Chemical screening in an estrogen receptor transactivation assay with metabolic competence

The U.S. EPA continues to utilize high-throughput screening data to evaluate potential biological effects of endocrine active substances without the use of animal testing. Determining the scope and need for in vitro metabolism in high-throughput assays requires the generation of larger data sets that assess the impact of xenobiotic transformations on toxicity-related endpoints. The objective of the current study was to screen a set of 768 ToxCast chemicals in the VM7Luc estrogen receptor transactivation assay (ERTA) using the Alginate Immobilization of Metabolic Enzymes (AIME) hepatic metabolism method. Chemicals were screened with or without metabolism to identify estrogenic effects and metabolism-dependent changes in bioactivity. Based on estrogenic hit calls, 85 chemicals were active in both assay modes, 16 chemicals were only active without metabolism, and 27 chemicals were only active with metabolism. Using a novel metabolism curve shift method that evaluates the shift in concentra...美国环境保护署（U.S. EPA）始终依托高通量筛选（high-throughput screening）数据，在不开展动物实验的条件下评估内分泌活性物质（endocrine active substances）的潜在生物学效应。明确高通量检测中外源化合物（xenobiotic）体外代谢（in vitro metabolism）的适用范畴与实际需求，需要构建更大规模的数据集，以评估外源性化合物转化对毒性相关终点（toxicity-related endpoints）的影响。本研究的核心目标为：采用藻酸盐固定代谢酶（Alginate Immobilization of Metabolic Enzymes, AIME）肝脏代谢法，在VM7Luc雌激素受体转录激活试验（estrogen receptor transactivation assay, ERTA）中对768种ToxCast化学物质实施筛选。本研究设置代谢与非代谢两种检测模式对受试化学物质进行筛查，以甄别其雌激素活性以及依赖代谢过程的生物活性（bioactivity）变化。基于雌激素活性阳性命中判定结果，85种化学物质在两种检测模式下均呈现活性，16种仅在非代谢模式下具有活性，另有27种仅在代谢模式下表现出活性。本研究采用一种新型代谢曲线偏移法（metabolism curve shift method），用于评估浓度...