A modular system to label endogenous presynaptic proteins using split fluorophores in <i>C. elegans</i>
Bibliographic record
Abstract
Abstract Visualizing the subcellular localization of presynaptic proteins with fluorescent proteins is a powerful tool to dissect the genetic and molecular mechanisms underlying synapse formation and patterning in live animals. Here, we utilize split green and red fluorescent proteins to visualize the localization of endogenously expressed presynaptic proteins at a single neuron resolution in Caenorhabditis elegans. By using CRISPR/Cas9 genome editing, we generated a collection of C. elegans strains in which endogenously expressed presynaptic proteins (RAB-3/Rab3, CLA-1/Piccolo, SYD-2/Liprin-α, UNC-10/RIM and ELKS-1/ELKS) are tagged with tandem repeats of GFP 11 and/or wrmScarlet 11 . We show that the expression of wrmScarlet 1-10 and GFP 1-10 under neuron-specific promoters can robustly label presynaptic proteins in different neuron types. We believe that combinations of knock-in strains and wrmScarlet 1-10 and GFP 1-10 plasmids are a versatile modular system to examine the localization of endogenous presynaptic proteins in any neuron type.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".