Characterization of a Streptococcus mutans Intergenic Region Containing a Small Toxic Peptide and Its cis-Encoded Antisense Small RNA Antitoxin
Bibliographic record
Abstract
Toxin-antitoxin (TA) modules consist of a pair of genes that encode two components: a protein toxin and an antitoxin, which may be in the form of either a labile protein or an antisense small RNA. Here we describe, to the best of our knowledge, the first functional chromosomal type I TA system in streptococci. Our model organism is the oral pathogen Streptococcus mutans. Our results showed that the genome of S. mutans UA159 reference strain harbors a previously unannotated Fst-like toxin (Fst-Sm) and its cis-encoded small RNA antitoxin (srSm) converging towards the end of the toxin gene in IGR176, a small intergenic region of 318 nt. Fst-Sm is a small hydrophobic peptide of 32 amino acid residues with homology to the Fst toxin family. Transcripts of ∼200 nt and ∼70 nt specific to fst-Sm mRNA and srSm RNA, respectively, were detected by Northern blot analysis throughout S. mutans growth. The toxin mRNA was considerably more stable than its cognate antitoxin. The half-life of srSm RNA was determined to be ∼30 min, while fst-Sm mRNA had a half-life of ∼90 min. Both fst-Sm and srSm RNAs were transcribed across direct tandem repeats providing a region of complementarity for inhibition of toxin translation. Overproduction of Fst-Sm had a toxic effect on E. coli and S. mutans cells which can be neutralized by coexpression of srSm RNA. Deletion of fst-Sm/srSm locus or overexpression of Fst-Sm/srSm had no effect on S. mutans cell growth in liquid medium and no differences in the total biofilm biomass were noted. In contrast, mild-overproduction of Fst-Sm/srSm type I TA system decreases the levels of persister cells tolerant to bacterial cell wall synthesis inhibitors.
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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) | 0.000 | 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".