Soil bacteria as sources of virulence signal providers promoting plant infection by Phytophthora pathogens
Bibliographic record
Abstract
Phytophthora species are known as "plant destroyers" capable of initiating single zoospore infection in the presence of a quorum of chemical signals from the same or closely related species of oomycetes. Since the natural oomycete population is too low to reach a quorum necessary to initiate a disease epidemic, creation of the quorum is reliant on alternate sources. Here, we show that a soil bacterial isolate, Bacillus megaterium Sb5, promotes plant infection by Phytophthora species. In the presence of Sb5 exudates, colonization of rhododendron leaf discs by 12 Phytophthora species/isolates was significantly enhanced, single zoospores of P. nicotianae infected annual vinca and P. sojae race 25 successfully attacked a non-host plant, Nicotiana benthamiana as well as resistant soybean cultivars with RPS1a or RPS3a. Sb5 exudates, most notably the fractions larger than 3 kDa, promoted plant infection by improving zoospore swimming, germination and plant attachment. Sb5 exudates also stimulated infection hypha growth and upregulated effector gene expression. These results suggest that environmental bacteria are important sources of virulence signal providers that promote plant infection by Phytophthora species, advancing our understanding of biotic factors in the environmental component of the Phytophthora disease triangle and of communal infection of plant pathogens.
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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".