DIA-Umpire: Comprehensive Computational Framework for Data-independent Acquisition Proteomics

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2015 Jan 20

PMID 25599550

Citations 285

Authors

Chih-Chiang Tsou

Dmitry Avtonomov

Brett Larsen

Monika Tucholska

Hyungwon Choi

Anne-Claude Gingras

Alexey I Nesvizhskii

Affiliations

Soon will be listed here.

Abstract

As a result of recent improvements in mass spectrometry (MS), there is increased interest in data-independent acquisition (DIA) strategies in which all peptides are systematically fragmented using wide mass-isolation windows ('multiplex fragmentation'). DIA-Umpire (http://diaumpire.sourceforge.net/), a comprehensive computational workflow and open-source software for DIA data, detects precursor and fragment chromatographic features and assembles them into pseudo-tandem MS spectra. These spectra can be identified with conventional database-searching and protein-inference tools, allowing sensitive, untargeted analysis of DIA data without the need for a spectral library. Quantification is done with both precursor- and fragment-ion intensities. Furthermore, DIA-Umpire enables targeted extraction of quantitative information based on peptides initially identified in only a subset of the samples, resulting in more consistent quantification across multiple samples. We demonstrated the performance of the method with control samples of varying complexity and publicly available glycoproteomics and affinity purification-MS data.

Citing Articles

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References

Chambers M, MacLean B, Burke R, Amodei D, Ruderman D, Neumann S . A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol. 2012; 30(10):918-20. PMC: 3471674. DOI: 10.1038/nbt.2377. View

Michalski A, Cox J, Mann M . More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. J Proteome Res. 2011; 10(4):1785-93. DOI: 10.1021/pr101060v. View

Nesvizhskii A . A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J Proteomics. 2010; 73(11):2092-123. PMC: 2956504. DOI: 10.1016/j.jprot.2010.08.009. View

Tautenhahn R, Bottcher C, Neumann S . Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics. 2008; 9:504. PMC: 2639432. DOI: 10.1186/1471-2105-9-504. View

Li G, Vissers J, Silva J, Golick D, Gorenstein M, Geromanos S . Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics. 2009; 9(6):1696-719. DOI: 10.1002/pmic.200800564. View

Rost H, Rosenberger G, Navarro P, Gillet L, Miladinovic S, Schubert O . OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat Biotechnol. 2014; 32(3):219-23. DOI: 10.1038/nbt.2841. View

Kim S, Mischerikow N, Bandeira N, Navarro J, Wich L, Mohammed S . The generating function of CID, ETD, and CID/ETD pairs of tandem mass spectra: applications to database search. Mol Cell Proteomics. 2010; 9(12):2840-52. PMC: 3101864. DOI: 10.1074/mcp.M110.003731. View

Keller A, Nesvizhskii A, Kolker E, Aebersold R . Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem. 2002; 74(20):5383-92. DOI: 10.1021/ac025747h. View

Escher C, Reiter L, MacLean B, Ossola R, Herzog F, Chilton J . Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics. 2012; 12(8):1111-21. PMC: 3918884. DOI: 10.1002/pmic.201100463. View

10.

Cox J, Michalski A, Mann M . Software lock mass by two-dimensional minimization of peptide mass errors. J Am Soc Mass Spectrom. 2011; 22(8):1373-80. PMC: 3231580. DOI: 10.1007/s13361-011-0142-8. View

11.

Distler U, Kuharev J, Navarro P, Levin Y, Schild H, Tenzer S . Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics. Nat Methods. 2013; 11(2):167-70. DOI: 10.1038/nmeth.2767. View

12.

Colangelo C, Chung L, Bruce C, Cheung K . Review of software tools for design and analysis of large scale MRM proteomic datasets. Methods. 2013; 61(3):287-98. PMC: 3775261. DOI: 10.1016/j.ymeth.2013.05.004. View

13.

Weisbrod C, Eng J, Hoopmann M, Baker T, Bruce J . Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. J Proteome Res. 2012; 11(3):1621-32. PMC: 3319072. DOI: 10.1021/pr2008175. View

14.

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

15.

Tate S, Larsen B, Bonner R, Gingras A . Label-free quantitative proteomics trends for protein-protein interactions. J Proteomics. 2012; 81:91-101. DOI: 10.1016/j.jprot.2012.10.027. View

16.

Shteynberg D, Deutsch E, Lam H, Eng J, Sun Z, Tasman N . iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates. Mol Cell Proteomics. 2011; 10(12):M111.007690. PMC: 3237071. DOI: 10.1074/mcp.M111.007690. View

17.

Egertson J, Kuehn A, Merrihew G, Bateman N, MacLean B, Ting Y . Multiplexed MS/MS for improved data-independent acquisition. Nat Methods. 2013; 10(8):744-6. PMC: 3881977. DOI: 10.1038/nmeth.2528. View

18.

Choi H, Larsen B, Lin Z, Breitkreutz A, Mellacheruvu D, Fermin D . SAINT: probabilistic scoring of affinity purification-mass spectrometry data. Nat Methods. 2010; 8(1):70-3. PMC: 3064265. DOI: 10.1038/nmeth.1541. View

19.

Purvine S, Eppel J, Yi E, Goodlett D . Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics. 2003; 3(6):847-50. DOI: 10.1002/pmic.200300362. View

20.

Collins B, Gillet L, Rosenberger G, Rost H, Vichalkovski A, Gstaiger M . Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system. Nat Methods. 2013; 10(12):1246-53. DOI: 10.1038/nmeth.2703. View