Bacterial type 1A topoisomerases maintain the stability of the genome by preventing and dealing with R-loop-and nucleotide excision repair-dependent topological stress
Bibliographic record
Abstract
ABSTRACT E. coli type 1A topoisomerases (topos), topo I ( topA ) and topo III ( topB ) have both relaxation and decatenation activities. B. subtilis and E. coli topA topB null cells can survive owing to DNA amplifications allowing overproduction of topo IV, the main cellular decatenase that can also relax supercoiling. We show that overproducing human topo IB, a relaxase but not a decatenase, can substitute for topo IV in allowing E. coli topA null but not topA topB null cells to survive. Deleting topB exacerbates phenotypes of topA null mutants including hypernegative supercoiling, R-loop formation, and RNase HI-sensitive replication, phenotypes that are not corrected by topo IV overproduction. These phenotypes lead to Ter DNA amplification causing a chromosome segregation defect that is corrected by topo IV overproduction. Furthermore, topA topB null mutants not overproducing topo IV acquire uvrB or uvrC mutations, revealing a nucleotide excision repair (NER)-dependent problem with replication fork progression. Thus, type IA topos maintain the stability of the genome by providing essential relaxase and decatenase activities to prevent and solve topological stress related to R-loops and NER. Moreover, excess R-loop formation is well tolerated in cells that have enough topoisomerase activity to support the subsequent replication-related topological stress.
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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 | 0.000 |
| 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 | 0.000 |
| 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".