Post on 26-Jan-2023
Global relative and absolute quantitation in microbial proteomicsAndreas Otto, Jorg Bernhardt, Michael Hecker and Dorte Becher
Available online at www.sciencedirect.com
Proteomic studies are designed to yield either qualitative
information on proteins (identification, distribution,
posttranslational modifications, interactions, structure and
function) or quantitative information (abundance, distribution
within different localizations, temporal changes in abundance
due to synthesis and degradation or both). To this end these
studies can draw upon a wide range of qualitative and
quantitative gel-based and gel-free techniques. This review
summarizes current proteomic workflows for global relative or
absolute protein quantitation and their application in microbial
physiology.
Address
Institute for Microbiology, Ernst Moritz Arndt University Greifswald,
F.-L.-Jahn-Strasse 15, 17487 Greifswald, Germany
Corresponding author: Becher, Dorte (dbecher@uni-greifswald.de)
Current Opinion in Microbiology 2012, 15:364–372
This review comes from a themed issue on Microbial proteomics
Edited by Bertrand Seraphin and Robert Hettich
For a complete overview see the Issue and the Editorial
Available online 21st March 2012
1369-5274/$ – see front matter, # 2012 Elsevier Ltd. All rights
reserved.
http://dx.doi.org/10.1016/j.mib.2012.02.005
IntroductionTo meet the demand of life sciences to monitor and to
understand cellular processes, -omics techniques have
evolved into elaborate and powerful tools for elucidating
regulatory processes on different cellular levels. In this
respect proteomics is particularly important, since it
focuses on proteins as the ‘workhorses of life’.
Modern proteomic techniques aim at obtaining a com-
prehensive description of the protein inventory of a cell
and at following changes in protein levels either on a
relative or on an absolute basis, enabling the scientist to
resolve processes of life in depth as well as at a global scale
at the same time. Whilst relative proteomic studies com-
pare, for example, different cell states, strains or (sub)
cellular localizations to elucidate relative changes in the
samples under investigation, absolute proteome studies
are more focused on the determination of absolute protein
levels of, for example, single metabolic pathways, ideally
comprising all detectable proteins in a complete sample.
Consequently, the analysis of protein composition and
its changes greatly facilitates the characterization of
Current Opinion in Microbiology 2012, 15:364–372
regulatory pathways and metabolic responses to external
and internal stimuli.
In fulfilling its goals, large-scale proteomics is principally
subject to a range of general requirements or limiting
factors. Most experiments are today designed to simul-
taneously identify and quantify large numbers of proteins
to delineate subgroups of significantly changing proteins.
Therefore, pitfalls are found predominantly with respect
to the number and comprehensiveness of identified/
quantified proteins at a given sample/condition, sample
complexity that has to be resolved with the pursued
proteomics approach, the type of quantification approach
(and therefore sample preparation) and quality assess-
ment of data/statistical evaluation. Furthermore, the bio-
logical questions have to match the technical aspects of
the selected proteomics approach [1].
The aim of this review is to highlight concepts and
workflows applied in current large-scale gel-based and
gel-free quantitative studies in the field of microbial
proteomics to elucidate global regulatory events.
Two-dimensional gel electrophoresisThe success of proteomics as a distinct and important
area in life sciences was closely related to the invention
of 2DE [2]. 2DE is an orthogonal separation technique
that resolves protein species from a complex mixture
according to their pI and molecular weight. Proteins
separated on 2D gels are visualized, for example, by
staining, identified on the basis of MALDI-MS and
compared in silico by differential gel image analysis.
The collected relative quantitative information reflects
differences related to the specific experimental setup,
for example, comparisons between stressed and non-
stressed cells, different time points or different mutants
of the same organism [3,4]. Gel-based proteomics is to
date unparalleled in terms of resolution of complex
protein mixtures. Moreover, differential protein expres-
sion and changes due to, for example, PTM of proteins
are directly made visible either by comparison of differ-
ent 2D gel images by appropriate software or by soph-
isticated methods like DIGE allowing multiplexed
analyses on a single 2D gel (Table 1). The combination
of resolving power on protein level with analytical
specificity of highly sensitive and accurate MALDI
TOF-TOF mass spectrometry even uncovers cases of
multiple proteins found in the same spot on a 2D gel,
thus avoiding false quantification values, and is able to
detect PTMs of specific protein species not otherwise
distinguishable on peptide level (e.g. methylation or
acetylation).
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365
Table 1
Quantitation strategies used in microbial large-scale proteomics studies.
Dynamic
range
Basis of
quantitation
Type of
quantitation
approach
Multiplexing Type of
information
used for
quantification
Level of
quantitative
information
Advantages Disadvantages
Gel-based
2D gels
(classical)
Up to 4
orders of
magnitude
Differential image
analysis
Relative/
absoluteaNot limited/
inter-gel
comparison
Signal intensity/
staining
Protein Quantitation on
protein level
Limited in pI
range/hydrophobicity
2D gels (DIGE) Up to 4
orders of
magnitude
Differential image
analysis of different
imaging channels
of the same gel
Relative 3 Signal intensity/
staining
Protein Quantitation on
protein level
samples to be
compared run
on the same gel
Limited in pI
range/hydrophobicity
Gel-free/mass spectrometry-based chemical labeling
iTRAQ, TMT 2 Isobaric mass tags Relative 2–8 MS/MS Protein/
peptide
Multiplexing up
to 8 samples
Late introduction of
label; highly
reproducible sample
processing required
Metabolic labeling
SILAC 1–2 Heavy labeling of
alkaline amino acids
in organisms/cell
cultures
Relative 2–3 MS Peptide Excellent method
for determination
of small changes
in protein amount;
suited for subcellular
fractionation due to
early introduction
of label
Auxotrophy required
15N labeling 1–2 Labeling of complete
organisms with heavy
nitrogen/cell cultures
Relative 2 MS Peptide Excellent method
for determination
of small changes
in protein amount;
suited for subcellular
fractionation due to
early introduction
of label
Variable mass
changes depending
on primary sequence
of the peptide
Spiked-in peptides
AQUA 2 Comparison of artificial,
heavy peptides to
endogenous proteotypic
peptides
Relative/
absolute
Not limited MS Peptide Highly accurate;
very sensitive if used
with QQQ mass
spectrometers
Expensive; targeted
analysis of only a
subset of proteins/
peptides
Label free quantitation
Hi3 absolute
quantitation
3–4
(with MSE
acqusitionb)
Signal intensity of the
three most abundant
peptides of each
protein
Relative/
absolute
Not limited;
inter-run
comparison
MS Peptide Determination of
absolute quantitative
protein data for large
scale proteomics
experiments
Sample processing
steps and digestion/
recovery efficiency
must be determined
and kept constant
ww
w.s
cie
nced
irect.c
om
C
urre
nt
Op
inio
n in
Mic
rob
iolo
gy
2012,
15:3
64
–372
366 Microbial proteomics
Ta
ble
1(C
ontinued
)
Dynam
ic
rang
e
Basis
of
quantita
tio
n
Typ
eo
f
quantita
tio
n
ap
pro
ach
Multip
lexin
gT
yp
eo
f
info
rmatio
n
used
for
quantificatio
n
Levelo
f
quantita
tive
info
rmatio
n
Ad
vanta
ges
Dis
ad
vanta
ges
Pep
tid
eco
rrela
tio
n
pro
filin
g
3C
om
pariso
no
f
extr
acte
dio
nin
tensitie
s
over
diffe
rent
sam
ple
s
Rela
tive/
ab
so
lute
cN
ot
limited
;
inte
r-ru
n
co
mp
ariso
n
MS
Pep
tid
eN
oin
tro
ductio
no
f
lab
elre
quired
Hig
hly
rep
rod
ucib
le
sam
ple
pro
cessin
g
req
uired
aS
ee
Ref
[41��
].b
See
Ref
[42].
cS
ee
Ref
[37].
Current Opinion in Microbiology 2012, 15:364–372
For instance, concurrent mapping of the main vegetative
metabolic pathways at a glance was achieved for the
quantitative profiling of PTM in a study on S-Bacillithio-
lation in Bacillus subtilis elucidating intracellular regulat-
ory processes caused by hypochloric acid [5].
Additionally, protein synthesis and stability can be
examined by using 2DE in combination with radioactive
pulse chase labeling as performed in a study on long-term
glucose starvation in Staphylococcus aureus COL [6]. This
study illustrates the high versatility of 2DE as substan-
tiated by the powerful concurrent visualization and
characterization of changes in the main metabolic routes.
2DE proteomics data were successfully collated into a
database (Protecs) supporting the analysis of complex
biological questions. The database allowed comprehen-
sive analyses of preexisting and newly generated data on
anaerobiosis of S. aureus with statistical tools resulting in
the classification of exogenous stimuli previously sup-
posed to be unrelated into discrete groups with similar
physiological response patterns [7]. A related approach
was used in expression pattern analyses to determine the
targets of antimicrobial agents [8�].
Limitations of the classical 2D gel electrophoresis relat-
ing to issues on the reproducibility between gels are
overcome by the use of the DIGE technology. In a study
on ClpP-mediated proteolysis in S. aureus, DIGE was
used to discern the differences between three mutants on
a single gel revealing the importance of ClpP for phage
regulatory switches in the system under investigation [9].
In general, the application of gel-based DIGE workflows
in studies comparing closely related organisms on protein
level is extremely useful: in contrast to peptide-centered
shot-gun proteomics, small differences in protein primary
sequences of homologous proteins do not have a major
effect on the protein patterns on a 2D gel.
Despite other mass spectrometry-based technologies that
emerged with the technological progress of electrospray
instrumentation, 2DE in combination with MALDI-MS
still remains a pivotal methodology in proteomics that can
be routinely applied for parallel quantitative expression
profiling even by laboratories not associated to large
proteomics core facilities [3,10].
Gel-free proteomicsDuring the last decade, the preponderance of gel-cen-
tered analyses in proteomics has rapidly changed: gel-
free mass spectrometry-based proteomic methods have
revolutionized the whole field in terms of comprehen-
siveness, sensitivity and versatility. They enabled and
significantly improved the analysis of proteins previously
excluded from detection owing to their physico-chemical
properties.
A huge variety of methods exists, depending on the type
of mass analyzer and quantitation approach. In general, a
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Quantitative analysis and regulation Otto et al. 367
typical workflow in gel-free proteomics involves the
enzymatic digest of a complex protein mixture into pep-
tides that are further analyzed by ESI-LC–MS/MS. After
the determination of exact peptide masses, primary struc-
ture information is computed by analyzing the fragment
spectra obtained in the LC–MS/MS run. Subsequently,
the peptide identification data are processed into protein
identification data, and possible post-translational modi-
fications are annotated [11].
Proteomic analyses have in common that they suffer from
a limited resolution in the dynamic range as compared to
the range of abundance and number of protein species in
the samples. To overcome this limitation, global proteo-
mic studies almost exclusively rely on fractionation,
either conducted at subcellular, protein or peptide level,
although this constraint may be abolished in the future
[12��,13�].
Gel-free quantitation methods in global proteomic stu-
dies are subdivided into targeted methods that are used
for absolute quantitation and methods that include a
differential mass tag that is introduced either chemically,
enzymatically or metabolically [14]. Furthermore, a
rapidly growing group of relative and absolute quanti-
tation methods rely on label-free techniques. These
workflows imply a direct comparison of LC–MS/MS
datasets incorporating the signal intensities of the LC
peaks rather than comparisons of artificially introduced
isotope labels.
Because of the wide range of different methods a detailed
description is out of the scope of this review. Here, we
focus on exemplary studies of global microbial quantitat-
ive proteomics and refer to excellent reviews given else-
where.
Global relative quantitative gel-free proteomicstudiesGlobal studies in microbial proteomics yield information
that has not been available before: having looked at only
small aspects of the physiology of an organism, single
complexes and pathways or single cell states, proteomics
researchers are now put in the position to survey the
overall metabolic state(s) of the organism under the given
conditions from a ‘bird’s view’ and then to zoom in on the
molecular level in the areas of interest.
Metabolic labeling (Table 1) for quantitative gel-free
proteomic analyses of the model organism B. subtiliswas implemented as early as 2004 [15] and applied to
proteome investigations for various topics [16]. Two
global approaches for this gram-positive bacterium were
published in 2010 covering 1928 and 2142 proteins,
respectively [17,18�]. The first by Soufi et al. employed
SILAC to relatively quantify changes of protein abun-
dance between two physiological conditions and to
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simultaneously detect and quantify the dynamics in ser-
ine, threonine and tyrosine phosphorylation on a global
scale. The authors broadly confirmed previous gel-based
data and gained novel insights into the basic physiology
and changes in the kinome of phosphate-starved and
glucose-starved cells [17]. The second study comprises
conjoined transcriptome and proteome analyses to
describe global changes in glucose-starved B. subtilis cells
[18�]. Comprehensive proteomics data were obtained for
four different subcellular localizations including the ana-
lytically challenging membrane proteome. Altered levels
of gene expression and changes in protein amount were
traced over five time points. Time-dependent data were
visualized by Voronoi treemaps (Figure 1). It could be
inferred that degradation of ribosomes is a main source of
building blocks and energy in stationary phase cells.
Specific degradation of distinct components of metabolic
pathways as well as the unambiguous spatial localization
of a substantial fraction of the proteome could be deter-
mined. The proteome and transcriptome data from grow-
ing cells correlated, whereas in non-growing cells proteins
were still present but not synthesized any more [19�]. The
authors of the large-scale study on differences between
the aerobic and anaerobic lifestyle of Thermoplasma acid-ophilum explained discrepancies between proteome and
transcriptome data by extensive posttranscriptional regu-
latory mechanisms [20]. Conclusively, concurrent
sampling of proteome and transcriptome data in global
studies is highly eligible as this yields comprehensive and
complementary information on two different levels of
cellular regulation.
Considerable efforts in proteomic research are under-
taken for pathogenic bacteria [21–23]. As the emergence
and propagation of multiresistant strains, for example, of
S. aureus, are a major threat in our health systems today
[24], there is a strong need for novel antibiotic strategies.
Granting access to potentially novel targets, extensive
proteomic studies of S. aureus resolved more than 80% of
the proteome in growing cells [19�] and gained valuable
information on the composition and changes of the sur-
face proteome of staphylococci [25–28]. Quantitative
proteomics is also pushed forward to in situ conditions
by monitoring physiological changes of the pathogen after
internalization by human host cells [29�].
Besides stable isotopic labeling of complete organisms,
differential mass tag approaches like iTRAQ are inten-
sively made use of especially in highly multiplexed
studies. Addressing the host–pathogen interaction in
the Arabidopsis-Pseudomonas syringae system, Kaffarnick
et al. determined changes in the host’s extracellular
proteome pathosystem [30]. Taking advantage of even
two different quantitative proteomics techniques, Jayapal
et al. estimated protein turnover rates in Streptomycescoelicolor cultures undergoing transition from exponential
growth to stationary phase in a SILAC-iTRAQ
Current Opinion in Microbiology 2012, 15:364–372
368 Microbial proteomics
Figure 1
2
-2
CV
z-sc
ore
0.25 0.5 exponential growth 120 min stationary phase
Current Opinion in Microbiology
Voronoi treemaps as a powerful visualization tool. To support an in-depth physiological and functional data interpretation protein data should be
enriched with meta-information, which may be derived from functional ontologies such as GO (gene ontology), KEGG Brite, regulatory hierarchies,
COG or other functional categorization schemes (e.g. the SubtiWiki functional categorization as shown here). Voronoi treemaps are able to support a
simultaneous visualization of all protein expression data and complex gene functional categories with functionally most related protein clusters closest
to each other on limited space. Within the treemap the expression data of a proteome sample are mapped as color shades (blue — below, gray —
near, orange — above average expression level), uncertainty as color saturation level. The figure panels show samples from exponential growth phase
as well as from 1200 stationary phase of a Bacillus subtilis glucose-starved culture. Proteins within the same functional cluster with similar profiles
illustrate co-regulated cellular functions which are controlled in response to the acting stimulus.
multitagging strategy [31]. In this study the advantages of
the different approaches become apparent: while meta-
bolic labeling allows extensive fractionation schemes and
thus comprehensive studies on most complete pro-
teomes, the multiplex chemical labeling with isobaric
mass tags opens up clear-cut benefits for strain/mutant/
condition comparisons and at the same time avoids miss-
ing values in time course data sets.
Absolute determination of protein abundanceFor an integration of proteomic data into datasets for
systems biology it is crucial to obtain absolute quantitat-
ive proteomic data. Detecting the absolute protein con-
centration makes it possible to determine protein
stoichiometries from small functional units like metabolic
pathways up to complete proteomes and to compare
different samples in virtually limitless combinations
[32��]. To fulfill the daunting task of absolute quantifi-
cation of proteins and proteomes, currently two different
approaches are mainly applied: workflows based on the
targeted AQUA approach [33] and concepts based on
extracted signal intensities [34]. Other approaches relying
Current Opinion in Microbiology 2012, 15:364–372
on tagging complete genomes impress by their indepen-
dent methodological and analytical approach of fluor-
escence-aided proteome quantification leading to the
same results as compared to proteomic methods, but their
applicability for the broader scientific community seems
to be questionable in terms of analysis costs and time
[35,36].
In the AQUA approach synthetic isotopically labeled
peptides of known concentrations are spiked into the
endogenous peptides of the sample. The peptide mixture
is then subjected to targeted mass spectrometry [33],
resulting in absolute quantitative information for the
identified proteins. Having a massive impact on the
scientific community already, particularly in proteomics
studies looking at smaller functional units of single
proteins, this approach has recently been further concep-
tually refined to meet the requirements for global quan-
titative analyses.
The groundbreaking work published in 2009 by Mal-
mstrom et al. for absolute quantitation on a global scale
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Quantitative analysis and regulation Otto et al. 369
Figure 2
protein amountsare calculated
from Hi3reference &Hi3 protein
peptides
(a) – AQUA peptide supported 2D gel based (b) – AQUA peptide supported LCMS based (c) – Hi3 label-free abs.quantitation
trypticdigest
imaging and 2Dpattern analysis
lowvariancestaining
measuredproteinsamples
2D gels spike in ofheavy (AQUA)peptides
trypticdigest
LCMS&MS/MS
determines lightpeptide/heavypeptide ratios
anchor proteinbased quantitation
of all detectableproteins
measuredproteinsamples
spike in ofheavy (AQUA)peptides
trypticdigest
LCMS &MS/MS
determines lightpeptide/heavypeptide ratios
measuredproteinsamples
spike in of diges-ted referenceproteins
tRm/z
LCMS & MS/MS
ref. protein proteins
anchor peptideconcentrations
serve as referen -ces for quan -titation of all
other peptides
m/z
tRm/z
LCMS runs
tR
label-freequanti-tation
tR
m/z
proteinsproteins
Current Opinion in Microbiology
Absolute quantitation approaches in global studies. Absolute quantitative proteomic data are needed for integration into datasets for systems biology.
(a) The AQUA peptide supported 2D gel-based method relies on protein separation and detection in 2D gels (represented by blue spots/bars) with
absolute quantitation of a distinct set of anchor proteins (orange spots/bars) by the AQUA method (red bars indicate labeled reference peptides). (b)
Similarly, this approach may be performed on aligned label-free LC–MS datasets. Relative peptide abundances are derived from LC–MS maps and
absolute peptide abundances are determined by AQUA. (c) Label-free LC–MS datasets with a spiked-in reference protein serve as basis for absolute
quantitation approaches via the Hi3 method. The three most abundant peptides of all proteins detected in an LC–MS dataset are compared to the
three most intense peptides of a spiked-in reference protein of known concentration (red bars indicate the three most intense peptides of the spiked-in
reference protein and blue bars indicate the three most intense peptide of other proteins detected and compared).
combined the AQUA methodology with label-free quan-
titation and spectral libraries [37]. In follow-up studies,
the workflow was applied to investigate changes in 25
different states of Leptospira interrogans coping with anti-
biotic stresses [38��] as well as in a comprehensive multi-
omics study on Mycoplasma pneumonia [39�]. A unique
feature of these studies is the generation of very extensive
and consistent absolute quantitative data allowing a sys-
tematic interrogation of the cell’s physiological state.
Because of the absence of missing values these datasets
may be regarded as proteomic arrays comparable to arrays
in transcriptome studies [40].
Another approach for absolute protein quantitation on a
global scale is based on targeted mass spectrometry in
combination with 2DE [41��]. Absolute protein concen-
trations for a specific preselected subset of proteins of a
complex sample are determined by AQUA and the
respective protein extracts are subjected to 2DE
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(Figure 2). In analogy to Malmstrom et al. [37], the final
step includes the calibration of the 2D gels according to
the absolute concentration of the anchor proteins. This
fast and cost-effective method is applicable even in
laboratories where high-end mass spectrometry is not
available. Because of the possibility of intergel calibra-
tions the need for measurement capacity is small and once
set up, this approach may be used to complement existing
routine 2D workflows currently only covering relative
quantitation based on differential gel imaging. This
approach combines the advantages of gel-based and
gel-free analyses as well as of absolute and relative
quantitation and offers a unique platform for the precise
and extensive characterization of diverse stress and
environmental trigger signatures.
Label-free quantitation methods, although technically
challenging, are emerging in the field of absolute global
proteome quantitation studies since no cost-intensive
Current Opinion in Microbiology 2012, 15:364–372
370 Microbial proteomics
artificial heavy labeled peptides are needed. A majority of
the label-free absolute quantitation methods rely on the
concept of accurate mass retention time pairs combined
with the integration of the three most abundant peptides
of a protein compared to a spiked-in reference [34,42].
Implementations of this concept, either from academics
[43,44] or as part of a complete proteomics technology
[34,42,45] have greatly succeeded in label-free absolute
proteomics. In microbial proteomics this was used, for
example, for the analysis of different mutants of S. aureusSCV [46] and the probing of the exoproteome of Coryne-bacterium pseudotuberculosis [47].
Despite the success of absolute quantitation on a global
scale, this task remains to be of highest complexity and
exigency compared to relative proteomics studies or
studies aiming on absolute quantification of single
proteins.
Conclusion/outlookThe range of possibilities for global quantitation studies
in proteomics is manifold, offering microbiologists power-
ful experimental options for their lines of research. Whilst
spatio-temporal studies multiply costs and efforts, the
generation of absolute data requires precise compliance to
workflows. In all cases the design of a specific quantitative
study should be worked out with due diligence based on
the objective: the choice of the type of labeling and
proteomics technique determines the quantitation
accuracy, depth of proteome coverage and reproducibility
of the study [1,48].
In our opinion, the elucidation of PTM on a global scale
[11,49,50] and the determination of protein turnover
[51,52,53�] as well as quantitative studies on complex
microbial consortia [54,55�,56] are currently important
fields of progress for microbial proteomics.
References and recommended readingPapers of particular interest, published within the period of review,have been highlighted as:
� of special interest
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Global study following the changes in gene expression and changes in theprotein amount for five different time points in glucose starved cells ofBacillus subtilis. Spatio-temporal study with implemented visualization ofquantitative data with Voronoi treemaps.
19.�
Becher D, Hempel K, Sievers S, Zuhlke D, Pane-Farre J, Otto A,Fuchs S, Albrecht D, Bernhardt J, Engelmann S et al.: A proteomicview of an important human pathogen — towards thequantification of the entire Staphylococcus aureus proteome.PLoS One 2009, 4:e8176.
Study comprising more than 80% of the expressed cytosolic proteome ina growing staphylococcal cell covering four different cellular localizationsin a single proteomic study. High proteome coverage is yielded byextensive fractionation schemes combined with stable isotope labeling.
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Schmidt F, Scharf SS, Hildebrandt P, Burian M, Bernhardt J,Dhople V, Kalinka J, Gutjahr M, Hammer E, Volker U: Time-resolved quantitative proteome profiling of host–pathogeninteractions: the response of Staphylococcus aureus RN1HGto internalisation by human airway epithelial cells. Proteomics2010, 10:2801-2811.
Changes in the proteome of internalized Staphylococcus aureus RN1HGinternalized by human airway epithelial cells were kept track of by acombination of pulse-chase stable isotope labeling and high capacity cellsorting. Excellent approach of in vivo quantitative proteomics with lowsample consumption.
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Malmstrom L, Malmstrom J, Aebersold R: Quantitativeproteomics of microbes: Principles and applications tovirulence. Proteomics 2011, 11:2947-2956.
A milestone in absolute quantitation on a global scale: combination of theAQUA methodology with label free quantification and spectral libraries.
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37. Malmstrom J, Beck M, Schmidt A, Lange V, Deutsch EW,Aebersold R: Proteome-wide cellular protein concentrations ofthe human pathogen Leptospira interrogans. Nature 2009,460:762-765.
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Schmidt A, Beck M, Malmstrom J, Lam H, Claassen M,Campbell D, Aebersold R: Absolute quantification of microbialproteomes at different states by directed mass spectrometry.Mol Syst Biol 2011, 7:510.
Study on pathogenic progression and antibiotic defense of Leptospirainterrogans. Most comprehensive proteome pattern comparison basedon absolute proteome data to date.
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Maier T, Schmidt A, Guell M, Kuhner S, Gavin AC, Aebersold R,Serrano L: Quantification of mRNA and protein and integrationwith protein turnover in a bacterium. Mol Syst Biol 2011, 7:511.
Survey on protein turnover in Mycoplasma pneumoniae. This studycombines mRNA and absolute protein data together with different metadata to describe physiological perturbations in a systems biology study.
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Maass S, Sievers S, Zuhlke D, Kuzinski J, Sappa PK, Muntel J,Hessling B, Bernhardt J, Sietmann R, Volker U et al.: Efficient,global-scale quantification of absolute protein amounts byintegration of targeted mass spectrometry and two-dimensionalgel-based proteomics. Anal Chem 2011, 83:2677-2684.
Absolute protein quantification by targeted mass spectrometry in com-bination with 2DE. This workflow allows absolute quantitative studies witha relatively fast and cost effective methodology combined with theadvantages of 2DE.
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Current Opinion in Microbiology 2012, 15:364–372
372 Microbial proteomics
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Kramer G, Sprenger RR, Nessen MA, Roseboom W, Speijer D, deJong L, de Mattos MJ, Back J, de Koster CG: Proteome-widealterations in Escherichia coli translation rates uponanaerobiosis. Mol Cell Proteomics 2010, 9:2508-2516.
The authors present a methodology to identify stable and labile proteins ina global study to compare relative translation rates with relative mRNAlevels. Thereupon, possible discrepancies between mRNA expression/protein turnover can be used to uncover the basis for regulation bytranslation or by transcription.
54. Pan C, Fischer CR, Hyatt D, Bowen BP, Hettich RL, Banfield JF:Quantitative tracking of isotope flows in proteomes ofmicrobial communities. Mol Cell Proteomics 2011, 10M110.006049.
Current Opinion in Microbiology 2012, 15:364–372
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Belnap CP, Pan C, Denef VJ, Samatova NF, Hettich RL,Banfield JF: Quantitative proteomic analyses of the responseof acidophilic microbial communities to different pHconditions. ISME J 2011, 5:1152-1161.
Quantitative analyses of microbial communities. Global study enabling forin-depth characterization of changes in complex microbial consortiatriggered by environmental changes.
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