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Characterizing the Use of the RNA Mango Aptamer for RNA Pull‐Downs and Single Molecule Fluorescence

2017· article· en· W2944825724 on OpenAlexaff
Hannah M Poe, Clarisse van der Feltz, Xin Chen, Peter J. Unrau, Aaron A. Hoskins

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAptamerRNAFörster resonance energy transferRiboswitchBiophysicsChemistryFluorescenceNucleic acid structureFolding (DSP implementation)Single-molecule FRETBiochemistryComputational biologyBiologyNon-coding RNAMolecular biologyGene

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.043
GPT teacher head0.250
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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