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Jelley L, Douglas J, O'Neill M, Berquist K, Claasen A, Wang J, Utekar S, Johnston H, Judy B, Allais M, de Ligt J, Tan CE, Seeds R, Wood T, Aminisani N, Jennings T, Welch D, Turner N, McIntyre P, Dowell T, Trenholme A, Byrnes C, Webby R, French N, Winter D, Huang QS, Geoghegan JL. Spatial and temporal transmission dynamics of respiratory syncytial virus in New Zealand before and after the COVID-19 pandemic. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.15.24310412. [PMID: 39072023 PMCID: PMC11275701 DOI: 10.1101/2024.07.15.24310412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Human respiratory syncytial virus (RSV) is a major cause of acute respiratory infection. In 2020, RSV was effectively eliminated from the community in New Zealand due to non-pharmaceutical interventions (NPI) used to control the spread of COVID-19. However, in April 2021, following a brief quarantine-free travel agreement with Australia, there was a large-scale nationwide outbreak of RSV that led to reported cases more than five times higher, and hospitalisations more than three times higher, than the typical seasonal pattern. In this study, we generated 1,471 viral genomes of both RSV-A and RSV-B sampled between 2015 and 2022 from across New Zealand. Using a phylodynamics approach, we used these data to better understand RSV transmission patterns in New Zealand prior to 2020, and how RSV became re-established in the community following the relaxation of COVID-19 restrictions. We found that in 2021, there was a large epidemic of RSV in New Zealand that affected a broader age group range compared to the usual pattern of RSV infections. This epidemic was due to an increase in RSV importations, leading to several large genomic clusters of both RSV-A ON1 and RSV-B BA9 genotypes in New Zealand. However, while a number of importations were detected, there was also a major reduction in RSV genetic diversity compared to pre-pandemic seasonal outbreaks. These genomic clusters were temporally associated with the increase of migration in 2021 due to quarantine-free travel from Australia at the time. The closest genetic relatives to the New Zealand RSV genomes, when sampled, were viral genomes sampled in Australia during a large, off-season summer outbreak several months prior, rather than cryptic lineages that were sustained but not detected in New Zealand. These data reveal the impact of NPI used during the COVID-19 pandemic on other respiratory infections and highlight the important insights that can be gained from viral genomes.
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Rudar J, Kruczkiewicz P, Vernygora O, Golding GB, Hajibabaei M, Lung O. Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source. Microbiol Spectr 2024; 12:e0358423. [PMID: 38436242 PMCID: PMC10986507 DOI: 10.1128/spectrum.03584-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 02/11/2024] [Indexed: 03/05/2024] Open
Abstract
We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.
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Affiliation(s)
- Josip Rudar
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
- Department of Integrative Biology & Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Peter Kruczkiewicz
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Oksana Vernygora
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - G. Brian Golding
- Department of Biology, McMaster University, Hamilton, Ontario, Canada
| | - Mehrdad Hajibabaei
- Department of Integrative Biology & Centre for Biodiversity Genomics, University of Guelph, Guelph, Ontario, Canada
| | - Oliver Lung
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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3
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Wilson C, Thomson EC. Resilience to emerging infectious diseases and the importance of scientific innovation. Future Healthc J 2024; 11:100023. [PMID: 38646044 PMCID: PMC11025050 DOI: 10.1016/j.fhj.2024.100023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
This opinion piece emphasies the critical role of translational research in enhancing the UK's resilience against future pandemics. The COVID-19 pandemic demonstrated the lifesaving potential of scientific innovation, including genomic tracking of SARS-CoV-2, vaccine development, data linkage, modelling, and new treatments. These advances, achieved through collaborations between academic institutions, industry, government, public health bodies, and the NHS, occurred at an unprecedented pace. However, the UK's pandemic preparedness planning, as reflected in the 2016 Exercise Cygnus report, notably lacked provision for scientific innovation. This oversight highlights the necessity of integrating innovation and research into future preparedness strategies, not as a luxury but as a vital component of the healthcare infrastructure. The COVID-19 pandemic has underlined the importance of surge capacity for diagnostic labs, vaccine development and deployment strategies, real-time research embedded within the NHS, efficient data sharing, clear public communication, and the use of genomic tools for outbreak surveillance and monitoring pathogen response. Despite world-leading aspects of some of the UK's research response, the need to build much of the infrastructure in real-time led to avoidable delays. A proactive approach in incorporating research and innovation into the NHS's operational framework will be needed to ensure swift, evidence-based responses to future pandemics.
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Affiliation(s)
| | - Emma C. Thomson
- NHS Greater Glasgow & Clyde (NHS GG&C), Glasgow, United Kingdom
- MRC-University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- London School of Hygiene and Tropical Medicine (LSHTM), London, United Kingdom
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4
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Reuschl AK, Thorne LG, Whelan MVX, Ragazzini R, Furnon W, Cowton VM, De Lorenzo G, Mesner D, Turner JLE, Dowgier G, Bogoda N, Bonfanti P, Palmarini M, Patel AH, Jolly C, Towers GJ. Evolution of enhanced innate immune suppression by SARS-CoV-2 Omicron subvariants. Nat Microbiol 2024; 9:451-463. [PMID: 38228858 PMCID: PMC10847042 DOI: 10.1038/s41564-023-01588-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/13/2023] [Indexed: 01/18/2024]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human adaptation resulted in distinct lineages with enhanced transmissibility called variants of concern (VOCs). Omicron is the first VOC to evolve distinct globally dominant subvariants. Here we compared their replication in human cell lines and primary airway cultures and measured host responses to infection. We discovered that subvariants BA.4 and BA.5 have improved their suppression of innate immunity when compared with earlier subvariants BA.1 and BA.2. Similarly, more recent subvariants (BA.2.75 and XBB lineages) also triggered reduced innate immune activation. This correlated with increased expression of viral innate antagonists Orf6 and nucleocapsid, reminiscent of VOCs Alpha to Delta. Increased Orf6 levels suppressed host innate responses to infection by decreasing IRF3 and STAT1 signalling measured by transcription factor phosphorylation and nuclear translocation. Our data suggest that convergent evolution of enhanced innate immune antagonist expression is a common pathway of human adaptation and link Omicron subvariant dominance to improved innate immune evasion.
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Affiliation(s)
| | - Lucy G Thorne
- Division of Infection and Immunity, University College London, London, UK
- Department of Infectious Diseases, St Mary's Medical School, Imperial College London, London, UK
| | - Matthew V X Whelan
- Division of Infection and Immunity, University College London, London, UK
| | - Roberta Ragazzini
- Division of Infection and Immunity, University College London, London, UK
- Epithelial Stem Cell Biology and Regenerative Medicine Laboratory, The Francis Crick Institute, London, UK
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Vanessa M Cowton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | - Dejan Mesner
- Division of Infection and Immunity, University College London, London, UK
| | - Jane L E Turner
- Division of Infection and Immunity, University College London, London, UK
| | - Giulia Dowgier
- Division of Infection and Immunity, University College London, London, UK
- COVID Surveillance Unit, The Francis Crick Institute, London, UK
| | - Nathasha Bogoda
- Division of Infection and Immunity, University College London, London, UK
| | - Paola Bonfanti
- Division of Infection and Immunity, University College London, London, UK
- Epithelial Stem Cell Biology and Regenerative Medicine Laboratory, The Francis Crick Institute, London, UK
| | | | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Clare Jolly
- Division of Infection and Immunity, University College London, London, UK.
| | - Greg J Towers
- Division of Infection and Immunity, University College London, London, UK.
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5
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Lamb KD, Luka MM, Saathoff M, Orton RJ, Phan MVT, Cotten M, Yuan K, Robertson DL. Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules. PLoS Comput Biol 2024; 20:e1011795. [PMID: 38271457 PMCID: PMC10868779 DOI: 10.1371/journal.pcbi.1011795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 02/15/2024] [Accepted: 01/03/2024] [Indexed: 01/27/2024] Open
Abstract
The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.
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Affiliation(s)
- Kieran D. Lamb
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
- School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Martha M. Luka
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
- School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Megan Saathoff
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
| | - Richard J. Orton
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
| | - My V. T. Phan
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- College of Health Solutions, Arizona State University, Phoenix, Arizona, United States of America
| | - Matthew Cotten
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- College of Health Solutions, Arizona State University, Phoenix, Arizona, United States of America
- Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, Arizona, United States of America
| | - Ke Yuan
- School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom
- School of Cancer Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom
- Cancer Research UK Scotland Institute, Glasgow, Scotland, United Kingdom
| | - David L. Robertson
- Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom
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Meiseles A, Motro Y, Rokach L, Moran-Gilad J. Vulnerability of pangolin SARS-CoV-2 lineage assignment to adversarial attack. Artif Intell Med 2023; 146:102722. [PMID: 38042605 DOI: 10.1016/j.artmed.2023.102722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/14/2023] [Accepted: 11/14/2023] [Indexed: 12/04/2023]
Abstract
Pangolin is the most popular tool for SARS-CoV-2 lineage assignment. During COVID-19, healthcare professionals and policymakers required accurate and timely lineage assignment of SARS-CoV-2 genomes for pandemic response. Therefore, tools such as Pangolin use a machine learning model, pangoLEARN, for fast and accurate lineage assignment. Unfortunately, machine learning models are susceptible to adversarial attacks, in which minute changes to the inputs cause substantial changes in the model prediction. We present an attack that uses the pangoLEARN architecture to find perturbations that change the lineage assignment, often with only 2-3 base pair changes. The attacks we carried out show that pangolin is vulnerable to adversarial attack, with success rates between 0.98 and 1 for sequences from non-VoC lineages when pangoLEARN is used for lineage assignment. The attacks we carried out are almost never successful against VoC lineages because pangolin uses Usher and Scorpio - the non-machine-learning alternative methods for VoC lineage assignment. A malicious agent could use the proposed attack to fake or mask outbreaks or circulating lineages. Developers of software in the field of microbial genomics should be aware of the vulnerabilities of machine learning based models and mitigate such risks.
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Affiliation(s)
- Amiel Meiseles
- Dept. of Software and Information Systems Engineering, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Yair Motro
- Dept. of Health Policy and Management, School of Public Health, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Lior Rokach
- Dept. of Software and Information Systems Engineering, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Jacob Moran-Gilad
- Dept. of Health Policy and Management, School of Public Health, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel.
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7
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Laxton MR, Nightingale G, Lindgren F, Sivakumaran A, Othieno R. Extending the R number by applying hyperparameters of Log Gaussian Cox process models in an epidemiological context to provide insights into COVID-19 positivity in the City of Edinburgh and in students residing at Edinburgh University. PLoS One 2023; 18:e0291348. [PMID: 37988358 PMCID: PMC10662770 DOI: 10.1371/journal.pone.0291348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 08/29/2023] [Indexed: 11/23/2023] Open
Abstract
The impact of the COVID-19 pandemic on University students has been a topic of fiery debate and of public health research. This study demonstrates the use of a combination of spatiotemporal epidemiological models to describe the trends in COVID-19 positive cases on spatial, temporal and spatiotemporal scales. In addition, this study proposes new epidemiological metrics to describe the connectivity between observed positivity; an analogous metric to the R number in conventional epidemiology. The proposed indices, Rspatial, Rspatiotemporal and Rscaling will aim to improve the characterisation of the spread of infectious disease beyond that of the COVID-19 framework and as a result inform relevant public health policy. Apart from demonstrating the application of the novel epidemiological indices, the key findings in this study are: firstly, there were some Intermediate Zones in Edinburgh with noticeably high levels of COVID-19 positivity, and that the first outbreak during the study period was observed in Dalry and Fountainbridge. Secondly, the estimation of the distance over which the COVID-19 counts at the halls of residence are spatially correlated (or related to each other) was found to be 0.19km (0.13km to 0.27km) and is denoted by the index, Rspatial. This estimate is useful for public health policy in this setting, especially with contact tracing. Thirdly, the study indicates that the association between the surrounding community level of COVID-19 positivity (Intermediate Zones in Edinburgh) and that of the University of Edinburgh's halls of residence was not statistically significant. Fourthly, this study reveals that relatively high levels of COVID-19 positivity were observed for halls for which higher COVID-19 fines were issued (Spearman's correlation coefficient = 0.34), and separately, for halls which were non-ensuite relatively to those which were not (Spearman's correlation coefficient = 0.16). Finally, Intermediate Zones with the highest positivity were associated with student residences that experienced relatively high COVID-19 positivity (Spearman's correlation coefficient = 0.27).
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Affiliation(s)
- Megan Ruth Laxton
- School of Mathematics & Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Glenna Nightingale
- School of Health in Social Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Finn Lindgren
- School of Mathematics and Statistics, University of Edinburgh, Edinburgh, United Kingdom
| | - Arjuna Sivakumaran
- NHS Lothian, Department of Public Health and Health Policy, Scotland, United Kingdom
| | - Richard Othieno
- NHS Lothian, Department of Public Health and Health Policy, Scotland, United Kingdom
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8
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Tran M, Smurthwaite KS, Nghiem S, Cribb DM, Zahedi A, Ferdinand AD, Andersson P, Kirk MD, Glass K, Lancsar E. Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review. THE LANCET. MICROBE 2023; 4:e953-e962. [PMID: 37683688 DOI: 10.1016/s2666-5247(23)00180-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 09/10/2023]
Abstract
Whole-genome sequencing (WGS) has resulted in improvements to pathogen characterisation for the rapid investigation and management of disease outbreaks and surveillance. We conducted a systematic review to synthesise the economic evidence of WGS implementation for pathogen identification and surveillance. Of the 2285 unique publications identified through online database searches, 19 studies met the inclusion criteria. The economic evidence to support the broader application of WGS as a front-line pathogen characterisation and surveillance tool is insufficient and of low quality. WGS has been evaluated in various clinical settings, but these evaluations are predominantly investigations of a single pathogen. There are also considerable variations in the evaluation approach. Economic evaluations of costs, effectiveness, and cost-effectiveness are needed to support the implementation of WGS in public health settings.
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Affiliation(s)
- My Tran
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia.
| | - Kayla S Smurthwaite
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Son Nghiem
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Danielle M Cribb
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Alireza Zahedi
- Public Health Microbiology, Forensic and Scientific Services, Queensland Health, Brisbane QLD, Australia
| | - Angeline D Ferdinand
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Patiyan Andersson
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Martyn D Kirk
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Kathryn Glass
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Emily Lancsar
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
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9
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Kashima Y, Mizutani T, Okimoto Y, Maeda M, Musashino K, Nishide RI, Matsukura A, Nagase J, Suzuki Y. Evolution of the viral genomes of SARS-CoV-2 in association with the changes in local condition: a genomic epidemiological study of a suburban city of Japan. DNA Res 2023; 30:dsad020. [PMID: 37712596 PMCID: PMC10562954 DOI: 10.1093/dnares/dsad020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 09/01/2023] [Accepted: 09/14/2023] [Indexed: 09/16/2023] Open
Abstract
Understanding the factors driving the spread and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the local, regional, national, and international levels is important in protecting against future pandemics. By exploring their viral genomes, we attempted to analyse the spread of SARS-CoV-2 and its evolutionary convergence in Kashiwa City, as an example of a representative commuter town in Japan. From September 2020 to January 2023, a total of 47,134 nasopharyngeal swab and saliva specimens were collected from patients in 47 local clinics and hospitals, covering the vast majority of healthcare facilities. All SARS-CoV-2-positive samples were subjected to whole genome sequencing. Based on the analysis of 5,536 identified genomes, all major strains were represented. Unique regional mutations were occasionally identified in each strain. Inspection of these mutations revealed that the overall base substitution rate increased with progressive waves of the pandemic, at an overall rate of 2.56 bases/year. Interestingly, the spread and evolutionary patterns appeared to be distinct between regions and between individual clinics. Further analysis of the synonymous base substitution rate showed that the speed of viral evolution accelerated coincident with the beginning of public vaccination. Comprehensive genomic epidemiological studies, as presented here, should be useful in precisely understanding the pandemic and preparing for possible future pandemics.
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Affiliation(s)
- Yukie Kashima
- Laboratory of Functional Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Taketoshi Mizutani
- Laboratory of Functional Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Yuki Okimoto
- Kashiwa City Public Health Center, Kashiwa City, Chiba, Japan
| | - Minami Maeda
- Alluminox and Corporate Development, Rakuten Medical K.K., Tokyo, Japan
| | | | | | | | | | - Yutaka Suzuki
- Laboratory of Functional Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
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10
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Salzberger B, Mellmann A, Bludau A, Ciesek S, Corman V, Dilthey A, Donker T, Eckmanns T, Egelkamp R, Gatermann SG, Grundmann H, Häcker G, Kaase M, Lange B, Mielke M, Pletz MW, Semmler T, Thürmer A, Wieler LH, Wolff T, Widmer AF, Scheithauer S. An appeal for strengthening genomic pathogen surveillance to improve pandemic preparedness and infection prevention: the German perspective. Infection 2023:10.1007/s15010-023-02040-9. [PMID: 37129842 PMCID: PMC10152431 DOI: 10.1007/s15010-023-02040-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 04/13/2023] [Indexed: 05/03/2023]
Abstract
The SARS-CoV-2 pandemic has highlighted the importance of viable infection surveillance and the relevant infrastructure. From a German perspective, an integral part of this infrastructure, genomic pathogen sequencing, was at best fragmentary and stretched to its limits due to the lack or inefficient use of equipment, human resources, data management and coordination. The experience in other countries has shown that the rate of sequenced positive samples and linkage of genomic and epidemiological data (person, place, time) represent important factors for a successful application of genomic pathogen surveillance. Planning, establishing and consistently supporting adequate structures for genomic pathogen surveillance will be crucial to identify and combat future pandemics as well as other challenges in infectious diseases such as multi-drug resistant bacteria and healthcare-associated infections. Therefore, the authors propose a multifaceted and coordinated process for the definition of procedural, legal and technical standards for comprehensive genomic pathogen surveillance in Germany, covering the areas of genomic sequencing, data collection and data linkage, as well as target pathogens. A comparative analysis of the structures established in Germany and in other countries is applied. This proposal aims to better tackle epi- and pandemics to come and take action from the "lessons learned" from the SARS-CoV-2 pandemic.
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Affiliation(s)
- Bernd Salzberger
- Department for Infection Control and Infectious Diseases, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | - Alexander Mellmann
- Institute for Hygiene, University Hospital Münster, Robert-Koch-Straße 41, 48149, Münster, Germany.
| | - Anna Bludau
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Sandra Ciesek
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt Am Main, Germany
| | - Victor Corman
- Institute of Virology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Alexander Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Tjibbe Donker
- Institute for Infection Prevention and Hospital Epidemiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Richard Egelkamp
- Next Generation Sequencing, Public Health Agency of Lower Saxony, Hanover, Germany
| | - Sören G Gatermann
- Department of Medical Microbiology, Ruhr University Bochum, Bochum, Germany
| | - Hajo Grundmann
- Institute for Infection Prevention and Hospital Epidemiology, University Medical Center Freiburg, Freiburg, Germany
| | - Georg Häcker
- Faculty of Medicine, Institute of Medical Microbiology and Hygiene, Medical Centre University of Freiburg, Freiburg, Germany
| | - Martin Kaase
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Berit Lange
- Department of Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | | | - Mathias W Pletz
- Institute of Infectious Diseases and Infection Control, University Hospital, Jena, Germany
| | | | | | | | | | - Andreas F Widmer
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Simone Scheithauer
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany.
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11
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Pascall DJ, Vink E, Blacow R, Bulteel N, Campbell A, Campbell R, Clifford S, Davis C, da Silva Filipe A, El Sakka N, Fjodorova L, Forrest R, Goldstein E, Gunson R, Haughney J, Holden MTG, Honour P, Hughes J, James E, Lewis T, Lycett S, MacLean O, McHugh M, Mollett G, Onishi Y, Parcell B, Ray S, Robertson DL, Shabaan S, Shepherd JG, Smollett K, Templeton K, Wastnedge E, Wilkie C, Williams T, Thomson EC. The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: A genomics-based retrospective cohort analysis. PLoS One 2023; 18:e0284187. [PMID: 37053201 PMCID: PMC10101505 DOI: 10.1371/journal.pone.0284187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 03/24/2023] [Indexed: 04/14/2023] Open
Abstract
OBJECTIVES The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. METHODS In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. RESULTS Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus pre-Alpha variants). CONCLUSIONS The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.
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Affiliation(s)
- David J. Pascall
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- Joint Universities Pandemic and Epidemiological Research (JUNIPER) Consortium, United Kingdom
| | - Elen Vink
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- NHS Lothian, Edinburgh, United Kingdom
| | - Rachel Blacow
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- NHS Greater Glasgow and Clyde, Glasgow, United Kingdom
| | | | | | | | | | - Chris Davis
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Ana da Silva Filipe
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | | | | | | | | | - Rory Gunson
- NHS Greater Glasgow and Clyde, Glasgow, United Kingdom
| | - John Haughney
- NHS Greater Glasgow and Clyde, Glasgow, United Kingdom
| | - Matthew T. G. Holden
- Public Health Scotland, Edinburgh, United Kingdom
- School of Medicine, University of St Andrews, St Andrews, Fife, United Kingdom
| | | | - Joseph Hughes
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Edward James
- NHS Borders, Melrose, Scottish Borders, United Kingdom
| | - Tim Lewis
- NHS Lothian, Edinburgh, United Kingdom
| | - Samantha Lycett
- The Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
| | - Oscar MacLean
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | | | - Guy Mollett
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- NHS Greater Glasgow and Clyde, Glasgow, United Kingdom
| | | | - Ben Parcell
- School of Life Sciences, University of Dundee, Dundee, United Kingdom
| | - Surajit Ray
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
| | - David L. Robertson
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | | | - James G. Shepherd
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | - Katherine Smollett
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
| | | | | | - Craig Wilkie
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Thomas Williams
- NHS Lothian, Edinburgh, United Kingdom
- Royal Hospital for Children and Young People, University of Edinburgh, Edinburgh, United Kingdom
| | - Emma C. Thomson
- MRC–University of Glasgow Centre for Virus Research (CVR), Glasgow, United Kingdom
- NHS Greater Glasgow and Clyde, Glasgow, United Kingdom
- London School of Hygiene and Tropical Medicine, London, United Kingdom
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12
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De Maio N, Kalaghatgi P, Turakhia Y, Corbett-Detig R, Minh BQ, Goldman N. Maximum likelihood pandemic-scale phylogenetics. Nat Genet 2023; 55:746-752. [PMID: 37038003 PMCID: PMC10181937 DOI: 10.1038/s41588-023-01368-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 03/07/2023] [Indexed: 04/12/2023]
Abstract
Phylogenetics has a crucial role in genomic epidemiology. Enabled by unparalleled volumes of genome sequence data generated to study and help contain the COVID-19 pandemic, phylogenetic analyses of SARS-CoV-2 genomes have shed light on the virus's origins, spread, and the emergence and reproductive success of new variants. However, most phylogenetic approaches, including maximum likelihood and Bayesian methods, cannot scale to the size of the datasets from the current pandemic. We present 'MAximum Parsimonious Likelihood Estimation' (MAPLE), an approach for likelihood-based phylogenetic analysis of epidemiological genomic datasets at unprecedented scales. MAPLE infers SARS-CoV-2 phylogenies more accurately than existing maximum likelihood approaches while running up to thousands of times faster, and requiring at least 100 times less memory on large datasets. This extends the reach of genomic epidemiology, allowing the continued use of accurate phylogenetic, phylogeographic and phylodynamic analyses on datasets of millions of genomes.
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Affiliation(s)
- Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
| | | | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA, USA
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Bui Quang Minh
- School of Computing, College of Engineering, Computing and Cybernetics, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
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13
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Molina-Mora JA, Reales-González J, Camacho E, Duarte-Martínez F, Tsukayama P, Soto-Garita C, Brenes H, Cordero-Laurent E, Ribeiro dos Santos A, Guedes Salgado C, Santos Silva C, Santana de Souza J, Nunes G, Negri T, Vidal A, Oliveira R, Oliveira G, Muñoz-Medina JE, Salas-Lais AG, Mireles-Rivera G, Sosa E, Turjanski A, Monzani MC, Carobene MG, Remes Lenicov F, Schottlender G, Fernández Do Porto DA, Kreuze JF, Sacristán L, Guevara-Suarez M, Cristancho M, Campos-Sánchez R, Herrera-Estrella A. Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021. Front Public Health 2023; 11:1095202. [PMID: 36935725 PMCID: PMC10018007 DOI: 10.3389/fpubh.2023.1095202] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Latin America is one of the regions in which the COVID-19 pandemic has a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia, and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1,534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.
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Affiliation(s)
- Jose Arturo Molina-Mora
- Centro de investigación en Enfermedades Tropicales and Facultad de Microbiología, Universidad de Costa Rica, San José, Costa Rica
- *Correspondence: Jose Arturo Molina-Mora
| | | | - Erwin Camacho
- Investigaciones Biomédicas, Universidad de Sucre, Sincelejo, Colombia
| | - Francisco Duarte-Martínez
- Laboratorio de Genómica y Biología Molecular, Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud, Tres Ríos, Cartago, Costa Rica
| | - Pablo Tsukayama
- Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Claudio Soto-Garita
- Laboratorio de Genómica y Biología Molecular, Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud, Tres Ríos, Cartago, Costa Rica
| | - Hebleen Brenes
- Laboratorio de Genómica y Biología Molecular, Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud, Tres Ríos, Cartago, Costa Rica
| | - Estela Cordero-Laurent
- Laboratorio de Genómica y Biología Molecular, Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud, Tres Ríos, Cartago, Costa Rica
| | | | | | - Caio Santos Silva
- Instituto de Ciências Biológica, Universidade Federal do Pará, Belém, Brazil
| | | | - Gisele Nunes
- Environmental Genomics, Vale Institute of Technology, Belém, Pará, Brazil
| | - Tatianne Negri
- Environmental Genomics, Vale Institute of Technology, Belém, Pará, Brazil
| | - Amanda Vidal
- Environmental Genomics, Vale Institute of Technology, Belém, Pará, Brazil
| | - Renato Oliveira
- Environmental Genomics, Vale Institute of Technology, Belém, Pará, Brazil
| | - Guilherme Oliveira
- Environmental Genomics, Vale Institute of Technology, Belém, Pará, Brazil
| | - José Esteban Muñoz-Medina
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de Mexico, Mexico
| | - Angel Gustavo Salas-Lais
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de Mexico, Mexico
| | - Guadalupe Mireles-Rivera
- Laboratorio Nacional de Genómica para la Biodiversidad-Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Irapuato, Mexico
| | - Ezequiel Sosa
- Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Adrián Turjanski
- Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - María Cecilia Monzani
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
- Facultad de Medicina de la Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Mauricio G. Carobene
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
- Facultad de Medicina de la Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Federico Remes Lenicov
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
- Facultad de Medicina de la Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Gustavo Schottlender
- Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | | | | | - Luisa Sacristán
- Vicerrectoria de Investigación y Creación, Universidad de Los Andes, Bogotá, Colombia
| | | | - Marco Cristancho
- Vicerrectoria de Investigación y Creación, Universidad de Los Andes, Bogotá, Colombia
| | - Rebeca Campos-Sánchez
- Centro de Investigación en Biología Celular y Molecular, Universidad de Costa Rica, San José, Costa Rica
| | - Alfredo Herrera-Estrella
- Laboratorio Nacional de Genómica para la Biodiversidad-Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Irapuato, Mexico
- Alfredo Herrera-Estrella
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14
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Lista MJ, Winstone H, Wilson HD, Dyer A, Pickering S, Galao RP, De Lorenzo G, Cowton VM, Furnon W, Suarez N, Orton R, Palmarini M, Patel AH, Snell L, Nebbia G, Swanson C, Neil SJD. The P681H Mutation in the Spike Glycoprotein of the Alpha Variant of SARS-CoV-2 Escapes IFITM Restriction and Is Necessary for Type I Interferon Resistance. J Virol 2022; 96:e0125022. [PMID: 36350154 PMCID: PMC9749455 DOI: 10.1128/jvi.01250-22] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/10/2022] [Indexed: 11/11/2022] Open
Abstract
The appearance of new dominant variants of concern (VOC) of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) threatens the global response to the coronavirus disease 2019 (COVID-19) pandemic. Of these, the alpha variant (also known as B.1.1.7), which appeared initially in the United Kingdom, became the dominant variant in much of Europe and North America in the first half of 2021. The spike (S) glycoprotein of alpha acquired seven mutations and two deletions compared to the ancestral virus, including the P681H mutation adjacent to the polybasic cleavage site, which has been suggested to enhance S cleavage. Here, we show that the alpha spike protein confers a level of resistance to beta interferon (IFN-β) in human lung epithelial cells. This correlates with resistance to an entry restriction mediated by interferon-induced transmembrane protein 2 (IFITM2) and a pronounced infection enhancement by IFITM3. Furthermore, the P681H mutation is essential for resistance to IFN-β and context-dependent resistance to IFITMs in the alpha S. P681H reduces dependence on endosomal cathepsins, consistent with enhanced cell surface entry. However, reversion of H681 does not reduce cleaved spike incorporation into particles, indicating that it exerts its effect on entry and IFN-β downstream of furin cleavage. Overall, we suggest that, in addition to adaptive immune escape, mutations associated with VOC may well also confer a replication and/or transmission advantage through adaptation to resist innate immune mechanisms. IMPORTANCE Accumulating evidence suggests that variants of concern (VOC) of SARS-CoV-2 evolve to evade the human immune response, with much interest focused on mutations in the spike protein that escape from antibodies. However, resistance to the innate immune response is essential for efficient viral replication and transmission. Here, we show that the alpha (B.1.1.7) VOC of SARS-CoV-2 is substantially more resistant to type I interferons than the parental Wuhan-like virus. This correlates with resistance to the antiviral protein IFITM2 and enhancement by its paralogue IFITM3. The key determinant of this is a proline-to-histidine change at position 681 in S adjacent to the furin cleavage site, which in the context of the alpha spike modulates cell entry pathways of SARS-CoV-2. Reversion of the mutation is sufficient to restore interferon and IFITM2 sensitivity, highlighting the dynamic nature of the SARS CoV-2 as it adapts to both innate and adaptive immunity in the humans.
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Affiliation(s)
- Maria Jose Lista
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Helena Winstone
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Harry D. Wilson
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Adam Dyer
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Suzanne Pickering
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Rui Pedro Galao
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Giuditta De Lorenzo
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Vanessa M. Cowton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Nicolas Suarez
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Richard Orton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Arvind H. Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
| | - Luke Snell
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Gaia Nebbia
- Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Chad Swanson
- Department of Infectious Diseases, King’s College London, London, United Kingdom
| | - Stuart J. D. Neil
- Department of Infectious Diseases, King’s College London, London, United Kingdom
- UKRI Genotype-2-Phenotype Consortium, London, United Kingdom
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15
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Zhao LP, Lybrand TP, Gilbert PB, Payne TH, Pyo CW, Geraghty DE, Jerome KR. Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy. Sci Rep 2022; 12:19089. [PMID: 36352021 PMCID: PMC9645309 DOI: 10.1038/s41598-022-23342-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 10/30/2022] [Indexed: 11/11/2022] Open
Abstract
Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.37*10-4, 1.0*10-15, 4.76*10-7 and 1.56*10-4, respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p values < 1.0*10-15). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact remdesivir binding.
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Affiliation(s)
- Lue Ping Zhao
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Terry P Lybrand
- Quintepa Computing LLC, Nashville, TN, USA.
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA.
| | - Peter B Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Thomas H Payne
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Chul-Woo Pyo
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Daniel E Geraghty
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Keith R Jerome
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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16
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Makau DN, Lycett S, Michalska-Smith M, Paploski IAD, Cheeran MCJ, Craft ME, Kao RR, Schroeder DC, Doeschl-Wilson A, VanderWaal K. Ecological and evolutionary dynamics of multi-strain RNA viruses. Nat Ecol Evol 2022; 6:1414-1422. [PMID: 36138206 DOI: 10.1038/s41559-022-01860-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 07/28/2022] [Indexed: 11/09/2022]
Abstract
Potential interactions among co-circulating viral strains in host populations are often overlooked in the study of virus transmission. However, these interactions probably shape transmission dynamics by influencing host immune responses or altering the relative fitness among co-circulating strains. In this Review, we describe multi-strain dynamics from ecological and evolutionary perspectives, outline scales in which multi-strain dynamics occur and summarize important immunological, phylogenetic and mathematical modelling approaches used to quantify interactions among strains. We also discuss how host-pathogen interactions influence the co-circulation of pathogens. Finally, we highlight outstanding questions and knowledge gaps in the current theory and study of ecological and evolutionary dynamics of multi-strain viruses.
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Affiliation(s)
- Dennis N Makau
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | | | | | - Igor A D Paploski
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Maxim C-J Cheeran
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Meggan E Craft
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA
| | - Rowland R Kao
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Declan C Schroeder
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
- School of Biological Sciences, University of Reading, Reading, UK
| | | | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA.
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17
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Nadon C, Croxen M, Knox N, Tanner J, Zetner A, Yoshida C, Van Domselaar G. Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada’s public health laboratories. BMC Public Health 2022; 22:1817. [PMID: 36153510 PMCID: PMC9508744 DOI: 10.1186/s12889-022-14210-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 09/13/2022] [Indexed: 11/10/2022] Open
Abstract
Background Along with rapid diagnostic testing, contact tracing, and public health measures, an effective pandemic response incorporates genomics-based surveillance. Large-scale SARS-CoV-2 genome sequencing is a crucial component of the global response to COVID-19. Characterizing the state of genomics readiness among Canada’s public health laboratories was necessary to inform strategic planning and deployment of capacity-building resources in the early stages of the pandemic. Methods We used a qualitative study design and focus group discussions, encompassing both technical and leadership perspectives, to perform an in-depth evaluation of the state of pathogen genomics readiness in Canada. Results We found substantial diversity in the state of readiness for SARS-CoV-2 genomic surveillance across Canada. Despite this variability, we identified common barriers and needs in the areas of specimen access, data flow and sharing, computing infrastructure, and access to highly qualified bioinformatics personnel. Conclusions These findings enable the strategic prioritization and deployment of resources to increase Canada’s ability to perform effective public health genomic surveillance for COVID-19 and prepare for future emerging infectious diseases. They also provide a unique qualitative research model for use in capacity building. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-14210-9.
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18
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Attwood SW, Hill SC, Aanensen DM, Connor TR, Pybus OG. Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic. Nat Rev Genet 2022; 23:547-562. [PMID: 35459859 PMCID: PMC9028907 DOI: 10.1038/s41576-022-00483-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/23/2022] [Indexed: 01/05/2023]
Abstract
Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.
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Affiliation(s)
- Stephen W Attwood
- Department of Zoology, University of Oxford, Oxford, UK.
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK.
| | - Sarah C Hill
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Thomas R Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, Cardiff University, Cardiff, UK
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK.
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19
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Maestri S, Grosso V, Alfano M, Lavezzari D, Piubelli C, Bisoffi Z, Rossato M, Delledonne M. STArS (STrain-Amplicon-Seq), a targeted nanopore sequencing workflow for SARS-CoV-2 diagnostics and genotyping. Biol Methods Protoc 2022; 7:bpac020. [PMID: 36046362 PMCID: PMC9422081 DOI: 10.1093/biomethods/bpac020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/12/2022] [Indexed: 11/13/2022] Open
Abstract
Diagnostic tests based on reverse transcription-quantitative polymerase chain reaction (RT-qPCR) are the gold standard approach to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from clinical specimens. However, unless specifically optimized, this method is usually unable to recognize the specific viral strain responsible of coronavirus disease 2019, a crucial information that is proving increasingly important in relation to virus spread and treatment effectiveness. Even if some RT-qPCR commercial assays are currently being developed for the detection of viral strains, they focus only on single/few genetic variants that may not be sufficient to uniquely identify a specific strain. Therefore, genome sequencing approaches remain the most comprehensive solution for virus genotyping and to recognize viral strains, but their application is much less widespread due to higher costs. Starting from the well-established ARTIC protocol coupled to nanopore sequencing, in this work, we developed STArS (STrain-Amplicon-Seq), a cost/time-effective sequencing-based workflow for both SARS-CoV-2 diagnostics and genotyping. A set of 10 amplicons was initially selected from the ARTIC tiling panel, to cover: (i) all the main biologically relevant genetic variants located on the Spike gene; (ii) a minimal set of variants to uniquely identify the currently circulating strains; (iii) genomic sites usually amplified by RT-qPCR method to identify SARS-CoV-2 presence. PCR-amplified clinical samples (both positive and negative for SARS-CoV-2 presence) were pooled together with a serially diluted exogenous amplicon at known concentration and sequenced on a MinION device. Thanks to a scoring rule, STArS had the capability to accurately classify positive samples in agreement with RT-qPCR results, both at the qualitative and quantitative level. Moreover, the method allowed to effectively genotype strain-specific variants and thus also return the phylogenetic classification of SARS-CoV-2-postive samples. Thanks to the reduced turnaround time and costs, the proposed approach represents a step towards simplifying the clinical application of sequencing for viral genotyping, hopefully aiding in combatting the global pandemic.
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Affiliation(s)
- Simone Maestri
- Department of Biotechnology, University of Verona, 37134 Verona, Italy
- Center for Genomic Science of IIT@SEMM, Fondazione Istituto Italiano di Tecnologia, 20139 Milano, Italy
| | - Valentina Grosso
- Department of Biotechnology, University of Verona, 37134 Verona, Italy
| | | | - Denise Lavezzari
- Department of Biotechnology, University of Verona, 37134 Verona, Italy
| | - Chiara Piubelli
- Department of Infectious, Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Verona, Italy
| | - Zeno Bisoffi
- Department of Infectious, Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Verona, Italy
- Department of Diagnostics and Public Health, University of Verona, 37134, Verona, Italy
| | - Marzia Rossato
- Department of Biotechnology, University of Verona, 37134 Verona, Italy
- Genartis srl, 37126 Verona, Italy
| | - Massimo Delledonne
- Department of Biotechnology, University of Verona, 37134 Verona, Italy
- Genartis srl, 37126 Verona, Italy
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20
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Ye C, Thornlow B, Hinrichs A, Kramer A, Mirchandani C, Torvi D, Lanfear R, Corbett-Detig R, Turakhia Y. matOptimize: a parallel tree optimization method enables online phylogenetics for SARS-CoV-2. Bioinformatics 2022; 38:3734-3740. [PMID: 35731204 PMCID: PMC9344837 DOI: 10.1093/bioinformatics/btac401] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 05/21/2022] [Accepted: 06/16/2022] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Phylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the coronavirus disease 2019 (COVID-19) pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic. RESULTS Here, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. matOptimize is currently helping refine on a daily basis possibly the largest-ever phylogenetic tree, containing millions of SARS-CoV-2 sequences. AVAILABILITY AND IMPLEMENTATION The matOptimize code is freely available as part of the UShER package (https://github.com/yatisht/usher) and can also be installed via bioconda (https://bioconda.github.io/recipes/usher/README.html). All scripts we used to perform the experiments in this manuscript are available at https://github.com/yceh/matOptimize-experiments. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Cheng Ye
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA 92093, USA
| | - Bryan Thornlow
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Angie Hinrichs
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Alexander Kramer
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cade Mirchandani
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Devika Torvi
- Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA
| | - Robert Lanfear
- Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT 2601, Australia
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA 92093, USA
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21
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Ryutov A, Gai X, Ostrow D, Maglinte DT, Flores J, Salas EJ, Glucoft M, Smit M, Dien Bard J. Utility of viral whole-genome sequencing for institutional infection surveillance during the coronavirus disease 2019 (COVID-19) pandemic. Infect Control Hosp Epidemiol 2022; 43:1086-1088. [PMID: 33866984 PMCID: PMC8144805 DOI: 10.1017/ice.2021.185] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 04/11/2021] [Indexed: 01/19/2023]
Affiliation(s)
- Alex Ryutov
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
| | - Xiaowu Gai
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
- Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Dejerianne Ostrow
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
| | - Dennis T. Maglinte
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
| | - Jessica Flores
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
| | - Edahrline J. Salas
- Division of Infectious Diseases, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, California
| | - Marisa Glucoft
- Division of Infectious Diseases, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, California
| | - Michael Smit
- Keck School of Medicine, University of Southern California, Los Angeles, California
- Division of Infectious Diseases, Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, California
| | - Jennifer Dien Bard
- Department of Pathology and Laboratory Medicine, Children’s Hospital Los Angeles, Los Angeles, California
- Keck School of Medicine, University of Southern California, Los Angeles, California
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22
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Willett BJ, Grove J, MacLean OA, Wilkie C, De Lorenzo G, Furnon W, Cantoni D, Scott S, Logan N, Ashraf S, Manali M, Szemiel A, Cowton V, Vink E, Harvey WT, Davis C, Asamaphan P, Smollett K, Tong L, Orton R, Hughes J, Holland P, Silva V, Pascall DJ, Puxty K, da Silva Filipe A, Yebra G, Shaaban S, Holden MTG, Pinto RM, Gunson R, Templeton K, Murcia PR, Patel AH, Klenerman P, Dunachie S, Haughney J, Robertson DL, Palmarini M, Ray S, Thomson EC. SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nat Microbiol 2022; 7:1161-1179. [PMID: 35798890 PMCID: PMC9352574 DOI: 10.1038/s41564-022-01143-7] [Citation(s) in RCA: 324] [Impact Index Per Article: 162.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 05/03/2022] [Indexed: 12/12/2022]
Abstract
Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron (B.1.1.529), the fifth VOC to be described, harbours multiple amino acid mutations in spike, half of which lie within the receptor-binding domain. Here we demonstrate substantial evasion of neutralization by Omicron BA.1 and BA.2 variants in vitro using sera from individuals vaccinated with ChAdOx1, BNT162b2 and mRNA-1273. These data were mirrored by a substantial reduction in real-world vaccine effectiveness that was partially restored by booster vaccination. The Omicron variants BA.1 and BA.2 did not induce cell syncytia in vitro and favoured a TMPRSS2-independent endosomal entry pathway, these phenotypes mapping to distinct regions of the spike protein. Impaired cell fusion was determined by the receptor-binding domain, while endosomal entry mapped to the S2 domain. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant.
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Affiliation(s)
- Brian J Willett
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK.
| | - Joe Grove
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK.
| | - Oscar A MacLean
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Craig Wilkie
- School of Mathematics & Statistics, University of Glasgow, Glasgow, UK
| | - Giuditta De Lorenzo
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Diego Cantoni
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Sam Scott
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Nicola Logan
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Shirin Ashraf
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Maria Manali
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Agnieszka Szemiel
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Vanessa Cowton
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Elen Vink
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - William T Harvey
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Chris Davis
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Patawee Asamaphan
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Katherine Smollett
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Lily Tong
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Richard Orton
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Joseph Hughes
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | | | | | - David J Pascall
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | | | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | | | | | - Matthew T G Holden
- Public Health Scotland, Glasgow, UK
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Rute Maria Pinto
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | | | | | - Pablo R Murcia
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | | | | | | | - David L Robertson
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK
| | - Surajit Ray
- School of Mathematics & Statistics, University of Glasgow, Glasgow, UK
| | - Emma C Thomson
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK.
- NHS Greater Glasgow & Clyde, Glasgow, UK.
- London School of Hygiene and Tropical Medicine, London, UK.
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23
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Impact of COVID-19 on the Changing Patterns of Respiratory Syncytial Virus Infections. Infect Dis Rep 2022; 14:558-568. [PMID: 35893478 PMCID: PMC9394296 DOI: 10.3390/idr14040059] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 12/04/2022] Open
Abstract
Seasonal epidemics of respiratory syncytial virus (RSV) is one of the leading causes of hospitalization and mortality among children. Preventive measures implemented to reduce the spread of SARS-CoV-2, including facemasks, stay-at-home orders, closure of schools and local-national borders, and hand hygiene, may have also prevented the transmission of RSV and influenza. However, with the easing of COVID-19 imposed restrictions, many regions are noticing a delayed RSV outbreak. Some of these regions have also noted an increase in severity of these delayed RSV outbreaks partly due to a lack of protective immunity in the community following a lack of exposure from the previous season. Lessons learned from the COVID-19 pandemic can be implemented for controlling RSV outbreaks, including: (1) measures to reduce the spread, (2) effective vaccine development, and (3) genomic surveillance tools and computational modeling to predict the timing and severity of RSV outbreaks. These measures can help reduce the severity and prepare the health care system to deal with future RSV outbreaks by appropriate and timely allocation of health care resources.
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24
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Lawal OU, Zhang L, Parreira VR, Brown RS, Chettleburgh C, Dannah N, Delatolla R, Gilbride KA, Graber TE, Islam G, Knockleby J, Ma S, McDougall H, McKay RM, Mloszewska A, Oswald C, Servos M, Swinwood-Sky M, Ybazeta G, Habash M, Goodridge L. Metagenomics of Wastewater Influent from Wastewater Treatment Facilities across Ontario in the Era of Emerging SARS-CoV-2 Variants of Concern. Microbiol Resour Announc 2022; 11:e0036222. [PMID: 35638829 PMCID: PMC9302097 DOI: 10.1128/mra.00362-22] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 05/09/2022] [Indexed: 11/24/2022] Open
Abstract
We report metagenomic sequencing analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in composite wastewater influent from 10 regions in Ontario, Canada, during the transition between Delta and Omicron variants of concern. The Delta and Omicron BA.1/BA.1.1 and BA.2-defining mutations occurring in various frequencies were reported in the consensus and subconsensus sequences of the composite samples.
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Affiliation(s)
- Opeyemi U. Lawal
- Canadian Research Institute for Food Safety, Department of Food Science, University of Guelph, Guelph, Ontario, Canada
| | - Linkang Zhang
- Canadian Research Institute for Food Safety, Department of Food Science, University of Guelph, Guelph, Ontario, Canada
| | - Valeria R. Parreira
- Canadian Research Institute for Food Safety, Department of Food Science, University of Guelph, Guelph, Ontario, Canada
| | - R. Stephen Brown
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | | | - Nora Dannah
- Department of Chemistry and Biology, Ryerson University, Toronto, Ontario, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Kimberly A. Gilbride
- Department of Chemistry and Biology, Ryerson University, Toronto, Ontario, Canada
- Urban Water Research Centre, Ryerson University, Toronto, Ontario, Canada
| | - Tyson E. Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Golam Islam
- Faculty of Science, Ontario Tech University, Oshawa, Ontario, Canada
| | - James Knockleby
- Health Sciences North Research Institute, Sudbury, Ontario, Canada
| | - Sean Ma
- School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Hanlan McDougall
- School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
| | - R. Michael McKay
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada
| | | | - Claire Oswald
- Urban Water Research Centre, Ryerson University, Toronto, Ontario, Canada
- Department of Geography and Environmental Studies, Ryerson University, Toronto, Ontario, Canada
| | - Mark Servos
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Megan Swinwood-Sky
- School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Gustavo Ybazeta
- Health Sciences North Research Institute, Sudbury, Ontario, Canada
| | - Marc Habash
- School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada
| | - Lawrence Goodridge
- Canadian Research Institute for Food Safety, Department of Food Science, University of Guelph, Guelph, Ontario, Canada
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25
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Sá R, Isidro J, Borges V, Duarte S, Vieira L, Gomes JP, Tedim S, Matias J, Leite A. Unraveling the hurdles of a large COVID-19 epidemiological investigation by viral genomics. J Infect 2022; 85:64-74. [PMID: 35609706 PMCID: PMC9123803 DOI: 10.1016/j.jinf.2022.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/16/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022]
Abstract
COVID-19 local outbreak response relies on subjective information to reconstruct transmission chains. We assessed the concordance between epidemiologically linked cases and viral genetic profiles, in the Baixo Vouga Region (Portugal), from March to June 2020. A total of 1925 COVID-19 cases were identified, with 1143 being assigned to 154 epiclusters. Viral genomic data was available for 128 cases. Public health authorities identified two large epiclusters (280 and 101 cases each) with a central role on the spread of the disease. Still, the genomic data revealed that each epicluster included two distinct SARS-CoV-2 genetic profiles and thus more than one transmission network. We were able to show that the initial transmission dynamics reconstruction was most likely accurate, but the increasing dimension of the epiclusters and its extension to densely populated settings (healthcare and nursing home settings) triggered the misidentification of links. Genomics was also key to resolve some sporadic cases and misidentified direction of transmission. The epidemiological investigation showed a sensitivity of 70%-86% to detect transmission chains. This study contributes to the understanding of the hurdles and caveats associated with the epidemiological investigation of hundreds of community cases in the context of a massive outbreak caused by a highly transmissible and new respiratory virus.
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Affiliation(s)
- Regina Sá
- Public Health Unit of the Baixo Vouga Health Center Grouping, Regional Health Administration of the Center Portugal (ARSC), Aveiro, Portugal.
| | - Joana Isidro
- Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Vítor Borges
- Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Sílvia Duarte
- Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Luís Vieira
- Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - João P Gomes
- Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Sofia Tedim
- Department of Mathematics, University of Aveiro (UA), Aveiro, Portugal
| | - Judite Matias
- Public Health Unit of the Baixo Vouga Health Center Grouping, Regional Health Administration of the Center Portugal (ARSC), Aveiro, Portugal
| | - Andreia Leite
- NOVA National School of Public Health, Public Health Research Center, Universidade NOVA de Lisboa, Lisbon, Portugal; Comprehensive Health Research Center, Universidade NOVA de Lisboa, Lisbon, Portugal
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26
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Truong Nguyen P, Kant R, Van den Broeck F, Suvanto MT, Alburkat H, Virtanen J, Ahvenainen E, Castren R, Hong SL, Baele G, Ahava MJ, Jarva H, Jokiranta ST, Kallio-Kokko H, Kekäläinen E, Kirjavainen V, Kortela E, Kurkela S, Lappalainen M, Liimatainen H, Suchard MA, Hannula S, Ellonen P, Sironen T, Lemey P, Vapalahti O, Smura T. The phylodynamics of SARS-CoV-2 during 2020 in Finland. COMMUNICATIONS MEDICINE 2022; 2:65. [PMID: 35698660 PMCID: PMC9187640 DOI: 10.1038/s43856-022-00130-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 05/23/2022] [Indexed: 02/01/2023] Open
Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of infections and fatalities globally since its emergence in late 2019. The virus was first detected in Finland in January 2020, after which it rapidly spread among the populace in spring. However, compared to other European nations, Finland has had a low incidence of SARS-CoV-2. To gain insight into the origins and turnover of SARS-CoV-2 lineages circulating in Finland in 2020, we investigated the phylogeographic and -dynamic history of the virus. Methods The origins of SARS-CoV-2 introductions were inferred via Travel-aware Bayesian time-measured phylogeographic analyses. Sequences for the analyses included virus genomes belonging to the B.1 lineage and with the D614G mutation from countries of likely origin, which were determined utilizing Google mobility data. We collected all available sequences from spring and fall peaks to study lineage dynamics. Results We observed rapid turnover among Finnish lineages during this period. Clade 20C became the most prevalent among sequenced cases and was replaced by other strains in fall 2020. Bayesian phylogeographic reconstructions suggested 42 independent introductions into Finland during spring 2020, mainly from Italy, Austria, and Spain. Conclusions A single introduction from Spain might have seeded one-third of cases in Finland during spring in 2020. The investigations of the original introductions of SARS-CoV-2 to Finland during the early stages of the pandemic and of the subsequent lineage dynamics could be utilized to assess the role of transboundary movements and the effects of early intervention and public health measures.
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Affiliation(s)
- Phuoc Truong Nguyen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ravi Kant
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Frederik Van den Broeck
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Maija T. Suvanto
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Hussein Alburkat
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jenni Virtanen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Ella Ahvenainen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Robert Castren
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Samuel L. Hong
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Maarit J. Ahava
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hanna Jarva
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
- Department of Bacteriology and Immunology, University of Helsinki, Helsinki, Finland
| | - Suvi Tuulia Jokiranta
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
- Department of Bacteriology and Immunology, University of Helsinki, Helsinki, Finland
| | - Hannimari Kallio-Kokko
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Eliisa Kekäläinen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
| | - Vesa Kirjavainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Elisa Kortela
- Infectious Diseases, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Satu Kurkela
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Maija Lappalainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hanna Liimatainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Marc A. Suchard
- Departments of Biomathematics, Biostatistics and Human Genetics, University of California, Los Angeles (UCLA), Los Angeles, CA USA
| | - Sari Hannula
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Tarja Sironen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Olli Vapalahti
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Teemu Smura
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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27
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Guerrero‐Preston R, Rivera‐Amill V, Caraballo K, Rodríguez‐Torres S, Purcell‐Wiltz A, García AA, Torres RS, Zamuner FT, Zanettini C, MacKay MJ, Baits R, Salgado D, Khullar G, Metti J, Baker T, Dudley J, Vale K, Pérez G, De Jesús L, Miranda Y, Ortiz D, García‐Negrón A, Viera L, Ortiz A, Canabal JA, Romaguera J, Jiménez‐Velázquez I, Marchionni L, Rodríguez‐Orengo JF, Baez A, Mason CE, Sidransky D. Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS-CoV-2 variants. Immun Inflamm Dis 2022; 10:e634. [PMID: 35634961 PMCID: PMC9092005 DOI: 10.1002/iid3.634] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/18/2022] [Accepted: 04/20/2022] [Indexed: 11/23/2022] Open
Abstract
INTRODUCTION The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS-CoV-2 variants of concern (VOCs) such as Alpha and Omicron, which show increased transmissibility and immune evasion, rapidly became dominant VOCs worldwide. Our objective was to develop an evidenced-based genomic surveillance algorithm, combining reverse transcription polymerase chain reaction (RT-PCR) and sequencing technologies to quickly identify highly contagious VOCs, before cases accumulate exponentially. METHODS Deidentified data were obtained from 508,969 patients tested for coronavirus disease 2019 (COVID-19) with the TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) in four CLIA-certified clinical laboratories in Puerto Rico (n = 86,639) and in three CLIA-certified clinical laboratories in the United States (n = 422,330). RESULTS TaqPath data revealed a frequency of S Gene Target Failure (SGTF) > 47% for the last week of March 2021 in both, Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021. The weekly SGTF rate in US samples was high (>8%) from late December to early January and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico was concurrent with a sharp increase in VOCs among all SARS-CoV-2 sequences from Puerto Rico uploaded to Global Influenza Surveillance and Response System (GISAID) (n = 461). Alpha variant frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021. CONCLUSIONS According to the proposed evidence-based algorithm, approximately 50% of all SGTF patients should be managed with VOCs self-quarantine and contact tracing protocols, while WGS confirms their lineage in genomic surveillance laboratories. Our results suggest this workflow is useful for tracking VOCs with SGTF.
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Affiliation(s)
| | - Vanessa Rivera‐Amill
- Center for Research ResourcesPonce Health Sciences University‐Ponce Research InstitutePoncePuerto Rico
| | | | | | - Ana Purcell‐Wiltz
- LifeGene‐Biomarks, IncSan JuanPuerto Rico
- Biology DepartmentUniversity of Puerto RicoRíoPiedrasPuerto Rico
| | - Andrea A. García
- Center for Research ResourcesPonce Health Sciences University‐Ponce Research InstitutePoncePuerto Rico
| | - Raphael S. Torres
- Center for Research ResourcesPonce Health Sciences University‐Ponce Research InstitutePoncePuerto Rico
| | - Fernando T. Zamuner
- Department of Otolaryngology‐Head and Neck SurgeryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Claudio Zanettini
- Department of Pathology and Laboratory Medicine, Weill Cornell MedicineCornell UniversityNew YorkNew YorkUSA
| | | | | | | | | | | | | | | | | | - Gabriela Pérez
- Neurology Medicine DepartmentPalmetto General HospitalMiamiFloridaUSA
| | | | | | | | | | - Liliana Viera
- Department of SurgeryUniversity of Puerto Rico School of MedicineSan JuanPuerto Rico
| | - Alberto Ortiz
- Internal Medicine DepartmentUniversity of Puerto Rico School of MedicineSanJuanPuerto Rico
| | - Jorge A. Canabal
- Internal Medicine DepartmentUniversity of Puerto Rico School of MedicineSanJuanPuerto Rico
| | - Josefina Romaguera
- Obstetrics and Gynecology DepartmentUniversity of Puerto Rico School of MedicineSan JuanPuerto Rico
| | | | - Luigi Marchionni
- Department of Otolaryngology‐Head and Neck SurgeryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | | | - Adriana Baez
- Otolaryngology DepartmentUniversity of Puerto Rico School of MedicineSan JuanPuerto Rico
| | | | - David Sidransky
- Department of Otolaryngology‐Head and Neck SurgeryJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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28
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Volk D, Yang-Turner F, Didelot X, Crook DW, Wyllie D. Catwalk: identifying closely related sequences in large microbial sequence databases. Microb Genom 2022; 8. [PMID: 35771206 PMCID: PMC9455716 DOI: 10.1099/mgen.0.000850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
There is a need to identify microbial sequences that may form part of transmission chains, or that may represent importations across national boundaries, amidst large numbers of SARS-CoV-2 and other bacterial or viral sequences. Reference-based compression is a sequence analysis technique that allows both a compact storage of sequence data and comparisons between sequences. Published implementations of the approach are being challenged by the large sample collections now being generated. Our aim was to develop a fast software detecting highly similar sequences in large collections of microbial genomes, including millions of SARS-CoV-2 genomes. To do so, we developed Catwalk, a tool that bypasses bottlenecks in the generation, comparison and in-memory storage of microbial genomes generated by reference mapping. It is a compiled solution, coded in Nim to increase performance. It can be accessed via command line, rest api or web server interfaces. We tested Catwalk using both SARS-CoV-2 and Mycobacterium tuberculosis genomes generated by prospective public-health sequencing programmes. Pairwise sequence comparisons, using clinically relevant similarity cut-offs, took about 0.39 and 0.66 μs, respectively; in 1 s, between 1 and 2 million sequences can be searched. Catwalk operates about 1700 times faster than, and uses about 8 % of the RAM of, a Python reference-based compression and comparison tool in current use for outbreak detection. Catwalk can rapidly identify close relatives of a SARS-CoV-2 or M. tuberculosis genome amidst millions of samples.
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Affiliation(s)
- Denis Volk
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Fan Yang-Turner
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Present address: UKRI Science and Technologies Facilities Council, Harwell, UK
| | - Xavier Didelot
- School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.,Department of Statistics, University of Warwick, Coventry CV4 7AL, UK
| | - Derrick W Crook
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - David Wyllie
- UK Health Security Agency, Forvie Site, Addenbrookes' Campus, Robinson Way, Cambridge CB2 0SR, UK
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29
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De Maio N, Kalaghatgi P, Turakhia Y, Corbett-detig R, Minh BQ, Goldman N. Maximum likelihood pandemic-scale phylogenetics.. [PMID: 35350209 PMCID: PMC8963701 DOI: 10.1101/2022.03.22.485312] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Genomic data plays an essential role in the study of transmissible disease, as exemplified by its current use in identifying and tracking the spread of novel SARS-CoV-2 variants. However, with the increase in size of genomic epidemiological datasets, their phylogenetic analyses become increasingly impractical due to high computational demand. In particular, while maximum likelihood methods are go-to tools for phylogenetic inference, the scale of datasets from the ongoing pandemic has made apparent the urgent need for more computationally efficient approaches. Here we propose a new likelihood-based phylogenetic framework that greatly reduces both the memory and time demand of popular maximum likelihood approaches when analysing many closely related genomes, as in the scenario of SARS-CoV-2 genome data and more generally throughout genomic epidemiology. To achieve this, we rewrite the classical Felsenstein pruning algorithm so that we can infer phylogenetic trees on at least 10 times larger datasets with higher accuracy than existing maximum likelihood methods. Our algorithms provide a powerful framework for maximum-likelihood genomic epidemiology and could facilitate similarly groundbreaking applications in Bayesian phylogenomic analyses as well.
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30
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Steinig E, Duchêne S, Aglua I, Greenhill A, Ford R, Yoannes M, Jaworski J, Drekore J, Urakoko B, Poka H, Wurr C, Ebos E, Nangen D, Manning L, Laman M, Firth C, Smith S, Pomat W, Tong SYC, Coin L, McBryde E, Horwood P. Phylodynamic Inference of Bacterial Outbreak Parameters Using Nanopore Sequencing. Mol Biol Evol 2022; 39:msac040. [PMID: 35171290 PMCID: PMC8963328 DOI: 10.1093/molbev/msac040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Nanopore sequencing and phylodynamic modeling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Cost-effective bacterial genome sequencing and variant calling on nanopore platforms would greatly enhance surveillance and outbreak response in communities without access to sequencing infrastructure. Here, we adapt random forest models for single nucleotide polymorphism (SNP) polishing developed by Sanderson and colleagues (2020. High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic nanopore sequencing. Genome Res. 30(9):1354-1363) to estimate divergence and effective reproduction numbers (Re) of two methicillin-resistant Staphylococcus aureus (MRSA) outbreaks from remote communities in Far North Queensland and Papua New Guinea (PNG; n = 159). Successive barcoded panels of S. aureus isolates (2 × 12 per MinION) sequenced at low coverage (>5× to 10×) provided sufficient data to accurately infer genotypes with high recall when compared with Illumina references. Random forest models achieved high resolution on ST93 outbreak sequence types (>90% accuracy and precision) and enabled phylodynamic inference of epidemiological parameters using birth-death skyline models. Our method reproduced phylogenetic topology, origin of the outbreaks, and indications of epidemic growth (Re > 1). Nextflow pipelines implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks on portable nanopore platforms. Our study shows that nanopore technology can be used for bacterial outbreak reconstruction at competitive costs, providing opportunities for infection control in hospitals and communities without access to sequencing infrastructure, such as in remote northern Australia and PNG.
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Affiliation(s)
- Eike Steinig
- Department of Infectious Diseases, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Australian Institute of Tropical Health and Medicine, James Cook University, Townsville and Cairns, Australia
| | - Sebastián Duchêne
- Department of Infectious Diseases, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Izzard Aglua
- Joseph Nombri Memorial-Kundiawa General Hospital, Kundiawa, Papua New Guinea
| | - Andrew Greenhill
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
| | - Rebecca Ford
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
| | - Mition Yoannes
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
| | - Jan Jaworski
- Joseph Nombri Memorial-Kundiawa General Hospital, Kundiawa, Papua New Guinea
| | - Jimmy Drekore
- Simbu Children's Foundation, Kundiawa, Papua New Guinea
| | - Bohu Urakoko
- Joseph Nombri Memorial-Kundiawa General Hospital, Kundiawa, Papua New Guinea
| | - Harry Poka
- Joseph Nombri Memorial-Kundiawa General Hospital, Kundiawa, Papua New Guinea
| | - Clive Wurr
- Surgical Department, Goroka General Hospital, Goroka, Papua New Guinea
| | - Eri Ebos
- Surgical Department, Goroka General Hospital, Goroka, Papua New Guinea
| | - David Nangen
- Surgical Department, Goroka General Hospital, Goroka, Papua New Guinea
| | - Laurens Manning
- Department of Infectious Diseases, Fiona Stanley Hospital, Murdoch, Australia
- Medical School, University of Western Australia, Harry Perkins Research Institute, Fiona Stanley Hospital, Murdoch, Australia
| | - Moses Laman
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
| | - Cadhla Firth
- Australian Institute of Tropical Health and Medicine, James Cook University, Townsville and Cairns, Australia
| | - Simon Smith
- Cairns Hospital and Hinterland Health Service, Queensland Health, Cairns, Australia
| | - William Pomat
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
| | - Steven Y C Tong
- Department of Infectious Diseases, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Victorian Infectious Diseases Service, The Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Lachlan Coin
- Department of Infectious Diseases, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Emma McBryde
- Australian Institute of Tropical Health and Medicine, James Cook University, Townsville and Cairns, Australia
| | - Paul Horwood
- Papua New Guinea Institute of Medical Research, Goroka, Papua, Papua New Guinea
- College of Public Health, Medical & Veterinary Sciences, James Cook University, Townsville, Australia
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31
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Aggarwal D, Page AJ, Schaefer U, Savva GM, Myers R, Volz E, Ellaby N, Platt S, Groves N, Gallagher E, Tumelty NM, Le Viet T, Hughes GJ, Chen C, Turner C, Logan S, Harrison A, Peacock SJ, Chand M, Harrison EM. Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission. Nat Commun 2022; 13:1012. [PMID: 35197443 PMCID: PMC8866425 DOI: 10.1038/s41467-022-28371-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 01/18/2022] [Indexed: 01/16/2023] Open
Abstract
Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16-20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement.
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Affiliation(s)
- Dinesh Aggarwal
- University of Cambridge, Department of Medicine, Cambridge, UK.
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK.
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK.
- Wellcome Sanger Institute, Hinxton, Cambridge, UK.
| | - Andrew J Page
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Ulf Schaefer
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - George M Savva
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Richard Myers
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Erik Volz
- Imperial College London, Department of Infectious Disease Epidemiology, London, UK
| | - Nicholas Ellaby
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Steven Platt
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Natalie Groves
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | | | - Niamh M Tumelty
- University of Cambridge, Cambridge University Libraries, Cambridge, UK
| | - Thanh Le Viet
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Gareth J Hughes
- Public Health England National Infections Service, Field Service, Leeds, UK
| | - Cong Chen
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Charlie Turner
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Sophie Logan
- Public Health England, National Infections Service, Field Service, Nottingham, UK
| | - Abbie Harrison
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Sharon J Peacock
- University of Cambridge, Department of Medicine, Cambridge, UK
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Meera Chand
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Ewan M Harrison
- University of Cambridge, Department of Medicine, Cambridge, UK.
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK.
- Wellcome Sanger Institute, Hinxton, Cambridge, UK.
- University of Cambridge, Department of Public Health and Primary Care, Cambridge, UK.
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32
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Griffiths EJ, Timme RE, Mendes CI, Page AJ, Alikhan NF, Fornika D, Maguire F, Campos J, Park D, Olawoye IB, Oluniyi PE, Anderson D, Christoffels A, da Silva AG, Cameron R, Dooley D, Katz LS, Black A, Karsch-Mizrachi I, Barrett T, Johnston A, Connor TR, Nicholls SM, Witney AA, Tyson GH, Tausch SH, Raphenya AR, Alcock B, Aanensen DM, Hodcroft E, Hsiao WWL, Vasconcelos ATR, MacCannell DR. Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package. Gigascience 2022; 11:giac003. [PMID: 35169842 PMCID: PMC8847733 DOI: 10.1093/gigascience/giac003] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/15/2021] [Accepted: 01/07/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. RESULTS As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. CONCLUSIONS Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI's BioSample database.
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Affiliation(s)
- Emma J Griffiths
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Ruth E Timme
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD 20740, USA
| | - Catarina Inês Mendes
- Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa 1649-028, Portugal
| | - Andrew J Page
- Microbes in the Food Chain, Quadram Institute Bioscience, Norwich, Norfolk NR4 7UQ, UK
| | - Nabil-Fareed Alikhan
- Microbes in the Food Chain, Quadram Institute Bioscience, Norwich, Norfolk NR4 7UQ, UK
| | - Dan Fornika
- BC Centre for Disease Control Public Health Laboratory, Vancouver, BC V5Z 4R4, Canada
| | - Finlay Maguire
- Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 1W5, Canada
| | - Josefina Campos
- INEI-ANLIS “Dr Carlos G. Malbrán,” Buenos Aires C1282AFF, Argentina
| | - Daniel Park
- Infectious Disease and Microbiome Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Idowu B Olawoye
- African Center of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State 232103, Nigeria
- Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Ede, Osun State 232103, Nigeria
| | - Paul E Oluniyi
- African Center of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State 232103, Nigeria
- Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Ede, Osun State 232103, Nigeria
| | - Dominique Anderson
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville 7530, South Africa
| | - Alan Christoffels
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville 7530, South Africa
| | - Anders Gonçalves da Silva
- Microbiological Diagnostic Unit Public Health Laboratory, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Rhiannon Cameron
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Damion Dooley
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Lee S Katz
- Center for Food Safety, University of Georgia, Atlanta, GA 30333, USA
- Office of Advanced Molecular Detection, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, GA 30333, USA
| | - Allison Black
- Department of Epidemiology, University of Washington, WA 98109, USA
| | - Ilene Karsch-Mizrachi
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Tanya Barrett
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Anjanette Johnston
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Thomas R Connor
- Organisms and Environment Division, School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
- Public Health Wales, University Hospital of Wales, Cardiff CF14 4XW, UK
| | | | - Adam A Witney
- Institute for Infection and Immunity, St George's, University of London, London SW17 0RE, UK
| | - Gregory H Tyson
- Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, MD 20708, USA
| | - Simon H Tausch
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin 12277, Germany
| | - Amogelang R Raphenya
- Department of Biochemistry and Biomedical Sciences and the Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Brian Alcock
- Department of Biochemistry and Biomedical Sciences and the Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Cambridge CB10 1SA, UK
- The Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK
| | - Emma Hodcroft
- Biozentrum, University of Basel, Basel 3012, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - William W L Hsiao
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
- BC Centre for Disease Control Public Health Laboratory, Vancouver, BC V5Z 4R4, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z7 V6T 1Z7, Canada
| | - Ana Tereza R Vasconcelos
- Bioinformatics Laboratory National Laboratory of Scientific Computation LNCC/MCTI, Petrópolis 25651-075, Brazil
| | - Duncan R MacCannell
- Office of Advanced Molecular Detection, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, GA 30333, USA
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Characterization of the First SARS-CoV-2 Isolates from Aotearoa New Zealand as Part of a Rapid Response to the COVID-19 Pandemic. Viruses 2022; 14:v14020366. [PMID: 35215963 PMCID: PMC8877023 DOI: 10.3390/v14020366] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 01/31/2022] [Accepted: 02/08/2022] [Indexed: 02/04/2023] Open
Abstract
SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has wreaked havoc across the globe for the last two years. More than 300 million cases and over 5 million deaths later, we continue battling the first real pandemic of the 21st century. SARS-CoV-2 spread quickly, reaching most countries within the first half of 2020, and New Zealand was not an exception. Here, we describe the first isolation and characterization of SARS-CoV-2 variants during the initial virus outbreak in New Zealand. Patient-derived nasopharyngeal samples were used to inoculate Vero cells and, three to four days later, a cytopathic effect was observed in seven viral cultures. Viral growth kinetics was characterized using Vero and VeroE6/TMPRSS2 cells. The identity of the viruses was verified by RT-qPCR, Western blot, indirect immunofluorescence assays, and electron microscopy. Whole-genome sequences were analyzed using two different yet complementary deep sequencing platforms (MiSeq/Illumina and Ion PGM™/Ion Torrent™), classifying the viruses as SARS-CoV-2 B.55, B.31, B.1, or B.1.369 based on the Pango Lineage nomenclature. All seven SARS-CoV-2 isolates were susceptible to remdesivir (EC50 values from 0.83 to 2.42 µM) and β-D-N4-hydroxycytidine (molnupiravir, EC50 values from 0.96 to 1.15 µM) but not to favipiravir (>10 µM). Interestingly, four SARS-CoV-2 isolates, carrying the D614G substitution originally associated with increased transmissibility, were more susceptible (2.4-fold) to a commercial monoclonal antibody targeting the spike glycoprotein than the wild-type viruses. Altogether, this seminal work allowed for early access to SARS-CoV-2 isolates in New Zealand, paving the way for numerous clinical and scientific research projects in the country, including the development and validation of diagnostic assays, antiviral strategies, and a national COVID-19 vaccine development program.
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34
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Gu H, Xie R, Adam DC, Tsui JLH, Chu DK, Chang LDJ, Cheuk SSY, Gurung S, Krishnan P, Ng DYM, Liu GYZ, Wan CKC, Cheng SSM, Edwards KM, Leung KSM, Wu JT, Tsang DNC, Leung GM, Cowling BJ, Peiris M, Lam TTY, Dhanasekaran V, Poon LLM. Genomic epidemiology of SARS-CoV-2 under an elimination strategy in Hong Kong. Nat Commun 2022; 13:736. [PMID: 35136039 PMCID: PMC8825829 DOI: 10.1038/s41467-022-28420-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 01/19/2022] [Indexed: 12/15/2022] Open
Abstract
Hong Kong employed a strategy of intermittent public health and social measures alongside increasingly stringent travel regulations to eliminate domestic SARS-CoV-2 transmission. By analyzing 1899 genome sequences (>18% of confirmed cases) from 23-January-2020 to 26-January-2021, we reveal the effects of fluctuating control measures on the evolution and epidemiology of SARS-CoV-2 lineages in Hong Kong. Despite numerous importations, only three introductions were responsible for 90% of locally-acquired cases. Community outbreaks were caused by novel introductions rather than a resurgence of circulating strains. Thus, local outbreak prevention requires strong border control and community surveillance, especially during periods of less stringent social restriction. Non-adherence to prolonged preventative measures may explain sustained local transmission observed during wave four in late 2020 and early 2021. We also found that, due to a tight transmission bottleneck, transmission of low-frequency single nucleotide variants between hosts is rare.
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Affiliation(s)
- Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ruopeng Xie
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Dillon C Adam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Joseph L-H Tsui
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Daniel K Chu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Lydia D J Chang
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Sammi S Y Cheuk
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Shreya Gurung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Pavithra Krishnan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Daisy Y M Ng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gigi Y Z Liu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Carrie K C Wan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Samuel S M Cheng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kimberly M Edwards
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kathy S M Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Joseph T Wu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Dominic N C Tsang
- Centre for Health Protection, Department of Health, The Government of Hong Kong Special Administrative Region, Hong Kong, China
| | - Gabriel M Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Benjamin J Cowling
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
| | - Tommy T Y Lam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
| | - Vijaykrishna Dhanasekaran
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
| | - Leo L M Poon
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China.
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35
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Zhou J, Peacock TP, Brown JC, Goldhill DH, Elrefaey AME, Penrice-Randal R, Cowton VM, De Lorenzo G, Furnon W, Harvey WT, Kugathasan R, Frise R, Baillon L, Lassaunière R, Thakur N, Gallo G, Goldswain H, Donovan-Banfield I, Dong X, Randle NP, Sweeney F, Glynn MC, Quantrill JL, McKay PF, Patel AH, Palmarini M, Hiscox JA, Bailey D, Barclay WS. Mutations that adapt SARS-CoV-2 to mink or ferret do not increase fitness in the human airway. Cell Rep 2022; 38:110344. [PMID: 35093235 PMCID: PMC8768428 DOI: 10.1016/j.celrep.2022.110344] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 11/11/2021] [Accepted: 01/14/2022] [Indexed: 12/18/2022] Open
Abstract
SARS-CoV-2 has a broad mammalian species tropism infecting humans, cats, dogs, and farmed mink. Since the start of the 2019 pandemic, several reverse zoonotic outbreaks of SARS-CoV-2 have occurred in mink, one of which reinfected humans and caused a cluster of infections in Denmark. Here we investigate the molecular basis of mink and ferret adaptation and demonstrate the spike mutations Y453F, F486L, and N501T all specifically adapt SARS-CoV-2 to use mustelid ACE2. Furthermore, we risk assess these mutations and conclude mink-adapted viruses are unlikely to pose an increased threat to humans, as Y453F attenuates the virus replication in human cells and all three mink adaptations have minimal antigenic impact. Finally, we show that certain SARS-CoV-2 variants emerging from circulation in humans may naturally have a greater propensity to infect mustelid hosts and therefore these species should continue to be surveyed for reverse zoonotic infections.
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Affiliation(s)
- Jie Zhou
- Department of Infectious Disease, Imperial College London, London, UK
| | - Thomas P Peacock
- Department of Infectious Disease, Imperial College London, London, UK
| | - Jonathan C Brown
- Department of Infectious Disease, Imperial College London, London, UK
| | - Daniel H Goldhill
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Rebekah Penrice-Randal
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK
| | - Vanessa M Cowton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - William T Harvey
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | - Rebecca Frise
- Department of Infectious Disease, Imperial College London, London, UK
| | - Laury Baillon
- Department of Infectious Disease, Imperial College London, London, UK
| | - Ria Lassaunière
- Virus & Microbiological Special Diagnostics, Statens Serum Institut, Copenhagen, Denmark
| | - Nazia Thakur
- The Pirbright Institute, Woking, Surrey, UK; The Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Hannah Goldswain
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK
| | - I'ah Donovan-Banfield
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK
| | - Xiaofeng Dong
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK
| | - Nadine P Randle
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK
| | - Fiachra Sweeney
- Department of Infectious Disease, Imperial College London, London, UK
| | - Martha C Glynn
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Paul F McKay
- Department of Infectious Disease, Imperial College London, London, UK
| | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | - Julian A Hiscox
- Institute of Infection, Veterinary and Ecology Sciences, University of Liverpool, Liverpool, UK; Infectious Diseases Horizontal Technology Centre (ID HTC), A(∗)STAR, Singapore, Singapore
| | | | - Wendy S Barclay
- Department of Infectious Disease, Imperial College London, London, UK.
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36
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Unique Evolution of SARS-CoV-2 in the Second Large Cruise Ship Cluster in Japan. Microorganisms 2022; 10:microorganisms10010099. [PMID: 35056548 PMCID: PMC8778844 DOI: 10.3390/microorganisms10010099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 12/25/2021] [Accepted: 12/30/2021] [Indexed: 11/16/2022] Open
Abstract
In the initial phase of the novel coronavirus disease (COVID-19) pandemic, a large-scale cluster on the cruise ship Diamond Princess (DP) emerged in Japan. Genetic analysis of the DP strains has provided important information for elucidating the possible transmission process of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on a cruise ship. However, genome-based analyses of SARS-CoV-2 detected in large-scale cruise ship clusters other than the DP cluster have rarely been reported. In the present study, whole-genome sequences of 94 SARS-CoV-2 strains detected in the second large cruise ship cluster, which emerged on the Costa Atlantica (CA) in Japan, were characterized to understand the evolution of the virus in a crowded and confined place. Phylogenetic and haplotype network analysis indicated that the CA strains were derived from a common ancestral strain introduced on the CA cruise ship and spread in a superspreading event-like manner, resulting in several mutations that might have affected viral characteristics, including the P681H substitution in the spike protein. Moreover, there were significant genetic distances between CA strains and other strains isolated in different environments, such as cities under lockdown. These results provide new insights into the unique evolution patterns of SARS-CoV-2 in the CA cruise ship cluster.
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37
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McBroome J, Thornlow B, Hinrichs AS, Kramer A, De Maio N, Goldman N, Haussler D, Corbett-Detig R, Turakhia Y. A Daily-Updated Database and Tools for Comprehensive SARS-CoV-2 Mutation-Annotated Trees. Mol Biol Evol 2021; 38:5819-5824. [PMID: 34469548 PMCID: PMC8662617 DOI: 10.1093/molbev/msab264] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The vast scale of SARS-CoV-2 sequencing data has made it increasingly challenging to comprehensively analyze all available data using existing tools and file formats. To address this, we present a database of SARS-CoV-2 phylogenetic trees inferred with unrestricted public sequences, which we update daily to incorporate new sequences. Our database uses the recently proposed mutation-annotated tree (MAT) format to efficiently encode the tree with branches labeled with parsimony-inferred mutations, as well as Nextstrain clade and Pango lineage labels at clade roots. As of June 9, 2021, our SARS-CoV-2 MAT consists of 834,521 sequences and provides a comprehensive view of the virus' evolutionary history using public data. We also present matUtils-a command-line utility for rapidly querying, interpreting, and manipulating the MATs. Our daily-updated SARS-CoV-2 MAT database and matUtils software are available at http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/ and https://github.com/yatisht/usher, respectively.
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Affiliation(s)
- Jakob McBroome
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Bryan Thornlow
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Angie S Hinrichs
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Alexander Kramer
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, United Kingdom
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, United Kingdom
| | - David Haussler
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Yatish Turakhia
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
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38
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Chinnery PF, Pearce JJ, Kinsey AM, Jenkinson JM, Wells G, Watt FM. How COVID-19 has changed medical research funding. Interface Focus 2021; 11:20210025. [PMID: 34956595 PMCID: PMC8504879 DOI: 10.1098/rsfs.2021.0025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 12/15/2022] Open
Abstract
Here, we consider how the lessons we learned in 2020 from funding COVID-19 research could have a long-term impact on the way that we fund medical research. We look back at how UK government funding for COVID-19 medical research evolved, beginning with the early calls for proposals in February that pump-primed funding for vaccines and therapeutics, and culminating in the launch of the government's National Core Studies programme in October. We discuss how the research community mobilized to submit and review grants more rapidly than ever before, against a background of laboratory and office closures. We also highlight the challenges of running clinical trials as the number of hospitalized patients fluctuated with different waves of the disease.
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Affiliation(s)
| | - Jonathan J Pearce
- Medical Research Council, 58 Victoria Embankment, London E4Y 0DS, UK
| | - Anna M Kinsey
- Medical Research Council, 58 Victoria Embankment, London E4Y 0DS, UK
| | | | - Glenn Wells
- Medical Research Council, 58 Victoria Embankment, London E4Y 0DS, UK
| | - Fiona M Watt
- Medical Research Council, 58 Victoria Embankment, London E4Y 0DS, UK
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39
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Ye C, Thornlow B, Kramer A, McBroome J, Hinrichs A, Corbett-Detig R, Turakhia Y. Pandemic-scale phylogenetics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.12.03.470766. [PMID: 34927180 PMCID: PMC8679213 DOI: 10.1101/2021.12.03.470766] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Phylogenetics has been central to the genomic surveillance, epidemiology and contact tracing efforts during the COVD-19 pandemic. But the massive scale of genomic sequencing has rendered the pre-pandemic tools inadequate for comprehensive phylogenetic analyses. Here, we discuss the phylogenetic package that we developed to address the needs imposed by this pandemic. The package incorporates several pandemic-specific optimization and parallelization techniques and comprises four programs: UShER, matOptimize, RIPPLES and matUtils. Using high-performance computing, UShER and matOptimize maintain and refine daily a massive mutation-annotated phylogenetic tree consisting of all SARS-CoV-2 sequences available in online repositories. With UShER and RIPPLES, individual labs - even with modest compute resources - incorporate newly-sequenced SARS-CoV-2 genomes on this phylogeny and discover evidence for recombination in real-time. With matUtils, they rapidly query and visualize massive SARS-CoV-2 phylogenies. These tools have empowered scientists worldwide to study the SARS-CoV-2 evolution and transmission at an unprecedented scale, resolution and speed.
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Affiliation(s)
- Cheng Ye
- University of California, San Diego; San Diego, CA 92093, USA
| | - Bryan Thornlow
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Alexander Kramer
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Jakob McBroome
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Angie Hinrichs
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Russell Corbett-Detig
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Yatish Turakhia
- University of California, San Diego; San Diego, CA 92093, USA
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40
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Wagatsuma K, Sato R, Yamazaki S, Iwaya M, Takahashi Y, Nojima A, Oseki M, Abe T, Phyu WW, Tamura T, Sekizuka T, Kuroda M, Matsumoto HH, Saito R. Genomic Epidemiology Reveals Multiple Introductions of Severe Acute Respiratory Syndrome Coronavirus 2 in Niigata City, Japan, Between February and May 2020. Front Microbiol 2021; 12:749149. [PMID: 34777297 PMCID: PMC8581661 DOI: 10.3389/fmicb.2021.749149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/04/2021] [Indexed: 01/19/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) has caused a serious disease burden and poses a tremendous public health challenge worldwide. Here, we report a comprehensive epidemiological and genomic analysis of SARS-CoV-2 from 63 patients in Niigata City, a medium-sized Japanese city, during the early phase of the pandemic, between February and May 2020. Among the 63 patients, 32 (51%) were female, with a mean (±standard deviation) age of 47.9 ± 22.3 years. Fever (65%, 41/63), malaise (51%, 32/63), and cough (35%, 22/63) were the most common clinical symptoms. The median Ct value after the onset of symptoms lowered within 9 days at 20.9 cycles (interquartile range, 17–26 cycles), but after 10 days, the median Ct value exceeded 30 cycles (p < 0.001). Of the 63 cases, 27 were distributed in the first epidemic wave and 33 in the second, and between the two waves, three cases from abroad were identified. The first wave was epidemiologically characterized by a single cluster related to indoor sports activity spread in closed settings, which included mixing indoors with families, relatives, and colleagues. The second wave showed more epidemiologically diversified events, with most index cases not related to each other. Almost all secondary cases were infected by droplets or aerosols from closed indoor settings, but at least two cases in the first wave were suspected to be contact infections. Results of the genomic analysis identified two possible clusters in Niigata City, the first of which was attributed to clade S (19B by Nexstrain clade) with a monophyletic group derived from the Wuhan prototype strain but that of the second wave was polyphyletic suggesting multiple introductions, and the clade was changed to GR (20B), which mainly spread in Europe in early 2020. These findings depict characteristics of SARS-CoV-2 transmission in the early stages in local community settings during February to May 2020 in Japan, and this integrated approach of epidemiological and genomic analysis may provide valuable information for public health policy decision-making for successful containment of chains of infection.
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Affiliation(s)
- Keita Wagatsuma
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Ryosuke Sato
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Satoru Yamazaki
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Masako Iwaya
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | | | - Akiko Nojima
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Mitsuru Oseki
- Division of Health Science, Niigata City Institute of Public Health and Environment, Niigata, Japan
| | - Takashi Abe
- Division of Bioinformatics, Graduate School of Science and Technology, Niigata University, Niigata, Japan
| | - Wint Wint Phyu
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Tsutomu Tamura
- Virology Section, Niigata Prefectural Institute of Public Health and Environmental Science, Niigata, Japan
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Haruki H Matsumoto
- Division of Health and Welfare, Niigata Prefectural Government Office, Niigata, Japan
| | - Reiko Saito
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
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41
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Rapid Response to SARS-CoV-2 in Aotearoa New Zealand: Implementation of a Diagnostic Test and Characterization of the First COVID-19 Cases in the South Island. Viruses 2021; 13:v13112222. [PMID: 34835031 PMCID: PMC8623489 DOI: 10.3390/v13112222] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/28/2021] [Accepted: 11/02/2021] [Indexed: 12/13/2022] Open
Abstract
It has been 20 months since we first heard of SARS-CoV-2, the novel coronavirus detected in the Hubei province, China, in December 2019, responsible for the ongoing COVID-19 pandemic. Since then, a myriad of studies aimed at understanding and controlling SARS-CoV-2 have been published at a pace that has outshined the original effort to combat HIV during the beginning of the AIDS epidemic. This massive response started by developing strategies to not only diagnose individual SARS-CoV-2 infections but to monitor the transmission, evolution, and global spread of this new virus. We currently have hundreds of commercial diagnostic tests; however, that was not the case in early 2020, when just a handful of protocols were available, and few whole-genome SARS-CoV-2 sequences had been described. It was mid-January 2020 when several District Health Boards across New Zealand started planning the implementation of diagnostic testing for this emerging virus. Here, we describe our experience implementing a molecular test to detect SARS-CoV-2 infection, adapting the RT-qPCR assay to be used in a random-access platform (Hologic Panther Fusion® System) in a clinical laboratory, and characterizing the first whole-genome SARS-CoV-2 sequences obtained in the South Island, right at the beginning of the SARS-CoV-2 outbreak in New Zealand. We expect that this work will help us and others prepare for the unequivocal risk of similar viral outbreaks in the future.
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42
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Valesano AL, Fitzsimmons WJ, Blair CN, Woods RJ, Gilbert J, Rudnik D, Mortenson L, Friedrich TC, O’Connor DH, MacCannell DR, Petrie JG, Martin ET, Lauring AS. SARS-CoV-2 Genomic Surveillance Reveals Little Spread From a Large University Campus to the Surrounding Community. Open Forum Infect Dis 2021; 8:ofab518. [PMID: 34805437 PMCID: PMC8600169 DOI: 10.1093/ofid/ofab518] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 10/07/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) has had high incidence rates at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are poorly understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. METHODS We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan and the surrounding community during the Fall 2020 semester (August 16-November 24). We sequenced complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total cases in Washtenaw County over the study interval. RESULTS Phylogenetic analysis identified >200 introductions into the student population, most of which were not related to other student cases. There were 2 prolonged student transmission clusters, of 115 and 73 individuals, that spanned multiple on-campus residences. Remarkably, <5% of nonstudent genomes were descended from student clusters, and viral descendants of student cases were rare during a subsequent wave of infections in the community. CONCLUSIONS The largest outbreaks among students at the University of Michigan did not significantly contribute to the rise in community cases in Fall 2020. These results provide valuable insights into SARS-CoV-2 transmission dynamics at the regional level.
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Affiliation(s)
- Andrew L Valesano
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - William J Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Christopher N Blair
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Robert J Woods
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Julie Gilbert
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Dawn Rudnik
- University Health Service, University of Michigan, Ann Arbor, Michigan, USA
| | - Lindsey Mortenson
- University Health Service, University of Michigan, Ann Arbor, Michigan, USA
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David H O’Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Joshua G Petrie
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily T Martin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Adam S Lauring
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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43
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Onwuamah CK, Kanteh A, Abimbola BS, Ahmed RA, Okoli CL, Shaibu JO, James AB, Ajibaye O, Okwuraiwe AP, Fowora M, Otuonye N, Worwui A, Iwalokun B, Kanteh D, Audu RA, Adegbola RA, D'Alessandro U, Salako BL, Sesay AK. SARS-CoV-2 sequencing collaboration in west Africa shows best practices. Lancet Glob Health 2021; 9:e1499-e1500. [PMID: 34678187 PMCID: PMC8525915 DOI: 10.1016/s2214-109x(21)00389-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 08/18/2021] [Indexed: 01/19/2023]
Affiliation(s)
- Chika Kingsley Onwuamah
- Centre for Human Virology and Genomics, Nigerian Institute of Medical Research, Lagos, Nigeria.
| | - Abdoulie Kanteh
- Genomic Core facility, Medical Research Council Unit, The Gambia at LSHTM, Fajara, Banjul, The Gambia
| | | | - Rahaman Ademolu Ahmed
- Centre for Human Virology and Genomics, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Chika Leona Okoli
- Centre for Human Virology and Genomics, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Joseph Ojonugwa Shaibu
- Centre for Human Virology and Genomics, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Ayorinde B James
- Biochemistry and Nutrition Department, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Olusola Ajibaye
- Biochemistry and Nutrition Department, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Azuka P Okwuraiwe
- Centre for Human Virology and Genomics, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Muinah Fowora
- Central Research Laboratory, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Ngozi Otuonye
- Central Research Laboratory, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Archibald Worwui
- HPC facility, Medical Research Council Unit, The Gambia at LSHTM, Fajara, Banjul, The Gambia
| | - Bamidele Iwalokun
- Central Research Laboratory, Nigerian Institute of Medical Research, Lagos, Nigeria
| | - Dembo Kanteh
- Research Support Unit, Medical Research Council Unit, The Gambia at LSHTM, Fajara, Banjul, The Gambia
| | - Rosemary A Audu
- Microbiology Department, Nigerian Institute of Medical Research, Lagos, Nigeria
| | | | - Umberto D'Alessandro
- Disease Control and Elimination Research Group, Medical Research Council Unit, The Gambia at LSHTM, Fajara, Banjul, The Gambia
| | | | - Abdul Karim Sesay
- Genomic Core facility, Medical Research Council Unit, The Gambia at LSHTM, Fajara, Banjul, The Gambia
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Murall CL, Fournier E, Galvez JH, N'Guessan A, Reiling SJ, Quirion PO, Naderi S, Roy AM, Chen SH, Stretenowich P, Bourgey M, Bujold D, Gregoire R, Lepage P, St-Cyr J, Willet P, Dion R, Charest H, Lathrop M, Roger M, Bourque G, Ragoussis J, Shapiro BJ, Moreira S. A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada. Genome Med 2021; 13:169. [PMID: 34706766 PMCID: PMC8550813 DOI: 10.1186/s13073-021-00986-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 10/05/2021] [Indexed: 11/10/2022] Open
Abstract
Background Québec was the Canadian province most impacted by COVID-19, with 401,462 cases as of September 24th, 2021, and 11,347 deaths due mostly to a very severe first pandemic wave. In April 2020, we assembled the Coronavirus Sequencing in Québec (CoVSeQ) consortium to sequence SARS-CoV-2 genomes in Québec to track viral introduction events and transmission within the province. Methods Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec. We report 2921 high-quality SARS-CoV-2 genomes in the context of > 12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatiotemporal spread of the virus. Results Conservatively, we estimated approximately 600 independent introduction events, the majority of which happened from spring break until 2 weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (> 50 sequenced cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and “snowbird” destinations, most of the introductions were inferred to have originated from Europe via the Americas. Once introduced into Québec, viral lineage sizes were overdispersed, with a few lineages giving rise to most infections. Consistent with founder effects, the earliest lineages to arrive tended to spread most successfully. Fewer than 100 viral introductions arrived during spring break, of which 7–12 led to the largest transmission lineages of the first wave (accounting for 52–75% of all sequenced infections). These successful transmission lineages dispersed widely across the province. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travellers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Conclusions Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00986-9.
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Affiliation(s)
- Carmen Lía Murall
- McGill Genome Centre, Montreal, QC, Canada.,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.,Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada
| | - Eric Fournier
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
| | - Jose Hector Galvez
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Arnaud N'Guessan
- Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada
| | - Sarah J Reiling
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Pierre-Olivier Quirion
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada.,Calcul Québec, Montreal, QC, Canada
| | - Sana Naderi
- McGill Genome Centre, Montreal, QC, Canada.,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Anne-Marie Roy
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Shu-Huang Chen
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Paul Stretenowich
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Mathieu Bourgey
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - David Bujold
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Romain Gregoire
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | | | | | | | - Réjean Dion
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada.,Ecole de santé publique, Université de Montréal, Montreal, QC, Canada
| | - Hugues Charest
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
| | - Mark Lathrop
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Michel Roger
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada.,Département de Microbiologie, infectiologie et Immunologie, Université de Montréal, Montreal, QC, Canada
| | - Guillaume Bourque
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Jiannis Ragoussis
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada.,Department of Bioengineering, McGill University, Montreal, QC, Canada
| | - B Jesse Shapiro
- McGill Genome Centre, Montreal, QC, Canada. .,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada. .,Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada.
| | - Sandrine Moreira
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
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45
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Franceschi VB, Ferrareze PAG, Zimerman RA, Cybis GB, Thompson CE. Mutation hotspots and spatiotemporal distribution of SARS-CoV-2 lineages in Brazil, February 2020-2021. Virus Res 2021; 304:198532. [PMID: 34363852 PMCID: PMC8654641 DOI: 10.1016/j.virusres.2021.198532] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 07/21/2021] [Accepted: 07/29/2021] [Indexed: 12/21/2022]
Abstract
The COVID-19 pandemic has already reached more than 110 million people and is associated with 2.5 million deaths worldwide. Brazil is the third worst-hit country, with approximately 10.2 million cases and 250 thousand deaths. International efforts have been established to share information about Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemiology and evolution to support the development of effective strategies for public health and disease management. We aimed to analyze the high-quality genome sequences from Brazil from February 2020-2021 to identify mutation hotspots, geographical and temporal distribution of SARS-CoV-2 lineages by using phylogenetics and phylodynamics analyses. We describe heterogeneous sequencing efforts, the progression of the different lineages along time, evaluating mutational spectra and frequency oscillations derived from the prevalence of specific lineages across different Brazilian regions. We found at least seven major (1-7) and two minor clades related to the six most prevalent lineages in the country and described its spatial distribution and dynamics. The emergence and recent frequency shift of lineages (P.1 and P.2) carrying mutations of concern in the spike protein (e. g., E484K, N501Y) draws attention due to their association with immune evasion and enhanced receptor binding affinity. Improvements in genomic surveillance are of paramount importance and should be extended in Brazil to better inform policy makers about better decisions to fight the COVID-19 pandemic.
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Affiliation(s)
- Vinícius Bonetti Franceschi
- Graduate Program in Cell and Molecular Biology (PPGBCM), Center of Biotechnology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Patrícia Aline Gröhs Ferrareze
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil
| | - Ricardo Ariel Zimerman
- Department of Infection Control and Prevention, Hospital da Brigada Militar, Porto Alegre, RS, Brazil
| | - Gabriela Bettella Cybis
- Department of Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Claudia Elizabeth Thompson
- Graduate Program in Cell and Molecular Biology (PPGBCM), Center of Biotechnology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brazil; Department of Pharmacosciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), 245/200C Sarmento Leite St, Porto Alegre, RS 90050-170, Brazil.
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46
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González-González E, Garcia-Ramirez R, Díaz-Armas GG, Esparza M, Aguilar-Avelar C, Flores-Contreras EA, Rodríguez-Sánchez IP, Delgado-Balderas JR, Soto-García B, Aráiz-Hernández D, Abarca-Blanco M, Yee-de León JR, Velarde-Calvillo LP, Abarca-Blanco A, Yee-de León JF. Automated ELISA On-Chip for the Detection of Anti-SARS-CoV-2 Antibodies. SENSORS 2021; 21:s21206785. [PMID: 34695998 PMCID: PMC8539637 DOI: 10.3390/s21206785] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/22/2021] [Accepted: 09/26/2021] [Indexed: 12/29/2022]
Abstract
The COVID-19 pandemic has been the most critical public health issue in modern history due to its highly infectious and deathly potential, and the limited access to massive, low-cost, and reliable testing has significantly worsened the crisis. The recovery and the vaccination of millions of people against COVID-19 have made serological tests highly relevant to identify the presence and levels of SARS-CoV-2 antibodies. Due to its advantages, microfluidic-based technologies represent an attractive alternative to the conventional testing methodologies used for these purposes. In this work, we described the development of an automated ELISA on-chip capable of detecting anti-SARS-CoV-2 antibodies in serum samples from COVID-19 patients and vaccinated individuals. The colorimetric reactions were analyzed with a microplate reader. No statistically significant differences were observed when comparing the results of our automated ELISA on-chip against the ones obtained from a traditional ELISA on a microplate. Moreover, we demonstrated that it is possible to carry out the analysis of the colorimetric reaction by performing basic image analysis of photos taken with a smartphone, which constitutes a useful alternative when lacking specialized equipment or a laboratory setting. Our automated ELISA on-chip has the potential to be used in a clinical setting and mitigates some of the burden caused by testing deficiencies.
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Affiliation(s)
- Everardo González-González
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, NL, Mexico
| | - Ricardo Garcia-Ramirez
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Gladys Guadalupe Díaz-Armas
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Miguel Esparza
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Carlos Aguilar-Avelar
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Elda A. Flores-Contreras
- Departamento de Bioquímica y Medicina Molecular, Facultad de Medicina, Universidad Autónoma de Nuevo León, San Nicolás de los Garza 64460, NL, Mexico;
| | - Irám Pablo Rodríguez-Sánchez
- Laboratorio de Fisiología Molecular y Estructural, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolás de los Garza 66455, NL, Mexico;
| | - Jesus Rolando Delgado-Balderas
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Brenda Soto-García
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Diana Aráiz-Hernández
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Marisol Abarca-Blanco
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - José R. Yee-de León
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Liza P. Velarde-Calvillo
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
| | - Alejandro Abarca-Blanco
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
- Correspondence: (A.A.-B.); (J.F.Y.-d.L.)
| | - Juan F. Yee-de León
- Delee Corp., Mountain View, CA 94041, USA; (E.G.-G.); (R.G.-R.); (G.G.D.-A.); (M.E.); (C.A.-A.); (J.R.D.-B.); (B.S.-G.); (D.A.-H.); (M.A.-B.); (J.R.Y.-d.L.); (L.P.V.-C.)
- Correspondence: (A.A.-B.); (J.F.Y.-d.L.)
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47
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van Dorp L, Houldcroft CJ, Richard D, Balloux F. COVID-19, the first pandemic in the post-genomic era. Curr Opin Virol 2021; 50:40-48. [PMID: 34352474 PMCID: PMC8275481 DOI: 10.1016/j.coviro.2021.07.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 07/06/2021] [Accepted: 07/06/2021] [Indexed: 12/28/2022]
Abstract
The scale of the international efforts to sequence SARS-CoV-2 genomes is unprecedented. Early availability of genomes allowed rapid characterisation of the virus, thus kickstarting many highly successful vaccine development programmes. Worldwide genomic resources have provided a good understanding of the pandemic, supported close monitoring of the emergence of viral genomic diversity and pinpointed those sites to prioritise for functional characterisation. Continued genomic surveillance of global viral populations will be crucial to inform the timing of vaccine updates so as to pre-empt the spread of immune escape lineages. While genome sequencing has provided us with an exceptionally powerful tool to monitor the evolution of SARS-CoV-2, there is room for further improvements in particular in the form of less heterogeneous global surveillance and tools to rapidly identify concerning viral lineages.
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Affiliation(s)
- Lucy van Dorp
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
| | | | - Damien Richard
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK; Division of Infection and Immunity, University College London, London, WC1E 6BT, UK
| | - François Balloux
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
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48
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Lee K. Restarting international travel will be messy but enabled by improved risk-based analyses. LANCET REGIONAL HEALTH-WESTERN PACIFIC 2021; 13:100209. [PMID: 34527991 PMCID: PMC8403889 DOI: 10.1016/j.lanwpc.2021.100209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 06/21/2021] [Indexed: 11/25/2022]
Affiliation(s)
- Kelley Lee
- Professor and Tier 1 Canada Research Chair in Global Health Governance, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC Canada V5A 1S6
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49
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Szemiel AM, Merits A, Orton RJ, MacLean OA, Pinto RM, Wickenhagen A, Lieber G, Turnbull ML, Wang S, Furnon W, Suarez NM, Mair D, da Silva Filipe A, Willett BJ, Wilson SJ, Patel AH, Thomson EC, Palmarini M, Kohl A, Stewart ME. In vitro selection of Remdesivir resistance suggests evolutionary predictability of SARS-CoV-2. PLoS Pathog 2021; 17:e1009929. [PMID: 34534263 PMCID: PMC8496873 DOI: 10.1371/journal.ppat.1009929] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 10/07/2021] [Accepted: 08/30/2021] [Indexed: 01/18/2023] Open
Abstract
Remdesivir (RDV), a broadly acting nucleoside analogue, is the only FDA approved small molecule antiviral for the treatment of COVID-19 patients. To date, there are no reports identifying SARS-CoV-2 RDV resistance in patients, animal models or in vitro. Here, we selected drug-resistant viral populations by serially passaging SARS-CoV-2 in vitro in the presence of RDV. Using high throughput sequencing, we identified a single mutation in RNA-dependent RNA polymerase (NSP12) at a residue conserved among all coronaviruses in two independently evolved populations displaying decreased RDV sensitivity. Introduction of the NSP12 E802D mutation into our SARS-CoV-2 reverse genetics backbone confirmed its role in decreasing RDV sensitivity in vitro. Substitution of E802 did not affect viral replication or activity of an alternate nucleoside analogue (EIDD2801) but did affect virus fitness in a competition assay. Analysis of the globally circulating SARS-CoV-2 variants (>800,000 sequences) showed no evidence of widespread transmission of RDV-resistant mutants. Surprisingly, we observed an excess of substitutions in spike at corresponding sites identified in the emerging SARS-CoV-2 variants of concern (i.e., H69, E484, N501, H655) indicating that they can arise in vitro in the absence of immune selection. The identification and characterisation of a drug resistant signature within the SARS-CoV-2 genome has implications for clinical management and virus surveillance.
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Affiliation(s)
| | - Andres Merits
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Richard J. Orton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Oscar A. MacLean
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Rute Maria Pinto
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Arthur Wickenhagen
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Gauthier Lieber
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Matthew L. Turnbull
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Sainan Wang
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Nicolas M. Suarez
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Daniel Mair
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Brian J. Willett
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Sam J. Wilson
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Arvind H. Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Emma C. Thomson
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Massimo Palmarini
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Alain Kohl
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
| | - Meredith E. Stewart
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
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50
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Henery P, Vasileiou E, Hainey KJ, Buchanan D, Harrison E, Leyland AH, Alexis T, Robertson C, Agrawal U, Ritchie L, Stock SJ, McCowan C, Docherty A, Kerr S, Marple J, Wood R, Moore E, Simpson CR, Sheikh A, Katikireddi SV. Ethnic and social inequalities in COVID-19 outcomes in Scotland: protocol for early pandemic evaluation and enhanced surveillance of COVID-19 (EAVE II). BMJ Open 2021; 11:e048852. [PMID: 34376451 PMCID: PMC8359861 DOI: 10.1136/bmjopen-2021-048852] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION Evidence from previous pandemics, and the current COVID-19 pandemic, has found that risk of infection/severity of disease is disproportionately higher for ethnic minority groups, and those in lower socioeconomic positions. It is imperative that interventions to prevent the spread of COVID-19 are targeted towards high-risk populations. We will investigate the associations between social characteristics (such as ethnicity, occupation and socioeconomic position) and COVID-19 outcomes and the extent to which characteristics/risk factors might explain observed relationships in Scotland.The primary objective of this study is to describe the epidemiology of COVID-19 by social factors. Secondary objectives are to (1) examine receipt of treatment and prevention of COVID-19 by social factors; (2) quantify ethnic/social differences in adverse COVID-19 outcomes; (3) explore potential mediators of relationships between social factors and SARS-CoV-2 infection/COVID-19 prognosis; (4) examine whether occupational COVID-19 differences differ by other social factors and (5) assess quality of ethnicity coding within National Health Service datasets. METHODS AND ANALYSIS We will use a national cohort comprising the adult population of Scotland who completed the 2011 Census and were living in Scotland on 31 March 2020 (~4.3 million people). Census data will be linked to the Early Assessment of Vaccine and Anti-Viral Effectiveness II cohort consisting of primary/secondary care, laboratory data and death records. Sensitivity/specificity and positive/negative predictive values will be used to assess coding quality of ethnicity. Descriptive statistics will be used to examine differences in treatment and prevention of COVID-19. Poisson/Cox regression analyses and mediation techniques will examine ethnic and social differences, and drivers of inequalities in COVID-19. Effect modification (on additive and multiplicative scales) between key variables (such as ethnicity and occupation) will be assessed. ETHICS AND DISSEMINATION Ethical approval was obtained from the National Research Ethics Committee, South East Scotland 02. We will present findings of this study at international conferences, in peer-reviewed journals and to policy-makers.
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Affiliation(s)
- Paul Henery
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
- Public Health Scotland, Edinburgh, UK
| | | | - Kirsten J Hainey
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | | | - Ewen Harrison
- Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - Alastair H Leyland
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
| | | | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
| | - Utkarsh Agrawal
- School of Medicine, University of St Andrews, St Andrews, Fife, UK
| | - Lewis Ritchie
- General Practice and Primary Care, Aberdeen University, Aberdeen, UK
| | - Sarah Jane Stock
- Public Health Scotland, Edinburgh, UK
- Centre for Medical Informatics, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - Colin McCowan
- School of Medicine, University of St. Andrews, St. Andrews, UK
| | | | - Steven Kerr
- Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - James Marple
- Division of Community Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Rachael Wood
- Usher Institute, The University of Edinburgh, Edinburgh, UK
- Information Services Division, NHS National Services Scotland, Edinburgh, UK
| | | | - Colin R Simpson
- Usher Institute, The University of Edinburgh, Edinburgh, UK
- Wellington Faculty of Health, Victoria University of Wellington, Wellington, New Zealand
| | - Aziz Sheikh
- Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - Srinivasa Vittal Katikireddi
- MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
- Public Health Scotland, Edinburgh, UK
| |
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