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An open-source computational and data resource to analyze digital maps of immunopeptidomes.

Caron E, Espona L, Kowalewski DJ, Schuster H, Ternette N, Alpízar A, Schittenhelm RB, Ramarathinam SH, Lindestam Arlehamn CS, Chiek Koh C, Gillet LC, Rabsteyn A, Navarro P, Kim S, Lam H, Sturm T, Marcilla M, Sette A, Campbell DS, Deutsch EW, Moritz RL, Purcell AW, Rammensee HG, Stevanovic S, Aebersold R - Elife (2015)

Bottom Line: We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides.Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS).This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.

ABSTRACT
We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

No MeSH data available.


OpenSWATH analysis of HLA peptidomic data.(A) HLA class I peptides isolated from JY cells were acquired in SWATH/DIA mode using windows of 10 Da (blue) or 25 Da (red) width each. The graph shows the proportion of peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from a merged (A02+B07) or unmerged (A02 or B07) HLA allele-specific assay library. (B) pyProphet statistical analysis from a JY HLA class I peptide extract. The histogram plots show the distribution of decoy and target transition groups according to their discriminant score (dscore) determined by the pyProphet software. (C) HLA class I peptides were isolated form various cell types and analyzed by SWATH-MS using windows of 25 Da width each. The histogram shows the number of HLA peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from different HLA allele-specific assay library.DOI:http://dx.doi.org/10.7554/eLife.07661.022
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fig3s1: OpenSWATH analysis of HLA peptidomic data.(A) HLA class I peptides isolated from JY cells were acquired in SWATH/DIA mode using windows of 10 Da (blue) or 25 Da (red) width each. The graph shows the proportion of peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from a merged (A02+B07) or unmerged (A02 or B07) HLA allele-specific assay library. (B) pyProphet statistical analysis from a JY HLA class I peptide extract. The histogram plots show the distribution of decoy and target transition groups according to their discriminant score (dscore) determined by the pyProphet software. (C) HLA class I peptides were isolated form various cell types and analyzed by SWATH-MS using windows of 25 Da width each. The histogram shows the number of HLA peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from different HLA allele-specific assay library.DOI:http://dx.doi.org/10.7554/eLife.07661.022

Mentions: SWATH-MS is emerging as a robust next-generation proteomics technique for efficiently generating reproducible, consistent and quantitatively accurate measurements of peptides across multiple samples (Gillet et al., 2012; Collins et al., 2013; Rosenberger et al., 2014; Röst et al., 2014; Guo et al., 2015; Liu et al., 2015; Selevsek et al., 2015; Schubert et al., 2015a). To promote the worldwide development of SWATH-based MS platforms towards robust quantitative measurements of HLA peptidomes, we assessed whether the HLA allele-specific assay libraries described above could be used to extract quantitative information from digital SWATH maps acquired by different laboratories. Importantly, four independent laboratories generated their own digital SWATH maps using TripleTOF 5600 MS operated in DIA acquisition mode. Naturally presented HLA class I peptides were isolated from the cell types mentioned above (i.e., JYEBV+, Jurkat, PBMC and C1R). Precursors in the range of 400–1200 Th were divided into 32 SWATH windows of 25 Da (Gillet et al., 2012). All ionized peptide precursors in this mass range were fragmented, generating comprehensive and quantitative digital fragment ion maps. The HLA peptidome of JYEBV+ cells was analyzed using the OpenSWATH (Röst et al., 2014) software tool and a combined assay library containing 22,206 transitions for 1507 HLA-A02 and 2194 HLA-B07 peptides—the two dominant HLA alleles expressed on these cells. At an estimated peptide-level FDR of 1% (m-score < 0.01), a total of 3150 unique HLA class I peptides were identified from the digital SWATH map (Figure 3A,B,C, Figure 3—figure supplement 1A,B, Figure 3—figure supplement 7 and Figure 3—source data 1). Notably, assays generated from the synthetic EBV-related class I peptides enabled the identification of one EBV-derived HLA-A02 peptide (Figure 3C), thereby demonstrating that building high-quality assay libraries from synthetic class I peptides of pathogen origin could be useful for the identification of non-self HLA-bound peptides by SWATH-MS. To analyze self-HLA peptides isolated from PBMC (HLA-A03, -A26, -B51 and -B57), Jurkat (HLA-A03, B07 and -B35), C1R-B27 (HLA-B27) and C1R-B40 (HLA-B40) cells, the matching HLA class I allele-specific peptide assay libraries were combined accordingly using SpectraST and then processed in the OpenSWATH software. High-throughput targeted analysis from these four additional peptidomic datasets indicated that ∼81% of HLA class I peptides present in an assay library could be extracted from a quantitative digital SWATH map in a cell type-independent manner (peptide-level FDR 1%) (Figure 3—figure supplement 1C, Figure 3—figure supplements 2–6 and Figure 3—source data 1). We next optimized the SWATH acquisition conditions according to the size distribution of HLA class I peptides. Most class I peptide precursors (∼98%) fall within the range of 400–700 Th and were divided in 30 SWATH windows of 10 Da width each. Using SWATH data generated from JYEBV+ cells, we found that narrowing the size of the windows by 2.5-fold resulted in a ∼13% fold-increase in the identification of class I peptides (Figure 3—figure supplement 1A). The R2 value for SWATH-MS quantification was 0.979 from two technical replicates (Figure 3D). In accordance with previous studies, we also observed that the dynamic range of peptides quantified in different cell types using SWATH-MS, based on their signal intensity, was about 3-4 orders of magnitude (Figure 3E) (Hassan et al., 2013; Bassani-Sternberg et al., 2015). Altogether, we demonstrate the feasibility of an international effort to build standardized HLA allele-specific peptide assay libraries, which were used to extract quantitative information from digital SWATH maps acquired in different sites. We therefore provide a proof of concept that acquisition of SWATH-MS HLA peptidomic data may enable robust analysis of the human immunopeptidome on a global scale.10.7554/eLife.07661.020Figure 3.High-throughput targeted analysis of HLA peptidomic data by SWATH-MS.


An open-source computational and data resource to analyze digital maps of immunopeptidomes.

Caron E, Espona L, Kowalewski DJ, Schuster H, Ternette N, Alpízar A, Schittenhelm RB, Ramarathinam SH, Lindestam Arlehamn CS, Chiek Koh C, Gillet LC, Rabsteyn A, Navarro P, Kim S, Lam H, Sturm T, Marcilla M, Sette A, Campbell DS, Deutsch EW, Moritz RL, Purcell AW, Rammensee HG, Stevanovic S, Aebersold R - Elife (2015)

OpenSWATH analysis of HLA peptidomic data.(A) HLA class I peptides isolated from JY cells were acquired in SWATH/DIA mode using windows of 10 Da (blue) or 25 Da (red) width each. The graph shows the proportion of peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from a merged (A02+B07) or unmerged (A02 or B07) HLA allele-specific assay library. (B) pyProphet statistical analysis from a JY HLA class I peptide extract. The histogram plots show the distribution of decoy and target transition groups according to their discriminant score (dscore) determined by the pyProphet software. (C) HLA class I peptides were isolated form various cell types and analyzed by SWATH-MS using windows of 25 Da width each. The histogram shows the number of HLA peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from different HLA allele-specific assay library.DOI:http://dx.doi.org/10.7554/eLife.07661.022
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4507788&req=5

fig3s1: OpenSWATH analysis of HLA peptidomic data.(A) HLA class I peptides isolated from JY cells were acquired in SWATH/DIA mode using windows of 10 Da (blue) or 25 Da (red) width each. The graph shows the proportion of peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from a merged (A02+B07) or unmerged (A02 or B07) HLA allele-specific assay library. (B) pyProphet statistical analysis from a JY HLA class I peptide extract. The histogram plots show the distribution of decoy and target transition groups according to their discriminant score (dscore) determined by the pyProphet software. (C) HLA class I peptides were isolated form various cell types and analyzed by SWATH-MS using windows of 25 Da width each. The histogram shows the number of HLA peptides that were confidently extracted (FDR < 0.01) using OpenSWATH from different HLA allele-specific assay library.DOI:http://dx.doi.org/10.7554/eLife.07661.022
Mentions: SWATH-MS is emerging as a robust next-generation proteomics technique for efficiently generating reproducible, consistent and quantitatively accurate measurements of peptides across multiple samples (Gillet et al., 2012; Collins et al., 2013; Rosenberger et al., 2014; Röst et al., 2014; Guo et al., 2015; Liu et al., 2015; Selevsek et al., 2015; Schubert et al., 2015a). To promote the worldwide development of SWATH-based MS platforms towards robust quantitative measurements of HLA peptidomes, we assessed whether the HLA allele-specific assay libraries described above could be used to extract quantitative information from digital SWATH maps acquired by different laboratories. Importantly, four independent laboratories generated their own digital SWATH maps using TripleTOF 5600 MS operated in DIA acquisition mode. Naturally presented HLA class I peptides were isolated from the cell types mentioned above (i.e., JYEBV+, Jurkat, PBMC and C1R). Precursors in the range of 400–1200 Th were divided into 32 SWATH windows of 25 Da (Gillet et al., 2012). All ionized peptide precursors in this mass range were fragmented, generating comprehensive and quantitative digital fragment ion maps. The HLA peptidome of JYEBV+ cells was analyzed using the OpenSWATH (Röst et al., 2014) software tool and a combined assay library containing 22,206 transitions for 1507 HLA-A02 and 2194 HLA-B07 peptides—the two dominant HLA alleles expressed on these cells. At an estimated peptide-level FDR of 1% (m-score < 0.01), a total of 3150 unique HLA class I peptides were identified from the digital SWATH map (Figure 3A,B,C, Figure 3—figure supplement 1A,B, Figure 3—figure supplement 7 and Figure 3—source data 1). Notably, assays generated from the synthetic EBV-related class I peptides enabled the identification of one EBV-derived HLA-A02 peptide (Figure 3C), thereby demonstrating that building high-quality assay libraries from synthetic class I peptides of pathogen origin could be useful for the identification of non-self HLA-bound peptides by SWATH-MS. To analyze self-HLA peptides isolated from PBMC (HLA-A03, -A26, -B51 and -B57), Jurkat (HLA-A03, B07 and -B35), C1R-B27 (HLA-B27) and C1R-B40 (HLA-B40) cells, the matching HLA class I allele-specific peptide assay libraries were combined accordingly using SpectraST and then processed in the OpenSWATH software. High-throughput targeted analysis from these four additional peptidomic datasets indicated that ∼81% of HLA class I peptides present in an assay library could be extracted from a quantitative digital SWATH map in a cell type-independent manner (peptide-level FDR 1%) (Figure 3—figure supplement 1C, Figure 3—figure supplements 2–6 and Figure 3—source data 1). We next optimized the SWATH acquisition conditions according to the size distribution of HLA class I peptides. Most class I peptide precursors (∼98%) fall within the range of 400–700 Th and were divided in 30 SWATH windows of 10 Da width each. Using SWATH data generated from JYEBV+ cells, we found that narrowing the size of the windows by 2.5-fold resulted in a ∼13% fold-increase in the identification of class I peptides (Figure 3—figure supplement 1A). The R2 value for SWATH-MS quantification was 0.979 from two technical replicates (Figure 3D). In accordance with previous studies, we also observed that the dynamic range of peptides quantified in different cell types using SWATH-MS, based on their signal intensity, was about 3-4 orders of magnitude (Figure 3E) (Hassan et al., 2013; Bassani-Sternberg et al., 2015). Altogether, we demonstrate the feasibility of an international effort to build standardized HLA allele-specific peptide assay libraries, which were used to extract quantitative information from digital SWATH maps acquired in different sites. We therefore provide a proof of concept that acquisition of SWATH-MS HLA peptidomic data may enable robust analysis of the human immunopeptidome on a global scale.10.7554/eLife.07661.020Figure 3.High-throughput targeted analysis of HLA peptidomic data by SWATH-MS.

Bottom Line: We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides.Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS).This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.

ABSTRACT
We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

No MeSH data available.