Abstract

The best way to prevent diseases caused by pathogens is by the use of vaccines. The advent of genomics enables genome-wide searches of new vaccine candidates, called reverse vaccinology. The most common strategy to apply reverse vaccinology is by designing subunit recombinant vaccines, which usually generate an humoral immune response due to B-cell epitopes in proteins. A major problem for this strategy is the identification of protective immunogenic proteins from the surfome of the pathogen. Epitope mimicry may lead to auto-immune phenomena related to several human diseases. A sequence-based computational analysis has been carried out applying the BLASTP algorithm. Therefore, two huge databases have been created, one with the most complete and current linear B-cell epitopes, and the other one with the surface-protein sequences of the main human respiratory bacterial pathogens. We found that none of the 7353 linear B-cell epitopes analysed shares any sequence identity region with human proteins capable of generating antibodies, and that only 1% of the 2175 exposed proteins analysed contain a stretch of shared sequence with the human proteome. These findings suggest the existence of a mechanism to avoid autoimmunity. We also propose a strategy for corroborating or warning about the viability of a protein linear B-cell epitope as a putative vaccine candidate in a reverse vaccinology study; so, epitopes without any sequence identity with human proteins should be very good vaccine candidates, and the other way around.