Celiac disease is caused by intolerance to cereal gluten proteins, and HLA-DQ molecules are involved in the disease pathogenesis by presentation of gluten peptides to CD4+ T cells. The α- or β-chain sharing HLA molecules DQ2.5, DQ2.2, and DQ7.5 display different risks for the disease. It was recently demonstrated that T cells of DQ2.5 and DQ2.2 patients recognize distinct sets of gluten epitopes, suggesting that these two DQ2 variants select different peptides for display. To explore whether this is the case, we performed a comprehensive comparison of the endogenous self-peptides bound to HLA-DQ molecules of B-lymphoblastoid cell lines. Peptides were eluted from affinity-purified HLA molecules of nine cell lines and subjected to quadrupole orbitrap mass spectrometry and MaxQuant software analysis. Altogether, 12,712 endogenous peptides were identified at very different relative abundances. Hierarchical clustering of normalized quantitative data demonstrated significant differences in repertoires of peptides between the three DQ variant molecules. The neural network-based method, NNAlign, was used to identify peptide-binding motifs. The binding motifs of DQ2.5 and DQ7.5 concurred with previously established binding motifs. The binding motif of DQ2.2 was strikingly different from that of DQ2.5 with position P3 being a major anchor having a preference for threonine and serine. This is notable as three recently identified epitopes of gluten recognized by T cells of DQ2.2 celiac patients harbor serine at position P3. This study demonstrates that relative quantitative comparison of endogenous peptides sampled from our protein metabolism by HLA molecules provides clues to understand HLA association with disease.
Electronic supplementary material
The online version of this article (doi:10.1007/s00251-014-0819-9) contains supplementary material, which is available to authorized users.
Antigen presentation/processing; Binding motif; Celiac disease; Mass spectrometry; MHC
MHC class I molecules (HLA-I in humans) present peptides derived from endogenous proteins to CTLs. Whereas the peptide-binding specificities of HLA-A and -B molecules have been studied extensively, little is known about HLA-C specificities. Combining a positional scanning combinatorial peptide library approach with a peptide–HLA-I dissociation assay, in this study we present a general strategy to determine the peptide-binding specificity of any MHC class I molecule. We applied this novel strategy to 17 of the most common HLA-C molecules, and for 16 of these we successfully generated matrices representing their peptide-binding motifs. The motifs prominently shared a conserved C-terminal primary anchor with hydrophobic amino acid residues, as well as one or more diverse primary and auxiliary anchors at P1, P2, P3, and/or P7. Matrices were used to generate a large panel of HLA-C–specific peptide-binding data and update our pan-specific NetMHCpan predictor, whose predictive performance was considerably improved with respect to peptide binding to HLA-C. The updated predictor was used to assess the specificities of HLA-C molecules, which were found to cover a more limited sequence space than HLA-A and -B molecules. Assessing the functional significance of these new tools, HLA-C*07:01 transgenic mice were immunized with stable HLA-C*07:01 binders; six of six tested stable peptide binders were immunogenic. Finally, we generated HLA-C tetramers and labeled human CD8+ T cells and NK cells. These new resources should support future research on the biology of HLA-C molecules. The data are deposited at the Immune Epitope Database, and the updated NetMHCpan predictor is available at the Center for Biological Sequence Analysis and the Immune Epitope Database.
Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide–MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0.
MHC class II; Tcell epitope; MHC binding specificity; Peptide–MHC binding; Human leukocyte antigens; Artificial neural networks
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.
MHC; HLA; Binding motif; Functional clustering; MHC specificity; Supertypes
It is important to accurately determine the performance of peptide:MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last benchmark dataset from 2009 with prediction performances generated on data subsequently added to the Immune Epitope Database (IEDB) which served as a blind set.
We found that cross-validated performances systematically overestimated performance on the blind set. This was found not to be due to the presence of similar peptides in the cross-validation dataset. Rather, we found that small size and low sequence/affinity diversity of either training or blind datasets were associated with large differences in cross-validated vs. blind prediction performances. We use these findings to derive quantitative rules of how large and diverse datasets need to be to provide generalizable performance estimates.
It has long been known that cross-validated prediction performance estimates often overestimate performance on independently generated blind set data. We here identify and quantify the specific factors contributing to this effect for MHC-I binding predictions. An increasing number of peptides for which MHC binding affinities are measured experimentally have been selected based on binding predictions and thus are less diverse than historic datasets sampling the entire sequence and affinity space, making them more difficult benchmark data sets. This has to be taken into account when comparing performance metrics between different benchmarks, and when deriving error estimates for predictions based on benchmark performance.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-241) contains supplementary material, which is available to authorized users.
Benchmarking of MHC class I predictors; Epitope prediction; Sequence similarity; Cross-validation
We have generated a panel of transgenic mice expressing HLA-A*01:03, -A*24:02, -B*08:01, -B*27:05, -B*35:01, -B*44:02, or -C*07:01 as chimeric monochain molecules (i.e., appropriate HLA α1α2 H chain domains fused with a mouse α3 domain and covalently linked to human β2-microglobulin). Whereas surface expression of several transgenes was markedly reduced in recipient mice that coexpressed endogenous H-2 class I molecules, substantial surface expression of all human transgenes was observed in mice lacking H-2 class I molecules. In these HLA monochain transgenic/H-2 class I null mice, we observed a quantitative and qualitative restoration of the peripheral CD8+ T cell repertoire, which exhibited a TCR diversity comparable with C57BL/6 WT mice. Potent epitope-specific, HLA-restricted, IFN-γ–producing CD8+ T cell responses were generated against known reference T cell epitopes after either peptide or DNA immunization. HLA-wise, these new transgenic strains encompass a large proportion of individuals from all major human races and ethnicities. In combination with the previously created HLA-A*02:01 and -B*07:02 transgenic mice, the novel HLA transgenic mice described in this report should be a versatile preclinical animal model that will speed up the identification and optimization of HLA-restricted CD8+ T cell epitopes of potential interest in various autoimmune human diseases and in preclinical evaluation of T cell–based vaccines.
Human cytomegalovirus (HCMV) is an important human pathogen. It is a leading cause of congenital infection and a leading infectious threat to recipients of solid organ transplants as well as of allogeneic hematopoietic cell transplants. Moreover, it has recently been suggested that HCMV may promote tumor development. Both CD4+ and CD8+ T cell responses are important for long-term control of the virus, and adoptive transfer of HCMV-specific T cells has led to protection from reactivation and HCMV disease. Identification of HCMV-specific T cell epitopes has primarily focused on CD8+ T cell responses against the pp65 phosphoprotein. In this study, we have focused on CD4+ and CD8+ T cell responses against the immediate early 1 and 2 proteins (IE1 and IE2). Using overlapping peptides spanning the entire IE1 and IE2 sequences, peripheral blood mononuclear cells from 16 healthy, HLA-typed, donors were screened by ex vivo IFN-γ ELISpot and in vitro intracellular cytokine secretion assays. The specificities of CD4+ and CD8+ T cell responses were identified and validated by HLA class II and I tetramers, respectively. Eighty-one CD4+ and 44 CD8+ T cell responses were identified representing at least seven different CD4 epitopes and 14 CD8 epitopes restricted by seven and 11 different HLA class II and I molecules, respectively, in total covering 91 and 98% of the Caucasian population, respectively. Presented in the context of several different HLA class II molecules, two epitope areas in IE1 and IE2 were recognized in about half of the analyzed donors. These data may be used to design a versatile anti-HCMV vaccine and/or immunotherapy strategy.
HLA-B*57 is strongly associated with immune control of HIV and delayed AIDS progression. The closely related, but less protective, HLA-B*58:01 presents similar epitopes, but HLA-B*58:01+ individuals do not generate CD8+ T cells targeting the KF11-Gag epitope, which has been linked to low viremia. Here we show that HLA-B*58:01 binds and presents KF11 peptide, but HIV-infected HLA-B*58:01+ cells fail to process KF11. This unexpected finding demonstrates that immunodominance patterns can be influenced by intracellular events independent of HLA binding motifs.
Peptide-major histocompatibility complex (p-MHC) class I tetramer complexes have facilitated the early detection and functional characterisation of epitope specific CD8+ cytotoxic T lymphocytes (CTL). Here, we report on the generation of seven recombinant bovine leukocyte antigens (BoLA) and recombinant bovine β2-microglobulin from which p-MHC class I tetramers can be derived in ~48 h. We validated a set of p-MHC class I tetramers against a panel of CTL lines specific to seven epitopes on five different antigens of Theileria parva, a protozoan pathogen causing the lethal bovine disease East Coast fever. One of the p-MHC class I tetramers was tested in ex vivo assays and we detected T. parva specific CTL in peripheral blood of cattle at day 15-17 post-immunization with a live parasite vaccine. The algorithm NetMHCpan predicted alternative epitope sequences for some of the T. parva CTL epitopes. Using an ELISA assay to measure peptide-BoLA monomer formation and p-MHC class I tetramers of new specificity, we demonstrate that a predicted alternative epitope Tp229-37 rather than the previously reported Tp227-37 epitope is the correct Tp2 epitope presented by BoLA-6*04101. We also verified the prediction by NetMHCpan that the Tp587-95 epitope reported as BoLA-T5 restricted can also be presented by BoLA-1*02301, a molecule similar in sequence to BoLA-T5. In addition, Tp587-95 specific bovine CTL were simultaneously stained by Tp5-BoLA-1*02301 and Tp5-BoLA-T5 tetramers suggesting that one T cell receptor can bind to two different BoLA MHC class I molecules presenting the Tp587-95 epitope and that these BoLA molecules fall into a single functional supertype.
The cartography of β-cell epitopes targeted by CD8+ T cells in type 1 diabetic (T1D) patients remains largely confined to the common HLA-A2 restriction. We aimed to identify β-cell epitopes restricted by the HLA-B7 (B*07:02) molecule, which is associated with mild T1D protection. Using DNA immunization on HLA-B7–transgenic mice and prediction algorithms, we identified GAD and preproinsulin candidate epitopes. Interferon-γ (IFN-γ) enzyme-linked immunospot assays on peripheral blood mononuclear cells showed that most candidates were recognized by new-onset T1D patients, but not by type 2 diabetic and healthy subjects. Some epitopes were highly immunodominant and specific to either T1D children (GAD530–538; 44% T cell–positive patients) or adults (GAD311–320; 38%). All epitopes displayed weak binding affinity and stability for HLA-B7 compared with HLA-A2–restricted ones, a general feature of HLA-B7. Single-cell PCR analysis on β-cell–specific (HLA-B7 tetramer–positive) T cells revealed uniform IFN-γ and transforming growth factor-β (TGF-β) mRNA expression, different from HLA-A2–restricted T cells. We conclude that HLA-B7–restricted islet epitopes display weak HLA-binding profiles, are different in T1D children and adults, and are recognized by IFN-γ+TGF-β+CD8+ T cells. These features may explain the T1D-protective effect of HLA-B7. The novel epitopes identified should find valuable applications for immune staging of HLA-B7+ individuals.
Recent studies in the SIV-macaque model of HIV infection suggest that Nef-specific CD8+ T-cell responses may mediate highly effective immune control of viraemia. In HIV infection Nef recognition dominates in acute infection, but in large cohort studies of chronically infected subjects, breadth of T cell responses to Nef has not been correlated with significant viraemic control. Improved disease outcomes have instead been associated with targeting Gag and, in some cases, Pol. However analyses of the breadth of Nef-specific T cell responses have been confounded by the extreme immunogenicity and multiple epitope overlap within the central regions of Nef, making discrimination of distinct responses impossible via IFN-gamma ELISPOT assays. Thus an alternative approach to assess Nef as an immune target is needed. Here, we show in a cohort of >700 individuals with chronic C-clade infection that >50% of HLA-B-selected polymorphisms within Nef are associated with a predicted fitness cost to the virus, and that HLA-B alleles that successfully drive selection within Nef are those linked with lower viral loads. Furthermore, the specific CD8+ T cell epitopes that are restricted by protective HLA Class I alleles correspond substantially to effective SIV-specific epitopes in Nef. Distinguishing such individual HIV-specific responses within Nef requires specific peptide-MHC I tetramers. Overall, these data suggest that CD8+ T cell targeting of certain specific Nef epitopes contributes to HIV suppression. These data suggest that a re-evaluation of the potential use of Nef in HIV T-cell vaccine candidates would be justified.
Targeting CD4+ T cells through their unique antigen-specific, MHC class II-restricted T cell receptor makes MHC class II tetramers an attractive strategy to identify, validate and manipulate these cells at the single cell level. Currently, generating class II tetramers is a specialized undertaking effectively limiting their use and emphasizing the need for improved methods of production. Using class II chains expressed individually in E. coli as versatile recombinant reagents, we have previously generated peptide-MHC class II monomers, but failed to generate functional class II tetramers. Adding a monomer purification principle based upon affinity-tagged peptides, we here provide a robust method to produce class II tetramers and demonstrate staining of antigen-specific CD4+ T cells. We also provide evidence that both MHC class II and T cell receptor molecules largely accept affinity-tagged peptides. As a general approach to class II tetramer generation, this method should support rational CD4+ T cell epitope discovery as well as enable specific monitoring and manipulation of CD4+ T cell responses.
The potential contribution of HLA-A alleles to viremic control in chronic HIV type 1 (HIV-1) infection has been relatively understudied compared with HLA-B. In these studies, we show that HLA-A*7401 is associated with favorable viremic control in extended southern African cohorts of >2100 C-clade–infected subjects. We present evidence that HLA-A*7401 operates an effect that is independent of HLA-B*5703, with which it is in linkage disequilibrium in some populations, to mediate lowered viremia. We describe a novel statistical approach to detecting additive effects between class I alleles in control of HIV-1 disease, highlighting improved viremic control in subjects with HLA-A*7401 combined with HLA-B*57. In common with HLA-B alleles that are associated with effective control of viremia, HLA-A*7401 presents highly targeted epitopes in several proteins, including Gag, Pol, Rev, and Nef, of which the Gag epitopes appear immunodominant. We identify eight novel putative HLA-A*7401–restricted epitopes, of which three have been defined to the optimal epitope. In common with HLA-B alleles linked with slow progression, viremic control through an HLA-A*7401–restricted response appears to be associated with the selection of escape mutants within Gag epitopes that reduce viral replicative capacity. These studies highlight the potentially important contribution of an HLA-A allele to immune control of HIV infection, which may have been concealed by a stronger effect mediated by an HLA-B allele with which it is in linkage disequilibrium. In addition, these studies identify a factor contributing to different HIV disease outcomes in individuals expressing HLA-B*5703.
The strongest genetic influence on immune control in HIV-1 infection is the HLA class I genotype. Rapid disease progression in B-clade infection has been linked to HLA-B*35 expression, in particular to the less common HLA-B*3502 and HLA-B*3503 subtypes but also to the most prevalent subtype, HLA-B*3501. In these studies we first demonstrated that whereas HLA-B*3501 is associated with a high viral set point in two further B-clade-infected cohorts, in Japan and Mexico, this association does not hold in two large C-clade-infected African cohorts. We tested the hypothesis that clade-specific differences in HLA associations with disease outcomes may be related to distinct targeting of critical CD8+ T-cell epitopes. We observed that only one epitope was significantly targeted differentially, namely, the Gag-specific epitope NPPIPVGDIY (NY10, Gag positions 253 to 262) (P = 2 × 10−5). In common with two other HLA-B*3501-restricted epitopes, in Gag and Nef, that were not targeted differentially, a response toward NY10 was associated with a significantly lower viral set point. Nonimmunogenicity of NY10 in B-clade-infected subjects derives from the Gag-D260E polymorphism present in ∼90% of B-clade sequences, which critically reduces recognition of the Gag NY10 epitope. These data suggest that in spite of any inherent HLA-linked T-cell receptor repertoire differences that may exist, maximizing the breadth of the Gag-specific CD8+ T-cell response, by the addition of even a single epitope, may be of overriding importance in achieving immune control of HIV infection. This distinction is of direct relevance to development of vaccines designed to optimize the anti-HIV CD8+ T-cell response in all individuals, irrespective of HLA type.
Genetic variation within the HLA-B locus has the strongest impact on HIV disease progression of any polymorphisms within the human genome. However, identifying the exact mechanism involved is complicated by several factors. HLA-Bw4 alleles provide ligands for NK cells and for CD8 T cells, and strong linkage disequilibrium between HLA class I alleles complicates the discrimination of individual HLA allelic effects from those of other HLA and non-HLA alleles on the same haplotype. Here, we exploit an experiment of nature involving two recently diverged HLA alleles, HLA-B*42:01 and HLA-B*42:02, which differ by only a single amino acid. Crucially, they occur primarily on identical HLA class I haplotypes and, as Bw6 alleles, do not act as NK cell ligands and are therefore largely unconfounded by other genetic factors. We show that in an outbred cohort (n = 2,093) of HIV C-clade-infected individuals, a single amino acid change at position 9 of the HLA-B molecule critically affects peptide binding and significantly alters the cytotoxic T lymphocyte (CTL) epitopes targeted, measured directly ex vivo by gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay (P = 2 × 10−10) and functionally through CTL escape mutation (P = 2 × 10−8). HLA-B*42:01, which presents multiple Gag epitopes, is associated with a 0.52 log10 lower viral-load set point than HLA-B*42:02 (P = 0.02), which presents no p24 Gag epitopes. The magnitude of this effect from a single amino acid difference in the HLA-A*30:01/B*42/Cw*17:01 haplotype is equivalent to 75% of that of HLA-B*57:03, the most protective HLA class I allele in this population. This naturally controlled experiment represents perhaps the clearest demonstration of the direct impact of a particular HIV-specific CTL on disease control.
CD8+ T cells (TCD8) confer protective immunity against many infectious diseases, suggesting that microbial TCD8 determinants are promising vaccine targets. Nevertheless, current T cell antigen identification approaches do not discern which epitopes drive protective immunity during active infection — information that is critical for the rational design of TCD8-targeted vaccines. We employed a proteomics-based approach for large-scale discovery of naturally processed determinants derived from a complex pathogen, vaccinia virus (VACV), that are presented by the most frequent representatives of four major HLA class I supertypes. Immunologic characterization revealed that many previously unidentified VACV determinants were recognized by smallpox-vaccinated human peripheral blood cells in a variegated manner. Many such determinants were recognized by HLA class I–transgenic mouse immune TCD8 too and elicited protective TCD8 immunity against lethal intranasal VACV infection. Notably, efficient processing and stable presentation of immune determinants as well as the availability of naive TCD8 precursors were sufficient to drive a multifunctional, protective TCD8 response. Our approach uses fundamental insights into T cell epitope processing and presentation to define targets of protective TCD8 immunity within human pathogens that have complex proteomes, suggesting that this approach has general applicability in vaccine sciences.
We here report a novel phage display selection strategy enabling fast and easy selection of thermostabilized proteins. The approach is illustrated with stabilization of an aggregation-prone soluble single chain T cell receptor (scTCR) characteristic of the murine MOPC315 myeloma model. Random mutation scTCR phage libraries were prepared in E. coli over-expressing the periplasmic chaperone FkpA, and such over-expression during library preparation proved crucial for successful downstream selection. The thermostabilized scTCRmut variants selected were produced in high yields and isolated as monomers. Thus, the purified scTCRs could be studied with regard to specificity and equilibrium binding kinetics to pMHC using surface plasmon resonance (SPR). The results demonstrate a difference in affinity for pMHCs that display germ line or tumor-specific peptides which explains the tumor-specific reactivity of the TCR. This FkpA-assisted thermostabilization strategy extends the utility of recombinant TCRs and furthermore, may be of general use for efficient evolution of proteins.
Aberrant glycosylation of mucins and other extracellular proteins is an important event in carcinogenesis and the resulting cancer associated glycans have been suggested as targets in cancer immunotherapy. We assessed the role of O-linked GalNAc glycosylation on antigen uptake, processing, and presentation on MHC class I and II molecules. The effect of GalNAc O-glycosylation was monitored with a model system based on ovalbumin (OVA)-MUC1 fusion peptides (+/− glycosylation) loaded onto dendritic cells co-cultured with IL-2 secreting OVA peptide-specific T cell hybridomas. To evaluate the in vivo response to a cancer related tumor antigen, Balb/c or B6.Cg(CB)-Tg(HLA-A/H2-D)2Enge/J (HLA-A2 transgenic) mice were immunized with a non-glycosylated or GalNAc-glycosylated MUC1 derived peptide followed by comparison of T cell proliferation, IFN-γ release, and antibody induction. GalNAc-glycosylation promoted presentation of OVA-MUC1 fusion peptides by MHC class II molecules and the MUC1 antigen elicited specific Ab production and T cell proliferation in both Balb/c and HLA-A2 transgenic mice. In contrast, GalNAc-glycosylation inhibited the presentation of OVA-MUC1 fusion peptides by MHC class I and abolished MUC1 specific CD8+ T cell responses in HLA-A2 transgenic mice. GalNAc glycosylation of MUC1 antigen therefore facilitates uptake, MHC class II presentation, and antibody response but might block the antigen presentation to CD8+ T cells.
Antibodies empower numerous important scientific, clinical, diagnostic, and industrial applications. Ideally, the epitope(s) targeted by an antibody should be identified and characterized, thereby establishing antibody reactivity, highlighting possible cross-reactivities, and perhaps even warning against unwanted (e.g. autoimmune) reactivities. Antibodies target proteins as either conformational or linear epitopes. The latter are typically probed with peptides, but the cost of peptide screening programs tends to prohibit comprehensive specificity analysis. To perform high-throughput, high-resolution mapping of linear antibody epitopes, we have used ultrahigh-density peptide microarrays generating several hundred thousand different peptides per array. Using exhaustive length and substitution analysis, we have successfully examined the specificity of a panel of polyclonal antibodies raised against linear epitopes of the human proteome and obtained very detailed descriptions of the involved specificities. The epitopes identified ranged from 4 to 12 amino acids in size. In general, the antibodies were of exquisite specificity, frequently disallowing even single conservative substitutions. In several cases, multiple distinct epitopes could be identified for the same target protein, suggesting an efficient approach to the generation of paired antibodies. Two alternative epitope mapping approaches identified similar, although not necessarily identical, epitopes. These results show that ultrahigh-density peptide microarrays can be used for linear epitope mapping. With an upper theoretical limit of 2,000,000 individual peptides per array, these peptide microarrays may even be used for a systematic validation of antibodies at the proteomic level.
The genetic polymorphism that has the greatest impact on immune control of human immunodeficiency virus (HIV) infection is expression of HLA-B*57. Understanding of the mechanism for this strong effect remains incomplete. HLA-B*57 alleles and the closely related HLA-B*5801 are often grouped together because of their similar peptide-binding motifs and HIV disease outcome associations. However, we show here that the apparently small differences between HLA-B*57 alleles, termed HLA-B*57 micropolymorphisms, have a significant impact on immune control of HIV. In a study cohort of >2,000 HIV C-clade-infected subjects from southern Africa, HLA-B*5703 is associated with a lower viral-load set point than HLA-B*5702 and HLA-B*5801 (medians, 5,980, 15,190, and 19,000 HIV copies/ml plasma; P = 0.24 and P = 0.0005). In order to better understand these observed differences in HLA-B*57/5801-mediated immune control of HIV, we undertook, in a study of >1,000 C-clade-infected subjects, a comprehensive analysis of the epitopes presented by these 3 alleles and of the selection pressure imposed on HIV by each response. In contrast to previous studies, we show that each of these three HLA alleles is characterized both by unique CD8+ T-cell specificities and by clear-cut differences in selection pressure imposed on the virus by those responses. These studies comprehensively define for the first time the CD8+ T-cell responses and immune selection pressures for which these protective alleles are responsible. These findings are consistent with HLA class I alleles mediating effective immune control of HIV through the number of p24 Gag-specific CD8+ T-cell responses generated that can drive significant selection pressure on the virus.
Binding of peptides to major histocompatibility complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC genomic region (called HLA) is extremely polymorphic comprising several thousand alleles, each encoding a distinct MHC molecule. The potentially unique specificity of the majority of HLA alleles that have been identified to date remains uncharacterized. Likewise, only a limited number of chimpanzee and rhesus macaque MHC class I molecules have been characterized experimentally. Here, we present NetMHCpan-2.0, a method that generates quantitative predictions of the affinity of any peptide–MHC class I interaction. NetMHCpan-2.0 has been trained on the hitherto largest set of quantitative MHC binding data available, covering HLA-A and HLA-B, as well as chimpanzee, rhesus macaque, gorilla, and mouse MHC class I molecules. We show that the NetMHCpan-2.0 method can accurately predict binding to uncharacterized HLA molecules, including HLA-C and HLA-G. Moreover, NetMHCpan-2.0 is demonstrated to accurately predict peptide binding to chimpanzee and macaque MHC class I molecules. The power of NetMHCpan-2.0 to guide immunologists in interpreting cellular immune responses in large out-bred populations is demonstrated. Further, we used NetMHCpan-2.0 to predict potential binding peptides for the pig MHC class I molecule SLA-1*0401. Ninety-three percent of the predicted peptides were demonstrated to bind stronger than 500 nM. The high performance of NetMHCpan-2.0 for non-human primates documents the method's ability to provide broad allelic coverage also beyond human MHC molecules. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan.
MHC class I; Binding specificity; Non-human primates; Artificial neural networks; CTL epitopes
Synthetic peptides are widely used in immunological research as epitopes to stimulate their cognate T cells. These preparations are never completely pure, but trace contaminants are commonly revealed by mass spectrometry quality controls. In an effort to characterize novel major histocompatibility complex (MHC) Class I-restricted β-cell epitopes in non-obese diabetic (NOD) mice, we identified islet-infiltrating CD8+ T cells recognizing a contaminating peptide. The amount of this contaminant was so small to be undetectable by direct mass spectrometry. Only after concentration by liquid chromatography, we observed a mass peak corresponding to an immunodominant islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP)206-214 epitope described in the literature. Generation of CD8+ T-cell clones recognizing IGRP206-214 using a novel method confirmed the identity of the contaminant, further underlining the immunodominance of IGRP206-214. If left undetected, minute impurities in synthetic peptide preparations may thus give spurious results.