Magel Viktoria, Blum Jonathan, Dolde Xenia, Leisner Heidrun, Grillberger Karin, Khalidi Hiba, Gardner Iain, Ecker Gerhard F, Pallocca Giorgia, Dreser Nadine, Leist Marcel
In Vitro Toxicology and Biomedicine, Dept Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, 78464 Konstanz, Germany.
Department of Pharmaceutical Chemistry, University of Vienna, 1090 Vienna, Austria.
Cells. 2024 Dec 12;13(24):2057. doi: 10.3390/cells13242057.
Cell-based test methods with a phenotypic readout are frequently used for toxicity screening. However, guidance on how to validate the hits and how to integrate this information with other data for purposes of risk assessment is missing. We present here such a procedure and exemplify it with a case study on neural crest cell (NCC)-based developmental toxicity of picoxystrobin. A library of potential environmental toxicants was screened in the UKN2 assay, which simultaneously measures migration and cytotoxicity in NCC. Several strobilurin fungicides, known as inhibitors of the mitochondrial respiratory chain complex III, emerged as specific hits. From these, picoxystrobin was chosen to exemplify a roadmap leading from cell-based testing towards toxicological predictions. Following a stringent confirmatory testing, an adverse outcome pathway was developed to provide a testable toxicity hypothesis. Mechanistic studies showed that the oxygen consumption rate was inhibited at sub-µM picoxystrobin concentrations after a 24 h pre-exposure. Migration was inhibited in the 100 nM range, under assay conditions forcing cells to rely on mitochondria. Biokinetic modeling was used to predict intracellular concentrations. Assuming an oral intake of picoxystrobin, consistent with the acceptable daily intake level, physiologically based kinetic modeling suggested that brain concentrations of 0.1-1 µM may be reached. Using this broad array of hazard and toxicokinetics data, we calculated a margin of exposure ≥ 80 between the lowest in vitro point of departure and the highest predicted tissue concentration. Thus, our study exemplifies a hit follow-up strategy and contributes to paving the way to next-generation risk assessment.
具有表型读数的基于细胞的测试方法常用于毒性筛选。然而,目前缺少关于如何验证筛选出的阳性结果以及如何将这些信息与其他数据整合以进行风险评估的指导。我们在此介绍这样一种程序,并以嘧菌酯对神经嵴细胞(NCC)的发育毒性的案例研究为例进行说明。在UKN2试验中对一系列潜在环境毒物进行了筛选,该试验可同时测量NCC的迁移和细胞毒性。几种已知为线粒体呼吸链复合物III抑制剂的甲氧基丙烯酸酯类杀菌剂成为特定的阳性结果。从中选择嘧菌酯来举例说明从基于细胞的测试到毒理学预测的路线图。经过严格的验证性测试后,建立了一条不良结局途径以提供一个可测试的毒性假设。机制研究表明,在24小时预暴露后,亚微摩尔浓度的嘧菌酯会抑制氧消耗率。在迫使细胞依赖线粒体的试验条件下,100 nM范围内的迁移受到抑制。生物动力学建模用于预测细胞内浓度。假设口服嘧菌酯,与每日可接受摄入量水平一致,基于生理学的动力学建模表明可能达到0.1 - 1 µM的脑浓度。利用这一系列广泛的危害和毒代动力学数据,我们计算出最低体外起始点与最高预测组织浓度之间的暴露边际≥80。因此,我们的研究举例说明了一种阳性结果跟进策略,并有助于为下一代风险评估铺平道路。