Amino Acids From Root Exudates Induce <i>Bacillus</i> Spore Germination to Enhance Root Colonisation and Plant Growth Promotion
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Bibliographic record
Abstract
Strains of Bacillus species, plant growth-promoting rhizobacteria, have been commercialised as biofertilisers; they are ideal for this because these species form spores that can be stored stably for a long time. However, for these spores to exert their full beneficial effects, they must germinate. The specific germination signals in the rhizosphere, particularly those from plant root exudates, remain largely unknown. Here, we investigated the germination signals from different growth states of cucumber (Cucumis sativus) for spores of Bacillus velezensis SQR9 and Bacillus subtilis NCIB 3610. We identified the corresponding germination receptors and compared them biochemically between the Bacillus species. Larger plants better stimulated spore germination. Five amino acids-L-isoleucine, L-ornithine, L-valine, L-serine and β-alanine were-identified as spore germination signals. Combined application of a mixture of these amino acids with bacterial spores markedly enhanced the cucumber growth-promoting properties of B. velezensis SQR9. The germination receptor for these amino acids was GerA in both Bacillus species. Differences in spore germination efficiency between B. subtilis and B. velezensis may be attributable to variations in the GerA ligand-recognition sites. Expression of GerA from B. subtilis NCIB 3610 in B. velezensis SQR9 enhanced the spore germination rate of the latter. Our study highlights the pivotal role of amino acids in regulating spore germination of Bacillus and subsequent plant root colonisation, emphasising their potential to enhance the efficacy of Bacillus-based biofertilisers. Engineering of germination receptors is a promising approach to enhance the spore germination efficiency of biofertiliser strains.
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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 it