Transcriptome-based antigen identification for Neisseria meningitidis.

The identification of suitable antigens is crucial to successful vaccine development based on subunit approaches. While many methods exist for the identification of vaccine candidates which are surface-exposed or secreted, immunogenic and conserved, contain B and T cell epitopes, most of these have a major drawback: they do not yield any information on whether the antigen is indeed expressed by the pathogen during infection. However, DNA microarrays offer a novel tool for the investigation of the transcriptional activity of all genes of a pathogenic microorganism under in vivo conditions. Employing whole genome DNA microarrays, we have analyzed the transcriptome of Neisseria meningitidis serogroup B bacteria during different stages of infection, i.e. exposure to human serum and the interaction with human epithelial and endothelial cells. Combined with data derived from genome-based approaches (such as reverse vaccinology) and immunogenicity studies, this novel transcriptome-based antigen identification should reveal ideal vaccine candidates against serogroup B meningococcal infection.