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Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration

Authors

  • Freimut Schliess,

    1. Clinic for Gastroenterology, Hepatology, and Infectiology, Heinrich Heine University, Düsseldorf, Germany
    Current affiliation:
    1. Profil Institute for Metabolic Research GmbH, Neuss, Germany
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    • These authors contributed equally to this work.

  • Stefan Hoehme,

    1. Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany
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    • These authors contributed equally to this work.

  • Sebastian G. Henkel,

    1. BioControl Jena GmbH, Jena, Germany
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    • These authors contributed equally to this work.

  • Ahmed Ghallab,

    1. Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
    Current affiliation:
    1. Faculty of Veterinary, Medicine, South Valley University, Qena, Egypt
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    • These authors contributed equally to this work.

  • Dominik Driesch,

    1. BioControl Jena GmbH, Jena, Germany
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  • Jan Böttger,

    1. Institute of Biochemistry, Faculty of Medicine, University of Leipzig, Leipzig, Germany
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  • Reinhard Guthke,

    1. Leibniz Institute for Natural Product Research and Infection Biology Hans Knoell Institute, Jena, Germany
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  • Michael Pfaff,

    1. BioControl Jena GmbH, Jena, Germany
    Current affiliation:
    1. Department of Medical Engineering and Biotechnology, University of Applied Sciences Jena, Jena, Germany
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  • Jan G. Hengstler,

    1. Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
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  • Rolf Gebhardt,

    1. Institute of Biochemistry, Faculty of Medicine, University of Leipzig, Leipzig, Germany
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  • Dieter Häussinger,

    1. Clinic for Gastroenterology, Hepatology, and Infectiology, Heinrich Heine University, Düsseldorf, Germany
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  • Dirk Drasdo,

    Corresponding author
    1. Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany
    2. INRIA, Le Chesnay, France
    3. Jacques-Luis Lions Laboratory, National Center of Scientific Research Joint Research Unit 7598, Pierre and Marie Curie University, Paris, France
    • Address reprint requests to: Dirk Drasdo, Ph.D., INRIA, BP 105, 8153 Le Chesnay Cedex, France. E-mail: dirk.drasdo@inria.fr; or Sebastian Zellmer, Ph.D., Department of Product Safety, German Federal Institute for Risk Assessment, Max-Dohrn Strasse 8-10, 10589 Berlin, Germany. E-mail: sebastian.zellmer@bfr.bund.de

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  • Sebastian Zellmer

    Corresponding author
    1. Institute of Biochemistry, Faculty of Medicine, University of Leipzig, Leipzig, Germany
    Current affiliation:
    1. Department of Product Safety, German Federal Institute for Risk Assessment, Berlin, Germany
    • Address reprint requests to: Dirk Drasdo, Ph.D., INRIA, BP 105, 8153 Le Chesnay Cedex, France. E-mail: dirk.drasdo@inria.fr; or Sebastian Zellmer, Ph.D., Department of Product Safety, German Federal Institute for Risk Assessment, Max-Dohrn Strasse 8-10, 10589 Berlin, Germany. E-mail: sebastian.zellmer@bfr.bund.de

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  • Potential conflict of interest: Dr. Pfaff owns stock in BioControl Jena.

  • This work was cofunded by the Virtual Liver Initiative (www.virtual-liver.de) of the German Federal Ministry of Education and Research, Collaborative Research Center 974 (Communication and Systems Relevance of Liver Damage and Regeneration), and the European Union Seventh Framework Programme for Research (projects NOTOX [Predicting long-term toxic effects using computer models based on systems characterization of organotypic cultures, http://notox-sb.eu/welcome/] and PASSPORT [PAtient Specific Simulation and PreOperative Realistic Training for liver surgery, http://www.passport-liver.eu/Homepage.html]).

  • Dirk Drasdo and Sebastian Zellmer share senior authorship.

  • See Editorial on Page 1823

Abstract

The impairment of hepatic metabolism due to liver injury has high systemic relevance. However, it is difficult to calculate the impairment of metabolic capacity from a specific pattern of liver damage with conventional techniques. We established an integrated metabolic spatial-temporal model (IM) using hepatic ammonia detoxification as a paradigm. First, a metabolic model (MM) based on mass balancing and mouse liver perfusion data was established to describe ammonia detoxification and its zonation. Next, the MM was combined with a spatial-temporal model simulating liver tissue damage and regeneration after CCl4 intoxication. The resulting IM simulated and visualized whether, where, and to what extent liver damage compromised ammonia detoxification. It allowed us to enter the extent and spatial patterns of liver damage and then calculate the outflow concentrations of ammonia, glutamine, and urea in the hepatic vein. The model was validated through comparisons with (1) published data for isolated, perfused livers with and without CCl4 intoxication and (2) a set of in vivo experiments. Using the experimentally determined portal concentrations of ammonia, the model adequately predicted metabolite concentrations over time in the hepatic vein during toxin-induced liver damage and regeneration in rodents. Further simulations, especially in combination with a simplified model of blood circulation with three ammonia-detoxifying compartments, indicated a yet unidentified process of ammonia consumption during liver regeneration and revealed unexpected concomitant changes in amino acid metabolism in the liver and at extrahepatic sites. Conclusion: The IM of hepatic ammonia detoxification considerably improves our understanding of the metabolic impact of liver disease and highlights the importance of integrated modeling approaches on the way toward virtual organisms. (Hepatology 2014;;60:2039–2050)

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