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Record W4391683596 · doi:10.1128/jb.00447-23

Vaginal community state types (CSTs) alter environmental cues and production of the <i>Staphylococcus aureus</i> toxic shock syndrome toxin-1 (TSST-1)

2024· article· en· W4391683596 on OpenAlexafffund
Carla S. Maduta, John K. McCormick, Karine Dufresne

Bibliographic record

VenueJournal of Bacteriology · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsBiologyStaphylococcus aureusToxic shock syndromeToxinMicrobiologyShock (circulatory)BacteriaGeneticsInternal medicineMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2024
Admission routes2
Has abstractyes

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