Protease-activated receptor-2 signaling through β-arrestin-2 mediates <i>Alternaria</i> alkaline serine protease-induced airway inflammation
Bibliographic record
Abstract
Alternaria alternata is a fungal allergen associated with severe asthma and asthma exacerbations. Similarly to other asthma-associated allergens, Alternaria secretes a serine-like trypsin protease(s) that is thought to act through the G protein-coupled receptor protease-activated receptor-2 (PAR 2 ) to induce asthma symptoms. However, specific mechanisms underlying Alternaria-induced PAR 2 activation and signaling remain ill-defined. We sought to determine whether Alternaria-induced PAR 2 signaling contributed to asthma symptoms via a PAR 2 /β-arrestin signaling axis, identify the protease activity responsible for PAR 2 signaling, and determine whether protease activity was sufficient for Alternaria-induced asthma symptoms in animal models. We initially used in vitro models to demonstrate Alternaria-induced PAR 2 /β-arrestin-2 signaling. Alternaria filtrates were then used to sensitize and challenge wild-type, PAR 2 −/− and β-arrestin-2 −/− mice in vivo. Intranasal administration of Alternaria filtrate resulted in a protease-dependent increase of airway inflammation and mucin production in wild-type but not PAR 2 −/− or β-arrestin-2 −/− mice. Protease was isolated from Alternaria preparations, and select in vitro and in vivo experiments were repeated to evaluate sufficiency of the isolated Alternaria protease to induce asthma phenotype. Administration of a single isolated serine protease from Alternaria, Alternaria alkaline serine protease (AASP), was sufficient to fully activate PAR 2 signaling and induce β-arrestin-2 −/− -dependent eosinophil and lymphocyte recruitment in vivo. In conclusion, Alternaria filtrates induce airway inflammation and mucus hyperplasia largely via AASP using the PAR 2 /β-arrestin signaling axis. Thus, β-arrestin-biased PAR 2 antagonists represent novel therapeutic targets for treating aeroallergen-induced asthma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".