High-throughput analyses and Bayesian network modeling highlight novel epigenetic Adverse Outcome Pathway networks of DNA methyltransferase inhibitor mediated transgenerational effects

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  • You Song
  • Jorke H. Kamstra
  • Yang Cao
  • Jana Asselman
  • Marc Anglès d'Auriac
  • Nikolai Friberg

A number of epigenetic modulating chemicals are known to affect multiple generations of a population from a single ancestral exposure, thus posing transgenerational hazards. The present study aimed to establish a high-throughput (HT) analytical workflow for cost-efficient concentration-response analysis of epigenetic and phenotypic effects, and to support the development of novel Adverse Outcome Pathway (AOP) networks for DNA methyltransferase (DNMT) inhibitor-mediated transgenerational effects on aquatic organisms. The model DNMT inhibitor 5-azacytidine (5AC) and the model freshwater crustacean Daphnia magna were used to generate new experimental data and served as prototypes to construct AOPs for aquatic organisms. Targeted HT bioassays (DNMT ELISA, MS-HRM and qPCR) in combination with multigenerational ecotoxicity tests revealed concentration-dependent transgenerational (F0-F3) effects of 5AC on total DNMT activity, DNA promoter methylation, gene body methylation, gene transcription and reproduction. Top sensitive toxicity pathways related to 5AC exposure, such as apoptosis and DNA damage responses were identified in both F0 and F3 using Gaussian Bayesian network modeling. Two novel epigenetic AOP networks on DNMT inhibitor mediated one-generational and transgenerational effects were developed for aquatic organisms and assessed for the weight of evidence. The new HT analytical workflow and AOPs can facilitate future ecological hazard assessment of epigenetic modulating chemicals.

OriginalsprogEngelsk
Artikelnummer124490
TidsskriftJournal of Hazardous Materials
Vol/bind408
ISSN0304-3894
DOI
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
This project was funded by the NIVA institutional funding scheme “Strategic Institutional Initiatives programme (SIS) for Restoration Ecology” and the Research Council of Norway (RCN) through the project “ RiskAOP - Quantitative Adverse Outcome Pathway assisted risk assessment of mitochondrial toxicants” (grant No. 301397 , https://www.niva.no/en/projectweb/riskaop ). Special thanks to the general support from the NIVA Computational Toxicology Program (NCTP, www.niva.no/nctp ). During the project period, Jana Asselman was supported by the FWO Science Foundation Flanders.

Publisher Copyright:
© 2020 The Authors

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