Abstract

Because of its versatile chemical properties, the amino acid cysteine plays a variety of vital roles in proteins. It can form structure-stabilizing elements (e.g., disulfide bonds), coordinate metal cofactors and is part of the catalytic center of many enzymes. Recently, a new role has been discovered for cysteine: so-called redox-sensitive proteins use the thiol group of cysteine as a specific sensor for Reactive Oxygen Species (ROS) and Reactive Nitrogen Species (RNS). The oxidation of such a redox-active cysteine, e.g., under conditions of elevated cellular ROS or RNS levels (oxidative or nitrosative stress), often results in a reversible thiol modification. This, in turn, might lead to structural changes and altered protein activity. When the oxidative stress subsides, cellular antioxidant systems, including thioredoxin and glutathione can reduce the redox-active cysteine and restore the original structure and activity of the redox-sensitive protein. This makes oxidative thiol modifications an attractive mechanism for cellular redox sensing and signaling.To study the target cysteines of oxidative and nitrosative stress and to quantify the extent of the thiol modifications generated under these conditions, we have recently developed a thiol trapping technique using isotope coded affinity tag (ICAT) chemistry (1). With this method, reduced cysteines are selectively labeled with the isotopically light form of ICAT and oxidized cysteines with the isotopically heavy form of ICAT. Thus we could globally quantify the ratio of reduced and oxidized cysteines in cellular proteins based on the modified peptide masses. Here, we present an expansion of this method, which we term NOxICAT, because it uses ICAT chemistry to detect changes in thiol modifications of proteins upon Nitrosative and Oxidative stress. The NOxICAT-method is a highly specific and quantitative method to study the global changes in the thiol redox state of cellular proteins under a variety of physiological and pathological stress conditions.

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