Identification of redox-sensitive cysteines in the arabidopsis proteome using OxiTRAQ, a quantitative redox proteomics method
KAUST DepartmentBioscience Core Lab
Online Publication Date2014-01-28
Print Publication Date2014-03
Permanent link to this recordhttp://hdl.handle.net/10754/563356
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AbstractCellular redox status plays a key role in mediating various physiological and developmental processes often through modulating activities of redox-sensitive proteins. Various stresses trigger over-production of reactive oxygen/nitrogen species which lead to oxidative modifications of redox-sensitive proteins. Identification and characterization of redox-sensitive proteins are important steps toward understanding molecular mechanisms of stress responses. Here, we report a high-throughput quantitative proteomic approach termed OxiTRAQ for identifying proteins whose thiols undergo reversible oxidative modifications in Arabidopsis cells subjected to oxidative stress. In this approach, a biotinylated thiol-reactive reagent is used for differential labeling of reduced and oxidized thiols. The biotin-tagged peptides are affinity purified, labeled with iTRAQ reagents, and analyzed using a paralleled HCD-CID fragmentation mode in an LTQ-Orbitrap. With this approach, we identified 195 cysteine-containing peptides from 179 proteins whose thiols underwent oxidative modifications in Arabidopsis cells following the treatment with hydrogen peroxide. A majority of those redox-sensitive proteins, including several transcription factors, were not identified by previous redox proteomics studies. This approach allows identification of the specific redox-regulated cysteine residues, and offers an effective tool for elucidation of redox proteomes. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
CitationLiu, P., Zhang, H., Wang, H., & Xia, Y. (2014). Identification of redox-sensitive cysteines in the Arabidopsis proteome using OxiTRAQ, a quantitative redox proteomics method. PROTEOMICS, 14(6), 750–762. doi:10.1002/pmic.201300307
SponsorsThis work was supported by Research Grants Council of Hong Kong (grant nos. HKBU1/CRF/10 and HKBU261910 to Y.X.) and by HKBU Strategic Development Fund (to Y.X.).
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