Transcriptome profiling of rice roots in early response to <i>Bacillus</i> <i>subtilis</i> (RR4) colonization
Bibliographic record
Abstract
Bacillus subtilis, a gram-positive soil bacterium, is widely used as a plant-growth-promoting agent. However, how Bacillus initially colonizes rice roots and evades the plant primary defense mechanisms, and how it influences root secretion of phytochemicals for further colonization remain obscure. To get an insight into how a plant perceives the bacterium upon initial root colonization, a microarray analysis was performed using rice roots treated with a rice rhizosphere isolate, B. subtilis RR4. About 891 transcripts (255 up-regulated and 636 down-regulated) were differentially expressed, indicating that the bacteria reprogram the plant to colonize it. In our experiments, RR4 mainly caused the suppression of transcripts encoding defense response enzymes such as chitinase, cell-wall-modifying enzymes such as pectinesterase, and genes associated with transport/exudation of phytochemicals, signifying that the bacteria modulate the gene expression of the plant to facilitate its colonization. Genes that regulate secondary metabolite production were up-regulated. Although the defense response genes in rice roots were suppressed initially, they were induced gradually at 4 and 10 days post-treatment. This was accompanied by an increased level of salicylic acid in the colonized rice roots. Thus, our results show that B. subtilis alters the transcriptome of rice roots for initial colonization by initially lowering the plants’ defenses, limiting root exudation and active cell growth, but boosting the plants’ defenses at a later stage.
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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) | 0.001 | 0.001 |
| 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".