Construction of a hybrid β-hexosaminidase subunit capable of forming stable homodimers that hydrolyze GM2 ganglioside in vivo
Bibliographic record
Abstract
Tay-Sachs or Sandhoff disease result from mutations in either the evolutionarily related HEXA or HEXB genes encoding respectively, the α- or β-subunits of β-hexosaminidase A (HexA). Of the three Hex isozymes, only HexA can interact with its cofactor, the GM2 activator protein (GM2AP), and hydrolyze GM2 ganglioside. A major impediment to establishing gene or enzyme replacement therapy based on HexA is the need to synthesize both subunits. Thus, we combined the critical features of both α- and β-subunits into a single hybrid µ-subunit that contains the α-subunit active site, the stable β-subunit interface and unique areas in each subunit needed to interact with GM2AP. To facilitate intracellular analysis and the purification of the µ-homodimer (HexM), CRISPR-based genome editing was used to disrupt the HEXA and HEXB genes in a Human Embryonic Kidney 293 cell line stably expressing the µ-subunit. In association with GM2AP, HexM was shown to hydrolyze a fluorescent GM2 ganglioside derivative both in cellulo and in vitro. Gene transfer studies in both Tay-Sachs and Sandhoff mouse models demonstrated that HexM expression reduced brain GM2 ganglioside levels.
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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 | 0.001 |
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".