MétaCan
Menu
Retour à la cohorte
Enregistrement W2746831066 · doi:10.1021/acs.accounts.7b00262

Discovery and Biosensing Applications of Diverse RNA-Cleaving DNAzymes

2017· article· en· W2746831066 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
fundUn bailleur canadien est enregistré sur le travail.

Notice bibliographique

RevueAccounts of Chemical Research · 2017
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueAdvanced biosensing and bioanalysis techniques
Établissements canadiensMcMaster University
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésDeoxyribozymeDNARNARibozymeCleaveChemistrySequence (biology)Computational biologyBiosensorCleavage (geology)BiochemistryCombinatorial chemistryNanotechnologyBiologyGeneMaterials science

Résumé

récupéré en direct d'OpenAlex

Conspectus DNA-based enzymes, or DNAzymes, are not known to exist in Nature but can be isolated from random-sequence DNA pools using test tube selection techniques. Since the report of the first DNAzyme in 1994, many catalytic DNA molecules for catalyzing wide-ranging chemical transformations have been isolated and studied. Our laboratory has a keen interest in searching for diverse DNAzymes capable of cleaving RNA-containing substrates, determining their sequence requirements and structural properties, and examining their potential as biosensors. This Account begins with the description of an accidental discovery on the sequence adaptability of a small DNAzyme known as “8-17”, when we performed 16 parallel selections to search for DNAzymes that targeted each and every possible dinucleotide junction of RNA for cleavage. DNAzyme 8-17 dominated all the selection pools targeting purine-containing junctions. In-depth sequence analysis revealed that 8-17 could manifest itself in many sequence options defined by the requirement of four absolutely conserved nucleotides. This study also exposed the fact that 8-17 had poor activity toward pyrimidine–pyrimidine junctions. With this information in hand, we proceeded to the discovery of diverse non-8-17 DNAzymes that exhibited robust catalytic activity under physiological conditions. These DNAzymes were found to universally interact with their substrates through two Watson–Crick binding arms and have a catalytic core of varying length and secondary-structure complexity. RNA-cleaving DNAzymes were also isolated to function at acidic conditions (pH 3–5), and these molecules exhibited intriguing pH profiles, with the highest activity precisely matching the pH used for their selection. Interestingly, these DNAzymes appear to use non-Watson–Crick interactions in defining their structures. More recently, we have embarked on the development of ligand-responsive RNA-cleaving fluorogenic DNAzymes that can recognize specific bacterial pathogens, such as Escherichia coli and Clostridium difficile, using a method that does not require a priori identification of a specific biomarker. Instead, the crude extracellular mixture as a whole is used as the target to drive the DNAzyme isolation. High recognition specificity can be achieved with a double-selection approach in which a DNA library is negatively selected against the cellular mixture prepared from unintended bacteria, followed by positive selection against the same mixture derived from a specific species or strain of bacterial pathogen. Finally, we have shown that DNAzymes’ compatibility with DNA replication can benefit the design of amplification mechanisms that uniquely link the action of RNA-cleaving DNAzymes to rolling circle amplification, an isothermal DNA amplification technique. These methods are well suited for translating the target-binding and cleavage activity of an analyte-activated RNA-cleaving DNAzyme into the production of massive amounts of DNA amplicons to achieve ultrahigh detection sensitivity. Given the high chemical stability of DNA, our ability to discover catalytic DNA sequences by simultaneously evaluating as many as 10 16 different DNA sequences, the accessibility to diverse RNA-cleaving DNAzymes in a single DNA pool, and the availability of methods for designing simple biosensors that incorporate RNA-cleaving DNAzymes, we believe we are moving closer to employing RNA-cleaving DNAzymes for exciting applications, such as point of care diagnostics or field detection of environmental toxins.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,311

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,038
Tête enseignante GPT0,394
Écart entre enseignants0,355 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle