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Network 1. Ursula Klingmüller. Regenerating Hepatocytes - a Systems Biology Approach. Coordinator: HD Dr. Jens Timmer Center for Data Analysis and Modeling Center for Systems Biology Department for Mathematics and Physics University of Freiburg . Deputy-Coordinator:
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Network 1 Ursula Klingmüller Regenerating Hepatocytes - a Systems Biology Approach Coordinator: HD Dr. Jens Timmer Center for Data Analysis and Modeling Center for Systems Biology Department for Mathematics and Physics University of Freiburg Deputy-Coordinator: PD Dr. Ursula Klingmüller Theodor-Boveri-Group Systems Biology of Signal Transduction German Cancer Research Center (DKFZ) Heidelberg
Platform Modeling Network 1 Regeneration Network 2 Detoxification and Dedifferentiation Platform Cell Biology BMBF-Funding Initiative: Systems of Life - Systems Biology Ursula Klingmüller Networks: regionally Platforms: nationwide
Platform Modeling Network 2 Detoxification and Dedifferentiation Platform Cell Biology Aim Ursula Klingmüller Network 1 Regeneration Systems Properties of Hepatocytes Determination of Conditions for in vitro Propagation and Differentiation of Hepatocytes Hepatocyte Cell Line
Platform Modeling Network 1 Regeneration Network 2 Detoxification and Dedifferentiation Platform Cell Biology Systems Biology of Regenerating Hepatocytes Ursula Klingmüller Data-based Mathematical Modeling of Signaling Pathways Involved in Hepatocyte Regeneration Systems Properties of Regenerating Hepatocytes
Regeneration of Hepatocytes Ursula Klingmüller Highly Regulated Growth Process
Hepatocytes von Weizsäcker Signaling Pathways Klingmüller 2. Walz/Merford/Sparna 3. Mohr 4. Hecht 5. Borner 6. Klingmüller bCatenin Transcription Factors Schütz/Nordheim Transcription Factors 8. Donauer/Walz 8 Consortium: Freiburg/Heidelberg/Tübingen/Würzburg Ursula Klingmüller Modeling Timmer
Progress: Standard Operating Procedures (SOPs) Ursula Klingmüller • Preparation of Primary Hepatocytes by Collagenase Perfusion: • C57/BL6 mice • 6-8 weeks old • male • Cultivation of Primary Hepatocytes: • Defined Medium • Starving Procedure
Success Story: Data-based Modeling of the JAK-STAT Pathway Ursula Klingmüller collaboration with the group of HD Dr. J. Timmer
Model 1: Feed Forward Cascade Ursula Klingmüller
Model 2: Cycling Ursula Klingmüller
Model 2 Hypothesis Testing: Mathematical Modeling of Quantitative Data Ursula Klingmüller Model 1
In Silico Prediction: Unobservable Components Ursula Klingmüller
Setting k4 = 0 or t = One cylce yields only 45% efficiency Most sensitive to nuclear shuttling parameters In Silico Prediction: Targets for Efficient Perturbation Ursula Klingmüller Transcriptional Yield
Experimental Validation of Prediction Ursula Klingmüller
New Knowledge Generated: JAK-STAT Pathway „Remote Sensor“ Ursula Klingmüller PNAS 100, 2003, 1028-1033
New Knowledge Generated: JAK-STAT Pathway „Remote Sensor“ Ursula Klingmüller • Continuous monitoring of receptor activity • Optimal use of limited STAT5 pool PNAS 100, 2003, 1028-1033
0 1 2 4 6 8 10 12 14 16 18 20 22 26 28 30 40 50 60 Quantitative Proteinarray The Challenge: Quantitative Time/Space Resolved Data Ursula Klingmüller Quantitative Immunoblotting + Epo Immunoblot Anti-EpoR Purification by Anti-EpoR Immunoprecipitation pEpoR
Identification of conditions for in vitro expansion and differentiation of hepatocytes Summary - Vision Ursula Klingmüller • Modular data-based models of signaling pathways • involved in hepatocyte regeneration • Incorporation of cross-talk • Generation of interconnected “big“ model