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Dellicour S, Bastide P, Rocu P, Fargette D, Hardy OJ, Suchard MA, Guindon S, Lemey P. How fast are viruses spreading in the wild? BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588821. [PMID: 38645268 PMCID: PMC11030353 DOI: 10.1101/2024.04.10.588821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genomic data collected from viral outbreaks can be exploited to reconstruct the dispersal history of viral lineages in a two-dimensional space using continuous phylogeographic inference. These spatially explicit reconstructions can subsequently be used to estimate dispersal metrics allowing to unveil the dispersal dynamics and evaluate the capacity to spread among hosts. Heterogeneous sampling intensity of genomic sequences can however impact the accuracy of dispersal insights gained through phylogeographic inference. In our study, we implement a simulation framework to evaluate the robustness of three dispersal metrics - a lineage dispersal velocity, a diffusion coefficient, and an isolation-by-distance signal metric - to the sampling effort. Our results reveal that both the diffusion coefficient and isolation-by-distance signal metrics appear to be robust to the number of samples considered for the phylogeographic reconstruction. We then use these two dispersal metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations. Our comparative analysis reveals a broad range of isolation-by-distance patterns and diffusion coefficients mostly reflecting the dispersal capacity of the main infected host species but also, in some cases, the likely signature of rapid and/or long-distance dispersal events driven by human-mediated movements through animal trade. Overall, our study provides key recommendations for the lineage dispersal metrics to consider in future studies and illustrates their application to compare the spread of viruses in various settings.
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Sanogo IN, Guinat C, Dellicour S, Diakité MA, Niang M, Koita OA, Camus C, Ducatez M. Genetic insights of H9N2 avian influenza viruses circulating in Mali and phylogeographic patterns in Northern and Western Africa. Virus Evol 2024; 10:veae011. [PMID: 38435712 PMCID: PMC10908551 DOI: 10.1093/ve/veae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 01/18/2024] [Accepted: 02/13/2024] [Indexed: 03/05/2024] Open
Abstract
Avian influenza viruses (AIVs) of the H9N2 subtype have become widespread in Western Africa since their first detection in 2017 in Burkina Faso. However, the genetic characteristics and diffusion patterns of the H9N2 virus remain poorly understood in Western Africa, mainly due to limited surveillance activities. In addition, Mali, a country considered to play an important role in the epidemiology of AIVs in the region, lacks more comprehensive data on the genetic characteristics of these viruses, especially the H9N2 subtype. To better understand the genetic characteristics and spatio-temporal dynamics of H9N2 virus within this region, we carried out a comprehensive genetic characterization of H9N2 viruses collected through active surveillance in live bird markets in Mali between 2021 and 2022. We also performed a continuous phylogeographic analysis to unravel the dispersal history of H9N2 lineages between Northern and Western Africa. The identified Malian H9N2 virus belonged to the G1 lineage, similar to viruses circulating in both Western and Northern Africa, and possessed multiple molecular markers associated with an increased potential for zoonotic transmission and virulence. Notably, some Malian strains carried the R-S-N-R motif at their cleavage site, mainly observed in H9N2 strains in Asia. Our continuous phylogeographic analysis revealed a single and significant long-distance lineage dispersal event of the H9N2 virus to Western Africa, likely to have originated from Morocco in 2015, shaping the westward diffusion of the H9N2 virus. Our study highlights the need for long-term surveillance of H9N2 viruses in poultry populations in Western Africa, which is crucial for a better understanding of virus evolution and effective management against potential zoonotic AIV strain emergence.
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Affiliation(s)
- Idrissa Nonmon Sanogo
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
- Faculté d’Agronomie et de Médecine Animale (FAMA), Université de Ségou, Ségou BP 24, Mali
| | - Claire Guinat
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels B-1050, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven BE-3000, Belgium
| | - Mohamed Adama Diakité
- Service diagnostic et recherche Laboratoire Central Vétérinaire, Bamako BP 2295, Mali
| | - Mamadou Niang
- Food and Agriculture Organization of the United Nations (FAO-UN), Emergency Centre for Transboundary Animal Diseases (ECTAD), Regional Office for Africa (RAF), Accra BP 1628, Ghana
| | - Ousmane A Koita
- Laboratoire de Biologie Moléculaire Appliquée, Faculté des Sciences et Techniques (FAST), University of Sciences, Techniques and Technologies of Bamako (USTTB), Mali Université de Bamako, Bamako E 3206, Mali
| | - Christelle Camus
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
| | - Mariette Ducatez
- Interactions Hôtes-Agents Pathogènes (IHAP), UMR 1225, Université de Toulouse, INRAE, ENVT, Toulouse 31076, France
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3
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Bahrami MA, Tabari S, Tahmasebi S, Zangouri V, Ravangard R. Strategies to Promote Empowerment Status of Breast Cancer Women. Int J Breast Cancer 2024; 2024:3305399. [PMID: 38348180 PMCID: PMC10861285 DOI: 10.1155/2024/3305399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/01/2024] [Accepted: 01/25/2024] [Indexed: 02/15/2024] Open
Abstract
Background As the second leading cause of death in women in the world, breast cancer has several physical and psychological effects. Nowadays, nonclinical approaches such as patient empowerment have been considered by physicians along with clinical care. Given the increasing number of breast cancer women worldwide, promoting the empowerment of these patients is one of the key factors affecting their survival and quality of life. Therefore, because of no comprehensive research on the empowerment needs and related improvement strategies, this study is aimed at determining the empowerment status of breast cancer patients referred to the Shahid Motahari Breast Cancer Clinic in Iran, Shiraz, and at providing strategies to improve their empowerment in 2021. Methods This applied study was conducted in two phases. In the quantitative phase, 310 Cancer-Related Patient Empowerment Scale questionnaires (Persian format) were distributed among the studied patients selected through the random sampling method in the clinic, and the items with "unacceptable status" became the basis for determining the empowerment strategies through the scoping review and semistructured interviews with 22 medical staff and patients through the thematic analysis. The collected data were analyzed using the SPSS 20.0 and MAXQDA10 software. Results The mean score of the participants' empowerment strategies was 3.58. The results showed that trust in the physician, family support, and spiritual beliefs could affect the empowerment of the studied patients. Moreover, the participants needed empowerment strategies in 11 scale items with unacceptable status, for which 46 strategies were determined in the scoping review and interview phase. Conclusion The results of this study provided useful strategies for empowering breast cancer patients, the most important of which were classified into five categories of financial support, informational support, interaction with the physician, occupational support, and complementary therapies, the use of which by the stakeholders could help to improve the patients' quality of life while improving their empowerment.
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Affiliation(s)
- Mohammad Amin Bahrami
- Health Human Resources Research Center, Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Shahrzad Tabari
- Student Research Committee, Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sedigheh Tahmasebi
- Breast Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Vahid Zangouri
- Breast Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ramin Ravangard
- Health Human Resources Research Center, Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
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Carnegie L, Raghwani J, Fournié G, Hill SC. Phylodynamic approaches to studying avian influenza virus. Avian Pathol 2023; 52:289-308. [PMID: 37565466 DOI: 10.1080/03079457.2023.2236568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 06/23/2023] [Accepted: 07/07/2023] [Indexed: 08/12/2023]
Abstract
Avian influenza viruses can cause severe disease in domestic and wild birds and are a pandemic threat. Phylodynamics is the study of how epidemiological, evolutionary, and immunological processes can interact to shape viral phylogenies. This review summarizes how phylodynamic methods have and could contribute to the study of avian influenza viruses. Specifically, we assess how phylodynamics can be used to examine viral spread within and between wild or domestic bird populations at various geographical scales, identify factors associated with virus dispersal, and determine the order and timing of virus lineage movement between geographic regions or poultry production systems. We discuss factors that can complicate the interpretation of phylodynamic results and identify how future methodological developments could contribute to improved control of the virus.
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Affiliation(s)
- L Carnegie
- Department of Pathobiology and Population Sciences, Royal Veterinary College (RVC), Hatfield, UK
| | - J Raghwani
- Department of Pathobiology and Population Sciences, Royal Veterinary College (RVC), Hatfield, UK
| | - G Fournié
- Department of Pathobiology and Population Sciences, Royal Veterinary College (RVC), Hatfield, UK
- Université de Lyon, INRAE, VetAgro Sup, UMR EPIA, Marcy l'Etoile, France
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint Genes Champanelle, France
| | - S C Hill
- Department of Pathobiology and Population Sciences, Royal Veterinary College (RVC), Hatfield, UK
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5
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Van Borm S, Boseret G, Dellicour S, Steensels M, Roupie V, Vandenbussche F, Mathijs E, Vilain A, Driesen M, Dispas M, Delcloo AW, Lemey P, Mertens I, Gilbert M, Lambrecht B, van den Berg T. Combined Phylogeographic Analyses and Epidemiologic Contact Tracing to Characterize Atypically Pathogenic Avian Influenza (H3N1) Epidemic, Belgium, 2019. Emerg Infect Dis 2023; 29:351-359. [PMID: 36692362 PMCID: PMC9881769 DOI: 10.3201/eid2902.220765] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.
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Dellicour S, Lemey P, Suchard MA, Gilbert M, Baele G. Accommodating sampling location uncertainty in continuous phylogeography. Virus Evol 2022; 8:veac041. [PMID: 35795297 PMCID: PMC9248920 DOI: 10.1093/ve/veac041] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 04/22/2022] [Accepted: 05/18/2022] [Indexed: 02/01/2023] Open
Abstract
Phylogeographic inference of the dispersal history of viral lineages offers key opportunities to tackle epidemiological questions about the spread of fast-evolving pathogens across human, animal and plant populations. In continuous space, i.e. when locations are specified by longitude and latitude, these reconstructions are however often limited by the availability or accessibility of precise sampling locations required for such spatially explicit analyses. We here review the different approaches that can be considered when genomic sequences are associated with a geographic area of sampling instead of precise coordinates. In particular, we describe and compare the approaches to define homogeneous and heterogeneous prior ranges of sampling coordinates.
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Affiliation(s)
| | | | | | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 av. FD Roosevelt, Bruxelles 1050, Belgium
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7
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Accounting for spatial sampling patterns in Bayesian phylogeography. Proc Natl Acad Sci U S A 2021; 118:2105273118. [PMID: 34930835 PMCID: PMC8719894 DOI: 10.1073/pnas.2105273118] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2021] [Indexed: 12/13/2022] Open
Abstract
Statistical phylogeography has led to substantial progress in our understanding of the pace and means by which organisms colonize their habitats. Yet, inference from these models often relies on implicit assumptions pertaining to spatial sampling design, potentially leading to biased estimation of key biological parameters. While sampled locations sometimes convey signal about the processes that shape spatial biodiversity, they do not always do so. We present a statistical approach that permits accurate estimation of dispersal rates, even in cases where spatial sampling is driven by practical motivations unrelated to the outcome of the evolutionary process. The proposed framework paves the way to further developments in phylogeography with key applications, including the efficient monitoring of pandemics and invasive species during the course of their evolution. Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.
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Makau DN, Alkhamis MA, Paploski IAD, Corzo CA, Lycett S, VanderWaal K. Integrating animal movements with phylogeography to model the spread of PRRSV in the USA. Virus Evol 2021; 7:veab060. [PMID: 34532062 PMCID: PMC8438914 DOI: 10.1093/ve/veab060] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/22/2021] [Accepted: 06/14/2021] [Indexed: 12/17/2022] Open
Abstract
Viral sequence data coupled with phylodynamic models have become instrumental in investigating the outbreaks of human and animal diseases, and the incorporation of the hypothesized drivers of pathogen spread can enhance the interpretation from phylodynamic inference. Integrating animal movement data with phylodynamics allows us to quantify the extent to which the spatial diffusion of a pathogen is influenced by animal movements and contrast the relative importance of different types of movements in shaping pathogen distribution. We combine animal movement, spatial, and environmental data in a Bayesian phylodynamic framework to explain the spatial diffusion and evolutionary trends of a rapidly spreading sub-lineage (denoted L1A) of porcine reproductive and respiratory syndrome virus (PRRSV) Type 2 from 2014 to 2017. PRRSV is the most important endemic pathogen affecting pigs in the USA, and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the US swine industry to date. Data included 984 open reading frame 5 (ORF5) PRRSV L1A sequences obtained from two production systems in a swine-dense production region (∼85,000 mi2) in the USA between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector were summarized by age class (wean: 3–4 weeks; feeder: 8–25 weeks; breeding: ≥21 weeks). We implemented a discrete-space phylogeographic generalized linear model using Bayesian evolutionary analysis by sampling trees (BEAST) to infer factors associated with variability in between-sector diffusion rates of PRRSV L1A. We found that between-sector spread was enhanced by the movement of feeder pigs, spatial adjacency of sectors, and farm density in the destination sector. The PRRSV L1A strain was introduced in the study area in early 2013, and genetic diversity and effective population size peaked in 2015 before fluctuating seasonally (peaking during the summer months). Our study underscores the importance of animal movements and shows, for the first time, that the movement of feeder pigs (8–25 weeks old) shaped the spatial patterns of PRRSV spread much more strongly than the movements of other age classes of pigs. The inclusion of movement data into phylodynamic models as done in this analysis may enhance our ability to identify crucial pathways of disease spread that can be targeted to mitigate the spatial spread of infectious human and animal pathogens.
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Affiliation(s)
- Dennis N Makau
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
| | - Moh A Alkhamis
- Department of Epidemiology and Biostatistics, Faculty of Public Health, Health Sciences Center, Kuwait University, Kuwait City, 24923, Safat 13110, Kuwait
| | - Igor A D Paploski
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
| | - Cesar A Corzo
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
| | - Samantha Lycett
- Roslin Institute, University of Edinburgh, Edinburgh, Midlothian, EH25 9RG, UK
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
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9
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Nahata KD, Bollen N, Gill MS, Layan M, Bourhy H, Dellicour S, Baele G. On the Use of Phylogeographic Inference to Infer the Dispersal History of Rabies Virus: A Review Study. Viruses 2021; 13:v13081628. [PMID: 34452492 PMCID: PMC8402743 DOI: 10.3390/v13081628] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 12/28/2022] Open
Abstract
Rabies is a neglected zoonotic disease which is caused by negative strand RNA-viruses belonging to the genus Lyssavirus. Within this genus, rabies viruses circulate in a diverse set of mammalian reservoir hosts, is present worldwide, and is almost always fatal in non-vaccinated humans. Approximately 59,000 people are still estimated to die from rabies each year, leading to a global initiative to work towards the goal of zero human deaths from dog-mediated rabies by 2030, requiring scientific efforts from different research fields. The past decade has seen a much increased use of phylogeographic and phylodynamic analyses to study the evolution and spread of rabies virus. We here review published studies in these research areas, making a distinction between the geographic resolution associated with the available sequence data. We pay special attention to environmental factors that these studies found to be relevant to the spread of rabies virus. Importantly, we highlight a knowledge gap in terms of applying these methods when all required data were available but not fully exploited. We conclude with an overview of recent methodological developments that have yet to be applied in phylogeographic and phylodynamic analyses of rabies virus.
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Affiliation(s)
- Kanika D. Nahata
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
- Correspondence:
| | - Nena Bollen
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
| | - Mandev S. Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
| | - Maylis Layan
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Sorbonne Université, UMR2000, CNRS, 75015 Paris, France;
| | - Hervé Bourhy
- Lyssavirus Epidemiology and Neuropathology Unit, Institut Pasteur, 75015 Paris, France;
- WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, 75015 Paris, France
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Bruxelles, Belgium
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute KU Leuven, 3000 Leuven, Belgium; (N.B.); (M.S.G.); (S.D.); (G.B.)
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10
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Dellicour S, Gill MS, Faria NR, Rambaut A, Pybus OG, Suchard MA, Lemey P. Relax, Keep Walking - A Practical Guide to Continuous Phylogeographic Inference with BEAST. Mol Biol Evol 2021; 38:3486-3493. [PMID: 33528560 PMCID: PMC8321535 DOI: 10.1093/molbev/msab031] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.
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Affiliation(s)
- Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, United Kingdom
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
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11
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He WT, Ji X, He W, Dellicour S, Wang S, Li G, Zhang L, Gilbert M, Zhu H, Xing G, Veit M, Huang Z, Han GZ, Huang Y, Suchard MA, Baele G, Lemey P, Su S. Genomic Epidemiology, Evolution, and Transmission Dynamics of Porcine Deltacoronavirus. Mol Biol Evol 2020; 37:2641-2654. [PMID: 32407507 PMCID: PMC7454817 DOI: 10.1093/molbev/msaa117] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown once again that coronavirus (CoV) in animals are potential sources for epidemics in humans. Porcine deltacoronavirus (PDCoV) is an emerging enteropathogen of swine with a worldwide distribution. Here, we implemented and described an approach to analyze the epidemiology of PDCoV following its emergence in the pig population. We performed an integrated analysis of full genome sequence data from 21 newly sequenced viruses, along with comprehensive epidemiological surveillance data collected globally over the last 15 years. We found four distinct phylogenetic lineages of PDCoV, which differ in their geographic circulation patterns. Interestingly, we identified more frequent intra- and interlineage recombination and higher virus genetic diversity in the Chinese lineages compared with the USA lineage where pigs are raised in different farming systems and ecological environments. Most recombination breakpoints are located in the ORF1ab gene rather than in genes encoding structural proteins. We also identified five amino acids under positive selection in the spike protein suggesting a role for adaptive evolution. According to structural mapping, three positively selected sites are located in the N-terminal domain of the S1 subunit, which is the most likely involved in binding to a carbohydrate receptor, whereas the other two are located in or near the fusion peptide of the S2 subunit and thus might affect membrane fusion. Finally, our phylogeographic investigations highlighted notable South-North transmission as well as frequent long-distance dispersal events in China that could implicate human-mediated transmission. Our findings provide new insights into the evolution and dispersal of PDCoV that contribute to our understanding of the critical factors involved in CoVs emergence.
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Affiliation(s)
- Wan-Ting He
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Xiang Ji
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA.,Department of Mathematics, Tulane University, New Orleans, LA
| | - Wei He
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium.,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Shilei Wang
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Gairu Li
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Letian Zhang
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - Marius Gilbert
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Henan Zhu
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA
| | - Gang Xing
- Key Laboratory of Animal Virology of Ministry of Agriculture, Zhejiang University, Hangzhou, China
| | - Michael Veit
- Institute for Virology, Center for Infection Medicine, Veterinary Faculty, Free University Berlin, Berlin, Germany
| | - Zhen Huang
- Zhengzhou New Channel Agricultural Technology Co., Ltd, Zhengzhou, Henan, China
| | - Guan-Zhu Han
- Jiangsu Key Laboratory for Microbes and Functional Genomics, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, China
| | - Yaowei Huang
- Key Laboratory of Animal Virology of Ministry of Agriculture, Zhejiang University, Hangzhou, China
| | - Marc A Suchard
- Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA.,Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Shuo Su
- MOE International Joint Collaborative Research Laboratory for Animal Health & Food Safety, Jiangsu Engineering Laboratory of Animal Immunology, Institute of Immunology, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
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