<i>Rhizobium leguminosarum</i> Biovar viciae 1-Aminocyclopropane-1-Carboxylate Deaminase Promotes Nodulation of Pea Plants
Bibliographic record
Abstract
Ethylene inhibits nodulation in various legumes. In order to investigate strategies employed by Rhizobium to regulate nodulation, the 1-aminocyclopropane-1-carboxylate (ACC) deaminase gene was isolated and characterized from one of the ACC deaminase-producing rhizobia, Rhizobium leguminosarum bv. viciae 128C53K. ACC deaminase degrades ACC, the immediate precursor of ethylene in higher plants. Through the action of this enzyme, ACC deaminase-containing bacteria can reduce ethylene biosynthesis in plants. Insertion mutants with mutations in the rhizobial ACC deaminase gene (acdS) and its regulatory gene, a leucine-responsive regulatory protein-like gene (lrpL), were constructed and tested to determine their abilities to nodulate Pisum sativum L. cv. Sparkle (pea). Both mutants, neither of which synthesized ACC deaminase, showed decreased nodulation efficiency compared to that of the parental strain. Our results suggest that ACC deaminase in R. leguminosarum bv. viciae 128C53K enhances the nodulation of P. sativum L. cv. Sparkle, likely by modulating ethylene levels in the plant roots during the early stages of nodule development. ACC deaminase might be the second described strategy utilized by Rhizobium to promote nodulation by adjusting ethylene levels in legumes.
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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".