Identification of basepairs within Tn5 termini that are critical sfor H-NS binding to the transpososome and regulation of Tn5 transposition
Bibliographic record
Abstract
BACKGROUND: The H-NS protein is a global regulator of gene expression in bacteria and can also bind transposition complexes (transpososomes). In Tn5 transposition H-NS promotes transpososome assembly in vitro and disruption of the hns gene causes a modest decrease in Tn5 transposition (three- to five-fold). This is consistent with H-NS acting as a positive regulator of Tn5 transposition. Molecular determinants for H-NS binding to the Tn5 transpososome have not been determined, nor has the strength of the interaction been established. There is also uncertainty as to whether H-NS regulates Tn5 transposition in vivo through an interaction with the transposition machinery as disruption of the hns gene has pleiotropic effects on Escherichia coli, the organism used in this study. RESULTS: In the current work we have further examined determinants for H-NS binding to the Tn5 transpososome through both mutational studies on Tn5 termini (or 'transposon ends') and protein-protein cross-linking analysis. We identify mutations in two different segments of the transposon ends that abrogate H-NS binding and characterize the affinity of H-NS for wild type transposon ends in the context of the transpososome. We also show that H-NS forms cross-links with the Tn5 transposase protein specifically in the transpososome, an observation consistent with the two proteins occupying overlapping binding sites in the transposon ends. Finally, we make use of the end mutations to test the idea that H-NS exerts its impact on Tn5 transposition in vivo by binding directly to the transpososome. Consistent with this possibility, we show that two different end mutations reduce the sensitivity of the Tn5 system to H-NS regulation. CONCLUSIONS: H-NS typically regulates cellular functions through its potent transcriptional repressor function. Work presented here provides support for an alternative mechanism of H-NS-based regulation, and adds to our understanding of how bacterial transposition can be regulated.
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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) | 0.002 | 0.000 |
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".