Peptide binding specificity of major histocompatibility complex class I resolved into an array of apparently independent subspecificities: quantitation by peptide libraries and improved prediction of binding

Stryhn, Anette; Pedersen, Lars Østergaard; Romme, Tina; Holm, Charlotte Bisgaard; Holm, Arne; Buus, Søren

doi:10.1002/eji.1830260836

Cited by 90 publications

(83 citation statements)

References 47 publications

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“…The peptide binding specificity of a given HLA-I is determined by favoring or disfavoring of certain amino acids in certain positions of the peptide. An unbiased method has previously been reported capable of determining the peptide binding specificities of HLA-I molecules using PSCPLs (17). To investigate whether Tpn 1-87 alters or shows a preference for facilitation based on the peptide binding specificity of HLA-A*02:01, i.e.…”

Section: Resultsmentioning

confidence: 99%

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Tapasin Discriminates Peptide-Human Leukocyte Antigen-A*02:01 Complexes Formed with Natural Ligands

Røder

Geironson

Rasmussen

et al. 2011

Journal of Biological Chemistry

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A plethora of peptides are generated intracellularly, and most peptide-human leukocyte antigen (HLA)-I interactions are of a transient, unproductive nature. Without a quality control mechanism, the HLA-I system would be stressed by futile attempts to present peptides not sufficient for the stable peptide-HLA-I complex formation required for long term presentation. Tapasin is thought to be central to this essential quality control, but the underlying mechanisms remain unknown. Here, we report that the N-terminal region of tapasin, Tpn 1-87 , assisted folding of peptide-HLA-A*02:01 complexes according to the identity of the peptide. The facilitation was also specific for the identity of the HLA-I heavy chain, where it correlated to established tapasin dependence hierarchies. Two large sets of HLA-A*02:01 binding peptides, one extracted from natural HLA-I ligands from the SYFPEITHI database and one consisting of medium to high affinity non-SYFPEITHI ligands, were studied in the context of HLA-A*02:01 binding and stability. We show that the SYFPEITHI peptides induced more stable HLA-A*02:01 molecules than the other ligands, although affinities were similar. Remarkably, Tpn 1-87 could functionally discriminate the selected SYFPEITHI peptides from the other peptide binders with high sensitivity and specificity. We suggest that this HLA-I-and peptide-specific function, together with the functions exerted by the more C-terminal parts of tapasin, are major features of tapasin-mediated HLA-I quality control. These findings are important for understanding the biogenesis of HLA-I molecules, the selection of presented T-cell epitopes, and the identification of immunogenic targets in both basic research and vaccine design.Mature HLA-I 3 molecules are located on the surface of all nucleated cells where they present peptides to CD8ϩ T lymphocytes. Before the peptide-HLA-I complex is transported to the cell surface, maturation and assembly with peptides occur in the ER. During late stage maturation, HLA-I molecules are integrated in the peptide-loading complex (PLC), which at least consists of TAP1/2, tapasin, calreticulin, protein disulfide isomerase, ERp57, and HLA-I (1, 2). Integration of HLA-I into the PLC is mediated by tapasin, which structurally bridges HLA-I and TAP (3, 4). Tapasin is a multi-domain protein, which has been suggested to perform multiple functions. Tapasin has been shown to enhance peptide binding to TAP, facilitate peptide loading onto HLA-I, edit the HLA-I bound peptide repertoire, and retain and recycle suboptimally loaded peptide-HLA-I complexes (5-9). Consequently, in the absence of tapasin, cell surface-expressed HLA-I molecules are less stable and present a partly different peptide repertoire than HLA-I on wild-type cells (10 -12). The effect of tapasin depends on the HLA-I allomorph where certain allomorphs, such as HLA-A*02:01, are dependent on tapasin for efficient presentation, whereas others are less influenced (10 -12).Recently, we showed that an N-terminal fragment of tapasin, Tpn 1-87 , assi...

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Section: Resultsmentioning

confidence: 99%

“…We used a previously reported method capable of determining the HLA-I peptide binding specificity using PSCPLs (17). In brief, peptides are synthesized with completely random amino acids at all positions in the peptide except at a chosen position.…”

Section: Methodsmentioning

confidence: 99%

Tapasin Discriminates Peptide-Human Leukocyte Antigen-A*02:01 Complexes Formed with Natural Ligands

Røder

Geironson

Rasmussen

et al. 2011

Journal of Biological Chemistry

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“…Prediction matrices of Parker et al [26] were generated from a limited set of peptides, perhaps explaining a recent report [33] describing poor correspondence between the predicted MHC binding peptides and those determined experimentally. Quantitative matrices have also been derived from positional scanning combinatorial peptide libraries (PSCPL) [27,28], where all possible peptides of a given length are represented by sets of sublibraries and in each sublibrary, one amino acid is kept fixed whereas the remaining positions contain mixtures of all amino acids. Unfortunately, to date, prediction of pMHCI binding using these PSCPL-derived matrices is not freely accessible.…”

Section: Discussionmentioning

confidence: 99%

Prediction of MHC class I binding peptides using profile motifs

2002

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ABSTRACT:Peptides that bind to a given major histocompatibility complex (MHC) molecule share sequence similarity. Therefore, a position specific scoring matrix (PSSM) or profile derived from a set of peptides known to bind to a specific MHC molecule would be a suitable predictor of whether other peptides might bind, thus anticipating possible T-cell epitopes within a protein. In this approach, the binding potential of any peptide sequence (query) to a given MHC molecule is linked to its similarity to a group of aligned peptides known to bind to that MHC, and can be obtained by comparing the query to the PSSM. This article describes the derivation of alignments and profiles from a collection of peptides known to bind a specific MHC, compatible with the structural and molecular basis of the peptide-MHC class I (MHCI) interaction. Moreover, in order to apply these profiles to the prediction of peptide-MHCI binding, we have developed a new search algorithm (RANKPEP) that ranks all possible peptides from an input protein using the PSSM coefficients. The predictive power of the method was evaluated by running RANKPEP on proteins known to bear MHCI K b -and D b -restricted T-cell epitopes. Analysis of the results indicates that Ͼ 80% of these epitopes are among the top 2% of scoring peptides. Prediction of peptide-MHC binding using a variety of MHCI-specific PSSMs is available on line at our RANK-PEP web server (www.mifoundation.org/Tools/rankpep.html). In addition, the RANKPEP server also allows the user to enter additional profiles, making the server a powerful and versatile computational biology benchmark for the prediction of peptide-MHC binding. Human Immunology 63, 701-709 (2002).

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“…Synthesized peptides were purified by reverse-phase HPLC to .80% purity and validated by mass spectrometry. Positional scanning combinatorial peptide libraries (PSCPL) were synthesized as previously described (17). Briefly, eight of nine positions comprised an equimolar pool of 19 of the 20 natural amino acids (i.e., excluding cysteine), whereas the remaining position comprised 1 of the 20 natural amino acids (i.e., including cysteine), thereby interrogating the position-specific effect of this latter amino acid.…”

Section: Peptidesmentioning

confidence: 99%

“…Determining peptide-binding motifs by a scintillation proximity-based dissociation assay Nonameric peptide-binding motifs were determined for HLA-C*01:02, -C*02:02, -C*03:02, -C*03:03, -C*03:04, -C*04:01, -C*05:01, -C*06:02, -C*07:01, -C*07:02, -C*07:04, -C*08:01, -C*08:02, -C*12:03, -C*14:02, -C*15:02, and -C*16:01 using a recently developed scintillation proximity assay (SPA)-based peptide-MHC-I dissociation assay (23) in combination with nonameric PSCPL (17). In 384-well streptavidin-coated FlashPlate HTS Plus microplates (PerkinElmer, SMP410), recombinant biotinylated MHC-I H chain in 8 M urea was diluted at least 100 times (to 50 nM) into PBS/0.1% Lutrol F68 containing 78 mg/ml (78 mM) of each sublibrary with 2-10 nM [ …”

Section: Radiolabelingmentioning

confidence: 99%

Uncovering the Peptide-Binding Specificities of HLA-C: A General Strategy To Determine the Specificity of Any MHC Class I Molecule

Rasmussen

Harndahl

Stryhn

et al. 2014

The Journal of Immunology

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MHC class I molecules (HLA-I in humans) present peptides derived from endogenous proteins to CTLs. Whereas the peptide-binding specificities of HLA-A and -B molecules have been studied extensively, little is known about HLA-C specificities. Combining a positional scanning combinatorial peptide library approach with a peptide–HLA-I dissociation assay, in this study we present a general strategy to determine the peptide-binding specificity of any MHC class I molecule. We applied this novel strategy to 17 of the most common HLA-C molecules, and for 16 of these we successfully generated matrices representing their peptide-binding motifs. The motifs prominently shared a conserved C-terminal primary anchor with hydrophobic amino acid residues, as well as one or more diverse primary and auxiliary anchors at P1, P2, P3, and/or P7. Matrices were used to generate a large panel of HLA-C–specific peptide-binding data and update our pan-specific NetMHCpan predictor, whose predictive performance was considerably improved with respect to peptide binding to HLA-C. The updated predictor was used to assess the specificities of HLA-C molecules, which were found to cover a more limited sequence space than HLA-A and -B molecules. Assessing the functional significance of these new tools, HLA-C*07:01 transgenic mice were immunized with stable HLA-C*07:01 binders; six of six tested stable peptide binders were immunogenic. Finally, we generated HLA-C tetramers and labeled human CD8+ T cells and NK cells. These new resources should support future research on the biology of HLA-C molecules. The data are deposited at the Immune Epitope Database, and the updated NetMHCpan predictor is available at the Center for Biological Sequence Analysis and the Immune Epitope Database.

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Peptide binding specificity of major histocompatibility complex class I resolved into an array of apparently independent subspecificities: quantitation by peptide libraries and improved prediction of binding

Cited by 90 publications

References 47 publications

Tapasin Discriminates Peptide-Human Leukocyte Antigen-A*02:01 Complexes Formed with Natural Ligands

Tapasin Discriminates Peptide-Human Leukocyte Antigen-A*02:01 Complexes Formed with Natural Ligands

Prediction of MHC class I binding peptides using profile motifs

Uncovering the Peptide-Binding Specificities of HLA-C: A General Strategy To Determine the Specificity of Any MHC Class I Molecule

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