24 October 2013, 16:15
Ernst-Abbe-Platz 2, seminar room 3423

Prediction of liver zonation under different metabolic conditions and during regeneration

Dipl.- Ing. Martin Bartl
(Institute for Automation and Systems Engineering, TU Ilmenau; Research Group Theoretical Systems Biology, FSU Jena)

Liver metabolism is known to be zonated, i.e. certain metabolic reactions take place at specific locations within the liver lobules that form, as many identical subunits, the liver as a highly structured organ. This zonation is known e.g. for the hepatic nitrogen, carbohydrate, lipid and xenobiotic metabolism. In order to support organoriented, spatio-temporal modelling of the liver, essential reactions of its zonated nitrogen metabolism were described and predicted using a combined metabolic modelling and optimization approach. Based on the modelling, optimization was used to predict zonation under different metabolic conditions, in particular those with respect to ammonia detoxification and glutamine regulation.

More specifically, the metabolic model was based on whole-organ liver perfusion data. The model describes, using a two-compartment structure, the zonated nitrogen metabolism of the liver lobules taking into account the periportal zone (with glutamine breakdown to ammonia by glutaminase G and ammonia detoxification to urea by the key enzyme carbamoyl phosphate synthetase CPS) and the pericentral zone (with glutamine synthesis by
glutamine synthetase GS). An extended, multi-compartment version of this model was used to predict in-depth zonation by optimization methods with respect to optimal enzyme activity distributions along the compartments. The optimization approach was based on physiologically meaningful criteria and constraints of liver organ function. There were, however, no constraints with respect to the location of the considered reactions, i.e. all
reactions were allowed to take place in each compartment. Under normal metabolic conditions, a distinct zonation was predicted by the optimization ranging from the periportal side with a zonal expression of only G, via parallel expression of G and CPS, followed by glutaminase-independent ureogenesis, to the pericentral side with a small zone of GS.

With respect to ammonia detoxification, different metabolic conditions were investigated considering varying ammonia concentrations at the periportal inflow (with a constant glutamine inflow concentration at normal metabolic level). Only moderate changes in the predicted zonation indicate a high robustness of ammonia detoxification with respect to varying ammonia inflow concentrations. With respect to glutamine regulation, different metabolic conditions were studied using varying glutamine concentrations at the periportal inflow (with constant ammonia inflow). For low glutamine inflow concentrations, the optimization predicts an enlarged G zone at the pericentral side and a correspondingly reduced CPS zone. Under conditions of high glutamine inflow, however, the CPS zone is enlarged and the pericentral GS zone gets smaller until it disappears completely. Ammonia detoxification is not compromised by the investigated changes in glutamine inflow concentrations.

Also the regenerating liver after CCl4 intoxication was studied. This yielded the prediction of a phenomenon that could be called ‘adaptive’ or ‘dynamic’ zonation – i.e. changing patterns of enzyme distributions along the liver lobule acinus during regeneration until the healthy state is restored. The prediction indicates in the case of maximum damage that there is only high activity of carbamoyl phosphate synthetase, the key enzyme for ureogenesis. During the regeneration process, the enzymatic activity of carbamoyl phosphate synthetase extends continuously with only slow development of glutaminase in the periportal zone. Only in the later stages of regeneration, glutamine synthetase is fully recovered in the pericentral zone.

In summary, the predictions obtained refine our understanding of zonal expression of G, CPS, the small GS zone, changing patterns of enzyme expression under different metabolic conditions and adaptive liver zonation during regeneration. The combination of metabolic models and optimization techniques provides a promising approach to identify unknown structures of liver zonation. The application of this approach to a higher detail of liver lobule representation, other zonated metabolic reactions or other organs has the potential to unravel further unknown phenomena.

Martin Bartl1,2,3,*, Michael Pfaff2,4, Sebastian Henkel2, Sebastian Zellmer5,6, Stefan Schuster7, Rolf Gebhardt5, Dominik Driesch2, Pu Li1

1 Institute for Automation and Systems Engineering, Ilmenau University of Technology, {martin.bartl; pu.li}@tu-ilmenau.de
2 BioControl Jena GmbH, {sebastian.henkel; dominik.driesch}@biocontrol-jena.com
3 Research Group Theoretical Systems Biology, Friedrich Schiller University Jena
4 Present Affiliation: Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena, michael.pfaff@fh-jena.de
5 Institute of Biochemistry, University of Leipzig, rolf.gebhardt@medizin.uni-leipzig.de
6 Present Affiliation: Department: Safety of Consumer Products, Federal Institute for Risk Assessment, Berlin, sebastian.zellmer@bfr.bund.de
7 Department of Bioinformatics, Friedrich Schiller University Jena, stefan.schu@uni-jena.de
*corresponding author