A Data Processing Tool for Mass Spectrometry Data from iSRM Strategy in Proteomics

ZHANG Wei; WEI Jun-ying; JIA Ting; XU Chang-ming; ZHANG Ji-yang; ZHU Yun-ping; QIAN Xiao-hong; ZHANG Yang-jun; XIE Hong-wei

doi:10.7538/zpxb.2013.34.01.0015

Journal of Chinese Mass Spectrometry Society > 2013 > 34(1): 15-22. > DOI: 10.7538/zpxb.2013.34.01.0015 CSTR: 32365.14.zpxb.2013.34.01.0015

ZHANG Wei, WEI Jun-ying, JIA Ting, XU Chang-ming, ZHANG Ji-yang, ZHU Yun-ping, QIAN Xiao-hong, ZHANG Yang-jun, XIE Hong-wei. A Data Processing Tool for Mass Spectrometry Data from iSRM Strategy in Proteomics[J]. Journal of Chinese Mass Spectrometry Society, 2013, 34(1): 15-22. DOI: 10.7538/zpxb.2013.34.01.0015

Citation:

PDF (1080 KB)

A Data Processing Tool for Mass Spectrometry Data from iSRM Strategy in Proteomics

1.
Department of Automatic Control, College of Mechatronics and Automation, National University of Defence Technology, Changsha 410073, China
2.
State Key Laboratory of Proteomics, Beijing Proteome Research Center,Beijing Institute of Radiation Medicine, Beijing 102206, China
3.
Reproductive Medical Center, the Second Hospital Affiliated to Shandong University of Traditional Chinese Medicine, Ji’nan 250001, China

More Information

Graphical Abstract

Abstract

Abstract

In proteomics research, selected reaction monitoring (SRM) technology based on mass spectrometry has been widely applied in the protein quantitative analysis because of its high reproducibility and accuracy. Intelligent selected reaction monitoring (iSRM) technology is a new SRM experimental strategy. In order to process the mass spectrometry data produced by iSRM, a peptide quantitative information extraction tool called iSQuant is developed. iSQuant is written with MATLAB programming language, and thus is convenient and user-friendly. Finally, a replicated dataset and a standard dataset are used to evaluate the performances of iSQuant. The results show that iSQuant has superior reproducibility and linearity.
- intelligent selected reaction monitoring (iSRM),
- mass spectrometry analysis,
- proteomics,
- analysis tool,
- reproducibility,
- linearity

FullText(HTML)

References (21)

References

[1]	AEBERSOLD R, MANN M. Mass spectrometrybased proteomics [J]. Nature, 2003, 422(6 928): 198-207.
[2]	YATES J R, RUSE C I, Nakorchevsky a proteo-mics by mass spectrometry: Approaches, advances, and applications [J]. Annu Rev Biomed Eng, 2009, 11(1): 49-79.
[3]	张伟, 张纪阳, 刘辉, 等. 蛋白质质谱分析的无标记定量算法研究进展[J]. 生物化学与生物物理进展, 2011, 38(6): 506-518.
[4]	LANGE V, PICOTTI P, DOMON B, et al. Selected reaction monitoring for quantitative proteomics: A tutorial [J]. Mol Syst Biol, 2008, 4(10): 222-235.
[5]	PICOTTI P, AEBERSOLD R. Selected reaction monitoring-based proteomics: Workflows, potential, pitfalls and future directions [J]. Nat Methods, 2012, 9(6): 555-566.
[6]	BR-NSTRUP M. Absolute quantification strategies in proteomics based on mass spectrometry[J]. Expert Rev Proteomics, 2004, 1(4): 503-512.
[7]	YOST R A, ENKE C G. Triple quadrupole mass spectrometry for direct mixture analysis and structural elucidation[J]. Anal Chem, 1979, 51(12): 1251-1264.
[8]	YOST R A, ENKE C G. Selected ion fragmentation with a tandem quadrupole mass spectrometer[J]. J Am Chem Soc, 1978, 100(7): 2274-2275.
[9]	LIN D, TABB D L, YATES J R. Large-scale protein identification using mass spectrometry [J]. Biochim Biophys Acta, 2003, 1 646(1/2): 1-10.
[10]	KIYONAMI R, SCHOEN A, PRAKASH A, et al.Increased selectivity, analytical precision, and throughput in targeted proteomics [J]. Mol Cell Proteomics, 2011, 10(2): M110002931.
[11]	REITER L, RINNER O, PICOTTI P, et al. mP-rophet: Automated data processing and statistical validation for largescale SRM experiments [J]. Nat Methods, 2011, 8(5): 430-435.
[12]	MACLEAN B, TOMAZELA D M, SHULMAN N, et al. Skyline: An open source document editor for creating and analyzing targeted proteomics experiments [J]. Bioinformatics, 2010, 26(7): 966-968.
[13]	BRUSNIAK M Y, KWOK S T, CHRISTIANSEN M, et al. ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry [J]. BMC Bioinformatics, 2011, 12: 78.
[14]	LANGE V, MALMSTROM JA, DIDION J, et al.Targeted quantitative analysis of streptococcus pyogenes virulence factors by multiple reaction monitoring [J]. Mol Cell Proteomics, 2008, 7(8): 1489-1500.
[15]	MARTIN D B, HOLZMAN T, MAY D, et al. MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments [J]. Mol Cell Proteomics, 2008, 7(11): 2270-2278.
[16]	卫军营, 张养军, 赵炎, 等. 质谱智能选择反应检测用于蛋白质绝对定量中母离子对确证的方法研究[J]. 分析化学, 2012, 40(1): 59-65.
[17]	SONG Y, HAO Y, SUN A, et al. Sample preparation project for the subcellular proteome of mouse liver [J]. Proteomics, 2006, 19（6）: 5269-6277.
[18]	WANG G, WU W W, ZENG W, et al. Label-free protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes [J]. J Proteome Res, 2006, 5(5): 1214-1223.
[19]	COLAERT N, VANDEKERCKHOVE J, GEVAERT K, et al. A comparison of MS²-based label-free quantitative proteomic techniques with regards to accuracy and precision [J]. Proteomics, 2011, 11(6): 1110-1113.
[20]	AMERICA A H, CORDEWENER J H, Comparative LCMS: A landscape of peaks and valleys [J]. Proteomics, 2008, 8(4): 731-749.
[21]	VALOT B, LANGELLA O, NANO E, et al. MassChroQ: A versatile tool for mass spectrometry quantification [J]. Proteomics, 2011, 11(17): 3572-3577.

Cited By

Get Citation

PDF

XML

Article views (911) PDF downloads (953)

Turn off MathJax

Article Contents

Abstract

References

A Data Processing Tool for Mass Spectrometry Data from iSRM Strategy in Proteomics

Abstract

References

Catalog

Export File

Citation

Format

Content