A straightforward approach for bioorthogonal labeling of proteins and organelles in live mammalian cells, using a short peptide tag
Bibliographic record
Abstract
Abstract In the high-resolution microscopy era, genetic code expansion (GCE)-based bioorthogonal labeling offers an elegant way for direct labeling of proteins in live cells with fluorescent dyes. This labeling approach is currently not broadly used live cell applications, partly because it needs to be adjusted to the specific protein under study. Here, we present a generic, 14-residues long, N-terminal tag for GCE-based labeling of proteins in live mammalian cells. Using this tag, we generated a library of GCE-based organelle markers, demonstrating the applicability of the tag for labeling a plethora of proteins and organelles. Finally, we show that the HA epitope, used as a backbone in our tag, can be substituted with other epitopes and, in some cases, can be completely removed, reducing the tag length to 5 residues. The GCE-tag presented here offers a powerful, easy-to-implement tool for live cell labeling of cellular proteins with small and bright probes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".