Vaginal community state types (CSTs) alter environmental cues and production of the <i>Staphylococcus aureus</i> toxic shock syndrome toxin-1 (TSST-1)
Bibliographic record
Abstract
ABSTRACT Menstrual toxic shock syndrome (mTSS) is a rare but life-threatening disease associated with the use of high-absorbency tampons. The production of the Staphylococcus aureus toxic shock syndrome toxin-1 (TSST-1) superantigen is involved in nearly all cases of mTSS and is tightly controlled by regulators responding to the environment. In the prototypic mTSS strain S. aureus MN8, the major repressor of TSST-1 is the carbon catabolite protein A (CcpA), which responds to glucose concentrations in the vaginal tract. Healthy vaginal Lactobacillus species also depend on glucose for both growth and acidification of the vaginal environment through lactic acid production. We hypothesized that interactions between the vaginal microbiota [herein referred to as community state types (CSTs)] and S. aureus MN8 depend on environmental cues and that these interactions subsequently affect TSST-1 production. Using S. aureus MN8 Δ ccpA growing in various glucose concentrations, we demonstrate that the supernatants from different CSTs grown in vaginally defined medium (VDM) could significantly decrease tst expression. When co-culturing CST species with MN8 ∆ ccpA , we show that Lactobacillus jensenii completely inhibits TSST-1 production in conditions mimicking healthy menstruation or mTSS. Finally, we show that growing S. aureus in “unhealthy” or “transitional” CST supernatants results in higher interleukin 2 (IL-2) production from T cells. These findings suggest that dysbiotic CSTs may encourage TSST-1 production in the vaginal tract and further indicate that the CSTs are likely important for the protection from mTSS. IMPORTANCE In this study, we investigate the impact of the vaginal microbiota against Staphylococcus aureus in conditions mimicking the vaginal environment at various stages of the menstrual cycle. We demonstrate that Lactobacillus jensenii can inhibit toxic shock syndrome toxin-1 (TSST-1) production, suggesting the potential for probiotic activity in treating and preventing menstrual toxic shock syndrome (mTSS). On the other side of the spectrum, “unhealthy” or “transient” bacteria such as Gardnerella vaginalis and Lactobacillus iners support more TSST-1 production by S. aureus , suggesting that community state types are important in the development of mTSS. This study sets forward a model for examining contact-independent interactions between pathogenic bacteria and the vaginal microbiota. It also demonstrates the necessity of replicating the environment when studying one as dynamic as the vagina.
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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".