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Celiac disease T-cell epitopes from gamma-gliadins: immunoreactivity depends on the genome of origin, transcript frequency, and flanking protein variation.

ABSTRACT: BACKGROUND: Celiac disease (CD) is caused by an uncontrolled immune response to gluten, a heterogeneous mixture of wheat storage proteins. The CD-toxicity of these proteins and their derived peptides is depending on the presence of specific T-cell epitopes (9-mer peptides; CD epitopes) that mediate the stimulation of HLA-DQ2/8 restricted T-cells. Next to the thoroughly characterized major T-cell epitopes derived from the ?-gliadin fraction of gluten, ?-gliadin peptides are also known to stimulate T-cells of celiac disease patients. To pinpoint CD-toxic ?-gliadins in hexaploid bread wheat, we examined the variation of T-cell epitopes involved in CD in ?-gliadin transcripts of developing bread wheat grains. RESULTS: A detailed analysis of the genetic variation present in ?-gliadin transcripts of bread wheat (T. aestivum, allo-hexaploid, carrying the A, B and D genome), together with genomic ?-gliadin sequences from ancestrally related diploid wheat species, enabled the assignment of sequence variants to one of the three genomic ?-gliadin loci, Gli-A1, Gli-B1 or Gli-D1. Almost half of the ?-gliadin transcripts of bread wheat (49%) was assigned to locus Gli-D1. Transcripts from each locus differed in CD epitope content and composition. The Gli-D1 transcripts contained the highest frequency of canonical CD epitope cores (on average 10.1 per transcript) followed by the Gli-A1 transcripts (8.6) and the Gli-B1 transcripts (5.4). The natural variants of the major CD epitope from ?-gliadins, DQ2-?-I, showed variation in their capacity to induce in vitro proliferation of a DQ2-?-I specific and HLA-DQ2 restricted T-cell clone. CONCLUSIONS: Evaluating the CD epitopes derived from ?-gliadins in their natural context of flanking protein variation, genome specificity and transcript frequency is a significant step towards accurate quantification of the CD toxicity of bread wheat. This approach can be used to predict relative levels of CD toxicity of individual wheat cultivars directly from their transcripts (cDNAs).

SUBMITTER: Salentijn EM

PROVIDER: S-EPMC3469346 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Celiac disease T-cell epitopes from gamma-gliadins: immunoreactivity depends on the genome of origin, transcript frequency, and flanking protein variation.

Salentijn Elma M J EM Mitea D Cristina DC Goryunova Svetlana V SV van der Meer Ingrid M IM Padioleau Ismael I Gilissen Luud J W J LJ Koning Frits F Smulders Marinus J M MJ

BMC genomics 20120622

<h4>Background</h4>Celiac disease (CD) is caused by an uncontrolled immune response to gluten, a heterogeneous mixture of wheat storage proteins. The CD-toxicity of these proteins and their derived peptides is depending on the presence of specific T-cell epitopes (9-mer peptides; CD epitopes) that mediate the stimulation of HLA-DQ2/8 restricted T-cells. Next to the thoroughly characterized major T-cell epitopes derived from the α-gliadin fraction of gluten, γ-gliadin peptides are also known to s ...[more]

PMID: 22726570

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Project description:IntroductionCeliac disease (CD) is an autoimmune gastrointestinal disorder causes immune-mediated enteropathy against gluten. Gluten immunogenic peptides have the potential to trigger immune responses which leads to damage the small intestine. HLA-DQ2/DQ8 are major alleles that bind to epitope/antigenic region of gluten and induce celiac disease. There is a need to identify CD associated epitopes in protein-based foods and therapeutics.MethodsIn this study, computational tools have been developed to predict CD associated epitopes and motifs. Dataset used for training, testing and evaluation contain experimentally validated CD associated and non-CD associate peptides. We perform positional analysis to identify the most significant position of an amino acid residue in the peptide and checked the frequency of HLA alleles. We also compute amino acid composition to develop machine learning based models. We also developed ensemble method that combines motif-based approach and machine learning based models.Results and discussionOur analysis support existing hypothesis that proline (P) and glutamine (Q) are highly abundant in CD associated peptides. A model based on density of P&Q in peptides has been developed for predicting CD associated peptides which achieve maximum AUROC 0.98 on independent data. We discovered motifs (e.g., QPF, QPQ, PYP) which occurs specifically in CD associated peptides. We also developed machine learning based models using peptide composition and achieved maximum AUROC 0.99. Finally, we developed ensemble method that combines motif-based approach and machine learning based models. The ensemble model-predict CD associated motifs with 100% accuracy on an independent dataset, not used for training. Finally, the best models and motifs has been integrated in a web server and standalone software package "CDpred". We hope this server anticipate the scientific community for the prediction, designing and scanning of CD associated peptides as well as CD associated motifs in a protein/peptide sequence (https://webs.iiitd.edu.in/raghava/cdpred/).

Dataset Information

Celiac disease T-cell epitopes from gamma-gliadins: immunoreactivity depends on the genome of origin, transcript frequency, and flanking protein variation.

Publications

Celiac disease T-cell epitopes from gamma-gliadins: immunoreactivity depends on the genome of origin, transcript frequency, and flanking protein variation.

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