Identification of environmental chemicals that activate p53 signaling after in vitro metabolic activation

Abstract

Currently, approximately 80,000 chemicals are used in commerce. Most have little-to-no toxicity information. The U.S. Toxicology in the 21st Century (Tox21) program has conducted a battery of in vitro assays using a quantitative high-throughput screening (qHTS) platform to gain toxicity information on environmental chemicals. Due to technical challenges, standard methods for providing xenobiotic metabolism could not be applied to qHTS assays. To address this limitation, we screened the Tox21 10,000-compound (10K) library, with concentrations ranging from 2.8 nM to 92 µM, using a p53 beta-lactamase reporter gene assay (p53-bla) alone or with rat liver microsomes (RLM) or human liver microsomes (HLM) supplemented with NADPH, to identify compounds that induce p53 signaling after biotransformation. Two hundred and seventy-eight compounds were identified as active under any of these three conditions. Of these 278 compounds, 73 gave more potent responses in the p53-bla assay with RLM, and 2 were more potent in the p53-bla assay with HLM compared with the responses they generated in the p53-bla assay without microsomes. To confirm the role of metabolism in the differential responses, we re-tested these 75 compounds in the absence of NADPH or with heat-attenuated microsomes. Forty-four compounds treated with RLM, but none with HLM, became less potent under these conditions, confirming the role of RLM in metabolic activation. Further evidence of biotransformation was obtained by measuring the half-life of the parent compounds in the presence of microsomes. Together, the data support the use of RLM in qHTS for identifying chemicals requiring biotransformation to induce biological responses.

Keywords: High-throughput metabolism assay; High-throughput screening; In silico metabolism prediction; In vitro metabolism; Microsomes; p53.

Fig. 1

Structure–Activity Relationship (SAR) of compounds that induce the p53 signaling pathway. All compounds with associated structures present in the library were clustered, based on structural similarity using the Self-Organizing Map (SOM) algorithm (Kohonen 2006). Then, each cluster was evaluated for enrichment with active agonists (compared to the library average) using the Fisher’s exact test. In the heatmaps, each hexagon represents a cluster of structurally similar compounds. Clusters are colored by the significance of enrichment (negative log p value) such that more significantly enriched clusters are colored closer to a maroon color and the other clusters are colored with different shades as indicated in the color bar. A light gray color shade represents that the degree of enrichment of the cluster is close to the library average

Fig. 2

Concentration–response curves of representative compounds in p53-bla assays. Cells were treated with the compounds in the absence or presence of rat/human liver microsomes. a chlorpyrifos, b amiprofos-methyl, c disulfoton, d coumaphos, e terbufos, and f fonofos. Each value represents the mean ± SD of three independent experiments. Without MS, without microsomes

Fig. 3

Concentration–response curves of representative compounds in p53-bla assays. Cells were treated with the compounds in the absence or presence of heat-attenuated rat liver microsomes or rat liver microsomes in the absence of NADPH. a chlorpyrifos, b amiprofos-methyl, c disulfoton, d coumaphos, e terbufos, and f fonofos. Each value represents the mean ± SD of three independent experiments. MS, with microsomes; Heat-attenuated MS, with heat-attenuated microsomes; No NADPH, without NADPH

Fig. 4

The ratio of the CL_int for rat and human liver microsomes. The CL_int was predicted using ADMET predictor. The y axis indicates the ratios that were calculated as rat microsomes CL_int/human microsomes CL_int