Effective assessment of CD4+ T cell Immunodominance patterns: impact of antigen processing and HLA restriction
Alvaro-Benito, M.; Abualrous, E. T.; Lingel, H.; Meltendorf, S.; Holzapfel, J.; Sticht, J.; Kuropka, B.; Clementi, C.; Kuppler, F.; Brunner-Weinzierl, M. C.; Freund, C.
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CD4+ T cell responses to viral infections are driven by immunodominant determinants. Accessing the peptides defining these determinants in humans is essential for advancing our understanding and potentially tuning immune responses to pathogens. State of the art methods identifying CD4+ T cell immunodominant epitopes are constrained by limitations in throughput, performance or both. Here, we leverage on the combined use of a reconstituted antigen processing system and of in silico prediction tools to query and study CD4+ T cell immunodominance of two model SARS-CoV-2 antigens. We applied this combined platform over a DRB1* panel with broad population and functional coverage to gain mechanistic insights beyond single allotypes. This approach delineates a minimalistic peptide pool (59 candidates) featuring a high immunogenic profile (similar response to 10-fold larger pools) through a representative human sample. Analysis of antigen-encoded and processing-related features on IEDB curated immunodominant peptides reveal that distinct antigen processing mechanisms apply for the Nucleocapsid and Spike model antigens. Notably, the First Bind and then cut mechanism was favored for Nucleocapsid-derived epitopes (up to 55 %), whereas the First Cut and then bind predominated for the Spike (80 %). Together, our results highlight differential processing pathways underlying CD4 T cell immunodominance for distinct viral antigens providing a mechanistic foundation to improve epitope prediction algorithms. Significance StatementEfficient access to immunodominant CD4+ T cell epitopes will inform improved peptide pool design for studying or tuning immunity towards any pathogen. Despite advances in the field, in silico epitope prediction remains error-prone and experimental efforts are logistically challenging. Epitope prediction tools are mainly focused on the identification of binding motifs while neglecting key processing steps. Considering antigen processing factors and constraints is expected to improve their performance. We describe and apply a platform for the systematic investigation of antigen processing mechanisms and how they impinge on the selection of CD4+ T cell immunodominance. Our results validate distinct immunodominant epitope selection pathways for two model antigens at the human population level.
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