Convergent evolution of PICIs-mediated phage interference

Staphylococcal pathogenicity islands (SaPIs), the prototype members of the family of phage inducible chromosomal islands (PICIs), are extremely mobile phage satellites, which are transferred between bacterial hosts after their induction by a helper phage. The intimate relationship between SaPIs and their helper phages is one of the most studied examples of virus satellite interactions in prokaryotic cells. SaPIs encode and disseminate virulence and fitness factors, representing a driving force for bacterial adaptation and pathogenesis. Many SaPIs encode a conserved morphogenetic operon, including a core set of genes whose function allows them to parasitize and exploit the phage life cycle. One of the central mechanisms of this molecular piracy is the specific packaging of the SaPI genomes into reduced sized capsid structures derived from phage proteins. Pac phages were classically thought to be the only phages involved in the mobilisation of phage-mediated virulence genes, including the transfer of SaPIs within related and non-related bacteria. This study presents the involvement of S. aureus cos phages in the intra- and intergeneric transfer of cos SaPIs for the first time. A novel example of molecular parasitism is shown, by which this newly characterised group of cos SaPIs uses two distinct and complementary mechanisms to take over the helper phage packaging machinery for their own reproduction. SaPIbov5, the prototype of the cos SaPIs, does not encode the characteristic morphogenetic operon found in pac SaPIs. However, cos SaPIs features both pac and cos phage cleavage sequences in their genome, ensuring SaPI packaging in small- and full-sized phage particles, depending on the helper phage. Moreover, cos-site packaging in S. aureus was shown to require the activity of a phage HNH nuclease. The HNH protein functions together with the large terminase subunit, triggering cleavage and melting of the cos-site sequence. In addition, a novel piracy strategy, severely interfering with the helper phage reproduction, was identified in cos SaPIs and characterised. This mechanism of piracy depends on the cos SaPI-encoded ccm gene, which encodes a capsid protein involved in the formation of small phage particles, modifying the assembling process via a scaffolding mechanism. This strategy resembles the ones described for pac SaPIs and represents a remarkable example of convergent evolution. A further convergent mechanism of capsid size-reduction was identified and characterised for the Enterococcus faecalis EfCIV583 pathogenicity island, another member of the PICI family. In this case, the self-encoded CpmE conducts this molecular piracy through a putative scaffolding function. Similar to cos SaPIs, EfCIV583 carries the helper phage cleavage sequence in its genome enabling its mobilisation by the phage terminase complex. The results presented in this thesis show how two examples of non-related members of the PICI family follow the same evolutionary convergent strategy to interfere with their helper phage. These findings could indicate that the described strategies might be widespread among PICIs and implicate a significant impact of PICIs mediated-virulence gene transfer in bacterial evolution and the emergence of pathogenic bacteria.

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.