Abstract
Within the framework of reduction, refinement and replacement of animal experiments, new approaches for identification and characterization of chemical hazards have been developed. Grouping and read across has been promoted as a most promising alternative approach. It uses existing toxicological information on a group of chemicals to make predictions on the toxicity of uncharacterized ones. In the present work, the feasibility of applying in vitro and in silico techniques to group chemicals for read across was studied using the food mycotoxin zearalenone (ZEN) and metabolites as a case study. ZEN and its reduced metabolites are known to act through activation of the estrogen receptor α (ERα). The ranking of their estrogenic potencies appeared highly conserved across test systems including binding, in vitro and in vivo assays. This data suggests that activation of ERα may play a role in the molecular initiating event (MIE) and be predictive of adverse effects and provides the rationale to model receptor-binding for hazard identification. The investigation of receptor-ligand interactions through docking simulation proved to accurately rank estrogenic potencies of ZEN and reduced metabolites, showing the suitability of the model to address estrogenic potency for this group of compounds. Therefore, the model was further applied to biologically uncharacterized, commercially unavailable, oxidized ZEN metabolites (6α-, 6β-, 8α-, 8β-, 13- and 15-OH-ZEN). Except for 15-OH-ZEN, the data indicate that in general, the oxidized metabolites would be considered a lower estrogenic concern than ZEN and reduced metabolites.
Highlights
In the process of chemical risk assessment, the steps of hazard identification and hazard characterization refer to the qualitative description and dose-response analysis of toxic effects (Schilter et al, 2013)
Zearalenone (ZEN), α and β zearalenol (ZEL), α and β zearalanol (ZAL), hypothemycin, 17 β-estradiol (E2), dimethylsulfoxide (DMSO), penicillin/streptomycin (P/S), Dulbecco’s phosphate buffered saline (PBS) and formalin solution neutral buffered 10% were purchased from Sigma Aldrich (Buchs, Switzerland); Dulbecco’s Minimum Essential Medium (DMEM) high glucose with stable glutamine from PAA (Linz, Austria), charcoal stripped fetal bovine serum (FBS) and Hoechst 33258 were from Invitrogen (Eugene, Oregon, USA) and G418 from Roche (Mannheim, Germany)
It is widely recognized that the Adverse Outcome Pathway (AOP) concept could play an essential role to define the data required to facilitate the formation of relevant chemical categories for read-across: chemicals could be grouped according to key events, but more likely according to molecular initiating event (MIE) (Crofton et al, 2014; Patlewicz et al, 2014)
Summary
In the process of chemical risk assessment, the steps of hazard identification and hazard characterization refer to the qualitative description and dose-response analysis of toxic effects (Schilter et al, 2013). Both have relied on in vivo animal studies. Several avenues have been developed to achieve such a challenging goal, including the application of in vitro and computational toxicology tools (NRC, 2007; Bradbury et al, 2004) In this context, the technique of chemical grouping and read-across has been promoted as a most promising and pragmatic alternative approach. Finding adequate analogs is not straightforward and has to be based on a number of structural and biological features (OECD, 2011; Patlewicz et al, 2014; Schilter et al, 2013; Wu et al, 2010)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.