Critical Membrane Concentration and Mass-Balance Model to Identify Baseline Cytotoxicity of Hydrophobic and Ionizable Organic Chemicals in Mammalian Cell Lines

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 (IC10,baseline) using a mass balance model whose main chemical input parameter was the liposome-water partition constants (Klip/w) for neutral chemicals or the speciation-corrected Dlip/w(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/IC10,baseline) increased with increasing hydrophobicity, and the relationship started to level off at log Dlip/w around 2. The bioassay-specific models were applied to 392 chemicals covering a broad range of hydrophobicity and speciation. Comparing the predicted IC10,baseline and experimental cytotoxicity IC10, 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/IC10,baseline (M)] = 1.23 + 4.97 × (1 – e–0.236 log Dlip/w). 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.所有化学物质均可干扰细胞膜，进而引发基线毒性（baseline toxicity）——即任意化学物质所能引发的最低毒性水平。对于所有化学物质而言，其临界膜负荷（critical membrane burden）均为恒定值；换言之，触发基线毒性所需的给药浓度，会随化学物质疏水性（hydrophobicity）的升高而降低。基于化学物质疏水性构建的定量构效关系（Quantitative structure–activity relationships），已被用于预测人类及哺乳动物细胞系中引发基线毒性的标称浓度。然而，这类模型的适用范围仅局限于亲水中性化合物。为开发可覆盖更多疏水性带电有机化学物质的预测模型，本研究针对不同生物测定（bioassay）条件下的哺乳动物细胞（AREc32、AhR-CALUX、PPARγ-BLA及SH-SY5Y）采用了质量平衡模型（mass balance model）。本研究通过质量平衡模型，将基线毒性的临界膜负荷转换为基线毒性诱导10%细胞毒性（cytotoxicity）的标称浓度（IC10,baseline）；该模型的核心化学输入参数为：中性化学物质的脂质体-水分配常数（liposome-water partition constants，Klip/w），或可电离化学物质（ionizable chemicals）经形态校正后的Dlip/w(pH 7.4)，同时纳入了生物测定专属的细胞与培养基的蛋白质、脂质及水分含量。在这些生物测定专属模型中，log(1/IC10,baseline)随疏水性升高而递增，并在log Dlip/w约为2时趋于平缓。本研究将上述生物测定专属模型应用于392种覆盖宽泛疏水性范围与不同形态的化学物质。通过对比预测得到的IC10,baseline与实验测得的细胞毒性IC10，研究人员不仅确认了已知基线毒性物质（baseline toxicants）与其余多种化学物质均属于基线毒性物质，还依据这四种细胞系中的作用模式（modes of action）特异性对剩余化学物质进行了分类，证实了部分杀菌剂、抗生素及解偶联剂存在过量毒性。鉴于各生物测定专属模型间具有相似性，本研究提出了适用于贴壁人类细胞系的通用基线毒性模型：log[1/IC10,baseline (M)] = 1.23 + 4.97 × (1 – e–0.236 log Dlip/w)。本研究推导得到的基线毒性模型，可用于报告基因（reporter gene）与神经毒性测定（neurotoxicity assays）中的特异性分析，同时也可为基于细胞的测定（cell-based assays）的给药方案规划提供参考。