Simultaneous Boosting of Plant Growth and Immunity by <i>Bacillus</i> volatiles Through GLK‐Mediated Enhancement of Chloroplast Functions
Bibliographic record
Abstract
Microbial volatile organic compounds (mVOCs) offer significant benefits to plants, such as promoting growth and activating immune responses, positioning them as promising tools for crop productivity. However, the mechanisms driving mVOCs-mediated plant growth promotion (PGP) and immunity remain unclear. Here, we demonstrated that VOCs produced by the rapeseed (Brassica napus)-derived endophyte Bacillus velezensis CanL-30 (BvVOCs) simultaneously stimulate PGP and immunity in both Arabidopsis thaliana and rapeseed under controlled and field conditions. Gas chromatography-mass spectrometry analysis revealed that 2-heptanone and 2-nonanone in BvVOCs exhibit plant-growth-promoting activity, whereas decane and undecane possess disease resistance-inducing activity in plants. Using metabolomics and transcriptomics, along with genetic and chemical methodologies, we reveal that BvVOCs enhance photosynthetic capacity to promote growth, while jasmonic acid-dependent signalling underpins immunity activation. Furthermore, light intensity significantly influenced BvVOCs effects on PGP and immunity. Crucially, BvVOCs upregulate expression of the GOLDEN2-LIKE (GLK) transcription factors GLK1 and GLK2, and BvVOCs-driven PGP and immunity were lost in glk1glk2 double mutant plants. These findings clarify the molecular basis of Bacillus-based VOCs in boosting growth and disease resistance, underscoring their potential for sustainable pest management in agriculture.
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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".