Protease activities of vaginal Porphyromonas species disrupt coagulation and extracellular matrix in the cervicovaginal niche
Bibliographic record
Abstract
Porphyromonas asaccharolytica and Porphyromonas uenonis are common inhabitants of the vaginal microbiome, but their presence has been linked to adverse health outcomes for women, including bacterial vaginosis and preterm birth. However, little is known about the pathogenesis mechanisms of these bacteria. The related oral opportunistic pathogen, Porphyromonas gingivalis, is comparatively well-studied and known to secrete numerous extracellular matrix-targeting proteases. Among these are the gingipain family of cysteine proteases that drive periodontal disease progression and hematogenic transmission to the placenta. In this study, we demonstrate that vaginal Porphyromonas species secrete broad-acting proteases capable of freely diffusing within the cervicovaginal niche. These proteases degrade collagens that are enriched within the cervix (type I) and chorioamniotic membranes (type IV), as well as fibrinogen, which inhibits clot formation. Bioinformatic queries confirmed the absence of gingipain orthologs and identified five serine, cysteine, and metalloprotease candidates in each species. Inhibition assays revealed that each species' proteolytic activity can be partially attributed to a secreted metalloprotease with broad substrate specificity that is distantly related to the P. gingivalis endopeptidase PepO. This characterization of virulence activities in vaginal Porphyromonas species highlights their potential to alter the homeostasis of reproductive tissues and harm human pregnancy through clotting disruption, fetal membrane weakening, and premature cervical remodeling.
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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 | 0.001 | 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".