Literature DB >> 17305241

Stable isotope-free quantitative shotgun proteomics combined with sample pattern recognition for rapid diagnostics.

Stefanie Wienkoop1, Estibaliz Larrainzar, Michaela Niemann, Esther M Gonzalez, Ute Lehmann, Wolfram Weckwerth.   

Abstract

Mass spectrometry (MS) has become a powerful tool for the quantitative analysis of complex protein samples. A high-throughput strategy for the comparative analysis of multiple protein samples with high complexity becomes more and more important. Two strategies, spectral count and peak intensity, for label-free MS analysis of prefractionated complex mixtures have been described recently to be useful for quantitation. Here we compare both strategies for rapid and quantitative 1-D shotgun LC/MS/MS analyses of highly complex protein mixtures using silica-based monolithic columns. First, we validated linearity and sensitivity of these methods by spiking varying amounts of an internal standard protein in a complex plant protein extract. Secondly, quantitative data of proteins of Medicago truncatula nodules were visualized with independent components analysis using data either obtained from spectral count or peak integration performed with commercial software. Spectral count showed apparent advantages over peak integration because several peptides per protein are automatically averaged, the linear dynamic range of quantitation increases in complex matrices and the number of quantified proteins surpasses the number of proteins using peak integration. Thus, for the need of rapid comparative analysis of highly complex protein samples, spectral count enables sample pattern recognition and identification of biomarkers in nongel based proteomic studies.

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Year:  2006        PMID: 17305241     DOI: 10.1002/jssc.200600290

Source DB:  PubMed          Journal:  J Sep Sci        ISSN: 1615-9306            Impact factor:   3.645


  14 in total

1.  Comparative proteomic analysis of non-small-cell lung cancer and normal controls using serum label-free quantitative shotgun technology.

Authors:  Jun Pan; Hai-Quan Chen; Yi-Hua Sun; Jun-Hua Zhang; Xiao-Yang Luo
Journal:  Lung       Date:  2008-05-09       Impact factor: 2.584

2.  Differential expression of extracellular matrix proteins in senescent and young human fibroblasts: a comparative proteomics and microarray study.

Authors:  Kyeong Eun Yang; Joseph Kwon; Ji-Heon Rhim; Jong Soon Choi; Seung Il Kim; Seung-Hoon Lee; Junsoo Park; Ik-Soon Jang
Journal:  Mol Cells       Date:  2011-05-11       Impact factor: 5.034

3.  Systemic cold stress adaptation of Chlamydomonas reinhardtii.

Authors:  Luis Valledor; Takeshi Furuhashi; Anne-Mette Hanak; Wolfram Weckwerth
Journal:  Mol Cell Proteomics       Date:  2013-04-05       Impact factor: 5.911

4.  Medicago truncatula root nodule proteome analysis reveals differential plant and bacteroid responses to drought stress.

Authors:  Estíbaliz Larrainzar; Stefanie Wienkoop; Wolfram Weckwerth; Rubén Ladrera; Cesar Arrese-Igor; Esther M González
Journal:  Plant Physiol       Date:  2007-06-01       Impact factor: 8.340

5.  Functional proteomics of barley and barley chloroplasts - strategies, methods and perspectives.

Authors:  Jørgen Petersen; Adelina Rogowska-Wrzesinska; Ole N Jensen
Journal:  Front Plant Sci       Date:  2013-03-18       Impact factor: 5.753

6.  Gel-based and gel-free quantitative proteomics approaches at a glance.

Authors:  Cosette Abdallah; Eliane Dumas-Gaudot; Jenny Renaut; Kjell Sergeant
Journal:  Int J Plant Genomics       Date:  2012-11-20

7.  ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites.

Authors:  Jan Hummel; Michaela Niemann; Stefanie Wienkoop; Waltraud Schulze; Dirk Steinhauser; Joachim Selbig; Dirk Walther; Wolfram Weckwerth
Journal:  BMC Bioinformatics       Date:  2007-06-23       Impact factor: 3.169

8.  Comparative proteomics reveal characteristics of life-history transitions in a social insect.

Authors:  Florian Wolschin; Gro V Amdam
Journal:  Proteome Sci       Date:  2007-07-17       Impact factor: 2.480

9.  Quantifying raft proteins in neonatal mouse brain by 'tube-gel' protein digestion label-free shotgun proteomics.

Authors:  Hongwei Yu; Bassam Wakim; Man Li; Brian Halligan; G Stephen Tint; Shailendra B Patel
Journal:  Proteome Sci       Date:  2007-09-24       Impact factor: 2.480

10.  Integration of metabolomic and proteomic phenotypes: analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.

Authors:  Stefanie Wienkoop; Katja Morgenthal; Florian Wolschin; Matthias Scholz; Joachim Selbig; Wolfram Weckwerth
Journal:  Mol Cell Proteomics       Date:  2008-04-28       Impact factor: 5.911

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