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.
All deep sequencing data are deposited on the Sequence Read Archive (SRA), with accession codes PRJNA806475 [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA806475] and PRJNA708266 [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA708266]. Processed peptide data is provided as a supplemental dataset with this submission. Source data for FP measurements listed in Figure 4 is provided with this submission.
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
© 2022, Huisman et al.
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The members of the Mycobacterium tuberculosis complex (MTBC) causing human tuberculosis comprise 10 phylogenetic lineages that differ in their geographical distribution. The human consequences of this phylogenetic diversity remain poorly understood. Here, we assessed the phenotypic properties at the host-pathogen interface of 14 clinical strains representing five major MTBC lineages. Using a human in vitro granuloma model combined with bacterial load assessment, microscopy, flow cytometry, and multiplexed-bead arrays, we observed considerable intra-lineage diversity. Yet, modern lineages were overall associated with increased growth rate and more pronounced granulomatous responses. MTBC lineages exhibited distinct propensities to accumulate triglyceride lipid droplets—a phenotype associated with dormancy—that was particularly pronounced in lineage 2 and reduced in lineage 3 strains. The most favorable granuloma responses were associated with strong CD4 and CD8 T cell activation as well as inflammatory responses mediated by CXCL9, granzyme B, and TNF. Both of which showed consistent negative correlation with bacterial proliferation across genetically distant MTBC strains of different lineages. Taken together, our data indicate that different virulence strategies and protective immune traits associate with MTBC genetic diversity at lineage and strain level.