Bitter Taste Receptor T2R14 and Autophagy Flux in Gingival Epithelial Cells
Bibliographic record
Abstract
Macroautophagy (hereafter autophagy) is a lysosomal degradation pathway that functions in nutrient recycling and as a mechanism of innate immunity. Previously, we reported a novel host–bacteria interaction between cariogenic S. mutans and bitter taste receptor (T2R14) in gingival epithelial cells (GECs), leading to an innate immune response. Further, S. mutans might be using the host immune system to inhibit other Gram-positive bacteria, such as S. aureus. To determine whether these bacteria exploit the autophagic machinery of GEC, it is first necessary to evaluate the role of T2R14 in modulating autophagic flux. So far, the role of T2R14 in the regulation of autophagy is not well characterized. Therefore, in this study, for the first time, we report that T2R14 downregulates autophagy flux in GECs, and T2R14 knockout increases acidic vacuoles. However, the treatments of GEC WT with a T2R14 agonist and antagonist did not lead to a significant change in acidic vacuole formation. Transmission electron microscopy morphometric results also suggested an increased number of autophagic vesicles in T2R14-knockout GEC. Further, our results suggest that S. mutans competence stimulating peptide CSP-1 showed robust intracellular calcium release and this effect is both T2R14- and autophagy protein 7-dependent. In this study, we provide the first evidence that T2R14 modulates autophagy flux in GEC. The results of the current study could help in identifying the impact of T2R in regulation of the immuno-microenvironment of GEC and subsequently oral health.
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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) | 0.002 | 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".