieve Europe programme) and A.P.T.'s QIB internship was additionally funded by ‘Ayuda de la SEIMC’. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Uncontrolled Keywords:	ARTIC, genome, genomic epidemiology, NGS, SARS-CoV-2 and sequencing
Subjects:	B200 Pharmacology, Toxicology and Pharmacy C500 Microbiology C700 Molecular Biology, Biophysics and Biochemistry
Department:	Faculties > Health and Life Sciences > Applied Sciences
Depositing User:	Elena Carlaw
Date Deposited:	07 Sep 2021 15:01
Last Modified:	07 Sep 2021 15:01
URI:	http://nrl.northumbria.ac.uk/id/eprint/47096

Downloads