Hyaluronate lyase activity of Streptococcus suis serotype 2 and modulatory effects of hyaluronic acid on the bacterium’s virulence properties
Bibliographic record
Abstract
BACKGROUND: Streptococcus suis serotype 2 is a major swine pathogen and zoonotic agent worldwide causing mainly meningitis and septicemia. Hyaluronate lyases are enzymes that degrade hyaluronic acid, a major constituent of animal tissues, and have been reported as virulence factors in various bacterial species. Since the hyaluronate lyase of S. suis has been considered ambiguously as a virulence factor, we screened 50 isolates from the three major clonal complexes found in North America (sequence type [ST] 1, ST25, and ST28) known to differ in their degree of virulence in order to link the presence or absence of this activity with the degree of virulence. Moreover, the effect of exogenous hyaluronic acid on S. suis virulence factor gene expression and the pro-inflammatory response of brain macrovascular endothelial cells (BMEC) was also investigated. RESULTS: We found that all but one ST1 isolates (high virulence) were devoid of hyaluronate lyase activity whereas all ST25 (intermediate virulence) and ST28 (low virulence) isolates possessed the activity. A 2 bp insertion was responsible for the lack of activity in ST1 strains. Since the most virulent isolates did not degrade hyaluronic acid, this tissue component may be found during the infectious process. Therefore, we investigated its effect on S. suis and host cells. Hyaluronic acid was found to modulate S. suis adhesion to BMEC, to increase S. suis virulence factor expression, and to enhance pro-inflammatory cytokine secretion by BMEC. CONCLUSIONS: These findings suggest that S. suis hyaluronate lyase does not represent a critical virulence factor in its active form. However, exogenous hyaluronic acid that is likely to interact with S. suis and host cells during the course of infection appears to modulate several virulence determinants of the bacterium, in addition to promote inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 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".