ABSTRACT
An approach is described for the simultaneous identification and quantitation of oxidant-sensitive cysteine thiols in a complex protein mixture using a thiol-specific, acid-cleavable isotope-coded affinity tag (ICAT) reagent (Applied Biosystems, USA). The approach is based on the fact that only free cysteine thiols are susceptible to labeling by the iodoacetamide-based ICAT, and that mass spectrometry can be used to quantitate the relative labeling of free thiols. Applying this approach, we have identified cysteine thiols of proteins in a rabbit heart membrane fraction that are sensitive to a high concentration of hydrogen peroxide. Previously known and some novel proteins with oxidant-sensitive cysteines were identified. Of the many protein thiols labeled by the ICAT, only relatively few were oxidized more than 50% despite the high concentration of oxidant used, indicating that oxidant-sensitive thiols are relatively rare, and denoting their specificity and potential functional relevance.
Subject(s)
Affinity Labels , Cysteine/analysis , Proteins/analysis , Proteomics/methods , Animals , Carbon Isotopes , Cysteine/metabolism , Hydrogen Peroxide/metabolism , Membrane Proteins/analysis , Myocardium/chemistry , Oxidants/metabolism , Oxidation-Reduction , Proteins/metabolism , Rabbits , Sulfhydryl Compounds/analysis , Sulfhydryl Compounds/metabolismABSTRACT
A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.
