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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.


Related in: MedlinePlus

Generation of assay libraries from a large collection of synthetic HLA class II peptides.(A) Workflow to generate an assay library from synthetic peptides. A total of 20,176 predicted peptides (with a range of 2 to 10 per ORF, and an average of 5), were synthesized and arranged into 23 peptide pools of ~900 peptides (Lindestam Arlehamn et al., PLoS Pathog, 2013). Spiked-in reference iRT peptides were used and the pools of synthetic peptides were analyzed in DDA mode using a 5600 Triple-TOF and an Orbitrap ELITE (CID and HCD fragmentation). The identified peptides were then processed through our computational pipeline to generate the assay library. (B) Venn diagram showing the overlap between peptides identified by the 5600 Triple-TOF and by the ELITE (CID and HCD fragmentation methods). Number of peptides identified is indicated in parenthesis. (C) Histogram showing the distribution of the precursor charge state.DOI:http://dx.doi.org/10.7554/eLife.07661.016
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fig2s3: Generation of assay libraries from a large collection of synthetic HLA class II peptides.(A) Workflow to generate an assay library from synthetic peptides. A total of 20,176 predicted peptides (with a range of 2 to 10 per ORF, and an average of 5), were synthesized and arranged into 23 peptide pools of ~900 peptides (Lindestam Arlehamn et al., PLoS Pathog, 2013). Spiked-in reference iRT peptides were used and the pools of synthetic peptides were analyzed in DDA mode using a 5600 Triple-TOF and an Orbitrap ELITE (CID and HCD fragmentation). The identified peptides were then processed through our computational pipeline to generate the assay library. (B) Venn diagram showing the overlap between peptides identified by the 5600 Triple-TOF and by the ELITE (CID and HCD fragmentation methods). Number of peptides identified is indicated in parenthesis. (C) Histogram showing the distribution of the precursor charge state.DOI:http://dx.doi.org/10.7554/eLife.07661.016

Mentions: Libraries of consensus fragment ion spectra can be converted into high quality assays for high-throughput targeted analysis of SWATH-MS data, an emerging approach for reproducible, consistent and accurate quantitative measurements of peptides (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). Here, we aimed at initiating a worldwide community-based effort to generate pilot HLA allele-specific peptide assay libraries that could be further used for the analysis of SWATH-MS HLA peptidomic data. Naturally presented and/or synthetic HLA class I and class II peptides were provided from six independent laboratories and were analyzed using four distinct TripleTOF 5600 MS instruments operated in DDA acquisition mode in four different international institutions. Naturally presented HLA class I peptides from JYEBV+ (HLA-A02 and -B07), PBMC (HLA-A03, -A26, -B51 and -B57), and Jurkat (HLA-A03, -B07 and -B35) cells were isolated by immunoaffinity chromatography (Figure 2—source data 1). Natural class I peptides from three C1R cell lines—stably expressing HLA-C04 as well as HLA-B27, -B39 or -B40 molecules—were also isolated using the same procedure. Synthetic EBV-derived peptides known to bind HLA-A02 or -B07 were also used to build the libraries (Figure 2—source data 2). All laboratories used the spiked-in landmark iRT peptides for retention time normalization (Escher et al., 2012). The DDA data generated by the different groups were shared and pipelined through the computational workflow described above, resulting in the identification of 7668 (peptide-level FDR 1%; average cFDR 0.5%) or 11,275 (peptide-level FDR 5%; average cFDR 2.5%) distinct HLA class I peptides distributed across eleven different HLA class I alleles (Figure 2—figure supplement 2B and Figure 2—source data 3). To properly assess the efficiency of generating HLA peptide assay libraries from synthetic peptides, a large collection of 20,176 synthetic HLA class II peptides was analyzed by DDA using different mass spectrometers and fragmentation methods (Figure 2—figure supplement 3 and Figure 2—source data 2). Our results show that a total of 15,875 peptides (∼79%) were identified (Figure 2—source data 2). A large collection of synthetic HLA class I peptides was not available but could be used in the future to extend the contents of the present class I libraries derived from native peptides. All identified peptides were used to build the HLA allele-specific peptide assay libraries (‘Materials and methods’). To date, the pilot libraries contain a total of 223,735 transitions for 26,857 unique peptides and were stored by class and allele in the SWATHAtlas database (Figure 2—source data 5 and http://www.swathatlas.org). By using the automated HLA peptide annotation method described above, we observed that similar binding affinities were predicted for HLA class I peptides identified at peptide-level FDR 1% and peptide-level FDR 5% (Figure 2—figure supplement 4 and Figure 2—figure supplement 5), suggesting that a large fraction of true positives were excluded at peptide-level FDR 1%. Our data also show that 95% of the annotated class I peptides in this study were predicted to bind their respective HLA molecules with an IC50 ranging from 72 nM (for HLA-A01) to 5682 nM (for HLA-B51) at peptide-level FDR 1% (Figure 2—figure supplement 4). Similar results were obtained at peptide-level FDR 5% (Figure 2—figure supplement 5). This result supports a recent study indicating that HLA class I alleles are associated with peptide-binding repertoires of different affinity (Paul et al., 2013). Altogether, we demonstrated the feasibility of collecting DDA data from multiple international laboratories to generate standardized HLA allele-specific peptide assay libraries. We anticipate this global effort as a first step towards the development of a standardized Pan-human HLA peptide assay library, which could be used to rapidly and reproducibly quantify the entire repertoire of peptides presented by HLA molecules using 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)

Generation of assay libraries from a large collection of synthetic HLA class II peptides.(A) Workflow to generate an assay library from synthetic peptides. A total of 20,176 predicted peptides (with a range of 2 to 10 per ORF, and an average of 5), were synthesized and arranged into 23 peptide pools of ~900 peptides (Lindestam Arlehamn et al., PLoS Pathog, 2013). Spiked-in reference iRT peptides were used and the pools of synthetic peptides were analyzed in DDA mode using a 5600 Triple-TOF and an Orbitrap ELITE (CID and HCD fragmentation). The identified peptides were then processed through our computational pipeline to generate the assay library. (B) Venn diagram showing the overlap between peptides identified by the 5600 Triple-TOF and by the ELITE (CID and HCD fragmentation methods). Number of peptides identified is indicated in parenthesis. (C) Histogram showing the distribution of the precursor charge state.DOI:http://dx.doi.org/10.7554/eLife.07661.016
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Related In: Results  -  Collection

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

fig2s3: Generation of assay libraries from a large collection of synthetic HLA class II peptides.(A) Workflow to generate an assay library from synthetic peptides. A total of 20,176 predicted peptides (with a range of 2 to 10 per ORF, and an average of 5), were synthesized and arranged into 23 peptide pools of ~900 peptides (Lindestam Arlehamn et al., PLoS Pathog, 2013). Spiked-in reference iRT peptides were used and the pools of synthetic peptides were analyzed in DDA mode using a 5600 Triple-TOF and an Orbitrap ELITE (CID and HCD fragmentation). The identified peptides were then processed through our computational pipeline to generate the assay library. (B) Venn diagram showing the overlap between peptides identified by the 5600 Triple-TOF and by the ELITE (CID and HCD fragmentation methods). Number of peptides identified is indicated in parenthesis. (C) Histogram showing the distribution of the precursor charge state.DOI:http://dx.doi.org/10.7554/eLife.07661.016
Mentions: Libraries of consensus fragment ion spectra can be converted into high quality assays for high-throughput targeted analysis of SWATH-MS data, an emerging approach for reproducible, consistent and accurate quantitative measurements of peptides (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). Here, we aimed at initiating a worldwide community-based effort to generate pilot HLA allele-specific peptide assay libraries that could be further used for the analysis of SWATH-MS HLA peptidomic data. Naturally presented and/or synthetic HLA class I and class II peptides were provided from six independent laboratories and were analyzed using four distinct TripleTOF 5600 MS instruments operated in DDA acquisition mode in four different international institutions. Naturally presented HLA class I peptides from JYEBV+ (HLA-A02 and -B07), PBMC (HLA-A03, -A26, -B51 and -B57), and Jurkat (HLA-A03, -B07 and -B35) cells were isolated by immunoaffinity chromatography (Figure 2—source data 1). Natural class I peptides from three C1R cell lines—stably expressing HLA-C04 as well as HLA-B27, -B39 or -B40 molecules—were also isolated using the same procedure. Synthetic EBV-derived peptides known to bind HLA-A02 or -B07 were also used to build the libraries (Figure 2—source data 2). All laboratories used the spiked-in landmark iRT peptides for retention time normalization (Escher et al., 2012). The DDA data generated by the different groups were shared and pipelined through the computational workflow described above, resulting in the identification of 7668 (peptide-level FDR 1%; average cFDR 0.5%) or 11,275 (peptide-level FDR 5%; average cFDR 2.5%) distinct HLA class I peptides distributed across eleven different HLA class I alleles (Figure 2—figure supplement 2B and Figure 2—source data 3). To properly assess the efficiency of generating HLA peptide assay libraries from synthetic peptides, a large collection of 20,176 synthetic HLA class II peptides was analyzed by DDA using different mass spectrometers and fragmentation methods (Figure 2—figure supplement 3 and Figure 2—source data 2). Our results show that a total of 15,875 peptides (∼79%) were identified (Figure 2—source data 2). A large collection of synthetic HLA class I peptides was not available but could be used in the future to extend the contents of the present class I libraries derived from native peptides. All identified peptides were used to build the HLA allele-specific peptide assay libraries (‘Materials and methods’). To date, the pilot libraries contain a total of 223,735 transitions for 26,857 unique peptides and were stored by class and allele in the SWATHAtlas database (Figure 2—source data 5 and http://www.swathatlas.org). By using the automated HLA peptide annotation method described above, we observed that similar binding affinities were predicted for HLA class I peptides identified at peptide-level FDR 1% and peptide-level FDR 5% (Figure 2—figure supplement 4 and Figure 2—figure supplement 5), suggesting that a large fraction of true positives were excluded at peptide-level FDR 1%. Our data also show that 95% of the annotated class I peptides in this study were predicted to bind their respective HLA molecules with an IC50 ranging from 72 nM (for HLA-A01) to 5682 nM (for HLA-B51) at peptide-level FDR 1% (Figure 2—figure supplement 4). Similar results were obtained at peptide-level FDR 5% (Figure 2—figure supplement 5). This result supports a recent study indicating that HLA class I alleles are associated with peptide-binding repertoires of different affinity (Paul et al., 2013). Altogether, we demonstrated the feasibility of collecting DDA data from multiple international laboratories to generate standardized HLA allele-specific peptide assay libraries. We anticipate this global effort as a first step towards the development of a standardized Pan-human HLA peptide assay library, which could be used to rapidly and reproducibly quantify the entire repertoire of peptides presented by HLA molecules using 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.


Related in: MedlinePlus