Isolation, Characterization and Biological Properties of Membrane Vesicles Produced by the Swine Pathogen Streptococcus suis
Bibliographic record
Abstract
Streptococcus suis, more particularly serotype 2, is a major swine pathogen and an emerging zoonotic agent worldwide that mainly causes meningitis, septicemia, endocarditis, and pneumonia. Although several potential virulence factors produced by S. suis have been identified in the last decade, the pathogenesis of S. suis infections is still not fully understood. In the present study, we showed that S. suis produces membrane vesicles (MVs) that range in diameter from 13 to 130 nm and that appear to be coated by capsular material. A proteomic analysis of the MVs revealed that they contain 46 proteins, 9 of which are considered as proven or suspected virulence factors. Biological assays confirmed that S. suis MVs possess active subtilisin-like protease (SspA) and DNase (SsnA). S. suis MVs degraded neutrophil extracellular traps, a property that may contribute to the ability of the bacterium to escape the host defense response. MVs also activated the nuclear factor-kappa B (NF-κB) signaling pathway in both monocytes and macrophages, inducing the secretion of pro-inflammatory cytokines, which may in turn contribute to increase the permeability of the blood brain barrier. The present study brought evidence that S. suis MVs may play a role as a virulence factor in the pathogenesis of S. suis infections, and given their composition be an excellent candidate for vaccine development.
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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".