Natural Genetic Transformation of <i>Streptococcus mutans</i> Growing in Biofilms
Bibliographic record
Abstract
Streptococcus mutans is a bacterium that has evolved to be dependent upon a biofilm "lifestyle" for survival and persistence in its natural ecosystem, dental plaque. We initiated this study to identify the genes involved in the development of genetic competence in S. mutans and to assay the natural genetic transformability of biofilm-grown cells. Using genomic analyses, we identified a quorum-sensing peptide pheromone signaling system similar to those previously found in other streptococci. The genetic locus of this system comprises three genes, comC, comD, and comE, that encode a precursor to the peptide competence factor, a histidine kinase, and a response regulator, respectively. We deduced the sequence of comC and its active pheromone product and chemically synthesized the corresponding 21-amino-acid competence-stimulating peptide (CSP). Addition of CSP to noncompetent cells facilitated increased transformation frequencies, with typically 1% of the total cell population transformed. To further confirm the roles of these genes in genetic competence, we inactivated them by insertion-duplication mutagenesis or allelic replacement followed by assays of transformation efficiency. We also demonstrated that biofilm-grown S. mutans cells were transformed at a rate 10- to 600-fold higher than planktonic S. mutans cells. Donor DNA included a suicide plasmid, S. mutans chromosomal DNA harboring a heterologous erythromycin resistance gene, and a replicative plasmid. The cells were optimally transformed during the formation of 8- to 16-h-old biofilms primarily consisting of microcolonies on solid surfaces. We also found that dead cells in the biofilms could act as donors of a chromosomally encoded antibiotic resistance determinant. This work demonstrated that a peptide pheromone system controls genetic competence in S. mutans and that the system functions optimally when the cells are living in actively growing biofilms.
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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) | 0.000 | 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) | 0.001 | 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".