| Literature DB >> 32712314 |
Lohany Dias Mamede1, Keila Gonçalves de Paula2, Bianca de Oliveira3, Janete Soares Coelho Dos Santos4, Lucas Maciel Cunha2, Moacyr Comar Junior5, Lenice Roteia Cardoso Jung2, Alex Gutterres Taranto6, Débora de Oliveira Lopes7, Sophie Yvette Leclercq8.
Abstract
Streptococcus pneumoniae is a pathogen that resides in the upper respiratory tract of healthy individuals, maintaining a commensal relationship with its host. However, the virulent form may be the etiology of pneumonia, meningitis, bacteremia, and other respiratory tract infections. Streptococcal diseases are preventable by vaccination; but currently available vaccines have some drawbacks, especially due to the high capsule variability of streptococci strains. Thus, an effective prevention strategy continues to be the focus of extensive research. In our work, several bioinformatics tools were used to identify immunogenic peptides from a selected pool of 46 conserved proteins from Streptococcus pneumoniae. In silico analysis showed that 10 proteins had epitopes with affinity for B and T lymphocytes, which were present in at least 26 different pathogens serotypes and were considered promiscuous. The multi-epitope protein, designated HC44, was designed based on these epitopes and specific linkers to improve stability and exposure to T lymphocytes. The recombinant HC44 protein was expressed in E.coli and Swiss-Webster mice were immunised by intraperitoneal injection. Immunisation with the multi-epitope HC44 protein resulted in the production of very high levels of IgG with title superior to 1/1.200.000. However, subtype IgG was highly unbalanced toward IgG1 and no protection was afforded after challenge with S.pneumoniae in a sepsis model. Thus, our strategy has been effective in constructing a highly antigenic protein but novel immunisation strategies should be investigated to reorient the immune system toward a protective response.Entities:
Keywords: Multi-epitope protein antigen; Reverse vaccinology; Streptococcus pneumoniae; Structural vaccinology
Year: 2020 PMID: 32712314 DOI: 10.1016/j.meegid.2020.104473
Source DB: PubMed Journal: Infect Genet Evol ISSN: 1567-1348 Impact factor: 3.342