Mechanisms of plant growth promotion of Pseudomonas chlororaphis PA23 and potential effects on soil microbial communities
Bibliographic record
Abstract
Plant growth-promoting bacteria (PGPB) are a heterogeneous group of soil microbes that confer beneficial effects to plants. Recent interest in sustainable and organic agriculture has highlighted the potential uses of PGPB as agricultural adjuncts. Currently, PGPB are used to increase crop yield and productivity. Substantial work has been done on the active metabolites secreted by PGPB that drive plant growth. However, little is known about their effects on the global transcriptome of the host plant. P. chlororaphis PA23 is a gram-negative bacterium that has shown great potential as a plant growth promoting agent. Using a combination of next-generation RNA sequencing and bioinformatic analyses, the mechanisms that underlie P. chlororaphis PA23 induced growth in Brassica napus seedlings were investigated. The results showed that P. chlororaphis modulates plant phytohormone signaling systems resulting in elevated expression levels of genes associated with photosynthesis and root hair development. Next, the scalability of P. chlororaphis PA23 as an agricultural adjunct with a Glycine max field study was investigated. An increase in soybean pod set following P. chlororaphis PA23 treatment was observed, suggesting plant growth-promoting activity under field conditions. To determine the effects of P. chlororaphis PA23 on the microbial communities found in the soil, a combination of marker-based sequencing and bioinformatic analyses were utilized. Here I report that the addition of P. chlororaphis PA23 does not alter the bacterial or fungal species diversity. Furthermore, I report that the community composition within the rhizosphere does not change in response to P. chlororaphis PA23. This research provides the necessary information for the development of P. chlororaphis PA23 as an agricultural adjunct and lays the foundation for multi-year field studies that integrate the utilization of P. chlororaphis PA23 as a PGPB.
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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) | 0.001 | 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 | 0.001 | 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".