Recognizing Millions of Consistently Unidentified Spectra Across Hundreds of Shotgun Proteomics Datasets

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2016 Aug 6

PMID 27493588

Citations 75

Authors

Johannes Griss

Yasset Perez-Riverol

Steve Lewis

David L Tabb

Jose A Dianes

Noemi Del-Toro

Marc Rurik

Mathias W Walzer

Oliver Kohlbacher

Henning Hermjakob

Rui Wang

Juan Antonio Vizcaino

Affiliations

Soon will be listed here.

Abstract

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

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References

Collins M, Wright J, Jones M, Rayner J, Choudhary J . Confident and sensitive phosphoproteomics using combinations of collision induced dissociation and electron transfer dissociation. J Proteomics. 2014; 103:1-14. PMC: 4047622. DOI: 10.1016/j.jprot.2014.03.010. View

Schittmayer M, Fritz K, Liesinger L, Griss J, Birner-Gruenberger R . Cleaning out the Litterbox of Proteomic Scientists' Favorite Pet: Optimized Data Analysis Avoiding Trypsin Artifacts. J Proteome Res. 2016; 15(4):1222-9. PMC: 4820788. DOI: 10.1021/acs.jproteome.5b01105. View

Frank A, Pevzner P . PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal Chem. 2005; 77(4):964-73. DOI: 10.1021/ac048788h. View

Vizcaino J, Csordas A, Del-Toro N, Dianes J, Griss J, Lavidas I . 2016 update of the PRIDE database and its related tools. Nucleic Acids Res. 2015; 44(D1):D447-56. PMC: 4702828. DOI: 10.1093/nar/gkv1145. View

Lam H, Deutsch E, Eddes J, Eng J, King N, Stein S . Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics. 2007; 7(5):655-67. DOI: 10.1002/pmic.200600625. View

The M, Kall L . MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics. J Proteome Res. 2015; 15(3):713-20. DOI: 10.1021/acs.jproteome.5b00749. View

Sleno L . The use of mass defect in modern mass spectrometry. J Mass Spectrom. 2012; 47(2):226-36. DOI: 10.1002/jms.2953. View

van Gestel R, van Solinge W, van der Toorn H, Rijksen G, Heck A, van Wijk R . Quantitative erythrocyte membrane proteome analysis with Blue-native/SDS PAGE. J Proteomics. 2009; 73(3):456-65. DOI: 10.1016/j.jprot.2009.08.010. View

Yao Q, Tian Y, Li P, Tian L, Qian Y, Li J . Design and development of a medical big data processing system based on Hadoop. J Med Syst. 2015; 39(3):23. DOI: 10.1007/s10916-015-0220-8. View

10.

Wang J, Perez-Santiago J, Katz J, Mallick P, Bandeira N . Peptide identification from mixture tandem mass spectra. Mol Cell Proteomics. 2010; 9(7):1476-85. PMC: 2938093. DOI: 10.1074/mcp.M000136-MCP201. View

11.

Craig R, Cortens J, Beavis R . Open source system for analyzing, validating, and storing protein identification data. J Proteome Res. 2004; 3(6):1234-42. DOI: 10.1021/pr049882h. View

12.

Craig R, Beavis R . TANDEM: matching proteins with tandem mass spectra. Bioinformatics. 2004; 20(9):1466-7. DOI: 10.1093/bioinformatics/bth092. View

13.

Omenn G, Lane L, Lundberg E, Beavis R, Nesvizhskii A, Deutsch E . Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification. J Proteome Res. 2015; 14(9):3452-60. PMC: 4755311. DOI: 10.1021/acs.jproteome.5b00499. View

14.

Mi H, Muruganujan A, Thomas P . PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res. 2012; 41(Database issue):D377-86. PMC: 3531194. DOI: 10.1093/nar/gks1118. View

15.

Chick J, Kolippakkam D, Nusinow D, Zhai B, Rad R, Huttlin E . A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides. Nat Biotechnol. 2015; 33(7):743-9. PMC: 4515955. DOI: 10.1038/nbt.3267. View

16.

Ye X, Li L . Macroporous reversed-phase separation of proteins combined with reversed-phase separation of phosphopeptides and tandem mass spectrometry for profiling the phosphoproteome of MDA-MB-231 cells. Electrophoresis. 2014; 35(24):3479-86. DOI: 10.1002/elps.201300586. View

17.

Menschaert G, Van Criekinge W, Notelaers T, Koch A, Crappe J, Gevaert K . Deep proteome coverage based on ribosome profiling aids mass spectrometry-based protein and peptide discovery and provides evidence of alternative translation products and near-cognate translation initiation events. Mol Cell Proteomics. 2013; 12(7):1780-90. PMC: 3708165. DOI: 10.1074/mcp.M113.027540. View

18.

Desiere F, Deutsch E, King N, Nesvizhskii A, Mallick P, Eng J . The PeptideAtlas project. Nucleic Acids Res. 2005; 34(Database issue):D655-8. PMC: 1347403. DOI: 10.1093/nar/gkj040. View

19.

Griss J, Foster J, Hermjakob H, Vizcaino J . PRIDE Cluster: building a consensus of proteomics data. Nat Methods. 2013; 10(2):95-6. PMC: 3667236. DOI: 10.1038/nmeth.2343. View

20.

Frank A, Monroe M, Shah A, Carver J, Bandeira N, Moore R . Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra. Nat Methods. 2011; 8(7):587-91. PMC: 3128193. DOI: 10.1038/nmeth.1609. View