Improved predictions of immunogenicity reveal SARS-Cov-2 CD8 T-cell epitopes
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ABSTRACT:
PROVIDER: PRJNA830364 | ENA |
REPOSITORIES: ENA
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Project description:The appended raw files, csv files and other documents were deposited in the public domain in support for the publication "Expanding the MAPPs assay to accommodate MHC-II pan re-ceptors for improved predictability of potential T cell epitopes" by Katharina Hartman, Guido Steiner, Michel Siegel, Cary M. Looney, Timothy P. Hickling, Katharine Bray-French, Sebastian Springer, Celine Marban-Doran and Axel Ducret.
The abstract is as follows: A critical step in the immunogenicity cascade is attributed to human leukocyte antigen (HLA) II presentation triggering T cell immune responses. The liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based major histocompatibility complex (MHC) II-associated peptide proteomics (MAPPs) assay is implemented during preclinical risk assessments to identify bio-therapeutic-derived T cell epitopes. Although studies indicate HLA-DP and HLA-DQ alleles are linked to immunogenicity, most MAPPs studies are restricted to HLA-DR as the dominant HLA II genotype due to lack of well-characterized immunoprecipitating antibodies. Herein we ad-dress this issue by testing various commercially-available clones of MHC-II pan (CR3/43, WR18, and Tu39), HLA-DP (B7/21), and HLA-DQ (SPV-L3 and 1a3) antibodies in the MAPPs assay, and characterizing identified peptides according to binding specificity. Our results reveal that HLA II receptor-precipitating reagents with similar reported specificities differ based on clonality and that MHC-II pan antibodies do not entirely exhibit pan-specific tendencies. Since no individual antibody clone is able to recover the complete HLA II peptide repertoire, we recommend a mixed strategy of clones L243, WR18, and SPV-L3 in a single immunoprecipitation step for more robust compound-specific peptide detection. Ultimately, our optimized MAPPs strategy im-proves the predictability and additional identification of T cell epitopes in immunogenicity risk assessments.
The dataset is divided in two sections, one supporting the figures 1-4, the other one supporting the figure 5-6. The collective data has aslo be used to generate the supplementary tables S1-S9.
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