Virtual Liver

BMBF project

Modeling the influence of classical and alternatively activated macrophages on the regulation of pro- and anti-apoptotic processes in hepatocytes in the course of the LPS-induced inflammatory reaction.

Project Overview

 
 

The Virtual Liver Network cosists of 70 research groups distributed across Germany. The major aim of the network is the development of a dynamic multiscale model that represents liver physiology, morphology, and function.

At the Institute for System Dynamics we are working on modeling the LPS-induced inflammatory response of the liver. Lipopolysaccharide (LPS) ist a component of the bacterial cell wall of Gram-negative bacteria and induces a strong immune response in humans such as fever or septic shock. LPS is recognized by cells of the immune system, the macrophages, as well as by other cell types within the liver and induces a complex response.

The aim of the project was a model-based description and, thus, an improved understanding of the response of macrophages to LPS. We developed a large-scale Boolean model covering the major signaling pathways actiavted in macrophages by LPS as well as a dynamic model of gene expression. In the next step, we investigated the influence of the macrophage-derived inflammatory mediators on the liver cells, the hepatocytes, with special focus on the interaction with apoptotic signaling.

Publications

  • J. Rex, A. Lutz, L. E. Faletti, U. Albrecht, M. Thomas, J. G. Bode, C. Borner, O. Sawodny, I. Merfort, “IL-1beta and TNFalpha differentially influence NF-kappaB activity and FasL-induced apoptosis in primary murine hepatocytes during LPS-induced inflammation”, Frontiers in Physiology, 2019, doi: 10.3389/fphys.2019.00117
  • J. Rex, U. Albrecht, C. Ehlting, M. Thomas, U. M. Zanger, O. Sawodny, D. Häussinger, M. Ederer, R. Feuer & J. G. Bode, “Model-Based Characterization of Inflammatory Gene Expression Patterns of Activated Macrophages”, PLoS Computational Biology, 2016, doi:10.1371/journal.pcbi.1005018
  • R. Feuer, S. Vlaic, J. Arlt, O. Sawodny, U. Dahmen, U. M. Zanger & M. Thomas, “LEMming: A Linear Error Model to Normalize Parallel Quantitative Real-Time PCR (qPCR) Data as an Alternative to Reference Gene Based Methods”, PLoS One, 10, 2015, doi:10.1371/journal.pone.0135852
  • A. Lutz, J. Sanwald, M. Thomas, R. Feuer, O. Sawodny, M. Ederer, C. Borner, M. Humar & I. Merfort, “Interleukin-1beta Enhances FasL-Induced Caspase-3/-7 Activity without Increasing Apoptosis in Primary Mouse Hepatocytes”, PLoS One, 9, pp. 1-27, 2014, doi:10.1371/journal.pone.0115603
  • R. Schlatter, N. Philippi, G. Wangorsch, R. Pick, O. Sawodny, C. Borner, J. Timmer, M. Ederer & T. Dandekar, “Integration of Boolean models exemplified on hepatocyte signal transduction”, Briefings in Bioinformatics, 13, pp. 365-376, 2011, doi:10.1093/bib/bbr065
  • R. Schlatter, K. Schmich, A. Lutz, J. Trefzger, O. Sawodny, M. Ederer & I. Merfort, “Modeling the TNFa-Induced Apoptosis Pathway in Hepatocytes”, PLoS One, 6, 2011, doi:10.1371/journal.pone.0018646
  • N. Philippi, D. Walter, R. Schlatter, K. S. Ferreira, M. Ederer, O. Sawodny, J. Timmer, C. Borner & T. Dandekar, “Modeling system states in liver cells: Survival, apoptosis and their modifications in response to viral infection”, BMC Systems Biology, 2009, doi:10.1186/1752-0509-3-97
  • R. Schlatter, H. Conzelmann, E. Gilles, O. Sawodny & T. Sauter, “Analysis of an apoptotic core model focused on experimental design using artifical data”, IET Systems Biology, 3, pp. 255-265, 2009, doi:10.1049/iet-syb.2008.0138
  • R. Schlatter, K. Schmich, I. A. Vizcarra, P. Scheurich, T. Sauter, C. Borner, M. Ederer, I. Merfort & O. Sawodny, “ON/OFF and Beyond - A Boolean Model of Apoptosis”, PLoS Computational Biology, 5, pp. e1000595, 2009, doi:10.1371/journal.pcbi.1000595
  • J. Sanwald, U. Albrecht, J. Wagenpfeil, M. Thomas, O. Sawodny, J. G. Bode & R. Feuer, “ Modeling the LPS-induced Effects on Transcription Factor Activation and Gene Expression in Murine Macrophages”, International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy, 2015, pp. 3989-3992, doi:10.1109/EMBC.2015.7319268
  • M. Ederer, R. Schlatter, J. Witt, R. Feuer, J. Bona-Lovasz, S. Henkel & O. Sawodny, “An Introduction to Kinetic, Constraint-Based and Boolean Modeling in Systems Biology”, IEEE Conference on Control Applications (CCA), Yokohama, Japan, 2010, pp. 129-134, doi:10.1109/CCA.2010.5611136
  • R. Schlatter, D. Knies, M. Ederer & O. Sawodny, “Analysis of Boolean Models using Quality Assurance Methods from Software Engineering”, IEEE Conference on Control Applications (CCA), Yokohama, Japan, 2010, pp. 518-523, doi:10.1109/CCA.2010.5611070

Partners

Institute of Pharmaceutical Sciences, Prof. Irmgard Merfort, Albert Ludwigs University of Freiburg, Germany
Institute of Moleculare Medicine and Cell Research, Prof. Christoph Borner, Albert Ludwigs University of Freiburg, Germany
Clinic for Gastroenterology, Hepatology and Infectious Diseases, Prof. Johannes G. Bode, Heinrich Heine University of Düsseldorf, Germany
Dr. Margarete Fischer-Bosch Institut of Clinical Pharmacology, Prof. Dr. Ulrich Zanger, Stuttgart, Germany

Funding

The Virtual Liver Network is funded by the BMBF. The funding initiative is coordinated by the Projektträger Jülich (PtJ-BIO).

Contact

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