The problem of hypernegative supercoiling and r-loop formation in transcription
Bibliographic record
Abstract
DNA supercoiling and topoisomerases have long been known to affect transcription initiation. In many studies, topA mutants were used to perturb chromosomal supercoiling. Although such studies clearly revealed that supercoiling could significantly affect gene expression, they did not tell much about the essential function(s) of DNA topoisomerase I, encoded by topA. Indeed, the topA mutants used in these studies were growing relatively well, although this gene is normally essential for growth. These mutants were either carrying a topA allele with enough residual activity to permit growth, or if deleted for the topA gene, they were carrying a compensatory mutation allowing them to grow. We have recently used a set of isogenic strains carrying a conditional gyrB mutation that allowed us to study the real effects of losing topoisomerase I activity on cell physiology. The results of our work show that an essential function of topoisomerase I is related to transcription, more precisely to inhibit R-loop formation. This is in agreement with a series of biochemical studies that revealed a role for topoisomerase I in inhibiting R-loop formation during transcription in the presence of DNA gyrase. In addition, our studies may have revealed an important role for DNA supercoiling in modulating gene expression, not only at the level of transcription initiation but also during elongation. In this paper, we will first discuss global and local supercoiling, then we will address the topic of R-loop formation and finally, we will review the subject of hypersupercoiling and R-loop formation in gene expression. Whenever possible, we will try to make correlations with growth phenotypes, since such correlations reveal the essential function of DNA topoisomerase I.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".