High-throughput screening for class I peptide MHC binding via yeast surface display

T cells rely on short peptides presented by highly polymorphic major histocompatibility complexes (MHCs) to selectively initiate adaptive immune responses. Despite its importance, few techniques can systematically evaluate stable peptide presentation across diverse MHC alleles. Here, we describe a yeast display pipeline that can be deployed to rapidly screen peptides to identify class I pMHC binders across many alleles. Through this, we isolate unique biological phenomena such as alteration of the peptide presentation of HLA-B57 via interaction with the antiviral small molecule abacavir. We apply this approach to multiple pathogen proteomes (<i><i>Mycobacterium tuberculosis</i></i> Type VII secretion substrates, SARS-CoV-2, Dengue, and Zika) to create a comprehensive list of potential T cell antigens. Altogether, this platform acts as a flexible tool to generate large unbiased datasets for class I peptide binding at a speed and scale competitive with the biological systems they represent.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-11-20
DOI
https://doi.org/10.1073/pnas.2514741122
Citations
1
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.81
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article

High-throughput screening for class I peptide MHC binding via yeast surface display

Michael E. Birnbaum, Forest M. White, Patrick V. Holec, Owen Leddy et al.
1 citations
Proceedings of the National Academy of Sciences
vaccines and immunoinformatics approaches
0.81
article

High-throughput screening for class I peptide MHC binding via yeast surface display

Michael E. Birnbaum, Forest M. White, Patrick V. Holec, Owen Leddy, Kathryn C. Breuckman, Bryan D. Bryson
article en
1 citations

Abstract

T cells rely on short peptides presented by highly polymorphic major histocompatibility complexes (MHCs) to selectively initiate adaptive immune responses. Despite its importance, few techniques can systematically evaluate stable peptide presentation across diverse MHC alleles. Here, we describe a yeast display pipeline that can be deployed to rapidly screen peptides to identify class I pMHC binders across many alleles. Through this, we isolate unique biological phenomena such as alteration of the peptide presentation of HLA-B57 via interaction with the antiviral small molecule abacavir. We apply this approach to multiple pathogen proteomes (<i><i>Mycobacterium tuberculosis</i></i> Type VII secretion substrates, SARS-CoV-2, Dengue, and Zika) to create a comprehensive list of potential T cell antigens. Altogether, this platform acts as a flexible tool to generate large unbiased datasets for class I peptide binding at a speed and scale competitive with the biological systems they represent.

Proceedings of the National Academy of SciencesVol. 122(47)
Ragon Institute of MGH, MIT and Harvard (US), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 21%
vaccines and immunoinformatics approaches
0.81
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High-throughput screening for class I peptide MHC binding via yeast surface display — Michael E. Birnbaum, Forest M. White, et al. · Proceedings of the National Academy of Sciences (2025) | TGRS Research Map | TGRS