Literature DB >> 21594918

Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes.

L V Bindschedler1, R Cramer.   

Abstract

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.

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Year:  2011        PMID: 21594918     DOI: 10.1002/rcm.4872

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  2 in total

1.  Proteomic analysis of Artemisia annua--towards elucidating the biosynthetic pathways of the antimalarial pro-drug artemisinin.

Authors:  Laura Bryant; Brian Flatley; Chhaya Patole; Geoffrey D Brown; Rainer Cramer
Journal:  BMC Plant Biol       Date:  2015-07-09       Impact factor: 4.215

2.  Proteomic analysis of the medicinal plant Artemisia annua: Data from leaf and trichome extracts.

Authors:  Laura Bryant; Chhaya Patole; Rainer Cramer
Journal:  Data Brief       Date:  2016-02-23
  2 in total

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