Chalmers Conferences, 9th European Conference on Mathematical and Theoretical Biology

Integrative modelling and experimental validation of ammonia detoxification after drug induced liver damage
Geraldine Celliere, Ahmed Ghallab, Sebastian Henkel, Stefan Hoehme, Freimut Schliess, Sebastian Zellmer, Jan Hengstler, Dirk Drasdo

Last modified: 2014-03-31

Abstract


The liver is the main ammonia-detoxifying organ. Acute or chronic hyperammonemia due to liver damage can lead to hepatic encephalopathy and death. Liver is compartmentalized into so-called liver lobules, which constitute the smallest functional and anatomical repetitive units of liver. Ammonia transported with the blood into the liver passes two zones within a liver lobule, of which the interior zone is most efficient in detoxifying the blood from ammonia. In case of a paracetamol over dose, the major reason of acute liver failure in human, the pericentral region of the liver lobule is destroyed, leading to an increase of ammonia in the systemic circulation. Current therapies are largely inefficient.

By comparing simulation results of an integrated model with experimental data on metabolite concentrations contributing to ammonia metabolism in mice, we predicted a so far unestablished mechanism that detoxifies ammonia (a ‘missing ammonia sink’). The mathematical model integrates a spatio-temporal mathematical model on the recovery of liver mass and architecture (Hoehme et. al. PNAS, 2010) with a compartment model of ammonia metabolism (Schliess et. al. Hepatology, accepted). Validation experiments identified indeed a so far unrecognized reaction degrading ammonia, which may be used clinically. Simulations with different model refinements and extensions verify that without such a sink, the experimental data cannot be explained quantitatively. Our modeling strategy is an example of how mathematical modeling can guide experiments in an iterative manner. The findings may open the path to a new treatment strategy of hyperammonemia.

Keywords


liver damage and regeneration, hyperammonemia, metabolic compartment model, spatio-temporal model