Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines
Author(s) -
Michelle P. Aranha,
Thomas Penfound,
Sanaz Salehi,
Anne Botteaux,
Pierre R. Smeesters,
James B. Dale,
Jeremy C. Smith
Publication year - 2021
Publication title -
the journal of immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.737
H-Index - 372
eISSN - 1550-6606
pISSN - 0022-1767
DOI - 10.4049/jimmunol.2100286
Subject(s) - epitope , virulence , heterologous , biology , avidity , peptide , peptide sequence , cross reactivity , computational biology , genetics , antigen , biochemistry , cross reactions , gene
Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. One obstacle to the development of M protein-based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.
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