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Development of a Differentiation of Infected from Vaccinated Animals (DIVA) diagnostic test for use in conjunction with inactivated louping ill virus vaccine and application to field surveillance

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  • Full or part time
    Dr J Daly
    Dr K Gough
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Project title: Development of a Differentiation of Infected from Vaccinated Animals (DIVA) diagnostic test for use in conjunction with inactivated louping ill virus vaccine and application to field surveillance

Principal supervisor: Dr Janet Daly

Other supervisors: Dr Mara Rocchi (Moredun Institute), Dr Kevin Gough (SVMS)

Background: The School of Veterinary Medicine and Science (SVMS) undertakes research on many key aspects of companion animals and livestock health and production. Research at the School is integrated into the University structure with established world class research in biomedical sciences within the other University Schools. Research undertaken at the School is relevant to both Veterinary Medicine and Science and Comparative and Human Medicine.

Project description:
Louping ill virus (LIV) is a tick-borne virus that is endemic in the Scottish uplands. It causes neurological disease in sheep, which can be fatal. The most effective control measure against LIV is vaccination. Surveillance and vaccine effectiveness studies in the field are hampered by the difficulty in determining whether antibodies detected by the traditional haemagglutination inhibition test are a result of infection or vaccination. Recombinant vaccines that do not express all of the viral proteins allow a diagnostic test to be developed that detects antibodies to proteins only present during natural infection enabling a ‘distinguishing infected from vaccinated animals’ (DIVA) strategy to be employed. However, development of such vaccines is costly and inactivated virus vaccines continue to predominate in livestock vaccination programmes.

The traditional technique of phage display has been revolutionized by combining it with next generation sequencing and bioinformatics analysis. In this project, the next generation phage display approach will be applied to identify peptides recognized by LIV- infected but not vaccinated sheep. These peptides reflect subtle differences in the virus proteins that result from the effect of the chemical treatments used to inactivate the virus for inclusion in the vaccine. The peptides identified will be synthesized and used to develop and validate an ELISA-based assay to detect infection-specific antibodies. This assay will be applied in surveillance studies to evaluate the true prevalence of LIV infection in the field.

The 3 year project is split between two sites, the University of Nottingham’s Sutton Bonington campus and the Moredun Institute, Edinburgh. It is anticipated that the majority of the time will be spend at the Nottingham site initially, with the final stages being conducted at the Moredun Institute.

Further information and Application
Applicants should have a minimum of a 2.1 undergraduate degree or a minimum of a 2.2 degree and a master’s degree in biological or veterinary sciences or similar subjects.

Informal enquiries may be addressed to the principal supervisor: [email protected]

Candidates should apply online http://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx and include a CV. Queries regarding the application process should be addressed to Postgraduate Admissions (email: [email protected])

Start Date:
1st October 2017 or as soon as possible thereafter.

Closing date:
The position will be filled when a suitable candidate has been identified. Early application is strongly encouraged.




Funding Notes

Must be eligible for home / EU fees. The studentship is available for 3 years and provides the standard UK/EU postgraduate stipend. Funding restrictions apply to international students

How good is research at University of Nottingham in Agriculture, Veterinary and Food Science?

FTE Category A staff submitted: 111.45

Research output data provided by the Research Excellence Framework (REF)

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