Antigen discovery and specification of immunodominance hierarchies for MHCII-restricted epitopes

Abstract

Identifying immunodominant T cell epitopes remains a significant challenge in the context of infectious disease, autoimmunity, and immuno-oncology. To address the challenge of antigen discovery, we developed a quantitative proteomic approach that enabled unbiased identification of MHCII-associated peptide epitopes and biochemical features of antigenicity. Based on these data, we trained a deep neural network algorithm for genome-scale predictions of immunodominant MHCII-restricted epitopes. This algorithm is entitled bacteria-origin T cell antigen (BOTA) predictor. In validation studies, BOTA accurately predicted novel CD4 T cell epitopes derived from the model pathogen Listeria monocytogenes and the commensal microorganism Muribaculum intestinale. To conclusively define immunodominant T cell epitopes predicted by BOTA, we developed a high-throughput approach to screen DNA-encoded peptide-MHCII libraries for functional recognition by TCRs identified from single cell RNA sequencing. Collectively, these studies provide a framework for defining the immunodominance landscape across a broad range of immune pathologies.

Deciphering and predicting CD4+ T cell immunodominance of influenza virus hemagglutinin

“…The molecular context in which a peptide is embedded and its structural accessibility might influence the propensity of unfolding during the progressive pH acidification that occurs in the endocytic pathway, therefore affecting the exposition of denatured stretches of the antigen to the proteolytic environment of the late endosomes (Graham et al, 2018;Kim and Sadegh-Nasseri, 2015;Landry, 2008). To evaluate the role of structural constraints of HA in influencing the immunodominance observed in the memory repertoires, we adopted a recently developed algorithm that uses antigen conformational stability to estimate the likelihood of antigen processing (Mettu et al, 2016).…”

“…Indeed, we found that, although being a prerequisite for recognition by T cells, peptide-MHC-II binding affinity, either predicted in silico or measured in vitro, is a weak correlate of T cell recognition and in particular of immunodominance. Along with the protein antigen expression level and subcellular localization, the position within the 3D structure of the native antigen may profoundly influence the amount of processed peptides (Abelin et al, 2019;Graham et al, 2018). Recent reports have shown that T cell epitopes from viral antigens tend to localize adjacent to highly flexible, surface-exposed regions of the protein that could act as sites of initial proteolytic cleavage (Koblischke et al, 2017;Landry, 2008;Mirano-Bascos et al, 2008), suggesting that the physical accessibility within the tertiary structure is a requirement for efficient peptide release by proteases.…”

Optimized Whole Genome Association Scanning for Discovery of HLA Class I-Restricted Minor Histocompatibility Antigens

“…Whole transcriptome RNA sequencing and HLA ligandome analysis by mass spectrometry can be implemented as additional steps to select for peptides that are expressed and presented on the cell surface. These techniques significantly decrease false discovery (31,38,41,42), but also reduce the sensitivity and lead to a higher chance that antigens are missed (38), illustrating that prediction tools for minor histocompatibility antigens still require optimization.…”

CD4+ Th immunogenicity of the Ascaris spp. secreted products

“…Experimental approaches based on recombinant proteins or subcellular fractions containing endosomal compartments rich on MHCII have been applied to define epitope selection on single antigens 19,20 . Culture of primary DC and quantitative immunopeptidomics of infected cells has also been used to define CD4 + T h cell epitopes from Listeria monocytogenes in mouse 21 . However, the complex infection cycle of Ascaris spp.…”