Biology Reference
In-Depth Information
Chapter 8
Proteomic Analysis of Redox-Dependent Changes
Using Cysteine-Labeling 2D DIGE
Hong-Lin Chan , John Sinclair , and John F. Timms
Abstract
Redox-modifi cation of proteins plays an important role in the regulation of protein function and cellular
physiology and in pathological conditions such as oncogenic activation, inhibition of tumor suppression,
and ischemia reperfusion injury. This occurs, at least in part, through the reduction or oxidation of cysteine
groups in these proteins resulting in the modulation of their activities. Herein, we focus on the development
of a pair of cysteine-labeling iodoacetylated cyanine dyes (ICy3/5) for two-dimensional difference gel
electrophoresis (2D DIGE) to monitor redox-dependent changes on cysteine residues. The method is
applied to a cellular model of human mammary luminal epithelial cells treated with H
2
O
2
to induce oxidative
stress. Differences in labeling are caused either by differential protein expression or from the loss or gain
of reactive thiol groups of cysteines in response to oxidative stress. Proteins displaying differential labeling
would then be picked for MS-based identifi cation. In summary, this cysteine-labeling 2D-DIGE approach
provides an MS-compatible and reproducible technique for identifying alterations in the expression and
redox-modifi cation of free thiol-containing proteins.
Key words:
Thiol-reactive cyanine dyes, Two-dimensional difference gel electrophoresis, Redox
proteomics, Mass spectrometry
1. Introduction
Two-dimensional gel electrophoresis (2DE) is one of the most
widely used proteomic separation methods and has been employed
for the analysis of differential protein expression in many different
biological sample types (
1, 2
). However, as most users realize, 2DE
and the methods commonly used for in-gel protein visualization
are inherently variable and many replicate gels must be run before
signifi cant differences in protein expression can be ascribed with
accuracy. Moreover, these protein visualization methods often have
narrow linear dynamic ranges of detection, making them unsuit-
able for the analysis of biological samples where protein copy
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