The siderophore biosynthetic gene <i>SID1</i> , but not the ferroxidase gene <i>FET3</i> , is required for full <i>Fusarium graminearum</i> virulence
Bibliographic record
Abstract
SUMMARY: To acquire iron from plant hosts, fungal pathogens have evolved at least two pathways for iron uptake. One system is hinged on the secretion and subsequent uptake of low-molecular-weight iron chelators termed siderophores, while the other uses cell-surface reductases to solubilize ferric iron by reducing it to ferrous iron for uptake. We identified five iron uptake-related genes from the head blight pathogen Fusarium graminearum and showed that they were transcribed in response to iron limitation. To examine the relative contribution of the reductive and siderophore pathways of iron uptake, we created mutants disrupted at the ferroxidase gene FET3 (Deltafet3) or the siderophore biosynthetic gene SID1 (Deltasid1). The Deltafet3 mutants produced wild-type amounts of siderophores and grew at the same rate as the wild-type under iron limitation, but accumulated high levels of free intracellular iron. The Deltasid1 mutants did not produce siderophores and grew slowly under low iron conditions. Transcription of the iron uptake-related genes was induced in the Deltasid1 mutant regardless of the growth medium iron content, whereas these genes were transcribed normally in the Deltafet3 mutant. Finally, the Deltasid1 mutants could infect single, inoculated spikelets, but were unable to spread from spikelet-to-spikelet through the rachises of wheat spikes, while the Deltafet3 mutants behaved as wild-type throughout infection. Together, our data suggest that siderophore-mediated iron uptake is the major pathway of cellular iron uptake and is required for full virulence in F. graminearum.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".