Integrated Omic Analyses Identify Pathways and Transcriptomic Regulators Associated With Chemical Alterations of In Vitro Neural Network Formation.

adverse outcome pathway developmental neurotoxicity environmental chemicals metabolomics neural network formation omics research

Journal

Toxicological sciences : an official journal of the Society of Toxicology
ISSN: 1096-0929
Titre abrégé: Toxicol Sci
Pays: United States
ID NLM: 9805461

Informations de publication

Date de publication:
28 02 2022
Historique:
pubmed: 21 12 2021
medline: 24 3 2022
entrez: 20 12 2021
Statut: ppublish

Résumé

Development of in vitro new approach methodologies has been driven by the need for developmental neurotoxicity (DNT) hazard data on thousands of chemicals. The network formation assay characterizes DNT hazard based on changes in network formation but provides no mechanistic information. This study investigated nervous system signaling pathways and upstream physiological regulators underlying chemically induced neural network dysfunction. Rat primary cortical neural networks grown on microelectrode arrays were exposed for 12 days in vitro to cytosine arabinoside, 5-fluorouracil, domoic acid, cypermethrin, deltamethrin, or haloperidol as these exposures altered network formation in previous studies. RNA-seq from cells and gas chromatography/mass spectrometry analysis of media extracts collected on days in vitro 12 provided gene expression and metabolomic identification, respectively. The integration of differentially expressed genes and metabolites for each neurotoxicant was analyzed using ingenuity pathway analysis. All 6 compounds altered gene expression that linked to developmental disorders and neurological diseases. Other enriched canonical pathways overlapped among compounds of the same class; eg, genes and metabolites altered by both cytosine arabinoside and 5-fluorouracil exposures are enriched in axonal guidance pathways. Integrated analysis of upstream regulators was heterogeneous across compounds, but identified several transcriptomic regulators including CREB1, SOX2, NOTCH1, and PRODH. These results demonstrate that changes in network formation are accompanied by transcriptomic and metabolomic changes and that different classes of compounds produce differing responses. This approach can enhance information obtained from new approach methodologies and contribute to the identification and development of adverse outcome pathways associated with DNT.

Identifiants

pubmed: 34927697
pii: 6470578
doi: 10.1093/toxsci/kfab151
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

118-133

Subventions

Organisme : U.S. Environmental Protection Agency
Organisme : Pathway Innovations Project
Organisme : Center for Computational Toxicology and Exposure

Informations de copyright

Published by Oxford University Press on behalf of the Society of Toxicology 2021. This work is written by US Government employees and is in the public domain in the US.

Auteurs

Carmen A Marable (CA)

Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.

Christopher L Frank (CL)

Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.

Roland F Seim (RF)

Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Athens, Georgia 30605, USA.
Chemical Processes and Systems Branch, Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Athens, Georgia 30605, USA.

Susan Hester (S)

Experimental Toxicokinetics and Exposure Branch, Chemical Characterization and Exposure Division, Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.

W Matthew Henderson (WM)

Chemical Processes and Systems Branch, Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Athens, Georgia 30605, USA.

Brian Chorley (B)

Advanced Experimental Toxicology Models Branch, Biomolecular and Computational Toxicology Division, Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.

Timothy J Shafer (TJ)

Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.

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Classifications MeSH