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A role for differential variable gene pairing in creating T cell receptors specific for unique major histocompatibility ligands.

ABSTRACT: A limited set of T cell receptor (TCR) variable (V) gene segments are used to create a repertoire of TCRs that recognize all major histocompatibility complex (MHC) ligands within a species. How individual ??TCRs are constructed to specifically recognize a limited set of MHC ligands is unclear. Here we have identified a role for the differential pairing of particular V gene segments in creating TCRs that recognized MHC class II ligands exclusively, or cross-reacted with classical and nonclassical MHC class I ligands. Biophysical and structural experiments indicated that TCR specificity for MHC ligands is not driven by germline-encoded pairwise interactions.Rather, identical TCR? chains can have altered peptide-MHC (pMHC) binding modes when paired with different TCR? chains. The ability of TCR chain pairing to modify how V region residues interact with pMHC helps to explain how the same V genes are used to create TCRs specific for unique MHC ligands.

SUBMITTER: Stadinski BD

PROVIDER: S-EPMC3253227 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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A role for differential variable gene pairing in creating T cell receptors specific for unique major histocompatibility ligands.

Stadinski Brian D BD Trenh Peter P Smith Rebecca L RL Bautista Bianca B Huseby Priya G PG Li Guoqi G Stern Lawrence J LJ Huseby Eric S ES

Immunity 20111101 5

A limited set of T cell receptor (TCR) variable (V) gene segments are used to create a repertoire of TCRs that recognize all major histocompatibility complex (MHC) ligands within a species. How individual αβTCRs are constructed to specifically recognize a limited set of MHC ligands is unclear. Here we have identified a role for the differential pairing of particular V gene segments in creating TCRs that recognized MHC class II ligands exclusively, or cross-reacted with classical and nonclassical ...[more]

PMID: 22101158

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Project description:CD4+ T cells have a major role in regulating immune responses. They are activated by recognition of peptides mostly generated from exogenous antigens through the major histocompatibility complex (MHC) class II pathway. Identification of epitopes is important and computational prediction of epitopes is used widely to save time and resources. Although there are algorithms to predict binding affinity of peptides to MHC II molecules, no accurate methods exist to predict which ligands are generated as a result of natural antigen processing. We utilized a dataset of around 14,000 naturally processed ligands identified by mass spectrometry of peptides eluted from MHC class II expressing cells to investigate the existence of sequence signatures potentially related to the cleavage mechanisms that liberate the presented peptides from their source antigens. This analysis revealed preferred amino acids surrounding both N- and C-terminuses of ligands, indicating sequence-specific cleavage preferences. We used these cleavage motifs to develop a method for predicting naturally processed MHC II ligands, and validated that it had predictive power to identify ligands from independent studies. We further confirmed that prediction of ligands based on cleavage motifs could be combined with predictions of MHC binding, and that the combined prediction had superior performance. However, when attempting to predict CD4+ T cell epitopes, either alone or in combination with MHC binding predictions, predictions based on the cleavage motifs did not show predictive power. Given that peptides identified as epitopes based on CD4+ T cell reactivity typically do not have well-defined termini, it is possible that motifs are present but outside of the mapped epitope. Our attempts to take that into account computationally did not show any sign of an increased presence of cleavage motifs around well-characterized CD4+ T cell epitopes. While it is possible that our attempts to translate the cleavage motifs in MHC II ligand elution data into T cell epitope predictions were suboptimal, other possible explanations are that the cleavage signal is too diluted to be detected, or that elution data are enriched for ligands generated through an antigen processing and presentation pathway that is less frequently utilized for T cell epitopes.

Project description:BACKGROUND:Identification of antigenic peptide epitopes is an essential prerequisite in T cell-based molecular vaccine design. Computational (sequence-based and structure-based) methods are inexpensive and efficient compared to experimental approaches in screening numerous peptides against their cognate MHC alleles. In structure-based protocols, suited to alleles with limited epitope data, the first step is to identify high-binding peptides using docking techniques, which need improvement in speed and efficiency to be useful in large-scale screening studies. We present pDOCK: a new computational technique for rapid and accurate docking of flexible peptides to MHC receptors and primarily apply it on a non-redundant dataset of 186 pMHC (MHC-I and MHC-II) complexes with X-ray crystal structures. RESULTS:We have compared our docked structures with experimental crystallographic structures for the immunologically relevant nonameric core of the bound peptide for MHC-I and MHC-II complexes. Primary testing for re-docking of peptides into their respective MHC grooves generated 159 out of 186 peptides with C? RMSD of less than 1.00 Å, with a mean of 0.56 Å. Amongst the 25 peptides used for single and variant template docking, the C? RMSD values were below 1.00 A for 23 peptides. Compared to our earlier docking methodology, pDOCK shows upto 2.5 fold improvement in the accuracy and is ~60% faster. Results of validation against previously published studies represent a seven-fold increase in pDOCK accuracy. CONCLUSIONS:The limitations of our previous methodology have been addressed in the new docking protocol making it a rapid and accurate method to evaluate pMHC binding. pDOCK is a generic method and although benchmarks against experimental structures, it can be applied to alleles with no structural data using sequence information. Our outcomes establish the efficacy of our procedure to predict highly accurate peptide structures permitting conformational sampling of the peptide in MHC binding groove. Our results also support the applicability of pDOCK for in silico identification of promiscuous peptide epitopes that are relevant to higher proportions of human population with greater propensity to activate T cells making them key targets for the design of vaccines and immunotherapies.

Dataset Information

A role for differential variable gene pairing in creating T cell receptors specific for unique major histocompatibility ligands.

Publications

A role for differential variable gene pairing in creating T cell receptors specific for unique major histocompatibility ligands.

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