The Negative Effects of Bile Acids and Tumor Necrosis Factor-α on the Transcription of Cholesterol 7α-Hydroxylase Gene (CYP7A1) Converge to Hepatic Nuclear Factor-4
Bibliographic record
Abstract
Bile acids regulate the cholesterol 7alpha-hydroxylase gene (CYP7A1), which encodes the rate-limiting enzyme in the classical pathway of bile acid synthesis. Here we report a novel mechanism whereby bile acid feedback regulates CYP7A1 transcription through the nuclear receptor hepatocyte nuclear factor-4 (HNF-4), which binds to the bile acid response element (BARE) at nt -149/-118 relative to the transcription start site. Using transient transfection assays of HepG2 cells with Gal4-HNF-4 fusion proteins, we show that chenodeoxycholic acid (CDCA) dampened the transactivation potential of HNF-4. Overexpression of a constitutive active form of MEKK1, an upstream mitogen-activated protein kinase (MAPK) module triggered by stress signals, strongly repressed the promoter activity of CYP7A1 via the consensus sequence for HNF-4 embedded in the BARE. Similarly, MEKK1 inhibited the activity of HNF-4 in the Gal4-based assay. The involvement of the MEKK1-dependent pathway in the bile acid-mediated repression of CYP7A1 was confirmed by co-transfecting a dominant negative form of the stress-activated protein kinase kinase, SEK, which abolished the effect of CDCA upon CYP7A1 transcription. Treatment of transfected HepG2 cells with tumor necrosis factor alpha (TNF-alpha), an activator of the MEKK1 pathway, led to the repression of CYP7A1 via the HNF-4 site in the BARE. TNF-alpha also inhibited the transactivation potential of HNF-4. Collectively, our results demonstrate for the first time that HNF-4, in combination with a MAPK signaling pathway, acts as a bile acid sensor in the liver. Furthermore, the effects of CDCA and TNF-alpha converge to HNF-4, which binds to the BARE of CYP7A1, suggesting a link between the cascades elicited by bile acids and pro-inflammatory stimuli in the liver.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".