The global bacterial regulator H-NS promotes transpososome formation and transposition in the Tn5 system
Bibliographic record
Abstract
The histone-like nucleoid structuring protein (H-NS) is an important regulator of stress response and virulence genes in gram-negative bacteria. In addition to binding regulatory regions of genes in a structure-specific manner, H-NS also binds in a structure-specific manner to sites in the Tn10 transpososome, allowing it to act as a positive regulator of Tn10 transposition. This is the only example to date of H-NS regulating a transposition system by interacting directly with the transposition machinery. In general, transposition complexes tend to include segments of deformed DNA and given the capacity of H-NS to bind such structures, and the results from the Tn10 system, we asked if H-NS might regulate another transposition system (Tn5) by directly binding the transposition machinery. We show in the current work that H-NS does bind Tn5 transposition complexes and use hydroxyl radical footprinting to characterize the H-NS interaction with the Tn5 transpososome. We also show that H-NS can promote Tn5 transpososome formation in vitro, which correlates with the Tn5 system showing a dependence on H-NS for transposition in vivo. Taken together the results suggest that H-NS might play an important role in the regulation of many different bacterial transposition systems and thereby contribute directly to lateral gene transfer.
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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 | 0.000 |
| 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".