Superantigens promote <i>Staphylococcus aureus</i> bloodstream infection by eliciting pathogenic interferon-gamma (IFNγ) production that subverts macrophage function
Bibliographic record
Abstract
ABSTRACT Staphylococcus aureus is a foremost bacterial pathogen responsible for a vast array of human diseases. Staphylococcal superantigens (SAgs) constitute a family of potent exotoxins secreted by S. aureus , and SAg genes are found ubiquitously in human isolates. SAgs bind directly to MHC class II molecules and T cell receptors, driving extensive T cell activation and cytokine release. Although these toxins have been implicated in serious disease including toxic shock syndrome, we aimed to further elucidate the mechanisms by which SAgs contribute to staphylococcal pathogenesis during septic bloodstream infections. As most conventional mouse strains respond poorly to staphylococcal SAgs, we utilized transgenic mice encoding humanized MHC class II molecules (HLA-DR4) as these animals are much more susceptible to SAg activity. Herein, we demonstrate that SAgs contribute to the severity of S. aureus bacteremia by increasing bacterial burden, most notably in the liver. We established that S. aureus bloodstream infection severity is mediated by CD4+ T cells and interferon-gamma (IFNγ) is produced to very high levels during infection in a SAg-dependent manner. Bacterial burden and disease severity were reduced by antibody blocking of IFNγ, phenocopying isogenic SAg deletion mutant strains. Additionally, cytokine analysis demonstrated that the immune system was skewed towards a proinflammatory response that was reduced by IFNγ blocking. Infection kinetics and flow cytometry analyses suggested this was a macrophage driven mechanism, which was confirmed through macrophage depletion experiments. Further validation with human leukocytes indicated that excessive IFNγ allowed S. aureus to replicate at a higher rate within macrophages. Together, this suggests that SAgs promote S. aureus survival by manipulating immune responses that would otherwise be effective at clearing S. aureus . This work implicates SAg toxins as critical targets for preventing persistent or severe S. aureus disease.
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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 | 0.001 |
| 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".