Investigating novel approaches to the detection of virus neutralising antibodies to rabies and Rift Valley fever virus

Serosurveillance is a powerful tool fundamental to understanding infectious disease dynamics. The presence of virus neutralising antibody (VNAb) in sera is considered the best evidence of infection, or indeed vaccination, and the gold standard serological assay for their detection is the virus neutralisation test (VNT). However, VNTs are labour intensive, costly and time consuming. In addition, VNTs for the detection of antibodies to highly pathogenic viruses require the use of high containment facilities, restricting the application of these assays to the few laboratories with adequate facilities. As a result, robust serological data on such viruses are limited. In this thesis I develop novel VNTs for the detection of VNAb to two important, highly pathogenic, zoonotic viruses; rabies and Rift Valley fever virus (RVFV). The pseudotype-based neutralisation test developed in this study allows for the detection of rabies VNAb without the requirement for high containment facilities. This assay was utilised to investigate the presence of rabies VNAb in animals from a variety of ecological settings. In this thesis I present evidence of natural rabies infection in both domestic dogs and lions from rabies endemic settings. The assay was further used to investigate the kinetics of VNAb response to rabies vaccination in a cohort of free-roaming dogs. The RVFV neutralisation assay developed herein utilises a recombinant luciferase expressing RVFV, which allows for rapid, high-throughput serosurveillance of this important neglected pathogen. In this thesis I present evidence of RVFV infection in a variety of domestic and wildlife species from Northern Tanzania, in addition to the detection of low-level transmission of RVFV during interepidemic periods. Additionally, the investigation of a longitudinal cohort of domestic livestock also provided evidence of rapid waning of RVF VNAb following natural infection. Collectively, the serological data presented in this thesis are consistent with existing data in the literature generated using the gold standard VNTs. Increasing the availability of serological assays will allow the generation of robust serological data, which are imperative to enhancing our understanding of the complex, multi-host ecology of these two viruses.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.