Screening of predicted secreted antigens from Mycobacterium bovis identifies potential novel differential diagnostic reagents

Gareth J. Jones, R. Glyn Hewinson, H. Martin Vordermeier

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

27 Dyfyniadau (Scopus)

Crynodeb

To date, the most promising vaccination strategies for the control of bovine tuberculosis (TB) focus on improving the efficacy of Mycobacterium bovis bacillus Calmette-Guérin (BCG). However, vaccination with BCG results in sensitization of animals to bovine tuberculin and compromises tests currently used for diagnosis of bovine TB infection. Thus, the development of specific diagnostic reagents capable of discriminating between infected and uninfected vaccinated animals (DIVA) is of high priority. To test the hypothesis that M. bovis-secreted proteins are likely to contain immunogenic antigens that can be used to increase the specificity of diagnostic tests, we screened 379 pools of overlapping peptides representing 119 antigens for their ability to stimulate a gamma inferferon (IFN-γ) response in vitro using whole blood from both TB reactor and BCG-vaccinated animals. Peptide pools representing antigens Rv3020c and Rv2346c induced responses in 61% and 57% of the TB reactor animals, respectively, without inducing responses in any BCG-vaccinated animal studied. Furthermore, individual peptides contained within pools recognized by BCG vaccinates were identified that were specific and induced IFN-γ responses in TB reactor animals. From these results, we constructed a cocktail of nine peptides representing multiple antigen targets that was recognized by 54% of TB reactor animals but also failed to induce responses in any BCG-vaccinated animal studied. In summary, we have identified three peptide cocktails for prioritization in larger trials to discriminate between M. bovis infection and BCG vaccination.

Iaith wreiddiolSaesneg
Tudalennau (o-i)1344-1348
Nifer y tudalennau5
CyfnodolynClinical and Vaccine Immunology
Cyfrol17
Rhif cyhoeddi9
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 01 Medi 2010

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