Engineering a dysbiotic biofilm model for testing root caries interventions through microbial modulation
Bibliographic record
Abstract
Abstract Background This study aimed to engineer and optimise a dysbiotic biofilm model to develop in vitro root caries for investigating microbial modulation strategies. The model involved growing complex biofilms from a saliva inoculum collected from four volunteers using two strategies. In the first strategy (“pre-treatment strategy”), bovine root slabs were used, and two natural compounds were incorporated at time 0 of the 10-day biofilm experiment, which included sucrose cycles mimicking the cariogenic environment. In the second strategy (“post-treatment strategy”), mature biofilms were grown in a modified Calgary biofilm device coated with collagen and hydroxyapatite for 7 days and then were exposed to the same natural compounds. The metatranscriptome of each biofilm was then determined and analysed. Collagenase activity was examined, and the biofilms and dentine were imaged using confocal and scanning electron microscopy (SEM). Mineral loss and lesion formation were confirmed through micro-computed tomography (μ-CT). Results The pH confirmed the cariogenic condition. In the metatranscriptome, we achieved a biofilm compositional complexity, showing a great diversity of the metabolically active microbiome in both pre- and post-treatment strategies, including reads mapped to microorganisms other than bacteria, such as archaea and viruses. Carbohydrate esterases had increased expression in the post-treated biofilms and in samples without sugar cycles, while glucosyltransferases were highly expressed in the presence of sucrose cycles. Enrichment for functions related to nitrogen compound metabolism and organic cyclic component metabolism in groups without sucrose compared to the sucrose-treated group. Pre-treatment of the roots with cranberry reduced microbial viability and gelatinase (but not collagenase) activity (p < 0.05). SEM images showed the complexity of biofilms was maintained, with a thick extracellular polysaccharides layer. Conclusions This root caries model was optimized to produce complex cariogenic biofilms and root caries-like lesions, and could be used to test microbial modulation in vitro. Pre-treatments before biofilm development and cariogenic challenges were more effective than post-treatments. The clinical significance lies in the potential to apply the findings to develop varnish products for post-professional tooth prophylaxis, aiming at implementing a strategy for dysbiosis reversal in translational research. Video Abstract
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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 | 0.000 | 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) | 0.095 | 0.002 |
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".