Arbuscular mycorrhisation with Glomus irregulare induces expression of potato PR homologues genes in response to infection by Fusarium sambucinum
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) are symbiotic, root-inhabiting fungi colonising a wide range of vascular plant species. We previously showed that AMF modulate the expression of mycotoxin genes in Fusarium sambucinum. Here, we tested the hypothesis that AMF may induce defence responses in potato to protect against infection with F. sambucinum. We analysed the response of AMF-colonised potato plants to the pathogenic fungus F. sambucinum by monitoring the expression of defence-related genes ChtA3, gluB, CEVI16, OSM-8e and PR-1. In response to F. sambucinum infection, we found that the AMF treatment upregulated the expression of all defence genes except OSM-8e in potato roots at 72 and 120h post infection (hpi). However, we found variable transcriptional regulation with gluB and CEVI16 in shoots at both times 72 and 120hpi in AMF-colonisation and infected plants. Overall, differential regulation of defence-related genes in leaf tissues indicate that AMF are a systemic bio-inducer and their effect could extend into non-infected parts. Thus, AMF significantly suppressed disease severity of F. sambucinum on potato plants compared with those infected and non-mycorrhizal plants. Furthermore, the AMF treatment decreased the negative effects of F. sambucinum on biomass and potato tuber production.
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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".