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Related Experiment Video

Updated: Jan 10, 2026

Protein Engineering by Yeast Surface Display
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High-throughput screening for class I peptide MHC binding via yeast surface display.

Patrick V Holec1,2, Kathryn C Breuckman2, Owen Leddy1,2,3

  • 1Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.

Proceedings of the National Academy of Sciences of the United States of America
|November 20, 2025
PubMed
Summary

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This summary is machine-generated.

A new yeast display method rapidly screens peptides for T cell antigen presentation across diverse MHC alleles. This platform identifies potential antigens from pathogens and reveals drug interactions affecting peptide presentation.

Area of Science:

  • Immunology
  • Molecular Biology
  • Biochemistry

Background:

  • T cells are crucial for adaptive immunity, recognizing short peptides presented by Major Histocompatibility Complex (MHC) molecules.
  • Evaluating peptide-MHC (pMHC) interactions across numerous MHC alleles is challenging due to their high polymorphism.
  • Existing methods lack the speed and scale to systematically assess peptide presentation diversity.

Purpose of the Study:

  • To develop a rapid and scalable yeast display pipeline for identifying class I pMHC binders across diverse MHC alleles.
  • To investigate unique biological phenomena, such as drug-induced alterations in peptide presentation.
  • To generate comprehensive lists of potential T cell antigens from various pathogen proteomes.

Main Methods:

  • A yeast display pipeline was engineered for high-throughput screening of peptide binders.
Keywords:
antigen presentationpeptide–MHCyeast display

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  • The system was validated by identifying pMHC class I binders across multiple MHC alleles.
  • The method was applied to pathogen proteomes including *Mycobacterium tuberculosis*, SARS-CoV-2, Dengue, and Zika viruses.

    • Main Results:

    • The yeast display pipeline successfully screened peptides and identified class I pMHC binders across numerous alleles.
    • The study revealed that the antiviral drug abacavir alters peptide presentation by HLA-B57.
    • A comprehensive list of potential T cell antigens was generated from selected pathogen proteomes.

    Conclusions:

    • The developed yeast display platform offers a flexible and efficient tool for generating large, unbiased datasets of class I peptide binding.
    • This approach accelerates the discovery of T cell antigens and aids in understanding immune responses to pathogens and drug interactions.
    • The platform's speed and scalability make it competitive with biological systems for antigen discovery.