Induction of Systemic Resistance against Aphids by Endophytic Bacillus velezensis YC7010 via Expressing PHYTOALEXIN DEFICIENT4 in Arabidopsis
Bibliographic record
Abstract
Aphids are the most destructive insect pests. They suck the sap and transmit plant viruses, causing widespread yield loss of many crops. A multifunctional endophytic bacterial strain Bacillus velezensis YC7010 has been found to induce systemic resistance against bacterial and fungal pathogens of rice. However, its activity against insects attack and underlying cellular and molecular defense mechanisms are not elucidated yet. Here we show that root drenching of Arabidopsis seedlings with B. velezensis YC7010 can induce systemic resistance against green peach aphid (GPA), Myzus persicae. Treatment of bacterial suspension of B. velezensis YC7010 at 2 × 107 CFU/ml to Arabidopsis rhizosphere induced higher accumulation of hydrogen peroxide, cell death and callose deposition in leaves compared to untreated plants at six days after infestation of GPA. Salicylic acid, jasmonic acid, ethylene and abscisic acid were not required to confer defense against GPA in Arabidopsis plants treated by B. velezensis YC7010. Bacterial treatment with B. velezensis YC7010 significantly reduced settling, feeding and reproduction of GPA on Arabidopsis leaves via strongly expressing senescence-promoting gene PHYTOALEXIN DEFICIENT4 (PAD4) while suppressing BOTRYTIS-INDUCED KINASE1 (BIK1). These results indicate that B. velezensis YC7010-induced systemic resistance to the GPA is a hypersensitive response mainly dependent on higher expression of PAD4 with suppression of BIK1, resulting in more accumulation of hydrogen peroxide, cell death and callose deposition in Arabidopsis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".