Name & Project Klingmüller, Dooley, Schirmacher
State of the art, and own contributions (1/2 page)
Up to now, a few systems biology approaches have partially focused on the dynamics of
TGF-β signal transduction. Computer simulations completely based on previously published
data led to the prediction of a nuclear phosphatase responsible for dephosphorylation of
nuclear SMADs [3]. Combination of computer simulations with experimental data sets
showed that accumulation of phosphorylated SMAD2 in the nucleus is dependent on a
decrease of the nuclear export rate [4]. Another study correlated receptor mediated
endocytosis with the dynamic response of the TGF-β pathway by measuring phosphorylation
of SMAD2 [5]. These published models are either based on experimental data retrieved by
over-expressing the fluorescently-labeled protein of interest under a constitutively active
promoter or by fitting experimental data from one protein to model predictions. In both cases
the experimental conditions do not reflect the dynamics of involved proteins in vivo and
conduct the integration of cellular artefacts into computational models.
In our previous work, Klingmüller-TGF-beta Modell, Kummer TGF-beta Modell.......andere
Modelle? Jak-Stat
This project is on generating tg mouse lines expressing fluorescently labeled proteins under
cell type specific control of the endogenous gene promoter („knock in“). Further, this project
comprises the generation of tg cell type specific TGF-beta (Smad binding element, SBE) and
BMP (BMP response element, BRE) signalling reporter (luciferase) mice. These animals will
be used for quantitative imaging in isolated living cells, e.g. hepatocytes, HSCs or Kupffer
cells, in tissue slices of asserved liver tissue as well as in living mice. All strains derived
expressing fluorescent fusion proteins will be generated on the same isogenic background.
In contrast to the aforementioned previous investigations, data generated within the present
project will be based on endogenous protein levels, thus implying much more reliable
information for mathematical modeling.
In preliminary work, we have already successfully generated several functional floxed tg and
knock out mice of the TGF-beta and PDGF system, e.g., c-reactive protein (CRP) promoterSmad7/TGF-beta1 tg for LPS inducible hepatocyte specific Smad7 or TGF-beta1 expession
(Dooley, Gastroenterol 08); doxycyclin inducible TGF-beta1 tg (Ueberham, Hepatology
2003; Weng, Hepatol 2007; Dooley, Gastroenterol 08); Alb-Smad7-tg-flox for hepatocyte
specific (Albumin promoter), inducible Smad7 expression (unpublished); Smad7-Exon1
deleted (Hamzavi, JCellMolMed 08) or a Smad7 knock out flox (unpublished);
The Dooley group has a long term experience in TGF-β mediated signaling in the different
liver cell types as well as in the analysis of pro- and anti-fibrotic signal transduction pathways
(Wiercinska et al., Hepatology 2006; Seyhan et al., J Cell. Mol. Med 2006, Hamzavi et al., J
Cell. Mol. Med 2008, Weng et al., Hepatology 2007, Dooley et al., Gastroenterology 2008;
Godoy et al., Hepatology 2009). To analyse the progression of a healthy liver into fibrotic
tissue, different animal models like bile duct ligation, CCL4 treatment, partial hepatectomy
and alcohol challenge are established (Hamzawi et al., J. Cell. Mol. Med 2008) Isolation,
cultivation and reliable supply of primary mouse and human hepatocytes as well as other cell
types from the liver, e.g. endothelial cells, hepatic stellate cells and Kupffer cells (Purps et al.,
Biochem Biophys Res Commun. 2007), is guaranteed by SOP’s which were set up in our lab
(Klingmüller et al., Proc IEE Systems Biology 2006). To explore the dynamic behaviour of
the TGF-β signaling components, a novel mathematical model of the pathway was
established, taking into account negative feedback mechanisms (Wegner et al., Biophysical
Journal 2008 in preparation,). Time-resolved and standardised quantitative immunoblotting
techniques (Schilling et al., FEBS Joural 2005) were established to enable a follow up of the
dynamic behaviour of endogenous TGF-β signaling components. Furthermore, hepatocyte
specific TGF-β signaling was experimentally linked with endocytosis and currently models of
this pathway and endocytosis are combined.
Description of planned work for five years, including clearly formulated milestones after
three years (maximum 1.5 page)
The project bridges the knowledge of novel fluorescence labeling, generation of genetically
modified mice and living cell/animal monitoring techniques for quantitative Systems Biology.
This comprises highly sensitive fluorescence spectroscopy, fluorescence tracking, fluorescent
probe design, and high resolution optical imaging techniques on one hand as well as the
biochemical analysis of molecular mechanisms regulating the dynamics of signaling pathways
involved in inflammatory and regenerative responses and finally the mathematical modeling
know-how. Thus, we will be able to provide a novel in vivo labeling and fluorescence
microscopy platform as well as mathematical algorithms to quantitatively elucidate complex
biological networks.
Focus of the present proposal will be on the JAK-STAT and TGF- signalling pathways.
Observation of dimerization (aggregation) and quantification of protein interactions will be
achieved by the use of multicolor FRET, colocalization, and coincidence analysis of the
fluorescence signals recorded at the single-molecule level. The trajectories and movements of
proteins involved in JAK-STAT and TGF- signaling will be directly visualized applying
molecular optical switches in combination with highly sensitive fluorescence tracking
microscopy. Thus, mechanisms of protein interaction and quantification (e.g. dimerization or
multimerization processes) can be performed at an individual (single-molecule) level even in
living cells. Fluorescence labeling of proteins will be performed using new bright fluorescent
fusion proteins with improved photostability.
Identification of inflammatory/hepatocyte proliferation regulatory events in the liver linked to
TGF-β signalling, is so far based on histological analysis of either Smad activation or TGF-β
expression, unable to show detailed dynamic events. However, it is known that processes like
liver regeneration occur with biphasic kinetics. To access cell type specific quantitative
dynamic data in living animals, we will focus on the development of transgenic mice, which
carry a luciferase gene under the control of either a Smad binding element (SBE) or a BMP
responsive element (BRE), utilizing the CRE/loxP system. With these mice, we will monitor
the real time kinetics of TGF-β signaling during liver regeneration after partial hepatectomie
or, alternatively, after a single injection of CCl4 in the context of the whole organ in a living
animal. In addition, knock-in of fluorescent tags (mCherry) into the genomic sequence of
Smads 1/2/3/4/7, SnoN, Stat3 and Socs3 will enable a flexible endogenous labeling of the
respective proteins. Furthermore, expression of the resulting proteins will be completely
controlled by their native promoters and obtained results will reflect endogenous events.
Intercrossed mouse strains (SBE-/BRE-luciferase x tagged-Smad3, SBE/BRE-luciferase x
Smad7, tagged Smad3 x tagged Smad7) will permit access to dynamic data of TGF-β
signaling, monitoring in parallel the events of the inhibitory branch (SMAD7) and the active
signaling branch (Smad3), during pro- and anti-fibrotic processes in living animals and
primary hepatocytes. (soll man hier auch überlegen CRE/loxP zu verwenden, um die
Markierung zelltypspezifisch aktivieren zu können?)
Transgenic mice and primary hepatocytes will be available for the network to validate and
develop SOP’s for the uptake of generated fluorophores.
These animal models will be used with the aforementioned imaging techniques for
quantitative data generation and spatio-temporal mathematical modeling.
Standardisierung der Daten?
Milestones: to be discussed
Vorschlag.
Mx: Publication based model generation and hypothesis
M1: Generation of constructs (a selection, 1-3)
M2: Generation of tg animals (1-3)
M3: Imaging in isolated cells
M4: Imaging in tissue slices
M5: Live cell imaging in slices
M6: In vivo imaging in living animal
M7: Quantitative data generation
M9: Model generation
Contribution to economic exploitation (¼ page)
Currently quantitative analysis of protein or specific nucleic acid sequences is based on wellestablished ex vivo methods such as fluorescence in situ hybridization (FISH) and SDS gel
electrophoresis. However, the dynamic nature of biological processes, e.g. transcription,
requires methods that can follow progression of reactions (as gene expression) in individual
living cells. Although imaging of biological processes in vivo has been revolutionized since
the introduction of genetically encoded fluorescent reagents, the quantitative extraction of
dynamic information from such like in vivo experiments is still hindered and in most cases
hitherto impossible. Thus, the present project exactly meets the criteria of current Systems
Biology efforts and will definitely contribute to establish predictive medicine within the next
10-15 years. That is, Quantitative Systems Biology will make an important contribution to the
determination of probabilistic, individualized future health histories. Our proposed scientific
approaches track key elements for the refined understanding of cellular function and control.
Therefore, it will be of central commercial relevance within the next decades.
The applicants have the required knowledge and experience to successfully demonstrate the
development of novel techniques for quantitative in vivo Systems Biology. In the course of
the project we intend to apply for new patents to assure our new techniques.