Literature DB >> 32835336

An integrated national scale SARS-CoV-2 genomic surveillance network.

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Year:  2020        PMID: 32835336      PMCID: PMC7266609          DOI: 10.1016/S2666-5247(20)30054-9

Source DB:  PubMed          Journal:  Lancet Microbe        ISSN: 2666-5247


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The Coronavirus Disease 2019 (COVID-19) Genomics UK Consortium (COG-UK) was launched in March, 2020, with £20 million support from UK Research and Innovation, the UK Department of Health and Social Care, and Wellcome Trust. The goal of this consortium is to sequence severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for up to 230 000 patients, health-care workers, and other essential workers in the UK with COVID-19, which will help to enable the tracking of SARS-CoV-2 transmission, identify viral mutations, and integrate with health data to assess how the viral genome interacts with cofactors and consequences of COVID-19. Results from this initiative are guiding decision makers, including the weekly reports to the UK Scientific Advisory Group for Emergencies (SAGE). This initiative is the first time that large-scale genomic epidemiology has been used to guide and inform the public health response to a pandemic in the UK, setting the stage for genomics to serve as a core tool for outbreak tracking in future pandemics. COG-UK builds on the UK's strengths in pathogen genomics, population health sciences, and health informatics. It benefits from a large and well equipped network of specialist academic and research facilities working in close collaboration with the UK's public health agencies and the National Health Service (NHS). Partners in COG-UK at the time of writing are shown in the appendix (p 4). As COG-UK's example could help to inform other countries seeking to rapidly develop and scale-up national sequencing capacity and a joined-up health information system, we describe six key features of our experience. COG-UK is co-ordinated from an integrated hub (based between the University of Cambridge [Cambridge, UK] and Wellcome Sanger Institute [Cambridge, UK]), with sample collection and sequencing taking place at multiple organisations across the country. This decentralised model enables rapid sequencing and prioritisation at the point of need, while supporting equitable national access. The core of COG-UK is formed around a network of regional sequencing centres in UK academic institutions and UK public health agencies. Sequencing in regional sequencing centres is close to real time, with a 24–48 h turnaround time, with data interpreted and used locally. In addition, the Wellcome Sanger Institute provides a high volume national sequencing capacity using high throughput, cost efficient viral sequencing for UK hospitals that do not have sequencing capabilities (ie, contributing partners), the national testing centres for key workers, and overspill from the regional sequencing centres. To help prioritise finite sequencing resources, COG-UK has developed a sampling strategy to concurrently enable broad population-level analyses, targeted analyses of specific populations, and freedom to tackle local priorities. This strategy aims to maximise insight while minimising demands on stretched local facilities. To maximise speed and inclusiveness, COG-UK adopts a range of technical approaches (ie, amplicons, baits, and metagenomics) and technologies (ie, single molecule vs next generation sequencing approaches), enabling centres to build on existing pipelines and expertise. Several centres have adopted a tiling amplicon sequencing approach developed by the ARTIC network, which is run on multiple platforms to help achieve the very high sample throughput required. Tight linkage to diagnostic and public health laboratories minimises transport and analysis delays. The system needs to be continuous and rapid, with a target of 48 h from sample collection to analysis. Sequence data are uploaded to the Cloud Infrastructure for Microbial Bioinformatics (MRC-CLIMB) server; a centralised, replicated environment for data storage and analysis. MRC-CLIMB provides a ready-made starting point for the computational analysis, with the option to integrate with other resources within the UK or scale into the commercial cloud. A standardised lineage assignment to enable national and international comparison has been developed, which are linked to data and released interactively via Microreact. Sequence data are made open access through release into the European Nucleotide Archive through the European Bioinformatics Institute and the Global Initiative on Sharing All Influenza Data. To enhance the value of sequence data, we are creating an integrated dataset connecting viral genome data with multidimensional patient data from clinical, epidemiological, and other sources. By accessing existing NHS e-health records and related sources, the goal is to avoid adding to the burden on busy NHS staff. Each week a sequence data cutoff is applied across the consortium to give a defined dataset for weekly analysis to report to SAGE, initially focusing on: (1) local transmission versus imported cases, (2) rates of epidemic growth,5, 6 (3) reconstructing spatial movement, (4) chains of transmission, (5) observed genetic changes, and (6) identification of genomic changes potentially affecting common diagnostic tests or direct (eg, chemotherapeutics) or indirect therapies. Our website will provide a publication strategy, including open access publications, bespoke local and regional analyses, and data summaries suitable for the general public. In only 4 weeks, over 7000 genomes have been sequenced by COG-UK, the largest number of any country to date. We are committed to open and global collaboration. Reciprocity is crucial to genomic epidemiological approaches; the use of our data will be maximised if other countries adopt similar approaches.
  6 in total

1.  Phylodynamics of infectious disease epidemics.

Authors:  Erik M Volz; Sergei L Kosakovsky Pond; Melissa J Ward; Andrew J Leigh Brown; Simon D W Frost
Journal:  Genetics       Date:  2009-09-21       Impact factor: 4.562

2.  Evolutionary dynamics of local pandemic H1N1/2009 influenza virus lineages revealed by whole-genome analysis.

Authors:  Gregory J Baillie; Monica Galiano; Paul-Michael Agapow; Richard Myers; Rachael Chiam; Astrid Gall; Anne L Palser; Simon J Watson; Jessica Hedge; Anthony Underwood; Steven Platt; Estelle McLean; Richard G Pebody; Andrew Rambaut; Jonathan Green; Rod Daniels; Oliver G Pybus; Paul Kellam; Maria Zambon
Journal:  J Virol       Date:  2011-10-19       Impact factor: 5.103

3.  CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community.

Authors:  Thomas R Connor; Nicholas J Loman; Simon Thompson; Andy Smith; Joel Southgate; Radoslaw Poplawski; Matthew J Bull; Emily Richardson; Matthew Ismail; Simon Elwood- Thompson; Christine Kitchen; Martyn Guest; Marius Bakke; Samuel K Sheppard; Mark J Pallen
Journal:  Microb Genom       Date:  2016-09-20

4.  Microreact: visualizing and sharing data for genomic epidemiology and phylogeography.

Authors:  Silvia Argimón; Khalil Abudahab; Richard J E Goater; Artemij Fedosejev; Jyothish Bhai; Corinna Glasner; Edward J Feil; Matthew T G Holden; Corin A Yeats; Hajo Grundmann; Brian G Spratt; David M Aanensen
Journal:  Microb Genom       Date:  2016-11-30

5.  Use of Whole-Genome Sequencing in the Investigation of a Nosocomial Influenza Virus Outbreak.

Authors:  Catherine F Houlihan; Dan Frampton; R Bridget Ferns; Jade Raffle; Paul Grant; Myriam Reidy; Leila Hail; Kirsty Thomson; Frank Mattes; Zisis Kozlakidis; Deenan Pillay; Andrew Hayward; Eleni Nastouli
Journal:  J Infect Dis       Date:  2018-09-22       Impact factor: 5.226

6.  Pandemic potential of a strain of influenza A (H1N1): early findings.

Authors:  Christophe Fraser; Christl A Donnelly; Simon Cauchemez; William P Hanage; Maria D Van Kerkhove; T Déirdre Hollingsworth; Jamie Griffin; Rebecca F Baggaley; Helen E Jenkins; Emily J Lyons; Thibaut Jombart; Wes R Hinsley; Nicholas C Grassly; Francois Balloux; Azra C Ghani; Neil M Ferguson; Andrew Rambaut; Oliver G Pybus; Hugo Lopez-Gatell; Celia M Alpuche-Aranda; Ietza Bojorquez Chapela; Ethel Palacios Zavala; Dulce Ma Espejo Guevara; Francesco Checchi; Erika Garcia; Stephane Hugonnet; Cathy Roth
Journal:  Science       Date:  2009-05-11       Impact factor: 47.728

  6 in total
  74 in total

1.  Stability of SARS-CoV-2 phylogenies.

Authors:  Yatish Turakhia; Nicola De Maio; Bryan Thornlow; Landen Gozashti; Robert Lanfear; Conor R Walker; Angie S Hinrichs; Jason D Fernandes; Rui Borges; Greg Slodkowicz; Lukas Weilguny; David Haussler; Nick Goldman; Russell Corbett-Detig
Journal:  PLoS Genet       Date:  2020-11-18       Impact factor: 5.917

2.  Transforming the UK's diagnostics agenda after COVID-19.

Authors:  Dimitris K Grammatopoulos; Lawrence Young; Neil R Anderson
Journal:  Lancet       Date:  2022-04-23       Impact factor: 79.321

3.  Identifying SARS-CoV-2 regional introductions and transmission clusters in real time.

Authors:  Jakob McBroome; Jennifer Martin; Adriano de Bernardi Schneider; Yatish Turakhia; Russell Corbett-Detig
Journal:  Virus Evol       Date:  2022-06-16

4.  Patterns of within-host genetic diversity in SARS-CoV-2.

Authors:  Gerry Tonkin-Hill; Inigo Martincorena; Roberto Amato; Andrew R J Lawson; Moritz Gerstung; Ian Johnston; David K Jackson; Naomi Park; Stefanie V Lensing; Michael A Quail; Sónia Gonçalves; Cristina Ariani; Michael Spencer Chapman; William L Hamilton; Luke W Meredith; Grant Hall; Aminu S Jahun; Yasmin Chaudhry; Myra Hosmillo; Malte L Pinckert; Iliana Georgana; Anna Yakovleva; Laura G Caller; Sarah L Caddy; Theresa Feltwell; Fahad A Khokhar; Charlotte J Houldcroft; Martin D Curran; Surendra Parmar; Alex Alderton; Rachel Nelson; Ewan M Harrison; John Sillitoe; Stephen D Bentley; Jeffrey C Barrett; M Estee Torok; Ian G Goodfellow; Cordelia Langford; Dominic Kwiatkowski
Journal:  Elife       Date:  2021-08-13       Impact factor: 8.140

5.  Initial Insights Into the Genetic Epidemiology of SARS-CoV-2 Isolates From Kerala Suggest Local Spread From Limited Introductions.

Authors:  Chandni Radhakrishnan; Mohit Kumar Divakar; Abhinav Jain; Prasanth Viswanathan; Rahul C Bhoyar; Bani Jolly; Mohamed Imran; Disha Sharma; Mercy Rophina; Gyan Ranjan; Paras Sehgal; Beena Philomina Jose; Rajendran Vadukkoot Raman; Thulaseedharan Nallaveettil Kesavan; Kalpana George; Sheela Mathew; Jayesh Kumar Poovullathil; Sajeeth Kumar Keeriyatt Govindan; Priyanka Raveendranadhan Nair; Shameer Vadekkandiyil; Vineeth Gladson; Midhun Mohan; Fairoz Cheriyalingal Parambath; Mohit Mangla; Afra Shamnath; Sridhar Sivasubbu; Vinod Scaria
Journal:  Front Genet       Date:  2021-03-17       Impact factor: 4.599

6.  Validation testing to determine the sensitivity of lateral flow testing for asymptomatic SARS-CoV-2 detection in low prevalence settings: Testing frequency and public health messaging is key.

Authors:  Jack Ferguson; Steven Dunn; Angus Best; Jeremy Mirza; Benita Percival; Megan Mayhew; Oliver Megram; Fiona Ashford; Thomas White; Emma Moles-Garcia; Liam Crawford; Tim Plant; Andrew Bosworth; Michael Kidd; Alex Richter; Jonathan Deeks; Alan McNally
Journal:  PLoS Biol       Date:  2021-04-29       Impact factor: 8.029

7.  Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity.

Authors:  Emma C Thomson; Laura E Rosen; James G Shepherd; Roberto Spreafico; Ana da Silva Filipe; Jason A Wojcechowskyj; Chris Davis; Luca Piccoli; David J Pascall; Josh Dillen; Spyros Lytras; Nadine Czudnochowski; Rajiv Shah; Marcel Meury; Natasha Jesudason; Anna De Marco; Kathy Li; Jessica Bassi; Aine O'Toole; Dora Pinto; Rachel M Colquhoun; Katja Culap; Ben Jackson; Fabrizia Zatta; Andrew Rambaut; Stefano Jaconi; Vattipally B Sreenu; Jay Nix; Ivy Zhang; Ruth F Jarrett; William G Glass; Martina Beltramello; Kyriaki Nomikou; Matteo Pizzuto; Lily Tong; Elisabetta Cameroni; Tristan I Croll; Natasha Johnson; Julia Di Iulio; Arthur Wickenhagen; Alessandro Ceschi; Aoife M Harbison; Daniel Mair; Paolo Ferrari; Katherine Smollett; Federica Sallusto; Stephen Carmichael; Christian Garzoni; Jenna Nichols; Massimo Galli; Joseph Hughes; Agostino Riva; Antonia Ho; Marco Schiuma; Malcolm G Semple; Peter J M Openshaw; Elisa Fadda; J Kenneth Baillie; John D Chodera; Suzannah J Rihn; Samantha J Lycett; Herbert W Virgin; Amalio Telenti; Davide Corti; David L Robertson; Gyorgy Snell
Journal:  Cell       Date:  2021-01-28       Impact factor: 66.850

8.  SARS-CoV-2 within-host diversity and transmission.

Authors:  Katrina A Lythgoe; Matthew Hall; Luca Ferretti; Mariateresa de Cesare; George MacIntyre-Cockett; Amy Trebes; Monique Andersson; Newton Otecko; Emma L Wise; Nathan Moore; Jessica Lynch; Stephen Kidd; Nicholas Cortes; Matilde Mori; Rebecca Williams; Gabrielle Vernet; Anita Justice; Angie Green; Samuel M Nicholls; M Azim Ansari; Lucie Abeler-Dörner; Catrin E Moore; Timothy E A Peto; David W Eyre; Robert Shaw; Peter Simmonds; David Buck; John A Todd; Thomas R Connor; Shirin Ashraf; Ana da Silva Filipe; James Shepherd; Emma C Thomson; David Bonsall; Christophe Fraser; Tanya Golubchik
Journal:  Science       Date:  2021-03-09       Impact factor: 47.728

9.  Molecular epidemiology of SARS-CoV-2 in Cyprus.

Authors:  Jan Richter; Pavlos Fanis; Christina Tryfonos; Dana Koptides; George Krashias; Stavros Bashiardes; Andreas Hadjisavvas; Maria Loizidou; Anastasis Oulas; Denise Alexandrou; Olga Kalakouta; Mihalis I Panayiotidis; George M Spyrou; Christina Christodoulou
Journal:  PLoS One       Date:  2021-07-21       Impact factor: 3.240

10.  CLIMB-COVID: continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance.

Authors:  Samuel M Nicholls; Radoslaw Poplawski; Matthew J Bull; Anthony Underwood; Michael Chapman; Khalil Abu-Dahab; Ben Taylor; Rachel M Colquhoun; Will P M Rowe; Ben Jackson; Verity Hill; Áine O'Toole; Sara Rey; Joel Southgate; Roberto Amato; Rich Livett; Sónia Gonçalves; Ewan M Harrison; Sharon J Peacock; David M Aanensen; Andrew Rambaut; Thomas R Connor; Nicholas J Loman
Journal:  Genome Biol       Date:  2021-07-01       Impact factor: 13.583

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