Characterization of the active fragments of <i>Spodoptera litura</i> Lebocin‐1
Bibliographic record
Abstract
Insects can produce various antimicrobial peptides (AMPs) upon immune stimulation. One class of AMPs are characterized by their high proline content in certain fragments. They are generally called proline-rich antimicrobial peptides (PrAMPs). We previously reported the characterization of Spodoptera litura lebocin-1 (SlLeb-1), a PrAMP proprotein. Preliminary studies with synthetic polypeptides showed that among the four deductive active fragments, the C-terminal fragment SlLeb-1 (124-158) showed strong antibacterial activities. Here, we further characterized the antibacterial and antifungal activities of 124-158 and its four subfragments: 124-155, 124-149, 127-158, and 135-158. Only 124-158 and 127-158 could agglutinate bacteria, while 124-158 and four subfragments all could agglutinate Beauveria bassiana spores. Confocal microscopy showed that fluorescent peptides were located on the microbial surface. Fragment 135-158 lost activity completely against Escherichia coli and Staphylococcus aureus, and partially against Bacillus subtilis. Only 124-149 showed low activity against Serratia marcescens. Negative staining, transmission, and scanning electron microscopy of 124-158 treated bacteria showed different morphologies. Flow cytometry analysis of S. aureus showed that 124-158 and four subfragments changed bacterial subpopulations and caused an increase of DNA content. These results indicate that active fragments of SlLeb-1 may have diverse antimicrobial effects against different microbes. This study may provide an insight into the development of novel antimicrobial agents.
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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 | 0.000 | 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 | 0.001 |
| 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".