Synthetic Metabolites Derived From Host‐Exudates Modulate the Bacterial Wilt Occurrence
Bibliographic record
Abstract
Root exudate-mediated microbial community assembly is critical for host health and growth. However, disease-induced variations in plant-microbe interactions remain ambiguous. Here, we explored the intrinsic distinctions and interactions between the secretion patterns and microbial community composition of diseased and healthy tomatoes. Our results showed that rhizosphere microbial communities in healthy and diseased tomatoes were dominated by potentially beneficial genera (Bacillus, Rhodanobacter, Pseudolabrys, Gemmatimonas, Dongia, and Bradyrhizobium) and putative pathogens (Ralstonia and Neocosmospora), respectively, which were correlated with differential metabolites. Further metabolite addition experiments demonstrated the differential regulation mechanism of specific metabolites on host health. Drawing inspiration from synthetic communities, we displayed a way to construct the synthetic metabolites (SynMets), and we found that the SynMets (cortisol, quercetin, pyridoxal, and levodopa), which were enriched in healthy tomatoes could resist diseases by inhibiting pathogen growth and constructing beneficial microbial communities. Conversely, the SynMets (pyridoxine, N-benzylformamide, isoquinoline, and xanthine) enriched in diseased tomatoes could result in microbial imbalances by facilitating pathogen growth, thereby causing disease occurrence and growth limitation. In total, our research indicated the importance of SynMets-mediated pathogen reproduction and microbial community assembly for plant health and lays a foundation for targeted regulation of rhizosphere microecology through synthetic metabolites.
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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".