Ectomycorrhizal fungi induce systemic resistance against insects on a nonmycorrhizal plant in a CERK1‐dependent manner
Bibliographic record
Abstract
Summary Below‐ground microbes can induce systemic resistance against foliar pests and pathogens on diverse plant hosts. The prevalence of induced systemic resistance (ISR) among plant‐microbe‐pest systems raises the question of host specificity in microbial induction of ISR. To test whether ISR is limited by plant host range , we tested the ISR‐inducing ectomycorrhizal fungus Laccaria bicolor on the nonmycorrhizal plant Arabidopsis thaliana . We used the cabbage looper Trichoplusia ni and bacterial pathogen Pseudomonas syringae pv. tomato DC3000 ( Pto ) as readouts for ISR on Arabidopsis . We found that root inoculation with L. bicolor triggered ISR against T. ni and induced systemic susceptibility (ISS) against the bacterial pathogen Pto . We found that L. bicolor‐ triggered ISR against T. ni was dependent on jasmonic acid signaling and salicylic acid biosynthesis and signaling. Heat‐killed L. bicolor and chitin were sufficient to trigger ISR against T. ni and ISS against Pto . The chitin receptor CERK1 was necessary for L. bicolor‐ mediated effects on systemic immunity. Collectively our findings suggest that some ISR responses might not require intimate symbiotic association, but rather might be the result of root perception of conserved microbial signals.
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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) | 0.002 | 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".