A proto-aldehyde fluorescence quenched substrate for quantitative imaging of both protein and enzyme activity within cells
Bibliographic record
Abstract
Fluorogenic substrates are emerging tools that enable studying enzymatic processes within their native cellular environments. However, fluorogenic substrates that function within live cells are generally incompatible with cellular fixation, preventing their tandem application with fundamental cell biology methods such as immunocytochemistry. Here we report a simple approach to enable the stable chemical fixation of the fluorescent product of a series of dark-to-light bis-acetal based substrates (BABS). Cleavage of the BABS glycosidic bond leads to liberation of a hemiacetal in which one branch consists of a proto-aldehyde bearing the fluorophore and the other branch consists of an alcohol bearing the quencher. Spontaneous breakdown of this hemiacetal leads to formation of a fluorescent aldehyde. Trapping of this aldehyde by standard reductive amination to intracellular proteins allows its stable retention within cells and concomitant imaging of cellular proteins by traditional immunocytochemistry. These bis-acetal substrates enable measuring changes in lysosomal GCase activity in response to both chemical and genetic perturbations. These tools will aid in studying the role of GCase activity in diseases and accelerate the creation of new therapeutic approaches targeting the GCase pathway. We also expect this strategy to be broadly useful for creating fixable substrates for other lysosomal enzymes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".