High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures

Abstract The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in ca...

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Autores principales:	Jill A. Franzosa, Jessica A. Bonzo, John Jack, Nancy C. Baker, Parth Kothiya, Rafal P. Witek, Patrick Hurban, Stephen Siferd, Susan Hester, Imran Shah, Stephen S. Ferguson, Keith A. Houck, John F. Wambaugh
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/650b871553ac4893ba69a76c57d0eaab
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spelling	oai:doaj.org-article:650b871553ac4893ba69a76c57d0eaab2021-12-02T13:57:39ZHigh-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures10.1038/s41540-020-00166-22056-7189https://doaj.org/article/650b871553ac4893ba69a76c57d0eaab2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41540-020-00166-2https://doaj.org/toc/2056-7189Abstract The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.Jill A. FranzosaJessica A. BonzoJohn JackNancy C. BakerParth KothiyaRafal P. WitekPatrick HurbanStephen SiferdSusan HesterImran ShahStephen S. FergusonKeith A. HouckJohn F. WambaughNature PortfolioarticleBiology (General)QH301-705.5ENnpj Systems Biology and Applications, Vol 7, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Jill A. Franzosa Jessica A. Bonzo John Jack Nancy C. Baker Parth Kothiya Rafal P. Witek Patrick Hurban Stephen Siferd Susan Hester Imran Shah Stephen S. Ferguson Keith A. Houck John F. Wambaugh High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
description	Abstract The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.
format	article
author	Jill A. Franzosa Jessica A. Bonzo John Jack Nancy C. Baker Parth Kothiya Rafal P. Witek Patrick Hurban Stephen Siferd Susan Hester Imran Shah Stephen S. Ferguson Keith A. Houck John F. Wambaugh
author_facet	Jill A. Franzosa Jessica A. Bonzo John Jack Nancy C. Baker Parth Kothiya Rafal P. Witek Patrick Hurban Stephen Siferd Susan Hester Imran Shah Stephen S. Ferguson Keith A. Houck John F. Wambaugh
author_sort	Jill A. Franzosa
title	High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
title_short	High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
title_full	High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
title_fullStr	High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
title_full_unstemmed	High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
title_sort	high-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/650b871553ac4893ba69a76c57d0eaab
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High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures

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