Dietary Carbohydrates Modulate Streptococcus mutans Adherence and Bacterial Proteome
Bibliographic record
Abstract
INTRODUCTION: Streptococcus mutans adherence to the tooth surface and subsequent biofilm development is modulated by the carbohydrate source, but the corresponding effect on bacterial proteome has not been previously studied. This study aimed to assess the effect of different carbohydrates on S. mutans viability and bacterial proteome at 2 time points, early attachment (8 h) and biofilm maturation (24 h). METHODS: Hydroxyapatite (HAp) discs coated with parotid saliva proteins were inoculated with S. mutans UA159 in tryptone soy broth without dextrose supplemented with one of the following carbohydrates (n = 12/treatment/time point): 1% sucrose; 0.525% glucose + 0.525% fructose; 10% xylitol; 10% xylitol + 1% sucrose; or culture medium without supplementation as negative control. Once inoculated, HAp discs were incubated for 8 h or 24 h at 37°C and 10% CO2. After each incubation period, adhered bacteria were quantified using the plate-counting method for 6 HAp discs/group, and the remaining 6 HAp discs/group were used to extract bacterial cell wall proteins. Extracted proteins were analyzed using liquid chromatography coupled with mass spectrometry and then classified by their biological process. The study was conducted in three independent assays, and the number of bacteria adhered to the HAp discs was determined at each time point and analyzed by two-way ANOVA followed by Bonferroni test (α = 5%). RESULTS: The results suggest that xylitol significantly repressed bacterial adherence and metabolism at 8 h and 24 h; however, bacterial adherence and metabolism were significantly enhanced when xylitol was combined with sucrose, showing no negative effect on S. mutans at both time points. Bacterial proteome was modulated by the carbohydrate source. CONCLUSION: The cariogenicity of S. mutans biofilms may be reduced by the alternative sweetener xylitol; however, the combination with fermentable sugars may inhibit such a beneficial effect.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".