A Dual Reporter System for Detecting RNA Interactions in Bacterial Cells
Bibliographic record
Abstract
Detecting RNA-partner interactions in cells is often difficult due to a lack of suitable tools. Here we describe a dual reporter system capable of detecting intracellular interactions in which one of the partners is an RNA. The system utilizes two fluorescent proteins with similar maturation rates but distinct spectral properties, specifically cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP). By placing the CFP gene upstream and the YFP gene downstream of an RNA gene of interest, the production of YFP becomes sensitive to RNA-partner interaction, whereas the synthesis of CFP is not disturbed. Therefore, the RNA-partner interaction can be simply measured by the change in the ratio of fluorescence of YFP over CFP. The utility of our approach is demonstrated through verification of three known RNA-partner interactions in the model bacterium Escherichia coli. Our two-reporter strategy should be broadly useful to the study of RNA-targeted interactions in bacteria.
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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) | 0.000 | 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".