Major changes in grapevine wood microbiota are associated with the onset of esca, a devastating trunk disease
Bibliographic record
Abstract
Esca, a major grapevine trunk disease in old grapevines, is associated with the colonization of woody tissues by a broad range of plant pathogenic fungi. To identify which fungal and bacterial species are involved in the onset of this disease, we analysed the microbiota from woody tissues of young (10-year-old) grapevines at an early stage of esca. Using meta-barcoding, 515 fungal and 403 bacterial operational taxonomic units (OTUs) were identified in woody tissues. In situ hybridization showed that these fungi and bacteria co-inhabited in grapevine woody tissues. In non-necrotic woody tissues, fungal and bacterial microbiota varied according to organs and seasons but not diseased plant status. Phaeomoniella chlamydospora, involved in the Grapevine trunk disease, was the most abundant species in non-necrotic tissues from healthy plants, suggesting a possible non-pathogenic endophytic behaviour. Most diseased plants (70%) displayed cordons, with their central white-rot necrosis colonized essentially by two plant pathogenic fungi (Fomitiporia mediterranea: 60%-90% and P. chlamydospora: 5%-15%) and by a few bacterial taxa (Sphingomonas spp. and Mycobacterium spp.). The occurrence of a specific association of fungal and bacterial species in cordons from young grapevines expressing esca-foliar symptoms strongly suggests that that microbiota is involved in the onset of this complex disease.
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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) | 0.000 | 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 teacher head, 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".