DNA ligase III acts as a DNA strand break sensor in the cellular orchestration of DNA strand break repair
Bibliographic record
Abstract
In the current model of DNA SSBR, PARP1 is regarded as the sensor of single-strand breaks (SSBs). However, biochemical studies have implicated LIG3 as another possible SSB sensor. Using a laser micro-irradiation protocol that predominantly generates SSBs, we were able to demonstrate that PARP1 is dispensable for the accumulation of different single-strand break repair (SSBR) proteins at sites of DNA damage in live cells. Furthermore, we show in live cells for the first time that LIG3 plays a role in mediating the accumulation of the SSBR proteins XRCC1 and PNKP at sites of DNA damage. Importantly, the accumulation of LIG3 at sites of DNA damage did not require the BRCT domain-mediated interaction with XRCC1. We were able to show that the N-terminal ZnF domain of LIG3 plays a key role in the enzyme's SSB sensing function. Finally, we provide cellular evidence that LIG3 and not PARP1 acts as the sensor for DNA damage caused by the topoisomerase I inhibitor, irinotecan. Our results support the existence of a second damage-sensing mechanism in SSBR involving the detection of nicks in the genome by LIG3.
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 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".