Novel Antimicrobial Peptides Derived from Flatfish Genes
Bibliographic record
Abstract
We report on the identification of active novel antimicrobials determined by screening both the genomic information and the mRNA transcripts from a number of different flatfish for sequences encoding antimicrobial peptides, predicting the sequences of active peptides from the genetic information, producing the predicted peptides chemically, and testing them for their activities. We amplified 35 sequences from various species of flatfish using primers whose sequences are based on conserved flanking regions of a known antimicrobial peptide from winter flounder, pleurocidin. We analyzed the sequences of the amplified products and predicted which sequences were likely to encode functional antimicrobial peptides on the basis of charge, hydrophobicity, relation to flanking sequences, and similarity to known active peptides. Twenty peptides were then produced synthetically and tested for their activities against gram-positive and gram-negative bacteria and the yeast Candida albicans. The most active peptide (with the carboxy-terminus amidated sequence GWRTLLKKAEVKTVGKLALKHYL, derived from American plaice) showed inhibitory activity over a concentration range of 1 to 8 micro g/ml against a test panel of pathogens, including the intrinsically antibiotic-resistant organism Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus, and C. albicans. The methods described here will be useful for the identification of novel peptides with good antimicrobial activities.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".