PDF(Pubmed)
Abstract：
Omics techniques have been increasingly recognized as promising tools for Next Generation Risk Assessment. Targeted metabolomics offer the advantage of providing readily interpretable mechanistic information about perturbed biological pathways. In this study, a high-throughput LC-MS/MS-based broad targeted metabolomics system was applied to study nitrofurantoin metabolic dynamics over time and concentration and to provide a mechanistic-anchored approach for point of departure (PoD) derivation. Upon nitrofurantoin exposure at five concentrations (7.5 µM, 15 µM, 20 µM, 30 µM and 120 µM) and four time points (3, 6, 24 and 48 h), the intracellular metabolome of HepG2 cells was evaluated. In total, 256 uniquely identified metabolites were measured, annotated, and allocated in 13 different metabolite classes. Principal component analysis (PCA) and univariate statistical analysis showed clear metabolome-based time and concentration effects. Mechanistic information evidenced the differential activation of cellular pathways indicative of early adaptive and hepatotoxic response. At low concentrations, effects were seen mainly in the energy and lipid metabolism, in the mid concentration range, the activation of the antioxidant cellular response was evidenced by increased levels of glutathione (GSH) and metabolites from the de novo GSH synthesis pathway. At the highest concentrations, the depletion of GSH, together with alternations reflective of mitochondrial impairments, were indicative of a hepatotoxic response. Finally, a metabolomics-based PoD was derived by multivariate PCA using the whole set of measured metabolites. This approach allows using the entire dataset and derive PoD that can be mechanistically anchored to established key events. Our results show the suitability of high throughput targeted metabolomics to investigate mechanisms of hepatoxicity and derive point of departures that can be linked to existing adverse outcome pathways and contribute to the development of new ones.
摘要：
组学技术越来越被认为是下一代风险评估的有前途的工具。靶向代谢组学提供了提供关于扰动的生物途径的容易解释的机械信息的优点。在这项研究中,基于高通量LC-MS/MS的广泛靶向代谢组学系统被用于研究呋喃妥因随时间和浓度的代谢动力学,并为出发点(PoD)推导提供一种机制锚定方法.在五个浓度(7.5µM，15µM,20µM,30µM和120µM）和四个时间点（3、6、24和48h），评估了HepG2细胞的细胞内代谢组。总的来说,测量了256种独特鉴定的代谢物，注释，并分配给13种不同的代谢物类别。主成分分析（PCA）和单变量统计分析显示出明显的基于代谢组的时间和浓度效应。机制信息证明了指示早期适应性和肝毒性反应的细胞途径的差异激活。在低浓度下,影响主要表现在能量和脂质代谢，在中等浓度范围内，抗氧化剂细胞反应的激活由谷胱甘肽(GSH)和来自从头GSH合成途径的代谢物水平的增加证明。在最高浓度下，GSH的耗尽，连同反映线粒体损伤的变化，指示肝毒性反应。最后,基于代谢组学的PoD是通过多变量PCA使用整套测量的代谢物得出的.这种方法允许使用整个数据集并导出可以机械地锚定到已建立的关键事件的PoD。我们的结果表明，高通量靶向代谢组学适合研究肝毒性机制，并得出可以与现有不良结果途径相关并有助于开发新途径的偏离点。
