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Prolonged near-infrared fluorescence imaging of microRNAs and proteases in vivo by aggregation-enhanced emission from DNA-AuNC nanomachines

Developing a comprehensive strategy for imaging various biomarkers ( , microRNAs and proteases) is an exceptionally formidable task. Herein, we have designed a deoxyribonucleic acid-gold nanocluster (DNA-AuNC) nanomachine for detecting tumor-related TK1 mRNA and cathepsin B in living cells and . The...

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Bibliographic Details
Published in:Chemical science (Cambridge) 2024-01, Vol.15 (5), p.1829-1839
Main Authors: Wang, Ting, Jiang, Kai, Wang, Yifan, Xu, Limei, Liu, Yingqi, Zhang, Shiling, Xiong, Weiwei, Wang, Yemei, Zheng, Fenfen, Zhu, Jun-Jie
Format: Article
Language:English
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Summary:Developing a comprehensive strategy for imaging various biomarkers ( , microRNAs and proteases) is an exceptionally formidable task. Herein, we have designed a deoxyribonucleic acid-gold nanocluster (DNA-AuNC) nanomachine for detecting tumor-related TK1 mRNA and cathepsin B in living cells and . The DNA-AuNC nanomachine is constructed using AuNCs and DNA modules that incorporate a three component DNA hybrid (TD) and a single-stranded fuel DNA (FD). Upon being internalized into tumor cells, the TK1 mRNA initiates the DNA-AuNC nanomachine through DNA strand displacement cascades, leading to the amplified self-assembly and the aggregation-enhanced emission of AuNCs for imaging. Furthermore, with the aid of a protease nanomediator consisting of a mediator DNA/peptide complex and AuNCs (DpAuNCs), the DNA-AuNC nanomachine can be triggered by the protease-activated disassembly of the DNA/peptide complex on the nanomediator, resulting in the aggregation of AuNCs for protease amplified detection. It is worth noting that our study demonstrates the impressive tumor permeability and accumulation capabilities of the DNA-AuNC nanomachines amplified self-assembly, thereby facilitating prolonged imaging of TK1 mRNA and cathepsin B both and . This strategy presents a versatile and biomarker-specific paradigm for disease diagnosis.
ISSN:2041-6520
2041-6539
DOI:10.1039/d3sc05887e