HSPVdb—the Human Short Peptide Variation Database for improved mass spectrometry-based detection of polymorphic HLA-ligands

Nijveen, Harm; Kester, Michel G.D.; Hassan, Chopie; Viars, Aurélie; Ru, Arnoud H. de; Jager, Machiel de; Falkenburg, J.H.F.; Veelen, Peter A. van

doi:10.1007/s00251-010-0497-1

Cited by 14 publications

(17 citation statements)

References 28 publications

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“…In order to find and identify polymorphic peptides in the eluted peptides from B-LCL-HHC and B-LCL-JYpp65 cell lines, the tandem mass spectra were matched with a dedicated database, HSPVdb (21). We found 1439 polymorphic peptides of 8-to 11-mer length and a Mascot ion score of Ͼ35, accounting for 10% of the peptides in the ligandome.…”

Section: Resultsmentioning

confidence: 99%

“…NetPhos 2.0 (34) was used to predict phosphosites in identified phosphorylated ligands. For the identification of polymorphic peptides, the tandem mass spectra were matched against HSPVdb, a database optimized for finding polymorphic peptides (21 Peptide Synthesis-Peptides were synthesized according to standard fluorenylmethoxycarbonyl (Fmoc) chemistry using a SyroII peptide synthesizer (MultiSynTech, Witten, Germany). The integrity of the peptides was checked using reverse-phase HPLC and MS. Phosphopeptides were synthesized using the building blocks Fmoc-Ser-(PO(OBzl)OH)-OH or Fmoc-Thr(PO(OBzl)OH)-OH.…”

Section: Sample Preparation-thementioning

confidence: 99%

“…In a second step, post-translation modifications (phosphorylation, cysteinylation) were allowed in the database search. In a third step, the tandem mass spectra were matched against a newly in-house developed database for the optimal identification of polymorphic ligands to find potential minor histocompatibility antigens (21). This led to the identification of ϳ14,000 HLA class I ligands, the majority of which also were relatively quantitated.…”

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confidence: 99%

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The Human Leukocyte Antigen–presented Ligandome of B Lymphocytes

Hassan

Kester

et al. 2013

Molecular & Cellular Proteomics

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116

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The presented HLA class I ligands are the products of the intracellular processing machinery, with its continuous cycle of protein synthesis and degradation (3). Much is known about the proteins involved in antigen processing, but high fidelity ligand/epitope predictions are at present not possible. The discovery of additional involved enzymes (3, 4) and the exciting discovery of peptide splicing (5) have shown that antigen processing is even more complex than was previously thought. Moreover, gene expression studies have shown many nonstandard, unexpected protein products, including the production of antigens derived from aberrant protein fragments as a result of expression in alternative reading frames (6). Several studies report the identification of HLA ligands (7-10). Many results have been collected and discussed in a recent review on the large-scale analysis of HLA class I ligands (11). Collectively, these reports illustrate the need for in-depth elucidation of the HLA ligandome.Elucidation of T cell epitopes has traditionally been achieved with the use of a forward immunological approach, as pioneered by Hunt and coworkers (12,13). In this approach, the cognate peptide of T cells with the appropriate activity profile is elucidated via repeated rounds of chromatographic separation in combination with T cell recognition assays. Because T cells are not always available from the start, reverse immunological approaches (14 -17) have been developed to predict T cell epitopes through a combination of bioinformatics and in vitro proteasome digests. Predicted epitopes are synthesized and tested for their capability to activate T cells. The main disadvantage of this approach is that less than 0.1% of the peptides that survive intracellular processing are presented on HLA class I molecules (3).Therefore, we developed a large-scale peptidomics approach that is a reverse immunology approach based not on From the ‡Department of Immunohematology and Blood Transfusion,

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Section: Resultsmentioning

confidence: 99%

Section: Sample Preparation-thementioning

confidence: 99%

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confidence: 99%

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The Human Leukocyte Antigen–presented Ligandome of B Lymphocytes

Hassan

Kester

et al. 2013

Molecular & Cellular Proteomics

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116

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“…The complex ligand pool was fractionated by C18 reverse-phase HPLC and subsequently analyzed by on-line tandem MS for sequencing. Tandem mass spectra were matched to the Human Short Peptide Variation Database (HSPVdb) for polymorphic peptide identification, using the Mascot search engine (31,40). Peptide sequences encoded by both the normal and alternative reading frames were identified with a length of 7-14 aa, allowing methionine oxidation, a minimal Best Mascot Ion (BMI) score of 20, and a mass accuracy of 10 ppm.…”

Section: Selection Of Miha Candidates From Eluted Peptide Setmentioning

confidence: 99%

“…For this purpose peptide elution experiments were performed with EBV-transformed lymphoblastoid B cell lines (EBV-LCL), which express peptides derived from hematopoietic restricted genes, B cell lineage and multilineage specific genes, as well as genes overexpressed in transformed cells. Subsequently, this large set of eluted peptides was screened for potential MiHA, using a database dedicated to identifying polymorphic peptides (31). A set of 40 MiHA candidates was synthesized and subsequently evaluated by mass spectrometric analysis, SNP validation, and peptide-HLA binding assays.…”

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confidence: 99%

Discovery of T Cell Epitopes Implementing HLA-Peptidomics into a Reverse Immunology Approach

Hombrink

Hassan

Kester

et al. 2013

The Journal of Immunology

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T cell recognition of minor histocompatibility Ags (MiHA) plays an important role in the graft-versus-tumor effect of allogeneic stem cell transplantation. Selective infusion of T cells reactive for hematopoiesis-restricted MiHA presented in the context of HLA class I or II molecules may help to separate the graft-versus-tumor effects from graft-versus-host disease effects after allogeneic stem cell transplantation. Over the years, increasing numbers of MiHA have been identified by forward immunology approaches, and the relevance of these MiHA has been illustrated by correlation with clinical outcome. As the tissue distribution of MiHA affects the clinical outcome of T cell responses against these Ags, it would be beneficial to identify additional predefined MiHA that are exclusively expressed on hematopoietic cells. Therefore, several reverse immunology approaches have been explored for the prediction of MiHA. Thus far, these approaches frequently resulted in the identification of T cells directed against epitopes that are not naturally processed and presented. In this study we established a method for the identification of biologically relevant MiHA, implementing mass spectrometry–based HLA-peptidomics into a reverse immunology approach. For this purpose, HLA class I binding peptides were eluted from transformed B cells, analyzed by mass spectrometry, and matched with a database dedicated to identifying polymorphic peptides. This process resulted in a set of 40 MiHA candidates that were evaluated in multiple selection steps. The identification of LB-NISCH-1A demonstrated the technical feasibility of our approach. On the basis of these results, we present an approach that can be of value for the efficient identification of MiHA or other T cell epitopes.

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