MHCcluster, a method for functional clustering of MHC molecules

The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially unique specificities remain experimentally uncharacterized for the vast majority of HLA molecules. Likewise, for nonhuman species, only a minor fraction of the known MHC molecules have been characterized. Here, we describe a tool, MHCcluster, to functionally cluster MHC molecules based on their predicted binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where both the functional relationship and the individual binding specificities of MHC molecules are visualized. We demonstrate that conventional sequence-based clustering will fail to identify the functional relationship between molecules, when applied to MHC system, and only through the use of the predicted binding specificity can a correct clustering be found. Clustering of prevalent HLA-A and HLA-B alleles using MHCcluster confirms the presence of 12 major specificity groups (supertypes) some however with highly divergent specificities. Importantly, some HLA molecules are shown not to fit any supertype classification. Also, we use MHCcluster to show that chimpanzee MHC class I molecules have a reduced functional diversity compared to that of HLA class I molecules. MHCcluster is available at www.cbs.dtu.dk/services/MHCcluster-2.0.     

Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate binding affinity prediction of peptides of length 8, 10 and 11. The method gives the opportunity to predict peptides with a different length than nine for MHC alleles where no such peptides have been measured. As validation, the performance of this approach is compared to predictors trained on peptides of the peptide length in question. In this validation, the approximation method has an accuracy that is comparable to or better than methods trained on a peptide length identical to the predicted peptides. AVAILABILITY: The algorithm has been implemented in the web-accessible servers NetMHC-3.0: http://www.cbs.dtu.dk/services/NetMHC-3.0, and NetMHCpan-1.1: http://www.cbs.dtu.dk/services/NetMHCpan-1.1     

MultiRTA: A simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes

Background

The binding of peptide fragments of antigens to class II MHC is a crucial step in initiating a helper T cell immune response. The identification of such peptide epitopes has potential applications in vaccine design and in better understanding autoimmune diseases and allergies. However, comprehensive experimental determination of peptide-MHC binding affinities is infeasible due to MHC diversity and the large number of possible peptide sequences. Computational methods trained on the limited experimental binding data can address this challenge. We present the MultiRTA method, an extension of our previous single-type RTA prediction method, which allows the prediction of peptide binding affinities for multiple MHC allotypes not used to train the model. Thus predictions can be made for many MHC allotypes for which experimental binding data is unavailable.

Results

We fit MultiRTA models for both HLA-DR and HLA-DP using large experimental binding data sets. The performance in predicting binding affinities for novel MHC allotypes, not in the training set, was tested in two different ways. First, we performed leave-one-allele-out cross-validation, in which predictions are made for one allotype using a model fit to binding data for the remaining MHC allotypes. Comparison of the HLA-DR results with those of two other prediction methods applied to the same data sets showed that MultiRTA achieved performance comparable to NetMHCIIpan and better than the earlier TEPITOPE method. We also directly tested model transferability by making leave-one-allele-out predictions for additional experimentally characterized sets of overlapping peptide epitopes binding to multiple MHC allotypes. In addition, we determined the applicability of prediction methods like MultiRTA to other MHC allotypes by examining the degree of MHC variation accounted for in the training set. An examination of predictions for the promiscuous binding CLIP peptide revealed variations in binding affinity among alleles as well as potentially distinct binding registers for HLA-DR and HLA-DP. Finally, we analyzed the optimal MultiRTA parameters to discover the most important peptide residues for promiscuous and allele-specific binding to HLA-DR and HLA-DP allotypes.

Conclusions

The MultiRTA method yields competitive performance but with a significantly simpler and physically interpretable model compared with previous prediction methods. A MultiRTA prediction webserver is available at http://bordnerlab.org/MultiRTA.

     

Prediction of MHC class II binding affinity using SMM-align,a novel stabilization matrix alignment method

Background  

Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.     

Towards universal structure-based prediction of class II MHC epitopes for diverse allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632-0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register.     

Sequence variability analysis of human class I and class II MHC molecules: functional and structural correlates of amino acid polymorphisms

Major histocompatibility complex class I (MHCI) and class II (MHCII) molecules display peptides on antigen-presenting cell surfaces for subsequent T-cell recognition. Within the human population, allelic variation among the classical MHCI and II gene products is the basis for differential peptide binding, thymic repertoire bias and allograft rejection. While available 3D structural analysis suggests that polymorphisms are found primarily within the peptide-binding site, a broader informatic approach pinpointing functional polymorphisms relevant for immune recognition is currently lacking. To this end, we have now analyzed known human class I (774) and class II (485) alleles at each amino acid position using a variability metric (V). Polymorphisms (V>1) have been identified in residues that contact the peptide and/or T-cell receptor (TCR). Using sequence logos to investigate TCR contact sites on HLA molecules, we have identified conserved MHCI residues distinct from those of conserved MHCII residues. In addition, specific class II (HLA-DP, -DQ, -DR) and class I (HLA-A, -B, -C) contacts for TCR binding are revealed. We discuss these findings in the context of TCR restriction and alloreactivity.     

Cooperativity during the formation of peptide/MHC class II complexes

To generate an effective immune response, class II major histocompatibility complex molecules (MHCII) must present a diverse array of peptide ligands for recognition by T lymphocytes. Peptide/MHCII complexes are stabilized by hydrophobic anchoring of peptide side chains to pockets in the MHCII protein and the formation of hydrogen bonds to the peptide backbone. Many current models of peptide/MHCII association assume an additive and independent contribution of the interactions between major MHCII pockets and corresponding side chains in the peptide. However, significant conformational rearrangements occur in both the peptide and MHCII during binding. Therefore, we hypothesize that peptide binding to MHCII could be viewed as a folding process in which both molecules cooperate to produce the final conformation. To directly test this hypothesis, we adapt a serial mutagenesis strategy to study cooperativity in the interaction of the human MHCII HLA-DR1 and a peptide derived from influenza hemagglutinin. Substitutions in either the peptide or HLA-DR1 that are predicted to interfere with hydrogen bond formation show cooperative effects on complex stability and affinity. Substitution of a peptide side chain that provides a hydrophobic contact also contributes to the cooperative effect, suggesting a role for all energetic sources in the folding process. We propose that cooperativity throughout the peptide-binding groove reflects the folding of segments of the MHCII molecule into helices around the peptide with a concomitant folding of the peptide into a polyproline helix. The implications of cooperativity for peptide/MHCII structure and epitope selection are discussed.     

Consensus classification of human leukocyte antigen class II proteins

Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA–peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II–peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II–peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at http://sysbio.icm.edu.pl/HLA.     

HLA-DO is a negative modulator of HLA-DM-mediated MHC class II peptide loading

Background: Class II molecules of the major histocompatibility complex become loaded with antigenic peptides after dissociation of invariant chainderived peptides (CLIP) from the peptide-binding groove. The human leukocyte antigen (HLA)-DM is a prerequisite for this process, which takes place in specialised intracellular compartments. HLA-DM catalyses the peptide-exchange process, simultaneously functioning as a peptide ‘editor’, favouring the presentation of stably binding peptides. Recently, HLA-DO, an unconventional class II molecule, has been found associated with HLA-DM in B cells, yet its function has remained elusive.Results: The function of the HLA-DO complex was investigated by expression of both chains of the HLA-DO heterodimer (either alone or fused to green fluorescent protein) in human Mel JuSo cells. Expression of HLA-DO resulted in greatly enhanced surface expression of CLIP via HLA-DR3, the conversion of class II complexes to the SDS-unstable phenotype and reduced antigen presentation to T-cell clones. Analysis of peptides eluted from HLA-DR3 demonstrated that CLIP was the major peptide bound to class II in the HLA-DO transfectants. Peptide exchange assays in vitro revealed that HLA-DO functions directly at the level of class II peptide loading by inhibiting the catalytic action of HLA-DM.Conclusions: HLA-DO is a negative modulator of HLA-DM. By stably associating with HLA-DM, the catalytic action of HLA-DM on class II peptide loading is inhibited. HLA-DO thus affects the peptide repertoire that is eventually presented to the immune system by MHC class II molecules.     

Peptide binding inhibits aggregation of soluble MHC class II in solution

Affinity-purified major histocompatability complex (MHC) class II molecules are known to bind antigenic peptide in vitro. This peptide-bound MHC class II is known to undergo a change in structure upon stable binding of antigenic peptide. Previous results from our, and other laboratories, have suggested a relationship between MHC class II structure and peptide association that enables class II to enter into a stable conformation upon peptide binding. In this report we describe that stable binding of high-affinity antigenic peptide to MHC class II molecule results in transition of aggregated purified MHC class II proteins to a stable heterodimeric state. Such transition was demonstrated by using purified human HLA-DR2 class II molecule and high-affinity myelin basic protein (MBP) 83-102)Y83 peptide. Highly aggregated purified DR2 (high molecular weight; HMW) was first separated from heterodimer (low molecular weight: LMW) in the presence of 50-fold molar excess of MBP(83-102)Y83 peptide. We then show that the aggregated HMW preparation can be successfully converted into a stable dimer by further incubation with MBP(83-102)Y83 and changing various binding parameters such as pH, temperature, reducing agent, and peptide concentrations. Under optimized conditions, the highly aggregated inactive DR2 molecules can be completely loaded with the antigenic peptide. The transformed heterodimers with bound peptide prepared by this method are biologically active, as shown by their ability to induce the production of gamma-interferon by SS8T-transformed human T cells. These results suggest that in solution, MHC class II molecules may be aggregated in the absence of bound peptide. Such aggregated MHC class II molecules can be converted to stable and biologically active heterodimers in the presence of high-affinity antigenic peptide.     

Patterns of constitutive and IFN-γ inducible expression of HLA class II molecules in human melanoma cell lines

Major histocompatibility complex (MHC) class II proteins (HLA-DR, HLA-DP and HLA-DQ) play a fundamental role in the regulation of the immune response. The level of expression of human leukocyte antigen (HLA) class II antigens is regulated by interferon-gamma (IFN-gamma) and depends on the status of class II trans-activator protein (CIITA), a co-activator of the MHC class II gene promoter. In this study, we measured levels of constitutive and IFN-gamma-induced expression of MHC class II molecules, analysed the expression of CIITA and investigated the association between MHC class II transactivator polymorphism and expression of different MHC class II molecules in a large panel of melanoma cell lines obtained from the European Searchable Tumour Cell Line Database. Many cell lines showed no constitutive expression of HLA-DP, HLA-DQ and HLA-DR and no IFN-gamma-induced increase in HLA class II surface expression. However, in some cases, IFN-gamma treatment led to enhanced surface expression of HLA-DP and HLA-DR. HLA-DQ was less frequently expressed under basal conditions and was less frequently induced by IFN-gamma. In these melanoma cell lines, constitutive surface expression of HLA-DR and HLA-DP was higher than that of HLA-DQ. In addition, high constitutive level of cell surface expression of HLA-DR was correlated with lower inducibility of this expression by IFN-gamma. Finally, substitution A-->G in the 5' flanking region of CIITA promoter type III was associated with higher expression of constitutive HLA-DR (p<0.005). This study yielded a panel of melanoma cell lines with different patterns of constitutive and IFN-gamma-induced expression of HLA class II that can be used in future studies of the mechanisms of regulation of HLA class II expression.     

MHC class II binding of peptides derived from HLA-DR 1.

The aim of these studies was to determine whether auto- and alloreactivity can arise from T cell recognition of MHC-peptides in context of syngeneic MHC. Four synthetic peptides derived from the first domain of the HLA-DR beta 1 * 0101 chain were used in limiting dilution analysis to prime T cells from HLA-DR1- and HLA-DR1+ responders. The frequency of T cells responding to these four peptides was similar in individuals with or without HLA-DR1. In both cases, the peptide corresponding to the nonpolymorphic sequence 43-62, was less immunogenic than peptides corresponding to the three hypervariable regions 1-20, 21-42, and 66-90, eliciting a lower number of reactive T cells. Experiments using a T cell line with specific reactivity to peptide 21-42 showed, however, that this response can be efficiently blocked by adding to the culture a nonpolymorphic sequence peptide. This suggests that alloreactivity can be blocked by use of monomorphic (self) peptides. The binding of both "monomorphic" and "polymorphic" synthetic DR1 peptides to affinity purified HLA-DR 1 and DR 11 molecules was measured using radiolabeled peptides and high performance size exclusion chromatography. The data showed that the polymorphic as well as monomorphic synthetic DR1 peptides bound to both DR1 and DR11 molecules. Competitive inhibition studies indicated that the monomorphic 43-62 peptide can block the binding of the polymorphic peptides, consistent with the results obtained in T cell cultures. Taken together these data suggest that anti-MHC autoreactive T cells are present in the periphery and that both auto and alloreactivity can be elicited by MHC peptides binding to MHC class II molecules.     

Cellular localization of class I (HLA-A, B, C) and class II (HLA-DR and DQ) MHC antigens on the epithelial cells of normal human jejunum

HLA class I and class II (HLA-DR (human I-E equivalent) and DQ (human I-A equivalent] antigens were localized by immunofluorescence technique on thin frozen sections of normal human jejunum using a panel of monomorphic monoclonal antibodies. HLA class I (A, B and C) and HLA-DR molecules were found in the basolateral membrane of enterocytes; HLA-DR were also detected in a patchy distribution in the apical part of enterocytes; HLA-DQ molecules (the human equivalent of the murine I-A molecular subset) were not detected on normal enterocytes. All three molecules were detected on the membrane of lymphocytes and monocytes present in the lamina propria.     

NetTepi: an integrated method for the prediction of T cell epitopes

Multiple factors determine the ability of a peptide to elicit a cytotoxic T cell lymphocyte response. Binding to a major histocompatibility complex class I (MHC-I) molecule is one of the most essential factors, as no peptide can become a T cell epitope unless presented on the cell surface in complex with an MHC-I molecule. As such, peptide-MHC (pMHC) binding affinity predictors are currently the premier methods for T cell epitope prediction, and these prediction methods have been shown to have high predictive performances in multiple studies. However, not all MHC-I binders are T cell epitopes, and multiple studies have investigated what additional factors are important for determining the immunogenicity of a peptide. A recent study suggested that pMHC stability plays an important role in determining if a peptide can become a T cell epitope. Likewise, a T cell propensity model has been proposed for identifying MHC binding peptides with amino acid compositions favoring T cell receptor interactions. In this study, we investigate if improved accuracy for T cell epitope discovery can be achieved by integrating predictions for pMHC binding affinity, pMHC stability, and T cell propensity. We show that a weighted sum approach allows pMHC stability and T cell propensity predictions to enrich pMHC binding affinity predictions. The integrated model leads to a consistent and significant increase in predictive performance and we demonstrate how this can be utilized to decrease the experimental workload of epitope screens. The final method, NetTepi, is publically available at www.cbs.dtu.dk/services/NetTepi.     

Peptide length significantly influences in vitro affinity for MHC class II molecules

Background

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Results

By analysing 1279 peptide elongation events covering 19 distinct HLA alleles it was observed that, in general, peptide elongation resulted in increased MHC class II molecule affinity. It was also possible to determine an optimal peptide length for MHC class II affinity of approximately 18–20 amino acids; elongation of peptides beyond this length resulted in a null or negative effect on affinity.

Conclusion

The observed relationship between peptide length and MHC class II affinity has significant implications for the design of vaccines and the study of the epitopic basis of immunological disease.     

Cellular localization of class I (HLA-A,B, C) and class II (HLA-DR and DQ) MHC antigens on the epithelial cells of normal human jejunum

HLA class I and class II (HLA-DR (human I-E equivalent) and DQ (human I-A equivalent] antigens were localized by immunofluorescence technique on thin frozen sections of normal human jejunum using a panel of monomorphic monoclonal antibodies. HLA class I (A, B and C) and HLA-DR molecules were found in the basolateral membrane of enterocytes; HLA-DR were also detected in a patchy distribution in the apical part of enterocytes; HLA-DQ molecules (the human equivalent of the murine I-A molecular subset) were not detected on normal enterocytes. All three molecules were detected on the membrane of lymphocytes and monocytes present in the lamina propria.     

Cooperativity of hydrophobic anchor interactions: evidence for epitope selection by MHC class II as a folding process

Peptide binding to MHC class II (MHCII) molecules is stabilized by hydrophobic anchoring and hydrogen bond formation. We view peptide binding as a process in which the peptide folds into the binding groove and to some extent the groove folds around the peptide. Our previous observation of cooperativity when analyzing binding properties of peptides modified at side chains with medium to high solvent accessibility is compatible with such a view. However, a large component of peptide binding is mediated by residues with strong hydrophobic interactions that bind to their respective pockets. If these reflect initial nucleation events they may be upstream of the folding process and not show cooperativity. To test whether the folding hypothesis extends to these anchor interactions, we measured dissociation and affinity to HLA-DR1 of an influenza hemagglutinin-derived peptide with multiple substitutions at major anchor residues. Our results show both negative and positive cooperative effects between hydrophobic pocket interactions. Cooperativity was also observed between hydrophobic pockets and positions with intermediate solvent accessibility, indicating that hydrophobic interactions participate in the overall folding process. These findings point out that predicting the binding potential of epitopes cannot assume additive and independent contributions of the interactions between major MHCII pockets and corresponding peptide side chains.