The <i>Streptococcus mutans vicX</i> Gene Product Modulates <i>gtfB</i> / <i>C</i> Expression, Biofilm Formation, Genetic Competence, and Oxidative Stress Tolerance
Bibliographic record
Abstract
Streptococcus mutans is considered one of the primary etiologic agents of dental caries. Previously, we characterized the VicRK two-component signal transduction system, which regulates multiple virulence factors of S. mutans. In this study, we focused on the vicX gene of the vicRKX tricistronic operon. To characterize vicX, we constructed a nonpolar deletion mutation in the vicX coding region in S. mutans UA159. The growth kinetics of the mutant (designated SmuvicX) showed that the doubling time was longer and that there was considerable sensitivity to paraquat-induced oxidative stress. Supplementing a culture of the wild-type UA159 strain with paraquat significantly increased the expression of vicX (P < 0.05, as determined by analysis of variance [ANOVA]), confirming the role of this gene in oxidative stress tolerance in S. mutans. Examination of mutant biofilms revealed architecturally altered cell clusters that were seemingly denser than the wild-type cell clusters. Interestingly, vicX-deficient cells grown in a glucose-supplemented medium exhibited significantly increased glucosyltransferase B/C (gtfB/C) expression compared with the expression in the wild type (P < 0.05, as determined by ANOVA). Moreover, a sucrose-dependent adhesion assay performed using an S. mutans GS5-derived vicX null mutant demonstrated that the adhesiveness of this mutant was enhanced compared with that of the parent strain and isogenic mutants of the parent strain lacking gtfB and/or gtfC. Also, disruption of vicX reduced the genetic transformability of the mutant approximately 10-fold compared with that of the parent strain (P < 0.05, as determined by ANOVA). Collectively, these findings provide insight into important phenotypes controlled by the vicX gene product that can impact S. mutans pathogenicity.
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 | 0.000 | 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 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".