Live cell imaging of single RNA molecules with fluorogenic Mango II arrays
Bibliographic record
Abstract
RNA molecules play vital roles in many cellular processes. Visualising their dynamics in live cells at single-molecule resolution is essential to elucidate their role in RNA metabolism. RNA aptamers, such as Spinach and Mango, have recently emerged as a powerful background-free technology for live-cell RNA imaging due to their fluorogenic properties upon ligand binding. Here, we report a novel array of Mango II aptamers for RNA imaging in live and fixed cells with high contrast and single-molecule sensitivity. Direct comparison of Mango II and MS2-tdMCP-mCherry dual-labelled mRNAs show marked improvements in signal to noise ratio using the fluorogenic Mango aptamers. Using both coding (β-actin mRNA) and long non-coding (NEAT1) RNAs, we show that the Mango array does not affect cellular localisation. Additionally, we can track single mRNAs for extended time periods, likely due to bleached fluorophore replacement. This property makes the arrays readily compatible with structured illumination super-resolution microscopy.
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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 | 0.000 |
| 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".