Systemic inactivation and phenotypic characterization of two-component systems in expression of Streptococcus mutans virulence properties
Bibliographic record
Abstract
AIM: To assess potential function of each two-component signal transduction system in the expression of Streptococcus mutans virulence properties. METHODS AND RESULTS: For each two-component system (TCS), the histidine kinase-encoding gene was inactivated by a polymerase chain reaction (PCR)-based deletion strategy and the effects of gene disruption on the cell's ability to form biofilms, become competent, and tolerate acid, osmotic, and oxidative stress conditions were tested. Our results demonstrated that none of the mutations were lethal for S. mutans. The TCS-2 (CiaRH) is involved in biofilm formation and tolerance to environmental stresses, the TCS-3 (ScnRK-like) participates in the survival of cells at acidic pH, and the TCS-9 affects the acid tolerance response and the process of streptococcal competence development. CONCLUSIONS: Our results confirmed the physiological role of the TCS in S. mutans cellular function, in particular the SncRK-like TCS and TCS-9 as they may represent new regulatory systems than can be involved in S. mutans pathogenesis. SIGNIFICANCE AND IMPACT OF THE STUDY: Multiple TCS govern important biological parameters of S. mutans enabling its survival and persistence in the biofilm community.
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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) | 0.001 | 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 | 0.001 |
| 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".