Abstract
Our aim is to develop a subunit MAP vaccine not interfering with the diagnosis of paratuberculosis or bovine tuberculosis. This study’s objective was to evaluate MAP-specific peptides defined by in silico analysis. Peptides were picked by 1) comparing MAP genomes to that of other mycobacterium species or 2) selected based on “experience”. Peptides predicted to bind bovine MHC II by in silico analysis were included in further studies, resulting in two panels 1) genome-based and 2) selected. Initially, two groups of 15 healthy goats were vaccinated with one of the two panels (50 µg/peptide in CAF01 adjuvant/CAF04 for boosting). Four MAP-infected goats were also vaccinated. In a second vaccination trail, groups of 8 healthy goat kids were vaccinated with genome-based peptides, selected peptides or selected peptides linked together in a recombinant protein (20 µg/peptide or 50 µg protein in Montanide ISA61 adjuvant). IFN-γ responses were measured by ELISA and ELISPOT upon stimulation with peptide pools or individual peptides. T cell lines were made by cultivating CD4+ cells in the presence of antigen, feeder cells plus cytokines, and used to evaluate responses to peptide pools and individual peptides. IFN-γ responses in healthy goats after the first vaccination were low, but testing of T cell lines from MAP-infected goats identified peptides inducing strong proliferative responses. Peptides for a second vaccination were selected by combining results from this study with a parallel cattle study. In the second trial, goats in the genome-based and the selected peptide group had solid IFN-γ responses while goats in the protein group had modest responses. Only a moderate boosting effect was seen in the second trail. The genome-based pool induced the strongest CD4+ T cell line responses and had the highest number of immunogenic peptides. This study shows 1) that detection of immunogenic antigens using in silico predictions and T cell lines work, and 2) the identified MAP-specific peptides show potential for use in a subunit vaccine.
Info
Conference Abstract, 2014
UN SDG Classification
DK Main Research Area
Science/Technology
