Department of Cell Toxicology, Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318 Leipzig, Germany.
Environmental Toxicology, Department of Geosciences, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
Chem Res Toxicol. 2024 May 20;37(5):744-756. doi: 10.1021/acs.chemrestox.4c00017. Epub 2024 Apr 23.
High-throughput cell-based bioassays are used for chemical screening and risk assessment. Chemical transformation processes caused by abiotic degradation or metabolization can reduce the chemical concentration or, in some cases, lead to the formation of more toxic transformation products. Unaccounted loss processes may falsify the bioassay results. Capturing the formation and effects of transformation products is important for relating the effects to Reporter gene cell lines are believed to have low metabolic activity, but inducibility of cytochrome P450 (CYP) enzymes has been reported. Baseline toxicity is the minimal toxicity a chemical can have and is caused by the incorporation of the chemical into cell membranes. In the present study, we improved an existing baseline toxicity model based on a newly defined critical membrane burden derived from freely dissolved effect concentrations, which are directly related to the membrane concentration. Experimental effect concentrations of 94 chemicals in three bioassays (AREc32, ARE- and GR-) were compared with baseline toxicity by calculating the toxic ratio (TR). CYP activities of all cell lines were determined by using fluorescence-based assays. Only ARE- showed a low basal CYP activity and inducibility and AREc32 showed a low inducibility. Overall cytotoxicity was similar in all three assays despite the different metabolic activities indicating that chemical metabolism is not relevant for the cytotoxicity of the tested chemicals in these assays. Up to 28 chemicals showed specific cytotoxicity with TR > 10 in the bioassays, but baseline toxicity could explain the effects of the majority of the remaining chemicals. Seven chemicals showed TR < 0.1 indicating inaccurate physicochemical properties or experimental artifacts like chemical precipitation, volatilization, degradation, or other loss processes during the bioassay. The new baseline model can be used not only to identify specific cytotoxicity mechanisms but also to identify potential problems in the experimental performance or evaluation of the bioassay and thus improve the quality of the bioassay data.
高通量基于细胞的生物测定法用于化学筛选和风险评估。非生物降解或代谢引起的化学转化过程会降低化学物质浓度，或者在某些情况下，导致形成更具毒性的转化产物。未被考虑到的损失过程可能会使生物测定结果产生偏差。捕捉转化产物的形成和影响对于将影响与报告基因细胞系被认为具有低代谢活性，但已报道细胞色素 P450 (CYP) 酶的诱导性。基线毒性是化学物质所能产生的最小毒性，是由化学物质掺入细胞膜引起的。在本研究中，我们改进了一个现有的基于从自由溶解效应浓度得出的临界膜负荷的基线毒性模型，该模型与膜浓度直接相关。在三个生物测定法（AREc32、ARE-和 GR-）中，通过计算毒性比 (TR) 将 94 种化学物质的实验效应浓度与基线毒性进行了比较。使用基于荧光的测定法测定了所有细胞系的 CYP 活性。只有 ARE-表现出低基础 CYP 活性和诱导性，而 AREc32 表现出低诱导性。尽管代谢活性不同，但所有三个测定法中的总体细胞毒性相似，这表明化学代谢对于这些测定法中测试化学物质的细胞毒性并不重要。在生物测定法中，多达 28 种化学物质显示出特定的细胞毒性，TR > 10，但基线毒性可以解释大多数剩余化学物质的作用。七种化学物质的 TR < 0.1，表明物理化学性质不准确或实验伪影，如在生物测定过程中的化学沉淀、挥发、降解或其他损失过程。新的基线模型不仅可以用于识别特定的细胞毒性机制，还可以用于识别生物测定实验性能或评估中的潜在问题，从而提高生物测定数据的质量。
