Biochemical characterization and comparison of aspartylglucosaminidases secreted in venom of the parasitoid wasps Asobara tabida and Leptopilina heterotoma
Bibliographic record
Abstract
Aspartylglucosaminidase (AGA) is a low-abundance intracellular enzyme that plays a key role in the last stage of glycoproteins degradation, and whose deficiency leads to human aspartylglucosaminuria, a lysosomal storage disease. Surprisingly, high amounts of AGA-like proteins are secreted in the venom of two phylogenetically distant hymenopteran parasitoid wasp species, Asobara tabida (Braconidae) and Leptopilina heterotoma (Cynipidae). These venom AGAs have a similar domain organization as mammalian AGAs. They share with them key residues for autocatalysis and activity, and the mature α- and β-subunits also form an (αβ)2 structure in solution. Interestingly, only one of these AGAs subunits (α for AtAGA and β for LhAGA) is glycosylated instead of the two subunits for lysosomal human AGA (hAGA), and these glycosylations are partially resistant to PGNase F treatment. The two venom AGAs are secreted as fully activated enzymes, they have a similar aspartylglucosaminidase activity and are both also efficient asparaginases. Once AGAs are injected into the larvae of the Drosophila melanogaster host, the asparaginase activity may play a role in modulating their physiology. Altogether, our data provide new elements for a better understanding of the secretion and the role of venom AGAs as virulence factors in the parasitoid wasps' success.
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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) | 0.000 | 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 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".