Bartl Martin, Pfaff Michael, Ghallab Ahmed, Driesch Dominik, Henkel Sebastian G, Hengstler Jan G, Schuster Stefan, Kaleta Christoph, Gebhardt Rolf, Zellmer Sebastian, Li Pu
Research Group Theoretical Systems Biology, Friedrich Schiller University Jena, Leutragraben 1, 07743, Jena, Germany.
BioControl Jena GmbH, Wildenbruchstr. 15, 07745, Jena, Germany.
Arch Toxicol. 2015 Nov;89(11):2069-78. doi: 10.1007/s00204-015-1596-4. Epub 2015 Oct 5.
The rodent liver eliminates toxic ammonia. In mammals, three enzymes (or enzyme systems) are involved in this process: glutaminase, glutamine synthetase and the urea cycle enzymes, represented by carbamoyl phosphate synthetase. The distribution of these enzymes for optimal ammonia detoxification was determined by numerical optimization. This in silico approach predicted that the enzymes have to be zonated in order to achieve maximal removal of toxic ammonia and minimal changes in glutamine concentration. Using 13 compartments, representing hepatocytes, the following predictions were generated: glutamine synthetase is active only within a narrow pericentral zone. Glutaminase and carbamoyl phosphate synthetase are located in the periportal zone in a non-homogeneous distribution. This correlates well with the paradoxical observation that in a first step glutamine-bound ammonia is released (by glutaminase) although one of the functions of the liver is detoxification by ammonia fixation. The in silico approach correctly predicted the in vivo enzyme distributions also for non-physiological conditions (e.g. starvation) and during regeneration after tetrachloromethane (CCl4) intoxication. Metabolite concentrations of glutamine, ammonia and urea in each compartment, representing individual hepatocytes, were predicted. Finally, a sensitivity analysis showed a striking robustness of the results. These bioinformatics predictions were validated experimentally by immunohistochemistry and are supported by the literature. In summary, optimization approaches like the one applied can provide valuable explanations and high-quality predictions for in vivo enzyme and metabolite distributions in tissues and can reveal unknown metabolic functions.
啮齿动物的肝脏可清除有毒氨。在哺乳动物中，三种酶（或酶系统）参与这一过程：谷氨酰胺酶、谷氨酰胺合成酶以及以氨甲酰磷酸合成酶为代表的尿素循环酶。通过数值优化确定了这些酶为实现最佳氨解毒的分布情况。这种计算机模拟方法预测，这些酶必须分区排列，以实现有毒氨的最大清除以及谷氨酰胺浓度的最小变化。使用代表肝细胞的13个区室，得出了以下预测结果：谷氨酰胺合成酶仅在狭窄的中央周围区具有活性。谷氨酰胺酶和氨甲酰磷酸合成酶以非均匀分布位于门静脉周围区。这与一个看似矛盾的观察结果密切相关，即尽管肝脏的功能之一是通过氨固定进行解毒，但在第一步中谷氨酰胺结合的氨会被释放（通过谷氨酰胺酶）。这种计算机模拟方法还正确预测了非生理条件（如饥饿）以及四氯化碳（CCl4）中毒后再生过程中的体内酶分布情况。预测了代表单个肝细胞的每个区室中谷氨酰胺、氨和尿素的代谢物浓度。最后，敏感性分析表明结果具有显著的稳健性。这些生物信息学预测通过免疫组织化学实验得到了验证，并得到了文献的支持。总之，像本文所应用的这种优化方法可以为组织中的体内酶和代谢物分布提供有价值的解释和高质量的预测，并能揭示未知的代谢功能。
