Fluorescence-Quenched Substrates for Live Cell Imaging of Human Glucocerebrosidase Activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Deficiency of the lysosomal glycoside hydrolase glucocerebrosidase (GCase) leads to abnormal accumulation of glucosyl ceramide in lysosomes and the development of the lysosomal storage disease known as Gaucher's disease. More recently, mutations in the GBA1 gene that encodes GCase have been uncovered as a major genetic risk factor for Parkinson's disease (PD). Current therapeutic strategies to increase GCase activity in lysosomes involve enzyme replacement therapy (ERT) and molecular chaperone therapy. One challenge associated with developing and optimizing these therapies is the difficulty in determining levels of GCase activity present within the lysosomes of live cells. Indeed, visualizing the activity of endogenous levels of any glycoside hydrolases, including GCase, has proven problematic within live mammalian cells. Here we describe the successful modular design and synthesis of fluorescence-quenched substrates for GCase. The selection of a suitable fluorophore and quencher pair permits the generation of substrates that allow convenient time-dependent monitoring of endogenous GCase activity within cells as well as localization of activity within lysosomes. These efficiently quenched (∼99.9%) fluorescent substrates also permit assessment of GCase inhibition in live cells by either confocal microscopy or high content imaging. Such substrates should enable improved understanding of GCase in situ as well the optimization of small-molecule chaperones for this enzyme. These findings also suggest routes to generate fluorescence-quenched substrates for other mammalian glycoside hydrolases for use in live cell imaging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| 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 it