2
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Wang D, Zhu W, Yang L, Shu Y. The Epidemiology, Virology, and Pathogenicity of Human Infections with Avian Influenza Viruses. Cold Spring Harb Perspect Med 2021; 11:cshperspect.a038620. [PMID: 31964651 DOI: 10.1101/cshperspect.a038620] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Influenza is a global challenge, and future pandemics of influenza are inevitable. One of the lessons learned from past pandemics is that all pandemic influenza viruses characterized to date possess viral genes originating from avian influenza viruses (AIVs). During the past decades, a wide range of AIVs have overcome the species barrier and infected humans with different clinical manifestations ranging from mild illness to severe disease and even death. Understanding the mechanisms of infection in the context of clinical outcomes, the mechanism of interspecies transmission, and the molecular determinants that confer interspecies transmission is important for pandemic preparedness. Here, we summarize the epidemiology, virology, and pathogenicity of human infections with AIVs to further our understanding of interspecies transmission.
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Affiliation(s)
- Dayan Wang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Medical Virology, National Health Commission of the People's Republic of China, Beijing 102206, P.R. China
| | - Wenfei Zhu
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Medical Virology, National Health Commission of the People's Republic of China, Beijing 102206, P.R. China
| | - Lei Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Medical Virology, National Health Commission of the People's Republic of China, Beijing 102206, P.R. China
| | - Yuelong Shu
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Medical Virology, National Health Commission of the People's Republic of China, Beijing 102206, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangdong 510275, P.R. China
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3
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Zhao L, Abbasi AB, Illingworth CJR. Mutational load causes stochastic evolutionary outcomes in acute RNA viral infection. Virus Evol 2019; 5:vez008. [PMID: 31024738 PMCID: PMC6476161 DOI: 10.1093/ve/vez008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Mutational load is known to be of importance for the evolution of RNA viruses, the combination of a high mutation rate and large population size leading to an accumulation of deleterious mutations. However, while the effects of mutational load on global viral populations have been considered, its quantitative effects at the within-host scale of infection are less well understood. We here show that even on the rapid timescale of acute disease, mutational load has an effect on within-host viral adaptation, reducing the effective selection acting upon beneficial variants by ∼10 per cent. Furthermore, mutational load induces considerable stochasticity in the pattern of evolution, causing a more than five-fold uncertainty in the effective fitness of a transmitted beneficial variant. Our work aims to bridge the gap between classic models from population genetic theory and the biology of viral infection. In an advance on some previous models of mutational load, we replace the assumption of a constant variant fitness cost with an experimentally-derived distribution of fitness effects. Expanding previous frameworks for evolutionary simulation, we introduce the Wright-Fisher model with continuous mutation, which describes a continuum of possible modes of replication within a cell. Our results advance our understanding of adaptation in the context of strong selection and a high mutation rate. Despite viral populations having large absolute sizes, critical events in viral adaptation, including antigenic drift and the onset of drug resistance, arise through stochastic evolutionary processes.
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Affiliation(s)
- Lei Zhao
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Ali B Abbasi
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Christopher J R Illingworth
- Department of Genetics, University of Cambridge, Cambridge, UK
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
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4
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Lipsitch M, Barclay W, Raman R, Russell CJ, Belser JA, Cobey S, Kasson PM, Lloyd-Smith JO, Maurer-Stroh S, Riley S, Beauchemin CA, Bedford T, Friedrich TC, Handel A, Herfst S, Murcia PR, Roche B, Wilke CO, Russell CA. Viral factors in influenza pandemic risk assessment. eLife 2016; 5. [PMID: 27834632 PMCID: PMC5156527 DOI: 10.7554/elife.18491] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 11/03/2016] [Indexed: 12/13/2022] Open
Abstract
The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.
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Affiliation(s)
- Marc Lipsitch
- Center for Communicable Disease Dynamics, Harvard T. H Chan School of Public Health, Boston, United States.,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, United States.,Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, United States
| | - Wendy Barclay
- Division of Infectious Disease, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Rahul Raman
- Department of Biological Engineering, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States
| | - Charles J Russell
- Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, United States
| | - Jessica A Belser
- Centers for Disease Control and Prevention, Atlanta, United States
| | - Sarah Cobey
- Department of Ecology and Evolutionary Biology, University of Chicago, Chicago, United States
| | - Peter M Kasson
- Department of Biomedical Engineering, University of Virginia, Charlottesville, United States.,Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, United States
| | - James O Lloyd-Smith
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States.,Fogarty International Center, National Institutes of Health, Bethesda, United States
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science Technology and Research, Singapore, Singapore.,National Public Health Laboratory, Communicable Diseases Division, Ministry of Health, Singapore, Singapore.,School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Steven Riley
- MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom.,Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin School of Veterinary Medicine, Madison, United States
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, United States
| | - Sander Herfst
- Department of Viroscience, Erasmus Medical Center, Rotterdam, Netherlands
| | - Pablo R Murcia
- MRC-University of Glasgow Centre For Virus Research, Glasgow, United Kingdom
| | | | - Claus O Wilke
- Center for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, United States.,Department of Integrative Biology, The University of Texas at Austin, Austin, United States
| | - Colin A Russell
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
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5
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Expected Effect of Deleterious Mutations on Within-Host Adaptation of Pathogens. J Virol 2015; 89:9242-51. [PMID: 26109724 DOI: 10.1128/jvi.00832-15] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 06/20/2015] [Indexed: 01/09/2023] Open
Abstract
UNLABELLED Adaptation is a common theme in both pathogen emergence, for example, in zoonotic cross-species transmission, and pathogen control, where adaptation might limit the effect of the immune response and antiviral treatment. When such evolution requires deleterious intermediate mutations, fitness ridges and valleys arise in the pathogen's fitness landscape. The effect of deleterious intermediate mutations on within-host pathogen adaptation is examined with deterministic calculations, appropriate for pathogens replicating in large populations with high error rates. The effect of deleterious intermediate mutations on pathogen adaptation is smaller than their name might suggest: when two mutations are required and each individual single mutation is fully deleterious, the pathogen can jump across the fitness valley by obtaining two mutations at once, leading to a proportion of adapted mutants that is 20-fold lower than that in the situation where the fitness of all mutants is neutral. The negative effects of deleterious intermediates are typically substantially smaller and outweighed by the fitness advantages of the adapted mutant. Moreover, requiring a specific mutation order has a substantially smaller effect on pathogen adaptation than the effect of all intermediates being deleterious. These results can be rationalized when the number of routes of mutation available to the pathogen is calculated, providing a simple approach to estimate the effect of deleterious mutations. The calculations discussed here are applicable when the effect of deleterious mutations on the within-host adaptation of pathogens is assessed, for example, in the context of zoonotic emergence, antigenic escape, and drug resistance. IMPORTANCE Adaptation is critical for pathogens after zoonotic transmission into a new host species or to achieve antigenic immune escape and drug resistance. Using a deterministic approach, the effects of deleterious intermediate mutations on pathogen adaptation were calculated while avoiding commonly made simplifications that do not apply to large pathogen populations replicating with high mutation rates. Perhaps unexpectedly, pathogen adaptation does not halt when the intermediate mutations are fully deleterious. The negative effects of deleterious mutations are substantially outweighed by the fitness gains of adaptation. To gain an understanding of the effect of deleterious mutations on pathogen adaptation, a simple approach that counts the number of routes available to the pathogen with and without deleterious intermediate mutations is introduced. This methodology enables a straightforward calculation of the proportion of the pathogen population that will cross a fitness valley or traverse a fitness ridge, without reverting to more complicated mathematical models.
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Kamal RP, Katz JM, York IA. Molecular determinants of influenza virus pathogenesis in mice. Curr Top Microbiol Immunol 2015; 385:243-74. [PMID: 25038937 DOI: 10.1007/82_2014_388] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Mice are widely used for studying influenza virus pathogenesis and immunology because of their low cost, the wide availability of mouse-specific reagents, and the large number of mouse strains available, including knockout and transgenic strains. However, mice do not fully recapitulate the signs of influenza infection of humans: transmission of influenza between mice is much less efficient than in humans, and influenza viruses often require adaptation before they are able to efficiently replicate in mice. In the process of mouse adaptation, influenza viruses acquire mutations that enhance their ability to attach to mouse cells, replicate within the cells, and suppress immunity, among other functions. Many such mouse-adaptive mutations have been identified, covering all 8 genomic segments of the virus. Identification and analysis of these mutations have provided insight into the molecular determinants of influenza virulence and pathogenesis, not only in mice but also in humans and other species. In particular, several mouse-adaptive mutations of avian influenza viruses have proved to be general mammalian-adaptive changes that are potential markers of pre-pandemic viruses. As well as evaluating influenza pathogenesis, mice have also been used as models for evaluation of novel vaccines and anti-viral therapies. Mice can be a useful animal model for studying influenza biology as long as differences between human and mice infections are taken into account.
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Affiliation(s)
- Ram P Kamal
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA,
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Illingworth CJR, Fischer A, Mustonen V. Identifying selection in the within-host evolution of influenza using viral sequence data. PLoS Comput Biol 2014; 10:e1003755. [PMID: 25080215 PMCID: PMC4117419 DOI: 10.1371/journal.pcbi.1003755] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 06/13/2014] [Indexed: 02/07/2023] Open
Abstract
The within-host evolution of influenza is a vital component of its epidemiology. A question of particular interest is the role that selection plays in shaping the viral population over the course of a single infection. We here describe a method to measure selection acting upon the influenza virus within an individual host, based upon time-resolved genome sequence data from an infection. Analysing sequence data from a transmission study conducted in pigs, describing part of the haemagglutinin gene (HA1) of an influenza virus, we find signatures of non-neutrality in six of a total of sixteen infections. We find evidence for both positive and negative selection acting upon specific alleles, while in three cases, the data suggest the presence of time-dependent selection. In one infection we observe what is potentially a specific immune response against the virus; a non-synonymous mutation in an epitope region of the virus is found to be under initially positive, then strongly negative selection. Crucially, given the lack of homologous recombination in influenza, our method accounts for linkage disequilibrium between nucleotides at different positions in the haemagglutinin gene, allowing for the analysis of populations in which multiple mutations are present at any given time. Our approach offers a new insight into the dynamics of influenza infection, providing a detailed characterisation of the forces that underlie viral evolution. The evolution of the influenza virus is of great importance for human health. Through evolution, current influenza viruses develop the ability to infect people who have been vaccinated against earlier strains. New strains of influenza that infect birds and pigs could evolve to infect and spread between people, causing a global pandemic. The influenza virus lives within a human or animal host, so that viral evolution happens within, or in the spread between, individuals. As such, what happens to the virus during the course of an infection is a question of great interest. We here describe a statistical method that uses viral genome sequence data to measure how evolution affects the influenza virus within a single host. Studying data from infections transmitted between pigs, we find evidence for evolutionary adaptation in six of sixteen animals for which data were available. In one case, an immune response mounted by a pig against the virus is apparent. Our method provides a statistical framework for using sequence data to study viral evolution on very short timescales, enabling new research into within-host viral evolution.
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Affiliation(s)
| | - Andrej Fischer
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Ville Mustonen
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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