Nuclear Factor-1 and Metal Transcription Factor-1 Synergistically Activate the Mouse Metallothionein-1 Gene in Response to Metal Ions
Bibliographic record
Abstract
Metal activation of metallothionein (MT) gene transcription is dependent on the presence of metal regulatory elements (MREs), which are present in five non-identical copies (MREa through MREe) in the promoter of the mouse MT-1 gene and on the capacity of metal transcription factor-1 (MTF-1) to bind to the MREs in the presence of zinc. We detected a protein, distinct from MTF-1, specifically binding to the MREc region. DNA binding competition experiments using synthetic oligonucleotides and specific anti-NF1 antibodies showed that this protein binds to an NF1 site overlapping the MREc element as well as to a second site upstream of the Sp1a site and corresponds to NF1 or a related protein. Transfection experiments showed that loss of the two NF1 sites decreased metal-induced MT promoter activity by 55-70% in transiently transfected cells and almost completely abrogated metal and tert-butylhydroquinone (tBHQ) induction in stably transfected cells. Similarly, expression of an inactive NF1 protein strongly inhibited MT-1 promoter activity. Using synthetic promoters containing NF1 and MRE sites fused to a minimal MT promoter, we showed that these NF1 sites did not confer metal induction but enhanced metal-induced promoter activity. Chromatin immunoprecipitation assays confirmed that NF1 binds to the mouse MT-1 promoter in vivo and showed that NF1 binding is zinc-inducible. In addition, zinc-induced NF1 DNA binding was MTF-1-dependent. Taken together, these studies show that NF1 acts synergistically with MTF-1 to activate the mouse MT-1 promoter in response to metal ions and tert-butylhydroquinone and contributes to maximal activation of the gene.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".