Modified vaccinia virus Ankara (MVA) has been used extensively as a recombinant vector for delivery of antigens from diverse pathogens. Its ability to generate strong antigen specific CD8+ T cell responses in humans has been shown in clinical trials of novel vaccines against malaria, tuberculosis, HIV I AIDS, influenza and cancer. The work in this thesis describes the use of BAC recombineering technology to harness the endogenous regulatory signal (promoter) that drives the expression of non-essential open reading frames (ORFs) in MVA for immunogenic expression of a recombinant antigen. Replacement of the ORFs of four non-essential genes in MVA; C11R, F11l, A44L and B8R with an epitope tagged luciferase positioned to use the same endogenous promoter showed early transgene expression equal to or slightly higher than traditional p7.5 and short synthetic promoter (SSP) constructs. The frequency of antigen-specific CD8+ T cell induced in mice by single dose MVA or adenovirus-prime, rMVA-boost vaccination showed equivalent or slightly higher responses by the endogenous promoters compared to the traditional p7.5 and SSP constructs. Assessment of the growth rate of these viruses showed they were unimpaired and the insertions were genetically stable. Furthermore, the endogenous promoter driven insertion loci of B8R and C11R were used for the construction of a bivalent MVA expressing an epitope tagged luciferase (rLucPb9) and a Photinus pyralis (pLuc) luciferase. The frequency of antigen-specific CD8+ T cells induced in mice by bivalent MV A was equivalent to single-pLuc and single-Pb9 recombinants co-administered as a mixture, at separate sites or administered alone following single dose MV A vaccination but slightly lower for Pb9-specific CD8+ T cell following adenovirus-prime, rMVA-boost.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:589603 |
| Date | January 2012 |
| Creators | Orubu, Toritse |
| Contributors | Gilbert, Sarah ; Cottingham, Matt |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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