Literature DB >> 20968308

Comparison of strong cation exchange and SDS-PAGE fractionation for analysis of multiprotein complexes.

Sudipto Das1, Allen D Bosley, Xiaoying Ye, King C Chan, Isabel Chu, Jeffery E Green, Haleem J Issaq, Timothy D Veenstra, Thorkell Andresson.   

Abstract

Affinity purification of protein complexes followed by identification using liquid chromatography/mass spectrometry (LC-MS/MS) is a robust method to study the fundamental process of protein interaction. Although affinity isolation reduces the complexity of the sample, fractionation prior to LC-MS/MS analysis is still necessary to maximize protein coverage. In this study, we compared the protein coverage obtained via LC-MS/MS analysis of protein complexes prefractionated using two commonly employed methods, SDS-PAGE and strong cation exchange chromatography (SCX). The two complexes analyzed focused on the nuclear proteins Bmi-1 and GATA3 that were expressed within the cells at low and high levels, respectively. Prefractionation of the complexes at the peptide level using SCX consistently resulted in the identification of approximately 3-fold more proteins compared to separation at the protein level using SDS-PAGE. The increase in the number of identified proteins was especially pronounced for the Bmi-1 complex, where the target protein was expressed at a low level. The data show that prefractionation of affinity isolated protein complexes using SCX prior to LC-MS/MS analysis significantly increases the number of identified proteins and individual protein coverage, particularly for target proteins expressed at low levels.

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Year:  2010        PMID: 20968308      PMCID: PMC3707127          DOI: 10.1021/pr100843x

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


  19 in total

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

Authors:  Yuan Fang; Dale P Robinson; Leonard J Foster
Journal:  J Proteome Res       Date:  2010-04-05       Impact factor: 4.466

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Journal:  PLoS Comput Biol       Date:  2007-03-30       Impact factor: 4.475

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