Literature DB >> 19345114

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

Jenny M Armenta1, Ina Hoeschele, Iulia M Lazar.   

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 17beta-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 approximately 60%-67% between duplicate, and approximately 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 approximately 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, approximately 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.

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Year:  2009        PMID: 19345114     DOI: 10.1016/j.jasms.2009.02.029

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  57 in total

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Journal:  Brief Funct Genomic Proteomic       Date:  2006-05-10

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Authors:  Lynn R Zieske
Journal:  J Exp Bot       Date:  2006-03-30       Impact factor: 6.992

5.  Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research.

Authors:  Sebastian Wiese; Kai A Reidegeld; Helmut E Meyer; Bettina Warscheid
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Review 6.  Proteome informatics for cancer research: from molecules to clinic.

Authors:  Vladimir Brusic; Ovidiu Marina; Catherine J Wu; Ellis L Reinherz
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

7.  Comparative study of three proteomic quantitative methods, DIGE, cICAT, and iTRAQ, using 2D gel- or LC-MALDI TOF/TOF.

Authors:  Wells W Wu; Guanghui Wang; Seung Joon Baek; Rong-Fong Shen
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8.  Quantitative proteome analysis of CD95 (Fas/Apo-1)-induced apoptosis by stable isotope labeling with amino acids in cell culture, 2-DE and MALDI-MS.

Authors:  Bernd Thiede; Annikki Kretschmer; Thomas Rudel
Journal:  Proteomics       Date:  2006-01       Impact factor: 3.984

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Authors:  Troy C Lund; Lorraine B Anderson; Valarie McCullar; Leeann Higgins; Gong H Yun; Bartek Grzywacz; Michael R Verneris; Jeffrey S Miller
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10.  Prevalidation of potential protein biomarkers in toxicology using iTRAQ reagent technology.

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Journal:  Proteomics       Date:  2007-05       Impact factor: 3.984

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  13 in total

1.  MALDI mass spectrometric imaging of cardiac tissue following myocardial infarction in a rat coronary artery ligation model.

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2.  Identification of proteins and phosphoproteins using pulsed Q collision induced dissociation (PQD).

Authors:  Wells W Wu; Guanghui Wang; Paul A Insel; Cheng-Te Hsiao; Sige Zou; Stuart Maudsley; Bronwen Martin; Rong-Fong Shen
Journal:  J Am Soc Mass Spectrom       Date:  2011-07-15       Impact factor: 3.109

3.  Discovery- and target-based protein quantification using iTRAQ and pulsed Q collision induced dissociation (PQD).

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4.  Impact of peptide modifications on the isobaric tags for relative and absolute quantitation method accuracy.

Authors:  Milagros J Tenga; Iulia M Lazar
Journal:  Anal Chem       Date:  2011-01-06       Impact factor: 6.986

5.  Fast proteomic protocol for biomarker fingerprinting in cancerous cells.

Authors:  Jenny M Armenta; Milagros Perez; Xu Yang; Danielle Shapiro; Debby Reed; Leepika Tuli; Carla V Finkielstein; Iulia M Lazar
Journal:  J Chromatogr A       Date:  2010-03-03       Impact factor: 4.759

6.  LTQ-iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments.

Authors:  Getiria Onsongo; Matthew D Stone; Susan K Van Riper; John Chilton; Baolin Wu; Leeann Higgins; Troy C Lund; John V Carlis; Timothy J Griffin
Journal:  Proteomics       Date:  2010-10       Impact factor: 3.984

7.  Quantitative plasma proteomic profiling identifies the vitamin E binding protein afamin as a potential pathogenic factor in SIV induced CNS disease.

Authors:  Gurudutt Pendyala; Sunia A Trauger; Gary Siuzdak; Howard S Fox
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8.  Quantitative nuclear proteomics identifies mTOR regulation of DNA damage response.

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9.  Effects of lycopene on protein expression in human primary prostatic epithelial cells.

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10.  Integrated Proteomic and Transcriptomic Analysis Reveals Long Noncoding RNA HOX Transcript Antisense Intergenic RNA (HOTAIR) Promotes Hepatocellular Carcinoma Cell Proliferation by Regulating Opioid Growth Factor Receptor (OGFr).

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Journal:  Mol Cell Proteomics       Date:  2017-10-27       Impact factor: 5.911

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