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"Pathogen Phylodynamics: Unifying Evolution, Infection and Immunity"

Mid-Term Report Summary - PATHPHYLODYN (Pathogen Phylodynamics: Unifying Evolution, Infection and Immunity)

The project PATHPHYLODYN aims to develop and apply new mathematical, computational and statistical methods in order to analyse the vast and increasing amount of genetic data from infectious diseases. If such methods can be created then genetic data has the potental to allow us to ask new questions about how pathogens cause infection and how they transmit and cause epidemics. To achieve this aim we are bringing together concepts from different areas of biology, including population dynamics, phylogenetics, population genetics, and spatial ecology. The project is working on several different lines of research. First, we have developed new methods for estimating, from very large sets of virus genomes, how fast viruses are adapting and evolving. These techniques have been applied to important human viruses including HIV-1 and influenza. Second, we are exploring new mathematical techniques for pathogen genome analysis that require less computation time than previous approaches. This largely theoretical work has involved the application of ideas from engineering to population biology for the first time. Third, we are investigating how immune responses and virus populations respond and adapt in response to each other. This work includes the analysis of a new type of genetic data, immune repertoire sequence data, which provide a description of the diversity of antibodies within an individual. These sequences allow us to directly observe how the immune system fine-tunes itself in the presence of a virus infection. Specifically, we are developing new techniques derived from evolutionary theory for the analysis of immune repertoire sequences. These methods are providing new insights into how antibodies diversify and change in frequency during HIV-1 infection. Lastly, we have been using evolutionary methods to analyse the Zika virus epidemic that emerged in the Americas in 2015. Our work on Zika viruses has helped to reveal the origins of this epidemic and its subsequent spread through South America, Central America, the Caribbean, and USA. As part of our research we create new computer code and software packages, which we make openly-available for other researchers around the world to use.