Isolate Identity Determines Plant Tolerance to Pathogen Attack in Assembled Mycorrhizal Communities
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) are widespread soil microorganisms that associate mutualistically with plant hosts. AMF receive photosynthates from the host in return for various benefits. One of such benefits is in the form of enhanced pathogen tolerance. However, this aspect of the symbiosis has been understudied compared to effects on plant growth and its ability to acquire nutrients. While it is known that increased AMF species richness positively correlates with plant productivity, the relationship between AMF diversity and host responses to pathogen attack remains obscure. The objective of this study was to test whether AMF isolates can differentially attenuate the deleterious effects of a root pathogen on plant growth, whether the richest assemblage of AMF isolates provides the most tolerance against the pathogen, and whether AMF-induced changes to root architecture serve as a mechanism for improved plant disease tolerance. In a growth chamber study, we exposed the plant oxeye daisy (Leucanthemum vulgare) to all combinations of three AMF isolates and to the plant root pathogen Rhizoctonia solani. We found that the pathogen caused an 81% reduction in shoot and a 70% reduction in root biomass. AMF significantly reduced the highly deleterious effect of the pathogen. Mycorrhizal plants infected with the pathogen produced 91% more dry shoot biomass and 72% more dry root biomass relative to plants solely infected with R. solani. AMF isolate identity was a better predictor of AMF-mediated host tolerance to the pathogen than AMF richness. However, the enhanced tolerance response did not result from AMF-mediated changes to root architecture. Our data indicate that AMF communities can play a major role in alleviating host pathogen attack but this depends primarily on the capacity of individual AMF isolates to provide this benefit.
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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 | 0.001 |
| 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) | 0.000 | 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".