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Mbewe W, Mukasa S, Ochwo-Ssemakula M, Sseruwagi P, Tairo F, Ndunguru J, Duffy S. Cassava brown streak virus evolves with a nucleotide-substitution rate that is typical for the family Potyviridae. Virus Res 2024; 346:199397. [PMID: 38750679 PMCID: PMC11145536 DOI: 10.1016/j.virusres.2024.199397] [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: 12/14/2023] [Revised: 05/08/2024] [Accepted: 05/12/2024] [Indexed: 05/25/2024]
Abstract
The ipomoviruses (family Potyviridae) that cause cassava brown streak disease (cassava brown streak virus [CBSV] and Uganda cassava brown streak virus [UCBSV]) are damaging plant pathogens that affect the sustainability of cassava production in East and Central Africa. However, little is known about the rate at which the viruses evolve and when they emerged in Africa - which inform how easily these viruses can host shift and resist RNAi approaches for control. We present here the rates of evolution determined from the coat protein gene (CP) of CBSV (Temporal signal in a UCBSV dataset was not sufficient for comparable analysis). Our BEAST analysis estimated the CBSV CP evolves at a mean rate of 1.43 × 10-3 nucleotide substitutions per site per year, with the most recent common ancestor of sampled CBSV isolates existing in 1944 (95% HPD, between years 1922 - 1963). We compared the published measured and estimated rates of evolution of CPs from ten families of plant viruses and showed that CBSV is an average-evolving potyvirid, but that members of Potyviridae evolve more quickly than members of Virgaviridae and the single representatives of Betaflexiviridae, Bunyaviridae, Caulimoviridae and Closteroviridae.
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Affiliation(s)
- Willard Mbewe
- Department of Biological Sciences, Malawi University of Science and Technology, P. O. Box 5196, Limbe, Malawi.
| | - Settumba Mukasa
- School of Agriculture and Environmental Science, Department of Agricultural Production, P. O. Box 7062, Makerere University, Kampala, Uganda
| | - Mildred Ochwo-Ssemakula
- School of Agriculture and Environmental Science, Department of Agricultural Production, P. O. Box 7062, Makerere University, Kampala, Uganda
| | - Peter Sseruwagi
- Mikocheni Agricultural Research Institute, P.O. Box 6226, Dar es Slaam, Tanzania
| | - Fred Tairo
- Mikocheni Agricultural Research Institute, P.O. Box 6226, Dar es Slaam, Tanzania
| | - Joseph Ndunguru
- Mikocheni Agricultural Research Institute, P.O. Box 6226, Dar es Slaam, Tanzania
| | - Siobain Duffy
- Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, NJ 08901, United States.
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2
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Khurana MP, Scheidwasser-Clow N, Penn MJ, Bhatt S, Duchêne DA. The Limits of the Constant-rate Birth-Death Prior for Phylogenetic Tree Topology Inference. Syst Biol 2024; 73:235-246. [PMID: 38153910 PMCID: PMC11129600 DOI: 10.1093/sysbio/syad075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 12/20/2023] [Accepted: 12/27/2023] [Indexed: 12/30/2023] Open
Abstract
Birth-death models are stochastic processes describing speciation and extinction through time and across taxa and are widely used in biology for inference of evolutionary timescales. Previous research has highlighted how the expected trees under the constant-rate birth-death (crBD) model tend to differ from empirical trees, for example, with respect to the amount of phylogenetic imbalance. However, our understanding of how trees differ between the crBD model and the signal in empirical data remains incomplete. In this Point of View, we aim to expose the degree to which the crBD model differs from empirically inferred phylogenies and test the limits of the model in practice. Using a wide range of topology indices to compare crBD expectations against a comprehensive dataset of 1189 empirically estimated trees, we confirm that crBD model trees frequently differ topologically compared with empirical trees. To place this in the context of standard practice in the field, we conducted a meta-analysis for a subset of the empirical studies. When comparing studies that used Bayesian methods and crBD priors with those that used other non-crBD priors and non-Bayesian methods (i.e., maximum likelihood methods), we do not find any significant differences in tree topology inferences. To scrutinize this finding for the case of highly imbalanced trees, we selected the 100 trees with the greatest imbalance from our dataset, simulated sequence data for these tree topologies under various evolutionary rates, and re-inferred the trees under maximum likelihood and using the crBD model in a Bayesian setting. We find that when the substitution rate is low, the crBD prior results in overly balanced trees, but the tendency is negligible when substitution rates are sufficiently high. Overall, our findings demonstrate the general robustness of crBD priors across a broad range of phylogenetic inference scenarios but also highlight that empirically observed phylogenetic imbalance is highly improbable under the crBD model, leading to systematic bias in data sets with limited information content.
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Affiliation(s)
- Mark P Khurana
- Section of Epidemiology, Department of Public Health, University of Copenhagen, 1352 Copenhagen, Denmark
| | - Neil Scheidwasser-Clow
- Section of Epidemiology, Department of Public Health, University of Copenhagen, 1352 Copenhagen, Denmark
| | - Matthew J Penn
- Department of Statistics, University of Oxford, OX1 3LB, Oxford, UK
| | - Samir Bhatt
- Section of Epidemiology, Department of Public Health, University of Copenhagen, 1352 Copenhagen, Denmark
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, SW7 2AZ, London, UK
| | - David A Duchêne
- Centre for Evolutionary Hologenomics, University of Copenhagen, 1352 Copenhagen, Denmark
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3
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Samson S, Lord É, Makarenkov V. Assessing the emergence time of SARS-CoV-2 zoonotic spillover. PLoS One 2024; 19:e0301195. [PMID: 38574109 PMCID: PMC10994396 DOI: 10.1371/journal.pone.0301195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/12/2024] [Indexed: 04/06/2024] Open
Abstract
Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.
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Affiliation(s)
- Stéphane Samson
- Department of Computer Sciences, Université du Québec à Montréal, Montréal, Canada
- Saint-Jean-sur-Richelieu Research and Development Centre, Agriculture and Agri-Food Canada, Saint-Jean-sur-Richelieu, Québec, Canada
| | - Étienne Lord
- Saint-Jean-sur-Richelieu Research and Development Centre, Agriculture and Agri-Food Canada, Saint-Jean-sur-Richelieu, Québec, Canada
| | - Vladimir Makarenkov
- Department of Computer Sciences, Université du Québec à Montréal, Montréal, Canada
- Mila—Quebec AI Institute, Montreal, QC, Canada
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4
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Ghafari M, Sõmera M, Sarmiento C, Niehl A, Hébrard E, Tsoleridis T, Ball J, Moury B, Lemey P, Katzourakis A, Fargette D. Revisiting the origins of the Sobemovirus genus: A case for ancient origins of plant viruses. PLoS Pathog 2024; 20:e1011911. [PMID: 38206964 PMCID: PMC10807823 DOI: 10.1371/journal.ppat.1011911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/24/2024] [Accepted: 12/18/2023] [Indexed: 01/13/2024] Open
Abstract
The discrepancy between short- and long-term rate estimates, known as the time-dependent rate phenomenon (TDRP), poses a challenge to extrapolating evolutionary rates over time and reconstructing evolutionary history of viruses. The TDRP reveals a decline in evolutionary rate estimates with the measurement timescale, explained empirically by a power-law rate decay, notably observed in animal and human viruses. A mechanistic evolutionary model, the Prisoner of War (PoW) model, has been proposed to address TDRP in viruses. Although TDRP has been studied in animal viruses, its impact on plant virus evolutionary history remains largely unexplored. Here, we investigated the consequences of TDRP in plant viruses by applying the PoW model to reconstruct the evolutionary history of sobemoviruses, plant pathogens with significant importance due to their impact on agriculture and plant health. Our analysis showed that the Sobemovirus genus dates back over four million years, indicating an ancient origin. We found evidence that supports deep host jumps to Poaceae, Fabaceae, and Solanaceae occurring between tens to hundreds of thousand years ago, followed by specialization. Remarkably, the TDRP-corrected evolutionary history of sobemoviruses was extended far beyond previous estimates that had suggested their emergence nearly 9,000 years ago, a time coinciding with the Neolithic period in the Near East. By incorporating sequences collected through metagenomic analyses, the resulting phylogenetic tree showcases increased genetic diversity, reflecting a deep history of sobemovirus species. We identified major radiation events beginning between 4,600 to 2,000 years ago, which aligns with the Neolithic period in various regions, suggesting a period of rapid diversification from then to the present. Our findings make a case for the possibility of deep evolutionary origins of plant viruses.
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Affiliation(s)
- Mahan Ghafari
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Merike Sõmera
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
| | - Cecilia Sarmiento
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
| | - Annette Niehl
- Julius Kühn Institute (JKI)–Federal Research Centre for Cultivated Plants, Institute for Epidemiology and Pathogen Diagnostics, Braunschweig, Germany
| | - Eugénie Hébrard
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Theocharis Tsoleridis
- The Wolfson Centre for Global Virus Research and School of Life Sciences, The University of Nottingham, Queen’s Medical Centre, Nottingham, United Kingdom
| | - Jonathan Ball
- The Wolfson Centre for Global Virus Research and School of Life Sciences, The University of Nottingham, Queen’s Medical Centre, Nottingham, United Kingdom
- Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, United Kingdom
| | | | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Aris Katzourakis
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Denis Fargette
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France
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5
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Murray GGR, Hossain ASMM, Miller EL, Bruchmann S, Balmer AJ, Matuszewska M, Herbert J, Hadjirin NF, Mugabi R, Li G, Ferrando ML, Fernandes de Oliveira IM, Nguyen T, Yen PLK, Phuc HD, Zaw Moe A, Su Wai T, Gottschalk M, Aragon V, Valentin-Weigand P, Heegaard PMH, Vrieling M, Thein Maw M, Thidar Myint H, Tun Win Y, Thi Hoa N, Bentley SD, Clavijo MJ, Wells JM, Tucker AW, Weinert LA. The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs. Proc Natl Acad Sci U S A 2023; 120:e2307773120. [PMID: 37963246 PMCID: PMC10666105 DOI: 10.1073/pnas.2307773120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 10/02/2023] [Indexed: 11/16/2023] Open
Abstract
The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized.
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Affiliation(s)
- Gemma G. R. Murray
- Department of Genetics, Evolution and Environment, University College London, LondonWC1E 6BT, United Kingdom
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
| | | | - Eric L. Miller
- Department of Biology, Haverford College, Haverford, PA19041
| | - Sebastian Bruchmann
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
| | - Andrew J. Balmer
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
| | - Marta Matuszewska
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
- Department of Medicine, University of Cambridge, CambridgeCB2 2QQ, United Kingdom
| | - Josephine Herbert
- Centre for Enzyme Innovation, University of Portsmouth, PortsmouthPO1 2DD, United Kingdom
| | - Nazreen F. Hadjirin
- Nuffield Department of Population Health, University of Oxford, OxfordOX3 7LF, United Kingdom
| | - Robert Mugabi
- College of Veterinary Medicine, Iowa State University, Ames, IA50011
| | - Ganwu Li
- College of Veterinary Medicine, Iowa State University, Ames, IA50011
| | - Maria Laura Ferrando
- Animal Sciences Department, Wageningen University, 6700 AHWageningen, The Netherlands
| | | | - Thanh Nguyen
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Phung L. K. Yen
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Ho D. Phuc
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Aung Zaw Moe
- Livestock Breeding and Veterinary Department, Yangon, Myanmar
| | - Thiri Su Wai
- Livestock Breeding and Veterinary Department, Yangon, Myanmar
| | - Marcelo Gottschalk
- Département de Pathologie et Microbiologie, Université de Montréal, QuébecJ2S 2M2, Canada
| | - Virginia Aragon
- Unitat Mixta d’Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal, Campus de la Universitat Autònoma de Barcelona, Barcelona08193, Spain
- OIE Collaborating Centre for the Research and Control of Emerging and Re-Emerging Swine Diseases in Europe (IRTA-CReSA), Barcelona08193, Spain
| | - Peter Valentin-Weigand
- Institute for Microbiology, University of Veterinary Medicine Hannover, Hannover30559, Germany
| | - Peter M. H. Heegaard
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby2800, Denmark
| | - Manouk Vrieling
- Wageningen Bioveterinary Research, 8221 RALelystad, The Netherlands
| | - Min Thein Maw
- Livestock Breeding and Veterinary Department, Yangon, Myanmar
| | | | - Ye Tun Win
- Livestock Breeding and Veterinary Department, Yangon, Myanmar
| | - Ngo Thi Hoa
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, OxfordOX3 7LG, United Kingdom
- Microbiology Department and Center for Tropical Medicine Research, Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam
| | - Stephen D. Bentley
- Parasites and Microbes Programme, Wellcome Sanger Institute, CambridgeCB10 1RQ, United Kingdom
| | - Maria J. Clavijo
- College of Veterinary Medicine, Iowa State University, Ames, IA50011
| | - Jerry M. Wells
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
- Animal Sciences Department, Wageningen University, 6700 AHWageningen, The Netherlands
| | - Alexander W. Tucker
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
| | - Lucy A. Weinert
- Department of Veterinary Medicine, University of Cambridge, CambridgeCB3 0ES, United Kingdom
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6
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Billard E, Barro M, Sérémé D, Bangratz M, Wonni I, Koala M, Kassankogno AI, Hébrard E, Thébaud G, Brugidou C, Poulicard N, Tollenaere C. Dynamics of the rice yellow mottle disease in western Burkina Faso: Epidemic monitoring, spatio-temporal variation of viral diversity, and pathogenicity in a disease hotspot. Virus Evol 2023; 9:vead049. [PMID: 37649958 PMCID: PMC10465090 DOI: 10.1093/ve/vead049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/04/2023] [Accepted: 08/20/2023] [Indexed: 09/01/2023] Open
Abstract
The rice yellow mottle virus (RYMV) is a model in plant virus molecular epidemiology, with the reconstruction of historical introduction routes at the scale of the African continent. However, information on patterns of viral prevalence and viral diversity over multiple years at a local scale remains scarce, in spite of potential implications for crop protection. Here, we describe a 5-year (2015-9) monitoring of RYMV prevalence in six sites from western Burkina Faso (geographic areas of Bama, Banzon, and Karfiguela). It confirmed one irrigated site as a disease hotspot and also found one rainfed lowland (RL) site with occasional high prevalence levels. Within the studied fields, a pattern of disease aggregation was evidenced at a 5-m distance, as expected for a mechanically transmitted virus. Next, we monitored RYMV genetic diversity in the irrigated disease hotspot site, revealing a high viral diversity, with the current coexistence of various distinct genetic groups at the site scale (ca. 520 ha) and also within various specific fields (25 m side). One genetic lineage, named S1bzn, is the most recently emerged group and increased in frequency over the studied period (from 20 per cent or less in 2015-6 to more than 65 per cent in 2019). Its genome results from a recombination between two other lineages (S1wa and S1ca). Finally, experimental work revealed that three rice varieties commonly cultivated in Burkina Faso were not different in terms of resistance level, and we also found no significant effect of RYMV genetic groups on symptom expression and viral load. We found, however, that infection outcome depended on the specific RYMV isolate, with two isolates from the lineage S1bzn accumulating at the highest level at early infections. Overall, this study documents a case of high viral prevalence, high viral diversity, and co-occurrence of divergent genetic lineages at a small geographic scale. A recently emerged lineage, which comprises viral isolates inducing severe symptoms and high accumulation under controlled conditions, could be recently rising through natural selection. Following up the monitoring of RYMV diversity is required to confirm this trend and further understand the factors driving the local maintenance of viral diversity.
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Affiliation(s)
- Estelle Billard
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Mariam Barro
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
- INERA, Institut de l’Environnement et de Recherches Agricoles, Laboratoire de Phytopathologie, Bobo-Dioulasso, Burkina Faso
| | - Drissa Sérémé
- INERA, Institut de l’Environnement et de Recherches Agricoles, Laboratoire de Virologie et de Biologie Végétale, Kamboinsé, Burkina Faso
| | - Martine Bangratz
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Issa Wonni
- INERA, Institut de l’Environnement et de Recherches Agricoles, Laboratoire de Phytopathologie, Bobo-Dioulasso, Burkina Faso
| | - Moustapha Koala
- INERA, Institut de l’Environnement et de Recherches Agricoles, Laboratoire de Virologie et de Biologie Végétale, Kamboinsé, Burkina Faso
| | - Abalo Itolou Kassankogno
- INERA, Institut de l’Environnement et de Recherches Agricoles, Laboratoire de Phytopathologie, Bobo-Dioulasso, Burkina Faso
| | - Eugénie Hébrard
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Gaël Thébaud
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Christophe Brugidou
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Nils Poulicard
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
| | - Charlotte Tollenaere
- PHIM, Plant Health Institute of Montpellier, Univ. Montpellier, IRD, CIRAD, INRAE, Institute Agro, Montpellier, France
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7
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Campos PE, Pruvost O, Boyer K, Chiroleu F, Cao TT, Gaudeul M, Baider C, Utteridge TMA, Becker N, Rieux A, Gagnevin L. Herbarium specimen sequencing allows precise dating of Xanthomonas citri pv. citri diversification history. Nat Commun 2023; 14:4306. [PMID: 37474518 PMCID: PMC10359311 DOI: 10.1038/s41467-023-39950-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/15/2023] [Indexed: 07/22/2023] Open
Abstract
Herbarium collections are an important source of dated, identified and preserved DNA, whose use in comparative genomics and phylogeography can shed light on the emergence and evolutionary history of plant pathogens. Here, we reconstruct 13 historical genomes of the bacterial crop pathogen Xanthomonas citri pv. citri (Xci) from infected Citrus herbarium specimens. Following authentication based on ancient DNA damage patterns, we compare them with a large set of modern genomes to estimate their phylogenetic relationships, pathogenicity-associated gene content and several evolutionary parameters. Our results indicate that Xci originated in Southern Asia ~11,500 years ago (perhaps in relation to Neolithic climate change and the development of agriculture) and diversified during the beginning of the 13th century, after Citrus diversification and before spreading to the rest of the world (probably via human-driven expansion of citriculture through early East-West trade and colonization).
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Affiliation(s)
- Paola E Campos
- CIRAD, UMR PVBMT, F-97410, St Pierre, La Réunion, France
- Institut de Systématique, Évolution, Biodiversité (ISyEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 rue Cuvier, CP 50, 75005, Paris, France
| | | | - Karine Boyer
- CIRAD, UMR PVBMT, F-97410, St Pierre, La Réunion, France
| | | | - Thuy Trang Cao
- CIRAD, UMR PVBMT, F-97410, St Pierre, La Réunion, France
| | - Myriam Gaudeul
- Institut de Systématique, Évolution, Biodiversité (ISyEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 rue Cuvier, CP 50, 75005, Paris, France
- Herbier national, Muséum national d'Histoire naturelle, CP39, 57 rue Cuvier, 75005, Paris, France
| | - Cláudia Baider
- The Mauritius Herbarium, Agricultural Services, Ministry of Agro-Industry and Food Security, R.E. Vaughan Building (MSIRI Compound), Reduit, 80835, Mauritius
| | | | - Nathalie Becker
- Institut de Systématique, Évolution, Biodiversité (ISyEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 rue Cuvier, CP 50, 75005, Paris, France
| | - Adrien Rieux
- CIRAD, UMR PVBMT, F-97410, St Pierre, La Réunion, France.
| | - Lionel Gagnevin
- PHIM Plant Health Institute, Univ. Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France.
- CIRAD, UMR PHIM, Montpellier, France.
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8
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Bondaryuk AN, Belykh OI, Andaev EI, Bukin YS. Inferring Evolutionary Timescale of Omsk Hemorrhagic Fever Virus. Viruses 2023; 15:1576. [PMID: 37515262 PMCID: PMC10385366 DOI: 10.3390/v15071576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/15/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Until 2020, there were only three original complete genome (CG) nucleotide sequences of Omsk hemorrhagic fever virus (OHFV) in GenBank. For this reason, the evolutionary rate and divergence time assessments reported in the literature were based on the E gene sequences, but notably without temporal signal evaluation, such that their reliability is unclear. As of July 2022, 47 OHFV CG sequences have been published, which enables testing of temporal signal in the data and inferring unbiased and reliable substitution rate and divergence time values. Regression analysis in the TempEst software demonstrated a stronger clocklike behavior in OHFV samples for the complete open reading frame (ORF) data set (R2 = 0.42) than for the E gene data set (R2 = 0.11). Bayesian evaluation of temporal signal indicated very strong evidence, with a log Bayes factor of more than 5, in favor of temporal signal in all data sets. Our results based on the complete ORF sequences showed a more precise OHFV substitution rate (95% highest posterior density (HPD) interval, 9.1 × 10-5-1.8 × 10-4 substitutions per site per year) and tree root height (416-896 years ago) compared with previous assessments. The rate obtained is significantly higher than tick-borne encephalitis virus by at least 3.8-fold. The phylogenetic analysis and past population dynamics reconstruction revealed the declining trend of OHFV genetic diversity, but there was phylogenomic evidence that implicit virus subpopulations evolved locally and underwent an exponential growth phase.
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Affiliation(s)
- Artem N Bondaryuk
- Laboratory of Natural Focal Viral Infections, Irkutsk Antiplague Research Institute of Siberia and the Far East, Irkutsk 664047, Russia
- Limnological Institute, Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia
| | - Olga I Belykh
- Limnological Institute, Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia
| | - Evgeny I Andaev
- Laboratory of Natural Focal Viral Infections, Irkutsk Antiplague Research Institute of Siberia and the Far East, Irkutsk 664047, Russia
| | - Yurij S Bukin
- Limnological Institute, Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia
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9
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Forni D, Molteni C, Cagliani R, Sironi M. Geographic Structuring and Divergence Time Frame of Monkeypox Virus in the Endemic Region. J Infect Dis 2023; 227:742-751. [PMID: 35831941 PMCID: PMC10044091 DOI: 10.1093/infdis/jiac298] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 07/08/2022] [Accepted: 07/12/2022] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Monkeypox is an emerging zoonosis endemic to Central and West Africa. Monkeypox virus (MPXV) is genetically structured in 2 major clades (clades 1 and 2/3), but its evolution is poorly explored. METHODS We retrieved MPXV genomes from public repositories and we analyzed geographic patterns using STRUCTURE. Molecular dating was performed using a using a Bayesian approach. RESULTS We show that the population transmitted in West Africa (clades 2/3) experienced limited drift. Conversely, clade 1 (transmitted in the Congo Basin) possibly underwent a bottleneck or founder effect. Depending on the model used, we estimated that the 2 clades separated ∼560-860 (highest posterior density: 450-960) years ago, a period characterized by expansions and contractions of rainforest areas, possibly creating the ecological conditions for the MPXV reservoir(s) to migrate. In the Congo Basin, MPXV diversity is characterized by 4 subpopulations that show no geographic structuring. Conversely, clades 2/3 are spatially structured with 2 populations located West and East of the Dahomey Gap. CONCLUSIONS The distinct histories of the 2 clades may derive from differences in MPXV ecology in West and Central Africa.
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Affiliation(s)
- Diego Forni
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, Bosisio Parini, Italy
| | - Cristian Molteni
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, Bosisio Parini, Italy
| | - Rachele Cagliani
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, Bosisio Parini, Italy
| | - Manuela Sironi
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, Bosisio Parini, Italy
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10
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Doizy A, Prin A, Cornu G, Chiroleu F, Rieux A. Phylostems: a new graphical tool to investigate temporal signal of heterochronous sequences datasets. BIOINFORMATICS ADVANCES 2023; 3:vbad026. [PMID: 36936370 PMCID: PMC10017117 DOI: 10.1093/bioadv/vbad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 02/16/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023]
Abstract
Motivation Molecular tip-dating of phylogenetic trees is a growing discipline that uses DNA sequences sampled at different points in time to co-estimate the timing of evolutionary events with rates of molecular evolution. Importantly, such inferences should only be performed on datasets displaying sufficient temporal signal, a feature important to test prior to any tip-dating inference. For this purpose, the most popular method considered to-date has been the 'root-to-tip regression' which consist in fitting a linear regression of the number of substitutions accumulated from the root to the tips of a phylogenetic tree as a function of sampling times. The main limitation of the regression method, in its current implementation, relies in the fact that the temporal signal can only be tested at the whole-tree scale (i.e. its root). Results To overcome this limitation we introduce Phylostems, a new graphical user-friendly tool developed to investigate temporal signal within every clade of a phylogenetic tree. We provide a 'how to' guide by running Phylostems on an empirical dataset and supply guidance for results interpretation. Availability and implementation Phylostems is freely available at https://pvbmt-apps.cirad.fr/apps/phylostems.
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Affiliation(s)
- Anna Doizy
- CIRAD, UMR PVBMT, La Réunion, St Pierre 97410, France
- DoAna—Statistiques Réunion, Reunion Island, Saint-Joseph F-97480, France
| | - Amaury Prin
- CIRAD, UMR PVBMT, La Réunion, St Pierre 97410, France
| | - Guillaume Cornu
- CIRAD, Univ Montpellier, UR Forests and Societies, 34398 Montpellier Cedex 5, France
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11
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Matuszewska M, Murray GGR, Ba X, Wood R, Holmes MA, Weinert LA. Stable antibiotic resistance and rapid human adaptation in livestock-associated MRSA. eLife 2022; 11:74819. [PMID: 35762208 PMCID: PMC9239682 DOI: 10.7554/elife.74819] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 05/23/2022] [Indexed: 01/11/2023] Open
Abstract
Mobile genetic elements (MGEs) are agents of horizontal gene transfer in bacteria, but can also be vertically inherited by daughter cells. Establishing the dynamics that led to contemporary patterns of MGEs in bacterial genomes is central to predicting the emergence and evolution of novel and resistant pathogens. Methicillin-resistant Staphylococcus aureus (MRSA) clonal-complex (CC) 398 is the dominant MRSA in European livestock and a growing cause of human infections. Previous studies have identified three categories of MGEs whose presence or absence distinguishes livestock-associated CC398 from a closely related and less antibiotic-resistant human-associated population. Here, we fully characterise the evolutionary dynamics of these MGEs using a collection of 1180 CC398 genomes, sampled from livestock and humans, over 27 years. We find that the emergence of livestock-associated CC398 coincided with the acquisition of a Tn916 transposon carrying a tetracycline resistance gene, which has been stably inherited for 57 years. This was followed by the acquisition of a type V SCCmec that carries methicillin, tetracycline, and heavy metal resistance genes, which has been maintained for 35 years, with occasional truncations and replacements with type IV SCCmec. In contrast, a class of prophages that carry a human immune evasion gene cluster and that are largely absent from livestock-associated CC398 have been repeatedly gained and lost in both human- and livestock-associated CC398. These contrasting dynamics mean that when livestock-associated MRSA is transmitted to humans, adaptation to the human host outpaces loss of antibiotic resistance. In addition, the stable inheritance of resistance-associated MGEs suggests that the impact of ongoing reductions in antibiotic and zinc oxide use in European farms on livestock-associated MRSA will be slow to be realised. Antibiotic-resistant infections are a growing threat to human health. In 2019, these hard-to-treat infections resulted in 4.95 million deaths making them the third leading cause of death that year. Excessive use of antibiotics in humans is likely driving the emergence of drug-resistant bacteria. But there is a concern that use of antibiotics on livestock farms is also contributing. A type of bacteria traced back to livestock is a growing cause of human infections that do not respond to treatment with the antibiotic methicillin in Europe. It is called livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA). Bacteria can share genes that make them drug resistant or more deadly. These genes are often carried on mobile genetic elements that promote their movement from one bacterial cell to another. The most common type of LA-MRSA in Europe is clonal-complex 398 (CC398). It has two mobile genetic elements carrying antibiotic-resistance genes, but generally lacks a mobile genetic element that helps the bacterium escape the human immune system. Learning more about how LA-MRSA acquired these genetic changes may help scientists develop better strategies to protect the public. Matuszewska, Murray et al. analyzed the genomes of more than 1,000 samples of CC398 collected from humans, pigs and 13 other animal species in 28 countries over 27 years. They used this data to reconstruct the bacteria’s evolutionary history. Matuszewska, Murray et al. show that two mobile elements containing antibiotic resistance genes in CC398 were gained decades ago. One is more than 50 years old and was likely acquired around the time antibiotic use in livestock became common. While most CC398 in livestock do not have a mobile element that helps LA-MRSA evade the human immune system, they often gain it when they infect humans. This leads to highly drug-resistant human MRSA infections. The results of this study suggest that LA-MRSA is a serious threat to human health. The resistance of this bacterium has persisted for decades, spreading across different livestock species and different countries. These drug-resistant bacteria in livestock readily infect humans. Current efforts to reduce antibiotic use in farms may take decades to mitigate these risks. Additionally, the ban on zinc-oxide use on livestock in the European Union (coming into force June 2022) may not help reduce LA-MRSA, because the genes conferring resistance to bacteria and zinc treatment are not always linked.
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Affiliation(s)
- Marta Matuszewska
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Gemma G R Murray
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Xiaoliang Ba
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Rhiannon Wood
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Mark A Holmes
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Lucy A Weinert
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
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12
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Ma H, Li W, Zhang M, Yang Z, Lin L, Ghonaim AH, He Q. The Diversity and Spatiotemporally Evolutionary Dynamic of Atypical Porcine Pestivirus in China. Front Microbiol 2022; 13:937918. [PMID: 35814668 PMCID: PMC9263985 DOI: 10.3389/fmicb.2022.937918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 05/30/2022] [Indexed: 02/04/2023] Open
Abstract
The presence of congenital tremor (CT) type A-II in newborn piglets, caused by atypical porcine pestivirus (APPV), has been a focus since 2016. However, the source, evolutionary history, and transmission pattern of APPV in China remain poorly understood. In this study, we undertook phylogenetic analyses based on available complete E2 gene sequences along with 98 newly sequenced E2 genes between 2016 and 2020 in China within the context of global genetic diversity. The phylogenies revealed four distinct lineages of APPV, and interestingly, all lineages could be detected in China with the greatest diversity. Bayesian phylogenetic analyses showed that the E2 gene evolves at a mean rate of 1.22 × 10−3 (8.54 × 10−4-1.60 × 10−3) substitutions/site/year. The most recent common ancestor for APPVs is dated to 1886 (1837–1924) CE, somewhat earlier than the documented emergence of CT (1922 CE). Our phylogeographic analyses suggested that the APPV population possibly originated in the Netherlands, a country with developed livestock husbandry, and was introduced into China during the period 1837–2010. Guangdong, as a primary seeding population together with Central and Southwest China as epidemic linkers, was responsible for the dispersal of APPVs in China. The transmission pattern of “China lineages” (lineage 3 and lineage 4) presented a “south to north” movement tendency, which was likely associated with the implementation of strict environmental policy in China since 2000. Reconstruction of demographic history showed that APPV population size experienced multiple changes, which correlated well with the dynamic of the number of pigs in the past decades in China. Besides, positively selected pressure and geography-driven adaptation were supposed to be key factors for the diversification of APPV lineages. Our findings provide comprehensive insights into the diversity and spatiotemporal dynamic of APPV in China.
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Affiliation(s)
- Hailong Ma
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
| | - Wentao Li
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
| | - Mengjia Zhang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
| | - Zhengxin Yang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
| | - Lili Lin
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
| | - Ahmed H. Ghonaim
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
- Desert Research Center, Cairo, Egypt
| | - Qigai He
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
- Key Laboratory of Preventive Veterinary Medicine in Hubei Province, The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
- *Correspondence: Qigai He
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13
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Forni D, Cagliani R, Pozzoli U, Mozzi A, Arrigoni F, De Gioia L, Clerici M, Sironi M. Dating the Emergence of Human Endemic Coronaviruses. Viruses 2022; 14:v14051095. [PMID: 35632836 PMCID: PMC9148137 DOI: 10.3390/v14051095] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 01/09/2023] Open
Abstract
Four endemic coronaviruses infect humans and cause mild symptoms. Because previous analyses were based on a limited number of sequences and did not control for effects that affect molecular dating, we re-assessed the timing of endemic coronavirus emergence. After controlling for recombination, selective pressure, and molecular clock model, we obtained similar tMRCA (time to the most recent common ancestor) estimates for the four coronaviruses, ranging from 72 (HCoV-229E) to 54 (HCoV-NL63) years ago. The split times of HCoV-229E and HCoV-OC43 from camel alphacoronavirus and bovine coronavirus were dated ~268 and ~99 years ago. The split times of HCoV-HKU1 and HCoV-NL63 could not be calculated, as their zoonoticic sources are unknown. To compare the timing of coronavirus emergence to that of another respiratory virus, we recorded the occurrence of influenza pandemics since 1500. Although there is no clear relationship between pandemic occurrence and human population size, the frequency of influenza pandemics seems to intensify starting around 1700, which corresponds with the initial phase of exponential increase of human population and to the emergence of HCoV-229E. The frequency of flu pandemics in the 19th century also suggests that the concurrence of HCoV-OC43 emergence and the Russian flu pandemic may be due to chance.
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Affiliation(s)
- Diego Forni
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (U.P.); (A.M.); (M.S.)
- Correspondence:
| | - Rachele Cagliani
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (U.P.); (A.M.); (M.S.)
| | - Uberto Pozzoli
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (U.P.); (A.M.); (M.S.)
| | - Alessandra Mozzi
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (U.P.); (A.M.); (M.S.)
| | - Federica Arrigoni
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, 20126 Milan, Italy; (F.A.); (L.D.G.)
| | - Luca De Gioia
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, 20126 Milan, Italy; (F.A.); (L.D.G.)
| | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, 20122 Milan, Italy;
- Don Carlo Gnocchi Foundation ONLUS, IRCCS, 20148 Milan, Italy
| | - Manuela Sironi
- Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy; (R.C.); (U.P.); (A.M.); (M.S.)
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14
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Shen ZJ, Jia H, Xie CD, Shagainar J, Feng Z, Zhang X, Li K, Zhou R. Bayesian Phylodynamic Analysis Reveals the Dispersal Patterns of African Swine Fever Virus. Viruses 2022; 14:v14050889. [PMID: 35632631 PMCID: PMC9147906 DOI: 10.3390/v14050889] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 04/01/2022] [Accepted: 04/05/2022] [Indexed: 02/07/2023] Open
Abstract
The evolutionary and demographic history of African swine fever virus (ASFV) is potentially quite valuable for developing efficient and sustainable management strategies. In this study, we performed phylogenetic, phylodynamic, and phylogeographic analyses of worldwide ASFV based on complete ASFV genomes, B646L gene, and E183L gene sequences obtained from NCBI to understand the epidemiology of ASFV. Bayesian phylodynamic analysis and phylogenetic analysis showed highly similar results of group clustering between E183L and the complete genome. The evidence of migration and the demographic history of ASFV were also revealed by the Bayesian phylodynamic analysis. The evolutionary rate was estimated to be 1.14 × 10−5 substitution/site/year. The large out-migration from the viral population in South Africa played a crucial role in spreading the virus worldwide. Our study not only provides resources for the better utilization of genomic data but also reveals the comprehensive worldwide evolutionary history of ASFV with a broad sampling window across ~70 years. The characteristics of the virus spatiotemporal transmission are also elucidated, which could be of great importance for devising strategies to control the virus.
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Affiliation(s)
- Zhao-Ji Shen
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (Z.-J.S.); (H.J.); (C.-D.X.); (J.S.)
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, College of Life Science and Engineering, Foshan University, Foshan 528231, China;
| | - Hong Jia
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (Z.-J.S.); (H.J.); (C.-D.X.); (J.S.)
| | - Chun-Di Xie
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (Z.-J.S.); (H.J.); (C.-D.X.); (J.S.)
| | - Jurmt Shagainar
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (Z.-J.S.); (H.J.); (C.-D.X.); (J.S.)
| | - Zheng Feng
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, College of Life Science and Engineering, Foshan University, Foshan 528231, China;
| | - Xiaodong Zhang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China;
| | - Kui Li
- Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Correspondence: (K.L.); (R.Z.)
| | - Rong Zhou
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (Z.-J.S.); (H.J.); (C.-D.X.); (J.S.)
- Correspondence: (K.L.); (R.Z.)
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15
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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] [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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16
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Zou G, Matuszewska M, Jia M, Zhou J, Ba X, Duan J, Zhang C, Zhao J, Tao M, Fan J, Zhang X, Jin W, Cui T, Zeng X, Jia M, Qian X, Huang C, Zhuo W, Yao Z, Zhang L, Li S, Li L, Huang Q, Wu B, Chen H, Tucker AW, Grant AJ, Holmes MA, Zhou R. A Survey of Chinese Pig Farms and Human Healthcare Isolates Reveals Separate Human and Animal Methicillin-Resistant Staphylococcus aureus Populations. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2103388. [PMID: 34894204 PMCID: PMC8811834 DOI: 10.1002/advs.202103388] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/10/2021] [Indexed: 06/14/2023]
Abstract
There has been increasing concern that the overuse of antibiotics in livestock farming is contributing to the burden of antimicrobial resistance in people. Farmed animals in Europe and North America, particularly pigs, provide a reservoir for livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA ST398 lineage) found in people. This study is designed to investigate the contribution of MRSA from Chinese pig farms to human infection. A collection of 483 MRSA are isolated from 55 farms and 4 hospitals in central China, a high pig farming density area. CC9 MRSA accounts for 97.2% of all farm isolates, but is not present in hospital isolates. ST398 isolates are found on farms and hospitals, but none of them formed part of the "LA-MRSA ST398 lineage" present in Europe and North America. The hospital ST398 MRSA isolate form a clade that is clearly separate from the farm ST398 isolates. Despite the presence of high levels of MRSA found on Chinese pig farms, the authors find no evidence of them spilling over to the human population. Nevertheless, the ST398 MRSA obtained from hospitals appear to be part of a widely distributed lineage in China. The new animal-adapted ST398 lineage that has emerged in China is of concern.
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Affiliation(s)
- Geng Zou
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Marta Matuszewska
- Department of Veterinary MedicineUniversity of CambridgeCambridgeCB3 0ESUK
| | - Ming Jia
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Jianwei Zhou
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Xiaoliang Ba
- Department of Veterinary MedicineUniversity of CambridgeCambridgeCB3 0ESUK
| | - Juan Duan
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | | | - Jian Zhao
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Meng Tao
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Jingyan Fan
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | | | | | | | | | - Min Jia
- Wuhan First HospitalWuhan430014China
| | | | - Chao Huang
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Wenxiao Zhuo
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Zhiming Yao
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Lijun Zhang
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Shaowen Li
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
| | - Lu Li
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
- Cooperative Innovation Center of Sustainable Pig ProductionWuhan430070China
- International Research Center for Animal Diseases (MOST)Wuhan430070China
| | - Qi Huang
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
- Cooperative Innovation Center of Sustainable Pig ProductionWuhan430070China
- International Research Center for Animal Diseases (MOST)Wuhan430070China
| | - Bin Wu
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
- Cooperative Innovation Center of Sustainable Pig ProductionWuhan430070China
- International Research Center for Animal Diseases (MOST)Wuhan430070China
| | - Huanchun Chen
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
- Cooperative Innovation Center of Sustainable Pig ProductionWuhan430070China
- International Research Center for Animal Diseases (MOST)Wuhan430070China
| | | | - Andrew J. Grant
- Department of Veterinary MedicineUniversity of CambridgeCambridgeCB3 0ESUK
| | - Mark A. Holmes
- Department of Veterinary MedicineUniversity of CambridgeCambridgeCB3 0ESUK
| | - Rui Zhou
- State Key Laboratory of Agricultural MicrobiologyHuazhong Agricultural University College of Veterinary MedicineWuhan430070China
- Cooperative Innovation Center of Sustainable Pig ProductionWuhan430070China
- International Research Center for Animal Diseases (MOST)Wuhan430070China
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17
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Unterman A, Sumida TS, Nouri N, Yan X, Zhao AY, Gasque V, Schupp JC, Asashima H, Liu Y, Cosme C, Deng W, Chen M, Raredon MSB, Hoehn KB, Wang G, Wang Z, DeIuliis G, Ravindra NG, Li N, Castaldi C, Wong P, Fournier J, Bermejo S, Sharma L, Casanovas-Massana A, Vogels CBF, Wyllie AL, Grubaugh ND, Melillo A, Meng H, Stein Y, Minasyan M, Mohanty S, Ruff WE, Cohen I, Raddassi K, Niklason LE, Ko AI, Montgomery RR, Farhadian SF, Iwasaki A, Shaw AC, van Dijk D, Zhao H, Kleinstein SH, Hafler DA, Kaminski N, Dela Cruz CS. Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nat Commun 2022; 13:440. [PMID: 35064122 PMCID: PMC8782894 DOI: 10.1038/s41467-021-27716-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 12/03/2021] [Indexed: 02/06/2023] Open
Abstract
Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100Ahi/HLA-DRlo classical monocytes and activated LAG-3hi T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8+ clones, unmutated IGHG+ B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.
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MESH Headings
- Adaptive Immunity/drug effects
- Adaptive Immunity/genetics
- Adaptive Immunity/immunology
- Aged
- Antibodies, Monoclonal, Humanized/therapeutic use
- CD4-Positive T-Lymphocytes/drug effects
- CD4-Positive T-Lymphocytes/immunology
- CD4-Positive T-Lymphocytes/metabolism
- CD8-Positive T-Lymphocytes/drug effects
- CD8-Positive T-Lymphocytes/immunology
- CD8-Positive T-Lymphocytes/metabolism
- COVID-19/genetics
- COVID-19/immunology
- Cells, Cultured
- Female
- Gene Expression Profiling/methods
- Gene Expression Regulation/drug effects
- Gene Expression Regulation/immunology
- Humans
- Immunity, Innate/drug effects
- Immunity, Innate/genetics
- Immunity, Innate/immunology
- Male
- RNA-Seq/methods
- Receptors, Antigen, B-Cell/genetics
- Receptors, Antigen, B-Cell/immunology
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/immunology
- SARS-CoV-2/drug effects
- SARS-CoV-2/immunology
- SARS-CoV-2/physiology
- Single-Cell Analysis/methods
- COVID-19 Drug Treatment
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Affiliation(s)
- Avraham Unterman
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA.
- Pulmonary Institute, Tel Aviv Sourasky Medical Center, Tel Aviv University, Tel Aviv, Israel.
| | - Tomokazu S Sumida
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA.
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA.
| | - Nima Nouri
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
- Center for Medical Informatics, Yale School of Medicine, New Haven, CT, USA
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Xiting Yan
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Amy Y Zhao
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Victor Gasque
- Department of Computer Science, Yale University, New Haven, CT, USA
- Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Jonas C Schupp
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
- Department of Respiratory Medicine, Hannover Medical School and Biomedical Research in End-stage and Obstructive Lung Disease Hannover, German Lung Research Center (DZL), Hannover, Germany
| | - Hiromitsu Asashima
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Yunqing Liu
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Carlos Cosme
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Wenxuan Deng
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Ming Chen
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Micha Sam Brickman Raredon
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Medical Scientist Training Program, Yale School of Medicine, New Haven, CT, USA
| | - Kenneth B Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Guilin Wang
- Yale Center for Genome Analysis/Keck Biotechnology Resource Laboratory, Department of Molecular Biophysics and Biochemistry, Yale School of Medicine, New Haven, CT, USA
| | - Zuoheng Wang
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Giuseppe DeIuliis
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Neal G Ravindra
- Department of Computer Science, Yale University, New Haven, CT, USA
- Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Ningshan Li
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
- SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | | | - Patrick Wong
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - John Fournier
- School of Medicine, Yale University, New Haven, CT, USA
| | - Santos Bermejo
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Lokesh Sharma
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Arnau Casanovas-Massana
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Chantal B F Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Anne L Wyllie
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Anthony Melillo
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Hailong Meng
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Yan Stein
- Pulmonary Institute, Tel Aviv Sourasky Medical Center, Tel Aviv University, Tel Aviv, Israel
| | - Maksym Minasyan
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Subhasis Mohanty
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - William E Ruff
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Inessa Cohen
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Khadir Raddassi
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Laura E Niklason
- Departments of Anesthesiology & Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Albert I Ko
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Ruth R Montgomery
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Shelli F Farhadian
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Akiko Iwasaki
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Albert C Shaw
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - David van Dijk
- Department of Computer Science, Yale University, New Haven, CT, USA
- Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
- Inter-Departmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Steven H Kleinstein
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
- Inter-Departmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - David A Hafler
- Department of Neurology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Immunobiology, School of Medicine, Yale University, New Haven, CT, USA
| | - Naftali Kaminski
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Charles S Dela Cruz
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
- West Haven Veterans Affair Medical Center, West Haven, CT, USA
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18
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OUP accepted manuscript. J Antimicrob Chemother 2022; 77:910-920. [DOI: 10.1093/jac/dkac011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/26/2021] [Indexed: 11/13/2022] Open
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19
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Torres Ortiz A, Coronel J, Vidal JR, Bonilla C, Moore DAJ, Gilman RH, Balloux F, Kon OM, Didelot X, Grandjean L. Genomic signatures of pre-resistance in Mycobacterium tuberculosis. Nat Commun 2021; 12:7312. [PMID: 34911948 PMCID: PMC8674244 DOI: 10.1038/s41467-021-27616-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 11/29/2021] [Indexed: 11/29/2022] Open
Abstract
Recent advances in bacterial whole-genome sequencing have resulted in a comprehensive catalog of antibiotic resistance genomic signatures in Mycobacterium tuberculosis. With a view to pre-empt the emergence of resistance, we hypothesized that pre-existing polymorphisms in susceptible genotypes (pre-resistance mutations) could increase the risk of becoming resistant in the future. We sequenced whole genomes from 3135 isolates sampled over a 17-year period. After reconstructing ancestral genomes on time-calibrated phylogenetic trees, we developed and applied a genome-wide survival analysis to determine the hazard of resistance acquisition. We demonstrate that M. tuberculosis lineage 2 has a higher risk of acquiring resistance than lineage 4, and estimate a higher hazard of rifampicin resistance evolution following isoniazid mono-resistance. Furthermore, we describe loci and genomic polymorphisms associated with a higher risk of resistance acquisition. Identifying markers of future antibiotic resistance could enable targeted therapy to prevent resistance emergence in M. tuberculosis and other pathogens.
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Affiliation(s)
- Arturo Torres Ortiz
- grid.7445.20000 0001 2113 8111Imperial College London, Department of Infectious Diseases, London, UK
| | - Jorge Coronel
- grid.11100.310000 0001 0673 9488Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Julia Rios Vidal
- grid.419858.90000 0004 0371 3700Unidad Técnica de Tuberculosis MDR, Ministerio de Salud, Lima, Perú
| | - Cesar Bonilla
- grid.419858.90000 0004 0371 3700Unidad Técnica de Tuberculosis MDR, Ministerio de Salud, Lima, Perú ,grid.441740.20000 0004 0542 2122Universidad Privada San Juan Bautista, Lima, Perú
| | - David A. J. Moore
- grid.8991.90000 0004 0425 469XLondon School of Hygiene and Tropical Medicine, London, UK
| | - Robert H. Gilman
- grid.21107.350000 0001 2171 9311Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | | | - Onn Min Kon
- grid.7445.20000 0001 2113 8111Respiratory Medicine, National Heart and Lung Institute, Imperial College London, London, UK
| | - Xavier Didelot
- grid.7372.10000 0000 8809 1613University of Warwick, School of Life Sciences and Department of Statistics, Warwick, UK
| | - Louis Grandjean
- Imperial College London, Department of Infectious Diseases, London, UK. .,UCL Department of Infection, Institute of Child Health, London, UK.
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20
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Hoehn KB, Turner JS, Miller FI, Jiang R, Pybus OG, Ellebedy AH, Kleinstein SH. Human B cell lineages associated with germinal centers following influenza vaccination are measurably evolving. eLife 2021; 10:e70873. [PMID: 34787567 PMCID: PMC8741214 DOI: 10.7554/elife.70873] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 11/11/2021] [Indexed: 11/23/2022] Open
Abstract
The poor efficacy of seasonal influenza virus vaccines is often attributed to pre-existing immunity interfering with the persistence and maturation of vaccine-induced B cell responses. We previously showed that a subset of vaccine-induced B cell lineages are recruited into germinal centers (GCs) following vaccination, suggesting that affinity maturation of these lineages against vaccine antigens can occur. However, it remains to be determined whether seasonal influenza vaccination stimulates additional evolution of vaccine-specific lineages, and previous work has found no significant increase in somatic hypermutation among influenza-binding lineages sampled from the blood following seasonal vaccination in humans. Here, we investigate this issue using a phylogenetic test of measurable immunoglobulin sequence evolution. We first validate this test through simulations and survey measurable evolution across multiple conditions. We find significant heterogeneity in measurable B cell evolution across conditions, with enrichment in primary response conditions such as HIV infection and early childhood development. We then show that measurable evolution following influenza vaccination is highly compartmentalized: while lineages in the blood are rarely measurably evolving following influenza vaccination, lineages containing GC B cells are frequently measurably evolving. Many of these lineages appear to derive from memory B cells. We conclude from these findings that seasonal influenza virus vaccination can stimulate additional evolution of responding B cell lineages, and imply that the poor efficacy of seasonal influenza vaccination is not due to a complete inhibition of vaccine-specific B cell evolution.
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Affiliation(s)
- Kenneth B Hoehn
- Department of Pathology, Yale School of MedicineNew HavenUnited States
| | - Jackson S Turner
- Department of Pathology and Immunology, Washington University School of MedicineSt LouisUnited States
| | | | - Ruoyi Jiang
- Department of Immunobiology, Yale School of MedicineNew HavenUnited States
| | - Oliver G Pybus
- Department of Zoology, University of OxfordOxfordUnited Kingdom
| | - Ali H Ellebedy
- Department of Pathology and Immunology, Washington University School of MedicineSt LouisUnited States
- The Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of MedicineSt LouisUnited States
| | - Steven H Kleinstein
- Department of Pathology, Yale School of MedicineNew HavenUnited States
- Department of Immunobiology, Yale School of MedicineNew HavenUnited States
- Interdepartmental Program in Computational Biology & Bioinformatics, Yale UniversityNew HavenUnited States
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21
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Rieux A, Campos P, Duvermy A, Scussel S, Martin D, Gaudeul M, Lefeuvre P, Becker N, Lett JM. Contribution of historical herbarium small RNAs to the reconstruction of a cassava mosaic geminivirus evolutionary history. Sci Rep 2021; 11:21280. [PMID: 34711837 PMCID: PMC8553777 DOI: 10.1038/s41598-021-00518-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 10/13/2021] [Indexed: 12/30/2022] Open
Abstract
Emerging viral diseases of plants are recognised as a growing threat to global food security. However, little is known about the evolutionary processes and ecological factors underlying the emergence and success of viruses that have caused past epidemics. With technological advances in the field of ancient genomics, it is now possible to sequence historical genomes to provide a better understanding of viral plant disease emergence and pathogen evolutionary history. In this context, herbarium specimens represent a valuable source of dated and preserved material. We report here the first historical genome of a crop pathogen DNA virus, a 90-year-old African cassava mosaic virus (ACMV), reconstructed from small RNA sequences bearing hallmarks of small interfering RNAs. Relative to tip-calibrated dating inferences using only modern data, those performed with the historical genome yielded both molecular evolution rate estimates that were significantly lower, and lineage divergence times that were significantly older. Crucially, divergence times estimated without the historical genome appeared in discordance with both historical disease reports and the existence of the historical genome itself. In conclusion, our study reports an updated time-frame for the history and evolution of ACMV and illustrates how the study of crop viral diseases could benefit from natural history collections.
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Affiliation(s)
- Adrien Rieux
- CIRAD, UMR PVBMT, 97410, St Pierre, La Réunion, France.
| | - Paola Campos
- CIRAD, UMR PVBMT, 97410, St Pierre, La Réunion, France
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 Rue Cuvier, CP 50, 75005, Paris, France
| | | | - Sarah Scussel
- CIRAD, UMR PVBMT, 97410, St Pierre, La Réunion, France
| | - Darren Martin
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Observatory, Cape Town, South Africa
| | - Myriam Gaudeul
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 Rue Cuvier, CP 50, 75005, Paris, France
- Herbier national (P), Muséum national d'Histoire Naturelle, CP39, 57 Rue Cuvier, 75005, Paris, France
| | | | - Nathalie Becker
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, 57 Rue Cuvier, CP 50, 75005, Paris, France
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22
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Forni D, Cagliani R, Arrigoni F, Benvenuti M, Mozzi A, Pozzoli U, Clerici M, De Gioia L, Sironi M. Adaptation of the endemic coronaviruses HCoV-OC43 and HCoV-229E to the human host. Virus Evol 2021; 7:veab061. [PMID: 34527284 PMCID: PMC8344746 DOI: 10.1093/ve/veab061] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/18/2021] [Accepted: 06/23/2021] [Indexed: 12/29/2022] Open
Abstract
Four coronaviruses (HCoV-OC43, HCoV-HKU1, HCoV-NL63, and HCoV-229E) are endemic in human populations. All these viruses are seasonal and generate short-term immunity. Like the highly pathogenic coronaviruses, the endemic coronaviruses have zoonotic origins. Thus, understanding the evolutionary dynamics of these human viruses might provide insight into the future trajectories of SARS-CoV-2 evolution. Because the zoonotic sources of HCoV-OC43 and HCoV-229E are known, we applied a population genetics-phylogenetic approach to investigate which selective events accompanied the divergence of these viruses from the animal ones. Results indicated that positive selection drove the evolution of some accessory proteins, as well as of the membrane proteins. However, the spike proteins of both viruses and the hemagglutinin-esterase (HE) of HCoV-OC43 represented the major selection targets. Specifically, for both viruses, most positively selected sites map to the receptor-binding domains (RBDs) and are polymorphic. Molecular dating for the HCoV-229E spike protein indicated that RBD Classes I, II, III, and IV emerged 3-9 years apart. However, since the appearance of Class V (with much higher binding affinity), around 25 years ago, limited genetic diversity accumulated in the RBD. These different time intervals are not fully consistent with the hypothesis that HCoV-229E spike evolution was driven by antigenic drift. An alternative, not mutually exclusive possibility is that strains with higher affinity for the cellular receptor have out-competed strains with lower affinity. The evolution of the HCoV-OC43 spike protein was also suggested to undergo antigenic drift. However, we also found abundant signals of positive selection in HE. Whereas such signals might result from antigenic drift, as well, previous data showing co-evolution of the spike protein with HE suggest that optimization for human cell infection also drove the evolution of this virus. These data provide insight into the possible trajectories of SARS-CoV-2 evolution, especially in case the virus should become endemic.
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Affiliation(s)
- Diego Forni
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, via don Luigi Monza, 23843 Bosisio Parini, Italy
| | - Rachele Cagliani
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, via don Luigi Monza, 23843 Bosisio Parini, Italy
| | - Federica Arrigoni
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, Piazza della Scienza, Milan 20126, Italy
| | - Martino Benvenuti
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, Piazza della Scienza, Milan 20126, Italy
| | - Alessandra Mozzi
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, via don Luigi Monza, 23843 Bosisio Parini, Italy
| | - Uberto Pozzoli
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, via don Luigi Monza, 23843 Bosisio Parini, Italy
| | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, via Francesco Sforza, Milan 20122, Italy
| | - Luca De Gioia
- Department of Biotechnology and Biosciences, University of Milan-Bicocca, Piazza della Scienza, Milan 20126, Italy
| | - Manuela Sironi
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, via don Luigi Monza, 23843 Bosisio Parini, Italy
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23
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Issaka S, Traoré O, Longué RDS, Pinel-Galzi A, Gill MS, Dellicour S, Bastide P, Guindon S, Hébrard E, Dugué MJ, Séré Y, Semballa S, Aké S, Lemey P, Fargette D. Rivers and landscape ecology of a plant virus, Rice yellow mottle virus along the Niger Valley. Virus Evol 2021; 7:veab072. [PMID: 36819970 PMCID: PMC9927878 DOI: 10.1093/ve/veab072] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 08/08/2021] [Accepted: 08/16/2021] [Indexed: 11/14/2022] Open
Abstract
To investigate the spread of Rice yellow mottle virus (RYMV) along the Niger River, regular sampling of virus isolates was conducted along 500 km of the Niger Valley in the Republic of Niger and was complemented by additional sampling in neighbouring countries in West Africa and Central Africa. The spread of RYMV into and within the Republic of Niger was inferred as a continuous process using a Bayesian statistical framework applied previously to reconstruct its dispersal history in West Africa, East Africa, and Madagascar. The spatial resolution along this section of the Niger River was the highest implemented for RYMV and possibly for any plant virus. We benefited from the results of early field surveys of the disease for the validation of the phylogeographic reconstruction and from the well-documented history of rice cultivation changes along the Niger River for their interpretation. As a prerequisite, the temporal signal of the RYMV data sets was revisited in the light of recent methodological advances. The role of the hydrographic network of the Niger Basin in RYMV spread was examined, and the link between virus population dynamics and the extent of irrigated rice was assessed. RYMV was introduced along the Niger River in the Republic of Niger in the early 1980s from areas to the southwest of the country where rice was increasingly grown. Viral spread was triggered by a major irrigation scheme made of a set of rice perimeters along the river valley. The subsequent spatial and temporal host continuity and the inoculum build-up allowed for a rapid spread of RYMV along the Niger River, upstream and downstream, over hundreds of kilometres, and led to the development of severe epidemics. There was no evidence of long-distance dissemination of the virus through natural water. Floating rice in the main meanders of the Middle Niger did not contribute to virus dispersal from West Africa to Central Africa. RYMV along the Niger River is an insightful example of how agricultural intensification favours pathogen emergence and spread.
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Affiliation(s)
| | - Oumar Traoré
- Laboratoire de Virologie et de Biotechnologie Végétale (LVBV), Laboratoire National de Biosécurité, Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou 01 BP 476, Burkina Faso
| | - Régis Dimitri Skopé Longué
- Laboratoire des Sciences Biologiques et Agronomiques pour le Développement (LaSBAD), Département des Sciences de la Vie, Université de Bangui, Bangui BP 908, République Centrafricaine
| | - Agnès Pinel-Galzi
- PHIM Plant Health Institute, Université de Montpellier, IRD, CIRAD, INRAE, Institut Agro., Montpellier cedex 5 BP 64501 34394, France
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, Leuven 3000, Belgium
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, Leuven 3000, Belgium,Spatial Epidemiology Lab. (SpELL), Université Libre de Bruxelles, CP160/12, 50, av. FD Roosevelt, Bruxelles 1050, Belgium
| | - Paul Bastide
- IMAG – UMR 5149, Université de Montpellier, Case courrier 051, Place Eugène Bataillon, Montpellier 34090, France
| | - Stéphane Guindon
- Department of Computer Science, LIRMM, CNRS and Université de Montpellier, Montpellier, France
| | - Eugénie Hébrard
- PHIM Plant Health Institute, Université de Montpellier, IRD, CIRAD, INRAE, Institut Agro., Montpellier cedex 5 BP 64501 34394, France
| | - Marie-Jo Dugué
- Agronomy and Farming Systems, 3 avenue des Cistes, Saint Mathieu de Tréviers 34270, France
| | - Yacouba Séré
- Agricultural Research and Development, Bobo-Dioulasso BP 1324, Burkina Faso
| | - Silla Semballa
- Laboratoire des Sciences Biologiques et Agronomiques pour le Développement (LaSBAD), Département des Sciences de la Vie, Université de Bangui, Bangui BP 908, République Centrafricaine
| | - Séverin Aké
- UFR Biosciences, Laboratoire de Physiologie Végétale, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire
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24
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Accounting for the Biological Complexity of Pathogenic Fungi in Phylogenetic Dating. J Fungi (Basel) 2021; 7:jof7080661. [PMID: 34436200 PMCID: PMC8400180 DOI: 10.3390/jof7080661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 11/17/2022] Open
Abstract
In the study of pathogen evolution, temporal dating of phylogenies provides information on when species and lineages may have diverged in the past. When combined with spatial and epidemiological data in phylodynamic models, these dated phylogenies can also help infer where and when outbreaks occurred, how pathogens may have spread to new geographic locations and/or niches, and how virulence or drug resistance has developed over time. Although widely applied to viruses and, increasingly, to bacterial pathogen outbreaks, phylogenetic dating is yet to be widely used in the study of pathogenic fungi. Fungi are complex organisms with several biological processes that could present issues with appropriate inference of phylogenies, clock rates, and divergence times, including high levels of recombination and slower mutation rates although with potentially high levels of mutation rate variation. Here, we discuss some of the key methodological challenges in accurate phylogeny reconstruction for fungi in the context of the temporal analyses conducted to date and make recommendations for future dating studies to aid development of a best practices roadmap in light of the increasing threat of fungal outbreaks and antifungal drug resistance worldwide.
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25
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Seth-Smith HMB, Bénard A, Bruisten SM, Versteeg B, Herrmann B, Kok J, Carter I, Peuchant O, Bébéar C, Lewis DA, Puerta T, Keše D, Balla E, Zákoucká H, Rob F, Morré SA, de Barbeyrac B, Galán JC, de Vries HJC, Thomson NR, Goldenberger D, Egli A. Ongoing evolution of Chlamydia trachomatis lymphogranuloma venereum: exploring the genomic diversity of circulating strains. Microb Genom 2021; 7. [PMID: 34184981 PMCID: PMC8461462 DOI: 10.1099/mgen.0.000599] [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] [Indexed: 11/18/2022] Open
Abstract
Lymphogranuloma venereum (LGV), the invasive infection of the sexually transmissible infection (STI) Chlamydia trachomatis, is caused by strains from the LGV biovar, most commonly represented by ompA-genotypes L2b and L2. We investigated the diversity in LGV samples across an international collection over seven years using typing and genome sequencing. LGV-positive samples (n=321) from eight countries collected between 2011 and 2017 (Spain n=97, Netherlands n=67, Switzerland n=64, Australia n=53, Sweden n=37, Hungary n=31, Czechia n=30, Slovenia n=10) were genotyped for pmpH and ompA variants. All were found to contain the 9 bp insertion in the pmpH gene, previously associated with ompA-genotype L2b. However, analysis of the ompA gene shows ompA-genotype L2b (n=83), ompA-genotype L2 (n=180) and several variants of these (n=52; 12 variant types), as well as other/mixed ompA-genotypes (n=6). To elucidate the genomic diversity, whole genome sequencing (WGS) was performed from selected samples using SureSelect target enrichment, resulting in 42 genomes, covering a diversity of ompA-genotypes and representing most of the countries sampled. A phylogeny of these data clearly shows that these ompA-genotypes derive from an ompA-genotype L2b ancestor, carrying up to eight SNPs per isolate. SNPs within ompA are overrepresented among genomic changes in these samples, each of which results in an amino acid change in the variable domains of OmpA (major outer membrane protein, MOMP). A reversion to ompA-genotype L2 with the L2b genomic backbone is commonly seen. The wide diversity of ompA-genotypes found in these recent LGV samples indicates that this gene is under immunological selection. Our results suggest that the ompA-genotype L2b genomic backbone is the dominant strain circulating and evolving particularly in men who have sex with men (MSM) populations.
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Affiliation(s)
- Helena M B Seth-Smith
- Clinical Bacteriology & Mycology, University Hospital Basel, University of Basel, Switzerland.,Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.,SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Angèle Bénard
- Present address: Healthcare Systems Research Group, VHIR, Universitat Autònoma de Barcelona, Passeig de la Vall d'Hebron 119-129, 08035 Barcelona, Spain.,Wellcome Trust Sanger Institute, Cambridge, UK
| | - Sylvia M Bruisten
- Department of Infectious Diseases, GGD Public Health Service of Amsterdam, Amsterdam, The Netherlands.,Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity (AII), Location Academic Medical Centre, Amsterdam, The Netherlands
| | - Bart Versteeg
- Department of Infectious Diseases, GGD Public Health Service of Amsterdam, Amsterdam, The Netherlands.,Clinical Research Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Björn Herrmann
- Section of Clinical Bacteriology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Jen Kok
- Centre for Infectious Diseases and Microbiology Laboratory Services, Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia.,Marie Bashir Institute for Infectious Diseases and Biosecurity & Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Ian Carter
- Centre for Infectious Diseases and Microbiology Laboratory Services, Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia
| | - Olivia Peuchant
- CHU Bordeaux, Department of Bacteriology, French National Reference Center for bacterial STIs, Bordeaux, France
| | - Cécile Bébéar
- CHU Bordeaux, Department of Bacteriology, French National Reference Center for bacterial STIs, Bordeaux, France
| | - David A Lewis
- Western Sydney Sexual Health Centre, Western Sydney Local Health District, Parramatta, New South Wales, Australia.,Marie Bashir Institute for Infectious Diseases and Biosecurity & Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Teresa Puerta
- Unidad de ITS/VIH, Centro Sanitario Sandoval, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
| | - Darja Keše
- University of Ljubljana, Faculty of Medicine, Institute of Microbiology and Immunology, Ljubljana, Slovenia
| | - Eszter Balla
- Bacterial STI Reference Laboratory, National Public Health Center (former National Center for Epidemiology), Budapest, Hungary
| | - Hana Zákoucká
- National Reference Laboratory for Diagnostics of Syphilis and Chlamydia Infections, National Institute of Public Health, Srobarova 48, 100 42, Prague 10, Czech Republic
| | - Filip Rob
- Department of Dermatovenereology, Second Faculty of Medicine, Charles University and Hospital Bulovka, Budinova 2, 180 81, Prague 8, Czech Republic
| | - Servaas A Morré
- Laboratory of Immunogenetics, Department of Medical Microbiology and Infection Control, VU University Medical Center Amsterdam, Amsterdam, The Netherlands.,Institute for Public Health Genomics (IPHG), Department of Genetics and Cell Biology, Research Institute GROW, University of Maastricht, Maastricht, The Netherlands
| | - Bertille de Barbeyrac
- CHU Bordeaux, Department of Bacteriology, French National Reference Center for bacterial STIs, Bordeaux, France
| | - Juan Carlos Galán
- Servicio de Microbiología, Hospital Universitario Ramón y Cajal. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain. CIBER en Epidemiología y Salud Pública (CIBERESP)
| | - Henry J C de Vries
- Department of Infectious Diseases, GGD Public Health Service of Amsterdam, Amsterdam, The Netherlands.,Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity (AII), Location Academic Medical Centre, Amsterdam, The Netherlands
| | - Nicholas R Thomson
- Wellcome Trust Sanger Institute, Cambridge, UK.,Clinical Research Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Daniel Goldenberger
- Clinical Bacteriology & Mycology, University Hospital Basel, University of Basel, Switzerland
| | - Adrian Egli
- Clinical Bacteriology & Mycology, University Hospital Basel, University of Basel, Switzerland.,Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland
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26
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Jara M, Crespo R, Roberts DL, Chapman A, Banda A, Machado G. Development of a Dissemination Platform for Spatiotemporal and Phylogenetic Analysis of Avian Infectious Bronchitis Virus. Front Vet Sci 2021; 8:624233. [PMID: 34017870 PMCID: PMC8129014 DOI: 10.3389/fvets.2021.624233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/27/2021] [Indexed: 11/13/2022] Open
Abstract
Infecting large portions of the global poultry populations, the avian infectious bronchitis virus (IBV) remains a major economic burden in North America. With more than 30 serotypes globally distributed, Arkansas, Connecticut, Delaware, Georgia, and Massachusetts are among the most predominant serotypes in the United States. Even though vaccination is widely used, the high mutation rate exhibited by IBV is continuously triggering the emergence of new viral strains and hindering control and prevention measures. For that reason, targeted strategies based on constantly updated information on the IBV circulation are necessary. Here, we sampled IBV-infected farms from one US state and collected and analyzed 65 genetic sequences coming from three different lineages along with the immunization information of each sampled farm. Phylodynamic analyses showed that IBV dispersal velocity was 12.3 km/year. The majority of IBV infections appeared to have derived from the introduction of the Arkansas DPI serotype, and the Arkansas DPI and Georgia 13 were the predominant serotypes. When analyzed against IBV sequences collected across the United States and deposited in the GenBank database, the most likely viral origin of our sequences was from the states of Alabama, Georgia, and Delaware. Information about vaccination showed that the MILDVAC-MASS+ARK vaccine was applied on 26% of the farms. Using a publicly accessible open-source tool for real-time interactive tracking of pathogen spread and evolution, we analyzed the spatiotemporal spread of IBV and developed an online reporting dashboard. Overall, our work demonstrates how the combination of genetic and spatial information could be used to track the spread and evolution of poultry diseases, providing timely information to the industry. Our results could allow producers and veterinarians to monitor in near-real time the current IBV strain circulating, making it more informative, for example, in vaccination-related decisions.
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Affiliation(s)
- Manuel Jara
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, United States
| | - Rocio Crespo
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, United States
| | - David L Roberts
- Department of Computer Science North Carolina State University, Raleigh, NC, United States
| | - Ashlyn Chapman
- Department of Computer Science North Carolina State University, Raleigh, NC, United States
| | - Alejandro Banda
- Poultry Research and Diagnostic Laboratory, College of Veterinary Medicine, Mississippi State University, Pearl, MS, United States
| | - Gustavo Machado
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, United States
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27
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Pontremoli C, Forni D, Clerici M, Cagliani R, Sironi M. Alternation between taxonomically divergent hosts is not the major determinant of flavivirus evolution. Virus Evol 2021; 7:veab040. [PMID: 33976907 PMCID: PMC8093920 DOI: 10.1093/ve/veab040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Flaviviruses display diverse epidemiological and ecological features. Tick-borne and mosquito-borne flaviviruses (TBFV and MBFV, respectively) are important human pathogens that alternate replication in invertebrate vectors and vertebrate hosts. The Flavivirus genus also includes insect-specific viruses (ISFVs) and viruses with unknown invertebrate hosts. It is generally accepted that viruses that alternate between taxonomically different hosts evolve slowly and that the evolution of MBFVs and TBFVs is dominated by strong constraints, with limited episodes of positive selection. We exploited the availability of flavivirus genomes to test these hypotheses and to compare their rates and patterns of evolution. We estimated the substitution rates of CFAV and CxFV (two ISFVs) and, by taking into account the time-frame of measurement, compared them with those of other flaviviruses. Results indicated that CFAV and CxFV display relatively different substitution rates. However, these data, together with estimates for single-host members of the Flaviviridae family, indicated that MBFVs do not display relatively slower evolution. Conversely, TBFVs displayed some of lowest substitution rates among flaviviruses. Analysis of selective patterns over longer evolutionary time-frames confirmed that MBFVs evolve under strong purifying selection. Interestingly, TBFVs and ISFVs did not show extremely different levels of constraint, although TBFVs alternate among hosts, whereas ISFVs do not. Additional results showed that episodic positive selection drove the evolution of MBFVs, despite their high constraint. Positive selection was also detected on two branches of the TBFVs phylogeny that define the seabird clade. Thus, positive selection was much more common during the evolution of arthropod-borne flaviviruses than previously thought. Overall, our data indicate that flavivirus evolutionary patterns are complex and most likely determined by multiple factors, not limited to the alternation between taxonomically divergent hosts. The frequency of both positive and purifying selection, especially in MBFVs, suggests that a minority of sites in the viral polyprotein experience weak constraint and can evolve to generate new viral phenotypes and possibly promote adaptation to new hosts.
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Affiliation(s)
| | - Diego Forni
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
| | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, Milan 20122, Italy,Don C. Gnocchi Foundation ONLUS, IRCCS, Milan 20121, Italy
| | - Rachele Cagliani
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
| | - Manuela Sironi
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
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28
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Duchene S, Lemey P, Stadler T, Ho SYW, Duchene DA, Dhanasekaran V, Baele G. Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations. Mol Biol Evol 2021; 37:3363-3379. [PMID: 32895707 PMCID: PMC7454806 DOI: 10.1093/molbev/msaa163] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here, we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behavior of this classification in analyses of five empirical data sets: modern samples of A/H1N1 influenza virus, the bacterium Bordetella pertussis, coronaviruses from mammalian hosts, ancient DNA from Hepatitis B virus, and mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.
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Affiliation(s)
- Sebastian Duchene
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Zürich, Switzerland
| | - Simon Y W Ho
- Swiss Institute of Bioinformatics, Basel, Switzerland.,School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia
| | - David A Duchene
- Research School of Biology, Australian National University, Canberra, ACT, Australia
| | - Vijaykrishna Dhanasekaran
- Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
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29
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Forni D, Pontremoli C, Clerici M, Pozzoli U, Cagliani R, Sironi M. Recent Out-of-Africa Migration of Human Herpes Simplex Viruses. Mol Biol Evol 2021; 37:1259-1271. [PMID: 31917410 DOI: 10.1093/molbev/msaa001] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Herpes simplex virus types 1 and 2 (HSV-1 and HSV-2) are ubiquitous human pathogens. Both viruses evolved from simplex viruses infecting African primates and they are thus thought to have left Africa during early human migrations. We analyzed the population structure of HSV-1 and HSV-2 circulating strains. Results indicated that HSV-1 populations have limited geographic structure and the most evident clustering by geography is likely due to recent bottlenecks. For HSV-2, the only level of population structure is accounted for by the so-called "worldwide" and "African" lineages. Analysis of ancestry components and nucleotide diversity, however, did not support the view that the worldwide lineage followed early humans during out-of-Africa dispersal. Although phylogeographic analysis confirmed an African origin for both viruses, molecular dating with a method that corrects for the time-dependent rate phenomenon indicated that HSV-1 and HSV-2 migrated from Africa in relatively recent times. In particular, we estimated that the HSV-2 worldwide lineage left the continent in the 18th century, which corresponds to the height of the transatlantic slave trade, possibly explaining the high prevalence of HSV-2 in the Americas (second highest after Africa). The limited geographic clustering of HSV-1 makes it difficult to date its exit from Africa. The split between the basal clade, containing mostly African sequences, and all other strains was dated at ∼5,000 years ago. Our data do not imply that herpes simplex viruses did not infect early humans but show that the worldwide distribution of circulating strains is the result of relatively recent events.
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Affiliation(s)
- Diego Forni
- Scientific Institute, IRCCS E. MEDEA, Bioinformatics, Lecco, Italy
| | | | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, Milan, Italy.,IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Uberto Pozzoli
- Scientific Institute, IRCCS E. MEDEA, Bioinformatics, Lecco, Italy
| | - Rachele Cagliani
- Scientific Institute, IRCCS E. MEDEA, Bioinformatics, Lecco, Italy
| | - Manuela Sironi
- Scientific Institute, IRCCS E. MEDEA, Bioinformatics, Lecco, Italy
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30
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Dissemination of Extended-Spectrum-β-Lactamase-Producing Enterobacter cloacae Complex from a Hospital to the Nearby Environment in Guadeloupe (French West Indies): ST114 Lineage Coding for a Successful IncHI2/ST1 Plasmid. Antimicrob Agents Chemother 2021; 65:AAC.02146-20. [PMID: 33361294 PMCID: PMC8092524 DOI: 10.1128/aac.02146-20] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 12/18/2020] [Indexed: 12/17/2022] Open
Abstract
Wastewater treatment plants are considered hot spots for antibiotic resistance. Most studies have addressed the impact on the aquatic environment, as water is an important source of anthropogenic pollutants. Wastewater treatment plants are considered hot spots for antibiotic resistance. Most studies have addressed the impact on the aquatic environment, as water is an important source of anthropogenic pollutants. Few investigations have been conducted on terrestrial animals living near treatment ponds. We isolated extended-spectrum-β-lactamase Enterobacter cloacae complex-producing strains from 35 clinical isolates, 29 samples of wastewater, 19 wild animals, and 10 domestic animals living in the hospital sewers and at or near a wastewater treatment plant to study the dissemination of clinically relevant resistance through hospital and urban effluents. After comparison of the antibiotic-resistant profiles of E. cloacae complex strains, a more detailed analysis of 41 whole-genome-sequenced strains demonstrated that the most common sequence type, ST114 (n = 20), was present in human (n = 9) and nonhuman (n = 11) samples, with a close genetic relatedness. Whole-genome sequencing confirmed local circulation of this pathogenic lineage in diverse animal species. In addition, nanopore sequencing and specific synteny of an IncHI2/ST1/blaCTX-M-15 plasmid recovered on the majority of these ST114 clones (n = 18) indicated successful worldwide diffusion of this mobile genetic element.
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31
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Richard D, Pruvost O, Balloux F, Boyer C, Rieux A, Lefeuvre P. Time-calibrated genomic evolution of a monomorphic bacterium during its establishment as an endemic crop pathogen. Mol Ecol 2020; 30:1823-1835. [PMID: 33305421 DOI: 10.1111/mec.15770] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Revised: 11/30/2020] [Accepted: 12/03/2020] [Indexed: 01/03/2023]
Abstract
Horizontal gene transfer is of major evolutionary importance as it allows for the redistribution of phenotypically important genes among lineages. Such genes with essential functions include those involved in resistance to antimicrobial compounds and virulence factors in pathogenic bacteria. Understanding gene turnover at microevolutionary scales is critical to assess the pace of this evolutionary process. Here, we characterized and quantified gene turnover for the epidemic lineage of a bacterial plant pathogen of major agricultural importance worldwide. Relying on a dense geographic sampling spanning 39 years of evolution, we estimated both the dynamics of single nucleotide polymorphism accumulation and gene content turnover. We identified extensive gene content variation among lineages even at the smallest phylogenetic and geographic scales. Gene turnover rate exceeded nucleotide substitution rate by three orders of magnitude. Accessory genes were found preferentially located on plasmids, but we identified a highly plastic chromosomal region hosting ecologically important genes such as transcription activator-like effectors. Whereas most changes in the gene content are probably transient, the rapid spread of a mobile element conferring resistance to copper compounds widely used for the management of plant bacterial pathogens illustrates how some accessory genes can become ubiquitous within a population over short timeframes.
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Affiliation(s)
- Damien Richard
- Cirad, UMR PVBMT, Réunion, France.,ANSES, Plant Health Laboratory, Réunion, France.,Université de la Réunion, UMR PVBMT, Réunion, France
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32
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Xu Y, Zhang S, Shen J, Wu Z, Du Z, Gao F. The phylogeographic history of tomato mosaic virus in Eurasia. Virology 2020; 554:42-47. [PMID: 33360588 DOI: 10.1016/j.virol.2020.12.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 12/14/2020] [Accepted: 12/14/2020] [Indexed: 11/19/2022]
Abstract
Tomato mosaic virus (ToMV) is a tobamovirus affecting solanaceous crops worldwide. The process of its emergence, however, is poorly understood. Here, Bayesian phylogenetic framework was employed to reconstruct the phylogeography of ToMV in Eurasia. The results showed that the ToMV in Europe, Middle East and East Asia has been evolving at a rate of 4.05 × 10-4 substitutions/site/year (95% credibility interval 2.43 × 10-4 - 5.62 × 10-4). Their most recent common ancestor (MRCA), most probably first appeared in Europe, was dated to around 1757 Common Era. The first introduction of ToMV into Middle East occurred in 1920s, with Europe as the source, while the first introduction of ToMV into East Asia occurred shortly afterwards, with Middle East as the source. From about 1950 onwards, inter-regional migrations of ToMV between Europe, Middle East and East Asia have been common. Overall, these data provide a glimpse into the phylogeographic history of ToMV in Eurasia.
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Affiliation(s)
- Yuting Xu
- Fujian Key Laboratory of Plant Virology, Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Shuling Zhang
- Department of Horticulture and Garden, Fujian Vocational College of Agriculture, Fuzhou, Fujian, 350119, China
| | - Jianguo Shen
- Technology Center of Fuzhou Customs District, Fuzhou, 350001, China
| | - Zujian Wu
- Fujian Key Laboratory of Plant Virology, Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Zhenguo Du
- Fujian Key Laboratory of Plant Virology, Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
| | - Fangluan Gao
- Fujian Key Laboratory of Plant Virology, Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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33
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Patton AH, Lawrance MF, Margres MJ, Kozakiewicz CP, Hamede R, Ruiz-Aravena M, Hamilton DG, Comte S, Ricci LE, Taylor RL, Stadler T, Leaché A, McCallum H, Jones ME, Hohenlohe PA, Storfer A. A transmissible cancer shifts from emergence to endemism in Tasmanian devils. Science 2020; 370:370/6522/eabb9772. [PMID: 33303589 DOI: 10.1126/science.abb9772] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 10/21/2020] [Indexed: 01/05/2023]
Abstract
Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is often used to infer epidemiological parameters essential for guiding intervention strategies for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). Here, we applied phylodynamics to elucidate the epidemiological dynamics of Tasmanian devil facial tumor disease (DFTD), a fatal, transmissible cancer with a genome thousands of times larger than that of any virus. Despite prior predictions of devil extinction, transmission rates have declined precipitously from ~3.5 secondary infections per infected individual to ~1 at present. Thus, DFTD appears to be transitioning from emergence to endemism, lending hope for the continued survival of the endangered Tasmanian devil. More generally, our study demonstrates a new phylodynamic analytical framework that can be applied to virtually any pathogen.
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Affiliation(s)
- Austin H Patton
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.,Department of Integrative Biology and Museum of Vertebrate Zoology, University of California, Berkeley, CA 94720, USA
| | - Matthew F Lawrance
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
| | - Mark J Margres
- Department of Integrative Biology, University of South Florida, Tampa, FL 33620, USA
| | | | - Rodrigo Hamede
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia.,CANECEV, Centre de Recherches Ecologiques et Evolutives sur le Cancer (CREEC), Montpellier 34090, France
| | - Manuel Ruiz-Aravena
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia.,Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA
| | - David G Hamilton
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia
| | - Sebastien Comte
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia.,Vertebrate Pest Research Unit, Invasive Species and Biosecurity, NSW Department of Primary Industries, Orange, New South Wales 2800, Australia
| | - Lauren E Ricci
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.,Department of Wildland Resources, Utah State University, Logan, UT 84322, USA
| | - Robyn L Taylor
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia
| | - Tanja Stadler
- Department for Biosystems Science and Engineering, ETH Zürich, Basel 4058, Switzerland.,Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Adam Leaché
- Department of Biology and Burke Museum of Natural History and Culture, University of Washington, Seattle, WA 98195, USA
| | - Hamish McCallum
- Vertebrate Pest Research Unit, Invasive Species and Biosecurity, NSW Department of Primary Industries, Orange, New South Wales 2800, Australia.,Environmental Futures Research Institute, Griffith University, Brisbane, Queensland 4111, Australia
| | - Menna E Jones
- School of Biological Sciences, University of Tasmania, Hobart, Tasmania 7001, Australia
| | - Paul A Hohenlohe
- Department of Biological Science, University of Idaho, Moscow, ID 83844, USA
| | - Andrew Storfer
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.
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34
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Kamau E, Otieno JR, Lewa CS, Mwema A, Murunga N, Nokes DJ, Agoti CN. Evolution of respiratory syncytial virus genotype BA in Kilifi, Kenya, 15 years on. Sci Rep 2020; 10:21176. [PMID: 33273687 PMCID: PMC7712891 DOI: 10.1038/s41598-020-78234-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 11/20/2020] [Indexed: 01/12/2023] Open
Abstract
Respiratory syncytial virus (RSV) is recognised as a leading cause of severe acute respiratory disease and deaths among infants and vulnerable adults. Clinical RSV isolates can be divided into several known genotypes. RSV genotype BA, characterised by a 60-nucleotide duplication in the G glycoprotein gene, emerged in 1999 and quickly disseminated globally replacing other RSV group B genotypes. Continual molecular epidemiology is critical to understand the evolutionary processes maintaining the success of the BA viruses. We analysed 735 G gene sequences from samples collected from paediatric patients in Kilifi, Kenya, between 2003 and 2017. The virus population comprised of several genetically distinct variants (n = 56) co-circulating within and between epidemics. In addition, there was consistent seasonal fluctuations in relative genetic diversity. Amino acid changes increasingly accumulated over the surveillance period including two residues (N178S and Q180R) that mapped to monoclonal antibody 2D10 epitopes, as well as addition of putative N-glycosylation sequons. Further, switching and toggling of amino acids within and between epidemics was observed. On a global phylogeny, the BA viruses from different countries form geographically isolated clusters suggesting substantial localized variants. This study offers insights into longitudinal population dynamics of a globally endemic RSV genotype within a discrete location.
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Affiliation(s)
- Everlyn Kamau
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya.
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
| | - James R Otieno
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
- Fogarty International Center, NIH, Bethesda, MD, USA
| | - Clement S Lewa
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
| | - Anthony Mwema
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
| | - Nickson Murunga
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
| | - D James Nokes
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
- School of Life Sciences and Zeeman Institute (SBIDER), University of Warwick, Coventry, UK
| | - Charles N Agoti
- Epidemiology and Demography Department, Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme, Kilifi, Kenya
- School of Health and Human Sciences, Pwani University, Kilifi, Kenya
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35
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Gao F, Kawakubo S, Ho SYW, Ohshima K. The evolutionary history and global spatio-temporal dynamics of potato virus Y. Virus Evol 2020; 6:veaa056. [PMID: 33324488 PMCID: PMC7724251 DOI: 10.1093/ve/veaa056] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Potato virus Y (PVY) is a destructive plant pathogen that causes considerable losses to global potato and tobacco production. Although the molecular structure of PVY is well characterized, the evolutionary and global transmission dynamics of this virus remain poorly understood. We investigated the phylodynamics of the virus by analysing 253 nucleotide sequences of the genes encoding the third protein (P3), cylindrical inclusion protein (CI), and the nuclear inclusion protein (NIb). Our Bayesian phylogenetic analyses showed that the mean substitution rates of different regions of the genome ranged from 8.50 × 10-5 to 1.34 × 10-4 substitutions/site/year, whereas the time to the most recent common ancestor of PVY varied with the length of the genomic regions and with the number of viral isolates being analysed. Our phylogeographic analysis showed that the PVY population originated in South America and was introduced into Europe in the 19th century, from where it spread around the globe. The migration pathways of PVY correlate well with the trade routes of potato tubers, suggesting that the global spread of PVY is associated with human activities.
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Affiliation(s)
- Fangluan Gao
- Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Shusuke Kawakubo
- Laboratory of Plant Virology, Department of Biological Sciences, Faculty of Agriculture, Saga University, 1-banchi, Honjo-machi, Saga 840-8502, Japan
| | - Simon Y W Ho
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW 2006, Australia
| | - Kazusato Ohshima
- Laboratory of Plant Virology, Department of Biological Sciences, Faculty of Agriculture, Saga University, 1-banchi, Honjo-machi, Saga 840-8502, Japan.,The United Graduate School of Agricultural Sciences, Kagoshima University, 1-21-24 Korimoto, Kagoshima 890-0065, Japan
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36
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Duchene S, Featherstone L, Haritopoulou-Sinanidou M, Rambaut A, Lemey P, Baele G. Temporal signal and the phylodynamic threshold of SARS-CoV-2. Virus Evol 2020; 6:veaa061. [PMID: 33235813 PMCID: PMC7454936 DOI: 10.1093/ve/veaa061] [Citation(s) in RCA: 250] [Impact Index Per Article: 62.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The ongoing SARS-CoV-2 outbreak marks the first time that large amounts of genome sequence data have been generated and made publicly available in near real time. Early analyses of these data revealed low sequence variation, a finding that is consistent with a recently emerging outbreak, but which raises the question of whether such data are sufficiently informative for phylogenetic inferences of evolutionary rates and time scales. The phylodynamic threshold is a key concept that refers to the point in time at which sufficient molecular evolutionary change has accumulated in available genome samples to obtain robust phylodynamic estimates. For example, before the phylodynamic threshold is reached, genomic variation is so low that even large amounts of genome sequences may be insufficient to estimate the virus’s evolutionary rate and the time scale of an outbreak. We collected genome sequences of SARS-CoV-2 from public databases at eight different points in time and conducted a range of tests of temporal signal to determine if and when the phylodynamic threshold was reached, and the range of inferences that could be reliably drawn from these data. Our results indicate that by 2 February 2020, estimates of evolutionary rates and time scales had become possible. Analyses of subsequent data sets, that included between 47 and 122 genomes, converged at an evolutionary rate of about 1.1 × 10−3 subs/site/year and a time of origin of around late November 2019. Our study provides guidelines to assess the phylodynamic threshold and demonstrates that establishing this threshold constitutes a fundamental step for understanding the power and limitations of early data in outbreak genome surveillance.
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Affiliation(s)
- Sebastian Duchene
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia, 3000
| | - Leo Featherstone
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia, 3000
| | - Melina Haritopoulou-Sinanidou
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia, 3000
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Philippe Lemey
- 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
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37
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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] [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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38
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Jara M, Rasmussen DA, Corzo CA, Machado G. Porcine reproductive and respiratory syndrome virus dissemination across pig production systems in the United States. Transbound Emerg Dis 2020; 68:667-683. [PMID: 32657491 DOI: 10.1111/tbed.13728] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 06/25/2020] [Accepted: 07/08/2020] [Indexed: 12/16/2022]
Abstract
Porcine reproductive and respiratory syndrome virus (PRRSV) remains widespread in the North American pig population. Despite improvements in virus characterization, it is unclear whether PRRSV infections are a product of viral circulation within production systems (local) or across production systems (external). Here, we examined the local and external dissemination dynamics of PRRSV and the processes facilitating its spread in three production systems. Overall, PRRSV genetic diversity has declined since 2018, while phylodynamic results support frequent external transmission. We found that PRRSV dissemination predominantly occurred mostly through transmission between farms of different production companies for several months, especially from November until May, a timeframe already established as PRRSV season. Although local PRRSV dissemination occurred mainly through regular pig flow (from sow to nursery and then to finisher farms), an important flux of PRRSV dissemination also occurred in the opposite direction, from finisher to sow and nursery farms, highlighting the importance of downstream farms as sources of the virus. Our results also showed that farms with pig densities of 500 to 1,000 pig/km2 and farms located at a range within 0.5 km and 0.7 km from major roads were more likely to be infected by PRRSV, whereas farms at an elevation of 41 to 61 meters and surrounded by denser vegetation were less likely to be infected, indicating their role as dissemination barriers. In conclusion, our results demonstrate that external dissemination was intense, and reinforce the importance of farm proximity on PRRSV spread. Thus, consideration of farm location, geographic characteristics and animal densities across production systems may help to forecast PRRSV collateral dissemination.
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Affiliation(s)
- Manuel Jara
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - David A Rasmussen
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, USA.,Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Cesar A Corzo
- Veterinary Population Medicine Department, College of Veterinary Medicine, University of Minnesota, St Paul, MN, USA
| | - Gustavo Machado
- Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
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39
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Kamau E, Otieno JR, Murunga N, Oketch JW, Ngoi JM, de Laurent ZR, Mwema A, Nyiro JU, Agoti CN, Nokes DJ. Genomic epidemiology and evolutionary dynamics of respiratory syncytial virus group B in Kilifi, Kenya, 2015-17. Virus Evol 2020; 6:veaa050. [PMID: 32913665 PMCID: PMC7474930 DOI: 10.1093/ve/veaa050] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Respiratory syncytial virus (RSV) circulates worldwide, occurring seasonally in communities, and is a leading cause of acute respiratory illness in young children. There is paucity of genomic data from purposively sampled populations by which to investigate evolutionary dynamics and transmission patterns of RSV. Here we present an analysis of 295 RSV group B (RSVB) genomes from Kilifi, coastal Kenya, sampled from individuals seeking outpatient care in nine health facilities across a defined geographical area (∼890 km2), over two RSV epidemics between 2015 and 2017. RSVB diversity was characterized by multiple virus introductions into the area and co-circulation of distinct genetic clusters, which transmitted and diversified locally with varying frequency. Increase in relative genetic diversity paralleled seasonal virus incidence. Importantly, we identified a cluster of viruses that emerged in the 2016/17 epidemic, carrying distinct amino-acid signatures including a novel nonsynonymous change (K68Q) in antigenic site ∅ in the Fusion protein. RSVB diversity was additionally marked by signature nonsynonymous substitutions that were unique to particular genomic clusters, some under diversifying selection. Our findings provide insights into recent evolutionary and epidemiological behaviors of RSVB, and highlight possible emergence of a novel antigenic variant, which has implications on current prophylactic strategies in development.
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Affiliation(s)
- Everlyn Kamau
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - James R Otieno
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Nickson Murunga
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - John W Oketch
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Joyce M Ngoi
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Zaydah R de Laurent
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Anthony Mwema
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Joyce U Nyiro
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Charles N Agoti
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.,School of Health and Human Sciences, Pwani University, Kilifi, Kenya
| | - D James Nokes
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.,School of Life Sciences and Zeeman Institute (SBIDER), University of Warwick, Coventry, UK
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40
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Perez-Quintero AL, Ortiz-Castro M, Lang JM, Rieux A, Wu G, Liu S, Chapman TA, Chang C, Ziegle J, Peng Z, White FF, Plazas MC, Leach JE, Broders K. Genomic Acquisitions in Emerging Populations of Xanthomonas vasicola pv. vasculorum Infecting Corn in the United States and Argentina. PHYTOPATHOLOGY 2020; 110:1161-1173. [PMID: 32040377 DOI: 10.1094/phyto-03-19-0077-r] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Xanthomonas vasicola pv. vasculorum is an emerging bacterial plant pathogen that causes bacterial leaf streak on corn. First described in South Africa in 1949, reports of this pathogen have greatly increased in the past years in South America and in the United States. The rapid spread of this disease in North and South America may be due to more favorable environmental conditions, susceptible hosts and/or genomic changes that favored the spread. To understand whether genetic mechanisms exist behind the recent spread of X. vasicola pv. vasculorum, we used comparative genomics to identify gene acquisitions in X. vasicola pv. vasculorum genomes from the United States and Argentina. We sequenced 41 genomes of X. vasicola pv. vasculorum and the related sorghum-infecting X. vasicola pv. holcicola and performed comparative analyses against all available X. vasicola genomes. Time-measured phylogenetic analyses showed that X. vasicola pv. vasculorum strains from the United States and Argentina are closely related and arose from two introductions to North and South America. Gene content comparisons identified clusters of genes enriched in corn X. vasicola pv. vasculorum that showed evidence of horizontal transfer including one cluster corresponding to a prophage found in all X. vasicola pv. vasculorum strains from the United States and Argentina as well as in X. vasicola pv. holcicola strains. In this work, we explore the genomes of an emerging phytopathogen population as a first step toward identifying genetic changes associated with the emergence. The acquisitions identified may contain virulence determinants or other factors associated with the spread of X. vasicola pv. vasculorum in North and South America and will be the subject of future work.
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Affiliation(s)
- Alvaro L Perez-Quintero
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
| | - Mary Ortiz-Castro
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
| | - Jillian M Lang
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
| | | | - Guangxi Wu
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
| | - Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, KS, U.S.A
| | - Toni A Chapman
- Biosecurity and Food Safety, NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, NSW, Australia
| | | | | | - Zhao Peng
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
| | - Frank F White
- Department of Plant Pathology, University of Florida, Gainesville, FL, U.S.A
| | - Maria Cristina Plazas
- Laboratorio de Fitopatología y Microbiología, Universidad Católica de Córdoba, Ob. Trejo 323, Córdoba, Argentina
| | - Jan E Leach
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
| | - Kirk Broders
- Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, U.S.A
- Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Republic of Panamá
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41
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Jara M, Frias-De-Diego A, Machado G. Phylogeography of Equine Infectious Anemia Virus. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00127] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
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42
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Vrancken B, Wawina-Bokalanga T, Vanmechelen B, Martí-Carreras J, Carroll MW, Nsio J, Kapetshi J, Makiala-Mandanda S, Muyembe-Tamfum JJ, Baele G, Vermeire K, Vergote V, Ahuka-Mundeke S, Maes P. Accounting for population structure reveals ambiguity in the Zaire Ebolavirus reservoir dynamics. PLoS Negl Trop Dis 2020; 14:e0008117. [PMID: 32130210 PMCID: PMC7075637 DOI: 10.1371/journal.pntd.0008117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 03/16/2020] [Accepted: 02/05/2020] [Indexed: 11/18/2022] Open
Abstract
Ebolaviruses pose a substantial threat to wildlife populations and to public health in Africa. Evolutionary analyses of virus genome sequences can contribute significantly to elucidate the origin of new outbreaks, which can help guide surveillance efforts. The reconstructed between-outbreak evolutionary history of Zaire ebolavirus so far has been highly consistent. By removing the confounding impact of population growth bursts during local outbreaks on the free mixing assumption that underlies coalescent-based demographic reconstructions, we find-contrary to what previous results indicated-that the circulation dynamics of Ebola virus in its animal reservoir are highly uncertain. Our findings also accentuate the need for a more fine-grained picture of the Ebola virus diversity in its reservoir to reliably infer the reservoir origin of outbreak lineages. In addition, the recent appearance of slower-evolving variants is in line with latency as a survival mechanism and with bats as the natural reservoir host.
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Affiliation(s)
- Bram Vrancken
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Tony Wawina-Bokalanga
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Bert Vanmechelen
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Joan Martí-Carreras
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Miles W. Carroll
- Research and Development Institute, National Infection Service, Public Health England, Porton Down, Wiltshire, United Kingdom
| | - Justus Nsio
- Ministère de la Santé, Kinshasa, Democratic Republic of the Congo
| | - Jimmy Kapetshi
- Institut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo
| | - Sheila Makiala-Mandanda
- Institut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo
| | | | - Guy Baele
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Kurt Vermeire
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Leuven, Belgium
| | - Valentijn Vergote
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
| | - Steve Ahuka-Mundeke
- Institut National de Recherche Biomédicale (INRB), Kinshasa, Democratic Republic of the Congo
| | - Piet Maes
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Division of Clinical and Epidemiological Virology, Leuven, Belgium
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43
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Evolutionary Dynamics of Oropouche Virus in South America. J Virol 2020; 94:JVI.01127-19. [PMID: 31801869 PMCID: PMC7022353 DOI: 10.1128/jvi.01127-19] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 11/19/2019] [Indexed: 01/09/2023] Open
Abstract
The emergence and reemergence of pathogens such as Zika virus, chikungunya virus, and yellow fever virus have drawn attention toward other cocirculating arboviruses in South America. Oropouche virus (OROV) is a poorly studied pathogen responsible for over a dozen outbreaks since the early 1960s and represents a public health burden to countries such as Brazil, Panama, and Peru. OROV is likely underreported since its symptomatology can be easily confounded with other febrile illnesses (e.g., dengue fever and leptospirosis) and point-of-care testing for the virus is still uncommon. With limited data, there is a need to optimize the information currently available. Analysis of OROV genomes can help us understand how the virus circulates in nature and can reveal the evolutionary forces that shape the genetic diversity of the virus, which has implications for molecular diagnostics and the design of potential vaccines. The Amazon basin is home to numerous arthropod-borne viral pathogens that cause febrile disease in humans. Among these, Oropouche orthobunyavirus (OROV) is a relatively understudied member of the genus Orthobunyavirus, family Peribunyaviridae, that causes periodic outbreaks in human populations in Brazil and other South American countries. Although several studies have described the genetic diversity of the virus, the evolutionary processes that shape the OROV genome remain poorly understood. Here, we present a comprehensive study of the genomic dynamics of OROV that encompasses phylogenetic analysis, evolutionary rate estimates, inference of natural selective pressures, recombination and reassortment, and structural analysis of OROV variants. Our study includes all available published sequences, as well as a set of new OROV genome sequences obtained from patients in Ecuador, representing the first set of genomes from this country. Our results show differing evolutionary processes on the three segments that comprise the viral genome. We infer differing times of the most recent common ancestors of the genome segments and propose that this can be explained by cryptic reassortment. We also present the discovery of previously unobserved putative N-linked glycosylation sites, as well as codons that evolve under positive selection on the viral surface proteins, and discuss the potential role of these features in the evolution of OROV through a combined phylogenetic and structural approach. IMPORTANCE The emergence and reemergence of pathogens such as Zika virus, chikungunya virus, and yellow fever virus have drawn attention toward other cocirculating arboviruses in South America. Oropouche virus (OROV) is a poorly studied pathogen responsible for over a dozen outbreaks since the early 1960s and represents a public health burden to countries such as Brazil, Panama, and Peru. OROV is likely underreported since its symptomatology can be easily confounded with other febrile illnesses (e.g., dengue fever and leptospirosis) and point-of-care testing for the virus is still uncommon. With limited data, there is a need to optimize the information currently available. Analysis of OROV genomes can help us understand how the virus circulates in nature and can reveal the evolutionary forces that shape the genetic diversity of the virus, which has implications for molecular diagnostics and the design of potential vaccines.
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Monjane AL, Dellicour S, Hartnady P, Oyeniran KA, Owor BE, Bezuidenhout M, Linderme D, Syed RA, Donaldson L, Murray S, Rybicki EP, Kvarnheden A, Yazdkhasti E, Lefeuvre P, Froissart R, Roumagnac P, Shepherd DN, Harkins GW, Suchard MA, Lemey P, Varsani A, Martin DP. Symptom evolution following the emergence of maize streak virus. eLife 2020; 9:51984. [PMID: 31939738 PMCID: PMC7034976 DOI: 10.7554/elife.51984] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 01/14/2020] [Indexed: 11/24/2022] Open
Abstract
For pathogens infecting single host species evolutionary trade-offs have previously been demonstrated between pathogen-induced mortality rates and transmission rates. It remains unclear, however, how such trade-offs impact sub-lethal pathogen-inflicted damage, and whether these trade-offs even occur in broad host-range pathogens. Here, we examine changes over the past 110 years in symptoms induced in maize by the broad host-range pathogen, maize streak virus (MSV). Specifically, we use the quantified symptom intensities of cloned MSV isolates in differentially resistant maize genotypes to phylogenetically infer ancestral symptom intensities and check for phylogenetic signal associated with these symptom intensities. We show that whereas symptoms reflecting harm to the host have remained constant or decreased, there has been an increase in how extensively MSV colonizes the cells upon which transmission vectors feed. This demonstrates an evolutionary trade-off between amounts of pathogen-inflicted harm and how effectively viruses position themselves within plants to enable onward transmission.
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Affiliation(s)
- Adérito L Monjane
- Fish Health Research Group, Norwegian Veterinary Institute, Oslo, Norway.,Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium.,Spatial Epidemiology Laboratory (SpELL), Université Libre de Bruxelles, Brussels, Belgium
| | - Penelope Hartnady
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Observatory, Cape Town, South Africa
| | - Kehinde A Oyeniran
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Observatory, Cape Town, South Africa
| | - Betty E Owor
- Department of Agricultural Production, School of Agricultural Sciences, Makerere University, Kampala, Uganda
| | - Marion Bezuidenhout
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Daphné Linderme
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Rizwan A Syed
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Lara Donaldson
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Shane Murray
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Edward P Rybicki
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa
| | - Anders Kvarnheden
- Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Elham Yazdkhasti
- Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | | | - Rémy Froissart
- University of Montpellier, Centre National de la Recherche Scientifique (CNRS), Institut de recherche pour le développement (IRD), UMR 5290, Maladie Infectieuses & Vecteurs: Écologie, Génétique Évolution & Contrôle" (MIVEGEC), Montpellier, France
| | - Philippe Roumagnac
- CIRAD, BGPI, Montpellier, France.,BGPI, INRA, CIRAD, SupAgro, Univ Montpellier, Montpellier, France
| | - Dionne N Shepherd
- Molecular and Cell Biology Department, University of Cape Town, Cape Town, South Africa.,Research Office, University of Cape Town, Cape Town, South Africa
| | - Gordon W Harkins
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Arvind Varsani
- The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, United States.,Structural Biology Research Unit, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Darren P Martin
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Observatory, Cape Town, South Africa
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RifeMagalis B, Strickland SL, Shank SD, Autissier P, Schuetz A, Sithinamsuwan P, Lerdlum S, Fletcher JLK, de Souza M, Ananworanich J, Valcour V, Williams KC, Kosakovsky Pond SL, RattoKim S, Salemi M. Phyloanatomic characterization of the distinct T cell and monocyte contributions to the peripheral blood HIV population within the host. Virus Evol 2020; 6:veaa005. [PMID: 32355568 PMCID: PMC7185683 DOI: 10.1093/ve/veaa005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Human immunodeficiency virus (HIV) is a rapidly evolving virus, allowing its genetic sequence to act as a fingerprint for epidemiological processes among, as well as within, individual infected hosts. Though primarily infecting the CD4+ T-cell population, HIV can also be found in monocytes, an immune cell population that differs in several aspects from the canonical T-cell viral target. Using single genome viral sequencing and statistical phylogenetic inference, we investigated the viral RNA diversity and relative contribution of each of these immune cell types to the viral population within the peripheral blood. Results provide evidence of an increased prevalence of circulating monocytes harboring virus in individuals with high viral load in the absence of suppressive antiretroviral therapy. Bayesian phyloanatomic analysis of three of these individuals demonstrated a measurable role for these cells, but not the circulating T-cell population, as a source of cell-free virus in the plasma, supporting the hypothesis that these cells can act as an additional conduit of virus spread.
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Affiliation(s)
- Brittany RifeMagalis
- Department of Pathology, Immunology, and Laboratory Medicine, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
| | - Samantha L Strickland
- Department of Pathology, Immunology, and Laboratory Medicine, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
| | - Stephen D Shank
- Department of Biology, Temple University, Philadelphia, PA 19122, USA
| | | | - Alexandra Schuetz
- Department of Retrovirology, Armed Forces Research Institute of Medical Sciences - United States Component, Bangkok 10400, Thailand
- SEARCH, Thai Red Cross AIDS Research Center, Bangkok 10330, Thailand
| | - Pasiri Sithinamsuwan
- U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Rockville, MD 20850, USA
| | - Sukalaya Lerdlum
- Division of Neurology, Department of Medicine, Phramongkutklao Hospital, Bangkok 10400, Thailand
| | - James L K Fletcher
- Faculty of Medicine, Department of Radiology, Chulalongkorn University, Bangkok 10330, Thailand
| | - Mark de Souza
- Faculty of Medicine, Department of Radiology, Chulalongkorn University, Bangkok 10330, Thailand
| | - Jintanat Ananworanich
- Department of Retrovirology, Armed Forces Research Institute of Medical Sciences - United States Component, Bangkok 10400, Thailand
- SEARCH, Thai Red Cross AIDS Research Center, Bangkok 10330, Thailand
- Faculty of Medicine, Department of Radiology, Chulalongkorn University, Bangkok 10330, Thailand
| | - Victor Valcour
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | | | | | - Silvia RattoKim
- Department of Retrovirology, Armed Forces Research Institute of Medical Sciences - United States Component, Bangkok 10400, Thailand
- SEARCH, Thai Red Cross AIDS Research Center, Bangkok 10330, Thailand
| | - Marco Salemi
- Department of Pathology, Immunology, and Laboratory Medicine, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
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46
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Fenderson LE, Kovach AI, Llamas B. Spatiotemporal landscape genetics: Investigating ecology and evolution through space and time. Mol Ecol 2019; 29:218-246. [DOI: 10.1111/mec.15315] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 09/22/2019] [Accepted: 11/13/2019] [Indexed: 12/22/2022]
Affiliation(s)
- Lindsey E. Fenderson
- Australian Centre for Ancient DNA School of Biological Sciences Environment Institute University of Adelaide Adelaide South Australia Australia
- Department of Natural Resources and the Environment University of New Hampshire Durham NH USA
| | - Adrienne I. Kovach
- Department of Natural Resources and the Environment University of New Hampshire Durham NH USA
| | - Bastien Llamas
- Australian Centre for Ancient DNA School of Biological Sciences Environment Institute University of Adelaide Adelaide South Australia Australia
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Steinig EJ, Duchene S, Robinson DA, Monecke S, Yokoyama M, Laabei M, Slickers P, Andersson P, Williamson D, Kearns A, Goering RV, Dickson E, Ehricht R, Ip M, O'Sullivan MVN, Coombs GW, Petersen A, Brennan G, Shore AC, Coleman DC, Pantosti A, de Lencastre H, Westh H, Kobayashi N, Heffernan H, Strommenger B, Layer F, Weber S, Aamot HV, Skakni L, Peacock SJ, Sarovich D, Harris S, Parkhill J, Massey RC, Holden MTG, Bentley SD, Tong SYC. Evolution and Global Transmission of a Multidrug-Resistant, Community-Associated Methicillin-Resistant Staphylococcus aureus Lineage from the Indian Subcontinent. mBio 2019; 10:e01105-19. [PMID: 31772058 PMCID: PMC6879714 DOI: 10.1128/mbio.01105-19] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 10/15/2019] [Indexed: 01/21/2023] Open
Abstract
The evolution and global transmission of antimicrobial resistance have been well documented for Gram-negative bacteria and health care-associated epidemic pathogens, often emerging from regions with heavy antimicrobial use. However, the degree to which similar processes occur with Gram-positive bacteria in the community setting is less well understood. In this study, we traced the recent origins and global spread of a multidrug-resistant, community-associated Staphylococcus aureus lineage from the Indian subcontinent, the Bengal Bay clone (ST772). We generated whole-genome sequence data of 340 isolates from 14 countries, including the first isolates from Bangladesh and India, to reconstruct the evolutionary history and genomic epidemiology of the lineage. Our data show that the clone emerged on the Indian subcontinent in the early 1960s and disseminated rapidly in the 1990s. Short-term outbreaks in community and health care settings occurred following intercontinental transmission, typically associated with travel and family contacts on the subcontinent, but ongoing endemic transmission was uncommon. Acquisition of a multidrug resistance integrated plasmid was instrumental in the emergence of a single dominant and globally disseminated clade in the early 1990s. Phenotypic data on biofilm, growth, and toxicity point to antimicrobial resistance as the driving force in the evolution of ST772. The Bengal Bay clone therefore combines the multidrug resistance of traditional health care-associated clones with the epidemiological transmission of community-associated methicillin-resistant S. aureus (MRSA). Our study demonstrates the importance of whole-genome sequencing for tracking the evolution of emerging and resistant pathogens. It provides a critical framework for ongoing surveillance of the clone on the Indian subcontinent and elsewhere.IMPORTANCE The Bengal Bay clone (ST772) is a community-associated and multidrug-resistant Staphylococcus aureus lineage first isolated from Bangladesh and India in 2004. In this study, we showed that the Bengal Bay clone emerged from a virulent progenitor circulating on the Indian subcontinent. Its subsequent global transmission was associated with travel or family contact in the region. ST772 progressively acquired specific resistance elements at limited cost to its fitness and continues to be exported globally, resulting in small-scale community and health care outbreaks. The Bengal Bay clone therefore combines the virulence potential and epidemiology of community-associated clones with the multidrug resistance of health care-associated S. aureus lineages. This study demonstrates the importance of whole-genome sequencing for the surveillance of highly antibiotic-resistant pathogens, which may emerge in the community setting of regions with poor antibiotic stewardship and rapidly spread into hospitals and communities across the world.
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Affiliation(s)
- Eike J Steinig
- Menzies School of Health Research, Darwin, Australia
- Australian Institute of Tropical Health and Medicine, Townsville, Australia
| | - Sebastian Duchene
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | | | - Stefan Monecke
- Leibniz Institute of Photonic Technology (IPHT), Jena, Germany
- InfectoGnostics Research Campus, Jena, Germany
- Technical University of Dresden, Dresden, Germany
| | - Maho Yokoyama
- Department of Biology and Biochemistry, University of Bath, Bath, United Kingdom
| | - Maisem Laabei
- Department of Biology and Biochemistry, University of Bath, Bath, United Kingdom
| | - Peter Slickers
- Leibniz Institute of Photonic Technology (IPHT), Jena, Germany
- InfectoGnostics Research Campus, Jena, Germany
| | | | - Deborah Williamson
- Doherty Applied Microbial Genomics, Department of Microbiology & Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Angela Kearns
- Public Health England, National Infection Service, London, United Kingdom
| | | | - Elizabeth Dickson
- Scottish Microbiology Reference Laboratories, Glasgow, United Kingdom
| | - Ralf Ehricht
- Leibniz Institute of Photonic Technology (IPHT), Jena, Germany
- Technical University of Dresden, Dresden, Germany
| | - Margaret Ip
- The Chinese University of Hong Kong, Hong Kong
| | - Matthew V N O'Sullivan
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Sydney, Australia, and New Wales Health Pathology, Westmead Hospital, Sydney, Australia
| | - Geoffrey W Coombs
- School of Veterinary and Laboratory Sciences, Murdoch University, Murdoch, Australia
| | | | - Grainne Brennan
- National MRSA Reference Laboratory, St. James's Hospital, Dublin, Ireland
| | - Anna C Shore
- Microbiology Research Unit, School of Dental Science, University of Dublin, Trinity College Dublin, Dublin, Ireland
| | - David C Coleman
- Microbiology Research Unit, School of Dental Science, University of Dublin, Trinity College Dublin, Dublin, Ireland
| | | | - Herminia de Lencastre
- Instituto de Tecnologia Química e Biológica, Oeiras, Portugal
- The Rockefeller University, New York, New York, USA
| | - Henrik Westh
- University of Copenhagen, Copenhagen, Denmark
- Hvidovre University Hospital, Hvidovre, Denmark
| | | | - Helen Heffernan
- Institute of Environmental Science and Research, Wellington, New Zealand
| | | | | | - Stefan Weber
- Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates
| | | | - Leila Skakni
- King Fahd Medical City, Riyadh, Kingdom of Saudi Arabia
| | - Sharon J Peacock
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Derek Sarovich
- Menzies School of Health Research, Darwin, Australia
- Sunshine Coast University, Sippy Downs, Australia
| | - Simon Harris
- Wellcome Sanger Institute, Cambridge, United Kingdom
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Ruth C Massey
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
| | - Mathew T G Holden
- Wellcome Sanger Institute, Cambridge, United Kingdom
- University of St. Andrews, St. Andrews, United Kingdom
| | | | - Steven Y C Tong
- Menzies School of Health Research, Darwin, Australia
- Victorian Infectious Disease Service, The Royal Melbourne Hospital, and Doherty Department, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Victoria, Australia
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The Effect of Sample Bias and Experimental Artefacts on the Statistical Phylogenetic Analysis of Picornaviruses. Viruses 2019; 11:v11111032. [PMID: 31698764 PMCID: PMC6893659 DOI: 10.3390/v11111032] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 11/04/2019] [Accepted: 11/04/2019] [Indexed: 12/05/2022] Open
Abstract
Statistical phylogenetic methods are a powerful tool for inferring the evolutionary history of viruses through time and space. The selection of mathematical models and analysis parameters has a major impact on the outcome, and has been relatively well-described in the literature. The preparation of a sequence dataset is less formalized, but its impact can be even more profound. This article used simulated datasets of enterovirus sequences to evaluate the effect of sample bias on picornavirus phylogenetic studies. Possible approaches to the reduction of large datasets and their potential for introducing additional artefacts were demonstrated. The most consistent results were obtained using “smart sampling”, which reduced sequence subsets from large studies more than those from smaller ones in order to preserve the rare sequences in a dataset. The effect of sequences with technical or annotation errors in the Bayesian framework was also analyzed. Sequences with about 0.5% sequencing errors or incorrect isolation dates altered by just 5 years could be detected by various approaches, but the efficiency of identification depended upon sequence position in a phylogenetic tree. Even a single erroneous sequence could profoundly destabilize the whole analysis by increasing the variance of the inferred evolutionary parameters.
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Abstract
Lassa virus is the causative agent of Lassa fever, a viral hemorrhagic fever with a case fatality rate of approximately 30% in Africa. Previous studies disclosed a geographical pattern in the distribution of Lassa virus strains and a westward movement of the virus across West Africa during evolution. Our study provides a deeper understanding of the geography of genetic lineages and sublineages of the virus in Nigeria. In addition, we modeled how the virus spread in the country. This knowledge allows us to predict into which geographical areas the virus might spread in the future and prioritize areas for Lassa fever surveillance. Our study not only aimed to generate Lassa virus sequences from across Nigeria but also to isolate and conserve the respective viruses for future research. Both isolates and sequences are important for the development and evaluation of medical countermeasures to treat and prevent Lassa fever, such as diagnostics, therapeutics, and vaccines. Lassa virus is genetically diverse with several lineages circulating in West Africa. This study aimed at describing the sequence variability of Lassa virus across Nigeria and inferring its spatiotemporal evolution. We sequenced and isolated 77 Lassa virus strains from 16 Nigerian states. The final data set, including previous works, comprised metadata and sequences of 219 unique strains sampled between 1969 and 2018 in 22 states. Most of this data originated from Lassa fever patients diagnosed at Irrua Specialist Teaching Hospital, Edo State, Nigeria. The majority of sequences clustered with the main Nigerian lineages II and III, while a few sequences formed a new cluster related to Lassa virus strains from Hylomyscus pamfi. Within lineages II and III, seven and five sublineages, respectively, were distinguishable. Phylogeographic analysis suggests an origin of lineage II in the southeastern part of the country around Ebonyi State and a main vector of dispersal toward the west across the Niger River, through Anambra, Kogi, Delta, and Edo into Ondo State. The frontline of virus dispersal appears to be in Ondo. Minor vectors are directed northeast toward Taraba and Adamawa and south toward Imo and Rivers. Lineage III might have spread from northern Plateau State into Kaduna, Nasarawa, Federal Capital Territory, and Bauchi. One sublineage moved south and crossed the Benue River into Benue State. This study provides a geographic mapping of lineages and phylogenetic clusters in Nigeria at a higher resolution. In addition, we estimated the direction and time frame of virus dispersal in the country. IMPORTANCE Lassa virus is the causative agent of Lassa fever, a viral hemorrhagic fever with a case fatality rate of approximately 30% in Africa. Previous studies disclosed a geographical pattern in the distribution of Lassa virus strains and a westward movement of the virus across West Africa during evolution. Our study provides a deeper understanding of the geography of genetic lineages and sublineages of the virus in Nigeria. In addition, we modeled how the virus spread in the country. This knowledge allows us to predict into which geographical areas the virus might spread in the future and prioritize areas for Lassa fever surveillance. Our study not only aimed to generate Lassa virus sequences from across Nigeria but also to isolate and conserve the respective viruses for future research. Both isolates and sequences are important for the development and evaluation of medical countermeasures to treat and prevent Lassa fever, such as diagnostics, therapeutics, and vaccines.
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Characteristics and evolutionary history of hepatitis B virus quasi-subgenotype B3 in Southeast Asia. Virus Res 2019; 273:197762. [PMID: 31541667 DOI: 10.1016/j.virusres.2019.197762] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 09/17/2019] [Accepted: 09/17/2019] [Indexed: 12/16/2022]
Abstract
To analyze the hepatitis B virus (HBV) quasi-subgenotype B3 characters and molecular evolution in Southeast Asia, 411 serum samples with HBsAg positive were collected from Xishuangbanna, China. After DNA extraction, PCR amplification and sequencing, a total of 183 HBV full-length genomes were obtained. Phylogenetic analysis showed 139 stains (76.0%) were genotype B, 41 strains were genotype C (22.4%) and 3 strains were genotype I (1.6%). Among genotype B, 34 sequences were identified as quasi-subgenotype B3. Quasi-subgenotype B3 sequences from this study and quasi-subgenotype B3 sequences from the GenBank (total of 141 complete genome sequences) were grouped into quasi-subgenotype B3 (B3, formerly B5, Chinese B6 and B7-9). Sixteen peculiar nucleotides distributed in quasi-subgenotype B3 were identified, which were differ from B1, B2, B4 and B5(formerly B6) (nt93 T, nt100C, nt355 G, nt843 T, nt861C, nt912C, nt929 T, nt930 G, nt1023 T, nt1041 T, nt2651C, nt2693 T, nt2970C, nt3054A, nt3087A and nt3171 G). Then Evolutionary dynamics analysis of HBV quasi-subgenotype B3 was performed. The mean rate of nucleotide substitution for HBV quasi-subgenotype B3 was estimated to be around 5.556-5.660 × 10-4 substitutions/site/year. Estimated time to most recent ancestor of quasi-subgenotype B3 was around the 1847-1945(95%HPD), and Yunnan strains might be the parental strains. The Bayesian sky plot showed a steady spreading of HBV quasi-genotype B3 from early of 1940s to 90 s. In summary, HBV quasi-subgenotype B3 infection is prevalent in Southeast Asia based on the current reports and still with a high prevalence rate based on the evolutionary dynamics analysis. Current vaccine and nucleotide analogues might have effective prevention and treatment for HBV quasi-subgenotype B3 based on the rare clinically relevant mutation sites included in quasi-subgenotype B3.
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