Heterogeneity assessment of functional T cell avidity.

The potency of cellular immune responses strongly depends on T cell avidity to antigen. Yet, functional avidity measurements are rarely performed in patients, mainly due to the technical challenges of characterizing heterogeneous T cells. The mean functional T cell avidity can be determined by the IFN-γ Elispot assay, with titrated amounts of peptide. Using this assay, we developed a method revealing the heterogeneity of functional avidity, represented by the steepness/hillslope of the peptide titration curve, documented by proof of principle experiments and mathematical modeling. Our data show that not only natural polyclonal CD8 T cell populations from cancer patients, but also monoclonal T cells differ strongly in their heterogeneity of functional avidity. Interestingly, clones and polyclonal cells displayed comparable ranges of heterogeneity. We conclude that besides the mean functional avidity, it is feasible and useful to determine its heterogeneity (hillslope) for characterizing T cell responses in basic research and patient investigation

Scrutinizing MHC-I Binding Peptides and Their Limits of Variation

Designed peptides that bind to major histocompatibility protein I (MHC-I) allomorphs bear the promise of representing epitopes that stimulate a desired immune response. A rigorous bioinformatical exploration of sequence patterns hidden in peptides that bind to the mouse MHC-I allomorph H-2Kb is presented. We exemplify and validate these motif findings by systematically dissecting the epitope SIINFEKL and analyzing the resulting fragments for their binding potential to H-2Kb in a thermal denaturation assay. The results demonstrate that only fragments exclusively retaining the carboxy- or amino-terminus of the reference peptide exhibit significant binding potential, with the N-terminal pentapeptide SIINF as shortest ligand. This study demonstrates that sophisticated machine-learning algorithms excel at extracting fine-grained patterns from peptide sequence data and predicting MHC-I binding peptides, thereby considerably extending existing linear prediction models and providing a fresh view on the computer-based molecular design of future synthetic vaccines. The server for prediction is available at http://modlab-cadd.ethz.ch (SLiDER tool, MHC-I version 2012).ISSN:1553-734XISSN:1553-735

Butyrophilin 3A1 binds phosphorylated antigens and stimulates human gammadelta T cells

Human T cells that express a T cell antigen receptor (TCR) containing gamma-chain variable region 9 and delta-chain variable region 2 (Vgamma9Vdelta2) recognize phosphorylated prenyl metabolites as antigens in the presence of antigen-presenting cells but independently of major histocompatibility complex (MHC), the MHC class I-related molecule MR1 and antigen-presenting CD1 molecules. Here we used genetic approaches to identify the molecule that binds and presents phosphorylated antigens. We found that the butyrophilin BTN3A1 bound phosphorylated antigens with low affinity, at a stoichiometry of 1:1, and stimulated mouse T cells with transgenic expression of a human Vgamma9Vdelta2 TCR. The structures of the BTN3A1 distal domain in complex with host- or microbe-derived phosphorylated antigens had an immunoglobulin-like fold in which the antigens bound in a shallow pocket. Soluble Vgamma9Vdelta2 TCR interacted specifically with BTN3A1-antigen complexes. Accordingly, BTN3A1 represents an antigen-presenting molecule required for the activation of Vgamma9Vdelta2 T cells