A proline rich protein from the gingival seal around teeth exhibits antimicrobial properties against Porphyromonas gingivalis
Bibliographic record
Abstract
The gingival seal around teeth prevents bacteria from destroying the tooth-supporting tissues and disseminating throughout the body. Porphyromonas gingivalis, a major periodontopathogen, degrades components of the specialized extracellular matrix that mediates attachment of the gingiva to the tooth. Of these, secretory calcium-binding phosphoprotein proline-glutamine rich 1 (SCPPPQ1) protein has a distinctive resistance to degradation, suggesting that it may offer resistance to bacterial attack. In silico analysis of its amino acid sequence was used to explore its molecular characteristics and to predict its two- and three-dimensional structure. SCPPPQ1 exhibits similarities with both proline-rich and cationic antimicrobial proteins, suggesting a putative antimicrobial potential. A combination of imaging approaches showed that incubation with 20 μM of purified SCPPPQ1 decrease bacterial number (p < 0.01). Fluorescence intensity decreased by 70% following a 2 h incubation of Porphyromonas gingivalis with the protein. Electron microscopy analyses revealed that SCPPPQ1 induced bacterial membrane disruption and breaches. While SCPPPQ1 has no effect on mammalian cells, our results suggest that it is bactericidal to Porphyromonas gingivalis, and that this protein, normally present in the gingival seal, may be exploited to maintain a healthy seal and prevent systemic dissemination of bacteria.
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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) | 0.001 | 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".