1
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Wegner F, Cabrera-Gil B, Tanguy A, Beckmann C, Beerenwinkel N, Bertelli C, Carrara M, Cerutti L, Chen C, Cordey S, Dumoulin A, du Plessis L, Friedli M, Gerth Y, Greub G, Härri A, Hirsch H, Howald C, Huber M, Imhof A, Kaiser L, Kufner V, Leib SL, Leuzinger K, Lleshi E, Martinetti G, Mäusezahl M, Moraz M, Neher R, Nolte O, Ramette A, Redondo M, Risch L, Rohner L, Roloff T, Schläepfer P, Schneider K, Singer F, Spina V, Stadler T, Studer E, Topolsky I, Trkola A, Walther D, Wohlwend N, Zehnder C, Neves A, Egli A. How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort. Microbiol Spectr 2024; 12:e0362823. [PMID: 38497714 PMCID: PMC11064629 DOI: 10.1128/spectrum.03628-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/01/2024] [Indexed: 03/19/2024] Open
Abstract
During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.
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Affiliation(s)
- Fanny Wegner
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | - Blanca Cabrera-Gil
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | | | | | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Claire Bertelli
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
| | - Matteo Carrara
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | | | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Samuel Cordey
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
| | | | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | | | - Yannick Gerth
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
| | - Gilbert Greub
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
| | | | - Hans Hirsch
- Clinical Virology, University Hospital, Basel, Switzerland
| | | | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Laurent Kaiser
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
| | - Verena Kufner
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Stephen L. Leib
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
| | | | - Etleva Lleshi
- Microbiology Department, Synlab, Bioggio, Switzerland
| | - Gladys Martinetti
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | | | - Milo Moraz
- Valais Hospital, Central Institute, Sion, Switzerland
| | - Richard Neher
- Biozentrum, University of Basel, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Oliver Nolte
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
| | | | | | | | - Tim Roloff
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | | | | | - Franziska Singer
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Valeria Spina
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Erik Studer
- Federal Office of Public Health, Bern, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Alexandra Trkola
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Daniel Walther
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | | | | | - Aitana Neves
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
| | - Adrian Egli
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
| | - the SPSP consortium
- Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland
- Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Genesupport, Geneva, Switzerland
- Viollier AG, Allschwil, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Clinical Microbiology, University Hospital, Lausanne, Switzerland
- NEXUS Personalized Health Technologies, ETH Zurich, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Health2030 Genome Center, Geneva, Switzerland
- Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland
- Valais Hospital, Central Institute, Sion, Switzerland
- Humanmedizinische Mikrobiologie, Zentrum für Labormedizin, St. Gallen, Switzerland
- Biolytix, Witterswil, Switzerland
- Clinical Virology, University Hospital, Basel, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
- Spitalregion Oberaargau, Langenthal, Switzerland
- Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
- Microbiology Department, Synlab, Bioggio, Switzerland
- Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Federal Office of Public Health, Bern, Switzerland
- Biozentrum, University of Basel, Switzerland & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
- Labor Dr. Risch, Buchs, Switzerland
- Clinical Microbiology, University Hospital, Basel, Switzerland
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2
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Majander K, Pla-Díaz M, du Plessis L, Arora N, Filippini J, Pezo-Lanfranco L, Eggers S, González-Candelas F, Schuenemann VJ. Redefining the treponemal history through pre-Columbian genomes from Brazil. Nature 2024; 627:182-188. [PMID: 38267579 PMCID: PMC10917687 DOI: 10.1038/s41586-023-06965-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 12/12/2023] [Indexed: 01/26/2024]
Abstract
The origins of treponemal diseases have long remained unknown, especially considering the sudden onset of the first syphilis epidemic in the late 15th century in Europe and its hypothesized arrival from the Americas with Columbus' expeditions1,2. Recently, ancient DNA evidence has revealed various treponemal infections circulating in early modern Europe and colonial-era Mexico3-6. However, there has been to our knowledge no genomic evidence of treponematosis recovered from either the Americas or the Old World that can be reliably dated to the time before the first trans-Atlantic contacts. Here, we present treponemal genomes from nearly 2,000-year-old human remains from Brazil. We reconstruct four ancient genomes of a prehistoric treponemal pathogen, most closely related to the bejel-causing agent Treponema pallidum endemicum. Contradicting the modern day geographical niche of bejel in the arid regions of the world, the results call into question the previous palaeopathological characterization of treponeme subspecies and showcase their adaptive potential. A high-coverage genome is used to improve molecular clock date estimations, placing the divergence of modern T. pallidum subspecies firmly in pre-Columbian times. Overall, our study demonstrates the opportunities within archaeogenetics to uncover key events in pathogen evolution and emergence, paving the way to new hypotheses on the origin and spread of treponematoses.
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Affiliation(s)
- Kerttu Majander
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.
- Department of Environmental Sciences, University of Basel, Basel, Switzerland.
| | - Marta Pla-Díaz
- Unidad Mixta Infección y Salud Pública, FISABIO/Universidad de Valencia-I2SysBio, Valencia, Spain
- CIBER in Epidemiology and Public Health, Instituto de Salud Carlos III, Madrid, Spain
| | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge, Lausanne, Switzerland
| | - Natasha Arora
- Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland
| | - Jose Filippini
- Department of Genetic and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
| | - Luis Pezo-Lanfranco
- Department of Genetic and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
- Institute of Environmental Science and Technology (ICTA) and Prehistory Department, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Sabine Eggers
- Department of Genetic and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
- Department of Anthropology, Natural History Museum Vienna, Vienna, Austria
| | - Fernando González-Candelas
- Unidad Mixta Infección y Salud Pública, FISABIO/Universidad de Valencia-I2SysBio, Valencia, Spain.
- CIBER in Epidemiology and Public Health, Instituto de Salud Carlos III, Madrid, Spain.
| | - Verena J Schuenemann
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.
- Department of Environmental Sciences, University of Basel, Basel, Switzerland.
- Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria.
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3
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Fiddaman SR, Dimopoulos EA, Lebrasseur O, du Plessis L, Vrancken B, Charlton S, Haruda AF, Tabbada K, Flammer PG, Dascalu S, Marković N, Li H, Franklin G, Symmons R, Baron H, Daróczi-Szabó L, Shaymuratova DN, Askeyev IV, Putelat O, Sana M, Davoudi H, Fathi H, Mucheshi AS, Vahdati AA, Zhang L, Foster A, Sykes N, Baumberg GC, Bulatović J, Askeyev AO, Askeyev OV, Mashkour M, Pybus OG, Nair V, Larson G, Smith AL, Frantz LAF. Ancient chicken remains reveal the origins of virulence in Marek's disease virus. Science 2023; 382:1276-1281. [PMID: 38096384 DOI: 10.1126/science.adg2238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 10/25/2023] [Indexed: 12/18/2023]
Abstract
The pronounced growth in livestock populations since the 1950s has altered the epidemiological and evolutionary trajectory of their associated pathogens. For example, Marek's disease virus (MDV), which causes lymphoid tumors in chickens, has experienced a marked increase in virulence over the past century. Today, MDV infections kill >90% of unvaccinated birds, and controlling it costs more than US$1 billion annually. By sequencing MDV genomes derived from archeological chickens, we demonstrate that it has been circulating for at least 1000 years. We functionally tested the Meq oncogene, one of 49 viral genes positively selected in modern strains, demonstrating that ancient MDV was likely incapable of driving tumor formation. Our results demonstrate the power of ancient DNA approaches to trace the molecular basis of virulence in economically relevant pathogens.
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Affiliation(s)
| | - Evangelos A Dimopoulos
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Ophélie Lebrasseur
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS/Université Toulouse III Paul Sabatier, Toulouse, France
- Instituto Nacional de Antropología y Pensamiento Latinoamericano, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
| | - Sophy Charlton
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
- BioArCh, Department of Archaeology, University of York, York, UK
| | - Ashleigh F Haruda
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Kristina Tabbada
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | | | | | | | - Hannah Li
- Institute of Immunity and Transplantation, University College London, London, UK
| | | | | | | | | | - Dilyara N Shaymuratova
- Laboratory of Biomonitoring, The Institute of Problems in Ecology and Mineral Wealth, Tatarstan Academy of Sciences, Kazan, Russia
| | - Igor V Askeyev
- Laboratory of Biomonitoring, The Institute of Problems in Ecology and Mineral Wealth, Tatarstan Academy of Sciences, Kazan, Russia
| | | | - Maria Sana
- Departament de Prehistòria, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Hossein Davoudi
- Bioarchaeology Laboratory, Central Laboratory, University of Tehran, Tehran, Iran
| | - Homa Fathi
- Bioarchaeology Laboratory, Central Laboratory, University of Tehran, Tehran, Iran
| | - Amir Saed Mucheshi
- Department of Art and Architecture, Payame Noor University (PNU), Tehran, Iran
| | - Ali Akbar Vahdati
- Iranian Ministry of Cultural Heritage, Tourism, and Handicrafts, North Khorasan Office, Iran
| | - Liangren Zhang
- Department of Archaeology, School of History, Nanjing University, China
| | | | - Naomi Sykes
- Department of Archaeology, University of Exeter, Exeter, UK
| | - Gabrielle Cass Baumberg
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Jelena Bulatović
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Arthur O Askeyev
- Laboratory of Biomonitoring, The Institute of Problems in Ecology and Mineral Wealth, Tatarstan Academy of Sciences, Kazan, Russia
| | - Oleg V Askeyev
- Laboratory of Biomonitoring, The Institute of Problems in Ecology and Mineral Wealth, Tatarstan Academy of Sciences, Kazan, Russia
| | - Marjan Mashkour
- Bioarchaeology Laboratory, Central Laboratory, University of Tehran, Tehran, Iran
- CNRS, National Museum Natural History Paris, Paris, France
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK
| | - Venugopal Nair
- Department of Biology, University of Oxford, Oxford, UK
- Viral Oncogenesis Group, Pirbright Institute, Woking, UK
| | - Greger Larson
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | | | - Laurent A F Frantz
- Palaeogenomics Group, Institute of Palaeoanatomy, Domestication Research and the History of Veterinary Medicine, Ludwig-Maximilians-Universitat, Munich, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
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4
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Akhmetova A, Guerrero J, McAdam P, Salvador LCM, Crispell J, Lavery J, Presho E, Kao RR, Biek R, Menzies F, Trimble N, Harwood R, Pepler PT, Oravcova K, Graham J, Skuce R, du Plessis L, Thompson S, Wright L, Byrne AW, Allen AR. Genomic epidemiology of Mycobacterium bovis infection in sympatric badger and cattle populations in Northern Ireland. Microb Genom 2023; 9. [PMID: 37227264 DOI: 10.1099/mgen.0.001023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023] Open
Abstract
Bovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Lack of understanding of transmission dynamics may undermine eradication efforts. Pathogen whole-genome sequencing improves epidemiological inferences, providing a means to determine the relative importance of inter- and intra-species host transmission for disease persistence. We sequenced an exceptional data set of 619 Mycobacterium bovis isolates from badgers and cattle in a 100 km2 bTB 'hotspot' in Northern Ireland. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided a unique opportunity to study disease transmission dynamics in unparalleled detail. Additionally, to assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area. Birth death models and TransPhylo analyses indicated that cattle were likely driving the local epidemic, with transmission from cattle to badgers being more common than badger to cattle. Furthermore, the presence of significant badger population genetic structure in the landscape was not associated with the spatial distribution of M. bovis genetic diversity, suggesting that badger-to-badger transmission is not playing a major role in transmission dynamics. Our data were consistent with badgers playing a smaller role in transmission of M. bovis infection in this study site, compared to cattle. We hypothesize, however, that this minor role may still be important for persistence. Comparison to other areas suggests that M. bovis transmission dynamics are likely to be context dependent, with the role of wildlife being difficult to generalize.
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Affiliation(s)
| | | | | | - Liliana C M Salvador
- Present address: School of Animal and Comparative Biomedical Sciences, University of Arizona, AZ, Tucson, USA
- Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, USA
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
- Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
| | | | | | | | - Rowland R Kao
- University of Edinburgh, Roslin Institute, Edinburgh, UK
| | | | - Fraser Menzies
- Department of Agriculture, Environment and Rural Affairs (DAERA), Belfast, UK
| | - Nigel Trimble
- Department of Agriculture, Environment and Rural Affairs (DAERA), Belfast, UK
| | - Roland Harwood
- Department of Agriculture, Environment and Rural Affairs (DAERA), Belfast, UK
| | | | | | | | - Robin Skuce
- Agrifood and Biosciences Institute, Belfast, UK
| | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Andrew W Byrne
- Department of Agriculture Food and the Marine (DAFM), Dublin, Ireland
- Agrifood and Biosciences Institute, Belfast, UK
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5
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Nadeau SA, Vaughan TG, Beckmann C, Topolsky I, Chen C, Hodcroft E, Schär T, Nissen I, Santacroce N, Burcklen E, Ferreira P, Jablonski KP, Posada-Céspedes S, Capece V, Seidel S, Santamaria de Souza N, Martinez-Gomez JM, Cheng P, Bosshard PP, Levesque MP, Kufner V, Schmutz S, Zaheri M, Huber M, Trkola A, Cordey S, Laubscher F, Gonçalves AR, Aeby S, Pillonel T, Jacot D, Bertelli C, Greub G, Leuzinger K, Stange M, Mari A, Roloff T, Seth-Smith H, Hirsch HH, Egli A, Redondo M, Kobel O, Noppen C, du Plessis L, Beerenwinkel N, Neher RA, Beisel C, Stadler T. Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data. Sci Transl Med 2023; 15:eabn7979. [PMID: 36346321 PMCID: PMC9765449 DOI: 10.1126/scitranslmed.abn7979] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020-the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland's border closures decoupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 to 98% reduction in introductions during Switzerland's strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred using a phylodynamic model. We found that transmission slowed 35 to 63% upon outbreak detection in summer 2020 but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.
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Affiliation(s)
- Sarah A. Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Corresponding author. (T.S.); (S.A.N.)
| | - Timothy G. Vaughan
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | | | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Emma Hodcroft
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Institute for Social and Preventive Medicine, University of Bern; 3012, Bern, Switzerland
| | - Tobias Schär
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Ina Nissen
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Natascha Santacroce
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Elodie Burcklen
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Pedro Ferreira
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Susana Posada-Céspedes
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Vincenzo Capece
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Sophie Seidel
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | | | - Julia M. Martinez-Gomez
- Department of Dermatology, University Hospital Zurich, University of Zurich; 8091, Zurich, Switzerland
| | - Phil Cheng
- Department of Dermatology, University Hospital Zurich, University of Zurich; 8091, Zurich, Switzerland
| | - Philipp P. Bosshard
- Department of Dermatology, University Hospital Zurich, University of Zurich; 8091, Zurich, Switzerland
| | - Mitchell P. Levesque
- Department of Dermatology, University Hospital Zurich, University of Zurich; 8091, Zurich, Switzerland
| | - Verena Kufner
- Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland
| | - Stefan Schmutz
- Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland
| | - Maryam Zaheri
- Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland
| | - Alexandra Trkola
- Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland
| | - Samuel Cordey
- Laboratory of Virology, Department of Diagnostics, Geneva University Hospitals & Faculty of Medicine; 1205, Geneva, Switzerland
| | - Florian Laubscher
- Laboratory of Virology, Department of Diagnostics, Geneva University Hospitals & Faculty of Medicine; 1205, Geneva, Switzerland
| | - Ana Rita Gonçalves
- Swiss National Reference Centre for Influenza, University Hospitals of Geneva; 1205, Geneva, Switzerland
| | - Sébastien Aeby
- Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland
| | - Trestan Pillonel
- Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland
| | - Damien Jacot
- Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland
| | - Claire Bertelli
- Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland
| | - Gilbert Greub
- Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland
| | - Karoline Leuzinger
- Division of Clinical Virology, University Hospital Basel; 4051, Basel, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland
| | - Madlen Stange
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.,Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland
| | - Alfredo Mari
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.,Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland
| | - Tim Roloff
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.,Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland
| | - Helena Seth-Smith
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.,Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland
| | - Hans H. Hirsch
- Division of Clinical Virology, University Hospital Basel; 4051, Basel, Switzerland.,Department of Biomedicine, University of Basel; 4031, Basel, Switzerland
| | - Adrian Egli
- Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.,Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland
| | | | | | | | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland
| | - Richard A. Neher
- SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Biozentrum, University of Basel; 4056, Basel, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.,Corresponding author. (T.S.); (S.A.N.)
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6
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McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Jackson B, Colquhoun R, O'Toole Á, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUG. Context-specific emergence and growth of the SARS-CoV-2 Delta variant. Nature 2022; 610:154-160. [PMID: 35952712 PMCID: PMC9534748 DOI: 10.1038/s41586-022-05200-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 08/05/2022] [Indexed: 02/01/2023]
Abstract
The SARS-CoV-2 Delta (Pango lineage B.1.617.2) variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. The emergence of the Delta variant in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 SARS-CoV-2 genomes from England together with 93,649 genomes from the rest of the world to reconstruct the emergence of Delta and quantify its introduction to and regional dissemination across England in the context of changing travel and social restrictions. Using analysis of human movement, contact tracing and virus genomic data, we find that the geographic focus of the expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced more than 1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers reduced onward transmission from importations; however, the transmission chains that later dominated the Delta wave in England were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove the nationwide dissemination of Delta, with some cities receiving more than 2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing-and not the number of importations-were associated with the faster relative spread of Delta. The invasion dynamics of Delta depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce the transmission of current and future variants of concern, such as Omicron (Pango lineage B.1.1.529).
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Affiliation(s)
- John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Sumali Bajaj
- Department of Zoology, University of Oxford, Oxford, UK
| | | | - Ben C Lambert
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Rhys Inward
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Erik Volz
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Christopher Ruis
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- 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
| | | | | | - Neo Wu
- Google, Mountain View, CA, USA
| | | | - Xiang Ji
- Department of Mathematics, School of Science and Engineering, Tulane University, New Orleans, LA, USA
| | | | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Thomas P Peacock
- Department of Infectious Disease, Imperial College London, London, UK
- UK Health Security Agency, London, UK
| | | | | | | | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Isaac I Bogoch
- Divisions of Internal Medicine and Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Kamran Khan
- BlueDot, Toronto, Ontario, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Wendy S Barclay
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Thomas Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, The Sir Martin Evans Building, Cardiff University, Cardiff, UK
- Quadram Institute, Norwich, UK
| | - Nicholas J Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Marc A Suchard
- Departments of Biostatistics, Biomathematics and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK.
- Pandemic Sciences Institute, University of Oxford, Oxford, UK.
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
- Pandemic Sciences Institute, University of Oxford, Oxford, UK.
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7
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Viana R, Moyo S, Amoako DG, Tegally H, Scheepers C, Althaus CL, Anyaneji UJ, Bester PA, Boni MF, Chand M, Choga WT, Colquhoun R, Davids M, Deforche K, Doolabh D, du Plessis L, Engelbrecht S, Everatt J, Giandhari J, Giovanetti M, Hardie D, Hill V, Hsiao NY, Iranzadeh A, Ismail A, Joseph C, Joseph R, Koopile L, Kosakovsky Pond SL, Kraemer MUG, Kuate-Lere L, Laguda-Akingba O, Lesetedi-Mafoko O, Lessells RJ, Lockman S, Lucaci AG, Maharaj A, Mahlangu B, Maponga T, Mahlakwane K, Makatini Z, Marais G, Maruapula D, Masupu K, Matshaba M, Mayaphi S, Mbhele N, Mbulawa MB, Mendes A, Mlisana K, Mnguni A, Mohale T, Moir M, Moruisi K, Mosepele M, Motsatsi G, Motswaledi MS, Mphoyakgosi T, Msomi N, Mwangi PN, Naidoo Y, Ntuli N, Nyaga M, Olubayo L, Pillay S, Radibe B, Ramphal Y, Ramphal U, San JE, Scott L, Shapiro R, Singh L, Smith-Lawrence P, Stevens W, Strydom A, Subramoney K, Tebeila N, Tshiabuila D, Tsui J, van Wyk S, Weaver S, Wibmer CK, Wilkinson E, Wolter N, Zarebski AE, Zuze B, Goedhals D, Preiser W, Treurnicht F, Venter M, Williamson C, Pybus OG, Bhiman J, Glass A, Martin DP, Rambaut A, Gaseitsiwe S, von Gottberg A, de Oliveira T. Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa. Nature 2022; 603:679-686. [PMID: 35042229 PMCID: PMC8942855 DOI: 10.1038/s41586-022-04411-y] [Citation(s) in RCA: 918] [Impact Index Per Article: 459.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 01/07/2022] [Indexed: 01/02/2023]
Abstract
The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron, B.1.1.529) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, which are predicted to influence antibody neutralization and spike function4. Here we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.
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Affiliation(s)
| | - Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana
| | - Daniel G Amoako
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Houriiyah Tegally
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Cathrine Scheepers
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
- South African Medical Research Council Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Christian L Althaus
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Ugochukwu J Anyaneji
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Phillip A Bester
- Division of Virology, National Health Laboratory Service, Bloemfontein, South Africa
- Division of Virology, University of the Free State, Bloemfontein, South Africa
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA
| | | | | | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Michaela Davids
- Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | | | - Deelan Doolabh
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Susan Engelbrecht
- Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa
| | - Josie Everatt
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Jennifer Giandhari
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Marta Giovanetti
- Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil
- Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Diana Hardie
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Division of Virology, NHLS Groote Schuur Laboratory, Cape Town, South Africa
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Nei-Yuan Hsiao
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Division of Virology, NHLS Groote Schuur Laboratory, Cape Town, South Africa
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
| | - Arash Iranzadeh
- Division of Computational Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Arshad Ismail
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | | | - Rageema Joseph
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Legodile Koopile
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
| | - Sergei L Kosakovsky Pond
- Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Philadelphia, PA, USA
| | | | - Lesego Kuate-Lere
- Health Services Management, Ministry of Health and Wellness, Gaborone, Botswana
| | - Oluwakemi Laguda-Akingba
- NHLS Port Elizabeth Laboratory, Port Elizabeth, South Africa
- Faculty of Health Sciences, Walter Sisulu University, Mthatha, South Africa
| | - Onalethatha Lesetedi-Mafoko
- Public Health Department, Integrated Disease Surveillance and Response, Ministry of Health and Wellness, Gaborone, Botswana
| | - Richard J Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Shahin Lockman
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alexander G Lucaci
- Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Philadelphia, PA, USA
| | - Arisha Maharaj
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Boitshoko Mahlangu
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Tongai Maponga
- Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa
| | - Kamela Mahlakwane
- Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa
- NHLS Tygerberg Laboratory, Tygerberg Hospital, Cape Town, South Africa
| | - Zinhle Makatini
- Department of Virology, Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa
| | - Gert Marais
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Division of Virology, NHLS Groote Schuur Laboratory, Cape Town, South Africa
| | - Dorcas Maruapula
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
| | - Kereng Masupu
- Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana
| | - Mogomotsi Matshaba
- Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana
- Baylor College of Medicine, Houston, TX, USA
| | - Simnikiwe Mayaphi
- Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | - Nokuzola Mbhele
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Mpaphi B Mbulawa
- National Health Laboratory, Health Services Management, Ministry of Health and Wellness, Gaborone, Botswana
| | - Adriano Mendes
- Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | - Koleka Mlisana
- National Health Laboratory Service (NHLS), Johannesburg, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Anele Mnguni
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Thabo Mohale
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Monika Moir
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Kgomotso Moruisi
- Health Services Management, Ministry of Health and Wellness, Gaborone, Botswana
| | - Mosepele Mosepele
- Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana
- Department of Medicine, Faculty of Medicine, University of Botswana, Gaborone, Botswana
| | - Gerald Motsatsi
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Modisa S Motswaledi
- Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana
- Department of Medical Laboratory Sciences, School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana
| | - Thongbotho Mphoyakgosi
- National Health Laboratory, Health Services Management, Ministry of Health and Wellness, Gaborone, Botswana
| | - Nokukhanya Msomi
- Discipline of Virology, School of Laboratory Medicine and Medical Sciences and National Health Laboratory Service (NHLS), University of KwaZulu-Natal, Durban, South Africa
| | - Peter N Mwangi
- Division of Virology, University of the Free State, Bloemfontein, South Africa
- Next Generation Sequencing Unit, Division of Virology, Faculty of Health Sciences, University of the Free State, Bloemfontein, South Africa
| | - Yeshnee Naidoo
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Noxolo Ntuli
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Martin Nyaga
- Division of Virology, University of the Free State, Bloemfontein, South Africa
- Next Generation Sequencing Unit, Division of Virology, Faculty of Health Sciences, University of the Free State, Bloemfontein, South Africa
| | - Lucier Olubayo
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
- Division of Computational Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Sureshnee Pillay
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Botshelo Radibe
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
| | - Yajna Ramphal
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Upasana Ramphal
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - James E San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Lesley Scott
- Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Roger Shapiro
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Lavanya Singh
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | | | - Wendy Stevens
- Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Amy Strydom
- Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | - Kathleen Subramoney
- Department of Virology, Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa
| | - Naume Tebeila
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Derek Tshiabuila
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Joseph Tsui
- Department of Zoology, University of Oxford, Oxford, UK
| | - Stephanie van Wyk
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Steven Weaver
- Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Philadelphia, PA, USA
| | - Constantinos K Wibmer
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Nicole Wolter
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Boitumelo Zuze
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
| | - Dominique Goedhals
- Division of Virology, University of the Free State, Bloemfontein, South Africa
- PathCare Vermaak, Pretoria, South Africa
| | - Wolfgang Preiser
- Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa
- NHLS Tygerberg Laboratory, Tygerberg Hospital, Cape Town, South Africa
| | - Florette Treurnicht
- Department of Virology, Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa
| | - Marietje Venter
- Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | - Carolyn Williamson
- Division of Medical Virology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Division of Virology, NHLS Groote Schuur Laboratory, Cape Town, South Africa
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Jinal Bhiman
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
- South African Medical Research Council Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Allison Glass
- Lancet Laboratories, Johannesburg, South Africa
- Department of Molecular Pathology, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Darren P Martin
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Simani Gaseitsiwe
- Botswana Harvard AIDS Institute Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anne von Gottberg
- National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa.
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
- Department of Global Health, University of Washington, Seattle, WA, USA.
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8
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Raghwani J, du Plessis L, McCrone JT, Hill SC, Parag KV, Thézé J, Kumar D, Puvar A, Pandit R, Pybus OG, Fournié G, Joshi M, Joshi C. Genomic Epidemiology of Early SARS-CoV-2 Transmission Dynamics, Gujarat, India. Emerg Infect Dis 2022; 28:751-758. [PMID: 35203112 PMCID: PMC8962880 DOI: 10.3201/eid2804.212053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Limited genomic sampling in many high-incidence countries has impeded studies of severe respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic epidemiology. Consequently, critical questions remain about the generation and global distribution of virus genetic diversity. We investigated SARS-CoV-2 transmission dynamics in Gujarat, India, during the state’s first epidemic wave to shed light on spread of the virus in one of the regions hardest hit by the pandemic. By integrating case data and 434 whole-genome sequences sampled across 20 districts, we reconstructed the epidemic dynamics and spatial spread of SARS-CoV-2 in Gujarat. Our findings indicate global and regional connectivity and population density were major drivers of the Gujarat outbreak. We detected >100 virus lineage introductions, most of which appear to be associated with international travel. Within Gujarat, virus dissemination occurred predominantly from densely populated regions to geographically proximate locations that had low population density, suggesting that urban centers contributed disproportionately to virus spread.
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9
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Zarebski AE, du Plessis L, Parag KV, Pybus OG. A computationally tractable birth-death model that combines phylogenetic and epidemiological data. PLoS Comput Biol 2022; 18:e1009805. [PMID: 35148311 PMCID: PMC8903285 DOI: 10.1371/journal.pcbi.1009805] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 03/08/2022] [Accepted: 01/05/2022] [Indexed: 11/19/2022] Open
Abstract
Inferring the dynamics of pathogen transmission during an outbreak is an important problem in infectious disease epidemiology. In mathematical epidemiology, estimates are often informed by time series of confirmed cases, while in phylodynamics genetic sequences of the pathogen, sampled through time, are the primary data source. Each type of data provides different, and potentially complementary, insight. Recent studies have recognised that combining data sources can improve estimates of the transmission rate and the number of infected individuals. However, inference methods are typically highly specialised and field-specific and are either computationally prohibitive or require intensive simulation, limiting their real-time utility. We present a novel birth-death phylogenetic model and derive a tractable analytic approximation of its likelihood, the computational complexity of which is linear in the size of the dataset. This approach combines epidemiological and phylodynamic data to produce estimates of key parameters of transmission dynamics and the unobserved prevalence. Using simulated data, we show (a) that the approximation agrees well with existing methods, (b) validate the claim of linear complexity and (c) explore robustness to model misspecification. This approximation facilitates inference on large datasets, which is increasingly important as large genomic sequence datasets become commonplace.
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Affiliation(s)
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Kris Varun Parag
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
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10
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Ghafari M, du Plessis L, Raghwani J, Bhatt S, Xu B, Pybus OG, Katzourakis A. Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza. Mol Biol Evol 2022; 39:6509523. [PMID: 35038728 PMCID: PMC8826518 DOI: 10.1093/molbev/msac009] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.
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Affiliation(s)
- Mahan Ghafari
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Jayna Raghwani
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, United Kingdom
| | - Bo Xu
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Aris Katzourakis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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11
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McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Jackson B, Colquhoun R, O'Toole Á, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUG. Context-specific emergence and growth of the SARS-CoV-2 Delta variant. medRxiv 2021:2021.12.14.21267606. [PMID: 34981069 PMCID: PMC8722612 DOI: 10.1101/2021.12.14.21267606] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases 1-3 . The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions 4,5 . Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.
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Affiliation(s)
- John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- contributed equally as first authors
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- contributed equally as first authors
| | - Sumali Bajaj
- Department of Zoology, University of Oxford, Oxford, UK
- contributed equally as first authors
| | - Rosario Evans Pena
- Department of Zoology, University of Oxford, Oxford, UK
- contributed equally as first authors
| | - Ben C Lambert
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Rhys Inward
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Erik Volz
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Christopher Ruis
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- 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
| | | | | | - Neo Wu
- Google, Mountain View, CA, USA
| | | | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USA
| | | | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Thomas P Peacock
- Department of Infectious Disease, Imperial College London, London, UK
- UK Health Security Agency, London, UK
| | | | | | | | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Isaac I Bogoch
- Divisions of Internal Medicine & Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, ON, Canada
| | - Kamran Khan
- BlueDot, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | | | | | - David M Aanensen
- Wellcome Sanger Institute, 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
| | - Wendy S Barclay
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Thomas Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, The Sir Martin Evans Building, Cardiff University, Cardiff, UK
- Quadram Institute, Norwich, UK
| | - Nicholas J Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Marc A Suchard
- Departments of Biostatistics, Biomathematics and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
- jointly supervised this work
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- jointly supervised this work
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK
- jointly supervised this work
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12
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McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Jackson B, Colquhoun R, O'Toole Á, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUG. Context-specific emergence and growth of the SARS-CoV-2 Delta variant. Res Sq 2021:rs.3.rs-1159614. [PMID: 34981043 PMCID: PMC8722606 DOI: 10.21203/rs.3.rs-1159614/v1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta’s invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.
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Affiliation(s)
- John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Sumali Bajaj
- Department of Zoology, University of Oxford, Oxford, UK
| | | | - Ben C Lambert
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Rhys Inward
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Samir Bhatt
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Erik Volz
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Christopher Ruis
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- 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
| | | | | | - Neo Wu
- Google, Mountain View, CA, USA
| | | | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USA
| | | | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Thomas P Peacock
- Department of Infectious Disease, Imperial College London, London, UK
- UK Health Security Agency, London, UK
| | | | | | | | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Isaac I Bogoch
- Divisions of Internal Medicine & Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, ON, Canada
| | - Kamran Khan
- BlueDot, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | | | | | - David M Aanensen
- Wellcome Sanger Institute, 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
| | - Wendy S Barclay
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Thomas Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, The Sir Martin Evans Building, Cardiff University, Cardiff, UK
- Quadram Institute, Norwich, UK
| | - Nicholas J Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Marc A Suchard
- Departments of Biostatistics, Biomathematics and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
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13
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Kraemer MUG, Hill V, Ruis C, Dellicour S, Bajaj S, McCrone JT, Baele G, Parag KV, Battle AL, Gutierrez B, Jackson B, Colquhoun R, O'Toole Á, Klein B, Vespignani A, Volz E, Faria NR, Aanensen DM, Loman NJ, du Plessis L, Cauchemez S, Rambaut A, Scarpino SV, Pybus OG. Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science 2021; 373:889-895. [PMID: 34301854 PMCID: PMC9269003 DOI: 10.1126/science.abj0113] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/12/2021] [Indexed: 12/24/2022]
Abstract
Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.
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Affiliation(s)
- Moritz U G Kraemer
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil.
- Department of Zoology, University of Oxford, Oxford, UK
| | - Verity Hill
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Christopher Ruis
- Department of Zoology, University of Oxford, Oxford, UK
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
| | - Simon Dellicour
- Network Science Institute, Northeastern University, Boston, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Sumali Bajaj
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - John T McCrone
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Guy Baele
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Kris V Parag
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Anya Lindström Battle
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Department of Plant Sciences, University of Oxford, Oxford, UK
| | - Bernardo Gutierrez
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Plant Sciences, University of Oxford, Oxford, UK
- Department of Zoology, University of Oxford, Oxford, UK
| | - Ben Jackson
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Áine O'Toole
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Brennan Klein
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
- Network Science Institute, Northeastern University, Boston, USA
| | - Alessandro Vespignani
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
- Network Science Institute, Northeastern University, Boston, USA
| | - Erik Volz
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Nuno R Faria
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
| | - David M Aanensen
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- 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
| | - Nicholas J Loman
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Louis du Plessis
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - Simon Cauchemez
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | - Andrew Rambaut
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Samuel V Scarpino
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium.
- Network Science Institute, Northeastern University, Boston, USA
- Vermont Complex Systems Center, University of Vermont, Burlington, USA
- Santa Fe Institute, Santa Fe, USA
| | - Oliver G Pybus
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil.
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
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14
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O’Toole Á, Scher E, Underwood A, Jackson B, Hill V, McCrone JT, Colquhoun R, Ruis C, Abu-Dahab K, Taylor B, Yeats C, du Plessis L, Maloney D, Medd N, Attwood SW, Aanensen DM, Holmes EC, Pybus OG, Rambaut A. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evol 2021; 7:veab064. [PMID: 34527285 PMCID: PMC8344591 DOI: 10.1093/ve/veab064] [Citation(s) in RCA: 489] [Impact Index Per Article: 163.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/09/2021] [Accepted: 07/05/2021] [Indexed: 12/20/2022] Open
Abstract
The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the 'real-time' generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic's transmission lineages.
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Affiliation(s)
- Áine O’Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Emily Scher
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Anthony Underwood
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Chris Ruis
- Department of Medicine, University of Cambridge, Cambridge CB2 0SP, UK
| | - Khalil Abu-Dahab
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Ben Taylor
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Corin Yeats
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - Daniel Maloney
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Nathan Medd
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Stephen W Attwood
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - David M Aanensen
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Edward C Holmes
- School of Life and Environmental Sciences and School of Medical Sciences, University of Sydney, Sydney, NSW 2006, Australia
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
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15
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Gutierrez B, Márquez S, Prado-Vivar B, Becerra-Wong M, Guadalupe JJ, da Silva Candido D, Fernandez-Cadena JC, Morey-Leon G, Armas-Gonzalez R, Andrade-Molina DM, Bruno A, de Mora D, Olmedo M, Portugal D, Gonzalez M, Orlando A, Drexler JF, Moreira-Soto A, Sander AL, Brünink S, Kühne A, Patiño L, Carrazco-Montalvo A, Mestanza O, Zurita J, Sevillano G, du Plessis L, McCrone JT, Coloma J, Trueba G, Barragán V, Rojas-Silva P, Grunauer M, Kraemer MU, Faria NR, Escalera-Zamudio M, Pybus OG, Cárdenas P. Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador. medRxiv 2021:2021.03.31.21254685. [PMID: 33851177 PMCID: PMC8043474 DOI: 10.1101/2021.03.31.21254685] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Characterisation of SARS-CoV-2 genetic diversity through space and time can reveal trends in virus importation and domestic circulation, and permit the exploration of questions regarding the early transmission dynamics. Here we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the COVID-19 pandemic. We generate and analyse 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylgeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions (NPIs), with differential degrees of persistence and national dissemination.
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Affiliation(s)
- Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK
- Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador
| | - Sully Márquez
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - Belén Prado-Vivar
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - Mónica Becerra-Wong
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - Juan José Guadalupe
- Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito, Quito, Ecuador
| | | | - Juan Carlos Fernandez-Cadena
- Omics Sciences Laboratory, Faculty of Medical Sciences, Universidad de Especialidades Espíritu Santo, Samborondón, Ecuador
| | - Gabriel Morey-Leon
- Faculty of Medical Sciences, Universidad de Guayaquil, Guayaquil, Ecuador
| | - Rubén Armas-Gonzalez
- Faculty of Sciences, Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador
| | - Derly Madeleiny Andrade-Molina
- Omics Sciences Laboratory, Faculty of Medical Sciences, Universidad de Especialidades Espíritu Santo, Samborondón, Ecuador
| | - Alfredo Bruno
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
- Universidad Agraria del Ecuador
| | - Domenica de Mora
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Maritza Olmedo
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Denisse Portugal
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Manuel Gonzalez
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Alberto Orlando
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Jan Felix Drexler
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Virology, Berlin, Germany
| | - Andres Moreira-Soto
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Virology, Berlin, Germany
| | - Anna-Lena Sander
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Virology, Berlin, Germany
| | - Sebastian Brünink
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Virology, Berlin, Germany
| | - Arne Kühne
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Virology, Berlin, Germany
| | - Leandro Patiño
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | | | - Orson Mestanza
- Instituto Nacional de Investigación en Salud Pública, Guayaquil, Ecuador
| | - Jeannete Zurita
- Facultad de Medicina, Pontificia Universidad Católica del Ecuador, Quito, Ecuador
- Unidad de Investigaciones en Biomedicina, Zurita & Zurita Laboratorios, Quito, Ecuador
| | - Gabriela Sevillano
- Unidad de Investigaciones en Biomedicina, Zurita & Zurita Laboratorios, Quito, Ecuador
| | | | - John T. McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Josefina Coloma
- School of Public Health, University of California, Berkeley, USA
| | - Gabriel Trueba
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - Verónica Barragán
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | | | - Michelle Grunauer
- Escuela de Medicina, Universidad San Francisco de Quito, Quito, Ecuador
| | | | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | | | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Paúl Cárdenas
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
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16
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Rambaut A, Holmes EC, O'Toole Á, Hill V, McCrone JT, Ruis C, du Plessis L, Pybus OG. Addendum: A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol 2021; 6:415. [PMID: 33514928 PMCID: PMC7845574 DOI: 10.1038/s41564-021-00872-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
An Addendum to this paper has been published: https://doi.org/10.1038/s41564-021-00872-5.
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Affiliation(s)
- Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
| | - Edward C Holmes
- Marie Bashir Institute for Infectious Diseases and Biosecurity, School of Life and Environmental Sciences and School of Medical Sciences, University of Sydney, Sydney, New South Wales, Australia.
| | - Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | | | | | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
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17
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du Plessis L, McCrone JT, Zarebski AE, Hill V, Ruis C, Gutierrez B, Raghwani J, Ashworth J, Colquhoun R, Connor TR, Faria NR, Jackson B, Loman NJ, O'Toole Á, Nicholls SM, Parag KV, Scher E, Vasylyeva TI, Volz EM, Watts A, Bogoch II, Khan K, Aanensen DM, Kraemer MUG, Rambaut A, Pybus OG. Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK. Science 2021; 371:708-712. [PMID: 33419936 PMCID: PMC7877493 DOI: 10.1126/science.abf2946] [Citation(s) in RCA: 234] [Impact Index Per Article: 78.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022]
Abstract
The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.
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Affiliation(s)
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | | | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Christopher Ruis
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK
- School of Biological and Environmental Sciences, Universidad San Francisco de Quito, Quito, Ecuador
| | | | - Jordan Ashworth
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Thomas R Connor
- School of Biosciences, Cardiff University, Cardiff, UK
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
| | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Nicholas J Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Samuel M Nicholls
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Kris V Parag
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Emily Scher
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | | | - Erik M Volz
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Alexander Watts
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
- BlueDot, Toronto, Canada
| | - Isaac I Bogoch
- Department of Medicine, University of Toronto, Toronto, Canada
- Divisions of General Internal Medicine and Infectious Diseases, University Health Network, Toronto, Canada
| | - Kamran Khan
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
- BlueDot, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
| | - 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
| | | | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
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18
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O'Toole Á, Scher E, Underwood A, Jackson B, Hill V, McCrone JT, Colquhoun R, Ruis C, Abu-Dahab K, Taylor B, Yeats C, du Plessis L, Maloney D, Medd N, Attwood SW, Aanensen DM, Holmes EC, Pybus OG, Rambaut A. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evol 2021; 7:veab064. [PMID: 34527285 DOI: 10.1093/ve/veab064/6315289] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/09/2021] [Accepted: 07/05/2021] [Indexed: 05/21/2023] Open
Abstract
The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the 'real-time' generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic's transmission lineages.
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Affiliation(s)
- Áine O'Toole
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Emily Scher
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Anthony Underwood
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Chris Ruis
- Department of Medicine, University of Cambridge, Cambridge CB2 0SP, UK
| | - Khalil Abu-Dahab
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Ben Taylor
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Corin Yeats
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - Daniel Maloney
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Nathan Medd
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
| | - Stephen W Attwood
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - David M Aanensen
- The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, Oxfordshire OX3 7LF, UK
| | - Edward C Holmes
- School of Life and Environmental Sciences and School of Medical Sciences, University of Sydney, Sydney, NSW 2006, Australia
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, Oxfordshire OX1 3SZ, UK
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH93FL, UK
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19
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Dellicour S, Lequime S, Vrancken B, Gill MS, Bastide P, Gangavarapu K, Matteson NL, Tan Y, du Plessis L, Fisher AA, Nelson MI, Gilbert M, Suchard MA, Andersen KG, Grubaugh ND, Pybus OG, Lemey P. Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework. Nat Commun 2020; 11:5620. [PMID: 33159066 PMCID: PMC7648063 DOI: 10.1038/s41467-020-19122-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 09/30/2020] [Indexed: 01/05/2023] Open
Abstract
Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.
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Affiliation(s)
- Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 Avenue FD Roosevelt, 1050, Bruxelles, Belgium.
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
| | - Sebastian Lequime
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Paul Bastide
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Nathaniel L Matteson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Yi Tan
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Infectious Diseases Group, J. Craig Venter Institute, Rockville, MD, USA
| | | | - Alexander A Fisher
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Martha I Nelson
- Fogarty International Center, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 Avenue FD Roosevelt, 1050, Bruxelles, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, 06510, USA
| | | | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
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20
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Candido DS, Claro IM, de Jesus JG, Souza WM, Moreira FRR, Dellicour S, Mellan TA, du Plessis L, Pereira RHM, Sales FCS, Manuli ER, Thézé J, Almeida L, Menezes MT, Voloch CM, Fumagalli MJ, Coletti TM, da Silva CAM, Ramundo MS, Amorim MR, Hoeltgebaum HH, Mishra S, Gill MS, Carvalho LM, Buss LF, Prete CA, Ashworth J, Nakaya HI, Peixoto PS, Brady OJ, Nicholls SM, Tanuri A, Rossi ÁD, Braga CKV, Gerber AL, de C Guimarães AP, Gaburo N, Alencar CS, Ferreira ACS, Lima CX, Levi JE, Granato C, Ferreira GM, Francisco RS, Granja F, Garcia MT, Moretti ML, Perroud MW, Castiñeiras TMPP, Lazari CS, Hill SC, de Souza Santos AA, Simeoni CL, Forato J, Sposito AC, Schreiber AZ, Santos MNN, de Sá CZ, Souza RP, Resende-Moreira LC, Teixeira MM, Hubner J, Leme PAF, Moreira RG, Nogueira ML, Ferguson NM, Costa SF, Proenca-Modena JL, Vasconcelos ATR, Bhatt S, Lemey P, Wu CH, Rambaut A, Loman NJ, Aguiar RS, Pybus OG, Sabino EC, Faria NR. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science 2020; 369:1255-1260. [PMID: 32703910 PMCID: PMC7402630 DOI: 10.1126/science.abd2161] [Citation(s) in RCA: 335] [Impact Index Per Article: 83.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 07/16/2020] [Indexed: 12/16/2022]
Abstract
Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.
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Affiliation(s)
- Darlan S Candido
- Department of Zoology, University of Oxford, Oxford, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Ingra M Claro
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Jaqueline G de Jesus
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - William M Souza
- Centro de Pesquisa em Virologia, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, Brazil
| | - Filipe R R Moreira
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Simon Dellicour
- Spatial Epidemiology Lab, Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Thomas A Mellan
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | | | | | - Flavia C S Sales
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Erika R Manuli
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Julien Thézé
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genès-Champanelle, France
| | - Luiz Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Mariane T Menezes
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Carolina M Voloch
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Marcilio J Fumagalli
- Centro de Pesquisa em Virologia, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, Brazil
| | - Thaís M Coletti
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Camila A M da Silva
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariana S Ramundo
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Mariene R Amorim
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Brazil
| | | | - Swapnil Mishra
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Luiz M Carvalho
- Escola de Matemática Aplicada (EMAp), Fundação Getúlio Vargas, Rio de Janeiro, Brazil
| | - Lewis F Buss
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Carlos A Prete
- Department of Electronic Systems Engineering, University of São Paulo, São Paulo, Brazil
| | | | - Helder I Nakaya
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Pedro S Peixoto
- Departamento de Matemática Aplicada, Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil
| | - Oliver J Brady
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Samuel M Nicholls
- Institute for Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Átila D Rossi
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Alexandra L Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Ana Paula de C Guimarães
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | | | - Cecila Salete Alencar
- LIM 03 Laboratório de Medicina Laboratorial, Hospital das Clínicas Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | - Cristiano X Lima
- Departamento de Cirurgia, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Simile Instituto de Imunologia Aplicada Ltda, Belo Horizonte, Brazil
| | | | | | - Giulia M Ferreira
- Laboratório de Virologia, Instituto de Ciências Biomédicas, Universidade Federal de Uberlândia, Uberlândia, Brazil
| | - Ronaldo S Francisco
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Fabiana Granja
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Brazil
- Centro de Estudos da Biodiversidade, Universidade Federal de Roraima, Boa Vista, Brazil
| | - Marcia T Garcia
- Divisão de Doenças Infecciosas, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brazil
| | - Maria Luiza Moretti
- Divisão de Doenças Infecciosas, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brazil
| | - Mauricio W Perroud
- Hospital Estadual Sumaré, Universidade Estadual de Campinas, Campinas, Brazil
| | - Terezinha M P P Castiñeiras
- Departamento de Doenças Infecciosas e Parasitárias, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Carolina S Lazari
- Divisão de Laboratório Central do Hospital das Clínicas, da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Sarah C Hill
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | | | - Camila L Simeoni
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Brazil
| | - Julia Forato
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Brazil
| | - Andrei C Sposito
- Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brazil
| | - Angelica Z Schreiber
- Departamento de Patologia Clínica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brazil
| | - Magnun N N Santos
- Departamento de Patologia Clínica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, Brazil
| | - Camila Zolini de Sá
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Renan P Souza
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Luciana C Resende-Moreira
- Departamento de Botânica, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Mauro M Teixeira
- Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Josy Hubner
- Departamento de Biologia Celular, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Patricia A F Leme
- Centro de Saúde da Comunidade, Universidade Estadual de Campinas, Campinas, Brazil
| | - Rennan G Moreira
- Centro de Laboratórios Multiusuários, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Maurício L Nogueira
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto, São Paulo, Brazil
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Silvia F Costa
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - José Luiz Proenca-Modena
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, Brazil
| | - Ana Tereza R Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Samir Bhatt
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Nick J Loman
- Institute for Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Renato S Aguiar
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Ester C Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Nuno Rodrigues Faria
- Department of Zoology, University of Oxford, Oxford, UK.
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
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21
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Lu J, Peng J, Xiong Q, Liu Z, Lin H, Tan X, Kang M, Yuan R, Zeng L, Zhou P, Liang C, Yi L, du Plessis L, Song T, Ma W, Sun J, Pybus OG, Ke C. Clinical, immunological and virological characterization of COVID-19 patients that test re-positive for SARS-CoV-2 by RT-PCR. EBioMedicine 2020; 59:102960. [PMID: 32853988 PMCID: PMC7444471 DOI: 10.1016/j.ebiom.2020.102960] [Citation(s) in RCA: 123] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 07/31/2020] [Accepted: 07/31/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Some COVID-19 cases test positive again for SARS-CoV-2 RNA following negative test results and discharge, raising questions about the meaning of virus detection. Better characterization of re-positive cases is urgently needed. METHODS Clinical data were obtained through Guangdong's COVID-19 surveillance network. Neutralization antibody titre was determined using microneutralization assays. Potential infectivity of clinical samples was evaluated by cell inoculation. SARS-CoV-2 RNA was detected using three different RT-PCR kits and multiplex PCR with nanopore sequencing. FINDINGS Among 619 discharged COVID-19 cases, 87 re-tested as SARS-CoV-2 positive in circumstances of social isolation. All re-positive cases had mild or moderate symptoms at initial diagnosis and were younger on average (median, 28). Re-positive cases (n = 59) exhibited similar neutralization antibodies (NAbs) titre distributions to other COVID-19 cases (n = 218) tested here. No infectious strain could be obtained by culture and no full-length viral genomes could be sequenced from re-positive cases. INTERPRETATION Re-positive SARS-CoV-2 cases do not appear to be caused by active reinfection and were identified in ~14% of discharged cases. A robust NAb response and potential virus genome degradation were detected in almost all re-positive cases, suggesting a substantially lower transmission risk, especially through respiratory routes.
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Affiliation(s)
- Jing Lu
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China; School of Public Health, Southern Medical University, Guangzhou, China
| | - Jinju Peng
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China; School of Public Health, Southern Medical University, Guangzhou, China
| | - Qianling Xiong
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China; School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhe Liu
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Huifang Lin
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xiaohua Tan
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Runyu Yuan
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Lilian Zeng
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Pingping Zhou
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Chumin Liang
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Lina Yi
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Wenjun Ma
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China
| | - Jiufeng Sun
- Guangdong Provincial Institution of Public Health, Guangdong Provincial Center for Disease Control and Prevention, 160 Qunxian Rd, Dashi Town, Panyu District, Guangdong Province, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Changwen Ke
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
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22
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Majander K, Pfrengle S, Kocher A, Neukamm J, du Plessis L, Pla-Díaz M, Arora N, Akgül G, Salo K, Schats R, Inskip S, Oinonen M, Valk H, Malve M, Kriiska A, Onkamo P, González-Candelas F, Kühnert D, Krause J, Schuenemann VJ. Ancient Bacterial Genomes Reveal a High Diversity of Treponema pallidum Strains in Early Modern Europe. Curr Biol 2020; 30:3788-3803.e10. [PMID: 32795443 DOI: 10.1016/j.cub.2020.07.058] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 04/24/2020] [Accepted: 07/16/2020] [Indexed: 12/30/2022]
Abstract
Syphilis is a globally re-emerging disease, which has marked European history with a devastating epidemic at the end of the 15th century. Together with non-venereal treponemal diseases, like bejel and yaws, which are found today in subtropical and tropical regions, it currently poses a substantial health threat worldwide. The origins and spread of treponemal diseases remain unresolved, including syphilis' potential introduction into Europe from the Americas. Here, we present the first genetic data from archaeological human remains reflecting a high diversity of Treponema pallidum in early modern Europe. Our study demonstrates that a variety of strains related to both venereal syphilis and yaws-causing T. pallidum subspecies were already present in Northern Europe in the early modern period. We also discovered a previously unknown T. pallidum lineage recovered as a sister group to yaws- and bejel-causing lineages. These findings imply a more complex pattern of geographical distribution and etiology of early treponemal epidemics than previously understood.
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Affiliation(s)
- Kerttu Majander
- Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; Institute for Archaeological Sciences, University of Tübingen, Rümelinstrasse 19-23, 72070 Tübingen, Germany; Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Kahlaische Strasse 10, 07745 Jena, Germany; Department of Biosciences, University of Helsinki, Viikinkaari 9, 00014 Helsinki, Finland.
| | - Saskia Pfrengle
- Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; Institute for Archaeological Sciences, University of Tübingen, Rümelinstrasse 19-23, 72070 Tübingen, Germany
| | - Arthur Kocher
- Transmission, Infection, Diversification and Evolution Group, Max Planck Institute for the Science of Human History, Kahlaische Strasse 10, 07745 Jena, Germany
| | - Judith Neukamm
- Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; Institute for Archaeological Sciences, University of Tübingen, Rümelinstrasse 19-23, 72070 Tübingen, Germany; Institute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, 72076 Tübingen, Germany
| | | | - Marta Pla-Díaz
- Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Natasha Arora
- Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057 Zurich, Switzerland
| | - Gülfirde Akgül
- Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
| | - Kati Salo
- Department of Biosciences, University of Helsinki, Viikinkaari 9, 00014 Helsinki, Finland; Archaeology, Faculty of Arts, University of Helsinki, Unioninkatu 38F, 00014 Helsinki, Finland
| | - Rachel Schats
- Laboratory for Human Osteoarchaeology, Faculty of Archaeology, Leiden University, Einsteinweg 2, 2333CC Leiden, the Netherlands
| | - Sarah Inskip
- McDonald Institute for Archaeological Research, University of Cambridge, Downing Street, Cambridge CB2 3ER, UK
| | - Markku Oinonen
- Laboratory of Chronology, Finnish Museum of Natural History, University of Helsinki, Gustaf Hällströmin katu 2, 00560 Helsinki, Finland
| | - Heiki Valk
- Institute of History and Archaeology, University of Tartu, Jakobi 2, 51005 Tartu, Tartumaa, Estonia
| | - Martin Malve
- Institute of History and Archaeology, University of Tartu, Jakobi 2, 51005 Tartu, Tartumaa, Estonia
| | - Aivar Kriiska
- Institute of History and Archaeology, University of Tartu, Jakobi 2, 51005 Tartu, Tartumaa, Estonia
| | - Päivi Onkamo
- Department of Biosciences, University of Helsinki, Viikinkaari 9, 00014 Helsinki, Finland; Department of Biology, University of Turku, Vesilinnantie 5, 20500 Turku, Finland
| | - Fernando González-Candelas
- Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Denise Kühnert
- Transmission, Infection, Diversification and Evolution Group, Max Planck Institute for the Science of Human History, Kahlaische Strasse 10, 07745 Jena, Germany
| | - Johannes Krause
- Institute for Archaeological Sciences, University of Tübingen, Rümelinstrasse 19-23, 72070 Tübingen, Germany; Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Kahlaische Strasse 10, 07745 Jena, Germany; Senckenberg Centre for Human Evolution and Palaeoenvironment (S-HEP), University of Tübingen, Tübingen, Germany.
| | - Verena J Schuenemann
- Institute of Evolutionary Medicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; Institute for Archaeological Sciences, University of Tübingen, Rümelinstrasse 19-23, 72070 Tübingen, Germany; Senckenberg Centre for Human Evolution and Palaeoenvironment (S-HEP), University of Tübingen, Tübingen, Germany.
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23
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Abstract
Estimating past population dynamics from molecular sequences that have been sampled longitudinally through time is an important problem in infectious disease epidemiology, molecular ecology, and macroevolution. Popular solutions, such as the skyline and skygrid methods, infer past effective population sizes from the coalescent event times of phylogenies reconstructed from sampled sequences but assume that sequence sampling times are uninformative about population size changes. Recent work has started to question this assumption by exploring how sampling time information can aid coalescent inference. Here, we develop, investigate, and implement a new skyline method, termed the epoch sampling skyline plot (ESP), to jointly estimate the dynamics of population size and sampling rate through time. The ESP is inspired by real-world data collection practices and comprises a flexible model in which the sequence sampling rate is proportional to the population size within an epoch but can change discontinuously between epochs. We show that the ESP is accurate under several realistic sampling protocols and we prove analytically that it can at least double the best precision achievable by standard approaches. We generalize the ESP to incorporate phylogenetic uncertainty in a new Bayesian package (BESP) in BEAST2. We re-examine two well-studied empirical data sets from virus epidemiology and molecular evolution and find that the BESP improves upon previous coalescent estimators and generates new, biologically useful insights into the sampling protocols underpinning these data sets. Sequence sampling times provide a rich source of information for coalescent inference that will become increasingly important as sequence collection intensifies and becomes more formalized.
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Affiliation(s)
- Kris V Parag
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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24
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Hill SC, de Souza R, Thézé J, Claro I, Aguiar RS, Abade L, Santos FCP, Cunha MS, Nogueira JS, Salles FCS, Rocco IM, Maeda AY, Vasami FGS, du Plessis L, Silveira PP, de Jesus JG, Quick J, Fernandes NCCA, Guerra JM, Réssio RA, Giovanetti M, Alcantara LCJ, Cirqueira CS, Díaz-Delgado J, Macedo FLL, Timenetsky MDCST, de Paula R, Spinola R, Telles de Deus J, Mucci LF, Tubaki RM, de Menezes RMT, Ramos PL, de Abreu AL, Cruz LN, Loman N, Dellicour S, Pybus OG, Sabino EC, Faria NR. Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 - 2018. PLoS Pathog 2020; 16:e1008699. [PMID: 32764827 PMCID: PMC7437926 DOI: 10.1371/journal.ppat.1008699] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 08/19/2020] [Accepted: 06/10/2020] [Indexed: 12/17/2022] Open
Abstract
São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species.
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Affiliation(s)
- Sarah C. Hill
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead, United Kingdom
| | | | - Julien Thézé
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genès-Champanelle, France
| | - Ingra Claro
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Renato S. Aguiar
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Rio de Janeiro, Brazil
| | - Leandro Abade
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | | | | | | | - Flavia C. S. Salles
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | | | | | | | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Paola P. Silveira
- Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Rio de Janeiro, Brazil
| | - Jaqueline G. de Jesus
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Joshua Quick
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
| | | | | | | | - Marta Giovanetti
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Luiz C. J. Alcantara
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | | | | | | | | | - Regiane de Paula
- Centro de Vigilância Epidemiológica "Prof. Alexandre Vranjac", São Paulo, Brazil
| | - Roberta Spinola
- Centro de Vigilância Epidemiológica "Prof. Alexandre Vranjac", São Paulo, Brazil
| | | | - Luís F. Mucci
- Superintendência do Controle de Endemias, São Paulo, Brazil
| | | | | | | | - Andre L. de Abreu
- Secretaria de Vigilância em Saúde, Ministério da Saúde (SVS/MS), Brasília-DF, Brazil
| | | | - Nick Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead, United Kingdom
| | - Ester C. Sabino
- Instituto de Medicina Tropical, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina e, Universidade de São Paulo, São Paulo, Brazil
| | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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25
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Deng X, Gu W, Federman S, du Plessis L, Pybus OG, Faria NR, Wang C, Yu G, Bushnell B, Pan CY, Guevara H, Sotomayor-Gonzalez A, Zorn K, Gopez A, Servellita V, Hsu E, Miller S, Bedford T, Greninger AL, Roychoudhury P, Starita LM, Famulare M, Chu HY, Shendure J, Jerome KR, Anderson C, Gangavarapu K, Zeller M, Spencer E, Andersen KG, MacCannell D, Paden CR, Li Y, Zhang J, Tong S, Armstrong G, Morrow S, Willis M, Matyas BT, Mase S, Kasirye O, Park M, Masinde G, Chan C, Yu AT, Chai SJ, Villarino E, Bonin B, Wadford DA, Chiu CY. Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California. Science 2020; 369:582-587. [PMID: 32513865 PMCID: PMC7286545 DOI: 10.1126/science.abb9263] [Citation(s) in RCA: 196] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 06/03/2020] [Indexed: 12/30/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally, with >365,000 cases in California as of 17 July 2020. We investigated the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning nine counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least seven different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington state, with lack of a predominant lineage and limited transmission among communities. Lineages associated with outbreak clusters in two counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain the spread of SARS-CoV-2 in California and other states.
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Affiliation(s)
- Xianding Deng
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Wei Gu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Scot Federman
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | | | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK
| | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, UK
| | - Candace Wang
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Guixia Yu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Brian Bushnell
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Chao-Yang Pan
- California Department of Public Health, Richmond, CA, USA
| | - Hugo Guevara
- California Department of Public Health, Richmond, CA, USA
| | - Alicia Sotomayor-Gonzalez
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Kelsey Zorn
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
| | - Allan Gopez
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Venice Servellita
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Elaine Hsu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Steve Miller
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Trevor Bedford
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Alexander L Greninger
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Pavitra Roychoudhury
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Helen Y Chu
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Keith R Jerome
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Catie Anderson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emily Spencer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | | | - Clinton R Paden
- U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Yan Li
- U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jing Zhang
- U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Suxiang Tong
- U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Scott Morrow
- San Mateo County Department of Public Health, San Mateo, CA, USA
| | - Matthew Willis
- Marin County Division of Public Health, San Rafael, CA, USA
| | - Bela T Matyas
- Solano County Department of Public Health, Fairfield, CA, USA
| | - Sundari Mase
- Sonoma County Department of Public Health, Santa Rosa, CA, USA
| | - Olivia Kasirye
- Sacramento County Division of Public Health, Sacramento, CA, USA
| | - Maggie Park
- San Joaquin County Department of Public Health, Stockton, CA, USA
| | - Godfred Masinde
- San Francisco County Department of Public Health, San Francisco, CA, USA
| | - Curtis Chan
- San Francisco County Department of Public Health, San Francisco, CA, USA
| | - Alexander T Yu
- California Department of Public Health, Richmond, CA, USA
| | - Shua J Chai
- California Department of Public Health, Richmond, CA, USA
- U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Elsa Villarino
- County of Santa Clara, Public Health Department, Santa Clara, CA, USA
| | - Brandon Bonin
- County of Santa Clara, Public Health Department, Santa Clara, CA, USA
| | | | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA.
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, CA, USA
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26
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Lu J, du Plessis L, Liu Z, Hill V, Kang M, Lin H, Sun J, François S, Kraemer MUG, Faria NR, McCrone JT, Peng J, Xiong Q, Yuan R, Zeng L, Zhou P, Liang C, Yi L, Liu J, Xiao J, Hu J, Liu T, Ma W, Li W, Su J, Zheng H, Peng B, Fang S, Su W, Li K, Sun R, Bai R, Tang X, Liang M, Quick J, Song T, Rambaut A, Loman N, Raghwani J, Pybus OG, Ke C. Genomic Epidemiology of SARS-CoV-2 in Guangdong Province, China. Cell 2020; 181:997-1003.e9. [PMID: 32359424 PMCID: PMC7192124 DOI: 10.1016/j.cell.2020.04.023] [Citation(s) in RCA: 184] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 04/09/2020] [Accepted: 04/14/2020] [Indexed: 01/08/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2 infection and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, China's most populous province, during early 2020 resulted in 1,388 reported RNA-positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China, we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain because of low virus genetic variation early in the pandemic. Our results illustrate how the timing, size, and duration of putative local transmission chains were constrained by national travel restrictions and by the province's large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required, because the number of cases imported from other countries has increased.
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Affiliation(s)
- Jing Lu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | | | - Zhe Liu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Verity Hill
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH8 9YL, UK
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Huifang Lin
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jiufeng Sun
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Sarah François
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
| | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
| | - John T McCrone
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH8 9YL, UK
| | - Jinju Peng
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Qianling Xiong
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Runyu Yuan
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Lilian Zeng
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Pingping Zhou
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Chumin Liang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Lina Yi
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jun Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianxiong Hu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Wenjun Ma
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Wei Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Juan Su
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Huanying Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Bo Peng
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Shisong Fang
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
| | - Ruilin Sun
- Guangdong Provincial Second People's Hospital, Guangzhou 510320, China
| | - Ru Bai
- Guangdong Provincial Second People's Hospital, Guangzhou 510320, China
| | - Xi Tang
- Foshan First People's Hospital, Foshan 528000, China
| | - Minfeng Liang
- Foshan First People's Hospital, Foshan 528000, China
| | - Josh Quick
- Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH8 9YL, UK
| | - Nick Loman
- Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK
| | - Jayna Raghwani
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK.
| | - Changwen Ke
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
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27
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Kraemer MUG, Yang CH, Gutierrez B, Wu CH, Klein B, Pigott DM, du Plessis L, Faria NR, Li R, Hanage WP, Brownstein JS, Layan M, Vespignani A, Tian H, Dye C, Pybus OG, Scarpino SV. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 2020. [PMID: 32213647 DOI: 10.1126/science:abb4218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
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Affiliation(s)
- Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Chia-Hung Yang
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK
- School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | - Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - David M Pigott
- Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA
| | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - Ruoran Li
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - John S Brownstein
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Sorbonne Université, Paris, France
| | - Alessandro Vespignani
- Network Science Institute, Northeastern University, Boston, MA, USA
- ISI Foundation, Turin, Italy
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | | | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Samuel V Scarpino
- Network Science Institute, Northeastern University, Boston, MA, USA.
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28
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Kraemer MUG, Yang CH, Gutierrez B, Wu CH, Klein B, Pigott DM, du Plessis L, Faria NR, Li R, Hanage WP, Brownstein JS, Layan M, Vespignani A, Tian H, Dye C, Pybus OG, Scarpino SV. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 2020; 368:493-497. [PMID: 32213647 PMCID: PMC7146642 DOI: 10.1126/science.abb4218] [Citation(s) in RCA: 1381] [Impact Index Per Article: 345.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 03/23/2020] [Indexed: 12/14/2022]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
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Affiliation(s)
- Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Chia-Hung Yang
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK
- School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | - Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - David M Pigott
- Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA
| | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - Ruoran Li
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - John S Brownstein
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Sorbonne Université, Paris, France
| | - Alessandro Vespignani
- Network Science Institute, Northeastern University, Boston, MA, USA
- ISI Foundation, Turin, Italy
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | | | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Samuel V Scarpino
- Network Science Institute, Northeastern University, Boston, MA, USA.
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29
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Kraemer MUG, Yang CH, Gutierrez B, Wu CH, Klein B, Pigott DM, du Plessis L, Faria NR, Li R, Hanage WP, Brownstein JS, Layan M, Vespignani A, Tian H, Dye C, Pybus OG, Scarpino SV. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 2020; 368:493-497. [PMID: 32213647 DOI: 10.5281/zenodo.3714914] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 03/23/2020] [Indexed: 05/21/2023]
Abstract
The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
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Affiliation(s)
- Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Chia-Hung Yang
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, Oxford, UK
- School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, UK
| | - Brennan Klein
- Network Science Institute, Northeastern University, Boston, MA, USA
| | - David M Pigott
- Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, WA, USA
| | | | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - Ruoran Li
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - John S Brownstein
- Harvard Medical School, Harvard University, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Sorbonne Université, Paris, France
| | - Alessandro Vespignani
- Network Science Institute, Northeastern University, Boston, MA, USA
- ISI Foundation, Turin, Italy
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | | | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, The Royal Veterinary College, London, UK
| | - Samuel V Scarpino
- Network Science Institute, Northeastern University, Boston, MA, USA.
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30
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Deng X, Gu W, Federman S, du Plessis L, Pybus OG, Faria N, Wang C, Yu G, Pan CY, Guevara H, Sotomayor-Gonzalez A, Zorn K, Gopez A, Servellita V, Hsu E, Miller S, Bedford T, Greninger AL, Roychoudhury P, Starita LM, Famulare M, Chu HY, Shendure J, Jerome KR, Anderson C, Gangavarapu K, Zeller M, Spencer E, Andersen KG, MacCannell D, Paden CR, Li Y, Zhang J, Tong S, Armstrong G, Morrow S, Willis M, Matyas BT, Mase S, Kasirye O, Park M, Chan C, Yu AT, Chai SJ, Villarino E, Bonin B, Wadford DA, Chiu CY. A Genomic Survey of SARS-CoV-2 Reveals Multiple Introductions into Northern California without a Predominant Lineage. medRxiv 2020. [PMID: 32511579 PMCID: PMC7276006 DOI: 10.1101/2020.03.27.20044925] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, resulting in >300,000 reported cases worldwide as of March 21st, 2020. Here we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2 in Northern California using samples from returning travelers, cruise ship passengers, and cases of community transmission with unclear infection sources. Virus genomes were sampled from 29 patients diagnosed with COVID-19 infection from Feb 3rd through Mar 15th. Phylogenetic analyses revealed at least 8 different SARS-CoV-2 lineages, suggesting multiple independent introductions of the virus into the state. Virus genomes from passengers on two consecutive excursions of the Grand Princess cruise ship clustered with those from an established epidemic in Washington State, including the WA1 genome representing the first reported case in the United States on January 19th. We also detected evidence for presumptive transmission of SARS-CoV-2 lineages from one community to another. These findings suggest that cryptic transmission of SARS-CoV-2 in Northern California to date is characterized by multiple transmission chains that originate via distinct introductions from international and interstate travel, rather than widespread community transmission of a single predominant lineage. Rapid testing and contact tracing, social distancing, and travel restrictions are measures that will help to slow SARS-CoV-2 spread in California and other regions of the USA.
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Affiliation(s)
- Xianding Deng
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | - Wei Gu
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | - Scot Federman
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | | | | | - Nuno Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - Candace Wang
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | - Guixia Yu
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | - Chao-Yang Pan
- California Department of Public Health, Richmond, California, USA
| | - Hugo Guevara
- California Department of Public Health, Richmond, California, USA
| | - Alicia Sotomayor-Gonzalez
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA
| | - Kelsey Zorn
- Department of Biochemistry and Biophysics, San Francisco, California, USA
| | - Allan Gopez
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
| | - Venice Servellita
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
| | - Elaine Hsu
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
| | - Steve Miller
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
| | - Trevor Bedford
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Alexander L Greninger
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Pavitra Roychoudhury
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Helen Y Chu
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA.,Department of Laboratory Medicine, University of Washington, Seattle, WA, USA.,Howards Hughes Medical Institute, Seattle, WA, USA
| | - Keith R Jerome
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.,Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
| | - Catie Anderson
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Karthik Gangavarapu
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Mark Zeller
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Emily Spencer
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Kristian G Andersen
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Duncan MacCannell
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Clinton R Paden
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Yan Li
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jing Zhang
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Suxiang Tong
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Gregory Armstrong
- United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Scott Morrow
- San Mateo County Department of Public Health, San Mateo, California, USA
| | - Matthew Willis
- Marin County Division of Public Health, San Rafael, California, USA
| | - Bela T Matyas
- Solano County Department of Public Health, Fairfield, California, USA
| | - Sundari Mase
- Sonoma County Department of Public Health, Santa Rosa, California, USA
| | - Olivia Kasirye
- Sacramento County Division of Public Health, Sacramento, California, USA
| | - Maggie Park
- San Joaquin County Department of Public Health, Stockton, California, USA
| | - Curtis Chan
- San Francisco County Department of Public Health, San Francisco, California, USA
| | - Alexander T Yu
- California Department of Public Health, Richmond, California, USA
| | - Shua J Chai
- California Department of Public Health, Richmond, California, USA.,United States Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Elsa Villarino
- Santa Clara County Department of Public Health, Santa Clara, California, USA
| | - Brandon Bonin
- Santa Clara County Department of Public Health, Santa Clara, California, USA
| | - Debra A Wadford
- California Department of Public Health, Richmond, California, USA
| | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, California, USA.,UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, California, USA.,Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, California, USA
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31
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Kraemer MU, Yang CH, Gutierrez B, Wu CH, Klein B, Pigott DM, du Plessis L, Faria NR, Li R, Hanage WP, Brownstein JS, Layan M, Vespignani A, Tian H, Dye C, Cauchemez S, Pybus OG, Scarpino SV. The effect of human mobility and control measures on the COVID-19 epidemic in China. medRxiv 2020:2020.03.02.20026708. [PMID: 32511452 PMCID: PMC7239080 DOI: 10.1101/2020.03.02.20026708] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.
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Affiliation(s)
- Moritz U.G. Kraemer
- Department of Zoology, University of Oxford, United Kingdom
- Harvard Medical School, Harvard University, Boston, United States
- Boston Children’s Hospital, Boston, United States
| | - Chia-Hung Yang
- Network Science Institute, Northeastern University, Boston, United States
| | - Bernardo Gutierrez
- Department of Zoology, University of Oxford, United Kingdom
- School of Biological and Environmental Sciences, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Chieh-Hsi Wu
- Mathematical Sciences, University of Southampton, Southampton, United Kingdom
| | - Brennan Klein
- Network Science Institute, Northeastern University, Boston, United States
| | - David M. Pigott
- Institute for Health Metrics and Evaluation, Department of Health Metrics, University of Washington, Seattle, United States
| | | | | | - Nuno R. Faria
- Department of Zoology, University of Oxford, United Kingdom
| | - Ruoran Li
- Harvard T.H. Chan School of Public Health, Boston, United States
| | | | - John S. Brownstein
- Harvard Medical School, Harvard University, Boston, United States
- Boston Children’s Hospital, Boston, United States
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | | | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | | | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | | | - Samuel V. Scarpino
- Network Science Institute, Northeastern University, Boston, United States
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32
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Vasylyeva TI, du Plessis L, Pineda-Peña AC, Kühnert D, Lemey P, Vandamme AM, Gomes P, Camacho RJ, Pybus OG, Abecasis AB, Faria NR. Tracing the Impact of Public Health Interventions on HIV-1 Transmission in Portugal Using Molecular Epidemiology. J Infect Dis 2020; 220:233-243. [PMID: 30805610 PMCID: PMC6581889 DOI: 10.1093/infdis/jiz085] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/21/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Estimation of temporal changes in human immunodeficiency virus (HIV) transmission patterns can help to elucidate the impact of preventive strategies and public health policies. METHODS Portuguese HIV-1 subtype B and G pol genetic sequences were appended to global reference data sets to identify country-specific transmission clades. Bayesian birth-death models were used to estimate subtype-specific effective reproductive numbers (Re). Discrete trait analysis (DTA) was used to quantify mixing among transmission groups. RESULTS We identified 5 subtype B Portuguese clades (26-79 sequences) and a large monophyletic subtype G Portuguese clade (236 sequences). We estimated that major shifts in HIV-1 transmission occurred around 1999 (95% Bayesian credible interval [BCI], 1998-2000) and 2000 (95% BCI, 1998-2001) for subtypes B and G, respectively. For subtype B, Re dropped from 1.91 (95% BCI, 1.73-2.09) to 0.62 (95% BCI,.52-.72). For subtype G, Re decreased from 1.49 (95% BCI, 1.39-1.59) to 0.72 (95% BCI, .63-.8). The DTA suggests that people who inject drugs (PWID) and heterosexuals were the source of most (>80%) virus lineage transitions for subtypes G and B, respectively. CONCLUSIONS The estimated declines in Re coincide with the introduction of highly active antiretroviral therapy and the scale-up of harm reduction for PWID. Inferred transmission events across transmission groups emphasize the importance of prevention efforts for bridging populations.
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Affiliation(s)
- Tetyana I Vasylyeva
- Department of Zoology, University of Oxford, United Kingdom.,New College, University of Oxford, United Kingdom
| | | | - Andrea C Pineda-Peña
- Center for Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa.,Molecular Biology and Immunology Department, Fundación Instituto de Inmunología de Colombia.,Basic Sciences Department, Universidad del Rosario, Bogotá, Colombia
| | - Denise Kühnert
- Max Planck Institute for the Science of Human History, Jena, Germany
| | - Philippe Lemey
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Anne-Mieke Vandamme
- Center for Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa.,Laboratory for Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Perpétua Gomes
- Laboratory of Molecular Biology, LMCBM, SPC, Hospital de Egas Moniz-Centro Hospitalar de Lisboa Ocidental, Lisbon.,Center for Interdisciplinary Research Egas Moniz, CiiEM, Almada, Portugal
| | - Ricardo J Camacho
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Belgium
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, United Kingdom
| | - Ana B Abecasis
- Center for Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa
| | - Nuno R Faria
- Department of Zoology, University of Oxford, United Kingdom
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33
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Bouckaert R, Vaughan TG, Barido-Sottani J, Duchêne S, Fourment M, Gavryushkina A, Heled J, Jones G, Kühnert D, De Maio N, Matschiner M, Mendes FK, Müller NF, Ogilvie HA, du Plessis L, Popinga A, Rambaut A, Rasmussen D, Siveroni I, Suchard MA, Wu CH, Xie D, Zhang C, Stadler T, Drummond AJ. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol 2019; 15:e1006650. [PMID: 30958812 PMCID: PMC6472827 DOI: 10.1371/journal.pcbi.1006650] [Citation(s) in RCA: 1552] [Impact Index Per Article: 310.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 04/18/2019] [Accepted: 02/04/2019] [Indexed: 11/18/2022] Open
Abstract
Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.
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Affiliation(s)
- Remco Bouckaert
- Centre of Computational Evolution, University of Auckland, Auckland, New Zealand
- Max Planck Institute for the Science of Human History, Jena, Germany
| | - Timothy G. Vaughan
- ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Joëlle Barido-Sottani
- ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sebastián Duchêne
- Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Mathieu Fourment
- ithree institute, University of Technology Sydney, Sydney, Australia
| | | | | | - Graham Jones
- Department of Biological and Environmental Sciences, University of Gothenburg, Box 461, SE 405 30 Göteborg, Sweden
| | - Denise Kühnert
- Max Planck Institute for the Science of Human History, Jena, Germany
| | - Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridgeshire, UK
| | - Michael Matschiner
- Department of Environmental Sciences, University of Basel, 4051 Basel, Switzerland
| | - Fábio K. Mendes
- Centre of Computational Evolution, University of Auckland, Auckland, New Zealand
| | - Nicola F. Müller
- ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Huw A. Ogilvie
- Department of Computer Science, Rice University, Houston, TX 77005-1892, USA
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
| | - Alex Popinga
- Centre of Computational Evolution, University of Auckland, Auckland, New Zealand
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, EH9 3FL UK
| | - David Rasmussen
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA
| | - Igor Siveroni
- Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, W2 1PG, UK
| | - Marc A. Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, OX1 3LB, UK
| | - Dong Xie
- Centre of Computational Evolution, University of Auckland, Auckland, New Zealand
| | - Chi Zhang
- Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
| | - Tanja Stadler
- ETH Zürich, Department of Biosystems Science and Engineering, 4058 Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Alexei J. Drummond
- Centre of Computational Evolution, University of Auckland, Auckland, New Zealand
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34
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Vasylyeva TI, Liulchuk M, du Plessis L, Fearnhill E, Zadorozhna V, Babii N, Scherbinska A, Novitsky V, Pybus OG, Faria NR. The Changing Epidemiological Profile of HIV-1 Subtype B Epidemic in Ukraine. AIDS Res Hum Retroviruses 2019; 35:155-163. [PMID: 30430838 PMCID: PMC6360399 DOI: 10.1089/aid.2018.0167] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
While HIV-1 subtype B has caused a large epidemic in the Western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV-1 subtype B viruses circulating in Ukraine, characterized the transmission group structure, and estimated key evolutionary and epidemiological parameters. We analyzed 120 HIV-1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002 and 2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and date the most recent common ancestors of identified clades. A phylodynamic birth-death model was used to estimate the effective reproductive number (Re) of these clades. We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV-1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV-1 subtype A into Ukraine. Re was estimated to be 1.42 [95% highest posterior density (HPD) 1.26-1.56] for Clade 1 and 1.69 (95% HPD 1.49-1.84) for Clade 2. Evidently, the subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV-1 subtype B.
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Affiliation(s)
| | - Mariia Liulchuk
- L.V. Gromashevskij Institute of Epidemiology and Infectious Diseases of National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Louis du Plessis
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Esther Fearnhill
- Institute for Global Health, University College London, United Kingdom
| | - Victoriia Zadorozhna
- L.V. Gromashevskij Institute of Epidemiology and Infectious Diseases of National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Nataliia Babii
- L.V. Gromashevskij Institute of Epidemiology and Infectious Diseases of National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Alla Scherbinska
- L.V. Gromashevskij Institute of Epidemiology and Infectious Diseases of National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Vladimir Novitsky
- Department of Immunology and Infectious diseases, Harvard TH Chan School of Public Health, Boston, Massachusetts
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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35
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Thézé J, Li T, du Plessis L, Bouquet J, Kraemer MUG, Somasekar S, Yu G, de Cesare M, Balmaseda A, Kuan G, Harris E, Wu CH, Ansari MA, Bowden R, Faria NR, Yagi S, Messenger S, Brooks T, Stone M, Bloch EM, Busch M, Muñoz-Medina JE, González-Bonilla CR, Wolinsky S, López S, Arias CF, Bonsall D, Chiu CY, Pybus OG. Genomic Epidemiology Reconstructs the Introduction and Spread of Zika Virus in Central America and Mexico. Cell Host Microbe 2018; 23:855-864.e7. [PMID: 29805095 PMCID: PMC6006413 DOI: 10.1016/j.chom.2018.04.017] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 03/27/2018] [Accepted: 04/26/2018] [Indexed: 02/06/2023]
Abstract
The Zika virus (ZIKV) epidemic in the Americas established ZIKV as a major public health threat and uncovered its association with severe diseases, including microcephaly. However, genetic epidemiology in some at-risk regions, particularly Central America and Mexico, remains limited. We report 61 ZIKV genomes from this region, generated using metagenomic sequencing with ZIKV-specific enrichment, and combine phylogenetic, epidemiological, and environmental data to reconstruct ZIKV transmission. These analyses revealed multiple independent ZIKV introductions to Central America and Mexico. One introduction, likely from Brazil via Honduras, led to most infections and the undetected spread of ZIKV through the region from late 2014. Multiple lines of evidence indicate biannual peaks of ZIKV transmission in the region, likely driven by varying local environmental conditions for mosquito vectors and herd immunity. The spatial and temporal heterogeneity of ZIKV transmission in Central America and Mexico challenges arbovirus surveillance and disease control measures.
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Affiliation(s)
- Julien Thézé
- Department of Zoology, University of Oxford, Oxford, UK
| | - Tony Li
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | | | - Jerome Bouquet
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK; Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Harvard University, Boston, MA, USA
| | - Sneha Somasekar
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Guixia Yu
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Mariateresa de Cesare
- Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Angel Balmaseda
- Laboratory Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministerio de Salud, Managua, Nicaragua
| | - Guillermina Kuan
- Centro de Salud Sócrates Flores Vivas, Ministerio de Salud, Managua, Nicaragua
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
| | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, Oxford, UK
| | - M Azim Ansari
- Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rory Bowden
- Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, UK
| | - Shigeo Yagi
- California Department of Public Health, Richmond, CA, USA
| | | | - Trevor Brooks
- Blood Systems Research Institute, San Francisco, CA, USA
| | - Mars Stone
- Blood Systems Research Institute, San Francisco, CA, USA
| | - Evan M Bloch
- Department of Pathology, Johns Hopkins University School of Medcine, Baltimore, MD, USA
| | - Michael Busch
- Blood Systems Research Institute, San Francisco, CA, USA
| | - José E Muñoz-Medina
- División de Laboratorios de Vigilancia e Investigación Epidemiológica, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Cesar R González-Bonilla
- División de Laboratorios de Vigilancia e Investigación Epidemiológica, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Steven Wolinsky
- Division of Infectious Diseases, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Susana López
- Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico
| | - Carlos F Arias
- Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico
| | - David Bonsall
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA; UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA; Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, CA, USA.
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
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36
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Schmid-Hempel P, Aebi M, Barribeau S, Kitajima T, du Plessis L, Schmid-Hempel R, Zoller S. The genomes of Crithidia bombi and C. expoeki, common parasites of bumblebees. PLoS One 2018; 13:e0189738. [PMID: 29304093 PMCID: PMC5755769 DOI: 10.1371/journal.pone.0189738] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2017] [Accepted: 11/30/2017] [Indexed: 11/19/2022] Open
Abstract
Trypanosomatids (Trypanosomatidae, Kinetoplastida) are flagellated protozoa containing many parasites of medical or agricultural importance. Among those, Crithidia bombi and C. expoeki, are common parasites in bumble bees around the world, and phylogenetically close to Leishmania and Leptomonas. They have a simple and direct life cycle with one host, and partially castrate the founding queens greatly reducing their fitness. Here, we report the nuclear genome sequences of one clone of each species, extracted from a field-collected infection. Using a combination of Roche 454 FLX Titanium, Pacific Biosciences PacBio RS, and Illumina GA2 instruments for C. bombi, and PacBio for C. expoeki, we could produce high-quality and well resolved sequences. We find that these genomes are around 32 and 34 MB, with 7,808 and 7,851 annotated genes for C. bombi and C. expoeki, respectively-which is somewhat less than reported from other trypanosomatids, with few introns, and organized in polycistronic units. A large fraction of genes received plausible functional support in comparison primarily with Leishmania and Trypanosoma. Comparing the annotated genes of the two species with those of six other trypanosomatids (C. fasciculata, L. pyrrhocoris, L. seymouri, B. ayalai, L. major, and T. brucei) shows similar gene repertoires and many orthologs. Similar to other trypanosomatids, we also find signs of concerted evolution in genes putatively involved in the interaction with the host, a high degree of synteny between C. bombi and C. expoeki, and considerable overlap with several other species in the set. A total of 86 orthologous gene groups show signatures of positive selection in the branch leading to the two Crithidia under study, mostly of unknown function. As an example, we examined the initiating glycosylation pathway of surface components in C. bombi, finding it deviates from most other eukaryotes and also from other kinetoplastids, which may indicate rapid evolution in the extracellular matrix that is involved in interactions with the host. Bumble bees are important pollinators and Crithidia-infections are suspected to cause substantial selection pressure on their host populations. These newly sequenced genomes provide tools that should help better understand host-parasite interactions in these pollinator pathogens.
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Affiliation(s)
| | - Markus Aebi
- Institute of Microbiology, ETH Zurich, Zürich, Switzerland
| | - Seth Barribeau
- Institute of Integrative Biology (IBZ), ETH Zurich, Zürich, Switzerland
| | | | - Louis du Plessis
- Institute of Integrative Biology (IBZ), ETH Zurich, Zürich, Switzerland
| | | | - Stefan Zoller
- Genetic Diversity Centre (GDC), ETH Zurich, Zürich, Switzerland
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37
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Abstract
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.
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Affiliation(s)
- Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland Insitute for Integrative Biology, ETH Zürich, Zürich, Switzerland Swiss Institute of Bioinformatics, Switzerland
| | - Gabriel E Leventhal
- Insitute for Integrative Biology, ETH Zürich, Zürich, Switzerland Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA
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38
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du Plessis L, Stadler T. Getting to the root of epidemic spread with phylodynamic analysis of genomic data. Trends Microbiol 2016; 23:383-6. [PMID: 26139467 DOI: 10.1016/j.tim.2015.04.007] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 04/13/2015] [Accepted: 04/23/2015] [Indexed: 11/30/2022]
Abstract
When epidemiological and evolutionary dynamics occur on similar timescales, pathogen genomes sampled from infected hosts carry a signature of the dynamics of epidemic spread. Phylodynamic inference methods aim to extract this signature from genetic data. We discuss the contribution of phylodynamics toward understanding the 2014 West African Ebola virus epidemic.
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Affiliation(s)
- Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland; Swiss Institute of Bioinformatics (SIB), Switzerland.
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Switzerland
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Sadd BM, Barribeau SM, Bloch G, de Graaf DC, Dearden P, Elsik CG, Gadau J, Grimmelikhuijzen CJP, Hasselmann M, Lozier JD, Robertson HM, Smagghe G, Stolle E, Van Vaerenbergh M, Waterhouse RM, Bornberg-Bauer E, Klasberg S, Bennett AK, Câmara F, Guigó R, Hoff K, Mariotti M, Munoz-Torres M, Murphy T, Santesmasses D, Amdam GV, Beckers M, Beye M, Biewer M, Bitondi MMG, Blaxter ML, Bourke AFG, Brown MJF, Buechel SD, Cameron R, Cappelle K, Carolan JC, Christiaens O, Ciborowski KL, Clarke DF, Colgan TJ, Collins DH, Cridge AG, Dalmay T, Dreier S, du Plessis L, Duncan E, Erler S, Evans J, Falcon T, Flores K, Freitas FCP, Fuchikawa T, Gempe T, Hartfelder K, Hauser F, Helbing S, Humann FC, Irvine F, Jermiin LS, Johnson CE, Johnson RM, Jones AK, Kadowaki T, Kidner JH, Koch V, Köhler A, Kraus FB, Lattorff HMG, Leask M, Lockett GA, Mallon EB, Antonio DSM, Marxer M, Meeus I, Moritz RFA, Nair A, Näpflin K, Nissen I, Niu J, Nunes FMF, Oakeshott JG, Osborne A, Otte M, Pinheiro DG, Rossié N, Rueppell O, Santos CG, Schmid-Hempel R, Schmitt BD, Schulte C, Simões ZLP, Soares MPM, Swevers L, Winnebeck EC, Wolschin F, Yu N, Zdobnov EM, Aqrawi PK, Blankenburg KP, Coyle M, Francisco L, Hernandez AG, Holder M, Hudson ME, Jackson L, Jayaseelan J, Joshi V, Kovar C, Lee SL, Mata R, Mathew T, Newsham IF, Ngo R, Okwuonu G, Pham C, Pu LL, Saada N, Santibanez J, Simmons D, Thornton R, Venkat A, Walden KKO, Wu YQ, Debyser G, Devreese B, Asher C, Blommaert J, Chipman AD, Chittka L, Fouks B, Liu J, O'Neill MP, Sumner S, Puiu D, Qu J, Salzberg SL, Scherer SE, Muzny DM, Richards S, Robinson GE, Gibbs RA, Schmid-Hempel P, Worley KC. The genomes of two key bumblebee species with primitive eusocial organization. Genome Biol 2015; 16:76. [PMID: 25908251 PMCID: PMC4414376 DOI: 10.1186/s13059-015-0623-3] [Citation(s) in RCA: 241] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 03/10/2015] [Indexed: 12/25/2022] Open
Abstract
Background The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0623-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ben M Sadd
- School of Biological Sciences, Illinois State University, Normal, IL, 61790, USA. .,Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Seth M Barribeau
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland. .,Department of Biology, East Carolina University, Greenville, NC, 27858, USA.
| | - Guy Bloch
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Dirk C de Graaf
- Laboratory of Zoophysiology, Faculty of Sciences, Ghent University, Krijgslaan 281, S2, 9000, Ghent, Belgium.
| | - Peter Dearden
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Christine G Elsik
- Division of Animal Sciences, Division of Plant Sciences, and MU Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. .,Department of Biology, Georgetown University, Washington, DC, 20057, USA.
| | - Jürgen Gadau
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.
| | - Cornelis J P Grimmelikhuijzen
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Martin Hasselmann
- University of Hohenheim, Institute of Animal Science, Garbenstrasse 17, 70599, Stuttgart, Germany.
| | - Jeffrey D Lozier
- Department of Biological Sciences, University of Alabama, Tuscaloosa, AL, 35487, USA.
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Guy Smagghe
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Eckart Stolle
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Matthias Van Vaerenbergh
- Laboratory of Zoophysiology, Faculty of Sciences, Ghent University, Krijgslaan 281, S2, 9000, Ghent, Belgium.
| | - Robert M Waterhouse
- Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA, 02139, USA. .,The Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA, 02142, USA.
| | - Erich Bornberg-Bauer
- Westfalian Wilhelms University, Institute of Evolution and Biodiversity, Huefferstrasse 1, 48149, Muenster, Germany.
| | - Steffen Klasberg
- Westfalian Wilhelms University, Institute of Evolution and Biodiversity, Huefferstrasse 1, 48149, Muenster, Germany.
| | - Anna K Bennett
- Department of Biology, Georgetown University, Washington, DC, 20057, USA.
| | - Francisco Câmara
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Roderic Guigó
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Katharina Hoff
- Ernst Moritz Arndt University Greifswald, Institute for Mathematics and Computer Science, Walther-Rathenau-Str. 47, 17487, Greifswald, Germany.
| | - Marco Mariotti
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Monica Munoz-Torres
- Department of Biology, Georgetown University, Washington, DC, 20057, USA. .,Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | - Terence Murphy
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, USA.
| | - Didac Santesmasses
- Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Gro V Amdam
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA. .,Department of Chemistry, Biotechnology and Food Science, Norwegian University of Food Science, N-1432, Aas, Norway.
| | - Matthew Beckers
- School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Martin Beye
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Matthias Biewer
- University of Hohenheim, Institute of Animal Science, Garbenstrasse 17, 70599, Stuttgart, Germany. .,University of Cologne, Institute of Genetics, Cologne, Germany.
| | - Márcia M G Bitondi
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901, Ribeirão Preto, Brazil.
| | - Mark L Blaxter
- Institute of Evolutionary Biology and Edinburgh Genomics, The Ashworth Laboratories, The King's Buildings, University of Edinburgh, Edinburgh, EH9 3FL, UK.
| | - Andrew F G Bourke
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Mark J F Brown
- School of Biological Sciences, Royal Holloway University of London, London, UK.
| | - Severine D Buechel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Rossanah Cameron
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Kaat Cappelle
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - James C Carolan
- Maynooth University Department of Biology, Maynooth University, Co, Kildare, Ireland.
| | - Olivier Christiaens
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Kate L Ciborowski
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK.
| | | | - Thomas J Colgan
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland.
| | - David H Collins
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Andrew G Cridge
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Tamas Dalmay
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| | - Stephanie Dreier
- Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
| | - Louis du Plessis
- Theoretical Biology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,Computational Evolution, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
| | - Elizabeth Duncan
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Silvio Erler
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Jay Evans
- USDA-ARS Bee Research Laboratory, Maryland, USA.
| | - Tiago Falcon
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Kevin Flores
- Center for Research in Scientific Computation, North Carolina State University Raleigh, Raleigh, NC, USA.
| | - Flávia C P Freitas
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Taro Fuchikawa
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel. .,Laboratory of Insect Ecology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan.
| | - Tanja Gempe
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Klaus Hartfelder
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Frank Hauser
- Center for Functional and Comparative Insect Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Sophie Helbing
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Fernanda C Humann
- Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, 15991-502, Matão, Brazil.
| | - Frano Irvine
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | | | - Claire E Johnson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Reed M Johnson
- Department of Entomology, The Ohio State University, Wooster, OH, 44791, USA.
| | - Andrew K Jones
- Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK.
| | - Tatsuhiko Kadowaki
- Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
| | - Jonathan H Kidner
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Vasco Koch
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Arian Köhler
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - F Bernhard Kraus
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,Department of Laboratory Medicine, University Hospital Halle (Saale), Halle, Germany.
| | - H Michael G Lattorff
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Megan Leask
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | | | - Eamonn B Mallon
- Department of Biology, University of Leicester, Leicester, UK.
| | - David S Marco Antonio
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Monika Marxer
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Ivan Meeus
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Robin F A Moritz
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Ajay Nair
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Kathrin Näpflin
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Inga Nissen
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Jinzhi Niu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Francis M F Nunes
- Departamento de Genética e Evolução, Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, 13565-905, São Carlos, Brazil.
| | | | - Amy Osborne
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Marianne Otte
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany.
| | - Daniel G Pinheiro
- Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, 14884-900, Jaboticabal, Brazil.
| | - Nina Rossié
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Olav Rueppell
- Department of Biology, University of North Carolina at Greensboro, 321 McIver Street, Greensboro, NC, 27403, USA.
| | - Carolina G Santos
- Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Regula Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Björn D Schmitt
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Christina Schulte
- Institute of Evolutionary Genetics, Heinrich Heine University Duesseldorf, Universitaetsstrasse 1, 40225, Duesseldorf, Germany.
| | - Zilá L P Simões
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901, Ribeirão Preto, Brazil.
| | - Michelle P M Soares
- Departamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14040-900, Ribeirão Preto, Brazil.
| | - Luc Swevers
- Institute of Biosciences & Applications, National Center for Scientific Research Demokritos, Athens, Greece.
| | | | - Florian Wolschin
- School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA. .,Department of Chemistry, Biotechnology and Food Science, Norwegian University of Food Science, N-1432, Aas, Norway.
| | - Na Yu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Evgeny M Zdobnov
- Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211, Geneva, Switzerland. .,Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211, Geneva, Switzerland.
| | - Peshtewani K Aqrawi
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Kerstin P Blankenburg
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Marcus Coyle
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Liezl Francisco
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Alvaro G Hernandez
- Roy J. Carver Biotechnology Center, University of Illinois Urbana-Champaign, Urbana, IL, USA.
| | - Michael Holder
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Matthew E Hudson
- Department of Crop Sciences and Institute of Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - LaRonda Jackson
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Joy Jayaseelan
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Vandita Joshi
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Christie Kovar
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Sandra L Lee
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Robert Mata
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Tittu Mathew
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Irene F Newsham
- Molecular Genetic Technology Program, School of Health Professions, MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 2, Houston, TX, 77025, USA.
| | - Robin Ngo
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Geoffrey Okwuonu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Christopher Pham
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Ling-Ling Pu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Nehad Saada
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Jireh Santibanez
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - DeNard Simmons
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Rebecca Thornton
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Aarti Venkat
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
| | - Kimberly K O Walden
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Yuan-Qing Wu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Griet Debyser
- Laboratory of Protein Biochemistry and Biomolecular Engineering, Department of Biochemistry and Microbiology, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium.
| | - Bart Devreese
- Laboratory of Protein Biochemistry and Biomolecular Engineering, Department of Biochemistry and Microbiology, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium.
| | - Claire Asher
- Institute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
| | - Julie Blommaert
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Ariel D Chipman
- Department of Ecology, Evolution, and Behavior, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Lars Chittka
- Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| | - Bertrand Fouks
- Institute of Biology, Martin-Luther-University Halle-Wittenberg, Wittenberg, Germany. .,Department of Biology, University of North Carolina at Greensboro, 321 McIver Street, Greensboro, NC, 27403, USA.
| | - Jisheng Liu
- Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium. .,School of Life Sciences, Guangzhou University, Guangzhou, China.
| | - Meaghan P O'Neill
- Laboratory for Evolution and Development, Genetics Otago and the National Research Centre for Growth and Development, Department of Biochemistry, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
| | - Seirian Sumner
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK.
| | - Daniela Puiu
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA.
| | - Jiaxin Qu
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Steven L Salzberg
- Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA.
| | - Steven E Scherer
- School of Life Sciences, Guangzhou University, Guangzhou, China.
| | - Donna M Muzny
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Stephen Richards
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Gene E Robinson
- Carl R. Woese Institute for Genomic Biology, Department of Entomology, Neuroscience Program, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL, 61801, USA.
| | - Richard A Gibbs
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Paul Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, Eidgenössiche Technische Hochschule (ETH) Zürich, CH-8092, Zürich, Switzerland.
| | - Kim C Worley
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, MS BCM226, One Baylor Plaza, Houston, TX, 77030, USA.
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Barribeau SM, Sadd BM, du Plessis L, Brown MJF, Buechel SD, Cappelle K, Carolan JC, Christiaens O, Colgan TJ, Erler S, Evans J, Helbing S, Karaus E, Lattorff HMG, Marxer M, Meeus I, Näpflin K, Niu J, Schmid-Hempel R, Smagghe G, Waterhouse RM, Yu N, Zdobnov EM, Schmid-Hempel P. A depauperate immune repertoire precedes evolution of sociality in bees. Genome Biol 2015; 16:83. [PMID: 25908406 PMCID: PMC4408586 DOI: 10.1186/s13059-015-0628-y] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2014] [Accepted: 03/11/2015] [Indexed: 11/10/2022] Open
Abstract
Background Sociality has many rewards, but can also be dangerous, as high population density and low genetic diversity, common in social insects, is ideal for parasite transmission. Despite this risk, honeybees and other sequenced social insects have far fewer canonical immune genes relative to solitary insects. Social protection from infection, including behavioral responses, may explain this depauperate immune repertoire. Here, based on full genome sequences, we describe the immune repertoire of two ecologically and commercially important bumblebee species that diverged approximately 18 million years ago, the North American Bombus impatiens and European Bombus terrestris. Results We find that the immune systems of these bumblebees, two species of honeybee, and a solitary leafcutting bee, are strikingly similar. Transcriptional assays confirm the expression of many of these genes in an immunological context and more strongly in young queens than males, affirming Bateman’s principle of greater investment in female immunity. We find evidence of positive selection in genes encoding antiviral responses, components of the Toll and JAK/STAT pathways, and serine protease inhibitors in both social and solitary bees. Finally, we detect many genes across pathways that differ in selection between bumblebees and honeybees, or between the social and solitary clades. Conclusions The similarity in immune complement across a gradient of sociality suggests that a reduced immune repertoire predates the evolution of sociality in bees. The differences in selection on immune genes likely reflect divergent pressures exerted by parasites across social contexts. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0628-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Seth M Barribeau
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland. .,Department of Biology, East Carolina University, Greenville, NC, 27858, USA.
| | - Ben M Sadd
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland. .,School of Biological Sciences, Illinois State University, Normal, IL, 61790, USA.
| | - Louis du Plessis
- Theoretical Biology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland. .,Computational Evolution, Department of Biosystems Science and Evolution, ETH Zürich, 4058, Basel, Switzerland. .,Swiss Institute of Bioinformatics, 1211, Lausanne, Switzerland.
| | - Mark J F Brown
- School of Biological Sciences, Royal Holloway University of London, London, TW20 0EX, UK.
| | - Severine D Buechel
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
| | - Kaat Cappelle
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
| | - James C Carolan
- Maynooth University Department of Biology, Maynooth University, Maynooth, Kildare, Ireland.
| | - Olivier Christiaens
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
| | - Thomas J Colgan
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, 2, Ireland. .,School of Biological and Chemical Sciences, Queen Mary University of London, E1 41NS, London, UK.
| | - Silvio Erler
- Department of Apiculture and Sericulture, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Cluj-Napoca, 400372, Romania. .,Institut für Biologie, Molekulare Ökologie, Martin-Luther-Universität Halle-Wittenberg, Wittenberg, 06120, Germany.
| | - Jay Evans
- USDA-ARS Bee Research Laboratory, Beltsville, MD, 20705, USA.
| | - Sophie Helbing
- Institut für Biologie, Molekulare Ökologie, Martin-Luther-Universität Halle-Wittenberg, Wittenberg, 06120, Germany.
| | - Elke Karaus
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
| | - H Michael G Lattorff
- Institut für Biologie, Molekulare Ökologie, Martin-Luther-Universität Halle-Wittenberg, Wittenberg, 06120, Germany. .,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103, Leipzig, Germany. .,Institut für Biologie, Tierphysiologie, Martin-Luther-Universität Halle-Wittenberg, Wittenberg, 06099, Germany.
| | - Monika Marxer
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
| | - Ivan Meeus
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
| | - Kathrin Näpflin
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
| | - Jinzhi Niu
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium. .,College of Plant Protection, Southwest University, Chongqing, 400716, PR China.
| | - Regula Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
| | - Guy Smagghe
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium. .,College of Plant Protection, Southwest University, Chongqing, 400716, PR China.
| | - Robert M Waterhouse
- Swiss Institute of Bioinformatics, 1211, Lausanne, Switzerland. .,Department of Genetic Medicine and Development, University of Geneva Medical School, 1211, Geneva, Switzerland. .,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. .,The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
| | - Na Yu
- Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, 9000, Ghent, Belgium.
| | - Evgeny M Zdobnov
- Swiss Institute of Bioinformatics, 1211, Lausanne, Switzerland. .,Department of Genetic Medicine and Development, University of Geneva Medical School, 1211, Geneva, Switzerland.
| | - Paul Schmid-Hempel
- Experimental Ecology, Institute of Integrative Biology, ETH Zürich, CH-8092, Zürich, Switzerland.
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Abstract
BACKGROUND AND METHODOLOGY The current Ebola virus epidemic in West Africa has been spreading at least since December 2013. The first confirmed case of Ebola virus in Sierra Leone was identified on May 25. Based on viral genetic sequencing data from 72 individuals in Sierra Leone collected between the end of May and mid June, we utilize a range of phylodynamic methods to estimate the basic reproductive number (R0). We additionally estimate the expected lengths of the incubation and infectious periods of the virus. Finally, we use phylogenetic trees to examine the role played by population structure in the epidemic. RESULTS The median estimates of R0 based on sequencing data alone range between 1.65-2.18, with the most plausible model yielding a median R0 of 2.18 (95% HPD 1.24-3.55). Importantly, our results indicate that, at least until mid June, relief efforts in Sierra Leone were ineffective at lowering the effective reproductive number of the virus. We estimate the expected length of the infectious period to be 2.58 days (median; 95% HPD 1.24-6.98). The dataset appears to be too small in order to estimate the incubation period with high certainty (median expected incubation period 4.92 days; 95% HPD 2.11-23.20). While our estimates of the duration of infection tend to be smaller than previously reported, phylodynamic analyses support a previous estimate that 70% of cases were observed and included in the present dataset. The dataset is too small to show a particular population structure with high significance, however our preliminary analyses suggest that half the population is spreading the virus with an R0 well above 2, while the other half of the population is spreading with an R0 below 1. CONCLUSIONS Overall we show that sequencing data can robustly infer key epidemiological parameters. Such estimates inform public health officials and help to coordinate effective public health efforts. Thus having more sequencing data available for the ongoing Ebola virus epidemic and at the start of new outbreaks will foster a quick understanding of the dynamics of the pathogen.
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Affiliation(s)
- Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Denise Kühnert
- Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | - David A Rasmussen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
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Abstract
BACKGROUND AND METHODOLOGY The current Ebola virus epidemic in West Africa has been spreading at least since December 2013. The first confirmed case of Ebola virus in Sierra Leone was identified on May 25. Based on viral genetic sequencing data from 72 individuals in Sierra Leone collected between the end of May and mid June, we utilize a range of phylodynamic methods to estimate the basic reproductive number (R0). We additionally estimate the expected lengths of the incubation and infectious periods of the virus. Finally, we use phylogenetic trees to examine the role played by population structure in the epidemic. RESULTS The median estimates of R0 based on sequencing data alone range between 1.65-2.18, with the most plausible model yielding a median R0 of 2.18 (95% HPD 1.24-3.55). Importantly, our results indicate that, at least until mid June, relief efforts in Sierra Leone were ineffective at lowering the effective reproductive number of the virus. We estimate the expected length of the infectious period to be 2.58 days (median; 95% HPD 1.24-6.98). The dataset appears to be too small in order to estimate the incubation period with high certainty (median expected incubation period 4.92 days; 95% HPD 2.11-23.20). While our estimates of the duration of infection tend to be smaller than previously reported, phylodynamic analyses support a previous estimate that 70% of cases were observed and included in the present dataset. The dataset is too small to show a particular population structure with high significance, however our preliminary analyses suggest that half the population is spreading the virus with an R0 well above 2, while the other half of the population is spreading with an R0 below 1. CONCLUSIONS Overall we show that sequencing data can robustly infer key epidemiological parameters. Such estimates inform public health officials and help to coordinate effective public health efforts. Thus having more sequencing data available for the ongoing Ebola virus epidemic and at the start of new outbreaks will foster a quick understanding of the dynamics of the pathogen.
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Affiliation(s)
- Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Denise Kühnert
- Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | - David A Rasmussen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
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Abstract
With high-throughput technologies providing vast amounts of data, it has become more important to provide systematic, quality annotations. The Gene Ontology (GO) project is the largest resource for cataloguing gene function. Nonetheless, its use is not yet ubiquitous and is still fraught with pitfalls. In this review, we provide a short primer to the GO for bioinformaticians. We summarize important aspects of the structure of the ontology, describe sources and types of functional annotations, survey measures of GO annotation similarity, review typical uses of GO and discuss other important considerations pertaining to the use of GO in bioinformatics applications.
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Affiliation(s)
- Louis du Plessis
- ETH Zurich, Computer Science, Universitätstr. 6, 8092 Zurich, Switzerland
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