Identification of interaction sites between the genomic segments of influenza virus as putative novel anti-viral targets
Influenza A virus is an important pathogen that causes global disease in humans and economically important livestock species. It has a segmented RNA genome that both underpins its rapid evolution and genomic diversity and represents a potential point of intervention for interrupting the virus lifecycle. Each new virus particle specifically incorporates one copy of each of the eight segments, probably via a network of so far, poorly characterised intermolecular RNA-RNA interactions that may well differ between strains of the virus. The identification of strain-specific interactions between different genomic segments in influenza virus with a key role in efficient particle formation has the potential to reveal novel means for attenuating vaccine strains and to improve prediction of future reassortment events. In a recent proof-of-principle study  we developed a network approach to characterise interactions in multi-segmented viruses, and showed that the key interactions identified for Bluetongue virus are indeed essential for particle formation. In order to be of relevance to the more complex scenario of influenza virus assembly, this approach needs to be extended by including data on the preferred interaction sites between genomic RNA and nucleoprotein .
This is an interdisciplinary project where the successful candidate will work with Twarock and her team to build existing avian influenza data into existing software, and then implement the network approach to identify putative interactions between different genomic segments of influenza virus. Contacts that appear central from the point of view of their positions and connectivity in the interaction network will then be tested in the Digard and Shelton laboratories using viral reverse genetics and molecular biology [1,3]. The goal is to identify key RNA-RNA contacts and establish their function in virus assembly, thus paving the way for the design of novel predicitve tools and virus assembly inhibitors.
Funding: This project is eligible for a University of Edinburgh 3.5 year PhD studentship.
All candidates should have or expect to have a minimum of an appropriate upper 2nd class degree. To qualify for full funding students must be UK or EU citizens who have been resident in the UK for 3 years prior to commencement.
Applications including a statement of interest and full CV with names and addresses (including email addresses) of two academic referees, should be emailed to [Email Address Removed]
When applying please state clearly the title of the studentship and the supervisor/s in your covering letter.
 K. Al Shaikhahmed, G. Leonov, P.-Y. Sung, R.J. Bingham, R. Twarock, P. Roy (2018) Dynamic network approach for the modelling of genomic sub-complexes in multi-segmented viruses. Nucleic Acids Research (https://doi.org/10.1093/nar/gky881)
 N. Lee, V. Le Sage, A.V. Nanni, D.J. Snyder, V.S. Cooper, S.S. Lakdawala (2017) Genome-wise analysis of influenza viral RNA and nucleoprotein association. Nucleic Acids Research 45: 8968-8977
 Hutchinson, E.C., Curran, M.D., Read, E.K., Gog, J.R. and Digard, P. (2008). Mutational analysis of cis-acting RNA signals in segment 7 of influenza A virus. J. Virol. 82, 11869-11879. doi:10.1128/JVI.01634-08.