Colonization compatibility with <i>Bacillus altitudinis</i> confers soybean seed rot resistance
Bibliographic record
Abstract
The plant microbiome and plant-associated bacteria are known to support plant health, but there are limited studies on seed and seedling microbiome to reveal how seed-associated bacteria may confer disease resistance. In this study, the application of antibiotics on soybean seedlings indicated that seed-associated bacteria were involved in the seed rot resistance against a soil-borne pathogen Calonectria ilicicola, but this resistance cannot be carried to withstand root rot. Using PacBio 16S rRNA gene full-length sequencing and microbiome analyses, 14 amplicon sequence variants (ASVs) including 2 ASVs matching to Bacillus altitudinis were found to be more abundant in the four most resistant varieties versus the four most susceptible varieties. Culture-dependent isolation obtained two B. altitudinis isolates that both exhibit antagonistic capability against six fungal pathogens. Application of B. altitudinis on the most resistant and susceptible soybean varieties revealed different colonization compatibility, and the seed rot resistance was restored in the five varieties showing higher bacterial colonization. Moreover, quantitative PCR confirmed the persistence of B. altitudinis on apical shoots till 21 days post-inoculation (dpi), but 9 dpi on roots of the resistant variety TN5. As for the susceptible variety HC, the persistence of B. altitudinis was only detected before 6 dpi on both shoots and roots. The short-term colonization of B. altitudinis on roots may explain the absence of root rot resistance. Collectively, this study advances the insight of B. altitudinis conferring soybean seed rot resistance and highlights the importance of considering bacterial compatibility with plant varieties and colonization persistence on plant tissues.
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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 | 0.001 |
| 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".