<i>Lactobacillus reuteri</i> -produced cyclic dipeptides quench <i>agr</i> -mediated expression of toxic shock syndrome toxin-1 in staphylococci
Bibliographic record
Abstract
The production of the staphylococcal exotoxin toxic shock syndrome toxin-1 (TSST-1) by Staphylococcus aureus has been associated with essentially all cases of menstruation-associated toxic shock syndrome (TSS). In this work, we show that the human vaginal isolate Lactobacillus reuteri RC-14 produces small signaling molecules that are able to interfere with the staphylococcal quorum-sensing system agr, a key regulator of virulence genes, and repress the expression of TSST-1 in S. aureus MN8, a prototype of menstrual TSS S. aureus strains. Quantitative real-time PCR data showed that transcription from the Ptst promoter, as well as the P2 and P3 promoters of the agr system from all four agr subgroups of S. aureus, was strongly inhibited in response to growth with L. reuteri RC-14 cultural supernatant. Alterations in the transcriptional levels of two other virulence-associated regulators sarA and saeRS were also observed, indicating a potential overall influence of L. reuteri RC-14 signals on the production of virulence factors in S. aureus. S. aureus promoter-lux reporter strains were used to screen biochemically fractionated L. reuteri RC-14 supernatant, and the cyclic dipeptides cyclo(L-Phe-L-Pro) and cyclo(L-Tyr-L-Pro) were identified as the signaling molecules. The results from this work contribute to a better understanding of interspecies cell-to-cell communication between Lactobacillus and Staphylococcus, and provide a unique mechanism by which endogenous or probiotic strains may attenuate virulence factor production by bacterial pathogens.
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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".