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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.


Distribution curves of peptide binding affinities for different HLA-A and -B alleles (5% peptide-level FDR; 2.5% cFDR).The predicted IC50 values of the annotated peptides in Figure 2—source data 3 were used to generate the distribution curves (blue line). The proportion of peptides with a predicted affinity lower than the established 500nM threshold (grey) is indicated for individual HLA alleles. The plots also indicate that 95% of the annotated peptides (green) are predicted to bind their respective HLA molecules with an IC50 ranging from 388 nM (HLA-A01) to 5761 nM (HLA-B51).DOI:http://dx.doi.org/10.7554/eLife.07661.018
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fig2s5: Distribution curves of peptide binding affinities for different HLA-A and -B alleles (5% peptide-level FDR; 2.5% cFDR).The predicted IC50 values of the annotated peptides in Figure 2—source data 3 were used to generate the distribution curves (blue line). The proportion of peptides with a predicted affinity lower than the established 500nM threshold (grey) is indicated for individual HLA alleles. The plots also indicate that 95% of the annotated peptides (green) are predicted to bind their respective HLA molecules with an IC50 ranging from 388 nM (HLA-A01) to 5761 nM (HLA-B51).DOI:http://dx.doi.org/10.7554/eLife.07661.018

Mentions: PBMC#2 was typed positive for HLA-A02, -A03, -B35, -B39, and is shown here as a representative sample. (A) The stand-alone software package of the HLA binding prediction algorithm NetMHC 3.4 was used to predict the binding affinity of all identified peptides to HLA-A02, -A03, -B35 and -B39 (four peptides are shown for simplicity). For each peptide, an annotation score was calculated by dividing the second lowest IC50 value (second best predicted allele) by the lowest IC50 value (best predicted allele). Peptides with a score ≥3 were annotated to the HLA allele predicted to bind best. Peptides with a score below 3 were considered as non-annotated. Non-annotated peptides were curated in the output files in Figure 2—source data 2 and correspond to 1) non-HLA peptides/contaminants, 2) peptides predicted to strongly bind more than one HLA allele (supertype peptides), 3) peptides predicted to bind HLA-C alleles, 4) exceptional HLA peptides with no known binding motifs. Annotation scores of all eluted peptides are shown in Figure 2—source data 2. Additional information is provided in Supplementary file 1. (B) Curves showing the distribution of the predicted HLA binding affinities for all HLA-A03-annotated peptides with a score ≥3. Overall, 91% of all HLA-A03-annotated peptides are predicted to have a binding affinity below 500 nM for the HLA-A03 molecule (see also Figure 2—figure supplement 4 and Figure 2—figure supplement 5). The same peptides are predicted to be non-binders for the other alleles – i.e., HLA-A02, -B35 and -B39. (C) Heat map visualization following clustering of predicted HLA binding affinity values. The white box highlights HLA-A03-annotated peptides. The four peptides in the table in (a) are indicated by arrows and their respective predicted binding affinity for the HLA-A03 molecule is indicated in parenthesis.


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)

Distribution curves of peptide binding affinities for different HLA-A and -B alleles (5% peptide-level FDR; 2.5% cFDR).The predicted IC50 values of the annotated peptides in Figure 2—source data 3 were used to generate the distribution curves (blue line). The proportion of peptides with a predicted affinity lower than the established 500nM threshold (grey) is indicated for individual HLA alleles. The plots also indicate that 95% of the annotated peptides (green) are predicted to bind their respective HLA molecules with an IC50 ranging from 388 nM (HLA-A01) to 5761 nM (HLA-B51).DOI:http://dx.doi.org/10.7554/eLife.07661.018
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4507788&req=5

fig2s5: Distribution curves of peptide binding affinities for different HLA-A and -B alleles (5% peptide-level FDR; 2.5% cFDR).The predicted IC50 values of the annotated peptides in Figure 2—source data 3 were used to generate the distribution curves (blue line). The proportion of peptides with a predicted affinity lower than the established 500nM threshold (grey) is indicated for individual HLA alleles. The plots also indicate that 95% of the annotated peptides (green) are predicted to bind their respective HLA molecules with an IC50 ranging from 388 nM (HLA-A01) to 5761 nM (HLA-B51).DOI:http://dx.doi.org/10.7554/eLife.07661.018
Mentions: PBMC#2 was typed positive for HLA-A02, -A03, -B35, -B39, and is shown here as a representative sample. (A) The stand-alone software package of the HLA binding prediction algorithm NetMHC 3.4 was used to predict the binding affinity of all identified peptides to HLA-A02, -A03, -B35 and -B39 (four peptides are shown for simplicity). For each peptide, an annotation score was calculated by dividing the second lowest IC50 value (second best predicted allele) by the lowest IC50 value (best predicted allele). Peptides with a score ≥3 were annotated to the HLA allele predicted to bind best. Peptides with a score below 3 were considered as non-annotated. Non-annotated peptides were curated in the output files in Figure 2—source data 2 and correspond to 1) non-HLA peptides/contaminants, 2) peptides predicted to strongly bind more than one HLA allele (supertype peptides), 3) peptides predicted to bind HLA-C alleles, 4) exceptional HLA peptides with no known binding motifs. Annotation scores of all eluted peptides are shown in Figure 2—source data 2. Additional information is provided in Supplementary file 1. (B) Curves showing the distribution of the predicted HLA binding affinities for all HLA-A03-annotated peptides with a score ≥3. Overall, 91% of all HLA-A03-annotated peptides are predicted to have a binding affinity below 500 nM for the HLA-A03 molecule (see also Figure 2—figure supplement 4 and Figure 2—figure supplement 5). The same peptides are predicted to be non-binders for the other alleles – i.e., HLA-A02, -B35 and -B39. (C) Heat map visualization following clustering of predicted HLA binding affinity values. The white box highlights HLA-A03-annotated peptides. The four peptides in the table in (a) are indicated by arrows and their respective predicted binding affinity for the HLA-A03 molecule is indicated in parenthesis.

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.