Interactions between <i>Fusarium graminearum</i> and hydroxycinnamic acids from cereal crops
Bibliographic record
Abstract
Hydroxycinnamic acids are abundant in kernel tissues of wheat and barley and contribute to defence against fusarium head blight. The fungal pathogen Fusarium graminearum possesses multiple genes encoding putative feruloyl esterases. These enzymes hydrolyze ester bonds that link hydroxycinnamic acids to structural polymers like arabinoxylans. We measured concentrations of hydroxycinnamic acids in barley during a malting procedure and demonstrate that the presence of F. graminearum significantly increased concentrations of free p-coumaric acid. When individual hydroxycinnamic acids were added to culture media at a 1 mm concentration, ferulic acid and p-coumaric acid reduced F. graminearum growth by approximately 70% and 30%, respectively. However, these hydroxycinnamic acids are readily metabolized by the fungus, which nearly eliminated an initial 0.5 mm concentration within 72 hours. Among six putative feruloyl esterase genes in the F. graminearum genome, faeC2 was the most highly expressed, and expression level was responsive to the available carbon source. We heterologously expressed FAEC2 and validated its activity as a feruloyl esterase enzyme, with higher activity on caffeic acid methyl ester compared to either ethyl ferulate or methyl 4-hydroxycinnamate. We also disrupted faeC2 through CRISPR-Cas9 gene editing and show that there is no evidence of compensatory upregulation of other fae genes, while most FAE enzyme activity is retained. This work enhances our understanding of what makes F. graminearum such a successful colonist of cereal crops and informs efforts to develop novel control strategies.
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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) | 0.001 | 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 | 0.001 |
| 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".