Integrated Metabolo-Proteomic Approach to Decipher the Mechanisms by Which Wheat QTL (Fhb1) Contributes to Resistance against Fusarium graminearum
Bibliographic record
Abstract
BACKGROUND: Resistance in plants to pathogen attack can be qualitative or quantitative. For the latter, hundreds of quantitative trait loci (QTLs) have been identified, but the mechanisms of resistance are largely unknown. Integrated non-target metabolomics and proteomics, using high resolution hybrid mass spectrometry, were applied to identify the mechanisms of resistance governed by the fusarium head blight resistance locus, Fhb1, in the near isogenic lines derived from wheat genotype Nyubai. FINDINGS: The metabolomic and proteomic profiles were compared between the near isogenic lines (NIL) with resistant and susceptible alleles of Fhb1 upon F. graminearum or mock-inoculation. The resistance-related metabolites and proteins identified were mapped to metabolic pathways. Metabolites of the shunt phenylpropanoid pathway such as hydroxycinnamic acid amides, phenolic glucosides and flavonoids were induced only in the resistant NIL, or induced at higher abundances in resistant than in susceptible NIL, following pathogen inoculation. The identities of these metabolites were confirmed, with fragmentation patterns, using the high resolution LC-LTQ-Orbitrap. Concurrently, the enzymes of phenylpropanoid biosynthesis such as cinnamyl alcohol dehydrogenase, caffeoyl-CoA O-methyltransferase, caffeic acid O-methyltransferase, flavonoid O-methyltransferase, agmatine coumaroyltransferase and peroxidase were also up-regulated. Increased cell wall thickening due to deposition of hydroxycinnamic acid amides and flavonoids was confirmed by histo-chemical localization of the metabolites using confocal microscopy. CONCLUSION: The present study demonstrates that the resistance in Fhb1 derived from the wheat genotype Nyubai is mainly associated with cell wall thickening due to deposition of hydroxycinnamic acid amides, phenolic glucosides and flavonoids, but not with the conversion of deoxynivalenol to less toxic deoxynivalenol 3-O-glucoside.
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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 | 0.001 | 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".