Conjugation-mediated DNA delivery to the filamentous fungus <i>Ustilago maydis</i>
Bibliographic record
Abstract
ABSTRACT Phytopathogenic fungi are ubiquitous throughout the environment and threaten global food security. This issue is further amplified by the increasing resistance of pathogens to antimicrobials. Current chemical-based antifungals target cells by inhibiting growth or metabolic function, making them ideal for fungal gain of resistance mutations. Biofungicides are a rising class of antifungals that have low potential for negative environmental impact and provide the fungi almost no potential for gaining resistance. Conjugative plasmids which play a role in the natural mechanism of horizontal gene transfer in bacteria, have been repurposed to deliver toxic genetic cargo to recipient cells, showing promise as next-generation antimicrobial agents. In this work, we have demonstrated the first protocol for delivering DNA from Escherichia coli to the filamentous phytopathogen, Ustilago maydis through conjugation. DNA delivery was confirmed using PCR screening of DNA isolated from the re-streaked transconjugants. Although challenges such as reduced conjugation efficiency and extrachromosomal replication persist, this work establishes the first step towards creating a conjugation-based biofungicide.
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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 | 0.000 |
| 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".