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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
18
pubmed:dateCreated
2007-2-19
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1615-9306
pubmed:author
pubmed:issnType
Print
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2793-801
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Stable isotope-free quantitative shotgun proteomics combined with sample pattern recognition for rapid diagnostics.
pubmed:affiliation
Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.
pubmed:publicationType
Journal Article