MHC binding peptides for designing of vaccines against Japanese encephalitis virus: A computational approach

Japanese encephalitis (JE), a viral disease has seen a drastic and fatal enlargement in the northern states of India in the current decade. The better and exact cure for the disease is still in waiting. For the cause an in silico strategy in the development of the peptide vaccine has been taken here for the study. A computational approach to find out the Major Histocompatibility Complex (MHC) binding peptide has been implemented. The prediction analysis identified MHC class I (using propred I) and MHC class II (using propred) binding peptides at an expectable percent predicted IC (50) threshold values. These predicted Human leukocyte antigen [HLA] allele binding peptides were further analyzed for potential conserved region using an Immune Epitope Database and Analysis Resource (IEDB). This analysis shows that HLA-DRB1*0101, HLA-DRB3*0101, HLA-DRB1*0401, HLA-DRB1*0102 and HLA-DRB1*07:01% of class II (in genotype 2) and HLA-A*0101, HLA-A*02, HLA-A*0301, HLA-A*2402, HLA-B*0702 and HLA-B*4402% of HLA I (in genotype 3) bound peptides are conserved. The predicted peptides MHC class I are ILDSNGDIIGLY, FVMDEAHFTDPA, KTRKILPQIIK, RLMSPNRVPNYNLF, APTRVVAAEMAEAL, YENVFHTLW and MHC class II molecule are TTGVYRIMARGILGT, NYNLFVMDEAHFTDP, AAAIFMTATPPGTTD, GDTTTGVYRIMARGI and FGEVGAVSL found to be top ranking with potential super antigenic property by binding to all HLA. Out of these the predicted peptide FVMDEAHFTDPA for allele HLA-A*02:01 in MHC class I and NYNLFVMDEAHFTDP for allele HLA-DRB3*01:01 in MHC class II was observed to be most potent and can be further proposed as a significant vaccine in the process. The reported results revealed that the immune-informatics techniques implemented in the development of small size peptide is useful in the development of vaccines against the Japanese encephalitis virus (JEV).     

Sequence and Structure Based Binding Prediction Study of HLA Class I and cTAP Binding Peptides for Japanese Encephalitis Vaccine Development

Japanese encephalitis is a major threat in developing countries, even the availability of several conventional vaccines, which demand development of more effective vaccines. The present study used propred I and Immune Epitope Database Artificial Neural Network (ANN) algorithm (IEDB-ANN) to identify the conserve and promiscuous T cell epitopes from JEV proteome followed by structure based analysis of potential epitopes. Among all identified 102 epitopes, ten epitope were promiscuous but two epitopes of glycoprotein viz. ⁵⁵LVTVNPFVA⁶³ and ³⁸IPIVSVASL⁴⁶ were found most promiscuous, highly conserved and high population coverage in comparison of known antigenic positive control peptides. The B cell epitopes of glycoprotein also share these two T cell epitopes revealed by BCPred algorithm which can be a basis to confer the protection by neutralizing antibody combined with an effective cell-mediated response. Further, Autodock 4.2 and NAMD–VMD molecular dynamics simulation were used for docking and molecular dynamics simulation respectively, to validate epitope and allele complex binding stability. The 3D structure models were generated for epitopes and corresponding HLA allele by Pepstr and Modeller 9.10 respectively. Epitope LVTVNPFVA–B5101 allele complex showed best energy minimization and stability over the time window during simulation. Here we also present the binding sequel of epitope LVTVNPFVA and its eventual transport through cTAP1 (PDB ID: 1JJ7) revealed by Autodock 4.2, which is an essential path for HLA class I binding epitopes to elicit immune response. The docking experiment of epitope LVTVNPFVA and cTAP1 very well show a 2 H-bond with a binding energy of ?1.88 kcal/mol and other binding state of epitope forming no H-bond with a binding energy of ?1.13 kcal/mol in the lower area of cTAP1 cavity. These results show a smooth pass through of the epitope across the channel of cTAP1. Overall, identified peptides have potential application in the design and development of short peptide based vaccines and diagnostic agents for Japanese encephalitis.     

T-Epitope Designer: A HLA-peptide binding prediction server

The current challenge in synthetic vaccine design is the development of a methodology to identify and test short antigen peptides as potential T-cell epitopes. Recently, we described a HLA-peptide binding model (using structural properties) capable of predicting peptides binding to any HLA allele. Consequently, we have developed a web server named T-EPITOPE DESIGNER to facilitate HLA-peptide binding prediction. The prediction server is based on a model that defines peptide binding pockets using information gleaned from X-ray crystal structures of HLA-peptide complexes, followed by the estimation of peptide binding to binding pockets. Thus, the prediction server enables the calculation of peptide binding to HLA alleles. This model is superior to many existing methods because of its potential application to any given HLA allele whose sequence is clearly defined. The web server finds potential application in T cell epitope vaccine design. AVAILABILITY: http://www.bioinformation.net/ted/     

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.     

Immunogenicity of HLA Class I and II Double Restricted Influenza A-Derived Peptides

The aim of the present study was to identify influenza A-derived peptides which bind to both HLA class I and -II molecules and by immunization lead to both HLA class I and class II restricted immune responses. Eight influenza A-derived 9-11mer peptides with simultaneous binding to both HLA-A*02:01 and HLA-DRB1*01:01 molecules were identified by bioinformatics and biochemical technology. Immunization of transgenic HLA-A*02:01/HLA-DRB1*01:01 mice with four of these double binding peptides gave rise to both HLA class I and class II restricted responses by CD8 and CD4 T cells, respectively, whereas four of the double binding peptides did result in HLA-A*02:01 restricted responses only. According to their cytokine profile, the CD4 T cell responses were of the Th2 type. In influenza infected mice, we were unable to detect natural processing in vivo of the double restricted peptides and in line with this, peptide vaccination did not decrease virus titres in the lungs of intranasally influenza challenged mice. Our data show that HLA class I and class II double binding peptides can be identified by bioinformatics and biochemical technology. By immunization, double binding peptides can give rise to both HLA class I and class I restricted responses, a quality which might be of potential interest for peptide-based vaccine development.     

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.     

A combined immuno-informatics and structure-based modeling approach for prediction of T cell epitopes of secretory proteins of Mycobacterium tuberculosis

The role of secretory proteins of Mycobacterium tuberculosis in pathogenesis and stimulation of specific host responses is well documented. They are also shown to activate different cell types, which subsequently present mycobacterial antigens to T cells. Therefore identification of T cell epitopes from this set of proteins may serve to define candidate antigens with vaccine potential. Fifty-two secretory proteins of M. tuberculosis H37Rv were analyzed computationally for the presence of HLA class I binding nonameric peptides. All possible overlapping nonameric peptide sequences from 52 secretory proteins were generated in silico and analyzed for their ability to bind to 33 alleles belonging to A, B and C loci of HLA class I. Fifteen percent of generated peptides are predicted to bind to HLA with halftime of dissociation T(1/2) >or=100 min and 73% of the peptides predicted to bind are mono-allelic in their binding. The structural basis for recognition of no-namers by different HLA molecules was studied employing structural modeling of HLA class I-peptide complexes and there exists a good correlation between structural analysis and binding prediction. Pathogen peptides that could behave as self- or partially self-peptides in the host were eliminated using a comparative study with the human proteome, thus reducing the number of peptides for analysis. The implications of the finding for vaccine development are discussed vis-à-vis the limitations of the use of subunit vaccine and DNA vaccine.     

Identification and characterization of novel, naturally processed measles virus class II HLA-DRB1 peptides

Previously, we identified a naturally processed and presented measles virus (MV) 19-amino-acid peptide, ASDVETAEGGEIHELLRLQ (MV-P), derived from the phosphoprotein and eluted from the human leukocyte antigen (HLA) class II molecule by using mass spectrometry. We report here the identification of a 14-amino-acid peptide, SAGKVSSTLASELG, derived from the MV nucleoprotein (MV-N) bound to HLA-DRB1*0301. Peripheral blood mononuclear cells (PBMC) from 281 previously vaccinated measles-mumps-rubella II (MMR-II) subjects (HLA discordant) were studied for peptide recognition by T cells. Significant gamma interferon (IFN-gamma) responses to MV-P and MV-N peptides were observed in 55.9 and 15.3% of subjects, respectively. MV-P- and MV-N-specific interleukin-4 (IL-4) responses were detected in 19.2 and 23.1%, respectively, of PBMC samples. Peptide-specific cytokine responses and HLA-DRB1 allele associations revealed that, for the MV-P peptide, the allele with the strongest association with both IFN-gamma (P = 0.02) and IL-4 (P = 0.03) secretion was DRB1*0301. For MV-N, the allele with the strongest association with IFN-gamma secretion was DRB1*1501 (P = 0.04), and the alleles with the strongest associations with IL-4 secretion were DRB1*1103 and DRB1*1303 (P = 0.01). These results indicate that HLA class II MV proteins can be processed, presented, and identified, and the ability to generate cell-mediated immune responses can be demonstrated. This information is promising for new vaccine design strategies with peptide-based vaccines.     

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.     

Immunomic analysis of the repertoire of T-cell specificities for influenza A virus in humans

Continuing antigenic drift allows influenza viruses to escape antibody-mediated recognition, and as a consequence, the vaccine currently in use needs to be altered annually. Highly conserved epitopes recognized by effector T cells may represent an alternative approach for the generation of a more universal influenza virus vaccine. Relatively few highly conserved epitopes are currently known in humans, and relatively few epitopes have been identified from proteins other than hemagglutinin and nucleoprotein. This prompted us to perform a study aimed at identifying a set of human T-cell epitopes that would provide broad coverage against different virus strains and subtypes. To provide coverage across different ethnicities, seven different HLA supertypes were considered. More than 4,000 peptides were selected from a panel of 23 influenza A virus strains based on predicted high-affinity binding to HLA class I or class II and high conservancy levels. Peripheral blood mononuclear cells from 44 healthy human blood donors were tested for reactivity against HLA-matched peptides by using gamma interferon enzyme-linked immunospot assays. Interestingly, we found that PB1 was the major target for both CD4(+) and CD8(+) T-cell responses. The 54 nonredundant epitopes (38 class I and 16 class II) identified herein provided high coverage among different ethnicities, were conserved in the majority of the strains analyzed, and were consistently recognized in multiple individuals. These results enable further functional studies of T-cell responses during influenza virus infection and provide a potential base for the development of a universal influenza vaccine.     

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.     

Broad-spectrum antiviral activity of RNA interference against four genotypes of Japanese encephalitis virus based on single microRNA polycistrons

Japanese encephalitis virus (JEV), a neurotropic mosquito-borne flavivirus, causes acute viral encephalitis and neurologic disease with a high fatality rate in humans and a range of animals. Small interfering RNA (siRNA) is a powerful antiviral agent able to inhibit JEV replication. However, the high rate of genetic variability between JEV strains (of four confirmed genotypes, genotypes I, II, III and IV) hampers the broad-spectrum application of siRNAs, and mutations within the targeted sequences could facilitate JEV escape from RNA interference (RNAi)-mediated antiviral therapy. To improve the broad-spectrum application of siRNAs and prevent the generation of escape mutants, multiple siRNAs targeting conserved viral sequences need to be combined. In this study, using a siRNA expression vector based on the miR-155 backbone and promoted by RNA polymerase II, we initially identified nine siRNAs targeting highly conserved regions of seven JEV genes among strains of the four genotypes of JEV to effectively block the replication of the JEV vaccine strain SA14-14-2. Then, we constructed single microRNA-like polycistrons to simultaneously express these effective siRNAs under a single RNA polymerase II promoter. Finally, these single siRNAs or multiple siRNAs from the microRNA-like polycistrons showed effective anti-virus activity in genotype I and genotype III JEV wild type strains, which are the predominant genotypes of JEV in mainland China. The anti-JEV effect of these microRNA-like polycistrons was also predicted in other genotypes of JEV (genotypes II and IV), The inhibitory efficacy indicated that siRNAs×9 could theoretically inhibit the replication of JEV genotypes II and IV.     

Naturally processed HLA class II peptides reveal highly conserved immunogenic flanking region sequence preferences that reflect antigen processing rather than peptide-MHC interactions

MHC class II heterodimers bind peptides 12-20 aa in length. The peptide flanking residues (PFRs) of these ligands extend from a central binding core consisting of nine amino acids. Increasing evidence suggests that the PFRs can alter the immunogenicity of T cell epitopes. We have previously noted that eluted peptide pool sequence data derived from an MHC class II Ag reflect patterns of enrichment not only in the core binding region but also in the PFRS: We sought to distinguish whether these enrichments reflect cellular processes or direct MHC-peptide interactions. Using the multiple sclerosis-associated allele HLA-DR2, pool sequence data from naturally processed ligands were compared with the patterns of enrichment obtained by binding semicombinatorial peptide libraries to empty HLA-DR2 molecules. Naturally processed ligands revealed patterns of enrichment reflecting both the binding motif of HLA-DR2 (position (P)1, aliphatic; P4, bulky hydrophobic; and P6, polar) as well as the nonbound flanking regions, including acidic residues at the N terminus and basic residues at the C terminus. These PFR enrichments were independent of MHC-peptide interactions. Further studies revealed similar patterns in nine other HLA alleles, with the C-terminal basic residues being as highly conserved as the previously described N-terminal prolines of MHC class II ligands. There is evidence that addition of C-terminal basic PFRs to known peptide epitopes is able to enhance both processing as well as T cell activation. Recognition of these allele-transcending patterns in the PFRs may prove useful in epitope identification and vaccine design.     

BIITE: A Tool to Determine HLA Class II Epitopes from T Cell ELISpot Data

Activation of CD4⁺ T cells requires the recognition of peptides that are presented by HLA class II molecules and can be assessed experimentally using the ELISpot assay. However, even given an individual’s HLA class II genotype, identifying which class II molecule is responsible for a positive ELISpot response to a given peptide is not trivial. The two main difficulties are the number of HLA class II molecules that can potentially be formed in a single individual (3–14) and the lack of clear peptide binding motifs for class II molecules. Here, we present a Bayesian framework to interpret ELISpot data (BIITE: Bayesian Immunogenicity Inference Tool for ELISpot); specifically BIITE identifies which HLA-II:peptide combination(s) are immunogenic based on cohort ELISpot data. We apply BIITE to two ELISpot datasets and explore the expected performance using simulations. We show this method can reach high accuracies, depending on the cohort size and the success rate of the ELISpot assay within the cohort.     

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     

Immunoinformatics Approach to Design T-cell Epitope-Based Vaccine Against Hendra Virus

Screening of HLA class II epitope-based peptides as potential vaccine candidates is one of the most rational approach for vaccine development against Hendra virus (HeV) infection, for which currently there is no successful vaccine in practice. In this study, screening of epitopes from HeV proteins viz matrix, glycoprotein, nucleocapsid, fusion, C protein, V protein, W protein and polymerase, followed by highest binding affinity & molecular dynamic simulation of selected T-cell epitopes with their corresponding HLA class II alleles has been done. The server ProPred facilitates the binding prediction of HLA class II allele specific epitopes from the antigenic protein sequences of HeV. PEPstrMOD server was used for PDB structure modeling of the screened epitopes and MODELLER was used for HLA alleles modeling. We docked the selected T-cell epitopes with their corresponding HLA allele structures using the AutoDock 4.2 tool. Further the selected docked complex structures were optimized by NAnoscale Molecular Dynamics program (NAMD) at 5 ps, with the CHARMM-22 force field parameter incorporated in Visual Molecular Dynamics (VMD 1.9.2) and complex structure stability was evaluated by calculating RMSD values. Epitopes IRIFVPATN (Nucleocapsid), MRNLLSQSL (Nucleocapsid), VRRAGKYYS (Matrix) and VRLKCLLCG (Fusion) proteins have shown considerable binding with DRB1*0806, DRB1*1304, DRB1*0701 and DRB1*0301 HLA class II allele respectively. Toxicity, antigenicity and population coverage of epitopes IRIFVPATN, MRNLLSQSL, VRRAGKYYS and VRLKCLLCG were analyzed by Toxin Pred, Vexijen and IEDB tool, respectively. The potential T-cell epitopes can be utilized in designing comprehensive epitope-based vaccines and diagnostic kits against Hendra virus after further in-vivo studies.

     

Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection

Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken.     

Anti-group A streptococcal vaccine epitope: structure, stability, and its ability to interact with HLA class II molecules

Streptococcus pyogenes infections remain a health problem in several countries due to poststreptococcal sequelae. We developed a vaccine epitope (StreptInCor) composed of 55 amino acids residues of the C-terminal portion of the M protein that encompasses both T and B cell protective epitopes. The nuclear magnetic resonance (NMR) structure of the StreptInCor peptide showed that the structure was composed of two microdomains linked by an 18-residue α-helix. A chemical stability study of the StreptInCor folding/unfolding process using far-UV circular dichroism showed that the structure was chemically stable with respect to pH and the concentration of urea. The T cell epitope is located in the first microdomain and encompasses 11 out of the 18 α-helix residues, whereas the B cell epitope is in the second microdomain and showed no α-helical structure. The prediction of StreptInCor epitope binding to different HLA class II molecules was evaluated based on an analysis of the 55 residues and the theoretical possibilities for the processed peptides to fit into the P1, P4, P6, and P9 pockets in the groove of several HLA class II molecules. We observed 7 potential sites along the amino acid sequence of StreptInCor that were capable of recognizing HLA class II molecules (DRB1*, DRB3*, DRB4*, and DRB5*). StreptInCor-overlapping peptides induced cellular and humoral immune responses of individuals bearing different HLA class II molecules and could be considered as a universal vaccine epitope.     

烟曲霉抗原Asp f16HLA-A*0201限制性的CD8+CTL抗原表位生物信息学预测与实验室鉴定

目的 预测与鉴定烟曲霉抗原Asp f16的HLA-A *0201限制性CD8+细胞毒性T细胞(CTL)抗原表位.方法 以国人常见的HLA-A*0201位点为靶点,依据生物信息学软件扫描烟曲霉特异性抗原Asp f16的全部427个氨基酸序列.使用HLA-A *0201转基因小鼠制备骨髓来源的树突状细胞(DC)和CTL.流式细胞仪技术检测DC表面MHC Ⅱ类抗原,CD80,CD86和CD11c的表达来验证其是否成熟.ELISPOT试验检测烟曲霉抗原多肽特异性CTL产生的细胞因子IFN-γ.四聚体(Tetramer)试验证实烟曲霉特异性CTL与抗原肽,HLA-A*0201分子复合体的亲和性.结果 根据与MHC I类分子结合的半衰期评分,选择了3个HLA-A*0201限制性抗原表位.流式细胞仪分析示成熟DC高表达HLA Ⅱ类抗原,CD80,CD86和CD11c.Tetramer试验证实烟曲霉特异性T细胞受体与抗原肽,HLA-A*0201分子复合体的高亲和性.ELISPOT实验结果 表明烟曲霉抗原肽体外可以活化CD8+CTL,被负载了抗原肽的DC刺激活化后可以产生IFN-γ.结论 本研究成功鉴定烟曲霉抗原Asp f16的HLA-A*0201限制性CD8+CTL表位,可作为疫苗设计的候选表位,为进一步研发新型抗烟曲霉疫苗提供参考.     

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.