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Size-Controlled DNA Tile Self-Assembly Nanostructures Through Caveolae-Mediated Endocytosis for Signal-Amplified Imaging of MicroRNAs in Living Cells.

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Signal-amplified imaging of microRNAs (miRNAs) is a promising strategy at the single-cell level because liquid biopsy fails to reflect real-time dynamic miRNA levels. However, the internalization pathways for available conventional… Click to show full abstract

Signal-amplified imaging of microRNAs (miRNAs) is a promising strategy at the single-cell level because liquid biopsy fails to reflect real-time dynamic miRNA levels. However, the internalization pathways for available conventional vectors predominantly involve endo-lysosomes, showing nonideal cytoplasmic delivery efficiency. In this study, size-controlled 9-tile nanoarrays are designed and constructed by integrating catalytic hairpin assembly (CHA) with DNA tile self-assembly technology to achieve caveolae-mediated endocytosis for the amplified imaging of miRNAs in a complex intracellular environment. Compared with classical CHA, the 9-tile nanoarrays possess high sensitivity and specificity for miRNAs, achieve excellent internalization efficiency by caveolar endocytosis, bypassing lysosomal traps, and exhibit more powerful signal-amplified imaging of intracellular miRNAs. Because of their excellent safety, physiological stability, and highly efficient cytoplasmic delivery, the 9-tile nanoarrays can realize real-time amplified monitoring of miRNAs in various tumor and identical cells of different periods, and imaging effects are consistent with the actual expression levels of miRNAs, ultimately demonstrating their feasibility and capacity. This strategy provides a high-potential delivery pathway for cell imaging and targeted delivery, simultaneously offering a meaningful reference for the application of DNA tile self-assembly technology in relevant fundamental research and medical diagnostics.

Keywords: tile; amplified imaging; self assembly; tile self; dna tile; signal amplified

Journal Title: Advanced science
Year Published: 2023

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