Using a comparative One Health approach to investigate the structural basis of antigenic variation among human and avian influenza viruses
Lead Research Organisation:
University of Glasgow
Department Name: College of Medical, Veterinary, Life Sci
Abstract
Human influenza viruses are estimated to cause 3-5 million cases of severe illness globally each year resulting in 250,000 to 500,000 deaths. Avian influenza viruses (AIVs) represent a threat to global poultry production and to human health through both zoonotic infection and the pandemic potential of reassortant viruses. The WHO's Global Influenza Surveillance and Response System has conducted virological surveillance for over half a century, is responsible for genetic and antigenic characterisation of circulating, and supports the selection of influenza viruses for human influenza vaccine production. Vaccination of poultry has become one of the principal practices for control of the endemic disease in many countries and human vaccination would be a vital component of the response in a pandemic situation.
The effectiveness of vaccines that exist to protect against human and avian influenza viruses are threatened by the emergence of antigenic variants. Suboptimal vaccine matching due to antigenic drift can result in vaccine failure burdening human and animal health, causing significant economic losses, and threatening food security. Influenza vaccine efficacy is highly dependent on antigenic matching of vaccine seed to circulating strains, and influenza strains are characterized by antigenic drift over time, structural changes in B-cell epitopes facilitate escape from pre-existing immunity. There is, therefore, a pressing need to better understand the molecular basis of antigenicity of the major influenza antigen, haemagglutinin. This is particularly true for AIVs which typically have received less attention and consequently about which less is known. Meanwhile, extensive resources have been invested in the antigenic characterisation of human seasonal influenza viruses, in particular influenza A H1N1 and H3N2, to guide decisions on human seasonal influenza vaccine composition. The extensive knowledge and data from human viruses can inform more rigorous and biologically informed models to apply to AIVs where there is an opportunity for significant advances to be made using a comparative One Health approach.
A biophysically-informed structural model of the immunological reactivity and receptor binding avidity of these human and avian pathogens based on the structures and amino-acid sequences of their antigenic proteins will be built. This will be used to identify the underlying factors that affect virus cross-reactivity, and hence vaccine efficacy. This model will extend previous work through greater integration of information on 3-D protein structures and the biophysics determining antibody-antigen interactions. The extensive data already generated for human influenza A viruses will be collated and used to refine this model. This refined model will then be applied to AIV, transferring knowledge from the medical field to the veterinary field. Laboratory work will be used to experimentally validate the structural model of HA phenotypic variation. Studies of AIVs will offer a provide a better understanding of the influence of changes in receptor-binding avidity on cross-reactivity, which can in turn benefit the medical field, since this has become very difficult to measure for human influenza A H3N2 viruses.
We will then use these results to predict cross-reactivity for newly emerging viruses and thereby the likelihood of vaccine escape, and to propose vaccine seed strains most likely to be effective for control of novel AIV threats benefitting veterinary vaccinology. The improved knowledge of the structural basis of variation in HA phenotype will also benefit existing methods used to predict evolutionary trajectories of influenza viruses, aiding decision makers concerned with the selection of human influenza viruses. Additionally, the biophysical model will allow predictions of previously unobserved changes to viral proteins to be made.
The effectiveness of vaccines that exist to protect against human and avian influenza viruses are threatened by the emergence of antigenic variants. Suboptimal vaccine matching due to antigenic drift can result in vaccine failure burdening human and animal health, causing significant economic losses, and threatening food security. Influenza vaccine efficacy is highly dependent on antigenic matching of vaccine seed to circulating strains, and influenza strains are characterized by antigenic drift over time, structural changes in B-cell epitopes facilitate escape from pre-existing immunity. There is, therefore, a pressing need to better understand the molecular basis of antigenicity of the major influenza antigen, haemagglutinin. This is particularly true for AIVs which typically have received less attention and consequently about which less is known. Meanwhile, extensive resources have been invested in the antigenic characterisation of human seasonal influenza viruses, in particular influenza A H1N1 and H3N2, to guide decisions on human seasonal influenza vaccine composition. The extensive knowledge and data from human viruses can inform more rigorous and biologically informed models to apply to AIVs where there is an opportunity for significant advances to be made using a comparative One Health approach.
A biophysically-informed structural model of the immunological reactivity and receptor binding avidity of these human and avian pathogens based on the structures and amino-acid sequences of their antigenic proteins will be built. This will be used to identify the underlying factors that affect virus cross-reactivity, and hence vaccine efficacy. This model will extend previous work through greater integration of information on 3-D protein structures and the biophysics determining antibody-antigen interactions. The extensive data already generated for human influenza A viruses will be collated and used to refine this model. This refined model will then be applied to AIV, transferring knowledge from the medical field to the veterinary field. Laboratory work will be used to experimentally validate the structural model of HA phenotypic variation. Studies of AIVs will offer a provide a better understanding of the influence of changes in receptor-binding avidity on cross-reactivity, which can in turn benefit the medical field, since this has become very difficult to measure for human influenza A H3N2 viruses.
We will then use these results to predict cross-reactivity for newly emerging viruses and thereby the likelihood of vaccine escape, and to propose vaccine seed strains most likely to be effective for control of novel AIV threats benefitting veterinary vaccinology. The improved knowledge of the structural basis of variation in HA phenotype will also benefit existing methods used to predict evolutionary trajectories of influenza viruses, aiding decision makers concerned with the selection of human influenza viruses. Additionally, the biophysical model will allow predictions of previously unobserved changes to viral proteins to be made.
Technical Summary
Biophysical model: A Bayesian model of the genotype-antigenic phenotype relationship will extend previous models by (a) incorporating additional parameters to better describe virus-antibody and receptor binding; (b) accounting for 3-D haemagglutinin (HA) structure allowing spatial inference of the extent of epitopes; and (c) developing a matrix describing the general antigenic distance of amino acid pairs allowing inference across the HA structure.
Human influenza model refinement: The biophysical model will be applied to human influenza A H1N1 and H3N2 data consisting largely of titres haemagglutinin inhibition (HI) and virus neutralisation assays and genetic sequence data for HA1. This process will be used to test and refine the model, analysing existing HA structures to determine spatial relationships between residues within epitopes and binding sites, incorporating existing avidity analyses to parameterize the biophysical model, and tuning the substitution model using antigenic and sequence data.
Avian influenza data and modelling: Antigenic and genetic data from avian influenza subtypes will be collated and modelled. The human influenza virus model will now be refined on the avian data. The phenotypic impact of amino acid substitutions in the AIV HA will be characterised and contribution to vaccine escape will be assessed. The phenotypic impact of previously unobserved amino acid substitutions will also be predicted.
Model validation: Mutant recombinant viruses will be generated using site-directed mutagenesis and reverse genetics using available HA backbones. Recombinant viruses will be assessed using the HI assay performed with polyclonal antiserum and monoclonal antibodies. Changes in HI titre, relative to the backbone, will be attributed to changes in antigenicity and avidity. Changes in receptor binding avidity will be directly assessed using the receptor-binding destroying enzyme assay and surface biolayer interferometry.
Human influenza model refinement: The biophysical model will be applied to human influenza A H1N1 and H3N2 data consisting largely of titres haemagglutinin inhibition (HI) and virus neutralisation assays and genetic sequence data for HA1. This process will be used to test and refine the model, analysing existing HA structures to determine spatial relationships between residues within epitopes and binding sites, incorporating existing avidity analyses to parameterize the biophysical model, and tuning the substitution model using antigenic and sequence data.
Avian influenza data and modelling: Antigenic and genetic data from avian influenza subtypes will be collated and modelled. The human influenza virus model will now be refined on the avian data. The phenotypic impact of amino acid substitutions in the AIV HA will be characterised and contribution to vaccine escape will be assessed. The phenotypic impact of previously unobserved amino acid substitutions will also be predicted.
Model validation: Mutant recombinant viruses will be generated using site-directed mutagenesis and reverse genetics using available HA backbones. Recombinant viruses will be assessed using the HI assay performed with polyclonal antiserum and monoclonal antibodies. Changes in HI titre, relative to the backbone, will be attributed to changes in antigenicity and avidity. Changes in receptor binding avidity will be directly assessed using the receptor-binding destroying enzyme assay and surface biolayer interferometry.
Organisations
- University of Glasgow (Lead Research Organisation)
- Francis Crick Institute (Collaboration)
- University of Cologne (Collaboration)
- Experimental Zooprophylactic Institute of the Venezie (Collaboration)
- Peter Doherty Institute for Infection and Immunity (Collaboration)
- National Institute of Infectious Diseases (Collaboration)
- University of Edinburgh (Fellow)
People |
ORCID iD |
William Harvey (Principal Investigator / Fellow) |
Publications
Wright DW
(2022)
Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer.
in Virus evolution
Willett BJ
(2022)
Publisher Correction: SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway.
in Nature microbiology
Willett BJ
(2022)
SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway.
in Nature microbiology
Scolamacchia F
(2021)
Different environmental gradients associated to the spatiotemporal and genetic pattern of the H5N8 highly pathogenic avian influenza outbreaks in poultry in Italy.
in Transboundary and emerging diseases
Peacock TP
(2018)
The molecular basis of antigenic variation among A(H9N2) avian influenza viruses.
in Emerging microbes & infections
Peacock TP
(2021)
Genetic determinants of receptor-binding preference and zoonotic potential of H9N2 avian influenza viruses.
in Journal of virology
Meng B
(2021)
Recurrent emergence of SARS-CoV-2 spike deletion H69/V70 and its role in the Alpha variant B.1.1.7.
in Cell reports
Maake L
(2020)
Genetic Basis of Antigenic Variation of SAT3 Foot-And-Mouth Disease Viruses in Southern Africa.
in Frontiers in veterinary science
Iannucci S
(2023)
The SARS-CoV-2 Spike Protein Mutation Explorer: using an interactive application to improve the public understanding of SARS-CoV-2 variants of concern.
in Journal of visual communication in medicine
Harvey WT
(2021)
SARS-CoV-2 variants, spike mutations and immune escape.
in Nature reviews. Microbiology
Harvey WT
(2023)
A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses.
in PLoS computational biology
Harvey WT
(2021)
Spatiotemporal reconstruction and transmission dynamics during the 2016-17 H5N8 highly pathogenic avian influenza epidemic in Italy.
in Transboundary and emerging diseases
Forde TL
(2020)
Genomic and Immunogenic Protein Diversity of Erysipelothrix rhusiopathiae Isolated From Pigs in Great Britain: Implications for Vaccine Protection.
in Frontiers in microbiology
Davis C
(2021)
Reduced neutralisation of the Delta (B.1.617.2) SARS-CoV-2 variant of concern following vaccination.
in PLoS pathogens
Davies V
(2019)
Improving the identification of antigenic sites in the H1N1 influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model.
in Journal of the Royal Statistical Society. Series C, Applied statistics
Description | Contribution to reports on recent antigenic evolution of human influenza viruses for the WHO's twice-yearly vaccine selection meetings |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Contribution to a national consultation/review |
Description | IZSve, Italy collaboration |
Organisation | Experimental Zooprophylactic Institute of the Venezie |
Country | Italy |
Sector | Public |
PI Contribution | I have been working to characterise the epidemiological dynamics of the 2017 avian influenza outbreak in Italy using a range of quantitative methods for evolutionary analysis. Moving forward we are interested in identifying environmental factors that govern the spread of epidemics of avian influenza in order to inform future control measures. |
Collaborator Contribution | My partners at the Instituto Zooprofilattico Sperimentale delle Venezie, Italy are responsible for monitoring incidence of avian influenza in Italy and are now the new EU reference lab for avian influenza. They include veterinarians who perform investigations at farms and identify and virologists who perform genetic sequencing of identified influenza viruses. |
Impact | This collaboration has produced one publication (Harvey et al. 2019 in Transboundary Emerging Diseases) in a special issue on avian influenza. A second manuscript with the same journal is currently under revision. The results of the first manuscript have helped evaluate the effectiveness of control measures implemented during the epidemic and have provided support for a change in policy to increase influenza surveillance in wild birds. Moving forward, we aim to build a model of farm risk that can help inform control measures. This is a multi-disciplinary collaboration involving mathematical modellers, veterinarians, epidemiologists and virologists. |
Start Year | 2017 |
Description | WHO CCs |
Organisation | Francis Crick Institute |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | My role in this collaboration is to provide statistical modelling of genotype-phenotype relationships in recently circulating seasonal human influenza viruses. These data are generated by the collaborating centres as part of the WHO global influenza surveillance and response system. |
Collaborator Contribution | The WHO Collaborating Centres based in London, Australia and Japan are the world leaders in influenza surveillance: two of five WHO CCs responsible for the worldwide genetic and antigenic surveillance of human influenza viruses. Key among their responsibilities, they meet twice yearly to provide the WHO recommendations on the composition of human influenza vaccines. In recent years they have consulted modelling groups in preparation for these meetings. |
Impact | With collaborators in Glasgow and the University of Cologne, I have contributed to reports made to the twice-yearly WHO vaccine composition meetings. These reports summarise the results of the models I have developed as part of this fellowship. These models quantify the effect of specific amino acid changes on antigenic phenotype and help to show antigenic novelty present in circulating viruses. |
Start Year | 2014 |
Description | WHO CCs |
Organisation | National Institute of Infectious Diseases |
Country | Japan |
Sector | Public |
PI Contribution | My role in this collaboration is to provide statistical modelling of genotype-phenotype relationships in recently circulating seasonal human influenza viruses. These data are generated by the collaborating centres as part of the WHO global influenza surveillance and response system. |
Collaborator Contribution | The WHO Collaborating Centres based in London, Australia and Japan are the world leaders in influenza surveillance: two of five WHO CCs responsible for the worldwide genetic and antigenic surveillance of human influenza viruses. Key among their responsibilities, they meet twice yearly to provide the WHO recommendations on the composition of human influenza vaccines. In recent years they have consulted modelling groups in preparation for these meetings. |
Impact | With collaborators in Glasgow and the University of Cologne, I have contributed to reports made to the twice-yearly WHO vaccine composition meetings. These reports summarise the results of the models I have developed as part of this fellowship. These models quantify the effect of specific amino acid changes on antigenic phenotype and help to show antigenic novelty present in circulating viruses. |
Start Year | 2014 |
Description | WHO CCs |
Organisation | Peter Doherty Institute for Infection and Immunity |
Department | WHO Collaborating Centre for Reference and Research on Influenza (VIDRL) |
Country | Australia |
Sector | Charity/Non Profit |
PI Contribution | My role in this collaboration is to provide statistical modelling of genotype-phenotype relationships in recently circulating seasonal human influenza viruses. These data are generated by the collaborating centres as part of the WHO global influenza surveillance and response system. |
Collaborator Contribution | The WHO Collaborating Centres based in London, Australia and Japan are the world leaders in influenza surveillance: two of five WHO CCs responsible for the worldwide genetic and antigenic surveillance of human influenza viruses. Key among their responsibilities, they meet twice yearly to provide the WHO recommendations on the composition of human influenza vaccines. In recent years they have consulted modelling groups in preparation for these meetings. |
Impact | With collaborators in Glasgow and the University of Cologne, I have contributed to reports made to the twice-yearly WHO vaccine composition meetings. These reports summarise the results of the models I have developed as part of this fellowship. These models quantify the effect of specific amino acid changes on antigenic phenotype and help to show antigenic novelty present in circulating viruses. |
Start Year | 2014 |
Description | WHO CCs |
Organisation | University of Cologne |
Country | Germany |
Sector | Academic/University |
PI Contribution | My role in this collaboration is to provide statistical modelling of genotype-phenotype relationships in recently circulating seasonal human influenza viruses. These data are generated by the collaborating centres as part of the WHO global influenza surveillance and response system. |
Collaborator Contribution | The WHO Collaborating Centres based in London, Australia and Japan are the world leaders in influenza surveillance: two of five WHO CCs responsible for the worldwide genetic and antigenic surveillance of human influenza viruses. Key among their responsibilities, they meet twice yearly to provide the WHO recommendations on the composition of human influenza vaccines. In recent years they have consulted modelling groups in preparation for these meetings. |
Impact | With collaborators in Glasgow and the University of Cologne, I have contributed to reports made to the twice-yearly WHO vaccine composition meetings. These reports summarise the results of the models I have developed as part of this fellowship. These models quantify the effect of specific amino acid changes on antigenic phenotype and help to show antigenic novelty present in circulating viruses. |
Start Year | 2014 |
Description | COG-UK-ME online dashboard |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | In collaboration with others who became part of the COVID-19 Genomics UK (COG-UK) consortium, I was part of a small team who designed the COG-UK Mutation Explorer online dashboard, an online platform to explore mutations in SARS-CoV-2 viruses sequenced in the UK. In addition to allowing monitoring and access to underlying data, the dashboard places mutations in circulating viruses in the context of data on antigenicity and drug resistance that has become available in the scientific literature. The dashboard has recorded thousands of users from countries around the world, leading to collaboration with industry, media requests and engagement with the general public via social media. |
Year(s) Of Engagement Activity | 2020,2021,2022 |
URL | https://sars2.cvr.gla.ac.uk/cog-uk/ |