Roles of Glucitol in the GutR-mediated Transcription Activation Process in Bacillus subtilis
Bibliographic record
Abstract
Glucitol induction in Bacillus subtilis requires a transcription activator, GutR, and a sequence located upstream of the gut promoter. To understand the initial steps involved in the GutR-mediated transcription activation process and the physiological roles of glucitol, GutR was overproduced and purified. In the absence of glucitol, GutR exists as a monomer and binds directly to its binding site in the gut regulatory region. This binding site was mapped to a 29-base pair imperfect inverted repeat located between -78 and -50, and there is only one GutR binding site within the regulatory region. The kinetic parameters of the interaction between GutR and its binding site were monitored in real time using surface plasmon resonance. The half-life of the GutR-DNA complex in the absence of glucitol was estimated to be 6.8 min. In contrast, in the presence of glucitol, the half-life of the complex was extended to longer than 19 h by affecting only the off-rate but not the on-rate. This effect is glucitol-specific. These data indicate that glucitol binds to GutR and induces GutR to have an extremely tight binding at its binding site. The physiological relevance of this process in transcription activation is discussed.
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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) | 0.000 | 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".