Manipulation of the seagrass‐associated microbiome reduces disease severity
Bibliographic record
Abstract
Host-associated microbes influence host health and function and can be a first line of defence against infections. While research increasingly shows that terrestrial plant microbiomes contribute to bacterial, fungal, and oomycete disease resistance, no comparable experimental work has investigated marine plant microbiomes or more diverse disease agents. We test the hypothesis that the eelgrass (Zostera marina) leaf microbiome increases resistance to seagrass wasting disease. From field eelgrass with paired diseased and asymptomatic tissue, 16S rRNA gene amplicon sequencing revealed that bacterial composition and richness varied markedly between diseased and asymptomatic tissue in one of the two years. This suggests that the influence of disease on eelgrass microbial communities may vary with environmental conditions. We next experimentally reduced the eelgrass microbiome with antibiotics and bleach, then inoculated plants with Labyrinthula zosterae, the causative agent of wasting disease. We detected significantly higher disease severity in eelgrass with a native microbiome than an experimentally reduced microbiome. Our results over multiple experiments do not support a protective role of the eelgrass microbiome against L. zosterae. Further studies of these marine host-microbe-pathogen relationships may continue to show new relationships between plant microbiomes and diseases.
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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) | 0.002 | 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".