Trigger Factor in<i>Streptococcus mutans</i>Is Involved in Stress Tolerance, Competence Development, and Biofilm Formation
Bibliographic record
Abstract
Trigger factor is a ribosome-associated peptidyl-prolyl cis/trans isomerase that is highly conserved in most bacteria. A gene, designated ropA, encoding an apparent trigger factor homologue, was identified in Streptococcus mutans, the primary etiological agent of human dental caries. Inactivation of ropA had no major impact on growth rate in planktonic cultures under the conditions tested, although the RopA-deficient mutant formed long chains in broth. Deficiency of RopA decreased tolerance to acid killing and to oxidative stresses induced by hydrogen peroxide and paraquat, and it reduced transformation efficiency about 200-fold. Addition of synthetic competence-stimulating peptide to the culture medium enhanced transformability of both the mutant and wild-type strains, although the ropA strain did not attain levels of competence observed for the parent. Loss of RopA decreased the capacity of S. mutans to form biofilms by over 80% when cultivated in glucose, but it increased biofilm formation by over 50% when sucrose was provided as the carbohydrate source. Western blot analysis revealed that the expression of glucosyltransferases B and D was lower in the RopA-deficient mutant. These results suggest that RopA is a key regulator of acid and oxidative stress tolerance, genetic competence, and biofilm formation, all critical virulence properties of S. mutans.
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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 | 0.000 |
| 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".