Leclerc Eric, Hamon Jeremy, Legendre Audrey, Bois Frederic Y
CNRS UMR 7338, Laboratoire de Biomécanique et Bioingénierie, Université de Technologie de Compiègne, France.
CNRS UMR 7338, Laboratoire de Biomécanique et Bioingénierie, Université de Technologie de Compiègne, France; Chair of Mathematical Modeling for Systems Toxicology, Université de Technologie de Compiègne, Centre de Recherche de Royallieu, 60205 Compiègne Cedex, France.
Toxicol In Vitro. 2014 Oct;28(7):1230-41. doi: 10.1016/j.tiv.2014.05.003. Epub 2014 Jun 12.
We present a systems biology analysis of rat primary hepatocytes response after exposure to 10 μM and 100 μM flutamide in liver microfluidic biochips. We coupled an in vitro pharmacokinetic (PK) model of flutamide to a system biology model of its reactive oxygen species (ROS) production and scavenging by the Nrf2 regulated glutathione production. The PK model was calibrated using data on flutamide kinetics, hydroxyflutamide and glutathione conjugates formation in microfluidic conditions. The parameters of Nrf2-related gene activities and the subsequent glutathione depletion were calibrated using microarray data from our microfluidic experiments and literature information. Following a 10 μM flutamide exposure, the model predicted a recovery time to baseline levels of glutathione (GSH) and ROS in agreement with our experimental observations. At 100 μM, the model predicted that metabolism saturation led to an important accumulation of flutamide in cells, a high ROS production and complete GSH depletion. The high levels of ROS predicted were consistent with the necrotic switch observed by transcriptomics, and the high cell mortality we had experimentally observed. The model predicted a transition between recoverable GSH depletion and deep GSH depletion at about 12.5 μM of flutamide (single perfusion exposure). Our work shows that in vitro biochip experiments can provide supporting information for complex in silico modeling including data from extra cellular and intra cellular levels. We believe that this approach can be an efficient strategy for a global integrated methodology in predictive toxicology.
我们展示了在肝微流控生物芯片中,大鼠原代肝细胞暴露于10μM和100μM氟他胺后的系统生物学分析。我们将氟他胺的体外药代动力学(PK)模型与通过Nrf2调节谷胱甘肽生成的活性氧(ROS)产生和清除的系统生物学模型相结合。PK模型使用微流控条件下氟他胺动力学、羟基氟他胺和谷胱甘肽共轭物形成的数据进行校准。Nrf2相关基因活性参数以及随后的谷胱甘肽消耗使用我们微流控实验的微阵列数据和文献信息进行校准。在暴露于10μM氟他胺后,该模型预测谷胱甘肽(GSH)和ROS恢复到基线水平的时间与我们的实验观察结果一致。在100μM时,该模型预测代谢饱和导致氟他胺在细胞中大量积累、大量ROS产生和GSH完全消耗。预测的高ROS水平与转录组学观察到的坏死转变以及我们实验观察到的高细胞死亡率一致。该模型预测在约12.5μM氟他胺(单次灌注暴露)时,可恢复的GSH消耗和深度GSH消耗之间会发生转变。我们的工作表明,体外生物芯片实验可为复杂的计算机模拟提供支持信息,包括来自细胞外和细胞内水平的数据。我们相信这种方法可以成为预测毒理学中全球综合方法的有效策略。