Salicylic acid fights against Fusarium wilt by inhibiting target of rapamycin signaling pathway in Fusarium oxysporum
Bibliographic record
Abstract
INTRODUCTION: Biofungicides with low toxicity and high efficiency are a global priority for sustainable agricultural development. Phytohormone salicylic acid (SA) is an ancient medicine against various diseases in humans and activates the immune system in plants, but little is known of its function as a biofungicide. OBJECTIVES: Here, Fusarium oxysporum, the causal agent of devastating Fusarium wilt and immunodepressed patients, was used as a model system to explore whether SA can enter the pathogen cells and suppress key targets of the pathogen. METHODS: Oxford Nanopore MinION sequencing and high-throughput chromosome conformation capture (Hi-C) sequencing were used to analyzed the genome of F. oxysporum. In addition, RNA-seq, qRT-PCR, and western blotting were conducted to detect gene and protein expression levels. RESULTS: We isolated and sequenced the genome of F. oxysporum from potato dry rot, and the F. oxysporum included 12 chromosomes and 52.3 Mb genomic length. Pharmacological assays showed that exogenous application of SA can efficiently arrest hyphal growth, spore production, and pathogenicity of F. oxysporum, whereas endogenous salicylate hydroxylases significantly detoxify SA. The synergistic growth inhibition of F. oxysporum was observed when SA was combined with rapamycin. Kinase assays showed that SA inhibits FoTOR complex 1 (FoTORC1) by activating FoSNF1 in vivo. Transgenic potato plants with the interference of FoTOR1 and FoSAH1 genes inhibited the invasive growth of hyphae and significantly prevented the occurrence of Fusarium wilt. CONCLUSION: This study revealed the underlying mechanisms of SA against F. oxysporum and provided insights into SA in controlling various fungal diseases by targeting the SNF1-TORC1 pathway of pathogens.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".