Increased phosphorylation of HexM improves lysosomal uptake and potential for managing GM2 gangliosidoses
Bibliographic record
Abstract
Tay-Sachs and Sandhoff diseases are genetic disorders resulting from mutations in HEXA or HEXB, which code for the α- and β-subunits of the heterodimer β-hexosaminidase A (HexA), respectively. Loss of HexA activity results in the accumulation of GM2 ganglioside (GM2) in neuronal lysosomes, culminating in neurodegeneration and death, often by age 4. Previously, we combined critical features of the α- and β-subunits of HexA into a single subunit to create a homodimeric enzyme known as HexM. HexM is twice as active as HexA and degrades GM2 in vivo, making it a candidate for enzyme replacement therapy (ERT). Here we show HexM production is scalable to meet ERT requirements and we describe an approach that enhances its cellular uptake via co-expression with an engineered GlcNAc-1-phosphotransferase that highly phosphorylates lysosomal proteins. Further, we developed a HexA overexpression system and functionally compared the recombinant enzyme to HexM, revealing the kinetic differences between the enzymes. This study further advances HexM as an ERT candidate and provides a convenient system to produce HexA for comparative studies.
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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 | 0.000 |
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".