Visualization of Protein‐Specific Glycosylation inside Living Cells
Bibliographic record
Abstract
Protein glycosylation is a ubiquitous post-translational modification that is involved in the regulation of many aspects of protein function. In order to uncover the biological roles of this modification, imaging the glycosylation state of specific proteins within living cells would be of fundamental importance. To date, however, this has not been achieved. Herein, we demonstrate protein-specific detection of the glycosylation of the intracellular proteins OGT, Foxo1, p53, and Akt1 in living cells. Our generally applicable approach relies on Diels-Alder chemistry to fluorescently label intracellular carbohydrates through metabolic engineering. The target proteins are tagged with enhanced green fluorescent protein (EGFP). Förster resonance energy transfer (FRET) between the EGFP and the glycan-anchored fluorophore is detected with high contrast even in presence of a large excess of acceptor fluorophores by fluorescence lifetime imaging microscopy (FLIM).
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".