The recombinant pea defensin Drr230a is active against impacting soybean and cotton pathogenic fungi from the genera Fusarium, Colletotrichum and Phakopsora
Bibliographic record
Abstract
Plant defensins are antifungal peptides produced by the innate immune system plants developed to circumvent fungal infection. The defensin Drr230a, originally isolated from pea, has been previously shown to be active against various entomopathogenic and phytopathogenic fungi. In the present study, the activity of a yeast-expressed recombinant Drr230a protein (rDrr230a) was tested against impacting soybean and cotton fungi. First, the gene was subcloned into the yeast expression vector pPICZαA and expressed in Pichia pastoris . Resulting rDrr230a exhibited in vitro activity against fungal growth and spore germination of Fusarium tucumaniae , which causes soybean sudden death syndrome, and against Colletotrichum gossypii var. cephalosporioides , which causes cotton ramulosis. The rDrr230a IC 50 corresponding to inhibition of fungal growth of F. tucumaniae and C. gossypii var. cephalosporioides was 7.67 and 0.84 µM, respectively, demonstrating moderate activity against F. tucumaniae and high potency against C. gossypii var. cephalosporioides . Additionally, rDrr230a at 25 ng/µl (3.83 µM) resulted in 100 % inhibition of spore germination of both fungi, demonstrating that rDrr230a affects fungal development since spore germination. Moreover, rDrr230a at 3 µg/µl (460.12 µM) inhibited 100 % of in vitro spore germination of the obligatory biotrophic fungus Phakopsora pachyrhizi , which causes Asian soybean rust. Interestingly, rDrr230a substantially decreased the severity of Asian rust, as demonstrated by in planta assay. To our knowledge, this is the first report of a plant defensin active against an obligatory biotrophic phytopathogenic fungus. Results revealed the potential of rDrr230a as a candidate to be used in plant genetic engineering to control relevant cotton and soybean fungal diseases.
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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 | 0.000 |
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".