Characterization of binding specificities of bovine leucocyte class I molecules: impacts for rational epitope discovery

Abstract

The binding of peptides to classical major histocompatibility complex (MHC) class I proteins is the single most selective step in antigen presentation. However, the peptide-binding specificity of cattle MHC (bovine leucocyte antigen, BoLA) class I (BoLA-I) molecules remains poorly characterized. Here, we demonstrate how a combination of high-throughput assays using positional scanning combinatorial peptide libraries, peptide dissociation, and peptide-binding affinity binding measurements can be combined with bioinformatics to effectively characterize the functionality of BoLA-I molecules. Using this strategy, we characterized eight BoLA-I molecules, and found the peptide specificity to resemble that of human MHC-I molecules with primary anchors most often at P2 and P9, and occasional auxiliary P1/P3/P5/P6 anchors. We analyzed nine reported CTL epitopes from Theileria parva, and in eight cases, stable and high affinity binding was confirmed. A set of peptides were tested for binding affinity to the eight BoLA proteins and used to refine the predictors of peptide–MHC binding NetMHC and NetMHCpan. The inclusion of BoLA-specific peptide-binding data led to a significant improvement in prediction accuracy for reported T. parva CTL epitopes. For reported CTL epitopes with weak or no predicted binding, these refined prediction methods suggested presence of nested minimal epitopes with high-predicted binding affinity. The enhanced affinity of the alternative peptides was in all cases confirmed experimentally. This study demonstrates how biochemical high-throughput assays combined with immunoinformatics can be used to characterize the peptide-binding motifs of BoLA-I molecules, boosting performance of MHC peptide-binding prediction methods, and empowering rational epitope discovery in cattle.

Current tools for predicting cancer-specific T cell immunity

“…2A). 41,54,55 Data generated by this assay were used for training of prediction algorithms. 56,57 It has been reported that pMHC complexes stability, as measured by a scintillation proximity assay, better correlates with immunogenicity than binding affinity.…”

Identification of immediate early gene products of bovine herpes virus 1 (BHV-1) as dominant antigens recognized by CD8 T cells in immune cattle

“…Earlier studies have demonstrated the ability of this method to accurately predict peptides that bind to MHC I, including BoLA-1 molecules [29][30][31], and the method has proved useful as a guide to confirm whether identified epitope sequences are indeed minimal epitopes [32]. Therefore, these analyses set out to: (i) quantify the degree to which in silico predictions are capable of identifying the validated epitopes; and (ii) identify possible alternative peptide variants (extensions or fragments) of the validated epitopes predicted to have improved binding affinity to the BoLA-I restriction element.…”

NNAlign_MA; semi-supervised MHC peptidome deconvolution for accurate characterization of MHC binding motifs and improved T cell epitope prediction

“…Recombinnt BoLA-1*00901 and human beta-2 microglobulins (β2m) were produced as previously described (61). In brief, biotinylated BoLA-1*00901 was generated in Escherichia coli, harvested as inclusion bodies, extracted into Tris-buffered 8 M urea and purified using ion exchange, hydrophobic, and gel filtration chromatographies.…”

“…Nonameric peptide binding motifs were determined for BoLA-1*00901, using PSCPL as previously described (34,61,63). Recombinant, biotinylated BoLA heavy chain molecules in 8 M urea were diluted at least 100-fold into PBS buffer containing 125I-labeled human β2m and peptide to initiate pMHC-I complex formation.…”