Pathophysiological responses of pine defensive metabolites largely lack differences between pine species but vary with eliciting ophiostomatoid fungal species
Bibliographic record
Abstract
Phytopathogenic ophiostomatoid fungi are common associates of bark beetles and contribute to beetle-associated mortality of trees. Mountain pine beetle outbreaks in Canada are facilitating novel associations between its vectored fungi (Grosmannia clavigera, Leptographium longiclavatum and Ophiostoma montium) and jack pine. How the induced defense-related metabolite responses of jack and lodgepole pines vary in response to the fungi is unknown. Understanding this variation is important to clarifying pine susceptibility to and the physiological impacts of infection. We used a comparative metabolite profiling approach to investigate the defense-related signaling, carbon utilization/mobilization, and synthesis responses of both pines to the fungi. Both pine species largely exhibited similar metabolite responses to the fungi. The magnitude of pine metabolite responses positively reflected pathogen virulence. Our findings indicate that pines can recognize and metabolomically respond to novel pathogens, likely due to signals common between the novel fungi and fungi coevolved with the pine. Thus, jack pine is likely as susceptible as lodgepole pine to infections by each of the MPB-vectored fungi. Furthermore, the magnitude of the metabolite responses of both pines varied by the eliciting fungal species, with the most virulent pathogen causing the greatest reduction in carbohydrates and the highest accumulation of defensive terpenes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".