Proteome-level diversity in RNA viruses

Studentship strategic priority area: Basic and Clinical Research
Keywords: Influenza, Proteomics, Mass spectrometry, Mutation, Evolution

Influenza viruses are major causes of respiratory disease globally with seasonal outbreaks responsible for hundreds of thousands of deaths worldwide every year. One of the main driving forces behind the success of influenza viruses is their capacity for mutation, brought about by high error rates in replication of the RNA genome. The effects of mutation in influenza virus genomes are compounded by errors in the transcription of viral mRNA, as this is performed by the same enzyme responsible for viral genome replication. Although mRNA mutations are not heritable, functional selection applies to the proteins they encode when they are translated, modified, trafficked and assembled into virions. As a result, mapping diversity in the pool of proteins in influenza virions can predict 'functionally permitted' mutations that could be a substrate for influenza virus evolution through natural selection.

This project will initially make use of a novel workflow to re-analyse mass spectrometry proteomics datasets to assess protein diversity within influenza virions, 'deep sequencing the viral proteome.' We expect to identify the effects of both point mutations and internal deletions that arise from truncated viral mRNA. We will identify sites in viral proteins that tolerate or resist mutation, map these to viral protein structures in order to identify the potential effects of amino acid changes on protein structure and function. This proteome-level variation will be compared to genomic and transcriptomic data and to variation in existing influenza genome sequence data. As such, the plasticity of the viral proteome will be measured in relation to the viral genome, giving insight into where adaptation can be tolerated in viral proteins. We will then build on this assessment of mutational tolerance in influenza virus proteins. Using a combination of in silico prediction and molecular virology studies we will assess to the potential impact of protein heterogeneity on the immune response and on the development of therapeutic/vaccine targets for influenza viruses. We will also leverage our data to engineer functionally permitted tags into influenza viruses by reverse genetics, creating a platform for further molecular biology and imaging studies.