Protein‐protein interactions monitored in cells from transgenic mice using bioluminescence resonance energy transfer
Bibliographic record
Abstract
Monitoring the dynamics of protein-protein interactions in their natural environment remains a challenge. Resonance energy transfer approaches represent a promising avenue to directly probe these interactions in real time. The present study aims at establishing a proof of principle that bioluminescence resonance energy transfer (BRET) can be used to study the regulation of protein-protein interaction in cells from transgenic animals. A transgenic mouse line coexpressing the beta(2)-adrenergic receptor fused to Renilla luciferase (beta(2)AR-Rluc) and beta arrestin-2 fused to a green fluorescent protein (GFP2-beta arr2) was generated. The fusion proteins were found to be functional in the transgenic animals and the beta(2)AR-Rluc maintained pharmacological properties, comparable to that of the native receptor. Sufficiently high luminescence signal was generated to allow detection of BRET in testis cells where the beta(2)AR-Rluc transgene was expressed at levels significantly higher than that of the endogenous receptor in this tissue but remain within physiological range when compared with other beta(2)AR-expressing tissues. Stimulation with a beta-adrenergic agonist led to a significant dose- and time-dependent increase in BRET, which reflected ligand-promoted recruitment of beta arr2 to the receptor. Our study demonstrates that BRET can be used to monitor the dynamic regulation of protein-protein interactions in cells derived from transgenic mice.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".