Pneumolysin suppresses the initial macrophage pro‐inflammatory response to <i>Streptococcus pneumoniae</i>
Bibliographic record
Abstract
Published data for the Streptococcus pneumoniae virulence factor Pneumolysin (Ply) show contradictory effects on the host inflammatory response to infection. Ply has been shown to activate the inflammasome, but also can bind to MRC-1 resulting in suppression of dendritic cell inflammatory responses. We have used an in vitro infection model of human monocyte-derived macrophages (MDM), and a mouse model of pneumonia to clarify whether pro- or anti-inflammatory effects dominate the effects of Ply on the initial macrophage inflammatory response to S. pneumoniae, and the consequences during early lung infection. We found that infection with S. pneumoniae expressing Ply suppressed tumour necrosis factor (TNF) and interleukin-6 production by MDMs compared to cells infected with ply-deficient S. pneumoniae. This effect was independent of bacterial effects on cell death. Transcriptional analysis demonstrated S. pneumoniae expressing Ply caused a qualitatively similar but quantitatively lower MDM transcriptional response to S. pneumoniae compared to ply-deficient S. pneumoniae, with reduced expression of TNF and type I IFN inducible genes. Reduction of the MDM inflammatory response was prevented by inhibition of SOCS1. In the early lung infection mouse model, the TNF response to ply-deficient S. pneumoniae was enhanced and bacterial clearance increased compared to infection with wild-type S. pneumoniae. Overall, these data show Ply inhibits the initial macrophage inflammatory response to S. pneumoniae, probably mediated through SOCS1, and this was associated with improved immune evasion during early lung infection.
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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".