Summary

Title

Mass spectrometry of HLA-I peptidomes reveals strong effects of protein abundance and turnover on antigen presentation

Description

HLA class I molecules reflect the health state of cells to cytotoxic T-cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (P<0.0001). When analyzing over-presented proteins - those with at least five-fold higher density score than expected for their abundance – we noticed that they are degraded almost 3 hours faster than similar but non-presented proteins (top 20% abundance class; median half-life 20.8h vs. 23.6h, p<0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain and nucleosomal proteins as particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our dataset. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides, suggesting the usefulness of combining MS-analysis with immunogenesis prediction for ranking and selection of epitopes for therapeutic use.

Sample Processing Protocol

Purification of HLA-I complexes. HLA-I peptidomes were obtained from 3-4 biological replicates per cell line. HLA-I complexes were purified from about 5x108 cell pellets after lysis with 0.25% sodium deoxycholate, 0.2 mM iodoacetamide, 1 mM EDTA, 1:200 Protease Inhibitors Cocktail (Sigma, MO), 1 mM PMSF, 1% octyl-β-D glucopyranoside (Sigma, MO) in PBS at 4 °C for 1 h. The lysates were cleared by 30 min centrifugation at 40,000 × g. We immunoaffinity purified HLA-I molecules from cleared lysate with the W6/32 antibody covalently bound to Protein-A Sepharose beads (Invitrogen, CA), because covalent binding of W6/32 antibody to the beads improves the purity of the eluted HLA-I complexes, diminishes co-elution of the antibodies which otherwise overload the C-18 cartridges and enables the reuse of the column. This affinity column was washed first with 10 column volumes of 150 mM NaCl, 20 mM Tris•HCl (buffer A), 10 column volumes of 400 mM NaCl, 20 mM Tris•HCl, 10 volumes of buffer A again, and finally with seven column volumes of 20 mM Tris•HCl, pH 8.0. The HLA-I molecules were eluted at room temperature by adding 500 µl of 0.1 N acetic acid, in total 7 elutions for each sample. Small aliquots of each elution fraction were analyzed by 12% SDS-PAGE to evaluate the yield and purity of the eluted HLA-I. Purification and concentration of HLA-I peptides. Eluted HLA-I peptides and the subunits of the HLA complex were loaded on Sep-Pak tC18 (Waters, MA) cartridges that were pre-washed with 80% acetonitrile (ACN) in 0.1% trifluoroacetic acid (TFA) and with 0.1% TFA only. After loading, the cartridges were washed with 0.1% TFA. The peptides were separated from the much more hydrophobic HLA-I heavy chains on the C18 cartridges by eluting them with 30% ACN in 0.1% TFA. They were further purified using a Silica C-18 column tips (Harvard Apparatus, MA) and eluted again with 30% ACN in 0.1% TFA. The peptides were concentrated and the volume was reduced to 15 µl using vacuum centrifugation. For MS analysis, we used 5 µl of this highly enriched HLA peptides. LC-MS/MS analysis of HLA-I peptides. HLA peptides were separated by a nanoflow HPLC (Proxeon Biosystems, Thermo Fisher Scientific, MA) and coupled on-line to a Q Exactive mass spectrometer (31) (Thermo Fisher Scientific, MA) with a nanoelectrospray ion source (Proxeon Biosystems). We packed a 20 cm long, 75 μm inner diameter column with ReproSil-Pur C18-AQ 1.9 μm resin (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) in buffer A (0.5% acetic acid). Peptides were eluted with a linear gradient of 2–30% buffer B (80% ACN and 0.5% acetic acid) at a flow rate of 250 nl/min over 90 min. Data was acquired using a data-dependent ‘top 10’ method, which isolated them and fragment them by higher energy collisional dissociation (HCD). We acquired full scan MS spectra at a resolution of 70,000 at 200 m/z with a target value of 3e6 ions. The ten most intense ions were sequentially isolated and accumulated to an AGC target value of 1e5 with a maximum injection time of generally 120 ms, except in a few cases where we used 250 ms to increase signal of the fragments. In case of unassigned precursor ion charge states, or charge states of four and above, no fragmentation was performed. The peptide match option was disabled. MS/MS resolution was 17,500 at 200 m/z. Fragmented m/z values were dynamically excluded from further selection for 15 or 20 seconds.

Data Processing Protocol

Mass spectrometry data analysis of HLA peptides. We employed the MaxQuant computational proteomics platform (32) version 1.3.10.15. Andromeda, a probabilistic search engine incorporated in the MaxQuant framework (33), was used to search the peak lists against the UniProt database (86,749 entries, June 2012) and a file containing 247 frequently observed contaminants such as human keratins, bovine serum proteins, and proteases. N-terminal acetylation (42.010565 Da) and methionine oxidation (15.994915 Da) were set as variable modifications. The second peptide identification option in Andromeda was enabled. The enzyme specificity was set as unspecific. Andromeda reports the posterior error probability and false discovery rate, which were used for statistical evaluation. A false discovery rate of 0.01 was required for peptides. As we are interested in HLA-I peptide identification rather than the protein identification common in proteomics, no protein false discovery rate was set. Likewise, as no sequence specific proteases are involved and peptides do not terminate in certain amino acids such as Arg or Lys, the special permutation rules in MaxQuant for these amino acids (32) were not used in creating the decoy database. Possible sequence matches were restricted to 8 to 15 a.a., a maximum peptides mass of 1,500 Da and a maximum charge states of three. The initial allowed mass deviation of the precursor ion was set to 6 ppm and the maximum fragment mass deviation was set to 20 ppm. We enabled the ‘match between runs’ option, which allows matching of identifications across different replicates that belongs to the same cell line, in a time window of 0.5 min and an initial alignment time window of 20 min. From the ‘peptide.txt’ output file produced by MaxQuant, hits to the reverse database and contaminants were eliminated. The resulting list of peptide is provided in Table S1.

Contact

Mario Oroshi, Proteomics
Matthias Mann, Dept. Proteomics and Signal Transduction Max-Planck Institute of Biochemistry Germany ( lab head )

Submission Date

24/11/2014

Publication Date

12/01/2015

Tissue

Not available

Cell Type

fibroblast
B cell

Instrument

Q Exactive

Software

Not available

Quantification

Not available

Experiment Type

Shotgun proteomics

Publication

    Bassani-Sternberg M, Pletscher-Frankild S, Jensen LJ, Mann M. Mass spectrometry of human leukocyte antigen class I peptidomes reveals strong effects of protein abundance and turnover on antigen presentation. Mol Cell Proteomics. 2015 Mar;14(3):658-73 PubMed: 25576301