Login / Signup

Estrogenic Responsiveness of Brown Trout Primary Hepatocyte Spheroids to Environmental Levels of 17α-Ethinylestradiol.

Rodrigo F AlvesCélia LopesEduardo RochaTânia Vieira Madureira
Published in: Journal of xenobiotics (2024)
Three-dimensional (3D) fish hepatocyte cultures are promising alternative models for replicating in vivo data. Few studies have attempted to characterise the structure and function of fish 3D liver models and illustrate their applicability. This study aimed to further characterise a previously established spheroid model obtained from juvenile brown trout ( Salmo trutta ) primary hepatocytes under estrogenic stimulation. The spheroids were exposed for six days to environmentally relevant concentrations of 17α-ethinylestradiol-EE2 (1-100 ng/L). The mRNA levels of peroxisome ( catalase-Cat and urate oxidase-Uox ), lipid metabolism ( acyl-CoA long chain synthetase 1-Acsl1 , apolipoprotein AI-ApoAI , and fatty acid binding protein 1-Fabp1 ), and estrogen-related ( estrogen receptor α-ERα , estrogen receptor β-ERβ , vitellogenin A-VtgA , zona pellucida glycoprotein 2.5-ZP2.5 , and zona pellucida glycoprotein 3a.2-ZP3a.2 ) target genes were evaluated by quantitative real-time polymerase chain reaction. Immunohistochemistry was used to assess Vtg and ZP protein expressions. At the highest EE2 concentration, VtgA and ZP2.5 genes were significantly upregulated. The remaining target genes were not significantly altered by EE2. Vtg and ZP immunostaining was consistently increased in spheroids exposed to 50 and 100 ng/L of EE2, whereas lower EE2 levels resulted in a weaker signal. EE2 did not induce significant changes in the spheroids' viability and morphological parameters. This study identified EE2 effects at environmentally relevant doses in trout liver spheroids, indicating its usefulness as a proxy for in vivo impacts of xenoestrogens.
Keyphrases
  • estrogen receptor
  • binding protein
  • fatty acid
  • genome wide
  • liver injury
  • high resolution
  • gene expression
  • machine learning
  • drug induced
  • mass spectrometry
  • big data
  • small molecule
  • climate change