Literature DB >> 20078137

Quantitative analysis of proteome coverage and recovery rates for upstream fractionation methods in proteomics.

Yuan Fang1, Dale P Robinson, Leonard J Foster.   

Abstract

The proteome of any cell or even any subcellular fraction remains too complex for complete analysis by one dimension of liquid chromatography-tandem mass spectrometry (LC-MS/MS). Hence, to achieve greater depth of coverage for a proteome of interest, most groups routinely subfractionate the sample prior to LC-MS/MS so that the material entering LC-MS/MS is less complex than the original sample. Protein and/or peptide fractionation methods that biochemists have used for decades, such as strong cation exchange chromatography (SCX), isoelectric focusing (IEF) and SDS-PAGE, are the most common prefractionation methods used currently. There has, as yet, been no comprehensive, controlled evaluation of the relative merits of the various methods, although some binary comparisons have been made. Here, we compare the most popular methods for fractionating samples at both the protein and peptide level, replicating all analyses to provide estimates of the variability in the analyses and controlling precisely for instrument time dedicated to each analysis, as well as directly measuring the recovery of protein or peptide from each fractionation procedure. For maximal proteome coverage, SDS-PAGE is very clearly the most effective method tested, with more than 90% of the entire data set found. When considering the amount of material recovered after each fractionation procedure, solution-based IEF and SCX performed similarly, with approximately 80% of the input being recovered.

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Year:  2010        PMID: 20078137     DOI: 10.1021/pr901063t

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  30 in total

1.  Proteomic technologies for the discovery of type 1 diabetes biomarkers.

Authors:  Wenbo Zhi; Sharad Purohit; Colleen Carey; Meiyao Wang; Jin-Xiong She
Journal:  J Diabetes Sci Technol       Date:  2010-07-01

2.  Systematic comparison of fractionation methods for in-depth analysis of plasma proteomes.

Authors:  Zhijun Cao; Hsin-Yao Tang; Huan Wang; Qin Liu; David W Speicher
Journal:  J Proteome Res       Date:  2012-05-18       Impact factor: 4.466

3.  Quantitative assessment of in-solution digestion efficiency identifies optimal protocols for unbiased protein analysis.

Authors:  Ileana R León; Veit Schwämmle; Ole N Jensen; Richard R Sprenger
Journal:  Mol Cell Proteomics       Date:  2013-06-21       Impact factor: 5.911

4.  Baking a mass-spectrometry data PIE with McMC and simulated annealing: predicting protein post-translational modifications from integrated top-down and bottom-up data.

Authors:  Stuart R Jefferys; Morgan C Giddings
Journal:  Bioinformatics       Date:  2011-03-15       Impact factor: 6.937

5.  Monitoring a nuclear factor-κB signature of drug resistance in multiple myeloma.

Authors:  Yun Xiang; Elizabeth R Remily-Wood; Vasco Oliveira; Danielle Yarde; Lili He; Jin Q Cheng; Linda Mathews; Kelly Boucher; Christopher Cubitt; Lia Perez; Ted J Gauthier; Steven A Eschrich; Kenneth H Shain; William S Dalton; Lori Hazlehurst; John M Koomen
Journal:  Mol Cell Proteomics       Date:  2011-08-16       Impact factor: 5.911

6.  High resolution quantitative proteomics of HeLa cells protein species using stable isotope labeling with amino acids in cell culture(SILAC), two-dimensional gel electrophoresis(2DE) and nano-liquid chromatograpohy coupled to an LTQ-OrbitrapMass spectrometer.

Authors:  Bernd Thiede; Christian J Koehler; Margarita Strozynski; Achim Treumann; Robert Stein; Ursula Zimny-Arndt; Monika Schmid; Peter R Jungblut
Journal:  Mol Cell Proteomics       Date:  2012-10-01       Impact factor: 5.911

7.  Analysis of the plasma proteome in COPD: Novel low abundance proteins reflect the severity of lung remodeling.

Authors:  Salim Merali; Carlos A Barrero; Russell P Bowler; Diane Er Chen; Gerard Criner; Alan Braverman; Samuel Litwin; Anthony Yeung; Steven G Kelsen
Journal:  COPD       Date:  2013-10-10       Impact factor: 2.409

8.  Comparison of bottom-up proteomic approaches for LC-MS analysis of complex proteomes.

Authors:  Leigh A Weston; Kerry M Bauer; Amanda B Hummon
Journal:  Anal Methods       Date:  2013-09-21       Impact factor: 2.896

Review 9.  Quality assessment for clinical proteomics.

Authors:  David L Tabb
Journal:  Clin Biochem       Date:  2012-12-12       Impact factor: 3.281

10.  Accurate label-free protein quantitation with high- and low-resolution mass spectrometers.

Authors:  Jocelyn F Krey; Phillip A Wilmarth; Jung-Bum Shin; John Klimek; Nicholas E Sherman; Erin D Jeffery; Dongseok Choi; Larry L David; Peter G Barr-Gillespie
Journal:  J Proteome Res       Date:  2013-12-10       Impact factor: 4.466

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