Reversible optogenetic control of kinase activity during differentiation and embryonic development
Bibliographic record
Abstract
A limited number of signaling pathways are repeatedly used to regulate a wide variety of processes during development and differentiation. The lack of tools to manipulate signaling pathways dynamically in space and time has been a major technical challenge for biologists. Optogenetic techniques, which utilize light to control protein functions in a reversible fashion, hold promise for modulating intracellular signaling networks with high spatial and temporal resolution. Applications of optogenetics in multicellular organisms, however, have not been widely reported. Here, we create an optimized bicistronic optogenetic system using Arabidopsis thaliana cryptochrome 2 (CRY2) protein and the N-terminal domain of cryptochrome-interacting basic-helix-loop-helix (CIBN). In a proof-of-principle study, we develop an optogenetic Raf kinase that allows reversible light-controlled activation of the Raf/MEK/ERK signaling cascade. In PC12 cells, this system significantly improves light-induced cell differentiation compared with co-transfection. When applied to Xenopus embryos, this system enables blue light-dependent reversible Raf activation at any desired developmental stage in specific cell lineages. Our system offers a powerful optogenetic tool suitable for manipulation of signaling pathways with high spatial and temporal resolution in a wide range of experimental settings.
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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) | 0.000 | 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 | 0.001 |
| 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 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".