6 resultados para HLA-DRB1* molecules

em University of Queensland eSpace - Australia


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Infection of humans with the West Nile flavivirus principally occurs via tick and mosquito bites. Here, we document the expression of antigen processing and presentation molecules in West Nile virus (WNV)-infected human skin fibroblast (HFF) cells. Using a new Flavivirus-specific antibody, 4G4, we have analyzed cell surface human leukocyte antigen (HLA) expression on virus-infected cells at a single cell level. Using this approach, we show that West Nile Virus infection alters surface HLA expression on both infected HFF and neighboring uninfected HFF cells. Interestingly, increased surface HLA evident on infected HFF cultures is almost entirely due to virus-induced interferon (IFN)alpha/beta because IFNalpha/beta-neutralizing antibodies completely prevent increased surface HLA expression. In contrast, RT-PCR analysis indicates that WNV infection results in increased mRNAs for HLA-A, -B, and -C genes, and HLA-associated molecules low molecular weight polypeptide-2 (LMP-2) and transporter associated with antigen presentation-1 (TAP-1), but induction of these mRNAs is not diminished in HFF cells cultured with IFNalpha/beta-neutralizing antibodies. Taken together, these data support the idea that that both cytokine-dependent and cytokine-independent mechanisms account for WNV-induced HLA expression in human skin fibroblasts. (C) 2004 Elsevier Inc. All rights reserved.

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A functional immune system requires a tight control over major histocompatibility complex (MHC) gene transcription, as the abnormal MHC expression patterns of severe immunodeficiency and autoimmune diseases demonstrate. Although the regulation of MHC expression has been well documented in humans and mice, little is known in other species. In this study, we detail the level of polymorphism in wolf and dog MHC gene promoters. The promoter regions of the DRB, DQA and DQB locus were sequenced in 90 wolves and 90 dogs. The level of polymorphism was high in the DQB promoters, with variation found within functionally relevant regions, including binding sites for transcription factors. Clear associations between DQB promoters and exon 2 alleles were noted in wolves, indicating strong linkage disequilibrium in this region. Low levels of polymorphism were found within the DRB and DQA promoter regions. However, a variable site was identified within the T box, a TNF-alpha response element, of the DQA promoter. Furthermore, we identified a previously unrecognised 18-base-pair deletion within exon 1 of the DQB locus.

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The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

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The BZLF1 antigen of Epstein-Barr virus includes three overlapping sequences of different lengths that conform to the binding motif of human leukocyte antigen (HLA) B*3501. These 9-mer ((56)LPOGQLTAy(64)), 11-mer ((54)EPLPQGQLTAy(64)), and 13-mer ((52)LPEPLPQGQLTAY(64)) peptides all bound well to B*3501; however, the CTL response in individuals expressing this HILA allele was directed strongly and exclusively towards the 11-mer peptide. In contrast, EBV-exposed donors expressing HLA B*3503 showed no significant CTL response to these peptides because the single amino acid difference between B*3501 and B*3503 within the F pocket inhibited HLA binding by these peptides. The extraordinarily long 13-mer peptide was the target for the CTL response in individuals expressing B*3508, which differs from B*3501 at a single position within the D pocket (B*3501, 156 Leucine; B*3508, 156 Arginine). This minor difference was shown to enhance binding of the 13-mer peptide, presumably through a stabilizing interaction between the negatively charged glutamate at position 3 of the peptide and the positively charged arginine at HLA position 156. The 13-mer epitope defined in this study represents the longest class I-binding viral epitope identified to date as a minimal determinant. Furthermore, the potency of the response indicates that peptides of this length do not present a major structural barrier to CTL recognition.

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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/.

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Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.