Aryl Hydrocarbon Receptor Repressor and TiPARP (ARTD14) Use Similar, but also Distinct Mechanisms to Repress Aryl Hydrocarbon Receptor Signaling
Bibliographic record
Abstract
The aryl hydrocarbon receptor (AHR) regulates the toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). The AHR repressor (AHRR) is an AHR target gene and functions as a ligand-induced repressor of AHR; however, its mechanism of inhibition is controversial. Recently, we reported that TCDD-inducible poly (ADP-ribose) polymerase (TiPARP; ARTD14) also acts as a repressor of AHR, representing a new player in the mechanism of AHR action. Here we compared the ability of AHRR- and TiPARP-mediated inhibition of AHR activity. TCDD increased AHRR mRNA levels and recruitment of AHRR to cytochrome P450 1A1 (CYP1A1) in MCF7 cells. Knockdown of TiPARP, but not AHRR, increased TCDD-induced CYP1A1 mRNA and AHR protein levels. Similarly, immortalized TiPARP(-/-) mouse embryonic fibroblasts (MEFs) and AHRR(-/-) MEFs exhibited enhanced AHR transactivation. However, unlike TiPARP(-/-) MEFs, AHRR(-/-) MEFs did not exhibit increased AHR protein levels. Overexpression of TiPARP in AHRR(-/-) MEFs or AHRRΔ8, the active isoform of AHRR, in TiPARP(-/-) MEFs reduced TCDD-induced CYP1A1 mRNA levels, suggesting that they independently repress AHR. GFP-AHRRΔ8 and GFP-TiPARP expressed as small diffuse nuclear foci in MCF7 and HuH7 cells. GFP-AHRRΔ8_Δ1-49, which lacks its putative nuclear localization signal, localized to both the nucleus and the cytoplasm, while the GFP-AHRRΔ8_Δ1-100 mutant localized predominantly in large cytoplasmic foci. Neither GFP-AHRRΔ8_Δ1-49 nor GFP-AHRRΔ8_Δ1-100 repressed AHR. Taken together, AHRR and TiPARP repress AHR transactivation by similar, but also different mechanisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".