A2
Quantitative Proteomics: Generating absolute
facilitating the identification of stoichiometries
numbers
and
Projectleaders:
Experimental:

PD Dr. U. Klingmüller, DKFZ, Heidelberg,
+49 6221 42 4481, u.klingmueller@dkfz-heidelberg

Prof. M. Mann, Max-Planck-Institute for Biochemistry, Martinsried,
+49 89 8578 2557, mmann@biochem.mpg.de
Summary:
Hepatocyte regeneration is orchestrated by the coordinated activation and
deactivation of multiple signaling pathways that form a complex signaling network. To
identify systems properties that permit the regulation and impinge on cellular
decisions such as proliferation, differentiation and survival a systems biology
approach is required that combines high quality experimental data with mathematical
modeling. To facilitate the selection of an appropriate modeling strategy and to define
the starting parameters it is important to generate absolute numbers of signaling
molecules per cell. We established quantitative immunoblotting as a reliable
technique to generate time-course data for modeling purposes (Schilling et al., 2005
FEBS). However to verify the numbers determined by this technique and monitor
more pathway components at the same time it is important to develop a mass
spectrometry approach that focuses on solving the problem of limited material
available and establishing strategies for the quantitative detection of the cellular
components. We will compare the use of the AQUA technology versus the iTRAQ
technology for reliable quantification (TopLab) Toplab will perform the absolute
quantitative determination of selected signaling proteins using the iTRAQ technique.
This method using different isotopically labelled peptides has – compared with the
AQUA technique- the advantage of four-fold multiplexing to analyze 3 samples and
one standard peptide mixture in one experiment. Critical points for all peptide
oriented quantitative approaches are the liberation and detectability of the peptides
derived from the interesting proteins. In the running project (sugar grant) the optimal
sample preparation strategy and the sensitivity of the iTRAQ technique is explored by
the analysis of 4 relevant signaling proteins (STAT3, SMAD2, SMAD3, Erk1) at 9
selected time points. In a continuation of the sugar grant we will determine these
properties for each signaling component under investigation and develop a routine
strategy to sensitively and reliably quantitate signaling components in primary
hepatocytes. The aim is to identify absolute numbers for known signaling pathway
components and their stoichiometries.
Work Plan:
Year 1:
(a)
We will identify in collaboration with Projects B1, B2, B3, B4, B5 and B6
suitable peptides for the reliable mass spectrometry quantification of components
in the JAK-STAT, the NFkappaB, the PI3 kinase and the SMAD signaling
cascades.
Year 2
(b)
Adaptation of the quantification procedure by mass spectrometry to the limited
material available for the primary hepatocytes. Generation of suitable standards.
Quantitative measurements by mass spectrometry for the selected pathway
components and determination of the stoichiometry of the components in primary
hepatocytes.
Year 3
(c)
Time-resolved quantitative proteomics and quality control by quantitative
immunoblotting.
Milestones:
Establishing quantitative proteomics to identify the stoichiometry of pathway
components and for the generation of time-resolved data
Budget TOPLAB
TOPLAB will continue with the special conditions according to the offer in the sugar
grant project A3:
Consumables:
Preexperiments to explore optimal peptides for synthesis, per protein
Synthetic peptides, (e.g. 3 phosphopeptides, 2 nonphosphorylated
peptides), per protein about (max)
Method optimization (i.e. 2D-chromatography), per protein
Sample preparation, cleavage, iTRAQ reaction, peptide separation,
MSMS analyses, data analysis, 3 time points, per protein
Budget Travel:
Text
2.700
8.000
1.200
2.500
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References:
Klingmüller U., A. Bauer, S. Bohl, P. J. Nickel, K. Breitkopf, S. Dooley, S. Zellmer, C.
Kern, I. Merfort, T. Sparna, J. Donauer, G. Walz, M. Geyerr, C. Kreutz, M.
Hermes, F. Götschel, A. Hecht, D. Walter, L. Egger, K. Neubert, C. Borner, M.
Brulport, W. Schormann, C. Sauer, F. Baumann, R. Preiss, S. MacNelly, P.
Godoy, E. Wiercinska, L. Ciuclan, P. Illes, K. Zeilinger, M. Heinrich, U. M. Zanger,
M. Reuss, A. Bader, R. Gebhardt, T. Maiwald, J. Timmer, F. von Weizsäcker, J.
G. Hengstler Primary mouse hepatocytes for systems biology approaches: a
standardized in vitro system for modeling of signal transduction pathways. IEE
Proc Systems Biology in press, 2006.
Schilling M., T. Maiwald, S. Bohl, M. Kollmann, C. Kreutz, J. Timmer, U. Klingmüller.
Computational Processing and Error Reduction Strategies for Standardized
Quantitative Data in Biological Networks. FEBS Journal 272, 6400-6411, 2005.
Schilling M., T. Maiwald, S. Bohl, M. Kollmann, C. Kreutz, J. Timmer, U. Klingmüller.
Quantitative Data Generation for Systems Biology – The Impact of Randomisation,
Calibrators and Normalisers. In press in IEE Proc Systems Biology, 2006.