A Novel Target-Specific, Salt-Resistant Antimicrobial Peptide against the Cariogenic Pathogen Streptococcus mutans
Bibliographic record
Abstract
In this study, we constructed and evaluated a target-specific, salt-resistant antimicrobial peptide (AMP) that selectively targeted Streptococcus mutans, a leading cariogenic pathogen. The rationale for creating such a peptide was based on the addition of a targeting domain of S. mutans ComC signaling peptide pheromone (CSP) to a killing domain consisting of a portion of the marine-derived, broad-spectrum AMP pleurocidin to generate a target-specific AMP. Here, we report the results of our assessment of such fusion peptides against S. mutans and two closely related species. The results showed that nearly 95% of S. mutans cells lost viability following exposure to fusion peptide IMB-2 (5.65 μM) for 15 min. In contrast, only 20% of S. sanguinis or S. gordonii cells were killed following the same exposure. Similar results were also observed in dual-species mixed cultures of S. mutans with S. sanguinis or S. gordonii. The peptide-guided killing was further confirmed in S. mutans biofilms and was shown to be dose dependent. An S. mutans mutant defective in the CSP receptor retained 60% survival following exposure to IMB-2, suggesting that the targeted peptide predominantly bound to the CSP receptor to mediate killing in the wild-type strain. Our work confirmed that IMB-2 retained its activity in the presence of physiological or higher salt concentrations. In particular, the fusion peptide showed a synergistic killing effect on S. mutans with a preventive dose of NaF. In addition, IMB-2 was relatively stable in the presence of saliva containing 1 mM EDTA and did not cause any hemolysis. We also found that replacement of serine-14 by histidine improved its activity at lower pH. Because of its effectiveness, salt resistance, and minimal toxicity to host cells, this novel target-specific peptide shows promise for future development as an anticaries agent.
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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) | 0.000 | 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 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".