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now widely accepted that mRNA levels do not always correlate with
translated protein amounts, due to posttranscriptional processing
and miRNA repression (
24, 25
). In addition, transcript expression
data can sometimes be misleading because it does not consider
protein localization within subcellular compartments. For these
reasons, proteomics emerges as a tool to substantiate expression at
the protein level, shed new light on underlying EMT mechanisms,
and reveal novel EMT effectors. In this regard, several studies
have recently adopted a proteomic strategy to gain insights into the
cellular process (for a review see ref.
26
).
The majority of proteomic EMT studies to date have imple-
mented a classical approach, coupling two-dimensional gel electro-
phoresis (2DE) and mass spectrometry (MS) to identify proteins in
the cell lysate that are differentially expressed (
26
). These studies
have provided useful protein identifi cation and regulatory informa-
tion, but generally on the most abundant proteins in the sample—
e.g., vimentin (
27, 28
). This may result from the limited sample
capacity and detection sensitivity of the 2DE technique (dynamic
range of protein separation is typically between 10
4
and 10
5
(
29
)),
or the absence of sample pre-fractionation for sub-proteome anal-
ysis. In addition, a major limitation of comparative 2DE analysis is
the high degree of gel-to-gel variation in spot patterns, which
makes it hard to distinguish any true biological variation from
experimental variation (
30
). A signifi cant advancement in 2DE
analysis and reproducibility was made by Unlu et al., who multi-
plexed samples labeled with fl uorescently resolvable dyes (CyDyes)
within the same 2D gel (
31
). This approach known as two-
dimensional fl uorescence difference gel electrophoresis (DIGE)
has several advantages over 2DE (
32, 33
). These include (1) the
use of fl uorescent labels that render DIGE much more quantitative
than the standard calorimetric staining methods, both with regard
to sensitivity, as less sample is required, and linearity, (2) minimizing
gel-to-gel variation as multiple DIGE samples are multiplexed on
the same gel, and (3) the use of an internal standard that normalizes
protein abundance measurements across multiple gels and provides
confi dence that differences in spot intensities are purely attributed
to biological and not experimental variation.
The DIGE workfl ow (see Fig.
1
) consists of protein extracts
being covalently tagged with spectrally resolvable fl uorescent
N
-hydroxysuccinimide derivative dyes via nucleophilic substitution
reactions between the fl uorophore and the
-amino group of lysine
residues, forming an amide (
30
). Usually, a minimal labeling strat-
egy is implemented where 1-2% of all lysines are labeled to avoid
large changes in mass and avoid compromising protein solubility
(
34
). Typically, two protein samples to be compared are labeled
with either Cy3 or Cy5 dye, while a third pooled sample contain-
ing equal amounts of all samples in the experiment is labeled with
Cy2 to serve as an internal standard (
35
). All labeled samples are
ε
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