Quantifying the effect of competition for detection between coeluting peptides on detection probabilities in mass-spectrometry-based proteomics

Journal of Proteome Research

Volumn 13, Issue 2, 2014, Pages 348-361

  Schliekelman, Paul ^a   Liu, Shangbin ^a  

^a UNIVERSITY OF GEORGIA   (United States)

Author keywords

elution time; LC MS MS; liquid chromatograph; mass spectrometry (MS); MS based proteomics; protein abundance; protein identification; retention time; simulation

Indexed keywords

CHROMATOGRAPHY, LIQUID; MODELS, THEORETICAL; PEPTIDES; PROBABILITY; PROTEOMICS; TANDEM MASS SPECTROMETRY;

EID: 84893847165     PISSN: 15353893     EISSN: 15353907     Source Type: Journal    
DOI: 10.1021/pr400034z     Document Type: Article

References (29)

1. Koziol, J. A.; Feng, A. C.; Schnitzer, J. E. Application of capture-recapture models to estimation of protein count in MudPIT experiments Anal. Chem. 2006, 78 (9) 3203-3207
2. Tang, H. X.; Arnold, R. J.; Alves, P.; Xun, Z. Y.; Clemmer, D. E.; Novotny, M. V.; Reilly, J. P.; Radivojac, P. A computational approach toward label-free protein quantification using predicted peptide detectability Bioinformatics 2006, 22 (14) E481-E488
3. Li, Y. F.; Arnold, R. J.; Tang, H. X.; Radivojac, P. The Importance of Peptide Detectability for Protein Identification, Quantification, and Experiment Design in MS/MS Proteomics J. Proteome Res. 2010, 9 (12) 6288-6297
4. Sanders, W. S.; Bridges, S. M.; McCarthy, F. M.; Nanduri, B.; Burgess, S. C. Prediction of peptides observable by mass spectrometry applied at the experimental set level BMC Bioinf. 2007, 8
5. Liu, H. B.; Sadygov, R. G.; Yates, J. R. A model for random sampling and estimation of relative protein abundance in shotgun proteomics Anal. Chem. 2004, 76 (14) 4193-4201
6. Alves, P.; Arnold, R. J.; Novotny, M. V.; Radivojac, P.; Reilly, J. P.; Tang, H. Advancement in Protein Inference from Shotgun Proteomics using Peptide Detectability Pac. Symp. Biocomput., 17th 2007, 12, 409-420
7. Kuster, B.; Schirle, M.; Mallick, P.; Aebersold, R. Scoring proteomes with proteotypic peptide probes Nat. Rev. Mol. Cell Biol. 2005, 6 (7) 577-583
8. Webb-Robertson, B. J. M.; Cannon, W. R.; Oehmen, C. S.; Shah, A. R.; Gurumoorthi, V.; Lipton, M. S.; Waters, K. M. A support vector machine model for the prediction of proteotypic peptides for accurate mass and time proteomics Bioinformatics 2008, 24 (13) 1503-1509
9. Eichacker, L. A.; Granvogl, B.; Mirus, O.; Muller, B. C.; Miess, C.; Schleiff, E. Hiding behind hydrophobicity-Transmembrane segments in mass spectrometry J. Biol. Chem. 2004, 279 (49) 50915-50922
10. Blonder, J.; Veenstra, T. D. Computational prediction of proteotypic peptides Expert Rev. Proteomics 2007, 4 (3) 351-354
11. Mallick, P.; Schirle, M.; Chen, S. S.; Flory, M. R.; Lee, H.; Martin, D.; Raught, B.; Schmitt, R.; Werner, T.; Kuster, B.; Aebersold, R. Computational prediction of proteotypic peptides for quantitative proteomics Nat. Biotechnol. 2007, 25 (1) 125-131
12. Mallick, P.; Schirle, M.; Kuster, B.; Aebersold, R. Predicting proteotypic peptides as probes for quantitative proteomics Mol.Cell.Proteomics 2006, 5 (10) S317-S317
13. Lu, P.; Vogel, C.; Wang, R.; Yao, X.; Marcotte, E. M. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation Nat. Biotechnol. 2007, 25 (1) 117-124
14. Le Bihan, T.; Robinson, M. D.; Stewart, I. I.; Figeys, D. Definition and characterization of a ″trypsinosome″ from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures J. Proteome Res. 2004, 3 (6) 1138-1148
15. Nielsen, M. L.; Savitski, M. M.; Kjeldsen, F.; Zubarev, R. A. Physicochemical properties determining the detection probability of tryptic peptides in Fourier transform mass spectrometry. A correlation study Anal. Chem. 2004, 76 (19) 5872-5877
16. Ethier, M.; Figeys, D. Strategy to design improved proteomic experiments based on statistical analyses of the chemical properties of identified peptides J. Proteome Res. 2005, 4 (6) 2201-2206
17. Fusaro, V. A.; Mani, D. R.; Mesirov, J. P.; Carr, S. A. Prediction of high-responding peptides for targeted protein assays by mass spectrometry Nat. Biotechnol. 2009, 27 (2) 190-198
18. Xu, C. M.; Zhang, J. Y.; Liu, H.; Sun, H. C.; Zhu, Y. P.; Xie, H. W. Advance of Peptide Detectability Prediction on Mass Spectrometry Platform in Proteomics Chin. J. Anal. Chem. 2010, 38 (2) 286-292
19. Alves, G.; Ogurtsov, A. Y.; Yu, Y. K. Assigning statistical significance to proteotypic peptides via database searches J. Proteomics 2011, 74 (2) 199-211
20. Savitski, M. M.; Nielsen, M. L.; Zubarev, R. A. ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures Mol. Cell. Proteomics 2006, 5 (5) 935-48
21. Petritis, K.; Kangas, L. J.; Ferguson, P. L.; Anderson, G. A.; Pasa-Tolic, L.; Lipton, M. S.; Auberry, K. J.; Strittmatter, E. F.; Shen, Y. F.; Zhao, R.; Smith, R. D. Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses Anal. Chem. 2003, 75 (5) 1039-1048
22. Barton, S. J.; Whittaker, J. C. Review of Factors That Influence the Abundance of Ions Produced in a Tandem Mass Spectrometer and Statistical Methods for Discovering These Factors Mass Spectrom. Rev. 2009, 28 (1) 177-187
23. Fenn, J. B. Ion Formation from Charged Droplets-Roles of Geometry, Energy, and Time J. Am. Soc. Mass Spectrom. 1993, 4 (7) 524-535
24. Gordon, E. F.; Mansoori, B. A.; Carroll, C. F.; Muddiman, D. C. Hydropathic influences on the quantification of equine heart cytochrome c using relative ion abundance measurements by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry J. Mass Spectrom. 1999, 34 (10) 1055-1062
25. Cech, N. B.; Krone, J. R.; Enke, C. G. Predicting electrospray response from chromatographic retention time Anal. Chem. 2001, 73 (2) 208-213
26. Gao, J.; Opiteck, G. J.; Friedrichs, M. S.; Dongre, A. R.; Hefta, S. A. Changes in the protein expression of yeast as a function of carbon source J. Proteome Res. 2003, 2 (6) 643-649
27. Bohrer, B. C.; Li, Y. F.; Reilly, J. P.; Clemmer, D. E.; DiMarchi, R. D.; Radivojac, P.; Tang, H. X.; Arnold, R. J. Combinatorial Libraries of Synthetic Peptides as a Model for Shotgun Proteomics Anal. Chem. 2010, 82 (15) 6559-6568
28. Petritis, K.; Kangas, L. J.; Yan, B.; Monroe, M. E.; Strittmatter, E. F.; Qian, W. J.; Adkins, J. N.; Moore, R. J.; Xu, Y.; Lipton, M. S.; Ii, D. G. C.; Smith, R. D. Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information Anal. Chem. 2006, 78 (14) 5026-5039
29. Pfeifer, N.; Leinenbach, A.; Huber, C. G.; Kohlbacher, O. Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics BMC Bioinf. 2007, 8