Antigen mining to define Mycobacterium bovis antigens for the differential diagnosis of vaccinated and infected animals: A VLA perspective.

Abstract

The urgency for new and improved cattle vaccines and diagnostic reagents has been acknowledged by the UK Government, and development of cattle vaccine is a research priority. Significant progress has been made to develop specific antigens that allow the differentiation of bacille Calmette-Guerin (BCG) vaccinated and M. bovis-infected cattle [diagnosis of infected from vaccinated individuals (DIVA) test]. This progress has been greatly facilitated by the completion of the genome sequences of Mycobacterium tuberculosis, M. bovis and BCG Pasteur. In this study, we describe how we applied this knowledge, through comparative genome and transcriptome analysis, to define DIVA antigens that complemented the prototype DIVA antigens ESAT-6 and CFP-10 by increasing their test sensitivity. In addition, we draw general conclusions from our experience, and discuss potential future approaches in this area.