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Record W2914626251 · doi:10.1039/c8cs00880a

Duplexed aptamers: history, design, theory, and application to biosensing

2019· review· en· W2914626251 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Society Reviews · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcGill UniversityMcGill University and Génome Québec Innovation Centre
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsAptamerBiosensorOligonucleotideNanotechnologyComputer scienceBiochemical engineeringEngineeringChemistryBiologyMaterials scienceMolecular biology

Abstract

fetched live from OpenAlex

Nucleic acid aptamers are single stranded DNA or RNA sequences that specifically bind a cognate ligand. In addition to their widespread use as stand-alone affinity binding reagents in analytical chemistry, aptamers have been engineered into a variety of ligand-specific biosensors, termed aptasensors. One of the most common aptasensor formats is the duplexed aptamer (DA). As defined herein, DAs are aptasensors containing two nucleic acid elements coupled via Watson-Crick base pairing: (i) an aptamer sequence, which serves as a ligand-specific receptor, and (ii) an aptamer-complementary element (ACE), such as a short DNA oligonucleotide, which is designed to hybridize to the aptamer. The ACE competes with ligand binding, such that DAs generate a signal upon ligand-dependent ACE-aptamer dehybridization. DAs possess intrinsic advantages over other aptasensor designs. For example, DA biosensing designs generalize across DNA and RNA aptamers, DAs are compatible with many readout methods, and DAs are inherently tunable on the basis of nucleic acid hybridization. However, despite their utility and popularity, DAs have not been well defined in the literature, leading to confusion over the differences between DAs and other aptasensor formats. In this review, we introduce a framework for DAs based on ACEs, and use this framework to distinguish DAs from other aptasensor formats and to categorize cis- and trans-DA designs. We then explore the ligand binding dynamics and chemical properties that underpin DA systems, which fall under conformational selection and induced fit models, and which mirror classical SN1 and SN2 models of nucleophilic substitution reactions. We further review a variety of in vitro and in vivo applications of DAs in the chemical and biological sciences, including riboswitches and riboregulators. Finally, we present future directions of DAs as ligand-responsive nucleic acids. Owing to their tractability, versatility and ease of engineering, DA biosensors bear a great potential for the development of new applications and technologies in fields ranging from analytical chemistry and mechanistic modeling to medicine and synthetic biology.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.052
GPT teacher head0.341
Teacher spread0.290 · 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