Microcystis aeruginosa exudate alters root development by impacting plant hormone accumulation and auxin signal transduction
Bibliographic record
Abstract
Microcystis aeruginosa , a typical cyanobacterial species, can alter the root development of aquatic plants. To explore how M. aeruginosa affects plant root development, we exposed Arabidopsis thaliana to M. aeruginosa exudate (MaE) and investigated the responses of plant hormone synthesis and auxin signal transduction. Results showed that MaE significantly advanced lateral root primordium development, increased lateral root number, and reduced primary root length. On the 7th day of MaE exposure, the level of cytokinin in the total roots of A. thaliana decreased, consistent with the decreased expression of cytokinin synthesis and metabolism genes on Day 5 and Day 7. The pathogen defense hormones salicylic acid (SA) and N-(jasmonate)-S-JA-Ile(JA-Ile) concentration significantly increased in MaE-treated roots, although their synthesis and metabolism genes expression level were down-regulated. Similarly, although auxin compounds concentration in roots showed no significant difference, their synthesis and metabolism genes expression level were down-regulated. In the auxin signal transduction pathway, auxin signal input remained unchanged between MaE and the control group, as indicated by DII expression levels, while auxin signal output was amplified by MaE, as shown by increased DR5 expression levels. The transcription factor ARF7, which controls lateral root development and is downstream in the auxin signal transduction pathway, was significantly activated by MaE. These results indicate that MaE affects plant root system architecture by altering plant hormone balance and auxin signal transduction.
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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 | 0.000 |
| 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".