Cytochrome P450-mediated 17β-estradiol metabolism in zebrafish (Danio rerio)
Bibliographic record
Abstract
Cytochrome P4501 (CYP1) and CYP3A proteins are primarily responsible for the metabolism of 17beta-estradiol (E(2)) in mammals. We have cloned and heterologously expressed CYP1A, CYP1B1, CYP1C1, CYP1C2, CYP1D1, and CYP3A65 from zebrafish (Danio rerio) to determine the CYP-mediated metabolism of E(2) in a non-mammalian species. Constructs of each CYP cDNA were created using a leader sequence from the bacterial ompA gene to allow appropriate expression in Escherichia coli without 5' modification of the gene. Membrane vesicles were purified, and functional CYP protein was verified using carbon monoxide difference spectra and fluorescent catalytic assays with the substrates 7-ethoxyresorufin and 7-benzyloxy-4-(trifluoromethyl)-coumarin. Rates of in vitro E(2) metabolism into 4-hydroxyE(2) (4-OHE(2)), 2-hydroxyE(2) (2-OHE(2)), and 16alpha-hydroxyE(1) (16alpha-OHE(1)) metabolites were determined by gas chromatography/mass spectrometry. The 2-OHE(2) metabolite was produced by all CYPs tested, while 4-OHE(2) was only detected following incubation with CYP1A, CYP1B1, CYP1C1, and CYP1C2. The 16alpha-OHE(1) metabolite was only produced by CYP1A. The highest rates of E(2) metabolism were from CYP1A and CYP1C1, followed by CYP1C2. CYP1B1, CYP1D1, and CYP3A65 had low rates of E(2) metabolism. E(2) metabolism by zebrafish CYP1A, CYP1C1, and CYP1C2 produced similar ratios of 4-OHE(2) to 2-OHE(2) as previous studies with mammalian CYP1As. CYP1B1 formed the highest ratio of 4-OHE(2) to 2-OHE(2) metabolites. Contrary to mammals, these results suggest that fish CYP1A and CYP1C proteins are primarily responsible for E(2) metabolism, with only minor contributions from CYP3A65 and CYP1B1. Similar to mammals, 2-OHE(2) is the predominant metabolite from CYP-mediated E(2) metabolism in fish, suggesting that all vertebrate species produce the same major E(2) metabolite.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".