The LiaFSR System Regulates the Cell Envelope Stress Response in<i>Streptococcus mutans</i>
Bibliographic record
Abstract
Maintaining cell envelope integrity is critical for bacterial survival, including bacteria living in a complex and dynamic environment such as the human oral cavity. Streptococcus mutans, a major etiological agent of dental caries, uses two-component signal transduction systems (TCSTSs) to monitor and respond to various environmental stimuli. Previous studies have shown that the LiaSR TCSTS in S. mutans regulates virulence traits such as acid tolerance and biofilm formation. Although not examined in streptococci, homologs of LiaSR are widely disseminated in Firmicutes and function as part of the cell envelope stress response network. We describe here liaSR and its upstream liaF gene in the cell envelope stress tolerance of S. mutans strain UA159. Transcriptional analysis established liaSR as part of the pentacistronic liaFSR-ppiB-pnpB operon. A survey of cell envelope antimicrobials revealed that mutants deficient in one or all of the liaFSR genes were susceptible to Lipid II cycle interfering antibiotics and to chemicals that perturbed the cell membrane integrity. These compounds induced liaR transcription in a concentration-dependent manner. Notably, under bacitracin stress conditions, the LiaFSR signaling system was shown to induce transcription of several genes involved in membrane protein synthesis, peptidoglycan biosynthesis, envelope chaperone/proteases, and transcriptional regulators. In the absence of an inducer such as bacitracin, LiaF repressed LiaR-regulated expression, whereas supplementing cultures with bacitracin resulted in derepression of liaSR. While LiaF appears to be an integral component of the LiaSR signaling cascade, taken collectively, we report a novel role for LiaFSR in sensing cell envelope stress and preserving envelope integrity in 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) | 0.000 | 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".