Herbicides as fungicides: Targeting heme biosynthesis in the maize pathogen <i>Ustilago maydis</i>
Bibliographic record
Abstract
Pathogens must efficiently acquire nutrients from host tissue to proliferate, and strategies to block pathogen access therefore hold promise for disease control. In this study, we investigated whether heme biosynthesis is an effective target for ablating the virulence of the phytopathogenic fungus Ustilago maydis on maize plants. We first constructed conditional heme auxotrophs of the fungus by placing the heme biosynthesis gene hem12 encoding uroporphyrinogen decarboxylase (Urod) under the control of nitrogen or carbon source-regulated promoters. These strains were heme auxotrophs under non-permissive conditions and unable to cause disease in maize seedlings, thus demonstrating the inability of the fungus to acquire sufficient heme from host tissue to support proliferation. Subsequent experiments characterized the role of endocytosis in heme uptake, the susceptibility of the fungus to heme toxicity as well as the transcriptional response to exogenous heme. The latter RNA-seq experiments identified a candidate ABC transporter with a role in the response to heme and xenobiotics. Given the importance of heme biosynthesis for U. maydis pathogenesis, we tested the ability of the well-characterized herbicide BroadStar to influence disease. This herbicide contains the active ingredient flumioxazin, an inhibitor of Hem14 in the heme biosynthesis pathway, and we found that it was an effective antifungal agent for blocking disease in maize. Thus, repurposing herbicides for which resistant plants are available may be an effective strategy to control pathogens and achieve crop protection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".