Department of Cell Toxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, DE-04318 Leipzig, Germany.
Department of Bioanalytical Toxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, DE-04318 Leipzig, Germany.
Chem Res Toxicol. 2021 Sep 20;34(9):2100-2109. doi: 10.1021/acs.chemrestox.1c00182. Epub 2021 Aug 6.
All chemicals can interfere with cellular membranes and this leads to baseline toxicity, which is the minimal toxicity any chemical elicits. The critical membrane burden is constant for all chemicals; that is, the dosing concentrations to trigger baseline toxicity decrease with increasing hydrophobicity of the chemicals. Quantitative structure-activity relationships, based on hydrophobicity of chemicals, have been established to predict nominal concentrations causing baseline toxicity in human and mammalian cell lines. However, their applicability is limited to hydrophilic neutral compounds. To develop a prediction model that includes more hydrophobic and charged organic chemicals, a mass balance model was applied for mammalian cells (AREc32, AhR-CALUX, PPARγ-BLA, and SH-SY5Y) considering different bioassay conditions. The critical membrane burden for baseline toxicity was converted into nominal concentration causing 10% cytotoxicity by baseline toxicity (IC) using a mass balance model whose main chemical input parameter was the liposome-water partition constants () for neutral chemicals or the speciation-corrected (pH 7.4) for ionizable chemicals plus the bioassay-specific protein, lipid, and water contents of cells and media. In these bioassay-specific models, log(1/IC) increased with increasing hydrophobicity, and the relationship started to level off at log around 2. The bioassay-specific models were applied to 392 chemicals covering a broad range of hydrophobicity and speciation. Comparing the predicted IC and experimental cytotoxicity IC, known baseline toxicants and many additional chemicals were identified as baseline toxicants, while the others were classified based on specificity of their modes of action in the four cell lines, confirming excess toxicity of some fungicides, antibiotics, and uncouplers. Given the similarity of the bioassay-specific models, we propose a generalized baseline-model for adherent human cell lines: log[1/IC (M)] = 1.23 + 4.97 × (1 - e). The derived models for baseline toxicity may serve for specificity analysis in reporter gene and neurotoxicity assays as well as for planning the dosing for cell-based assays.
所有化学物质都可能干扰细胞膜，从而导致基线毒性，即任何化学物质引发的最小毒性。所有化学物质的临界膜负荷是恒定的；也就是说，引发基线毒性的剂量浓度随着化学物质疏水性的增加而降低。已经建立了基于化学物质疏水性的定量构效关系，以预测在人类和哺乳动物细胞系中引起基线毒性的名义浓度。然而，它们的适用性仅限于亲水性中性化合物。为了开发一个包括更多疏水性和带电荷有机化学物质的预测模型，应用质量平衡模型来考虑不同生物测定条件下的哺乳动物细胞（AREc32、AhR-CALUX、PPARγ-BLA 和 SH-SY5Y）。将基线毒性的临界膜负荷转换为通过基线毒性（IC）引起 10%细胞毒性的名义浓度，该模型使用质量平衡模型，其主要化学输入参数是中性化学物质的脂质体-水分配常数（logP）或离子化化学物质的形态校正（pH 7.4）加上生物测定特异性的细胞和培养基中的蛋白质、脂质和水含量。在这些生物测定特异性模型中，log(1/IC)随着疏水性的增加而增加，并且该关系在 log 约 2 时开始趋于平稳。将生物测定特异性模型应用于 392 种涵盖广泛疏水性和形态的化学物质。将预测的 IC 与实验细胞毒性 IC 进行比较，确定了已知的基线毒物和许多其他化学物质为基线毒物，而其他化学物质则根据它们在四种细胞系中的作用模式特异性进行分类，证实了一些杀菌剂、抗生素和解偶联剂的过度毒性。鉴于生物测定特异性模型的相似性，我们提出了一个适用于贴壁人类细胞系的广义基线模型：log[1/IC（M）]=1.23+4.97×（1-e）。推导的基线毒性模型可用于报告基因和神经毒性测定中的特异性分析以及细胞测定中的剂量规划。
