New vaccine candidates that might better control the worldwide prevalence of Mycobacterium tuberculosis (Mtb) have yet to be described. Strong CD4+ T cell-mediated immune response (CMI) is correlated with protection from the development of TB disease; however, the selection of suitable vaccine antigens has been thwarted by the size and complexity of the (Mtb) proteome, and by the relative difficulty of delivering these antigens in the right immunological context. One possible solution is to develop immunotherapeutic vaccines for TB that are based on T cell epitopes representing multiple antigens. This text illustrates the stepwise development of epitope-driven vaccines from in silico epitope mapping to testing the vaccine in a live Mtb challenge model. First, we used the whole genome Mtb microarray to identify bacterial proteins expressed under the conditions thought to model Mtb survival and replication in human macrophages. Eighteen of these proteins were also found by Behr et al. to be absent from at least one strain of BCG; the sequences of these eighteen proteins were then screened for T-cell epitopes using the immuno-informatics algorithm, EpiMatrix. Of the seventeen representative epitopes evaluated in ELISpot assays, all seventeen were confirmed to elicit interferon (IFN)-gamma secretion by PBMC from Mtb-exposed subjects. A parallel live Mtb challenge study in mice showed prototype epitope-based TB vaccines to be robustly immunogenic but not as effective as BCG. These experiments illustrate the use of immuno-informatics tools for vaccine development and describe a pathway for the development of a more effective, epitope-driven, immunotherapeutic vaccine for TB.
Keywords: Bioinformatics, immunoinformatics, proteome, Mycobacterium tuberculosis, microarray, T cell epitope, antigen, vaccine
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