Cross-reactive immunogenicity of group A streptococcal vaccines designed using a recurrent neural network to identify...

Area of Science:

• Microbiology
• Immunology
• Vaccine Development

Background:

• Group A Streptococcus (Strep A) M protein is a key virulence factor and vaccine target.
• Over 200 Strep A M types exist, complicating vaccine design due to N-terminal sequence variations.
• Cross-protective epitopes in M protein N-terminal regions are sought for broad vaccine efficacy.

Purpose of the Study:

• To predict linear B-cell epitopes from 117 clinically relevant Strep A M types using computational tools.
• To design and evaluate recombinant hybrid protein vaccines incorporating these predicted epitopes.
• To assess the immunogenicity and cross-reactivity of antibodies elicited by these novel vaccine candidates.

Main Methods:

• Utilized ABCpred (recurrent neural network) and IEDB epitope conservancy analysis for epitope prediction.
• Synthesized nine peptides sharing ≥60% identity with 37 heterologous M proteins.
• Constructed two recombinant hybrid protein vaccines with repeated epitopes (2x or 3x).
• Assessed antibody responses, epitope-specificity (ELISA inhibition), and opsonic activity (HL-60 bactericidal assays) in immunized rabbits.

Main Results:

• Vaccines elicited significant antibody levels against homologous M protein synthetic peptides.
• Cross-reactive antibodies were generated against 16 of 37 heterologous M peptides.
• Antibody cross-reactivity was confirmed by ELISA inhibition and functional opsonic activity was demonstrated.

Conclusions:

• The study provides crucial data for designing broadly protective M protein-based Strep A vaccines.
• Identified cross-protective epitopes offer a promising strategy for next-generation Strep A vaccines.
• The developed epitope-based vaccines demonstrate potential for eliciting broad immunity against diverse Strep A M types.