Rapid microsphere-assisted peptide screening (MAPS) of promiscuous MHCII-binding peptides in Zika virus envelope protein

A high-throughput yeast display approach to profile pathogen proteomes for MHC-II binding

T cells play a critical role in the adaptive immune response, recognizing peptide antigens presented on the cell surface by major histocompatibility complex (MHC) proteins. While assessing peptides for MHC binding is an important component of probing these interactions, traditional assays for testing peptides of interest for MHC binding are limited in throughput. Here, we present a yeast display-based platform for assessing the binding of tens of thousands of user-defined peptides in a high-throughput manner. We apply this approach to assess a tiled library covering the SARS-CoV-2 proteome and four dengue virus serotypes for binding to human class II MHCs, including HLA-DR401, -DR402, and -DR404. While the peptide datasets show broad agreement with previously described MHC-binding motifs, they additionally reveal experimentally validated computational false positives and false negatives. We therefore present this approach as able to complement current experimental datasets and computational predictions. Further, our yeast display approach underlines design considerations for epitope identification experiments and serves as a framework for examining relationships between viral conservation and MHC binding, which can be used to identify potentially high-interest peptide binders from viral proteins. These results demonstrate the utility of our approach to determine peptide-MHC binding interactions in a manner that can supplement and potentially enhance current algorithm-based approaches.

Rapid Identification of MHCII-Binding Peptides Through Microsphere-Assisted Peptide Screening (MAPS)

CD4⁺ T cells play a vital role in the immune response, and their function requires T cell receptor (TCR) recognition of peptide epitopes presented in complex with MHC class II (MHCII) molecules. Consequently, rapidly identifying peptides that bind MHCII is critical to understanding and treating infectious disease, cancer, autoimmunity, allergy, and transplant rejection. Computational methods provide a fast, ultrahigh-throughput approach to predict MHCII-binding peptides but lack the accuracy of experimental methods. In contrast, experimental methods offer accurate, quantitative results at the expense of speed. To address the gap between these two approaches, we developed a high-throughput, semiquantitative experimental screening strategy termed microsphere-assisted peptide screening (MAPS). Here, we use the Zika virus envelope protein as an example to demonstrate the rapid identification of MHCII-binding peptides from a single pathogenic protein using MAPS. This process involves several key steps including peptide library design, peptide exchange into MHCII, peptide-MHCII loading onto microspheres, flow cytometry screening, and data analysis to identify peptides that bind to one or more MHCII alleles.

Yeast Intracellular Staining (yICS): Enabling High-Throughput, Quantitative Detection of Intracellular Proteins via Flow Cytometry for Pathway Engineering

The complexities of pathway engineering necessitate screening libraries to discover phenotypes of interest. However, this approach is challenging when desirable phenotypes cannot be directly linked to growth advantages or fluorescence. In these cases, the ability to rapidly quantify intracellular proteins in the pathway of interest is critical to expedite the clonal selection process. While Saccharomyces cerevisiae remains a common host for pathway engineering, current approaches for intracellular protein detection in yeast either have low throughput, can interfere with protein function, or lack the ability to detect multiple proteins simultaneously. To fill this need, we developed yeast intracellular staining (yICS) that enables fluorescent antibodies to access intracellular compartments of yeast cells while maintaining their cellular integrity for analysis by flow cytometry. Using the housekeeping proteins β actin and glyceraldehyde 3-phophate dehydrogenase (GAPDH) as targets for yICS, we demonstrated for the first time successful antibody-based flow cytometric detection of yeast intracellular proteins with no modification. Further, yICS characterization of a recombinant d-xylose assimilation pathway showed 3-plexed, quantitative detection of the xylose reductase (XR), xylitol dehydrogenase (XDH), and xylulokinase (XK) enzymes each fused with a small (6-10 amino acids) tag, revealing distinct enzyme expression profiles between plasmid-based and genome-integrated expression approaches. As a result of its high-throughput and quantitative capability, yICS enabled rapid screening of a library created from CRISPR-mediated XDH integration into the yeast δ site, identifying rare (1%) clones that led to an 8.4-fold increase in XDH activity. These results demonstrate the utility of yICS for greatly accelerating pathway engineering efforts, as well as any application where the high-throughput and quantitative detection of intracellular proteins is desired.