B5
Dynamic Modeling of HGF-mediated MAP-Kinase and PI3 Signaling
Determining Proliferative Responses in Hepatocytes
Projectleaders:
Experimental:

Prof. J.G. Hengstler, Center for Toxicology, University of Leipzig,
+49 3419724 614, jan.hengstler@medizin.uni-leipzig.de

PD Dr. U. Klingmüller, DKFZ, Heidelberg,
+49 6221 42 4481, u.klingmueller@dkfz-heidelberg
Modeling:

Prof. R. Heinrich, Theoretical Biophysics, Humboldt-University Berlin,
+49 30 2093 8698, Reinhart.Heinrich@rz.hu-berlin.de

Prof. J. Timmer, Center for Data Analysis and Modeling, University of
Freiburg, +49 761 203 5829, jeti@fdm.uni-freiburg.de
Summary:
Hepatocyte growth factor (HGF)/c-Met signaling promotes both proliferation and
scattering (migration) of hepatocytes. Major signaling cascades activated upon ligand
binding to the receptor tyrosine kinase c-met are the MAP kinase signaling cascade
and the phosphoinositide (PI)3 signaling pathway. Additional pathways activated are
the STAT and the phospholipase C pathways. Although the individual components of
the involved signaling cascades have been studied intensively, their specific
contribution to proliferation and migration of hepatocytes is poorly understood.
Detailed time-resolved data for the activation of the MAP-kinase signaling cascade
will be generated by the group of J. Hengstler and used for mathematical modeling
by the goups of R. Heinrich and J. Timmer refining existing kinetic descriptions of the
core components. Control analysis will be used to identify key components
controlling signal amplification and signal duration (Heinrich et al., 2002, Hornberg et
al., 2005). The PI3 kinase signaling pathway will be examined by the group of U.
Klingmüller by biochemical means and by live cell imaging. The time-resolved data
will be used to extend the mathematical model established in collaboration with J.
Timmer and finally used in combination with spatially resolved data to establish a
spatio-temporal model. Model predictions will be experimentally verified by applying
an RNAi strategy and by developing a tetracyclin inducible sytem that facilitates
dose-dependent over-expression of signaling components and of fluoresent labeled
signaling components. A key signaling cascade activated during the proliferative
phase of hepatocyte regeneration is the phosphoinositide (PI)3 kinase cascade that
is primarily triggered by the Met receptor in response to binding of the hepatocyte
growth factor (HGF). The TGFbeta mediated activation of the SMAD signaling
pathway is important during the termination phase of hepatocyte regeneration. Both
signaling cascades cross-modulate their respective activity e. g. HGF stimulation of
the Met receptor induces the production of TGFbeta and the phosphoinositide 5
phosphatase SHIP-1 is a target gene of SMAD2/3. Elucidating systems properties
governing the cross-talk of the signaling pathways will provide insight into
mechanisms supporting the switch from the proliferation phase towards
differentiation.
Work Plan:
All experiments will be done with primary mouse hepatocytes (B6, male) isolated and
cultured according to our recently published SOP (Klingmüller et al., 2006).
Year 1:
(a)
According to our previous studies identifying 20 ng/ml HGF and an observation
period of 180 min as an informative range the group of J. Hengstler will quantify
the HGF-induced the time course of c-met, Ras, Raf, Mek, ERK1/2 and Cyclin D
phosphorylation, cooperation with Project C2.
(b)
The group of U. Klingmüller will identify the most informative measurement
range for the activation of PI3 kinase by HGF in primary hepatocytes and
generate timecourse data for the ligand induced phosphorylation of the c-Met
receptor, the scaffold protein Gab1, complex formation with the regulatory and
the catalytic subunit of PI3 kinase and Akt using quantitative immunoblotting and
mass spectrometry.
(c)
To permit the expression of fluorescent-tagged signaling proteins at the level
of the endogenous protein or for targeted over expression and for the targeted
perturbation of signaling pathways, a tetracyclin inducible (Teton) system willl be
developed by the group of U. Klingmüller. The efficiency of target gene
expression in primary hepatocytes for adenoviral and lentiviral vectors will be
tested and optimized to deliver inducible target gene cassettes. Since no suitable
revTet repressor mouse line is available, in collaboration with Project 8 a liver
specific transgenic mouse line will be established expressing the most recent
tight revTet repressor in analogy to the successful albumine Cre mouse line.
(d)
First variants of kinetic models are developed in the groups of R. Heinrich and
J. Timmer both for the MAPK pathway and for the PI3 signaling cascade based
on an exisiting model decribing intial pathway activation. Both modeling
approaches will be performed in close collaboration. It will be explored which
pathway components are essential for model building and which kinetic
parameters are of crucial importance for pathway dynamics. Based on this
information suggestions for further experimental analysis are provided.
Year 2
(a)
The groups of J. Hengstler and U. Klingmüller in collaboration with B1 and B6
will develop a releyable assay for the quantification of DNA synthesis by 3Hthymidine incorporation (hepatocyte population) and by bromodeoxyuridine
(BrdU) incorporation (single hepatocyte). The transition between the HGFmediated activation of MAPK signaling regarding the scattering response and the
proliferative response will be analyzed by the group of J. Hengstler by automated
monitoring of hepatocyte mobility in time-lapse phase-contrast imaging.
Furthermore, a relationships between c-Met receptor endocytosis, MAPK
signaling, scattering and DNA synthesis will be examined in cooperation with
Dooley and Zerial (Network Endocytosis).
(b)
The influence of phosphatases (including MKP-1) for MAP-kinase signaling will
be examined by the group of J. Hengstler and included into the model developed
by the group of R. Heinrich to capture the effects of negative feed-back loops.
The model will be applied for simulating experiments on sustained and transient
pathway stimulation. Moreover, the effects of inhibiting c-met internalization or of
kinase activities within different pathways are reproduced. Control analysis is
used to identify key components controlling signal amplification and signal
duration.
(c)
In extensive time course experiments the HGF induced secretion of TGFbeta
by primary hepatocytes will be quantified in the group of U. Klingmüller by
enzyme linked immunosorbent assay (ELISA). Furthermore the induction of SHIP
by TGFbeta induction will be monitored at the RNA level by real time PCR and at
the protein level by quantitative immunoblotting. The time-resolved data will be
incorporated into the mathematical model and will be used to link the models for
PI3 kinase signaling and SMAD signaling (J.Timmer).
(d)
To monitor signaling pathways at the single cell level the group of U.
Klingmüller will express fluorescent-tagged variants of SMAD2/3 and pleckstrin
homology (PH) domains for monitoring the generation of phosphoinositides by
PI3 kinase in primary hepatocytes of the revTet-repressor knock-in mouse line by
means of inducible adenoviral or lentiviral vectors in collaboration with Project B4.
Year 3
(a)
Mathematical predictions will be derived regarding scattering and DNAsynthesis as a consequence of HGF-induced signaling will be derived by close
collaboration of the grops of J. Hengstler, U. Klingmüller, J. Timmer and R.
Heinrich and connected to the cell cycle control in cooperation with C2.
(b)
To experimentally verify model predictions the groups of J. Hengstler, U.
Klingmüller and S. Dooley (Network Endocytosis) will modulate the signaling
pathway by targeted over-expression by the Tet-inducible system, by small
molecule inhibitors and by siRNA knockdown. For siRNA knockdown SOPs
established by the Platform Cell Biology will be applied.
(c)
The mathematical models for the MAP kinase and the PI3K signaling
pathways will be connected and used to examine signal integration as well as to
elucidate feedback interactions between gene regulatory and signal transduction
networks. For Mathematical predictions regarding the cross modulation of PI3
kinase and SMAD signaling cascade mediated target gene expression will be
experimentally validated by microarray analysis and real time PCR by the group
of U. Klingmüller.
(d)
Spatial-resolved data will be acquired for GFP-tagged SMAD2/3 and the PH
domain of Grb1. and used to expand the mathematical models by including
spatial effects by the groups of U. Klingmüller in collaboration with the groups of
J. Timmer and R. Heinrich.
Milestones:
Mathematical model of the HGF-stimulated MAPK signaling pathway and the PI3
kinase signaling cascade
Modeling of the role of c-met endocytosis on MAPK signaling and of negative
feedback loops
Establishing points for cross-talk of the PI3 kinase and SMAD signaling pathways
and linking the mathematical models for PI3 kinase and SMAD signaling
For the targeted manipulation of signaling pathways in primary hepatocytes a
hepatocyte specific Tet-on inducible system is established comprising a novel
revTet repressor knock-in mouse line in combination with inducible viral vectors.
Generation of spatio-temporla data for nuclear-cytoplasmic cycling of SMAD2 and3
as well as quantification of the lipid products of PI3 kinase
Mathematical predictions regarding HGF-mediated scattering and DNA synthesis and
the switch from proliferation to termination
Experimental validation of model predictions
Budget Hengstler
Personal:
One graduate student (BATII/a/2-O). The student will perform the
hepatocyte isolation and cultivation, stimulate hepatocyte cultures with
HGF and analyse MAP-kinase signaling. The PhD student will be
supported by a second PhD student from the budget of the Centre for
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Toxicology, University of Leipzig
Consumables:
Isolation, cultivation and stimulation of hepatocytes (purchasing BL6
mice, collagenase, collagen coated dishes, FCS, Williams medium,
HGF)
Quantitative immunoblotting (primary antibodies for c-Met, ERK1/2,
Ras, Raf, MEK, MKP1 and secondary antibodies, nitrocellulose/PVDF
membrane, calnexin as normalizer)
Quantification of DNA synthesis by 3H-thymidine incorporation
(hepatocyte population) and by bromodeoxyuridine (BrdU)
incorporation and scattering analysis:
20.000
30.000
10.000
60.000
Budget Klingmüller
Personal:
One experienced postdoctoral fellow (BATIIa) with experience in cell
biology, molecular biology, transgenic animal generation, experience in
live cell imaging
Consumables:
Preparation, cultivation and stimulation of hepatocytes (purchasing
BL6 mice, collagenase, collagene treated plates, FCS, Williams
medium, HGF and TGFbeta). Quantitative immunoblotting (primary
antibodies for c-Met, Akt, PDK1, SHIP-1, SMAD2/3 and secondary
antibodies, nitrocellulose/PVDF membrane, BSA, recombinant proteins
as calibroators and antibodies against actin, HSC70, PDI, calnexin,
clathrine as normalizer)
Mass spectrometry (recombinant proteins for the identification of
suitable peptides and isotope labeled or mutated as standards, isotope
labeled peptides (AQUA technology from Sigma)
Generation of inducible retroviral vectors (restriction enzymes, cell
culture)
Live cell imaging r(estriction enzymes, chambers for live cell imaging)
Generation of revTet-repressor transgenic mouse line (establishment
of knock-in vector using BAC technolgy, ES cell culture)
171.300
30.000
20.000
10.000
10.000
20.000
90.000
Budget Heinrich
Personal
One BATIIa-O for mathematical modeling
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Budget Timmer
Personal
One graduate student (BATII/a/2) for mathematical modeling
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Budget Travel:
5000€ per partner for three years. 6 trips per person per year to the
collaborating partners, participation in one European conference in the
first two years and one international conference in the third year.
20.000
Sachkosten
a. for Mathematical modeling (Heinrich group: 3 PCs, special software)
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Gemeinkosten
(17.5 % auf PK und SK)
???Ursula rechnet nach??
3.000 Euro
p.a.
12.250
Euro p.a.
References:
Heinrich A. C., R. Pelanda, U. Klingmüller. A Mouse Model for Visualization and
Targeted Mutations in the Erythroid Lineage. Blood. (2004) 104(3):659-66.
Heinrich, R., Neel, B.G., and Rapoport, T.A. Mathematical models of protein kinase
signal transduction. Mol. Cell 9, 957-970, 2002.
Hornberg, J., Binder, B., Bruggeman, F., Schoeberl, B., Heinrich, R. and Westerhoff,
H. Control of MAPK signaling: from complexity to what really matters. Oncogene
24, 5533-5542, 2005.
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. Geyer, 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, K. Zeilinger, M. Heinrich, U. M. Zanger, 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. Systems Biology, in press, 2006.
Ruhnke M, Ungefroren H, Nussler A, Martin F, Brulport M, Schormann W, Hengstler
JG, Klapper W, Ulrichs K, Hutchinson JA, Soria B, Parwaresch RM, Heeckt P,
Kremer B, Fändrich F, Reprogramming of Human Peripheral Blood Monocytes into
Functional Hepatocyte and Pancreatic Islet-like Cells. Gastroenterology,
128:1774-86, 2005.
Schiffer IB, Gebhard S, Heimerdinger CK, Heling A, Hast J, Wollscheid U, Seliger B,
Tanner B, Gilbert S, Beckers T, Baasner S, Brenner W, Spangenberg C, Prawitt
D, Trost T, Schreiber WG, Zabel B, Thelen M, Lehr HA, Oesch F, Hengstler JG.
Switching of her-2/neu mediated MAPK signaling in a tetracycline-controlled
mouse tumor model. Cancer Res. 63, 7221-31, 2003.
Schilling, 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.
Swameye I., T. G. Müller, J. Timmer, O. Sandra, U. Klingmüller. Identification of
nucleocytoplasmic cycling as a remote sensor in cellular signaling by data-based
dynamic modeling. PNAS (2003) 100:1028-33.