Kinetic analysis of peptide loading onto HLA-DR molecules mediated by HLA-DM.

The nonclassical major histocompatibility complex class II molecule HLA-DM (DM) has recently been shown to play a central role in the class II-associated antigen presentation pathway: DM releases invariant chain-derived CLIP peptides (class II-associated invariant chain protein peptide) from HLA-DR (DR) molecules and thereby facilitates loading with antigenic peptides. Some observations have led to the suggestion that DM acts in a catalytic manner, but so far direct proof is missing. Here, we investigated in vitro the kinetics of exchange of endogenously bound CLIP for various peptides on DR1 and DR2a molecules: we found that in the presence of DM the peptide loading process follows Michaelis-Menten kinetics with turnover numbers of 3-12 DR molecules per minute per DM molecule, and with KM values of 500-1000 nM. In addition, surface plasmon resonance measurements showed that DM interacts efficiently with DR-CLIP complexes but only weakly with DR-peptide complexes isolated from DM-positive cells. Taken together, our data provide evidence that DM functions as an enzyme-like catalyst of peptide exchange and favors the generation of long-lived DR-peptide complexes that are no longer substrates for DM.

Crystallographic analysis of endogenous peptides associated with HLA-DR1 suggests a common, polyproline II-like conformation for bound peptides.

The structure of the human major histocompatibility complex (MHC) class II molecule HLA-DR1 derived from the human lymphoblastoid cell line LG-2 has been determined in a complex with the Staphylococcus aureus enterotoxin B superantigen. The HLA-DR1 molecule contains a mixture of endogenous peptides derived from cellular or serum proteins bound in the antigen-binding site, which copurify with the class II molecule. Continuous electron density for 13 amino acid residues is observed in the MHC peptide-binding site, suggesting that this is the core length of peptide that forms common interactions with the MHC molecule. Electron density is also observed for side chains of the endogenous peptides. The electron density corresponding to peptide side chains that interact with the DR1-binding site is more clearly defined than the electron density that extends out of the binding site. The regions of the endogenous peptides that interact with DRI are therefore either more restricted in conformation or sequence than the peptide side chains or amino acids that project out of the peptide-binding site. The hydrogen-bond interactions and conformation of a peptide model built into the electron density are similar to other HLA-DR-peptide structures. The bound peptides assume a regular conformation that is similar to a polyproline type II helix. The side-chain pockets and conserved asparagine residues of the DR1 molecule are well-positioned to interact with peptides in the polyproline type II conformation and may restrict the range of acceptable peptide conformations.

HLA-Cw allele analysis by PCR-restriction fragment length polymorphism: study of known and additional alleles.

We describe a technique for HLA-Cw genotyping by digestion of PCR-amplified genes with restriction endonucleases. Locus-specific primers selectively amplified HLA-Cw sequences from exon 2 in a single PCR that avoided coamplification of other classical and nonclassical class I genes. Amplified DNAs were digested with selected enzymes. Sixty-three homozygous cell lines from International Histocompatibility Workshop X and 113 unrelated individual cells were genotypes for HLA-Cw and compared with serology. The present protocol can distinguish 23 alleles corresponding to the known HLA-Cw sequences. Genotyping of serologically undetectable alleles (HLA-Cw Blank) and of heterozygous cells was made possible by using this method. Six additional HLA-Cw alleles were identified by unusual restriction patterns and confirmed by sequencing; this observation suggests the presence of another family of allele-sharing clusters in the HLA-B locus. This PCR-restriction endonuclease method provides a simple and convenient approach for HLA-Cw DNA typing, allowing the definition of serologically undetectable alleles, and will contribute to the evaluation of the biological role of the HLA-C locus.

MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.

Prediction of HLA-DQ3.2 beta ligands: evidence of multiple registers in class II binding peptides

Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2 beta complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2 beta receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2 beta binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2 beta binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve A(ROC) > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2 beta peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.

Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102:a bioinformatic approach to the prediction of new epitopes

Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.

Peptide binding to the HLA-DRB1 supertype:a proteochemometrics analysis

A proteochemometrics approach was applied to a set of 2666 peptides binding to 12 HLA-DRB1 proteins. Sequences of both peptide and protein were described using three z-descriptors. Cross terms accounting for adjacent positions and for every second position in the peptides were included in the models, as well as cross terms for peptide/protein interactions. Models were derived based on combinations of different blocks of variables. These models had moderate goodness of fit, as expressed by r2, which ranged from 0.685 to 0.732; and good cross-validated predictive ability, as expressed by q2, which varied from 0.678 to 0.719. The external predictive ability was tested using a set of 356 HLA-DRB1 binders, which showed an r2(pred) in the range 0.364-0.530. Peptide and protein positions involved in the interactions were analyzed in terms of hydrophobicity, steric bulk and polarity.

Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10-5). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted. © The Author 2010. Published by Oxford University Press. All rights reserved.

HLA-DRB1 associations with disease susceptibility and clinical course in Australians with multiple sclerosis

Human leucocyte antigen (HLA)-DRB1*1501 and other class II alleles influence susceptibility to multiple sclerosis (MS), but their contribution if any to the clinical course of MS remains uncertain. Here, we have investigated DRB1 alleles in a large sample of 1230 Australian MS cases, with some enrichment for subjects with primary progressive (PPMS) disease (n = 246) and 1210 healthy controls. Using logistic regression, we found that DRB1*1501 was strongly associated with risk (P = 7 x 10-45), as expected, and after adjusting for DRB1*1501, a predisposing effect was also observed for DRB1*03 (P = 5 x 10-7). Individuals homozygous for either DRB1*15 or DRB1*03 were considerably more at risk of MS than heterozygotes and non-carriers. Both the DRB1*04 and the DRB1*01/DRB1*15 genotype combination, respectively, protected against PPMS in comparison to subjects with relapsing disease. Together, these data provide further evidence of heterogeneity at the DRB1 locus and confirm the importance of HLA variants in the phenotypic expression of MS.

Proof of concept : A bioinformatic and serological screening method for identifying new peptide antigens for Chlamydia trachomatis related sequelae in women

This study aimed to identify new peptide antigens from Chlamydia (C.) trachomatis in a proof of concept approach which could be used to develop an epitope-based serological diagnostic for C. trachomatis related infertility in women. A bioinformatics analysis was conducted examining several immunodominant proteins from C. trachomatis to identify predicted immunoglobulin epitopes unique to C. trachomatis. A peptide array of these epitopes was screened against participant sera. The participants (all female) were categorized into the following cohorts based on their infection and gynecological history; acute (single treated infection with C. trachomatis), multiple (more than one C. trachomatis infection, all treated), sequelae (PID or tubal infertility with a history of C. trachomatis infection), and infertile (no history of C. trachomatis infection and no detected tubal damage). The bioinformatics strategy identified several promising epitopes. Participants who reacted positively in the peptide 11 ELISA were found to have an increased likelihood of being in the sequelae cohort compared to the infertile cohort with an odds ratio of 16.3 (95% c.i. 1.65 – 160), with 95% specificity and 46% sensitivity (0.19-0.74). The peptide 11 ELISA has the potential to be further developed as a screening tool for use during the early IVF work up and provides proof of concept that there may be further peptide antigens which could be identified using bioinformatics and screening approaches.

Haemochromatosis and HLA--H

The recently identified can didate gene, HLA-H, for haemochromatosis (HH) by Feder et al. generated considerable scientific interest coupled with a degree of uncertainty about the likely involvement of this gene in this common iron metabolism disorder, Feder et al. found a single point mutation resulting in an amino acid substitution (C282Y) that was homozygous in 148 (83%) of their patients, heterozygous in 9 patients (5%) but completely absent in 21 patients (12%). They proposed that the lack of a causative mutation in HLA-H in 12% of their patients was because these cases were not linked to chromosome 6p. A significant weakness in this argument is that all familial studies of the disorder so far have concluded that HH is due to a single major HLA-linked gene5-7. The ultimate test for a candidate gene is the clear segregation of a mutation with the disorder in all patients. Thus, some of the uncertainty surrounding the role of HLA-H in HH may be resolved by the identification of complete concordance of the C282Y mutation (or some other mutation) in HLA H with disease status in HH families. One potential problem in the design of such an experimental analysis is that a number of studies have shown the presence of a predominant ancestral haplotype in all HH populations examined: Australian, French, Italian, UK and US Thus in the analysis of a putative causative mutation, it is important to include families with...

Human CD141(+) (BDCA-3)(+) dendritic cells (DCs) represent a unique myeloid DC subset that cross-presents necrotic cell antigens

The characterization of human dendritic cell (DC) subsets is essential for the design of new vaccines. We report the first detailed functional analysis of the human CD141(+) DC subset. CD141(+) DCs are found in human lymph nodes, bone marrow, tonsil, and blood, and the latter proved to be the best source of highly purified cells for functional analysis. They are characterized by high expression of toll-like receptor 3, production of IL-12p70 and IFN-beta, and superior capacity to induce T helper 1 cell responses, when compared with the more commonly studied CD1c(+) DC subset. Polyinosine-polycytidylic acid (poly I:C)-activated CD141(+) DCs have a superior capacity to cross-present soluble protein antigen (Ag) to CD8(+) cytotoxic T lymphocytes than poly I:C-activated CD1c(+) DCs. Importantly, CD141(+) DCs, but not CD1c(+) DCs, were endowed with the capacity to cross-present viral Ag after their uptake of necrotic virus-infected cells. These findings establish the CD141(+) DC subset as an important functionally distinct human DC subtype with characteristics similar to those of the mouse CD8 alpha(+) DC subset. The data demonstrate a role for CD141(+) DCs in the induction of cytotoxic T lymphocyte responses and suggest that they may be the most relevant targets for vaccination against cancers, viruses, and other pathogens.

Identification of novel antigens in blood vessels in rectovaginal endometriosis

To identify specific markers of rectovaginal endometriotic nodule vasculature, highly enriched preparations of vascular endothelial cells and pericytes were obtained from endometriotic nodules and control endometrial and myometrial tissue by laser capture microdissection (LCM), and gene expression profiles were screened by microarray analysis. Of the 18 400 transcripts on the arrays, 734 were significantly overexpressed in vessels from fibromuscular tissue and 923 in vessels from stromal tissue of endometriotic nodules, compared with vessels dissected from control tissues. The most frequently expressed transcripts included known endothelial cell-associated genes, as well as transcripts with little or no previous association with vascular cells. The higher expression in blood vessels was further corroborated by immunohistochemical staining of six potential markers, five of which showed strong expression in pericytes. The most promising marker was matrix Gla protein, which was found to be present in both glandular epithelial cells and vascular endothelial cells of endometriotic lesions, although it was barely expressed at all in normal endometrium. LCM, combined with microarray analysis, constitutes a powerful tool for mapping the transcriptome of vascular cells. After immunohistochemical validation, markers of vascular endothelial and perivascular cells from endometriotic nodules could be identified, which may provide targets to improve early diagnosis or to selectively deliver therapeutic agents.