Literature DB >> 15924362

A comparison of the consistency of proteome quantitation using two-dimensional electrophoresis and shotgun isobaric tagging in Escherichia coli cells.

Leila H Choe1, Kunal Aggarwal, Zsofia Franck, Kelvin H Lee.   

Abstract

An important consideration in the measurement of quantitative changes in protein expression is the consistency of the observations for a given technique as well as the reproducibility of the experiment. A quantitative assessment of the technical and biological variability is crucial to avoid erroneous inferences and conclusions. Two methods for measuring quantitative changes in protein expression are two-dimensional electrophoresis (2-DE) and shotgun proteomics of isobaric-tagged samples using iTRAQ reagents. An assessment of changes in Escherichia coli protein expression in response to rhsA induction demonstrates that half of the quantified protein expression ratios have a coefficent of variation (CV) less than 0.31 using 2-DE and less than 0.24 using isobaric tags; whereas 95% of the quantified protein expression ratios have a CV less than 0.81 using 2-DE and less than 0.53 using isobaric tags. The selective removal of outlier data points from the shotgun method using Grubb's and Rosner's statistical outlier tests improves the consistency of the quantitation data obtained.

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Year:  2005        PMID: 15924362     DOI: 10.1002/elps.200410336

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  31 in total

1.  Data-independent proteomic screen identifies novel tamoxifen agonist that mediates drug resistance.

Authors:  Shawna Mae Hengel; Euan Murray; Simon Langdon; Larry Hayward; Jean O'Donoghue; Alexandre Panchaud; Ted Hupp; David R Goodlett
Journal:  J Proteome Res       Date:  2011-09-21       Impact factor: 4.466

2.  Quantitative proteomic analyses of influenza virus-infected cultured human lung cells.

Authors:  Kevin M Coombs; Alicia Berard; Wanhong Xu; Oleg Krokhin; Xiaobo Meng; John P Cortens; Darwyn Kobasa; John Wilkins; Earl G Brown
Journal:  J Virol       Date:  2010-08-11       Impact factor: 5.103

3.  Addressing accuracy and precision issues in iTRAQ quantitation.

Authors:  Natasha A Karp; Wolfgang Huber; Pawel G Sadowski; Philip D Charles; Svenja V Hester; Kathryn S Lilley
Journal:  Mol Cell Proteomics       Date:  2010-04-10       Impact factor: 5.911

Review 4.  Proteomic approaches to dissect platelet function: Half the story.

Authors:  Dmitri V Gnatenko; Peter L Perrotta; Wadie F Bahou
Journal:  Blood       Date:  2006-08-22       Impact factor: 22.113

Review 5.  Proteomics of the peroxisome.

Authors:  R A Saleem; J J Smith; J D Aitchison
Journal:  Biochim Biophys Acta       Date:  2006-09-12

6.  Quantitative proteomics in plants: choices in abundance.

Authors:  Jay J Thelen; Scott C Peck
Journal:  Plant Cell       Date:  2007-11-30       Impact factor: 11.277

7.  Proteomics analysis of epithelial cells reprogrammed in cell-free extract.

Authors:  Emma Pewsey; Christine Bruce; A Stephen Georgiou; Mark Jones; Duncan Baker; Saw Yen Ow; Phillip C Wright; Christel K Freberg; Philippe Collas; Alireza Fazeli
Journal:  Mol Cell Proteomics       Date:  2009-02-27       Impact factor: 5.911

8.  Time series proteome profiling to study endoplasmic reticulum stress response.

Authors:  Michelle Mintz; Adeline Vanderver; Kristy J Brown; Joseph Lin; Zuyi Wang; Christine Kaneski; Raphael Schiffmann; Kanneboyina Nagaraju; Eric P Hoffman; Yetrib Hathout
Journal:  J Proteome Res       Date:  2008-04-25       Impact factor: 4.466

9.  Protein extraction and 2-DE of water- and lipid-soluble proteins from bovine pericardium, a low-cellularity tissue.

Authors:  Leigh G Griffiths; Leila Choe; Kelvin H Lee; Kenneth F Reardon; E Christopher Orton
Journal:  Electrophoresis       Date:  2008-11       Impact factor: 3.535

10.  Matching isotopic distributions from metabolically labeled samples.

Authors:  Sean McIlwain; David Page; Edward L Huttlin; Michael R Sussman
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

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