The peptide-binding specificity of HLA-A*3001 demonstrates membership of the HLA-A3 supertype

Human leukocyte antigen class I (HLA-I) molecules are highly polymorphic peptide receptors, which select and present endogenously derived peptide epitopes to CD8+ cytotoxic T cells (CTL). The specificity of the HLA-I system is an important component of the overall specificity of the CTL immune system. Unfortunately, the large and rapidly increasing number of known HLA-I molecules seriously complicates a comprehensive analysis of the specificities of the entire HLA-I system (as of June 2008, the international HLA registry holds >1,650 unique HLA-I protein entries). In an attempt to reduce this complexity, it has been suggested to cluster the different HLA-I molecules into “supertypes” of largely overlapping peptide-binding specificities. Obviously, the HLA supertype concept is only valuable if membership can be assigned with reasonable accuracy. The supertype assignment of HLA-A*3001, a common HLA haplotype in populations of African descent, has variously been assigned to the A1, A3, or A24 supertypes. Using a biochemical HLA-A*3001 binding assay, and a large panel of nonamer peptides and peptide libraries, we here demonstrate that the specificity of HLA-A*3001 most closely resembles that of the HLA-A3 supertype. We discuss approaches to supertype assignment and underscore the importance of experimental verification.     

Classification of A1- and A24-supertype molecules by analysis of their MHC-peptide binding repertoires

At the functional level, the majority of human leukocyte antigen (HLA) class I MHC variants can be classified into about ten different major groups, or supertypes, characterized by overlapping peptide binding motifs and repertoires. Previous studies have detailed the peptide binding specificity of the HLA A2, A3, B7, and B44 supertypes, and predicted, on the basis of MHC pocket structures, known motifs, or the sequence of T cell epitopes, the existence of the HLA A1 and A24 supertypes. Direct experimental validation of the A1 and A24 supertypes, however, has been lacking. In the current study, the peptide-binding repertoires and main anchor specificities of several common HLA A molecules (A*0101, A*2301, A*2402, A*2601, A*2902, and A*3002) predicted to be members of the A1 or A24 supertypes were analyzed and defined using single amino acid substituted peptides and a large peptide library. Based on the present findings, the A1 supertype includes A*0101, A*2601, A*2902, and A*3002, whereas the A24 supertype includes A*2301 and A*2402. Interestingly, A*2902 is associated with a motif and peptide binding repertoire that overlaps significantly with those of all of the A1- and A24-supertype molecules studied, representing—to our knowledge—the first report of significant cross-reactivity among molecules belonging to different supertypes.     

Functional classification of class II human leukocyte antigen (HLA) molecules reveals seven different supertypes and a surprising degree of repertoire sharing across supertypes

Previous studies have attempted to define human leukocyte antigen (HLA) class II supertypes, analogous to the case for class I, on the basis of shared peptide-binding motifs or structure. In the present study, we determined the binding capacity of a large panel of non-redundant peptides for a set of 27 common HLA DR, DQ, and DP molecules. The measured binding data were then used to define class II supertypes on the basis of shared binding repertoires. Seven different supertypes (main DR, DR4, DRB3, main DQ, DQ7, main DP, and DP2) were defined. The molecules associated with the respective supertypes fell largely along lines defined by MHC locus and reflect, in broad terms, commonalities in reported peptide-binding motifs. Repertoire overlaps between molecules within the same class II supertype were found to be similar in magnitude to what has been observed for HLA class I supertypes. Surprisingly, however, the degree to which repertoires between molecules in the different class II supertypes also overlapped was found to be five to tenfold higher than repertoire overlaps noted between molecules in different class I supertypes. These results highlight a high degree of repertoire overlap amongst all HLA class II molecules, perhaps reflecting binding in multiple registers, and more pronounced dependence on backbone interactions rather than peptide anchor residues. This fundamental difference between HLA class I and class II would not have been predicted on the basis of analysis of either binding motifs or the sequence/predicted structures of the HLA molecules.     

Identification of five different Patr class I molecules that bind HLA supertype peptides and definition of their peptide binding motifs

We have sequenced the Pan troglodytes class I (Patr) molecules from three common chimpanzees and expressed them as single molecules in a class I-deficient cell line. These lines were utilized to obtain purified class I molecules to define the peptide binding motifs associated with five different Patr molecules. Based on these experiments, as well as analysis of the predicted structure of the B and F polymorphic MHC pockets, we classified five Patr molecules (Patr-A*0101, Patr-B*0901, Patr-B*0701, Patr-A*0602, and Patr-B*1301) within previously defined supertype specificities associated with HLA class I molecules (HLA-A3, -B7, -A1, and -A24 supertypes). The overlap in the binding repertoire between specific HLA and Patr class I molecules was in the range of 33 to 92%, depending on the particular Patr molecule as assessed by the binding of HIV-, hepatitis B virus-, and hepatitis C virus-derived epitopes. Finally, live cell binding assays of nine chimpanzee-derived B cell lines demonstrated that HLA supertype peptides bound to Patr class I molecules with frequencies in the 20-50% range.     

Identification of Conserved and HLA Promiscuous DENV3 T-Cell Epitopes

Anti-dengue T-cell responses have been implicated in both protection and immunopathology. However, most of the T-cell studies for dengue include few epitopes, with limited knowledge of their inter-serotype variation and the breadth of their human leukocyte antigen (HLA) affinity. In order to expand our knowledge of HLA-restricted dengue epitopes, we screened T-cell responses against 477 overlapping peptides derived from structural and non-structural proteins of the dengue virus serotype 3 (DENV3) by use of HLA class I and II transgenic mice (TgM): A2, A24, B7, DR2, DR3 and DR4. TgM were inoculated with peptides pools and the T-cell immunogenic peptides were identified by ELISPOT. Nine HLA class I and 97 HLA class II novel DENV3 epitopes were identified based on immunogenicity in TgM and their HLA affinity was further confirmed by binding assays analysis. A subset of these epitopes activated memory T-cells from DENV3 immune volunteers and was also capable of priming naïve T-cells, ex vivo, from dengue IgG negative individuals. Analysis of inter- and intra-serotype variation of such an epitope (A02-restricted) allowed us to identify altered peptide ligands not only in DENV3 but also in other DENV serotypes. These studies also characterized the HLA promiscuity of 23 HLA class II epitopes bearing highly conserved sequences, six of which could bind to more than 10 different HLA molecules representing a large percentage of the global population. These epitope data are invaluable to investigate the role of T-cells in dengue immunity/pathogenesis and vaccine design.     

Definition of supertypes for HLA molecules using clustering of specificity matrices

Major histocompatibility complex (MHC) proteins are encoded by extremely polymorphic genes and play a crucial role in immunity. However, not all genetically different MHC molecules are functionally different. Sette and Sidney (1999) have defined nine HLA class I supertypes and showed that with only nine main functional binding specificities it is possible to cover the binding properties of almost all known HLA class I molecules. Here we present a comprehensive study of the functional relationship between all HLA molecules with known specificities in a uniform and automated way. We have developed a novel method for clustering sequence motifs. We construct hidden Markov models for HLA class I molecules using a Gibbs sampling procedure and use the similarities among these to define clusters of specificities. These clusters are extensions of the previously suggested ones. We suggest splitting some of the alleles in the A1 supertype into a new A26 supertype, and some of the alleles in the B27 supertype into a new B39 supertype. Furthermore the B8 alleles may define their own supertype. We also use the published specificities for a number of HLA-DR types to define clusters with similar specificities. We report that the previously observed specificities of these class II molecules can be clustered into nine classes, which only partly correspond to the serological classification. We show that classification of HLA molecules may be done in a uniform and automated way. The definition of clusters allows for selection of representative HLA molecules that can cover the HLA specificity space better. This makes it possible to target most of the known HLA alleles with known specificities using only a few peptides, and may be used in construction of vaccines. Supplementary material is available at .     

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.     

Promiscuous CTL recognition of viral epitopes on multiple human leukocyte antigens: biological validation of the proposed HLA A24 supertype

Multiple HLA class I alleles can bind peptides with common sequence motifs due to structural similarities in the peptide binding cleft, and these groups of alleles have been classified into supertypes. Nine major HLA supertypes have been proposed, including an A24 supertype that includes A*2301, A*2402, and A*3001. Evidence for this A24 supertype is limited to HLA sequence homology and/or similarity in peptide binding motifs for the alleles. To investigate the immunological relevance of this proposed supertype, we have examined two viral epitopes (from EBV and CMV) initially defined as HLA-A*2301-binding peptides. The data clearly demonstrate that each peptide could be recognized by CTL clones in the context of A*2301 or A*2402; thus validating the inclusion of these three alleles within an A24 supertype. Furthermore, CTL responses to the EBV epitope were detectable in both A*2301(+) and A*2402(+) individuals who had been previously exposed to this virus. These data substantiate the biological relevance of the A24 supertype, and the identification of viral epitopes with the capacity to bind promiscuously across this supertype could aid efforts to develop CTL-based vaccines or immunotherapy. The degeneracy in HLA restriction displayed by some T cells in this study also suggests that the dogma of self-MHC restriction needs some refinement to accommodate foreign peptide recognition in the context of multiple supertype alleles.     

Large-scale production of class I bound peptides: assigning a signature to HLA-B*1501

 A peptide-based vaccine must be bound and presented by major histocompatibility complex class I molecules to elicit a CD8⁺ T-cell response. Because class I HLA molecules are highly polymorphic, it has yet to be established how well a vaccine peptide that stimulates one individual’s CD8⁺ cytotoxic T lymphocytes will be presented by a second individual’s different class I molecules. Therefore, to facilitate precise comparisons of class I peptide binding overlaps, we uniquely combined hollow-fiber bioreactors and mass spectrometry to assign precise peptide binding signatures to individual class I HLA molecules. In applying this strategy to HLA-B^*1501, we isolated milligram quantities of B^*1501-bound peptides and mapped them using mass spectrometry. Repeated analyses consistently assign the same peptide binding signature to B^*1501; the degree of peptide binding overlap between any two class I molecules can thus be determined through comparison of their peptide signatures. Received: 3 October 1996 / Revised: 20 November 1996     

Diversity of Natural Self-Derived Ligands Presented by Different HLA Class I Molecules in Transporter Antigen Processing-Deficient Cells

The transporter associated with antigen processing (TAP) translocates the cytosol-derived proteolytic peptides to the endoplasmic reticulum lumen where they complex with nascent human leukocyte antigen (HLA) class I molecules. Non-functional TAP complexes and viral or tumoral blocking of these transporters leads to reduced HLA class I surface expression and a drastic change in the available peptide repertoire. Using mass spectrometry to analyze complex human leukocyte antigen HLA-bound peptide pools isolated from large numbers of TAP-deficient cells, we identified 334 TAP-independent ligands naturally presented by four different HLA-A, -B, and -C class I molecules with very different TAP dependency from the same cell line. The repertoire of TAP-independent peptides examined favored increased peptide lengths and a lack of strict binding motifs for all four HLA class I molecules studied. The TAP-independent peptidome arose from 182 parental proteins, the majority of which yielded one HLA ligand. In contrast, TAP-independent antigen processing of very few cellular proteins generated multiple HLA ligands. Comparison between TAP-independent peptidome and proteome of several subcellular locations suggests that the secretory vesicle-like organelles could be a relevant source of parental proteins for TAP-independent HLA ligands. Finally, a predominant endoproteolytic peptidase specificity for Arg/Lys or Leu/Phe residues in the P₁ position of the scissile bond was found for the TAP-independent ligands. These data draw a new and intricate picture of TAP-independent pathways.     

Identifiying human MHC supertypes using bioinformatic methods

Classification of MHC molecules into supertypes in terms of peptide-binding specificities is an important issue, with direct implications for the development of epitope-based vaccines with wide population coverage. In view of extremely high MHC polymorphism (948 class I and 633 class II HLA alleles) the experimental solution of this task is presently impossible. In this study, we describe a bioinformatics strategy for classifying MHC molecules into supertypes using information drawn solely from three-dimensional protein structure. Two chemometric techniques-hierarchical clustering and principal component analysis-were used independently on a set of 783 HLA class I molecules to identify supertypes based on structural similarities and molecular interaction fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed "supertype fingerprints" to be identified. Thus, the A2 supertype fingerprint is Tyr(9)/Phe(9), Arg(97), and His(114) or Tyr(116); the A3-Tyr(9)/Phe(9)/Ser(9), Ile(97)/Met(97) and Glu(114) or Asp(116); the A24-Ser(9) and Met(97); the B7-Asn(63) and Leu(81); the B27-Glu(63) and Leu(81); for B44-Ala(81); the C1-Ser(77); and the C4-Asn(77).     

A Common Minimal Motif for the Ligands of HLA-B*27 Class I Molecules

CD8⁺ T cells identify and kill infected cells through the specific recognition of short viral antigens bound to human major histocompatibility complex (HLA) class I molecules. The colossal number of polymorphisms in HLA molecules makes it essential to characterize the antigen-presenting properties common to large HLA families or supertypes. In this context, the HLA-B*27 family comprising at least 100 different alleles, some of them widely distributed in the human population, is involved in the cellular immune response against pathogens and also associated to autoimmune spondyloarthritis being thus a relevant target of study. To this end, HLA binding assays performed using nine HLA-B*2705-restricted ligands endogenously processed and presented in virus-infected cells revealed a common minimal peptide motif for efficient binding to the HLA-B*27 family. The motif was independently confirmed using four unrelated peptides. This experimental approach, which could be easily transferred to other HLA class I families and supertypes, has implications for the validation of new bioinformatics tools in the functional clustering of HLA molecules, for the identification of antiviral cytotoxic T lymphocyte responses, and for future vaccine development.     

Use of selected reaction monitoring mass spectrometry for the detection of specific MHC class I peptide antigens on A3 supertype family members

The development of peptide-based vaccines that are useful in the therapeutic treatment of melanoma and other cancers ultimately requires the identification of a sufficient number of antigenic peptides so that most individuals, regardless of their major histocompatibility complex (MHC)–encoded class I molecule phenotype, can develop a cytotoxic T lymphocyte (CTL) response against one or more peptide components of the vaccine. While it is relatively easy to identify antigenic peptides that are presented by the most prevalent MHC class I molecules in the population, it is problematic to identify antigenic peptides that are presented by MHC class I molecules that have less frequent expression in the population. One manner in which this problem can be overcome is by taking advantage of known MHC class I supertypes, which are groupings of MHC class I molecules that bind peptides sharing a common motif. We have developed a mass spectrometric approach which can be used to determine if an antigenic peptide is naturally processed and presented by any given MHC class I molecule. This approach has been applied to the A3 supertype, and the results demonstrate that some, but not all, A3 supertype family–associated peptides can associate with all A3 supertype family members. The approach also demonstrates the shared nature of several newly identified peptide antigens. The use of this technology negates the need to test peptides for their ability to stimulate CTL responses in those cases where the peptide is not naturally processed and bound to the target MHC class I molecule of interest, thus allowing resources to be focused on the most promising vaccine candidates.     

A HLA-DRB supertype chart with potential overlapping peptide binding function

HLA-DRB alleles are class II alleles that are associated with CD4+ T-cell immune response. DRB alleles are polymorphic and currently there are about 622 named in the IMGT/HLA sequence database. Each allele binds short peptides with high sensitivity and specificity. However, it has been suggested that majority of HLA alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides showing distinct repertoires. Definition of DRB supertypes using binding data is limited to few (about 29) known alleles (< 5% of all known DRB alleles). Hence, we describe a strategy using structurally defined virtual pockets to group all known DRB alleles with regard to their overlapping peptide binding specificity.     

Detailed characterization of the peptide binding specificity of five common Patr class I MHC molecules

The chimpanzee (Pan troglodytes) is an important model for studying the immune response to several human pathogens, but the study of correlates of immunity has been hindered by the fact that little is known about the epitope-binding specificity of chimpanzee (Patr) class I MHC. In the present study we have characterized the peptide binding specificity of several common Patr class I molecules. Using single amino acid substitution analogs and large peptide libraries, quantitative peptide binding motifs have been derived for Patr A*0101, A*0701, A*0901, B*0101, and B*2401. Each molecule was found to bind peptides using position 2 and the C terminus as main anchor contacts. On the other hand, each Patr molecule is associated with a unique binding specificity, and the range of specificities is similar to that seen amongst HLA alleles. A high degree of cross-reactivity was noted between Patr A*0701 and Patr A*0901, suggesting the existence of a Patr-specific supertype. Consistent with previous studies suggesting that some cross-reactivity may exist between HLA and Patr alleles, Patr A*0901 was found to have an appreciable degree of cross-reactivity with molecules of the HLA A24-supertype. Finally, utilizing motif scans and peptide binding and intracellular cytokine staining assays, 77 hepatitis B virus (HBV)-derived epitopes were identified in five chimpanzees that were recently convalescent from acute HBV infection. Because the Patr alleles studied herein were found to be very common in two different chimpanzee populations, the present data should facilitate the use of chimpanzees for immunological studies.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

The HLA molecules DQA1*0501/B1*0201 and DQA1*0301/B1*0302 share an extensive overlap in peptide binding specificity

Assays to measure the binding capacity of peptides for HLA-DQA1*0501/B*0201 (DQ2.3) and DQA1*0301/B*0302 (DQ3.2) were developed using solubilized MHC molecules purified from EBV-transformed cell lines. These quantitative assays, based on the principle of the inhibition of binding of a high-affinity radiolabeled ligand, were validated by examining the binding capacity of known DQ-restricted epitopes or ligands. The availability of these assays allowed an investigation of patterns of cross-reactivity between different DQ molecules and with various common DR molecules. DQ2.3 and DQ3.2 were found to have significantly overlapping peptide binding repertoires. Specifically, of 13 peptides that bound either DQ2.3 or DQ3.2, nine (69.2%) bound both. The molecular basis of this high degree of cross-reactivity was further investigated with panels of single substitution analogs of the thyroid peroxidase 632-645Y epitope. It was found that DQ2.3 and DQ3.2 bind the same ligands by using similar anchor residues but different registers. These data suggest that in analogy to what was previously described for HLA-DR molecules, HLA-DQ supertypes characterized by largely overlapping binding repertoires can be defined. In light of the known linkage of both HLA-DQ2.3 and -DQ3.2 with insulin-dependent diabetes mellitus and celiac disease, these results might have important implications for understanding HLA class II autoimmune disease associations.     

Large scale mass spectrometric profiling of peptides eluted from HLA molecules reveals N-terminal-extended peptide motifs

The majority of >2000 HLA class I molecules can be clustered according to overlapping peptide binding specificities or motifs recognized by CD8(+) T cells. HLA class I motifs are classified based on the specificity of residues located in the P2 and the C-terminal positions of the peptide. However, it has been suggested that other positions might be relevant for peptide binding to HLA class I molecules and therefore be used for further characterization of HLA class I motifs. In this study we performed large-scale sequencing of endogenous peptides eluted from K562 cells (HLA class I null) made to express a single HLA molecule from HLA-B*3501, -B*3502, -B*3503, -B*3504, -B*3506, or -B*3508. Using sequence data from >1,000 peptides, we characterized novel peptide motifs that include dominant anchor residues extending to all positions in the peptide. The length distribution of HLA-B35-bound peptides included peptides of up to 15 residues. Remarkably, we determined that some peptides longer than 11 residues represented N-terminal-extended peptides containing an appropriate HLA-B35 peptide motif. These results provide evidence for the occurrence of endogenous N-terminal-extended peptide-HLA class I configurations. In addition, these results expand the knowledge about the identity of anchor positions in HLA class I-associated peptides that can be used for characterization of HLA class I motifs.     

A comparative analysis of viral peptides presented by contemporary human and chimpanzee MHC class I molecules

Genetic factors such as the MHC influence the immunocompetence of an individual. MHC genes are the most polymorphic genes in primates, which is often interpreted as an adaptation to establish good T cell responses to a wide range of (evolving) pathogens. Chimpanzee MHC (Patr) genes are less polymorphic than human MHC (HLA) genes, which is surprising because chimpanzee is the older species of the two and is therefore expected to display more variation. To quantify the effect of the reduced polymorphism, we compared the peptide binding repertoire of human and chimpanzee MHC molecules. Using a peptide-MHC binding predictor and proteomes of >900 mammalian viruses, we show that, at the population level, the total peptide binding repertoire of Patr-A molecules is ~36% lower than that of their human counterparts, whereas the reduction of the peptide binding repertoire of the Patr-B locus is only 15%. In line with these results, different Patr-A molecules turn out to have largely overlapping peptide binding repertoires, whereas the Patr-B molecules are more distinct from each other. This difference is somewhat less apparent at the individual level, where we found that only 25% of the viruses are significantly better presented by "simulated" humans with heterozygous HLA-A and -B loci. Taken together, our results indicate that the Patr-B molecules recovered more after the selective sweep, whereas the Patr-A locus shows the most signs of the selective sweep with regard to its peptide binding repertoire.     

Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules

MOTIVATION: Various computational methods have been proposed to tackle the problem of predicting the peptide binding ability for a specific MHC molecule. These methods are based on known binding peptide sequences. However, current available peptide databases do not have very abundant amounts of examples and are highly redundant. Existing studies show that MHC molecules can be classified into supertypes in terms of peptide-binding specificities. Therefore, we first give a method for reducing the redundancy in a given dataset based on information entropy, then present a novel approach for prediction by learning a predictive model from a dataset of binders for not only the molecule of interest but also for other MHC molecules. RESULTS: We experimented on the HLA-A family with the binding nonamers of A1 supertype (HLA-A*0101, A*2601, A*2902, A*3002), A2 supertype (A*0201, A*0202, A*0203, A*0206, A*6802), A3 supertype (A*0301, A*1101, A*3101, A*3301, A*6801) and A24 supertype (A*2301 and A*2402), whose data were collected from six publicly available peptide databases and two private sources. The results show that our approach significantly improves the prediction accuracy of peptides that bind a specific HLA molecule when we combine binding data of HLA molecules in the same supertype. Our approach can thus be used to help find new binders for MHC molecules.