# Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases

Ahmed Ghallab, Geraldine Celliere, Sebastian Henkel, Dominik Driesch, Stefan Hoehme, Ute Hofmann, Sebastian Zellmer, Patricio Godoy, Agapios Sachinidis, Meinolf Blaszkewicz, et al.

► To cite this version:

Ahmed Ghallab, Geraldine Celliere, Sebastian Henkel, Dominik Driesch, Stefan Hoehme, et al. Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases. Journal of Hepatology, 2015, 64 (4), pp.860-871. 10.1016/j.jhep.2015.11.018. hal-01257127

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Graphical abstract

Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases

pp xxx-xxx

Ahmed Ghallab *, Géraldine Cellière, Sebastian G. Henkel, Dominik Driesch, Stefan Hoehme, Ute Hofmann, Sebastian Zellmer, Patricio Godoy, Agapios Sachinidis, Meinolf Blaszkewicz, Raymond Reif, Rosemarie Marchan, Lars Kuepfer, Dieter Häussinger, Dirk Drasdo, Rolf Gebhardt, Jan G. Hengstler *

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Research Article

Model-guided identification of a therapeutic strategy to
reduce hyperammonemia in liver diseases

Ahmed Ghallab¹,²,*, Géraldine Cellière³,†, Sebastian G. Henkel⁴,†, Dominik Driesch⁴,
Stefan Hoehme⁵, Ute Hofmann⁶, Sebastian Zellmer⁷, Patricio Godoy¹, Agapios Sachinidis⁸,
Meinolf Blaszkewicz†, Raymond Reif¹, Rosemarie Marchan¹, Lars Kuepfer⁹, Dieter Häussinger¹⁰,
Dirk Drasdo³,⁵,‡, Rolf Gebhardt⁷,‡, Jan G. Hengstler¹,*,‡

¹Leibniz Research Centre for Working Environment and Human Factors at the Technical University Dortmund, Dortmund, Germany;

²Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt; ³Institute National de Recherche en Informatique et en Automatique (INRIA), INRIA Paris-Rocquencourt & Sorbonne Universités UPMC Univ Paris 6, LJLL, France

⁴BioControl Jena GmbH, Jena, Germany; ⁵Interdisciplinary Centre for Bioinformatics, University of Leipzig, Leipzig, Germany; ⁶Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology and University of Tuebingen, Germany; ⁷Institute of Biochemistry, Faculty of Medicine,

University of Leipzig, Leipzig, Germany; ⁸Institute of Neurophysiology and Center for Molecular Medicine Cologne (CMMC), University of Cologne, Robert-Koch-Str. 39, 50931 Cologne, Germany; ⁹Computational Systems Biology, Bayer Technology Services GmbH, Leverkusen, Germany;

¹⁰Clinic for Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany

**Background & Aims:** Recently, spatial-temporal/metabolic mathematical models have been established that allow the simulation of metabolic processes in tissues. We applied these models to decipher ammonia detoxification mechanisms in the liver.

**Methods:** An integrated metabolic-spatial-temporal model was used to generate hypotheses of ammonia metabolism. Predicted mechanisms were validated using time-resolved analyses of nitrogen metabolism, activity analyses, immunostaining and gene expression after induction of liver damage in mice. Moreover, blood from the portal vein, liver vein and mixed venous blood was analyzed in a time dependent manner.

**Results:** Modeling revealed an underestimation of ammonia consumption after liver damage when only the currently established mechanisms of ammonia detoxification were simulated. By iterative cycles of modeling and experiments, the reductive amidation of alpha-ketoglutarate (α-KG) via glutamate dehydrogenase (GDH) was identified as the lacking component. GDH is released from damaged hepatocytes into the blood where it consumes ammonia to generate glutamate, thereby providing systemic pro-

tection against hyperammonemia. This mechanism was exploited therapeutically in a mouse model of hyperammonemia by injecting GDH together with optimized doses of cofactors. Intravenous injection of GDH (720 U/kg), α-KG (280 mg/kg) and NADPH (180 mg/kg) reduced the elevated blood ammonia concentrations (>200 µM) to levels close to normal within only 15 min.

**Conclusion:** If successfully translated to patients the GDH-based therapy might provide a less aggressive therapeutic alternative for patients with severe hyperammonemia.

© 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Introduction

Recent developments have strongly improved our capability to generate information at multiple spatial and temporal scales [1,2]. However, research on disease pathogenesis is hampered by the difficulty to understand the orchestration of individual components. Here, mathematical models help to formalize relations between components, simulate their interplay, and to study processes that are too complex to be understood intuitively [1]. This is particularly important when studying the pathophysiology of metabolic liver diseases, where due to zonation different metabolic processes take place in pericentral and periportal hepatocytes [3]. To be able to investigate such complex processes we recently established a technique of integrated metabolic spatial-temporal modeling (IM) [4]. These IM integrate conventional metabolic models into spatial-temporal models of the liver lobule [1,4,5]. The present study was motivated by the IM predictions, which proposed that the conventional mechanisms where ammonia is metabolized by urea cycle enzymes in the periportal compartments of the liver lobules and by glutamine synthetase (GS) reaction in the pericentral compartments (Supplementary

Keywords: Systems biology; Spatio-temporal model; Ammonia; Liver damage; Liver regeneration.

Received 23 March 2015; received in revised form 15 November 2015; accepted 16 November 2015

* Corresponding authors. Addresses: Leibniz Research Centre for Working Environment and Human Factors, IfADo – Ardestr. 67, D-44139 Dortmund, Germany. Tel.: +49 02311084 356; fax: +49 02311084 403 (A. Ghallab) or Leibniz Research Centre for Working Environment and Human Factors, IfADo – Ardestr. 67, D-44139 Dortmund, Germany. Tel.: +49 02311084 349; fax: +49 02311084 403 (J.G. Hengstler).

E-mail addresses: ghallab@ifado.de (A. Ghallab), hengstler@ifado.de (J.G. Hengstler).

† These authors contributed equally to the work.

‡ These authors share co-senior authorship.

Abbreviations: CCl₄, carbon tetrachloride; GDH, glutamate dehydrogenase; AOA, aminoxy acetate; ALT, alanine transaminase; AST, aspartate transaminase; α-KG, alpha-ketoglutarate; PDAC, 2,6-pyridinedicarboxylic acid.

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ELSEVIER
Research Article

Fig. 1) failed to explain the experimental findings [4]. The IM was applied to an experimental scenario, where the entire pericentral and a part of the periportal compartment of the liver lobules were destroyed by a single high dose of the hepatotoxic compound carbon tetrachloride (CCl₄). This leads to compromised nitrogen metabolism and hyperammonemia. In the present study, we performed a series of new experiments accompanied by simulations with novel models to explore the mechanism responsible for the observed discrepancy. Experimentally, the time-resolved analysis of metabolites and metabolic activities after CCl₄ intoxication offers good conditions to study ammonia detoxification and possible compensatory mechanisms during the damage and regeneration process. Time-resolved analysis of metabolites was performed in the portal vein and heart blood, representing the 'liver inflow', and in the liver vein as 'liver outflow'. These analyses allowed a precise experimental validation of model predictions. Finally, iterative cycles of modeling and experimental validation allowed the identification of a so far unrecognized mechanism of ammonia detoxification. Importantly, this mechanism could be exploited therapeutically to reduce elevated blood ammonia concentrations close to normal levels by intravenous injection of glutamate dehydrogenase (GDH; 720 U/kg) and its cofactors alpha-ketoglutarate (α-KG; 280 mg/kg) as well as NADPH (180 mg/kg). This example illustrates how concrete therapies can be derived by model guided experimental strategies.

Materials and methods

A detailed description of materials and methods is provided in the *Supplementary materials*. Male C57BL/6N 10-12 weeks old mice were used (Charles River, Sulzfeld, Germany). Acute liver damage was induced by intraperitoneal injection of 1.6 g/kg CCl₄, unless other doses are indicated. Blood was taken from mice under anesthesia from the portal and hepatic veins, as well as the right heart chamber, and plasma was separated. Liver tissue samples were collected from defined anatomical positions for histopathology, immunohistochemistry, enzyme activity assays, gene array and q-RT-PCR analyses. The dead cell area was quantified in hematoxylin and eosin stained tissue sections using Cell^M software (Olympus, Hamburg, Germany). Whole-genome analysis of gene expression in mouse liver tissue was performed in control as well as after CCl₄ intoxication with Affymetrix gene arrays. The latter techniques are described fully in the *Supplementary materials and methods*. The analysis of ammonia and further metabolites was performed using commercially available kits. Concentrations of amino acids and organic acids in liver tissue were measured in duplicate using GC-MS. GS, GDH and transaminases activity assays were performed photometrically as described in the *Supplementary materials and methods*. NADP⁺ and NADPH were analyzed by LC-MS. Mouse hepatocytes were isolated by a two-step EGTA/collagenase perfusion technique and either used directly in suspension or cultivated in collagen sandwiches (*Supplementary materials and methods*). For the mathematical modeling of ammonia and the related metabolites the integrated metabolic, spatio-temporal model was applied [4,5]. In addition, the IM was replaced by a set of novel models that include further reactions and the blood compartment of the liver (*Supplementary materials and methods*). Statistical analysis was done with SPSS software as described in the *Supplementary materials*.

Results

An integrated spatial-temporal-metabolic model suggests a so far unrecognized mechanism of ammonia detoxification

The detoxification process in healthy, damaged and regenerating livers was simulated using a recently established integrated metabolic IM [4]. To compare the simulated metabolite concentrations

with the *in vivo* situation, an experiment was performed in which blood was collected from the portal vein (representing 85% of the 'liver inflow'), the heart (representing 15% of the 'liver inflow'), and the hepatic vein (representing the 'liver outflow') in a time-resolved manner after CCl₄ injection (Fig. 1A; *Supplementary Fig. 2*). The result shows that ammonia is detoxified during its passage through the liver as illustrated by the difference in ammonia concentrations between the portal vein and the hepatic vein in the control mice (Fig. 1B). This detoxification process is compromised after liver damage, particularly on days 1 and 2. Surprisingly, the IM model predicted higher ammonia concentrations than those experimentally observed, particularly on day 1 (Fig. 1C; see the video in the *Supplementary data*). Analyses of heart blood demonstrate the contribution of the extrahepatic compartment, which includes brain, muscles, kidneys and blood, to ammonia detoxification between days 1 and 4 after the induction of liver damage. However, this extrahepatic contribution is small compared to detoxification by the liver (*Supplementary Figs. 2-8*). In addition to the time-resolved study, similar experiments were also performed in a dose dependent manner on day 1 after CCl₄ administration when the discrepancy between simulated and measured ammonia was maximal. For this purpose, doses ranging between 10.9 and 1600 mg/kg CCl₄ were tested, resulting in a concentration dependent increase in the dead cell area, with only the highest dose causing damage to the entire CYP2E1 positive pericentral region of the liver lobule (Fig. 1D; *Supplementary Fig. 9A, B*). Destruction of the GS positive area occurred in with doses ranging between 38.1 and 132.4 mg/kg (Fig. 1D, E; *Supplementary Fig. 9C*); also CPS1 showed a dose dependent decrease (*Supplementary Fig. 9C*) leading to compromised ammonia metabolism (*Supplementary Fig. 10*). Using the IM [4], we also observed a discrepancy between the predicted and measured ammonia in the dose dependent study (Fig. 1F).

To find an explanation for this discrepancy, we performed time-resolved gene array analysis of mouse liver tissue after CCl₄ intoxication (Fig. 2A). Fuzzy clustering identified seven gene clusters which reflected time dependent gene expression alterations [6]. Clusters 4 and 6 contained genes whose expression was transiently repressed at early time points after CCl₄ intoxication (Fig. 2B). Further bioinformatics analyses revealed an over representation of nitrogen/ammonia metabolism KEGG and Gene ontology terms of genes in cluster 4 (Fig. 2C, D). Genes relevant for ammonia metabolism were further studied by qRT-PCR, immunostaining and activity assays. GS is the key enzyme for ammonia detoxification in the pericentral compartment. RNA levels of GS started to decrease as early as 6 h after CCl₄ injection, it was at its lowest between days 1 and 4, before finally recovering to initial levels between days 6 and 30 (Fig. 2E). A similar time-dependent curve was obtained for GS activity although the decrease occurred slightly later than that of RNA with very low levels between days 2 and 4 (Fig. 2E). The pattern and intensity of GS immunostaining was found to be comparable to GS activity (Fig. 2F). In addition, ornithine aminotransferase (OAT), an enzyme exclusively localized in GS positive pericentral hepatocytes that provides additional glutamate for fixing ammonia [7], decreased to almost undetectable levels with a delayed recovery (Supplementary Fig. 3A). The key enzymes of the periportal compartment, CPS1, ASS1, ASL and arginase1 were similarly analyzed in the same tissue (Supplementary Figs. 3B and 4). Extending the IM [4], with time-dependent

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JOURNAL OF HEPATOLOGY

enzyme concentrations (model 1), did not remove the discrepancy between model predictions and experimental data (Supplementary Fig. 11), indicating that our model lacks a relevant, but so far unrecognized mechanism of ammonia detoxification.

Acute liver damage provides systemic protection against ammonia by GDH release

Further evidence that an unrecognized mechanism of ammonia detoxification exists arose from metabolic analyses performed

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A

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Analyzed parameters

* ammonia

* urea

* glutamine

* glutamate

* glucose

* lactate

* pyruvate

* alanine

* α-ketoglutarate

* arginine

* other amino acids

* ALT, AST

B

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C

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D

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E

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F

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Research Article

using plasma from mice after CCl₄ injection (Fig. 3A). Most of the analyzed factors in plasma (urea, glutamine, glucose, lactate, pyruvate, alanine, arginine and other amino acids: *Supplementary Figs. 4-6*) were within the expected concentration ranges, α-KG, which dramatically decreased between 12 h and day 2 (Fig. 3A). This decrease was accompanied by an almost concurrent increase in glutamate levels, which persisted longer than the drop in α-KG. One potential explanation is the delayed recovery of GS, which uses glutamate and ammonia to form glutamine (Fig. 2E, F). The decrease in α-KG (and the increase in glutamate) was also accompanied by increased GDH activity in plasma, because GDH is released from damaged hepatocytes (Fig. 3A). The present observations suggest that GDH released from the damaged hepatocytes into the blood catalyzes, at least transiently, a reaction that consumes ammonia to produce glutamate (Fig. 3D). To test this hypothesis, we collected plasma from mice on day 1 after CCl₄ injection. Addition of α-KG alone was sufficient to slightly but significantly decrease blood ammonia concentrations (Fig. 3B). This decrease was enhanced by further adding NADPH and particularly GDH; whereas the GDH inhibitor, PDAC completely antagonized the effect. To test also higher ammonia concentrations typically observed in patients with severe pre-coma hyperammonemia, 600 µM ammonia was added to plasma collected on day 1 after CCl₄ administration. Under these conditions, α-KG also reduced ammonia and increased glutamate concentrations (Fig. 3C; Supplementary Fig. 12A). Together, these experiments suggest that a GDH reaction consuming ammonia in blood takes place when GDH is released from acutely damaged livers (Fig. 3D).

Validation of the 'GDH-driven ammonia consumption' in hepatocytes

The experiments described above suggest that high ammonia concentrations in plasma leads to a 'reverse' GDH reaction, which consumes rather than produces ammonia. To test whether this 'GDH-driven ammonia consumption' occurs not only in plasma but also in cells, we used an *in vitro* system with primary mouse hepatocytes incubated with ammonia in suspension (Fig. 4). PDAC was used to inhibit GDH (Fig. 4A) in order to determine its influence on ammonia metabolism. In hepatocytes isolated from control mice, unphysiologically high ammonia concentrations (2 mM) were required until PDAC caused a significant increase of ammonia levels in the suspension buffer (Fig. 4B). However, when hepatocytes from mice 24 h after CCl₄ intoxication were used, PDAC treatment increased ammonia concentrations in the suspension buffer, even with 0.5 mM ammonia. Furthermore, in the absence of ammonia, hepatocytes secreted a small but statistically significant amount of ammonia into the buffer. Similarly, glutamate production was reduced by PDAC,

an effect that was also stronger in hepatocytes isolated from CCl₄-exposed mice (Fig. 4C), which corresponds to the reverse GDH reaction proposed in Fig. 3D (right panel). CCl₄ destroys the pericentral hepatocytes (Fig. 1D), which explains the reduced glutamine generation by GS (Fig. 4D) and compromises urea cycle enzymes (Supplementary Fig. 3B, C), which explains the reduced urea production (Fig. 4E). Similar experiments were also performed with cultivated (instead of suspended) hepatocytes from untreated mice. The results demonstrate that inhibition of GDH at high ammonia concentrations increases ammonia-induced cytotoxicity (Supplementary Fig. 12B). These results show that the catalytic direction of GDH reverses a clearly becomes ammonia consuming also in hepatocytes in order to compensate the compromised metabolism by urea cycle enzymes and GS after intoxication.

Further evidence emerges from simulations with a set of novel models 1-4 (Supplementary Fig. 11). If a reversible GDH reaction was integrated into the hepatocyte compartment (Fig. 5A; Supplementary Fig. 11), the discrepancy between *in vivo* measured and simulated ammonia concentrations (Fig. 1C) completely disappeared (Fig. 5B). The quantitative agreement was obtained even without considering the blood compartment of the liver, suggesting that after CCl₄-induced damage, the ammonia consumption catalyzed by GDH in the hepatocytes represents the missing ammonia sink predicted by [4].

Therapy of hyperammonemia based on the reverse GDH reaction

The above described ammonia consumption catalyzed by the GDH reaction (Figs. 3B-D and 4) and the aforementioned decrease in plasma α-KG levels (Fig. 3A) prompted us to test whether supplementation of α-KG in mice helps to detoxify ammonia. Therefore, mice received a hepatotoxic dose of CCl₄ (1.6 g/kg) and 24 h later α-KG (280 mg/kg) was injected into the tail vein. Blood was collected immediately before as well as 15, 30 and 60 min after injection of α-KG. A decrease in plasma ammonia concentrations by 31, 40 and 43% was observed 15, 30 and 60 min after α-KG injection, respectively (Fig. 6A). Glutamate increased after 15 min and decreased again after longer periods probably due to the consumption by further metabolism. α-KG transiently increased in plasma after injection and then rapidly decreased. Analysis of GDH activity demonstrated that the experiment was performed under conditions of high plasma activity. In control mice, injection of α-KG did not alter blood concentrations of ammonia or glutamate (Fig. 6B). In addition, plasma α-KG levels were lower in CCl₄-treated mice compared to the control mice, suggesting increased consumption in mice with damaged livers.

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**Fig. 1. Evidence for a so far unrecognized mechanism of ammonia detoxification.** (A) Experimental design. (B) Ammonia concentrations in the portal vein, hepatic vein and heart. *p* < 0.05 compared to the corresponding controls (0 h). (C) Integrated metabolic spatio-temporal model using the technique described by [4] (video in the Supplementary data). Predicted ammonia concentrations in the liver outflow are higher compared to the experimental data. ***p* < 0.001, **p* < 0.01 and *p* < 0.05 compared to the measured ammonia output. (D) Dose dependent experiment (10.9 to 1600 mg/kg CCl₄ 24 h after administration) showing macroscopic alterations with a spotted pattern at 132.4 mg/kg and higher doses, corresponding to the central necrotic lesion in hematoxylin/eosin staining, scale bars: 100 µm. Destruction of the pericentral CYP2E1 positive region which begins at 132.4 mg/kg with central necrosis still surrounded by CYP2E1 positive surviving hepatocytes; the entire CYP2E1 positive region was destroyed at the highest dose of 1600 mg/kg. The GS positive region was destroyed only at 132.4 mg/kg and higher doses, which corresponds to the decrease in GS activity (E), scale bars: 200 µm. *p* < 0.05 when compared to the control group (0). (F) Comparison of analyzed and simulated ammonia concentrations in the liver vein for the experiment in (D); meas, in; analyzed concentrations in the portal vein (representing 85% of the liver inflow) and heart blood (representing 15% of the liver inflow); meas. out; analyzed concentrations in the liver vein; sim. out; simulated concentrations in the liver vein. Data are mean values and SD of three mice per time point and dose of CCl₄. ***p* < 0.001 and **p* < 0.01 compared to the measured ammonia output.
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C

<table><thead><tr><th colspan="2">KEGG nitrogen metabolism</th><th colspan="8">Time after CCl<sub>4</sub> administration</th></tr><tr><th>Symbol</th><th>Name</th><th>Healthy liver</th><th>Hour 2</th><th>Hour 8</th><th>Day1</th><th>Day 2</th><th>Day 4</th><th>Day 6</th><th>Day 8</th><th>Day 16</th></tr></thead><tbody><tr><td>Car1</td><td>Carbonic anhydrase 1</td><td>1</td><td>-1.12</td><td>-1.78</td><td>-2.42</td><td>-1.85</td><td>-1.11</td><td>1.1</td><td>1.15</td><td>1.02</td></tr><tr><td>Car3</td><td>Carbonic anhydrase 3</td><td>1</td><td>-2.94</td><td>-4.51</td><td>-32.55</td><td>-4.47</td><td>-1.33</td><td>-1.74</td><td>-1.71</td><td>-1.41</td></tr><tr><td>Car5a</td><td>Carbonic anhydrase 5a, mitochondrial</td><td>1</td><td>-1.64</td><td>-4</td><td>-4.44</td><td>-1.96</td><td>1.1</td><td>-1.17</td><td>1.02</td><td>-1.1</td></tr><tr><td>Cth</td><td>Cystathionase (cystathionine γ-lyase)</td><td>1</td><td>-1.28</td><td>-1.95</td><td>-2.59</td><td>-2.03</td><td>1.35</td><td>-1.08</td><td>-1.04</td><td>-1.09</td></tr><tr><td>Gls2</td><td>Glutaminase 2 (liver, mitochondrial)</td><td>1</td><td>-1.65</td><td>-2.44</td><td>-3.71</td><td>-2.13</td><td>-1.06</td><td>-1.26</td><td>-1.01</td><td>-1.14</td></tr><tr><td>Glul</td><td>Glutamate-ammonia ligase (glutamine synthetase)</td><td>1</td><td>1.13</td><td>-1.84</td><td>-5.82</td><td>-4.85</td><td>-2.36</td><td>-1.02</td><td>-1.27</td><td>-1.08</td></tr><tr><td>Hal</td><td>Histidine ammonia lyase</td><td>1</td><td>-1.71</td><td>-3.09</td><td>-3.86</td><td>-2.11</td><td>1.05</td><td>-1.37</td><td>1.14</td><td>1</td></tr></tbody></table>

D

<table><thead><tr><th colspan="2">GO urea cycle/urea metab. process</th><th colspan="8">Time after CCl<sub>4</sub> administration</th></tr><tr><th>Symbol</th><th>Name</th><th>Healthy liver</th><th>Hour 2</th><th>Hour 8</th><th>Day 1</th><th>Day 2</th><th>Day 4</th><th>Day 6</th><th>Day 8</th><th>Day 16</th></tr></thead><tbody><tr><td>Aldh6a1</td><td>Aldehyde dehydrogenase family 6, subfamily A1</td><td>1</td><td>-1.15</td><td>-1.63</td><td>-2.33</td><td>-2.09</td><td>-1.24</td><td>1.02</td><td>1.02</td><td>-1.03</td></tr><tr><td>Dpyd</td><td>Dihydropyrimidine dehydrogenase</td><td>1</td><td>-1.28</td><td>-1.71</td><td>-2.63</td><td>-2.15</td><td>-1.27</td><td>-1.08</td><td>1.07</td><td>-1.02</td></tr><tr><td>Dpys</td><td>Dihydropyrimidinase</td><td>1</td><td>-1.26</td><td>-2.91</td><td>-3.35</td><td>-1.87</td><td>-1.08</td><td>-1.01</td><td>-1.05</td><td>-1.12</td></tr><tr><td>Asl</td><td>Argininosuccinate lyase</td><td>1</td><td>1.06</td><td>1.5</td><td>-2.12</td><td>-1.74</td><td>-1.13</td><td>-1.13</td><td>-1.05</td><td>-1.09</td></tr><tr><td>Cebpa</td><td>CCAAT/enhancer binding protein (C/EBP), alpha</td><td>1</td><td>-1.25</td><td>-1.35</td><td>-2.07</td><td>-1.4</td><td>1.06</td><td>1.14</td><td>1.05</td><td>-1.07</td></tr><tr><td>Otc</td><td>Ornithine transcarbamylase</td><td>1</td><td>-1.22</td><td>-1.89</td><td>-3.26</td><td>-2.14</td><td>1.06</td><td>-1.08</td><td>1.01</td><td>-1.01</td></tr></tbody></table>

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<figure><img src="image_15.png" /><figcaption>**Fig. 2.** Spatio-temporal alterations of ammonia metabolizing enzymes after CCl₄ intoxication. (A) Experimental design. (B) Time dependent changes of gene expression in fuzzy cluster 4 from [6]. The dots correspond to the average of the mean scaled values for all 310 genes, between their respective maximal and minimal expression levels at each time point, using healthy liver (time 0) as reference. Error bars indicate standard error. (C) Changes in expression of genes associated to the KEGG terms ammonia/nitrogen metabolism (Gene Ontology [GO] ID 910) as revealed by KEGG pathways enrichment analysis in fuzzy cluster 4 (p = 2.36 × 10⁻⁷). (D) Changes in the expression of genes associated to the GO terms 'urea cycle/urea metabolic process' (Gene Ontology ID 0000050 and 0019627 respectively) as revealed by GO enrichment analysis in fuzzy cluster 4 (p = 3.83 × 10⁻⁴). In C and D, the values indicate fold of expression over healthy liver at each time point after CCl₄ administration, and correspond to the average of 5 independent biological replicates. Time course of GS RNA levels, GS activity (E) and immunostaining (F), Scale bars: 200 µm. *p* < 0.05 when compared to the control group (0 h).</figcaption></figure>
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**Fig. 3. Detoxification of ammonia by a reverse GDH reaction.** (A) After induction of liver damage by CCl₄, plasma activity of GDH transiently increases. This is accompanied by a decrease in alpha-ketoglutarate (α-KG) and an increase in glutamate. \*p <0.05 when compared to the corresponding control (0 h). Similar results were observed in liver tissue (Supplementary Tables 1 and 2). (B) Validation of the reverse GDH reaction using an inhibitor of GDH (PDAC). Plasma of mice 24 h after CCl₄ injection was analyzed. α-KG was added alone or in combination with AOA, NADPH, GDH and PDAC. \*\*\*p <0.001, \*\*p <0.01 and \*p <0.05 when compared to controls (0). (C) A similar experimental design was chosen as in B. However, 600 µM ammonia was added to also test the reaction at a higher but still clinically relevant concentration. α-KG decreases ammonia and increases glutamate concentrations, which can be blocked by the GDH inhibitor, PDAC. \*\*\*p <0.001, \*\*p <0.01 and \*p <0.05 when compared to the NH₄Cl group (0 h). Data are mean values and SD of 3 biological replicas. (D) Concept of the reverse glutamate dehydrogenase (GDH) reaction. In normal periportal hepatocytes, GDH generates ammonia, which is detoxified by the urea cycle. In pericentral hepatocytes, GDH generates glutamate which is required as a substrate for the GS reaction to form glutamine (Gln). Biosynthesis of α-KG takes place in the periportal hepatocytes; α-KG is then partially exported and taken up again by the pericentral hepatocytes, where it is needed for GS [25,26]. After induction of liver damage, the expression of urea cycle enzymes decreased and the pericentral region with GS is completely destroyed. This leads to increased blood ammonia concentrations. However, also GDH is released from damaged hepatocytes and catalyzes a reaction in blood consuming ammonia and α-KG to generate glutamate (Glu). This reaction can go until α-KG in blood is consumed. In this situation α-KG and NADPH should be therapeutically substituted.
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<figure><img src="image_20.png" /><figcaption>**Fig. 4.** Ammonia consumption by GDH in primary mouse hepatocytes. Hepatocytes were isolated from CCl₄ (1.6 g/kg) intoxicated (day 1) and untreated mice and suspended at a concentration of 2 million hepatocytes/ml for 1 h with different concentrations of ammonia. (A) Inhibition of GDH activity by PDAC. (B) Compromised ammonia detoxification after GDH inhibition. (C) Reduced glutamate production by GDH inhibition. **\*\*\*p < 0.001, \*\*p < 0.01 and \*p < 0.05 compared to – PDAC. \*\*\*p < 0.01 and \*\*p < 0.05 compared to hepatocytes from untreated mice. (D & E) compromised urea and glutamine production by hepatocytes of CCl₄ intoxicated mice. **\*\*p < 0.01 and \*\*p < 0.05 compared to hepatocytes from untreated mice. Data are mean values and SD of three independent experiments.</figcaption></figure>

<figure><img src="image_21.png" /><figcaption>**Fig. 5.** Integration of the GDH reaction into the metabolic model. (A) Scheme of the metabolic reactions and zones of the extended model including GDH in the blood of the liver and hepatocytes. (B) The model extension leads to a better fit between simulated and experimental data.</figcaption></figure>

In the aforementioned experiment, the molar amount of glutamate produced in the damaged liver after α-KG injection was higher than ammonia consumption (Fig. 6A). Therefore, the results cannot only be explained by the reverse GDH reaction, but may be due to the consumption of α-KG by transaminases that contribute to the generation of glutamate. Indeed, tail vein injection of the transaminases inhibitor AOA prior to α-KG injection reduced the production of glutamate (Fig. 6C) and improved ammonia detoxification. The efficiency of transaminases inhibition by AOA *in vivo* has been confirmed in preliminary experiments (Supplementary Figs. 13 and 14).

The reverse GDH reaction requires NADPH as a cofactor; however, NADPH concentrations are very low in blood. To determine how NADPH levels are altered in our model of liver damage, both NADPH and its oxidized form NADP⁺ were analyzed. Blood con-

centrations of both NADPH and NADP⁺ increased after induction of liver damage by CCl₄ (Supplementary Fig. 15A). In addition, an enhanced NADP⁺/NADPH⁻ ratio was observed in both blood and liver tissue (Supplementary Fig. 15B). This increase in NADP⁺/NADPH⁻ ratio fits to a switch in the GDH reaction from NADPH generation to NADPH consumption. Despite the increase in NADPH after induction of liver damage, the concentrations are still relatively low. Therefore, to study the influence of NADPH, plasma from mice collected 24 h after CCl₄ injection was incubated with varying concentrations of NADPH in the presence of NH₄Cl (1 mM), α-KG (3 mM), AOA (1 mM) and GDH (12,000 U/l) for one hour. A concentration dependent decrease in plasma ammonia and an increase in glutamate were observed with increasing concentrations of NADPH (Fig. 7A). A similar trend for ammonia and glutamate was observed with increasing concentrations of α-KG and GDH (Fig. 7B, C). Moreover, addition of AOA reduced both ammonia and glutamate concentrations (Supplementary Fig. 16). To understand how the orientation of the GDH reaction is controlled by ammonia and glutamate concentrations, titration experiments were performed, which indicated that GDH significantly consumes ammonia beginning at concentrations of 150 µM and higher (Fig. 7D). In contrast, unphysiologically high concentrations of more than 10 mM glutamate were required to block the reaction (Fig. 7E).

Based on these *in vitro* optimized concentrations, we designed an *in vivo* study to treat hyperammonemia in mice. After the induction of liver damage by CCl₄, transaminases activities were inhibited by AOA (13 mg/kg; tail vein injection; 24 h after CCl₄ administration). Thirty minutes later a cocktail of α-KG (280 mg/kg), GDH (720 U/kg) and NADPH (180 mg/kg) was intravenously injected. A dose of 280 mg/kg α-KG was chosen because

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<figure><img src="image_22.png" /><figcaption>**Fig. 6.** Reduction of blood ammonia concentrations by α-KG. (A) Tail vein injection of 280 mg/kg α-KG into mice 24 h after induction of liver damage by CCl₄ (1.6 g/kg). (B) Control experiment with α-KG (280 mg/kg) injected into the tail vein of untreated mice. \*\*\*p < 0.001, \*\*p < 0.01 and \*p < 0.05 when compared to the control group (0). (C) Influence of the transaminase inhibitor, AOA (13 mg/kg; tail vein injection) on ammonia detoxification by α-KG. \*\*p < 0.01 and \*p < 0.05 when compared to the corresponding control. Data are mean values and SD of three mice treated at different experimental days with individually prepared α-KG.</figcaption></figure>

it transiently normalized α-KG levels in mice 24 h after CCl₄-720 U/kg GDH was used because it resulted in plasma levels of approximately 6000 U/l 15 min after injection (Supplementary Fig. 17), an activity level shown to allow maximal ammonia consumption in plasma *in vitro* (Fig. 7C). The dose of 180 mg/kg NADPH was also considered as adequate in a pharmacokinetic experiment (Supplementary Fig. 18) as it transiently increased plasma NADPH to approximately 1.6 mM 2 min after injection. Injection of the α-KG/GDH/NADPH cocktail (KGN cocktail) reduced ammonia concentrations from 213 to 74 µM within 15 min after administration (Fig. 8). Simultaneously, glutamate levels increased from 131 to 369 µM. Analysis of α-KG and GDH activity in the plasma showed that substitution was successful 15 min after the injection of the KGN cocktail. Moreover, the activities of aspartate and alanine aminotransferase were successfully inhibited by AOA. The mice were observed for three weeks after the experiment and did not show any complications.

Discussion

Guided by simulations with an IM predicting a missing ammonia sink after severe CCl₄-induced liver damage, we identified the GDH reaction as fundamental for ammonia consumption, which

can be used therapeutically by the administration of a cocktail of GDH and cofactors.

Therapy for hyperammonemia remains challenging [8–10]. Hemodialysis is the most efficient treatment for reducing elevated blood ammonia concentrations [11,12]. For milder forms of hyperammonemia, pharmacologic management is possible [13]. Efficient strategies for patients with urea cycle defects include infusion of phenylacetate or benzoate. Phenylacetate combines with glutamine to form a product which can be excreted by the kidneys [9,13,14]. Conversely, benzoate combines with glycine to form hippurate, which is also excreted in urine [13,15]. Both compounds reduce the total body nitrogen content; however, this therapy has also failed in a fraction of patients with hyperammonemic crisis who became refractory most probably due to the accumulation of nitrogen waste [9]. This led to the concept that only blood ammonia concentrations below 500 µM should be treated pharmacologically; whereas, more severe hyperammonemia requires aggressive interventions with renal replacement therapies, such as hemodialysis [12,16]. In such situations with either severe or refractory hyperammonemia the therapeutic strategy developed in the present study may be an alternative to hemodialysis.

The current experiments demonstrate that infusion of a KGN-cocktail reduces ammonia close to normal levels within minutes.

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<figure><img src="image_23.png" /><figcaption>**Fig. 7. Optimization of cofactor concentrations for the GDH reaction and identification of maximal GDH activity.** (A) NADPH: mouse plasma collected 24 h after CCl₄ injection was incubated with varying concentrations of NADPH in the presence of NH₄Cl (1 mM) and other cofactors; aminooxy acetate (AOA) (1 mM), α-KG (3 mM) and GDH (12,000 U/L) for one hour. (B) Alpha-ketoglutarate (α-KG): plasma was collected from mice on day one after CCl₄ administration and incubated with varying concentrations of α-KG in the presence of NH₄Cl (1 mM) and other cofactors; AOA (1 mM), NADPH (1 mM) and GDH (12,000 U/L). (C) GDH: plasma from mice collected 24 h after CCl₄ injection was incubated with varying concentrations of GDH in the presence of NH₄Cl (1 mM) and other cofactors; AOA (1 mM), α-KG (3 mM), and NADPH (1 mM) for one hour. ***p < 0.001, **p < 0.01 and *p < 0.05 compared to the situation where the plasma was incubated with only NH₄Cl. (D) Ammonia detoxification by the cocktail. Different ammonia concentrations were added to plasma of untreated mice and a cocktail of α-KG (3 mM), NADPH (0.5 mM), GDH (6000 U/L) and AOA (1 mM) was added to analyze ammonia and glutamate one hour later. ***p < 0.001, **p < 0.01 and *p < 0.05 compared – cocktail. (E) Ammonia (600 µM) detoxification by the cocktail was only blocked by unphysiologically high glutamate concentrations. ***p < 0.001 compared to NH₄Cl alone. Data are mean values and SD of three biological replicas.</figcaption></figure>

Under these conditions, a GDH-catalyzed reaction takes place in blood where ammonia and α-KG are consumed to form glutamate in an NADPH-dependent reaction. GDH was also previously reported to switch its catalytic orientation under physiological conditions. In the periportal compartment of the liver lobule, GDH generates ammonia (Fig. 3D), which fuels the urea cycle. In the pericentral compartment, GDH is known to consume ammonia to generate glutamate for the GS reaction [17–19].

The present study shows by use of a GDH inhibitor that GDH released from damaged liver tissue may catalyze an ammonia consuming reaction under conditions of hyperammonemia. By releasing GDH from damaged hepatocytes into the blood, the damaged liver provides a mechanism that reduces blood ammonia levels. However, this protective mechanism is limited by the availability of the GDH substrate, α-KG. The present study shows that α-KG strongly decreases upon induction of acute liver dam-

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<figure><img src="image_24.png" /><figcaption>**Fig. 8.** Treatment of hyperammonemia by injection of a cocktail of GDH and optimized cofactor doses. A cocktail of GDH (720 U/kg), α-KG (280 mg/kg) and NADPH (180 mg/kg) (KGN) was injected into mice 24 h after induction of liver damage using CCl₄ (1.6 g/kg). Thirty minutes prior to treatment with the cocktail, mice received a single dose of 13 mg/kg AOA to block transaminases. Injection of the KGN cocktail reduced ammonia and increased glutamate concentrations in the blood of mice. α-KG and GDH activity increased while aspartate (AST) and alanine aminotransferase (ALT) activities decreased. Data are mean values and SD of four mice treated at different experimental days with individually prepared therapeutic cocktails. **\*\*\*p** < 0.001, **\*p** < 0.01 and \*p < 0.05 when compared to the control group (−30).</figcaption></figure>

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age, because it is consumed by the reverse GDH reaction. This prompted us to supplement α-KG, increase blood concentrations of NADPH, and infuse GDH. Indeed, the combined injection of α-KG, GDH and NADPH efficiently reduced blood ammonia concentrations. A GDH bolus was injected to result in plasma peak concentrations between 5000 and 6000 U/L. This is in the same order of magnitude as observed in patients after acetaminophen intoxication [20]. Therefore, in patients with acute liver intoxication with high blood GDH, therapy with α-KG and NADPH might be sufficient. However, it should be considered that the GDH reaction in blood described here (Fig. 3D) does not explain all experimental observations: α-KG decreases significantly 12 h after CCl₄ administration when there is no significant increase in blood GDH (Fig. 3A). This discrepancy may be explained by the intracellular change of the catalytic direction of GDH in the periportal hepatocytes, which may precede the GDH release into the blood. However, this was not further analyzed in the present study as

we choose to focus on the therapeutically more relevant GDH reaction taking place in blood. 420 421

α-KG was previously tested for the treatment of hyperammonemia between 1964 and 1978 [21,22], but this strategy was abandoned because it was not sufficiently efficient for clinical application. The reverse GDH reaction in the blood and its requirement for NADPH as a cofactor was not yet known when the early therapeutic studies with α-KG were performed. In addition, injection of α-KG alone in the present study resulted in only a relatively weak reduction of hyperammonemia. This reduction may be possible because in addition to GDH, NADPH is also released from deteriorating hepatocytes after CCl₄ injection. 422 423 424 425 426 427 428 429 430 431

The concept of treating hyperammonemia by α-KG/GDH/ NADPH infusion originates from simulations using an integrated metabolic spatio-temporal model [4]. This model is based on well-understood pathways of ammonia detoxification, such as urea cycle enzymes and the GS reaction [23,24]. It predicted higher ammonia concentrations compared to the measured data. Therefore, we analyzed liver tissue during the damage induction and regeneration processes, but the results could also not explain the discrepancy. Time-resolved gene array experiments following CCl₄ injection led to the observation that a general decrease in metabolizing enzymes occurs including enzymes involved in ammonia metabolism. All enzymes of the urea cycle were transcriptionally downregulated by at least 60%. Factors identified by the gene array analysis were further analyzed by activity assays and immunostaining. Key observations were: (a) the GS positive region, which is initially completely destroyed by CCl₄, shows a delayed recovery and does not return to normal levels before day 12; and (b) CPS1, the rate limiting enzyme in the urea cycle normally expressed in the periportal region, is downregulated during the destruction process (days 1–3), but its expression then extends throughout the entire liver lobule during days 4–6. The other urea cycle enzymes showed a similar time course as CPS1 with the exception of arginase1, which decreased only slightly during the destruction and regeneration process. Glutaminase showed a similar time course and pattern as CPS1. Nevertheless, none of these alterations could explain the observed discrepancy. However, the refined models that take into account the reversible GDH reaction show an excellent agreement with the experimental data suggesting that consumption by the GDH reaction represents the previously predicted ammonia sink, hence providing an example for model guided experimentation. 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463

In conclusion, a novel form of therapy has been identified that allows the rapid correction of hyperammonemia by the infusion of α-KG, GDH and NADPH. This pharmacotherapy may prove relevant as an emergency therapy for episodes of hyperammonemia in urea cycle disease or liver cirrhosis. 464 465 466 467 468

Financial support 469

This study was supported by the BMBF funded projects Virtual Liver (FKZ0315739), Lebersimulator and FP 7EU NOTOX. 471

Conflict of interest 472

The authors who have taken part in this study declared that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript. 473 474 475
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<table><tr><td>476</td><td><strong>Authors' contributions</strong></td><td>Ahmed Ghallab: study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; statistical analysis; critical revision of the manuscript.</td></tr><tr><td>479</td><td>480</td><td>Sebastian G. Henkel: mathematical modeling (integrated model of Schliess et al. (2014), model 0 and extrahepatic mass balance); analysis and interpretation of data; drafting of the manuscript</td></tr><tr><td>481</td><td>482</td><td>Géraldine Cellière: mathematical modeling (novel ammonia detoxification models, extension of model 0); analysis and interpretation of data; drafting of the manuscript, statistical analysis.</td></tr><tr><td>483</td><td>484</td><td>Dominik Driesch: mathematical modeling (integrated model of Schliess et al. (2014), model 0 and extrahepatic mass balance); analysis and interpretation of data; drafting of the manuscript.</td></tr><tr><td>485</td><td>486</td><td>Eute Hofmann: acquisition of data; analysis and interpretation of data; technical support; drafting of the manuscript.</td></tr><tr><td>487</td><td>488</td><td>Sebastian Zellmer: study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript.</td></tr><tr><td>489</td><td>490</td><td>Patricio Godoy: acquisition of data; analysis and interpretation of data; drafting of the manuscript.</td></tr><tr><td>491</td><td>492</td><td>Agapios Sachinidis: acquisition of data; analysis and interpretation of data; drafting of the manuscript.</td></tr><tr><td>493</td><td>494</td><td>Meinolf Blaszkewicz: acquisition of data; analysis and interpretation of data; technical support; drafting of the manuscript.</td></tr><tr><td>495</td><td>496</td><td>Raymond Reif: analysis and interpretation of data; drafting of the manuscript.</td></tr><tr><td>497</td><td>498</td><td>Rosemarie Marchan: critical revision of the manuscript.</td></tr><tr><td>499</td><td>500</td><td>Lars Kuepfer: mathematical modeling; drafting of the manuscript.</td></tr><tr><td>501</td><td>502</td><td>Dieter Häussinger: study concept and design; critical revision of the manuscript.</td></tr><tr><td>503</td><td>504</td><td>Dirk Drasdo: study concept and design; mathematical modeling (integrated model of Schliess et al. (2014), model 0 and novel models); analysis and interpretation of data; drafting of the manuscript, statistical analysis, critical revision of the manuscript</td></tr><tr><td>505</td><td>506</td><td>Rolf Gebhardt: study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript, critical revision of the manuscript.</td></tr><tr><td>507</td><td>508</td><td>Jan G. Hengstler: study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript, statistical analysis, critical revision of the manuscript; study supervision.</td></tr><tr><td>509</td><td>510</td><td></td></tr><tr><td>511</td><td>512</td><td></td></tr><tr><td>513</td><td>514</td><td></td></tr><tr><td>515</td><td>516</td><td></td></tr><tr><td>517</td><td>518</td><td></td></tr><tr><td>519</td><td>520</td><td></td></tr><tr><td>521</td><td>522</td><td></td></tr><tr><td>523</td><td>524</td><td></td></tr><tr><td>525</td><td>526</td><td></td></tr><tr><td>527</td><td>528</td><td></td></tr><tr><td>529</td><td><strong>Acknowledgments</strong></td><td>We thank Mrs. Gabi Baumhoer, Mrs. Georgia Günther and Mrs. Brigitte Begher-Tibbe – Leibniz Research Centre for Working Environment and Human Factors at the Technical University Dortmund, Dortmund, Germany; and Ms. Margit Henry and Ms. Tamara Rotsheyn – Institute of Neurophysiology and Center</td></tr></table>

for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany – for competent technical assistance.

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**Supplementary data**

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Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jhep.2015.11.018.

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**References**

541

*Author names in bold designate shared co-first authorship*

542

[1] Drasdo D, Hoehme S, Hengstler JG. How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis. J Hepatol 2014;61:951-956.

543
544
545

[2] Zellmer S, Schmidt-Heck W, Godoy P, Weng H, Meyer C, Lehmann T, et al. Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytes. Hepatology 2010;52:2127-2136.

546
547
548
549

[3] Godoy P, Hewitt NJ, Albrecht U, Andersen ME, Ansari N, Bhattacharya S, et al. Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Arch Toxicol 2013;87:1315-1530.

550
551
552
553

[4] Schliess F, Hoehme S, Henkel SG, Ghallab A, Driesch D, Bottger J, et al. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration. Hepatology 2014;60:2040-2051.

554
555
556
557

[5] Hoehme S, Brulport M, Bauer A, Bedawy E, Schormann W, Hermes M, et al. Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc Natl Acad Sci U S A 2010;107:10371-10376.

558
559
560
561

[6] Campos G, Schmidt-Heck W, Ghallab A, Rochlitz K, Putter L, Medinas DB, et al. The transcription factor CHOP, a central component of the transcriptional regulatory network induced upon CCl4 intoxication in mouse liver, is not a critical mediator of hepatotoxicity. Arch Toxicol 2014;88:1267-1280.

563
564
565
566
567

[7] Gebhardt R, Baldysiak-Figiel A, Krugel V, Ueberham E, Gaunitz F. Hepatocellular expression of glutamine synthetase: an indicator of morphogen actions as master regulators of zonation in adult liver. Prog Histochem Cytochem 2007;41:201-266.

568
569
570
571

[8] Levesque R, Leblanc M, Cardinal J, Teitlebaum J, Skrobik Y, Lebrun M. Haemodialysis for severe hyperammonaemic coma complicating urinary diversions. Nephrol Dial Transplant 1999;14:458-461.

572
573
574

[9] Enns GM, Berry SA, Berry GT, Rhead WJ, Brusilow SW, Hamosh A. Survival after treatment with phenylacetate and benzoate for urea-cycle disorders. N Engl J Med 2007;356:2282-2292.

575
576
577

[10] Poh Z, Chang PE. A current review of the diagnostic and treatment strategies of hepatic encephalopathy. Int J Hepatol 2012;2012 480309.

578
579

[11] Clay AS, Hainline BE. Hyperammonemia in the ICU. Chest 2007;132:1368-1378.

580
581

[12] Rajpoot DK, Gargus JJ. Acute hemodialysis for hyperammonemia in small neonates. Pediatr Nephrol 2004;19:390-395.

582
583

[13] Summar M. Current strategies for the management of neonatal urea cycle disorders. J Pediatrics 2001;138:S30-S39.

584
585

[14] Honda S, Yamamoto K, Sekizuka M, Oshima Y, Nagai K, Hashimoto G, et al. Successful treatment of severe hyperammonemia using sodium phenylacetate powder prepared in hospital pharmacy. Biol Pharm Bull 2002;25:1244-1246.

586
587
588
589

[15] Misel ML, Gish RG, Patton H, Mendler M. Sodium benzoate for treatment of hepatic encephalopathy. Gastroenterol Hepatol 2013;9:219-227.

590
591

[16] Collen JF, Das NP, Koff JM, Neff RT, Abbott KC. Hemodialysis for hyperammonemia associated with ornithine transcarbamylase deficiency. Appl Clin Genet 2008;1:1-5.

592
593
594

[17] Boon L, Geerts WJ, Jonker A, Lamers WH, Van Noorden CJ. High protein diet induces pericentral glutamate dehydrogenase and ornithine aminotransferase to provide sufficient glutamate for pericentral detoxification of ammonia in rat liver lobules. Histochem Cell Biol 1999;111:445-452.

595
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597
598
Research Article

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

[18] Sies H, Häussinger D, Grosskopf M. Mitochondrial nicotinamide nucleotide systems: ammonium chloride responses and associated metabolic transitions in hemoglobin-free perfused rat liver. Hoppe Seylers Z Physiol Chem 1974;355:305-320.

[19] Spanaki C, Plaitakis A. The role of glutamate dehydrogenase in mammalian ammonia metabolism. Neurotox Res 2012;21:117-127.

[20] McGill MR, Sharpe MR, Williams CD, Taha M, Curry SC, Jaeschke H. The mechanism underlying acetaminophen-induced hepatotoxicity in humans and mice involves mitochondrial damage and nuclear DNA fragmentation. J Clin Invest 2012;122:1574-1583.

[21] Meuret G, Beck K, Keul J, Gruenagel HH. On therapy of hepatic coma with metabolites of the urea cycle, glutamate and alpha-ketoglutarate. Dtsch Med Wochenschr 1968;93:1194-1197.

[22] Wildhirt E. The terminal stage of liver diseases and hepatic coma. Der Internist 1965;6:439-446.

[23] Gebhardt R, Mecke D. Heterogeneous distribution of glutamine synthetase among rat liver parenchymal cells in situ and in primary culture. EMBO J 1983;2:567-570.

[24] Häussinger D. Hepatocyte heterogeneity in glutamine and ammonia metabolism and the role of an intercellular glutamine cycle during ureogenesis in perfused rat liver. Eur J Biochem 1983;133:269-275.

[25] Stoll B, Häussinger D. Hepatocyte heterogeneity in uptake and metabolism of malate and related dicarboxylates in perfused rat liver. Eur J Biochem 1991;195:121-129.

[26] Stoll B, McNelly S, Buscher HP, Häussinger D. Functional hepatocyte heterogeneity in glutamate, aspartate and alpha-ketoglutarate uptake: a histoautoradiographical study. Hepatology 1991;13:247-253.

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