CAR, PXR and PPARalpha influencing human hepatocyte metabolism: Development of a nuclear receptor model
This project is part of the Virtual liver subproject A3.4, funded by the BMBF. Our aim is to develop a cell model of a nuclear receptor influenced hepatocyte.
Liver background picture was taken from here
Biological motivationCAR, PXR and PPARalpha are nuclear receptors that regulate the transcription of a broad range of genes in the hepatocyte metabolism. Thereby CAR and PXR mostly operate in the same way and PPARalpha acts contrarily (see Thomas et al.). Until now, the influence of nuclear receptors has not been integrated in hepatocyte models. Furthermore, it is considered a very difficult task to integrate signaling and metabolism in one model. With an intensive literature search for reactions, corresponding kinetic equations and parameters we constructed a preliminary version of a model, which is able to simulate equivalent time profiles to our measurement data. The resulting model covers the glycolysis, citrate cycle, ketogenesis, bile acid synthesis as well as parts of the amino acid metabolism.
Model constructionThe model was constructed on the basis of pathway information (KEGG knowledge base) and kinetic information (SABIO-RK and intensive literature search). We decided for each reaction individually which kind of kinetic equation we integrated, according to the published kinetic information. As these kinetic parameters are always dependent on the measurement techniques and environment (e.g., pH, temperature), we needed to adapt parts of the parameters to fit the simulation data to the measured metabolite time profiles. To this end, we decided to adapt the Vmax values. The estimation process was done with our Simulation Core Library, which is integrated in our SBMLsimulator software.
In the next step we will integrate a time dependent factor λ(t) in selected equations to shift the default model system to a nuclear receptor influenced model system. This is our way to model the changed enzyme activities through the nuclear receptors. Our method is comparable to the method of Mosca et al. These factors need to be estimated for each treatment, so that we will end up with 3 different models, each specific for one of the nuclear receptors.
|||Roland Keller, Alexander Dörr, Akito Tabira, Akira Funahashi, Michael J. Ziller, Richard Adams, Nicolas Rodriguez, Nicolas Le Novère, Noriko Hiroi, Hannes Planatscher, Andreas Zell, and Andreas Dräger. The systems biology simulation core algorithm. BMC Systems Biology, 7:55, July 2013. [ DOI | details | link | pdf ]|