Pertussis Toxin Inhibits Early Chemokine Production To Delay Neutrophil Recruitment in Response to<i>Bordetella pertussis</i>Respiratory Tract Infection in Mice
Bibliographic record
Abstract
Pertussis is an acute respiratory disease of humans caused by the bacterium Bordetella pertussis. Pertussis toxin (PT) plays a major role in the virulence of this pathogen, including important effects that it has soon after inoculation. Studies in our laboratory and other laboratories have indicated that PT inhibits early neutrophil influx to the lungs and airways in response to B. pertussis respiratory tract infection in mice. Previous in vitro and in vivo studies have shown that PT can affect neutrophils directly by ADP ribosylating G(i) proteins associated with surface chemokine receptors, thereby inhibiting neutrophil migration in response to chemokines. However, in this study, by comparing responses to wild-type (WT) and PT-deficient strains, we found that PT has an indirect inhibitory effect on neutrophil recruitment to the airways in response to infection. Analysis of lung chemokine expression indicated that PT suppresses early neutrophil recruitment by inhibiting chemokine upregulation in alveolar macrophages and other lung cells in response to B. pertussis infection. Enhancement of early neutrophil recruitment to the airways in response to WT infection by addition of exogenous keratinocyte-derived chemokine, one of the dominant neutrophil-attracting chemokines in mice, further revealed an indirect effect of PT on neutrophil chemotaxis. Additionally, we showed that intranasal administration of PT inhibits lipopolysaccharide-induced chemokine gene expression and neutrophil recruitment to the airways, presumably by modulation of signaling through Toll-like receptor 4. Collectively, these results demonstrate how PT inhibits early inflammatory responses in the respiratory tract, which reduces neutrophil influx in response to B. pertussis infection, potentially providing an advantage to the pathogen in this interaction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".