Abstract
The elucidation of the genomes of pathogenic mycobacteria and the application of bioinformatic tools has greatly assisted the process of defining antigenic proteins for diagnosis of, and subunit vaccination against, bovine tuberculosis. By applying in silico genome comparisons or transcriptome comparisons, it was possible to prioritise potentially specific and immunogenic proteins for testing in infected or vaccinated cattle. These approaches led to the identification of antigens supporting discrimination of infected from vaccinated animals (DIVA diagnosis) or subunit vaccine candidates. Some progress has also been made to develop algorithms predicting peptides binding to bovine major histocompatibility complex class II molecules. The following chapter will review these advances and consider them in the context of bovine TB vaccine development programmes.
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These studies were supported by the Department for Environment, Food and Rural Affairs UK and the Wellcome Trust.
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Vordermeier, M., Jones, G.J., Sampson, S., Gordon, S.V. (2013). Post-genomic Antigen Discovery: Bioinformatical Approaches to Reveal Novel T Cell Antigens of Mycobacterium bovis . In: Flower, D., Perrie, Y. (eds) Immunomic Discovery of Adjuvants and Candidate Subunit Vaccines. Immunomics Reviews:, vol 5. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5070-2_4
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