title: Antigen mining with iterative genome screens identifies novel diagnostics for the Mycobacterium tuberculosis complex.
abstract: The definition of antigens for the diagnosis of human and bovine tuberculosis is a research priority. If diagnosis is to be used alongside Mycobacterium bovis BCG-based vaccination regimens, it will be necessary to have reagents that allow the discrimination of infected and vaccinated animals. A list of 42 potential M. bovis-specific antigens was prepared by comparative analysis of the genomes of M. bovis, M. avium subsp. avium, M. avium subsp. paratuberculosis, and Streptomyces coelicolor. Potential antigens were tested by applying them in a high-throughput peptide-based screening system to M. bovis-infected and BCG-vaccinated cattle and to cattle without prior exposure to M. bovis. A response hierarchy of antigens was established by comparing responses in infected animals. Three antigens (Mb2555, Mb2890, and Mb3895) were selected for further study, as they were strongly recognized in experimentally infected animals but with low or no frequency in BCG-vaccinated and naïve cows. Interestingly, all three antigens were recognized in animals vaccinated against Johne's disease, suggesting the presences of epitopes cross-reacting with M. avium subsp. paratuberculosis antigens. Eight peptides from the three antigens studied in detail were identified as immunodominant and were characterized in terms of major histocompatibility complex class II restriction element usage and shown to be restricted through both DR and DQ molecules. Reasons for antigenic cross-reactivity with M. avium subsp. paratuberculosis and refinement of the in silico strategy to predict such cross-reactivity from the primary protein sequence will be discussed. Evaluation of the peptides identified from the three dominant antigens by use of larger field studies is now a priority.
authors.affiliation: TB Research Group, Veterinary Laboratories Agency-Weybridge, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom. k.ewer@vla.defra.gsi.gov.uk
authors.forename: Katie
authors.initials: K
authors.lastname: Ewer
authors.forename: Paul
authors.initials: P
authors.lastname: Cockle
authors.forename: Steve
authors.initials: S
authors.lastname: Gordon
authors.forename: Huma
authors.initials: H
authors.lastname: Mansoor
authors.forename: Marc
authors.initials: M
authors.lastname: Govaerts
authors.forename: Karl
authors.initials: K
authors.lastname: Walravens
authors.forename: Sylvie
authors.initials: S
authors.lastname: Marché
authors.forename: Glyn
authors.initials: G
authors.lastname: Hewinson
authors.forename: Martin
authors.initials: M
authors.lastname: Vordermeier
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D000942:Antigens, Bacterial / Q000235:genetics* / Q000276:immunology*; D002417:Cattle; D023281:Genomics; D006801:Humans; D008969:Molecular Sequence Data; D009162:Mycobacterium avium / Q000235:genetics; D009163:Mycobacterium bovis / Q000235:genetics; D009169:Mycobacterium tuberculosis / Q000235:genetics / Q000276:immunology*; D010455:Peptides; D016415:Sequence Alignment; D014376:Tuberculosis / Q000175:diagnosis* / Q000276:immunology
chemical_list: D000942:Antigens, Bacterial; D010455:Peptides