Cockroach allergen serine proteinases: Isolation, sequencing and signalling via proteinase‐activated receptor‐2
Bibliographic record
Abstract
Summary Background Allergy to the German cockroach (Blattella germanica) is a significant asthma risk factor for inner‐city communities. Cockroach, like other allergens, contains trypsin‐like enzyme activity that contributes to allergenicity and airway inflammation by activating proteinase‐activated receptors (PARs). To date, the enzymes responsible for the proteolytic activity of German cockroach allergen have not been characterized. Objectives We aimed to identify, isolate and characterize the trypsin‐like proteinases in German cockroach allergen extracts used for clinical skin tests. For each enzyme, we sought to determine (1) its substrate and inhibitor enzyme kinetics (Km and IC50), (2) its amino acid sequence and (3) its ability to activate calcium signalling and/or ERK1/2 phosphorylation via PAR2. Methods Using a trypsin‐specific activity‐based probe, we detected three distinct enzymes that were isolated using ion‐exchange chromatography. Each enzyme was sequenced by mass spectometery (deconvoluted with an expressed sequence tag library), evaluated kinetically for its substrate/inhibitor profile and assessed for its ability to activate PAR2 signalling. Findings Each of the three serine proteinase activity‐based probe‐labelled enzymes isolated was biochemically distinct, with different enzyme kinetic profiles and primary amino acid sequences. The three enzymes showed a 57%‐71% sequence identity with a proteinase previously cloned from the American cockroach (Per a 10). Each enzyme was found to activate both Ca++ and MAPK signalling via PAR2. Conclusions and Relevance We have identified three different serine proteinases from the German cockroach that may, via PAR2 activation, play different roles for allergen sensitization in vivo and may represent attractive therapeutic targets for asthma.
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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 | 0.001 |
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".