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Incorporating Metabolic Competence into High-Throughput Profiling Assays
Citation:
Jurgelewicz, A., K. Breaux, C. Willis, F. Harris, G. Byrd, J. Witten, D. Haggard, C. Deisenroth, AND J. Harrill. Incorporating Metabolic Competence into High-Throughput Profiling Assays. SOT Conference 2024: A New Approach Method (NAM) to Screen for the Impact of Endogenous Stress on Chemical Toxicity, Salt Lake City, UT, March 10 - 14, 2024. https://doi.org/10.23645/epacomptox.25488436
Impact/Purpose:
Presentation to SOT Conference 2024: A New Approach Method (NAM) to Screen for the Impact of Endogenous Stress on Chemical Toxicity
Description:
Background and Purpose: The US EPA aims to incorporate non-traditional toxicity testing strategies, referred to as new approach methods (NAMs), into regulatory decision making. The first tier of this strategy is focused on using high-throughput profiling (HTP) assays such as Cell Painting and high-throughput transcriptomics (HTTr) to characterize the biological activity of chemicals in human-derived cell models. However, these in vitro models largely lack xenobiotic metabolizing capabilities, limiting the ability of HTP assays to fully account for in vivo hazards. The Alginate Immobilized Metabolic Enzymes (AIME) platform encapsulates hepatic S9 fractions into microspheres that can metabolize chemicals in vitro prior to treatment of cells. This project aims to couple AIME with HTP assays and evaluate the impact of chemical metabolism on the gene expression and phenotypic profiles obtained from these screening assays. First, an in silico analysis evaluated concordance of high-confidence estrogen receptor (ERHC) gene expression signatures from HTTr screening in MCF7 cells to results from an AIME screen that identified metabolism-dependent estrogenic activity using VM7Luc4E2 cells, an MCF7 subclone that contains a luciferase reporter for estrogen receptor (ER) activation. We hypothesized that bioactivity at ERHC signatures would be observed in MCF7 cells for estrogenic parent chemicals bioinactivated by AIME and not observed for chemicals that require AIME bioactivation to produce estrogenic metabolites, thus confirming the suitability of these signatures for monitoring AIME performance in subsequent studies. Next, a proof-of-concept study in VM7Luc4E2 cells was designed to determine if incorporating in vitro metabolism into HTTr and Cell Painting using the AIME platform would result in shifts in biological activity associated with ER activation. Methods: HTTr was used to screen over 1,700 chemicals tested at 8 concentrations (0.03 - 100 µM) in MCF7 breast adenocarcinoma cells. Cell lysates were prepared for TempO-Seq analysis using the human whole transcriptome assay. Bioactivity of 33 ERHC signatures was evaluated for a subset of 14 chemicals that exhibited bioactivation, bioinactivation, or no change in ER response in a previous VM7Luc4E2 AIME screen. The number of ERHC signatures with concentration-responsive changes in normalized enrichment scores were tallied for each chemical and compared across categorical bins established from the AIME screen. The results from the in silico analysis were used to guide selection of 3 chemicals for a proof-of-concept study conducted in VM7Luc4E2 cells. The AIME lid-based platform +/- rat S9 was used to pre-treat cell culture media containing 17b-estradiol (200 pM) or 8 concentrations of trans-stilbene, ethylparaben and daidzein (0.002 – 200 µM), for 2 hours prior to cell treatment. After 24 hours of exposure to AIME-conditioned media, ER activity was evaluated using the luciferase BrightGloTM kit and overall bioactivity was evaluated using HTTr and Cell Painting. Results: Estrogenic parent chemicals that exhibited bioinactivation with the AIME platform in VM7Luc4E2 cells had a greater number of active ERHC signatures in MCF7 cells compared to chemicals that required bioactivation. For example, bioinactivated chemicals such as dehydroepiandrosterone had 33 active signatures. In comparison, bioactivated chemicals such as (E)-Anethole had 0 active signatures in the MCF7 cells which are deficient in metabolic capabilities. These results indicate that the ERHC signatures are potentially useful as a transcriptomic readout of ER bioactivity in future experiments incorporating AIME into HTTr. The proof-of-concept experiment is ongoing, but preliminary results show that incorporation of hepatic metabolism leads to bioinactivation of ethylparaben and bioactivation of trans-stilbene ER activity in VM7Luc4E2 cells. Future work will compare VM7Luc4E2 cell morphology and gene expression changes . . .
URLs/Downloads:
DOI: Incorporating Metabolic Competence into High-Throughput Profiling Assays
SOT_2024_V12.PDF (PDF, NA pp, 1751.251 KB, about PDF)