Ubiquitin pathway blockade reveals endogenous ADP-ribosylation marking PARP7 and AHR for degradation
Bibliographic record
Abstract
ADP-ribosylation is an important protein post-translational modification catalysed by a family of PARP enzymes in humans and is involved in DNA damage and immunity among other processes. While poly-ADP-ribosylation has been established as a protein degradation signal in several cases, the role of mono-ADP-ribosylation in protein turnover has remained elusive and mostly relies on overexpression systems. Here, we describe a way to visualise high levels of endogenous ADP-ribosylation by inhibiting the ubiquitin pathway. By blocking ubiquitylation/proteasome, we found that ADP-ribosylation by at least three different PARPs (PARP7, PARP1 and TNKS) can be greatly induced. We discovered that specific activation of the aryl hydrocarbon receptor (AHR) pathway in combination with the ubiquitin pathway inhibition promotes quantitative ADP-ribosylation of PARP7 targets, including the mono-ADP-ribosyltransferase PARP7 itself and AHR. We found that DTX2 is the E3 ligase responsible for degrading ADP-ribosylated PARP7, AHR and other PARP7 substrates. This PARP7-DTX2 crosstalk establishes a mechanism to rapidly shut down AHR-mediated transcription by decreasing its protein levels. Taken together, our findings uncover a paradigm where mono-ADP-ribosylation acts as a degradation mark.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".