Biomarker discovery in subclinical mycobacterial infections of cattle.

BackgroundBovine tuberculosis is a highly prevalent infectious disease of cattle worldwide; however, infection in the United States is limited to 0.01% of dairy herds. Thus detection of bovine TB is confounded by high background infection with M. avium subsp. paratuberculosis. The present study addresses variations in the circulating peptidome based on the pathogenesis of two biologically similar mycobacterial diseases of cattle.Methodology/principal findingsWe hypothesized that serum proteomes of animals in response to either M. bovis or M. paratuberculosis infection will display several commonalities and differences. Sera prospectively collected from animals experimentally infected with either M. bovis or M. paratuberculosis were analyzed using high-resolution proteomics approaches. iTRAQ, a liquid chromatography and tandem mass spectrometry approach, was used to simultaneously identify and quantify peptides from multiple infections and contemporaneous uninfected control groups. Four comparisons were performed: 1) M. bovis infection versus uninfected controls, 2) M. bovis versus M. paratuberculosis infection, 3) early, and 4) advanced M. paratuberculosis infection versus uninfected controls. One hundred and ten differentially elevated proteins (P < or = 0.05) were identified. Vitamin D binding protein precursor (DBP), alpha-1 acid glycoprotein, alpha-1B glycoprotein, fetuin, and serine proteinase inhibitor were identified in both infections. Transthyretin, retinol binding proteins, and cathelicidin were identified exclusively in M. paratuberculosis infection, while the serum levels of alpha-1-microglobulin/bikunin precursor (AMBP) protein, alpha-1 acid glycoprotein, fetuin, and alpha-1B glycoprotein were elevated exclusively in M. bovis infected animals.Conclusions/significanceThe discovery of these biomarkers has significant impact on the elucidation of pathogenesis of two mycobacterial diseases at the cellular and the molecular level and can be applied in the development of mycobacterium-specific diagnostic tools for the monitoring progression of disease, response to therapy, and/or vaccine based interventions.