Transcriptional regulation of ACC deaminase gene expression in<i>Pseudomonas putida</i>UW4
Bibliographic record
Abstract
One of the major mechanisms that plant growth-promoting bacteria use to facilitate plant growth is through the lowering of plant ethylene levels by the bacterial enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase. Many of the bacterial ACC deaminase genes (acdS) that have been examined to date are under the transcriptional control of a leucine-responsive regulatory protein, Lrp, encoded by acdR and referred to here as AcdR. The work presented here is focused on how AcdR and the newly discovered AcdB protein from Pseudomonas putida UW4 are involved in the regulation of acdS expression. First, the results of gel retardation experiments showed that AcdR binds to the acdS regulatory region, and this binding activity in vitro is not affected by the addition of 2 mmol x L-1 ACC but can be eliminated by addition of 20 microg x mL-1 leucine. Second, a potential regulatory protein, AcdB, involved in the regulation of acdS expression, was identified through both yeast 2-hybrid screen and coimmunoprecipitation based on its ability to bind to AcdR; subsequently, its binding to the acdS regulatory region in the presence of ACC was shown by gel retardation experiments. The data are interpreted in terms of a model in which AcdR and AcdB co-regulate the expression of the acdS gene.
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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 | 0.000 |
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".