Bacterial Blight Induced Shifts in Endophytic Microbiome of Rice Leaves and the Enrichment of Specific Bacterial Strains With Pathogen Antagonism
Bibliographic record
Abstract
The endophytic microbiome plays an important role in plant health and pathogenesis. However, little is known about its relationship with bacterial blight (BB) of rice caused by Xanthomonas oryzae pv. oryzae (Xoo). The current study compared the community compositional structure of the endophytic microbiota in healthy and BB symptomatic leaves of rice through a metabarcoding approach, which revealed BB-induced a decrease in the alpha-diversity of the fungal communities and an increase in the bacterial communities. BB-diseased rice leaves were enriched with saprophytic fungi that are capable of decomposing plant cell walls (e.g. Khuskia spp. and Leptosphaerulina spp), while healthy rice leaves were found to be significantly more abundant with plant pathogens or mycotoxin-producing fungi (e.g. Fusarium, Magnaporthe, and Aspergillus). The endophytic bacterial communities of BB-diseased leaves were significantly enriched with Pantoea, Pseudomonas, and Curtobacterium, strains. Pantoea sp. isolates from BB leaves are identified as promising candidates for the biocontrol of BB for their ability to inhibit in vitro growth of Xoo, suppress the development of rice BB disease, and possess multiple PGP characteristics. Our study revealed BB-induced complexed changes in the endophytic fungal and bacterial communities of rice leaves, and demonstrated that BB-associated enrichment of some endophytic bacterial taxa, e.g. Pantoea sp. isolates, may play important roles in suppressing the development of BB disease in rice.
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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".