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Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes
Author(s) -
Bindschedler L. V.,
Cramer R.
Publication year - 2011
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.4872
Subject(s) - stable isotope labeling by amino acids in cell culture , chemistry , stable isotope ratio , quantitative proteomics , isotope , isotopic labeling , mass spectrometry , proteomics , amino acid , sample preparation , software , chromatography , computational biology , biochemistry , computer science , organic chemistry , physics , quantum mechanics , biology , gene , programming language
Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample‐specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as 15 N labels the entire element content of the sample, i.e. for 15 N the entire peptide backbone in addition to all nitrogen‐containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high‐resolution MS data in quantitative proteomic analyses. Copyright © 2011 John Wiley & Sons, Ltd.