Summary

Title

Different Binding Motifs of the Celiac Disease Associated HLA Molecules DQ2.5, DQ2.2 and DQ7.5 Revealed by Relative Quantitative Proteomics of Endogenous Peptide Repertoires

Description

In this study relative quantitative analysis of endogenous peptides by mass spectrometry combined with neural network analysis have been used to address why the alpha- or beta-chain sharing human leukocyte antigen (HLA)-DQ molecules DQ2.5, DQ2.2 and DQ7.5 display different risks for celiac disease. Celiac disease is caused by intolerance to cereal gluten proteins, and HLA-DQ molecules are involved in the disease pathogenesis by presentation of gluten peptides to CD4+ T cells. It has recently been shown that T cells of DQ2.5 and DQ2.2 patients recognize different sets of gluten epitopes suggesting that these celiac disease associated DQ molecules select different peptides for display. To explore whether this is the case, we performed a comprehensive, large-scale comparison of the endogenous self-peptides bound to HLA-DQ molecules of B-lymphoblastoid cell lines (B-LCLs). Peptides were eluted from affinity-purified HLA molecules of nine cell lines and subjected to quadrupole orbitrap mass spectrometry and MaxQuant software analysis. Altogether, 12712 endogenous peptides were identified at very different relative abundances. Hierarchical clustering of normalized quantitative data demonstrated significant differences in repertoires of peptides between the three DQ variant molecules. The neural network-based method, NNAlign, was used to identify peptide-binding motifs. The binding motifs of DQ2.5 and DQ7.5 concurred with previously established binding motifs. The binding motif of DQ2.2 was strikingly different from that of DQ2.5 with position P3 being a major anchor having a preference for threonine and serine. This is notable as three recently identified epitopes of gluten recognized by T cells of DQ2.2 celiac patients harbor serine at position P3. The study demonstrates that relative quantitative comparison of endogenous peptides sampled from our protein metabolism by HLA molecules provides clues to understand HLA association with disease.

Sample Processing Protocol

HLA molecules were immunoprecipitated from 7e7 cells of each EBV-transformed BCLLs used. HLA-bound peptides were acid eluted with 0.1% trifluoroacetic acid at 37°C for 5 min two times. peptides were analyzed on a Dionex Ultimate 3000 nano-LC system which was connected to a QExactive mass spectrometer equipped with a nanoelectrospray ion source. An Acclaim PepMap100 RSLC column (C18, 2µm beads, 100Å, 75µm inner diameter) of 15 cm bed length was used to separate the peptides. The flow rate used was 0.3µl/min and the solvent gradient was 5 to 50% B in 45 min (solvent A: 0.1% formic acid, solvent B: 90% ACN/0.1% formic acid). The mass spectrometer was operated in the data-dependent acquisition mode using the Xcalibur 2.2 software. Single MS full-scan in the Orbitrap (300–1750 m/z, 70000 resolution at m/z 200, AGC target 1e6, maximum IT 20 ms) were followed by 10 data-dependent MS/MS scans in the Orbitrap after accumulation of 1e6 ions in the C-trap or an injection time of 120 ms at 35000 resolution (isolation width 2.0 m/z, underfill ratio 0.1%, dynamic exclusion 20 s) or after accumulation of 2e5 ions in the C-trap or an injection time of 60ms at 17500 resolution (isolation width 3.0 m/z, underfill ratio 0.4%, dynamic exclusion 20s). The normalized collision energy was set to 25%.

Data Processing Protocol

MS raw files were submitted to MaxQuant software version 1.4.0.5 using Andromeda as a search engine for peptide and protein identification. Pyro-glu (N-term Q and N-term E), deamidation (NQ) and oxidation (M) were set as variable modifications, and we used a first search error window of 20ppm and main search error of 6ppm. No fixed modifications were used. Unspecific enzyme option was selected and no miscleavages were allowed. Mass tolerance for fragment ions was set to 20ppm. Minimal unique peptides were set to 1, and a false discovery rate of 0.01 (1%) was used in all instances, and maximum PEP score allowed was 0.1. Identification of peptides was based on parent ion mass and fragmentation spectra. Retention time alignment was used, ions that had the same parent ion mass and which eluted with the same LC-retention time as a peptide with identified fragmentation spectra were correlated with an alignment window of 3 min. A Uniprot human database (version from December 2013) was used for peptide identification.

Contact

Gustavo de Souza, Dept. of Immunology
Gustavo de Souza, Dept. of Immunology, Oslo University Hospital, UiO ( lab head )

Submission Date

06/08/2014

Publication Date

04/12/2014

Tissue

Not available

Cell Type

B cell

Disease

celiac disease

Instrument

Q Exactive

Software

Not available

Quantification

Label free

Publication

    Bergseng E, Dørum S, Arntzen MØ, Nielsen M, Nygård S, Buus S, de Souza GA, Sollid LM. Different binding motifs of the celiac disease-associated HLA molecules DQ2.5, DQ2.2, and DQ7.5 revealed by relative quantitative proteomics of endogenous peptide repertoires. Immunogenetics. 2015 Feb;67(2):73-84 PubMed: 25502872