Quorum Quenching in <i>Agrobacterium tumefaciens</i> : Chance or Necessity?
Bibliographic record
Abstract
Cell-cell communication or “quorum sensing” (QS) between members of a population is an established phenomenon that has been described for many different bacterial species. A number of different types of QS systems have been discovered; however, a unifying theme is the synthesis of a small signal molecule, often called an autoinducer or pheromone, which activates a specific response when it accumulates to a threshold concentration within a population. A relatively new and exciting aspect of the field of QS that has received much recent attention is “quorum quenching” (QQ), or interference of a QS signaling system. This occurs through either the inhibition of a QS component or the depletion of the signal itself, resulting in an attenuation of the response. In the plant pathogen Agrobacterium tumefaciens, an enzyme (BlcC) that destroys the bacterium's QS signal has been recently described, prompting much speculation that this enzyme is specifically involved in the quenching of the QS system. A variety of explanations for the adaptive significance of QQ in the QS system of A. tumefaciens and implications for the bacterium's role as a plant pathogen have been suggested in the literature (for example, see references 4 and 27). However, the role of BlcC in QQ was never directly addressed. In A. tumefaciens, the QS system regulates Ti (tumor-inducing) plasmid conjugation. In this issue, Khan and Farrand (12) directly address the biological significance of BlcC by examining its effect on Ti plasmid conjugation both in culture and in planta. Their study has implications for our understanding of the possible roles in Agrobacterium and other bacteria of BlcC-like enzymes, which are generally thought to function as quorum quenchers of proteobacteria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".