Professor Andrew Rambaut University of Edinburgh UK
Combining whole genome sequencing and network models to understand the epidemiology of bovine TB in the UK
Dr Roman Biek, University of Glasgow, UK
Quantifying transmission dynamics of pathogens infecting multiple host species can pose significant research challenges, especially when the sampling process is biased towards certain types of host. This is exemplified by Mycobacterium bovis, the bacterium causing bovine TB (bTB) in cattle. In the UK, badgers are considered an important wildlife reservoir for bTB, which is thought to prevent the successful eradication of the disease from cattle. However, despite considerable research effort, the epidemiological role badgers play in maintaining and spreading bTB to cattle is still poorly understood. Here, we show how whole genome sequencing (WGS) technology can be combined with high-resolution data on contact networks of cattle to shed new light onto this problem. Focussing on a small cluster of infected cattle and badger samples from Northern Ireland, we provide the first direct genetic evidence of M bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. In addition to providing novel insights into bTB epidemiology, even at extremely local scales, our study suggests that WGS based on more extensive sampling will allow quantification of the extent and direction of M bovis transmission between cattle and badgers, especially in situations where detailed demographic and contact data for cattle are also available.
Incorporating geographic information systems data into phylogenetic analysis
Dr Rebecca Gray, University of Oxford, UK
Geographic information systems data (GIS) has been a valuable tool to correlate the spread of infectious diseases with environmental variables. Independently, molecular epidemiology relies upon pathogen genetic mutations that segregate in space and time, which are used in increasingly sophisticated evolutionary models to infer migration paths, rates, and population demography. Clearly a comprehensive approach that incorporates both GIS and evolutionary analyses would allow for rigorous hypothesis testing and greater understanding of the forces governing disease movements. I willdiscuss the advantages of using GIS in molecular epidemiological studies aswell as some of the current computational and theoretical challenges. I will present some recent work on West Nile Virus and rabies virus in which we have used information gained from the phylogeny on migration patterns within thecontext of GIS.
Antigenic flux in the influenza virus population
Dr Trevor Bedford, University of Edinburgh, UK
Owing to rapid mutation, the evolution of the influenza virus occurs on a human timescale; rather than being forced to infer past evolutionary events, we can observe them in near real-time. While individuals develop long-lasting immunity to particular influenza strains after infection, antigenic mutations to the influenza virus genome result in proteins that are recognized to a lesser degree by the human immune system, leaving individuals susceptible to future infection. Mutations are only transiently advantageous; the virus population must keep evolving antigenically to stay ahead of developing human immunity. This talk focuses the process of antigenic innovation and the spread of novel strains through the human population. In this case, we have serological data from the hemagglutination inhibition (HI) assay comparing the level of cross-reactivity between different strains of influenza, as well as sequence data across strains. Here, we use a probabilistic framework called Bayesian multidimensional scaling (BMDS) to find a single consistent representation of antigenic distances between viruses by placing strains on a two-dimensional map. We integrate sequence evolution by treating BMDS location as a continuous diffusion across the phylogenetic tree. In this context, we examine the process of antigenic drift and investigate historical choices in vaccine strain by the World Health Organization.
Multiscale evolutionary dynamics of HIV
Dr Katrina Lythgoe, Imperial College London, UK
Through the use of next-generation sequencing, evidence is growing that ancestral HIV-1 genotypes (i.e. the viral genotypes observed during early infection) are, at least sometimes, preferentially transmitted over the majority virus circulating in a donor at the time of transmission. This ancestral virus probably persists at a low frequency within hosts due to the cycling of virus through very long-lived memory CD4+ T-Cells, a process that we call ‘store and retrieve’. We show how incorporating the store and retrieve process into our models can help explain two puzzling phenomena: (1) the fact that HIV-1 appears to evolve much faster within individuals than it does at the epidemic level and (2) the low levels of resistance found in developed countries despite the widespread use of antiretroviral drugs. The preferential transmission of ancestral virus needs to be properly integrated into evolutionary models if we are to accurately predict the evolution of immune escape, drug resistance and virulence in HIV-1 at the population level. Moreover, early infection viruses should be the major target for vaccine design, since these are the viral strains primarily involved in transmission.