Comparison of pathogen‐induced expression and efficacy of two amphibian antimicrobial peptides, MsrA2 and temporin A, for engineering wide‐spectrum disease resistance in tobacco
Bibliographic record
Abstract
The rapid accumulation of defensive transgene products in plants only on pathogen invasion has clear advantages over their constitutive synthesis. In this study, two antimicrobial peptides from the skin secretions of frogs, MsrA2 (N-methionine-dermaseptin B1) and temporin A, were evaluated for engineering pathogen-induced disease resistance in plants. Both peptides inhibited plant-specific pathogens in vitro at micromolar concentrations that were not toxic to plant protoplasts. The plant-optimized nucleotide sequences encoding MsrA2 and temporin A were transcriptionally fused to the inducible win3.12T poplar promoter, which had strong systemic activity in response to fungal infection, and introduced into tobacco (Nicotiana tabacum L. cv. Xanthi). Transgene expression was very low in the leaves of unstressed plants; however, it was strongly increased after pathogen challenge or wounding. The pathogen responsiveness of the win3.12T promoter was found to be universal rather than species specific, with high activity in response to all pathogens tested. On induction, the amount of MsrA2 was up to 6-7 microg per gram of fresh leaf tissue. Most importantly, the induced accumulation of MsrA2 and temporin A in transgenic tobacco was sufficient to confer resistance to a variety of phytopathogenic fungi, such as Fusarium solani, F. oxysporum, Alternaria alternata, Botrytis cinerea, Sclerotinia sclerotiorum, the oomycete Pythium aphanidermatum and the bacterium Pectobacterium carotovorum. The accumulation of these peptides in transgenic plants did not alter the normal phenotype of tobacco. Thus, the expression of MsrA2 and temporin A in a pathogen-inducible manner enables the development of tobacco, and possibly other plant species, with wide-spectrum disease resistance, which can reduce the use of pesticides and the associated environmental risks.
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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) | 0.001 | 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) | 0.000 | 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".