Phosphoglycerate Kinase—A Novel Streptococcal Factor Involved in Neutrophil Activation and Degranulation
Bibliographic record
Abstract
BACKGROUND: Neutrophils have been proposed as important contributors to the hyperinflammatory responses that are associated with severe invasive Streptococcus pyogenes infections. In particular, streptococcal surface proteins have been implicated as potent neutrophil activators. Here we explore the impact of streptococcus-secreted factors on neutrophil activation and degranulation. METHODS: Primary human neutrophils were exposed to supernatants prepared from cultures of invasive S. pyogenes strains of varying serotypes in the stationary growth phase. Neutrophil activation was assessed by measurement of secreted resistin, an azurophilic granule marker, and by determination of the secretome profile, using mass spectrometry. RESULTS: Marked variation in resistin release and the neutrophil secretome profile were observed following exposure to different strains. A high resistin response was triggered exclusively by SpeB-negative strains, suggesting that at least 1 stimulatory factor is susceptible to SpeB proteolytic degradation. Further analysis, including proteomics and stimulation analyses, identified phosphoglycerate kinase as a stimulatory factor for neutrophils. CONCLUSIONS: Taken together, results of this study reveal a novel secreted streptococcal factor that, in the absence of SpeB, can trigger neutrophil activation and degranulation. This finding is of interest in light of reports of hypervirulent SpeB-negative S. pyogenes variants present during invasive infections.
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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".