Vfm a new quorum sensing system controls the virulence of <i> <scp>D</scp> ickeya dadantii </i>
Bibliographic record
Abstract
Dickeya dadantii is a plant pathogen that secretes cell wall-degrading enzymes (CWDE) that are responsible for soft-rot symptoms. Virulence genes are expressed in a concerted manner and culminate when bacterial multiplication slows. We identify a 25 kb vfm cluster required for D. dadantii CWDE production and pathogenesis. The vfm cluster encodes proteins displaying similarities both with enzymes involved in amino acid activation and with enzymes involved in fatty acid biosynthesis. These similarities suggest that the vfm genes direct the production of a metabolite. Cell-free supernatant from the D. dadantii wild-type strain restores CWDE production in vfm mutants. Collectively, our results indicate that vfm genes direct the synthesis of an extracellular signal and constitute a new quorum sensing system. Perception of the signal is achieved by the two-component system VfmH-VfmI, which activates the expression of the vfmE gene encoding an AraC regulator. VfmE then activates both the transcription of the CWDE genes and the expression of the vfm operons. The vfm gene cluster does not seem to be widespread among bacterial species but is conserved in other Dickeya species and could have been laterally transferred to Rahnella. This work highlights that entirely new families of bacterial languages remain to be discovered.
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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".