Development of a diagnostic compatible BCG vaccine against Bovine tuberculosis

Abstract

AbstractBovine tuberculosis (BTB) caused by Mycobacterium bovis remains a major problem in both the developed and developing countries. Control of BTB in the UK is carried out by test and slaughter of infected animals, based primarily on the tuberculin skin test (PPD). Vaccination with the attenuated strain of the M. bovis pathogen, BCG, is not used to control bovine tuberculosis in cattle at present, due to its variable efficacy and because it interferes with the PPD test. Diagnostic tests capable of Differentiating Infected from Vaccinated Animals (DIVA) have been developed that detect immune responses to M. bovis antigens absent in BCG; but these are too expensive and insufficiently sensitive to be used for BTB control worldwide. To address these problems we aimed to generate a synergistic vaccine and diagnostic approach that would permit the vaccination of cattle without interfering with the conventional PPD-based surveillance. The approach was to widen the pool of M. bovis antigens that could be used as DIVA targets, by identifying antigenic proteins that could be deleted from BCG without affecting the persistence and protective efficacy of the vaccine in cattle. Using transposon mutagenesis we identified genes that were essential and those that were non-essential for persistence in bovine lymph nodes. We then inactivated selected immunogenic, but non-essential genes in BCG Danish to create a diagnostic-compatible triple knock-out ΔBCG TK strain. The protective efficacy of the ΔBCG TK was tested in guinea pigs experimentally infected with M. bovis by aerosol and found to be equivalent to wild-type BCG. A complementary diagnostic skin test was developed with the antigenic proteins encoded by the deleted genes which did not cross-react in vaccinated or in uninfected guinea pigs. This study demonstrates the functionality of a new and improved BCG strain which retains its protective efficacy but is diagnostically compatible with a novel DIVA skin test that could be implemented in control programmes.