I have a keen interest interest in the development of quantitative methods for exploring the antigenic evolution of both human and avian influenza viruses. Influenza A viruses are characterised by rapid antigenic drift: amino acid substitutions cause biophysical structural changes to B-cell epitopes that facilitate escape from pre-existing immunity induced by infection or immunity. Accurate quantification of the antigenic impact of specific amino acid substitutions is a prerequisite for predicting the fitness and evolutionary success of particular genotypes. This information is hugely important when decisions of which influenza viruses to include in vaccine form
My work on influenza is carried out in collaboration with Prof. John McCauley and the Worldwide Influenza Centre at the Francis Crick Institute, one of six centres in the world responsible for analysing influenza viruses circulating in the human population, overseen by the World Health Organisation (WHO), and Prof. Munir Iqbal’s Avian Influenza Group at the Pirbright Institute.
My PhD was based at the University of Glasgow under the supervision of Richard Reeve, Dan Haydon, and John McCauley (The Francis Crick Institute) and focused on the antigenic drift of seasonal influenza viruses. Viruses of the influenza A subtypes A(H1N1) and A(H3N2) circulate globally in the human population causing seasonal epidemics and requiring a global surveillance program responsible for on-going antigenic characterisation and vaccine composition recommendations. The identification of emerging antigenic variants among circulating influenza viruses is critical to the vaccine selection process, with vaccine effectiveness maximised when constituents are antigenically similar to circulating viruses.
Analysing antigenic and genetic data generated at the The Worldwide Influenza Centre at the Francis Crick Institute (formerly the WHO Collaborating Centre for Reference and Research on Influenza at the National Institute for Medical Research), I have focused on the application of statistical models to these data in order to to identify molecular determinants of antigenic phenotype, quantify the antigenic impact of specific amino acid substitutions, and to make predictions of antigenicity from sequence. To find out more about my PhD work, find my thesis online.
Read more: Identification of low- and high-impact hemagglutinin amino acid substitutions that drive antigenic drift of influenza A(H1N1) viruses
Antigenic variation among RNA viruses of livestock and poultry
Working in collaboration with researchers at the Pirbright Institute and the ARC-Onderstepoort Veterinary Institute (OVI), Richard Reeve and I are involved in efforts to determine the genetic basis of antigenic variation among multiple serotypes of foot-and-mouth disease virus (FMDV). Globally, FMDV is one of the most economically important livestock diseases and is still widely distributed. Novel genetic and antigenic variants continue to emerge within each of the six recently observed serotypes of the virus, which has confounded attempts to develop vaccines that protect against a broad range viruses, even within serotypes. Such broad-range protection is one of the major goals underpinning current research in FMDV vaccine development, making it vitally important to identify those areas of the capsid that are targets for protective immunity.
Read more: Tracking the antigenic evolution of foot-and-mouth disease virus
More recently, Richard and I have applied these methods to avian influenza A(H9N2) collaborating with Thomas Peacock and Munir Iqbal at the Pirbright Institute. A(H9N2) viruses are a major cause of poultry production losses across Asia, vaccination is widespread however the emergence of antigenic variants is a significant factor compromising their efficacy. Most knowledge of the antigenicity of A(H9N2) viruses is derived from the results on monoclonal antibody escape studies in mice. Through this work we hope to reveal more about the antigenic evolution of natural isolates and the genetic differences among A(H9N2) viruses that contribute to loss of vaccine effectiveness.
Richard and I have also been working with Vinny Davies and Dirk Husmeier who are based within the School of Mathematics and Statistics in Glasgow. Vinny recently completed his PhD in Glasgow and has interests in the application of Markov chain Monte Carlo methods to biological data and the development of improved Bayesian methods for variable selection. Identifying the genetic changes involved in antigenic evolution usually requires distinguishing between large numbers of, often highly correlated, variables. We have successfully applied mixed-effects models using slab and spike priors to FMDV and influenza datasets detecting antigenic residues. To read about this work in detail take a look at Vinny’s thesis.
Read more: Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability
Sparse Bayesian variable selection for the identification of antigenic variability in the foot-and-mouth disease virus