Lipid mediated plant immunity in susceptible and tolerant soybean cultivars in response to Phytophthora sojae colonization and infection
Bibliographic record
Abstract
BACKGROUND: Soybean is one of the most cultivated crops globally and a staple food for much of the world's population. The annual global crop losses due to infection by Phytophthora sojae is currently estimated at $20B USD, yet we have limited understanding of the role of lipid mediators in the adaptative strategies used by the host plant to limit infection. Since root is the initial site of this infection, we examined the infection process in soybean root infected with Phytophthora sojae using scanning electron microscopy to observe the changes in root morphology and a multi-modal lipidomics approach to investigate how soybean cultivars remodel their lipid mediators to successfully limit infection by Phytophthora sojae. RESULTS: The results reveal the presence of elevated biogenic crystals and more severe damaged cells in the root morphology of the infected susceptible cultivar compared to the infected tolerant cultivars. Furthermore, induced accumulation of stigmasterol was observed in the susceptible cultivar whereas, induced accumulation of phospholipids and glycerolipids occurred in tolerant cultivar. CONCLUSION: The altered lipidome reported in this study suggest diacylglycerol and phosphatidic acid mediated lipid signalling impacting phytosterol anabolism appears to be a strategy used by tolerant soybean cultivars to successfully limit infection and colonization by Phytophthora sojae.
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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) | 0.001 | 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".