DNA wrapping is required for DNA damage recognition in the Escherichia coli DNA nucleotide excision repair pathway
Bibliographic record
Abstract
Localized DNA melting may provide a general strategy for recognition of the wide array of chemically and structurally diverse DNA lesions repaired by the nucleotide excision repair (NER) pathway. However, it is not clear what causes such DNA melting and how it is driven. Here, we show a DNA wrapping-melting model supported by results from dynamic monitoring of the key DNA-protein and protein-protein interactions involved in the early stages of the Escherichia coli NER process. Using an analytical technique involving capillary electrophoresis coupled with laser-induced fluorescence polarization, which combines a mobility shift assay with conformational analysis, we demonstrate that DNA wrapping around UvrB, mediated by UvrA, is an early event in the damage-recognition process during E. coli NER. DNA wrapping of UvrB was confirmed by Förster resonance energy transfer and fluorescence lifetime measurements. This wrapping did not occur with readily denaturable damaged DNA substrates ("bubble" DNA), suggesting that DNA wrapping of UvrB plays an important role in the induction of DNA melting around the damage site. Analysis of DNA wrapping of mutant UvrB Y96A further suggests that a cooperative interaction between DNA wrapping of UvrA(2)B and contact of the beta-hairpin of UvrB with the bulky damage moiety may be involved in the local DNA melting at the damage site.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".