Computational selection of novel antigenic targets in the Mycobacterium bovis proteome
|Title:||Computational selection of novel antigenic targets in the Mycobacterium bovis proteome||Authors:||Farrell, Damien
Malone, Kerri M.
Chubb, Anthony J.
Gordon, Stephen V.
|Permanent link:||http://hdl.handle.net/10197/7815||Date:||27-Jun-2014||Abstract:||The discovery of novel antigens is an essential requirement in devising new diagnostics for use in both M. tuberculosis (Mtb) and M. bovis control programmes. Reverse vaccinology is now a feasible method of extracting potential immunogenic epitopes from bacterial genomes to reduce the cost of experimental screening of antigens for anamnestic responses in infected hosts. Since a significant focus has been on the role of CD4+ T cells, the ability to predict peptide binding to MHC-II molecules is seen as a key step in discovery.Previous antigen-mining experiments for identification of novel diagnostic or vaccine candidates for human and bovine TB follow a targeted approach, where specific groups of proteins suspected to contain likely candidates are identified and evaluated for mmunogenicity. A disadvantage of those approaches is that they are restricted to a relatively small set of proteins biased by the initial selection criteria. Our objective was to computationally select antigens in a less biased manner.||Type of material:||Conference Publication||Keywords:||Tuberculosis||Language:||en||Status of Item:||Not peer reviewed||Conference Details:||EMBO Conference on Microbiology after the genomics revolution: GENOMES 2014, 24-27 June 2014, Pasteur Institute, Paris, France|
|Appears in Collections:||Conway Institute Research Collection|
Veterinary Medicine Research Collection
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