Characterizing the Use of the RNA Mango Aptamer for RNA Pull‐Downs and Single Molecule Fluorescence
Bibliographic record
Abstract
Methods for investigating the conformation and interactions of RNA and RNA/protein complexes are currently limited. This in turn has restricted our ability to understand the dynamics and interactions of small nuclear RNAs of the spliceosome. One way to address this challenge is by “tagging” the RNAs with an aptamer so that they can be readily purified and visualized. RNA Mango is an aptamer that has a high affinity (KD<10 nM) and specificity for derivatives of its fluorescent ligand, thiazole orange (TO1). Fluorescence of TO1 is enhanced 103‐fold when it is bound to the parallel‐stranded G‐quandruplex of RNA Mango, making the use of this ligand‐aptamer pair a promising strategy in RNA localization and purification experiments1. What makes this aptamer truly exciting is its ability to enable studies by a variety of biochemical techniques, including single molecule Förster Resonance Energy Transfer (smFRET) experiments and pull‐down assays. The goal of this work was to explore the versatility of RNA Mango incorporation into snRNAs through such experiments. For smFRET experiments, we labeled distinct positions of RNA Mango with Cy5 and Cy3 fluorophores, and determined that the aptamer has a folded FRET state of ~0.7 in monovalent ionic buffer solutions. Additional smFRET experiments suggest that the presence of TO1 derivatives in solution do not affect the folding of RNA Mango, whose properly folded G‐quadruplex is critical for the fluorescence of TO1. Thus, the RNA Mango aptamer itself is stable under a variety of conditions and TO1 binding may only introduce small conformational changes. We created a Saccharomyces cerevisiae strain with RNA Mango incorporated into the U4 snRNA, a component of the spliceosome, such that RNA Mango and TO1 derivatives can be used to isolate U4 and U4 containing splicing complexes. Primer extension assays comparing S. cerevisiae with wildtype and U4‐Mango showed that RNA Mango was successfully incorporated into the genome of our modified strain. We were able to purify snRNP complexes using U4 snRNA:RNA Mango and biotinylated TO1. This work demonstrates that RNA Mango can be integrated into the U4 snRNP to give further insights into the complexities of interactions in the spliceosome. Support or Funding Information Aaron Hoskins is a Beckman Young Investigator of the Arnold and Mable Beckman Foundation
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".