Tailed-Hoogsteen Triplex DNA Silver Nanoclusters Emit Red Fluorescence upon Target miRNA Sensing.
Hari Chandana YadavalliSooyeon ParkYeolhoe KimRiddhi NagdaTae-Hwan KimMin Kyun HanIl Lae JungYong Joo BhangWon Ho YangLouise Torp DalgaardSeong Wook YangPratik ShahPublished in: Small (Weinheim an der Bergstrasse, Germany) (2023)
MicroRNAs (miRNAs) are small RNA molecules, typically 21-22 nucleotides in size, which play a crucial role in regulating gene expression in most eukaryotes. Their significance in various biological processes and disease pathogenesis has led to considerable interest in their potential as biomarkers for diagnosis and therapeutic applications. In this study, a novel method for sensing target miRNAs using Tailed-Hoogsteen triplex DNA-encapsulated Silver Nanoclusters (DNA/AgNCs) is introduced. Upon hybridization of a miRNA with the tail, the Tailed-Hoogsteen triplex DNA/AgNCs exhibit a pronounced red fluorescence, effectively turning on the signal. It is successfully demonstrated that this miRNA sensor not only recognized target miRNAs in total RNA extracted from cells but also visualized target miRNAs when introduced into live cells, highlighting the advantages of the turn-on mechanism. Furthermore, through gel-fluorescence assays and small-angle X-ray scattering (SAXS) analysis, the turn-on mechanism is elucidated, revealing that the Tailed-Hoogsteen triplex DNA/AgNCs undergo a structural transition from a monomer to a dimer upon sensing the target miRNA. Overall, the findings suggest that Tailed-Hoogsteen triplex DNA/AgNCs hold great promise as practical sensors for small RNAs in both in vitro and cell imaging applications.
Keyphrases
- single molecule
- circulating tumor
- cell free
- nucleic acid
- gene expression
- living cells
- high resolution
- induced apoptosis
- sensitive detection
- gold nanoparticles
- fluorescent probe
- energy transfer
- cell cycle arrest
- circulating tumor cells
- dna methylation
- risk assessment
- quantum dots
- high throughput
- human health
- cell proliferation
- artificial intelligence
- mass spectrometry
- computed tomography
- big data
- climate change