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Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology

  • Jenny M. Armenta
  • Ina Hoeschele
  • Iulia M. LazarEmail author
Article

Abstract

An isotope tags for relative and absolute quantitation (iTRAQ)-based reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) method was developed for differential protein expression profiling in complex cellular extracts. The estrogen positive MCF-7 cell line, cultured in the presence of 17β-estradiol (E2) and tamoxifen (Tam), was used as a model system. MS analysis was performed with a linear trap quadrupole (LTQ) instrument operated by using pulsed Q dissociation (PQD) detection. Optimization experiments were conducted to maximize the iTRAQ labeling efficiency and the number of quantified proteins. MS data filtering criteria were chosen to result in a false positive identification rate of <4%. The reproducibility of protein identifications was ∼60%–67% between duplicate, and ∼50% among triplicate LC-MS/MS runs, respectively. The run-to-run reproducibility, in terms of relative standard deviations (RSD) of global mean iTRAQ ratios, was better than 10%. The quantitation accuracy improved with the number of peptides used for protein identification. From a total of 530 identified proteins (P < 0.001) in the E2/Tam treated MCF-7 cells, a list of 255 proteins (quantified by at least two peptides) was generated for differential expression analysis. A method was developed for the selection, normalization, and statistical evaluation of such datasets. An approximate ∼2-fold change in protein expression levels was necessary for a protein to be selected as a biomarker candidate. According to this data processing strategy, ∼16 proteins involved in biological processes such as apoptosis, RNA processing/metabolism, DNA replication/transcription/repair, cell proliferation and metastasis, were found to be up- or down-regulated.

Keywords

Tandem Mass Spectrum Relative Standard Deviation iTRAQ Reagent iTRAQ Ratio Linear Trap Quadrupole 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

13361_2011_200701287_MOESM1_ESM.doc (106 kb)
Supplementary material, approximately 109 KB.

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Copyright information

© American Society for Mass Spectrometry 2009

Authors and Affiliations

  • Jenny M. Armenta
    • 1
  • Ina Hoeschele
    • 1
    • 2
  • Iulia M. Lazar
    • 1
    • 3
    Email author
  1. 1.Virginia Bioinformatics InstituteVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  2. 2.Department of StatisticsVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  3. 3.Department of Biological SciencesVirginia Polytechnic Institute and State UniversityBlacksburgUSA

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