CD4+ T-cell epitope prediction using antigen processing constraints

Abstract

T-cell CD4+ epitopes are important targets of immunity against infectious diseases and cancer. State-of-the-art methods for MHC class II epitope prediction rely on supervised learning methods in which an implicit or explicit model of sequence specificity is constructed using a training set of peptides with experimentally tested MHC class II binding affinity. In this paper we present a novel method for CD4+ T-cell eptitope prediction based on modeling antigen-processing constraints. Previous work indicates that dominant CD4+ T-cell epitopes tend to occur adjacent to sites of initial proteolytic cleavage. Given an antigen with known three-dimensional structure, our algorithm first aggregates four types of conformational stability data in order to construct a profile of stability that allows us to identify regions of the protein that are most accessible to proteolysis. Using this profile, we then construct a profile of epitope likelihood based on the pattern of transitions from unstable to stable regions. We validate our method using 35 datasets of experimentally measured CD4+ T cell responses of mice bearing I-Ab or HLA-DR4 alleles as well as of human subjects. Overall, our results show that antigen processing constraints provide a significant source of predictive power. For epitope prediction in single-allele systems, our approach can be combined with sequence-based methods, or used in instances where little or no training data is available. In multiple-allele systems, sequence-based methods can only be used if the allele distribution of a population is known. In contrast, our approach does not make use of MHC binding prediction, and is thus agnostic to MHC class II genotypes.

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). In brief, an aggregate z-score of conformational stability was determined for each H1-HA residue by integrating four structural parameters obtained from the 3D structure of postfusion HA resolved by x-ray diffraction (PDB codes: 3LZG for HA1 domain [Xu et al, 2010]; 1HTM for HA2 domain in the postfusion conformation [Bullough et al, 1994]).…”

“…Top scoring H1-HA 15mer peptides for each donor were selected based on percentile rank calculated by comparison to a large set of random natural peptides. APL was computed as described in Mettu et al (2016). Briefly, an aggregate z-score of conformational stability was determined for each H1-HA residue by integrating four structural parameters obtained from the 3D structure of postfusion HA resolved by x-ray diffraction (PDB codes: 3LZG for HA1 domain [Xu et al, 2010]; 1HTM for HA2 domain in the postfusion conformation [Bullough et al, 1994]).…”

Peptide Epitope Hot Spots of CD4 T Cell Recognition Within Influenza Hemagglutinin During the Primary Response to Infection

“…It is reasonable to speculate that such selection is multifactorial. Selection of CD4 T cell responses in the host has been shown to reflect at least in part the sequential processes in antigen presentation, including antigen uptake into endosomal compartments of antigen presenting cells (APC), pH-induced unfolding, reduction of disulfide bonds, proteolytic release of antigenic peptide, acquisition of the peptide by host MHC class II molecules and editing by HLA-DM and, finally the export of the peptide:class II complex to the cell surface of the APC (reviewed in [44][45][46][47][48][49][50][51][52][53][54][55][56][57]). Factors that have been implicated in previous studies for selection of dominant epitopes by CD4 T cells include proteolytic processing, three dimensional structure, sensitivity to proteolytic enzymes, or biochemical features of peptide:MHC class II complexes [56,[58][59][60][61][62][63].…”

“…The hot spots, shown in Figure 4, suggest that they tend to be on the solvent exposed regions that may be particularly accessible to proteolytic enzymes. Interestingly, the element of access to proteolytic sensitivity in viral proteins has been implicated in selection of CD4 T cell immunodominant regions of HIV gp140 protein [69] and Zika virus C and E proteins [70], as well as in studies designed to generally predict antigenic site for CD4 T cell recognition [45].…”

Eliciting unnatural immune responses by activating cryptic epitopes in viral antigens

“…In that scenario, lysosomal enzymes, including cathepsins, might have a central role in processing of viral antigens. A previous study found that cathepsins are responsible for processing the HIV envelope into peptides of potential MHC class I and II epitopes that contribute to eliciting CD4 + T cell responses for developing adaptive immune responses toward protection (58, 59). Proper processing in APCs and loading on MHC does not, however, warrant successful elicitation of antibody responses.…”