ArticleArchives of toxicology2014
From transient transcriptome responses to disturbed neurodevelopment: role of histone acetylation and methylation as epigenetic switch between reversible and irreversible drug effects.
Article in Archives of toxicology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 77 citations in OpenAlex.
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- An overview of technologies for MS-based proteomics-centric multi-omics.Expert review of proteomics · 2022Article
- A large scale mass spectrometry-based histone screening for assessing epigenetic developmental toxicity.Scientific reports · 2022Article
- A human stem cell-derived test system for agents modifying neuronal N-methyl-D-aspartate-type glutamate receptor CaArchives of toxicology · 2021Article
- Kinetic modeling of stem cell transcriptome dynamics to identify regulatory modules of normal and disturbed neuroectodermal differentiation.Nucleic acids research · 2020Article
- Gestational exposures to organophosphorus insecticides: From acute poisoning to developmental neurotoxicity.Neuropharmacology · 2020Review
- Epigenomic landscape of enhancer elements during Hydra head organizer formation.Epigenetics & chromatin · 2020Article
- Testing of female reproductive disorders.Archives of toxicology · 2020Article
- Reproductive toxicity of boron.EXCLI journal · 2020Article
- Rotenone exerts developmental neurotoxicity in a human brain spheroid model.Toxicology and applied pharmacology · 2018Article
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- Highlight report: Toxicogenomics atlas of rat hepatotoxicants.EXCLI journal · 2018Article
- Can Valproic Acid Regulate Neurogenesis from Nestin+ Cells in the Adult Midbrain?Neurochemical research · 2017Article
- Definition of transcriptome-based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP-ToxArchives of toxicology · 2017Article
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The superordinate principles governing the transcriptome response of differentiating cells exposed to drugs are still unclear. Often, it is assumed that toxicogenomics data reflect the immediate mode of action (MoA) of drugs. Alternatively, transcriptome changes could describe altered differentiation states as indirect consequence of drug exposure. We used here the developmental toxicants valproate and trichostatin A to address this question. Neurally differentiating human embryonic stem cells were treated for 6 days. Histone acetylation (primary MoA) increased quickly and returned to baseline after 48 h. Histone H3 lysine methylation at the promoter of the neurodevelopmental regulators PAX6 or OTX2 was increasingly altered over time. Methylation changes remained persistent and correlated with neurodevelopmental defects and with effects on PAX6 gene expression, also when the drug was washed out after 3-4 days. We hypothesized that drug exposures altering only acetylation would lead to reversible transcriptome changes (indicating MoA), and challenges that altered methylation would lead to irreversible developmental disturbances. Data from pulse-chase experiments corroborated this assumption. Short drug treatment triggered reversible transcriptome changes; longer exposure disrupted neurodevelopment. The disturbed differentiation was reflected by an altered transcriptome pattern, and the observed changes were similar when the drug was washed out during the last 48 h. We conclude that transcriptome data after prolonged chemical stress of differentiating cells mainly reflect the altered developmental stage of the model system and not the drug MoA. We suggest that brief exposures, followed by immediate analysis, are more suitable for information on immediate drug responses and the toxicity MoA.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.