Amanda Jurgelewicz, Kristen Breaux, Clinton M Willis, Felix R Harris, Gabrielle Byrd, Joshua Witten, Derik E Haggard, Joseph L Bundy, Logan J Everett, Chad Deisenroth, Joshua A Harrill
{"title":"Incorporating Metabolic Competence into High-Throughput Profiling Assays.","authors":"Amanda Jurgelewicz, Kristen Breaux, Clinton M Willis, Felix R Harris, Gabrielle Byrd, Joshua Witten, Derik E Haggard, Joseph L Bundy, Logan J Everett, Chad Deisenroth, Joshua A Harrill","doi":"10.1093/toxsci/kfaf061","DOIUrl":null,"url":null,"abstract":"<p><p>High-throughput profiling assays such as high-throughput phenotypic profiling (HTPP) with Cell Painting and high-throughput transcriptomics (HTTr) with TempO-SeqTM have been used to characterize the bioactivity and potential hazards associated with large inventories of chemicals. Although both methods offer broad coverage of molecular targets, a limitation is that the cell types used in these in vitro assays typically lack the xenobiotic metabolism capabilities of humans or laboratory animals used for in vivo testing. To address this limitation, this proof-of-concept study coupled the Alginate Immobilization of Metabolic Enzymes (AIME) platform to both assays and evaluated the impact of metabolism on chemical bioactivity in a breast cancer cell line, VM7Luc4E2. HTPP detected concentration-dependent increases in chemical bioactivity corresponding to increased estrogen receptor (ER) activation measured using an ER transactivation assay (ERTA) that had been previously coupled to the AIME platform in VM7Luc4E2 cells. Additionally, HTTr detected a greater number of active genes in the metabolic condition associated with increased ER activation. This corresponded to a greater number of active ER high-confidence (ERHC) gene signatures and/or metabolism-induced shifts in ERHC signature enrichment as a transcriptomic readout of ER activity. This study demonstrates that the high-throughput profiling assays can detect changes in chemical bioactivity between parent compounds and metabolites generated using the AIME platform in a reproducible way. Incorporating metabolic competence into high-throughput profiling assays will better inform next generation risk assessment by capturing potential metabolite-based changes in bioactivity of test chemicals that may be missed by current screening approaches.</p>","PeriodicalId":23178,"journal":{"name":"Toxicological Sciences","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicological Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/toxsci/kfaf061","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
High-throughput profiling assays such as high-throughput phenotypic profiling (HTPP) with Cell Painting and high-throughput transcriptomics (HTTr) with TempO-SeqTM have been used to characterize the bioactivity and potential hazards associated with large inventories of chemicals. Although both methods offer broad coverage of molecular targets, a limitation is that the cell types used in these in vitro assays typically lack the xenobiotic metabolism capabilities of humans or laboratory animals used for in vivo testing. To address this limitation, this proof-of-concept study coupled the Alginate Immobilization of Metabolic Enzymes (AIME) platform to both assays and evaluated the impact of metabolism on chemical bioactivity in a breast cancer cell line, VM7Luc4E2. HTPP detected concentration-dependent increases in chemical bioactivity corresponding to increased estrogen receptor (ER) activation measured using an ER transactivation assay (ERTA) that had been previously coupled to the AIME platform in VM7Luc4E2 cells. Additionally, HTTr detected a greater number of active genes in the metabolic condition associated with increased ER activation. This corresponded to a greater number of active ER high-confidence (ERHC) gene signatures and/or metabolism-induced shifts in ERHC signature enrichment as a transcriptomic readout of ER activity. This study demonstrates that the high-throughput profiling assays can detect changes in chemical bioactivity between parent compounds and metabolites generated using the AIME platform in a reproducible way. Incorporating metabolic competence into high-throughput profiling assays will better inform next generation risk assessment by capturing potential metabolite-based changes in bioactivity of test chemicals that may be missed by current screening approaches.
期刊介绍:
The mission of Toxicological Sciences, the official journal of the Society of Toxicology, is to publish a broad spectrum of impactful research in the field of toxicology.
The primary focus of Toxicological Sciences is on original research articles. The journal also provides expert insight via contemporary and systematic reviews, as well as forum articles and editorial content that addresses important topics in the field.
The scope of Toxicological Sciences is focused on a broad spectrum of impactful toxicological research that will advance the multidisciplinary field of toxicology ranging from basic research to model development and application, and decision making. Submissions will include diverse technologies and approaches including, but not limited to: bioinformatics and computational biology, biochemistry, exposure science, histopathology, mass spectrometry, molecular biology, population-based sciences, tissue and cell-based systems, and whole-animal studies. Integrative approaches that combine realistic exposure scenarios with impactful analyses that move the field forward are encouraged.