Identification and quantification of protein carbonylation using light and heavy isotope labeled Girard's P reagent

Protein carbonyls are one of the most widely studied markers of oxidative stress. Determining increases in the concentration of protein carbonyls known to be associated with neurodegenerative diseases, heart disease, cancer and ageing. Identification of carbonylation sites in oxidized proteins has been a challenge. Even though recent advances in proteomics has facilitate the identification of carbonylation sites in oxidized proteins, confident identification remains a challenge due to the complicated nature of oxidative damage and the wide range of oxidative modifications. Here, we report the development of a multiplexing strategy that facilitates confident carbonylated peptide identification through a combination of heavy and light isotope coding and a multi-step filtering process. This procedure involves (1) labeling aliquots of oxidized proteins with heavy and light forms of Girard's reagent P (GPR) and combining them in a 1:1 ratio along with (2) LC/MS and MALDI-MS/MS analysis. The filtering process uses LUMS and MALDI-MSIMS data to rule out false positives by rejecting peptide doublets that do not appear with the correct concentration ratio, retention time, tag number, or resolution. This strategy was used for the identification of heavily oxidized transferrin peptides and resulted in identification 13 distinct peptides. The competency of the method was validated in a complex mixture using oxidized transferrin in a yeast lysate as well as oxidized yeast. Twenty-five percent of the peptides identified in a pure oxidized sample of transferrin were successfully identified from the complex mixture. Analysis of yeast proteome stressed with hydrogen peroxide using this multiplexing strategy resulted in identification of 41 carbonylated peptides from 36 distinct proteins. Differential isotope coding of model peptides at different concentrations followed by mixing at different ratios was used to establish the linear dynamic range for quantification of carbonylated peptides using light and heavy forms of GPR. (c) 2006 Elsevier B.V. All rights reserved.