A switch that controls cell death signaling

BCL-2 concentration:

  • TNFα: ON OFF

    Programmed cell death, called apoptosis, is critical for maintaining multicellular organisms and its dysfunction leads to many diseases. Therefore, researchers within the Virtual Liver Network are investigating how this important process is influenced by various effects.

    During apoptosis several molecular components within the cell change their levels as you can see in the simulations shown in the diagram above.

  • One key molecule, that executes apoptosis, is caspase-3 depicted in blue. The higher caspase-3 levels, the more prone to apoptosis are cells. Protective molecules, such as Bcl-2 shown in red can help to keep caspase-3 to moderate levels. TNFα is a molecule that is important for mediating inflammatory responses, for example it is produced by immune cells upon bacterial infection. But may it also affect apoptosis in hepatocytes?
  • Above, you can try yourself – what happens when you switch on or off the effects of TNFα? And by moving the vertical slider you can change the concentration of Bcl-2 within the cell. How does this influence caspase-3 levels?
  • If you want to have more details about these molecules and apoptosis in general, you can find that on the liver basics content page. Then come back here and try to manipulate the cell. Have fun!
  • Implememtation of simulation: Andreas Weidemann and Ivan Savora

  • Authors: Julia Sanwald, Anna Lutz, Kathrin Schmich, Rebekka Schlatter, Oliver Sawodny, Christoph Borner, Irmgard Merfort, Ronny Feuer, Michael Ederer

  • Further readings:
    Modeling the TNFα-Induced Apoptosis Pathway in Hepatocytes
    Tumor Necrosis Factor α Sensitizes Primary Murine Hepatocytes
    Switch from type II to I Fas/CD95 death signaling

  • Links to scientific data:
    Tumor necrosis factor α sensitizes primary murine hepatocytes to Fas/CD95-induced apoptosis in a Bim- and Bid-dependent manner:

    Modeling the TNFα-Induced Apoptosis Pathway in Hepatocytes:

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    Processing, analyzing and querying databases is a major challenge for today’s research scientists

    One of the major challenges in a complex multi-disciplinary project like the Virtual Liver Network is to understand and process data from a variety of data sources. Simply having access to data isn't enough.

  • Researchers need to be able to integrate many seemingly simple bits of data together to be able to answer more complex questions. Therefore, the group of Rebecca Wade at the Heidelberg Institute for Theoretical Studies developed a webserver LigDig. LigDig helps to solve a variety of tasks that are linked by the need to answer questions about proteins. Such questions are based on searching for the compounds that can bind to proteins.
  • LigDig can simplify complex tasks such as converting a chemical compound name from English into a computer based representation of this compound. This representation can be used to search compound databases. This might sound like a trivial task, but for example in the case of fructose 1,6-bisphosphate, a compound involved in regulating central energy metabolism, you can find the compound with different names in different databases: fructose 1,6-diphosphate, fructose bisphosphate, or even FBP.
  • In another example, researchers might be interested to know which proteins in a signaling or metabolic network will be inhibited by a selected inhibitor compound. LigDig allows researchers to search the ChEMBL database of protein-compound binding affinities, a measure of how tightly a protein and compound can bind to each other, and identify the proteins of interest, or to select a more specific inhibitor compound. It can be used, when researchers are modeling a signaling or metabolic network. They can find out this information and choose to add it to their mathematical model. Then they can see whether there is an observable effect on their results, based on their choice of inhibitor compound.
  • LigDig can also be used to compare the 3D structure of two or more binding sites on a protein. Knowing that one protein can bind to a particular compound, e.g. fructose 1,6-bisphosphate, a researcher can compare the known binding site for this protein to a binding site in another protein where it isn't known if fructose 1,6-bisphosphate can bind. If the two binding sites are similar then there is a good chance that the second protein can also bind fructose 1,6-bisphosphate.
  • In the picture, we show how the researcher who is interested in the human protein ERK1 (Uniprot P27361) can use LigDig. The tool identifies a compound Tamatinib. We see that at the moment two protein 3D structures containing this compound are available. Graph-based visualizations can show that Tamatinib can also bind to the protein FLT3, a tyrosine protein kinase receptor. Since there is currently no 3D structure of Tamatinib bound to protein FLT3, superposition of Tamatinib to another compound and protein, whose 3D structure is known gives a suggestion for how Tamatinib might bind to the protein FLT3.
  • Author: Jonathan C. Fuller

  • Further reading and figure reference: Fuller, Jonathan C, Martinez, Michael, Henrich, Stefan, Stank, Antonia, Richter, Stefan, Wade, Rebecca C LigDig: a web server for querying ligand-protein interactions Bioinformatics 2014 Oxford University Press.
  • LigDig is available at: http://mcm.h-its.org/ligdig
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    Liver-enriched nuclear receptors play an important role in the detoxification and energy homeostasis in the liver

    The biotransformation of foreign environmental chemicals (“xenobiotics”), which include most of the drugs in clinical use, is one of the primary functions of the liver. Liver cells express a large number of enzymes and transporters primarily for this purpose.

    Many drugs and other xenobiotics can turn on the production of this biotransformation machinery by a process called enzyme induction. The chemicals bind as ligands to certain signalling proteins, so-called nuclear receptors. They are a class of transcription factors, which regulate the expression of many different genes in a ligand-dependent fashion. Recent advances suggest that certain liver-enriched nuclear receptors link the hepatic drug detoxification system to lipid and energy homeostasis.

  • Researchers from the Virtual Liver Network (group of Prof. Ulrich M. Zanger, Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart) attempt to explore the complex relationships between drug detoxification and intermediary metabolism. They took human hepatocytes from different donors and exposed them to chemical substances, which are activators of different nuclear receptors (CAR, PXR, PPARα). After this, the expression changes of all genes (genome-wide) were determined with special methods.
  • The analysis of the data revealed the overlapping and distinct functions of each receptor in relation to others. For example, the chemical activator of PPARα, a master regulator of lipid homeostasis, induced most drug metabolizing enzyme genes. Conversely, chemical activator of the PXR, a master regulator of detoxification genes, inhibited the lipid metabolism via transcriptional downregulation of the main enzymes of fatty acids degradation. Thus, PPARα and PXR are pulling in the same direction when it is important to detoxify drugs, but they are opponents in terms of lipid and energy homeostasis.
  • To understand the reason for this, a mathematical model was created. It comprises the central carbon metabolism, the triglyceride metabolism, the urea and the bile acid pathways. Using this model the researchers can follow and simulate the effects of these selected nuclear receptors on the central and xenobiotic metabolism in human primary hepatocytes under different physiological conditions (see image). Next, it is planned to expand the established model by implementing several other nuclear receptors into the model, such as FXR, LXRα and HNF4α.
  • Authors: Benjamin A. Kandel, Maria Thomas and Ulrich M. Zanger

  • Image: Stephanie Hoffmann, Benjamin A. Kandel, Maria Thomas, Ulrich M. Zanger and Iryna Ilkavets

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