Induction of antimicrobial peptides from<i>Rana dybowskii</i>under Rana grylio virus stress, and bioactivity analysis
Bibliographic record
Abstract
The skin glands of Ranidae are a rich source of antimicrobial peptides. In this study, the genomic RNA of Rana dybowskii was extracted from its skin while under Rana grylio virus stress. Five new cDNA sequences encoding 5 mature peptides, Ranatuerin-2YJ (GLMDIFKVAVNKLLAAGMNKPRCKAAHC), Dybowskin-YJb (IIPLPLGYFAKKP), Dybowskin-YJa (IIPLPLGYFAKKKKKKDPVPLDQ), Temperin-YJa (VLPLLETCSMTCWENNQTFGK), and Temperin-YJb (VLPLVGNLLNDLLGK), were obtained by reverse transcription polymerase chain reaction with a pair of degenerate primers designed according to the conserved terminal sequences of cDNA encoding antimicrobial peptide precursors of genus Rana. The antimicrobial activities of the peptides were analyzed, and the results demonstrated that all these peptides showed a significant anti-Rana grylio virus activity, and the virus was gradually cleared with the increase in gene expression. Among the 5 peptides obtained in this work, Ranatuerin-2YJ also showed a broad-spectrum anti-Gram-positive bacteria and anti-Gram-negative bacteria activity with a minimal inhibitory concentration of 22.5 µg/mL and 7.64% hemolysis activity, both of which were significantly lower (p < 0.05) than that of the other peptides. Moreover, Ranatuerin-2YJ was widely distributed in the skin, liver, spleen, and blood of R. dybowskii, while the other 4 peptides could only be cloned from the skin, indicating that the Ranatuerin-2YJ in vivo plays an important role in the protection against pathogen invasion.
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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 | 0.000 |
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".