Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium.
Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Jette, Belgium.
Arch Toxicol. 2018 Oct;92(10):3007-3029. doi: 10.1007/s00204-018-2286-9. Epub 2018 Aug 25.
Omics technologies, and in particular metabolomics, have received an increasing attention during the assessment of hepatotoxicity in vitro. However, at present, a consensus on good metabolomics practices has yet to be reached. Therefore, in this review, a range of experimental approaches, applied methodologies, and data processing workflows are compared and critically evaluated. Experimental designs among the studies are similar, reporting the use of primary hepatocytes or hepatic cell lines as the most frequently used cell sources. Experiments are usually conducted in short time-frames (< 48 h) at sub-toxic dosages. Applied sample preparations are protein precipitation or Bligh-and-Dyer extraction. Most analytical platforms rely on chromatographic separations with mass spectrometric detection using high-resolution instruments. Untargeted metabolomics was typically used to allow the simultaneous detection of several classes of the metabolome, including endogenous metabolites that are not initially linked to toxicity. This non-biased detection platform is a valuable tool for generating hypothesis-based mechanistic research. The most frequently reported metabolites that are altered under toxicological impulses are alanine, lactate, and proline, which are often correlated. Other unspecific biomarkers of hepatotoxicity in vitro are the down-regulation of choline, glutathione, and 3-phospho-glycerate. Disruptions on the Krebs cycle are associated with increased glutamate, tryptophan, and valine. Phospholipid alterations are described in steatosis, lipo-apoptosis, and oxidative stress. Although there is a growing trend towards quality control, data analysis procedures do often not follow good contemporary metabolomics practices, which include feature filtering, false-discovery rate correction, and reporting the confidence of metabolite annotation. The currently annotated biomarkers can be used to identify hepatotoxicity in general and provide, to a certain extent, a tool for mechanistic distinction.
组学技术，特别是代谢组学，在体外评估肝毒性方面受到了越来越多的关注。然而，目前尚未就良好的代谢组学实践达成共识。因此，在这篇综述中，我们比较和批判性地评估了一系列实验方法、应用方法和数据处理工作流程。研究中的实验设计相似，报告使用原代肝细胞或肝细胞系作为最常用的细胞来源。实验通常在亚毒性剂量下进行短时间（<48 小时）。应用的样品制备方法是蛋白质沉淀或布莱和戴耶提取。大多数分析平台依赖于色谱分离，并用高分辨率仪器进行质谱检测。非靶向代谢组学通常用于同时检测代谢组的几个类别，包括最初与毒性无关的内源性代谢物。这种无偏检测平台是生成基于假说的机制研究的有价值工具。在毒性刺激下改变的最常报道的代谢物是丙氨酸、乳酸和脯氨酸，它们通常相关。其他非特异性体外肝毒性生物标志物是胆碱、谷胱甘肽和 3-磷酸甘油酸的下调。三羧酸循环的中断与谷氨酸、色氨酸和缬氨酸的增加有关。磷脂的改变与脂肪变性、脂肪凋亡和氧化应激有关。尽管质量控制的趋势不断增长，但数据分析程序并不总是遵循良好的当代代谢组学实践，包括特征过滤、错误发现率校正以及报告代谢物注释的置信度。目前已注释的生物标志物可用于一般的肝毒性识别，并在一定程度上提供用于机制区分的工具。
