Elicitation of systemic resistance against the bacterial speck pathogen in<i>Arabidopsis thaliana</i>by culture filtrates of plant growth-promoting fungi
Bibliographic record
Abstract
The potential for mediation of induced systemic resistance (ISR) and the mechanisms used by nonpathogenic beneficial microbes to mediate ISR are currently under intense investigation but have been overlooked in studies examining plant growth promoting fungi (PGPF) or their metabolites. Here, we examined whether culture filtrates (CFs) of three well-characterized PGPF isolates, which demonstrated different responses in hypersensitive reaction-like cell death and β-glucuronidase reporter gene expression of PR-1a and PDF 1.2 constructs, had the ability to induce systemic resistance against the bacterial leaf speck pathogen Pseudomonas syringae pv. tomato DC3000 (Pst) in Arabidopsis thaliana. Arabidopsis plants treated with CFs of Phoma sp. (GS6-2 and GS7-3) and sterile fungus (GU23-3) elicited ISR against the Pst pathogen, resulting in a reduction in the number of symptomatic leaves, restriction of disease severity, and suppression of pathogen proliferation, with the best results obtained with Phoma sp. To determine the mechanism used to induce systemic resistance, Arabidopsis genotypes expressing the bacterial salicylate hydroxylase gene or containing disruptions in the nonexpressor of pathogenesis-related genes 1 (NPR 1), jasmonic acid JA, and ethylene (ET) signaling were screened. We demonstrate that signal transduction leading to GS6-2-mediated ISR requires salicylic acid (SA) accumulation, whereas CF of GU23-3-mediated ISR stimulates a pathway dependent on JA signaling. However, GS7-3-mediated ISR does not require SA, JA, ET, or NPRl signaling. Our results suggest that ISR mediated by three PGPF isolates studied were divergent in the biochemical pathways affected.
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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".