Determination of a Predictive Cleavage Motif for Eluted Major Histocompatibility Complex Class II Ligands

Abstract

CD4+ T cells have a major role in regulating immune responses. They are activated by recognition of peptides mostly generated from exogenous antigens through the major histocompatibility complex (MHC) class II pathway. Identification of epitopes is important and computational prediction of epitopes is used widely to save time and resources. Although there are algorithms to predict binding affinity of peptides to MHC II molecules, no accurate methods exist to predict which ligands are generated as a result of natural antigen processing. We utilized a dataset of around 14,000 naturally processed ligands identified by mass spectrometry of peptides eluted from MHC class II expressing cells to investigate the existence of sequence signatures potentially related to the cleavage mechanisms that liberate the presented peptides from their source antigens. This analysis revealed preferred amino acids surrounding both N- and C-terminuses of ligands, indicating sequence-specific cleavage preferences. We used these cleavage motifs to develop a method for predicting naturally processed MHC II ligands, and validated that it had predictive power to identify ligands from independent studies. We further confirmed that prediction of ligands based on cleavage motifs could be combined with predictions of MHC binding, and that the combined prediction had superior performance. However, when attempting to predict CD4+ T cell epitopes, either alone or in combination with MHC binding predictions, predictions based on the cleavage motifs did not show predictive power. Given that peptides identified as epitopes based on CD4+ T cell reactivity typically do not have well-defined termini, it is possible that motifs are present but outside of the mapped epitope. Our attempts to take that into account computationally did not show any sign of an increased presence of cleavage motifs around well-characterized CD4+ T cell epitopes. While it is possible that our attempts to translate the cleavage motifs in MHC II ligand elution data into T cell epitope predictions were suboptimal, other possible explanations are that the cleavage signal is too diluted to be detected, or that elution data are enriched for ligands generated through an antigen processing and presentation pathway that is less frequently utilized for T cell epitopes.

Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data

“…The two latter observations are supported by an unsupervised deconvolution of the context motif using GibbsCluster 32 ( Figure 4B). This deconvolution clearly shows the strong preference for P at positions N+2 and C-2, and displays further well-defined motifs supporting the notion that proteolytic enzymes of more than one specificity are at play in the degradation of MHC II antigens in agreement with earlier findings 24 . Analysing the data separately for DR, DQ and H2 molecules revealed very similar results (see Supplementary Figures 5, 6 and 7), again suggesting that the observed signal and identified motifs are related to antigen processing and not MHC binding.…”

“…As discussed earlier 20,24 , this observation might not come as a surprise, since peptides tested for T cell immunogenicity most commonly are generated as overlapping peptides scanning a source protein, and hence are not expected to follow any rules of antigen processing. To account for this bias, and to try to bring out the full potential of modelling context, we next applied a scoring scheme where the score of a given peptide was assigned from the sum of the individual prediction values from all 13-21mer peptides with predicted binding cores overlapping the given peptide (for details see Materials and Methods).…”

“…Immunopeptidome data inherently contains signal from steps leading to antigen presentation and patterns of proteolytic digestion have been described in the terminal and context regions of ligands 20 . Earlier work has suggested that models that encode this context information have superior performance when predicting ligand data 20,24,25 . Here, we set out to validate this observation on the extensive data set gathered for this work.…”

“…Earlier work has suggested that the gained performance for prediction of MS ligands observed when including context information only to a minor degree is transferred to epitope identification 20,24 . Here, we set out to test if the models developed here would align with this finding.…”

“…EL data implicitly contains signal from steps of MHC II antigen presentation, such as antigen digestion, MHC loading of ligands and cell surface transport. Amino acid preferences in termini of immunopeptidome ligands is clear evidence of proteolytic digestion and ligand prediction has been improved by explicitly encoding this signal in prediction models 20,24,25 . Ligand length preferences of MHC II is also inherent to EL data but not BA data and this preference can hence be learned by models trained on EL data 20,21 .…”