Literature DB >> 27503384

Editor's Highlight: Computational Modeling of Plasma Vitellogenin Alterations in Response to Aromatase Inhibition in Fathead Minnows.

Wan-Yun Cheng1,2, Qiang Zhang3, Anthony Schroeder4, Daniel L Villeneuve5, Gerald T Ankley5, Rory Conolly6.   

Abstract

In vertebrates, conversion of testosterone into 17β-estradiol (E2) is catalyzed by cytochrome P450 (CYP) 19A aromatase. An important role of E2 in oviparous vertebrates such as fish is stimulation of hepatic synthesis of the glycolipoprotein vitellogenin (VTG), an egg yolk precursor essential to oocyte development and larval survival. In fathead minnows (FHMs) (Pimephales promelas) exposed to the aromatase inhibitor fadrozole, plasma VTG levels do not change in concert with plasma E2 levels. Specifically, while plasma VTG and E2 levels both drop quickly when aromatase is first inhibited, the recovery of plasma VTG upon cessation of aromatase inhibition is substantially delayed relative to the recovery of plasma E2. We modified an existing computational model of the FHM hypothalamic-pituitary-gonadal axis to evaluate alternative hypotheses that might explain this delay. In the first hypothesis, a feedback loop involving active transport of VTG from the blood into the ovary is used. The activity of the transporter is negatively regulated by ovarian VTG. In the second hypothesis, a type 1 coherent feed-forward loop is implemented in the liver. This loop has 2 arms, both requiring E2 activation. The first arm describes direct, canonical E2-driven transcriptional induction of VTG, and the second describes an E2-driven intermediate transcriptional regulator that is also required for VTG synthesis. Both hypotheses accurately described the observed VTG dynamics. This result could be used to guide design of laboratory experiments intended to determine if either of the motifs, or perhaps even both of them, actually do control VTG dynamics in FHMs exposed to aromatase inhibitors. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

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Keywords:  adverse outcome pathway; aquatic toxicology; computational toxicology.; endocrine toxicology; environmental toxicology; in vitro and altenatives; predictive toxicology

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Year:  2016        PMID: 27503384     DOI: 10.1093/toxsci/kfw142

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  5 in total

1.  Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.

Authors:  Rory B Conolly; Gerald T Ankley; WanYun Cheng; Michael L Mayo; David H Miller; Edward J Perkins; Daniel L Villeneuve; Karen H Watanabe
Journal:  Environ Sci Technol       Date:  2017-04-07       Impact factor: 9.028

Review 2.  Adverse outcome pathways: a concise introduction for toxicologists.

Authors:  Mathieu Vinken; Dries Knapen; Lucia Vergauwen; Jan G Hengstler; Michelle Angrish; Maurice Whelan
Journal:  Arch Toxicol       Date:  2017-06-28       Impact factor: 5.153

3.  Case Study in 21st Century Ecotoxicology: Using In Vitro Aromatase Inhibition Data to Predict Short-Term In Vivo Responses in Adult Female Fish.

Authors:  Daniel L Villeneuve; Brett R Blackwell; Jenna E Cavallin; Wan-Yun Cheng; David J Feifarek; Kathleen M Jensen; Michael W Kahl; Rebecca Y Milsk; Shane T Poole; Eric C Randolph; Travis W Saari; Gerald T Ankley
Journal:  Environ Toxicol Chem       Date:  2021-03-10       Impact factor: 4.218

Review 4.  Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

Authors:  Edward J Perkins; Roman Ashauer; Lyle Burgoon; Rory Conolly; Brigitte Landesmann; Cameron Mackay; Cheryl A Murphy; Nathan Pollesch; James R Wheeler; Anze Zupanic; Stefan Scholz
Journal:  Environ Toxicol Chem       Date:  2019-08-08       Impact factor: 3.742

5.  Anti-masculinization induced by aromatase inhibitors in adult female zebrafish.

Authors:  Lu Chen; Li Wang; Qiwei Cheng; Yi-Xuan Tu; Zhuang Yang; Run-Ze Li; Zhi-Hui Luo; Zhen-Xia Chen
Journal:  BMC Genomics       Date:  2020-01-07       Impact factor: 3.969

  5 in total

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