Dataset Information

Dendritic cells in islets of Langerhans constitutively present beta cell-derived peptides bound to their class II MHC molecules.

ABSTRACT: Islets of Langerhans from normal mice contained dendritic cells (DCs) in the range of 8-10 per islet. DCs were found in several mouse strains, including those from lymphocyte-deficient mice. DCs were absent in islets from colony stimulating factor-1 deficient mice and this absence correlated with small size islets. Most DCs were found next to blood vessels and resided in islets for several days. Some DCs contained insulin-like granules, and most expressed peptide-MHC complexes derived from beta cell proteins. Islet DCs were highly effective in presenting beta cell antigens to CD4 T cells ex vivo. Presentation of beta cell-derived peptide-MHC complexes by DCs neither depended on islet inflammation nor correlated with the extent of spontaneous beta cell death. Periislet stroma DCs did not contain beta cell peptide-MHC complexes; however, 50% of DCs in pancreatic node were positive. Hence, presentation of high levels of beta cell antigens normally takes place by islet DCs, a finding that has to be placed in the perspective of autoimmune diabetes.

SUBMITTER: Calderon B

PROVIDER: S-EPMC2329714 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature

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Dendritic cells in islets of Langerhans constitutively present beta cell-derived peptides bound to their class II MHC molecules.

Calderon Boris B Suri Anish A Miller Mark J MJ Unanue Emil R ER

Proceedings of the National Academy of Sciences of the United States of America 20080421 16

Islets of Langerhans from normal mice contained dendritic cells (DCs) in the range of 8-10 per islet. DCs were found in several mouse strains, including those from lymphocyte-deficient mice. DCs were absent in islets from colony stimulating factor-1 deficient mice and this absence correlated with small size islets. Most DCs were found next to blood vessels and resided in islets for several days. Some DCs contained insulin-like granules, and most expressed peptide-MHC complexes derived from beta ...[more]

PMID: 18427107

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Project description:BackgroundPeptides binding to Major Histocompatibility Complex (MHC) class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides. In this paper, we propose two approaches using multi-objective evolutionary algorithms (MOEA) for predicting peptides binding to MHC class II molecules. One uses the information from both binders and non-binders for self-discovery of motifs. The other, in addition, uses information from experimentally determined motifs for guided-discovery of motifs.ResultsThe proposed methods are intended for finding peptides binding to MHC class II I-Ag7 molecule - a promiscuous binder to a large number of low affinity peptides. Cross-validation results across experiments on two motifs derived for I-Ag7 datasets demonstrate better generalization abilities and accuracies of the present method over earlier approaches. Further, the proposed method was validated and compared on two publicly available benchmark datasets: (1) an ensemble of qualitative HLA-DRB1*0401 peptide data obtained from five different sources, and (2) quantitative peptide data obtained for sixteen different alleles comprising of three mouse alleles and thirteen HLA alleles. The proposed method outperformed earlier methods on most datasets, indicating that it is well suited for finding peptides binding to MHC class II molecules.ConclusionWe present two MOEA-based algorithms for finding motifs, one for self-discovery and the other for guided-discovery by experimentally determined motifs, and thereby predicting binding peptides to I-Ag7 molecule. Our experiments show that the proposed MOEA-based algorithms are better than earlier methods in predicting binding sites not only on I-Ag7 but also on most alleles of class II MHC benchmark datasets. This shows that our methods could be applicable to find binding motifs in a wide range of alleles.

Dataset Information

Dendritic cells in islets of Langerhans constitutively present beta cell-derived peptides bound to their class II MHC molecules.

Publications

Dendritic cells in islets of Langerhans constitutively present beta cell-derived peptides bound to their class II MHC molecules.

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