Inhibitory effect of ACC deaminase‐producing bacteria on crown gall formation in tomato plants infected by <i>Agrobacterium tumefaciens</i> or <i>A. vitis</i>
Bibliographic record
Abstract
This study showed that various rhizosphere bacteria producing the enzyme 1‐aminocyclopropane‐1‐carboxylate (ACC) deaminase (ACCD), which can degrade ACC, the immediate precursor of ethylene in plants, and thereby lower plant ethylene levels, can act as promising biocontrol agents of pathogenic strains of Agrobacterium tumefaciens and A. vitis . Soaking the roots of tomato ( Solanum lycopersicum ) seedlings in a suspension of the ACCD‐producing Pseudomonas putida UW4, Burkholderia phytofirmans PsJN or Azospirillum brasilense Cd1843 transformed by plasmid pRKTACC carrying the ACCD‐encoding gene acdS from UW4, significantly reduced the development of tumours on tomato plants injected 4–5 days later with pathogenic Agrobacterium strains via wounds on the plant stem. The fresh mass of tumours formed by plants pretreated with ACCD‐producing strains was typically four‐ to fivefold less than that of tumours formed on control plants inoculated only with a pathogenic Agrobacterium strain. Simultaneously, the level of ethylene evolution per amount of tumour mass on plants pretreated with ACCD‐producing bacteria decreased four to eight times compared with that from tumours formed on control plants or plants pretreated with bacteria deficient in ACCD production. Moreover, transgenic tomato plants expressing a bacterial ACCD were found to be highly resistant to crown gall formation relative to the parental, non‐transformed tomato plants. The results support the hypothesis that ethylene is a crucial factor in Agrobacterium tumour formation, and that ACCD‐produced rhizosphere bacteria may protect plants infected by pathogenic Agrobacteria from crown gall disease.
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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) | 0.001 | 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 | 0.001 |
| 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".