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other characterization approaches. Historically, quantitative analyses
at the proteome level were performed by two-dimensional poly-
acrylamide gel electrophoresis (2D-PAGE) and by the visual, com-
puter-aided comparison between the protein spot pattern of
mutant and wild-type plant material [
1
]. Because 2D-PAGE based
on isoelectric focusing (IEF) is technically demanding, restricted
to soluble proteins, and, depending on the choice of the staining,
quite expensive, alternative approaches that rely on mass spectrom-
etry for peptide or protein quantification were developed [
2
].
Among the different methods that exist, the linear positive correla-
tion between the number of spectra that identify a protein and
protein abundance has attracted considerable attention for quanti-
fication purposes [
3
]. Different flavors of the so-called spectral
counting methods were reported and the most advanced methods
use sophisticated normalization strategies that take into account
physicochemical features of peptides and their probability of being
detected in a complex protein mixture [
4
].
For several reasons,
Arabidopsis thaliana
is excellently suited
for large-scale proteome characterization because of its small
genome size with well-annotated genes and few sequencing errors.
Furthermore, it is prone to genetic manipulations and connects a
strong and devoted research community that is willing to share
tools and knowledge (see
www.arabidopsis.org
)
. Last but not least,
the community can utilize information from many organellar pro-
teome studies such that for many proteins their subcellular local-
ization is known. Based on the latter efforts, organellar proteome
maps were built that allow performing proteome analyses at the
level of the entire cell. Characteristics of organellar proteomes are
then inferred by assigning identified proteins to cell organelles
a
posteriori
, i.e., after the experiment. Since the study of dynamic
proteome changes is incompatible with lengthy organelle isolation
procedures, this approach is preferred to study dynamic quantita-
tive changes in protein abundance or status of posttranslational
modification in response to a signal. Examples of successful pro-
teome characterizations include studies on the plastid protein
import mutant
ppi2
[
5
], the
ALLENE OXIDE SYNTHASE
(
aos
)
mutant [
6
], the
clp
protease mutants [
7
], and the analysis of kinase
targets by phosphoproteome profiling [
8
].
We report here a simple experimental workflow for the charac-
terization of a mutation at the proteome level using protein extracts
from
Arabidopsis thaliana
root and leaf (Fig.
1
). Our quantifica-
tion approach relies on normalized spectral counting (nSpC) and
is therefore restricted to fast scanning trap instruments that acquire
peptide-centric data at high temporal resolution. While higher data
quality and deeper proteome coverage can be obtained with
Orbitrap- or FTICR-instruments, the workflow reported here is
similarly suitable for an LTQ ion trap. The downside of using the
