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

Jill A. Franzosa, Jessica A. Bonzo, John Jack, Nancy Baker, Parth Kothiya, Rafal P. Witek, Patrick Hurban, Stephen Siferd, Susan Hester, Imran Shah, Stephen Ferguson, Keith A. Houck, John F. Wambaugh

2021npj Systems Biology and Applications44 citationsDOIOpen Access PDF

Abstract

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 HepaRG TM 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 HepaRG TM cell cultures.

Topics & Concepts

High-throughput screeningComputational biologyThroughputChemistryBiologyBiotechnologyComputer scienceBiochemistryWirelessTelecommunicationsComputational Drug Discovery MethodsMicrobial Metabolic Engineering and BioproductionMetabolomics and Mass Spectrometry Studies
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