Modeling and systematic analysis of biomarker validation using selected reaction monitoring

Reanimation

Volumn 2014, Issue 1, 2014, Pages 1-12

  Atashpaz Gargari, Esmaeil ^a   Braga Neto, Ulisses M ^a,b   Dougherty, Edward R ^a,b  

^a Texas AandM University   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Biomarker validation; Mass spectrometry (MS); Proteomics; Selected reaction monitoring (SRM); Triple quadrupole (QQQ) systems

Indexed keywords

BIOLOGICAL MARKER; PEPTIDE;

ARTICLE; ENERGY; EXPERIMENT; IONIZATION; MASS SPECTROMETRY; MATHEMATICAL MODEL; METHODOLOGY; PARAMETERS; PROTEOMICS; PURIFICATION; SELECTED REACTION MONITORING; SIMULATION; VALIDATION PROCESS; WORKFLOW;

EID: 84912058814     PISSN: 16240693     EISSN: 19516959     Source Type: Journal    
DOI: 10.1186/s13637-014-0017-y     Document Type: Article

References (28)

1. R Aebersold, M Mann, Mass spectrometry-based proteomics. Nature 422(6928), 198–207 (2003).
2. C Dass, Fundamentals of Contemporary Mass Spectrometry (John Wiley & Sons, New York, 2007).
3. E de Hoffmann, Tandem mass spectrometry: a primer. J. Mass. Spectrom. 31(2), 129–137 (1996).
4. NR Kitteringham, RE Jenkins, CS Lane, VL Elliott, BK Park, Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J. Chromatogr. B 877(13), 1229–1239 (2009).
5. D Zakett, R Flynn, R Cooks, Chlorine isotope effects in mass spectrometry by multiple reaction monitoring. J. Phys. Chem. 82(22), 2359–2362 (1978).
6. J Baty, P Robinson, Single and multiple ion recording techniques for the analysis of diphenylhydantoin and its major metabolite in plasma. Biol. Mass Spectrom. 4(1), 36–41 (1977).
7. KK Murray, RK Boyd, MN Eberlin, GJ Langley, L Li, Y Naito, Standard definitions of terms relating to mass spectrometry (IUPAC recommendations 2013), Analytical Chemistry Division. Pure Appl. Chem. 85, 1515–1609 (2013). doi.org/10.1351/PAC-REC-06-04-06.
8. S Gallien, E Duriez, B Domon, Selected reaction monitoring applied to proteomics. J. Mass Spectrom. 46(3), 298–312 (2011).
9. EW Deutsch, H Lam, R Aebersold, PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows. EMBO Rep. 9(5), 429–434 (2008).
10. V Lange, JA Malmström, J Didion, NL King, BP Johansson, J Schäfer, J Rameseder, CH Wong, EW Deutsch, MY Brusniak, P Bühlmann, L Björck, B Domon, R Aebersold, Targeted quantitative analysis of streptococcus pyogenes virulence factors by multiple reaction monitoring. Mol. Cell. Proteomics 7(8), 1489–1500 (2008).
11. L Malmström, J Malmström, N Selevsek, G Rosenberger, R Aebersold, Automated workflow for large-scale selected reaction monitoring experiments. J. Proteome Res. 11, 1644–1653 (2012). doi:10.1021/pr200844d.
12. V Lange, P Picotti, B Domon, R Aebersold, Selected reaction monitoring for quantitative proteomics: a tutorial. Mol. Syst. Biol. 4(1), 222 (2008). doi:10.1038/msb.2008.61.
13. KW Lau, SR Hart, JA Lynch, SC Wong, SJ Hubbard, SJ Gaskell, Observations on the detection of b-and y-type ions in the collisionally activated decomposition spectra of protonated peptides. Rapid Commun. Mass. Spectrom. 23(10), 1508–1514 (2009).
14. Y Taniguchi, PJ Choi, GW Li, H Chen, M Babu, J Hearn, A Emili, XS Xie, Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science 329(5991), 533–538 (2010).
15. Y Sun, Braga-U Neto, ER Dougherty, A systematic model of the LC-MS proteomics pipeline. BMC Genomics 13(Suppl 6), 2 (2012).
16. C Furusawa, T Suzuki, A Kashiwagi, T Yomo, K Kaneko, Ubiquity of log-normal distributions in intra-cellular reaction dynamics. Biophysics 1, 25–31 (2005). doi:10.2142/biophysics.1.25.
17. C Furusawa, K Kaneko, Universal statistics for chemical abundances in a reproducing cell. J. Korean Phys. Soc. 50(1), 142 (2007).
18. J Hua, WD Tembe, ER Dougherty, Performance of feature-selection methods in the classification of high-dimension data. Pattern Recognit. 42(3), 409–424 (2009).
19. NL Anderson, NG Anderson, The human plasma proteome history, character, and diagnostic prospects. Mol. Cell. Proteomics 1(11), 845–867 (2002).
20. X Xu, TD Veenstra, Analysis of biofluids for biomarker research. Proteomics-Clinical Appl. 2(10-11), 1403–1412 (2008).
21. JE Bandow, Comparison of protein enrichment strategies for proteome analysis of plasma. Proteomics 10(7), 1416–1425 (2010).
22. W Timm, A Scherbart, S Böcker, O Kohlbacher, TW Nattkemper, Peak intensity prediction in MALDI-TOF mass spectrometry: a machine learning study to support quantitative proteomics. BMC Bioinf. 9(1), 443 (2008).
23. NB Cech, CG Enke, Practical implications of some recent studies in electrospray ionization fundamentals. Mass Spectrom. Rev. 20(6), 362–387 (2002).
24. P Picotti, O Rinner, R Stallmach, F Dautel, T Farrah, B Domon, H Wenschuh, R Aebersold, High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat. Methods 7(1), 43–46 (2009).
25. JM Froelich, GE Reid, The origin and control of ex vivo oxidative peptide modifications prior to mass spectrometry analysis. Proteomics 8(7), 1334–1345 (2008).
26. M Anderle, S Roy, H Lin, C Becker, K Joho, Quantifying reproducibility for differential proteomics: noise analysis for protein liquid chromatography-mass spectrometry of human serum. Bioinformatics 20(18), 3575–3582 (2004).
27. C Zhao, ML Bittner, RS Chapkin, ER Dougherty, Characterization of the effectiveness of reporting lists of small feature sets relative to the accuracy of the prior biological knowledge. Cancer Inf. 9, 49 (2010).
28. X Ye, J Blonder, TD Veenstra, Targeted proteomics for validation of biomarkers in clinical samples. Brief. Funct. Genomics Proteomics 8(2), 126–135 (2009).