MétaCan
Menu
Back to cohort
Record W3134079052 · doi:10.1261/rna.078493.120

RNA Peach and Mango: orthogonal two-color fluorogenic aptamers distinguish nearly identical ligands

2021· article· en· W3134079052 on OpenAlexafffund
Kristen Y. S. Kong, Sunny C.Y. Jeng, Batool Rayyan, Peter J. Unrau

Bibliographic record

VenueRNA · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAptamerBiotinRNABiologySELEX Aptamer TechniqueFluorophoreBiotinylationSystematic evolution of ligands by exponential enrichmentBiochemistryOligonucleotideIn vitroBiophysicsFluorescenceComputational biologyGeneticsDNAGene

Abstract

fetched live from OpenAlex

Two-channel fluorogenic RNA aptamer-based imaging is currently challenging. While we have previously characterized the Mango series of aptamers that bind tightly and specifically to the green fluorophore TO1-Biotin, the next aim was to identify an effective fluorogenic aptamer partner for two-color imaging. A competitive in vitro selection for TO3-Biotin binding aptamers was performed resulting in the Peach I and II aptamers. Remarkably, given that the TO1-Biotin and TO3-Biotin heterocycles differ by only two bridging carbons, these new aptamers exhibit a marked preference for TO3-Biotin binding relative to the iM3 and Mango III A10U aptamers, which preferentially bind TO1-Biotin. Peach I, like Mango I and II, appears to contain a quadruplex core isolated by a GAA^A type tetraloop-like adaptor from its closing stem. Thermal melts of the Peach aptamers reveal that TO3-Biotin binding is cooperative, while TO1-Biotin binding is not, suggesting a unique and currently uncharacterized mode of ligand differentiation. Using only fluorescent measurements, the concentrations of Peach and Mango aptamers could be reliably determined in vitro. The utility of this orthogonal pair provides a possible route to in vivo two-color RNA imaging.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.008
GPT teacher head0.274
Teacher spread0.266 · 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 teacher head, 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

Citations25
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueRNASame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207