| Literature DB >> 33642159 |
Jay A Spencer1, Tom Penfound2, Sanaz Salehi2, Michelle P Aranha3, Lauren E Wade2, Rupesh Agarwal3, Jeremy C Smith3, James B Dale2, Jerome Baudry4.
Abstract
The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal sequence of the protein defines the more than 200 M types of Strep A and also contains epitopes that elicit opsonic antibodies, some of which cross-react with heterologous M types. Current efforts to develop broadly protective M protein-based vaccines are directed at identifying potential cross-protective epitopes located in the N-terminal regions of cluster-related M proteins for use as vaccine antigens. In this study, we have used a comprehensive approach using the recurrent neural network ABCpred and IEDB epitope conservancy analysis tools to predict 16 residue linear B-cell epitopes from 117 clinically relevant M types of Strep A (~88% of global Strep A infections). To examine the immunogenicity of these epitope-based vaccines, nine peptides that together shared ≥60% sequence identity with 37 heterologous M proteins were incorporated into two recombinant hybrid protein vaccines, in which the epitopes were repeated 2 or 3 times, respectively. The combined immune responses of immunized rabbits showed that the vaccines elicited significant levels of antibodies against all nine vaccine epitopes present in homologous N-terminal 1-50 amino acid synthetic M peptides, as well as cross-reactive antibodies against 16 of 37 heterologous M peptides predicted to contain similar epitopes. The epitope-specificity of the cross-reactive antibodies was confirmed by ELISA inhibition assays and functional opsonic activity was assayed in HL-60-based bactericidal assays. The results provide important information for the future design of broadly protective M protein-based Strep A vaccines.Entities:
Keywords: Bioinformatics; Linear epitopes; M protein; Neural networks; Streptococcus pyogenes (S. pyogenes); Vaccine development
Year: 2021 PMID: 33642159 PMCID: PMC8045747 DOI: 10.1016/j.vaccine.2021.01.075
Source DB: PubMed Journal: Vaccine ISSN: 0264-410X Impact factor: 3.641