Aptamer-Loop DNA Nanoflower Recognition and Multicolor Fluorescent Carbon Quantum Dots Labeling System for Multitarget Living Cell Imaging

被引:0
|
作者
Guo, Xilin [1 ]
Tian, Baohua [2 ]
Li, Xinxin [2 ]
Lei, Yu [1 ]
Sun, Mingyuan [1 ]
Miao, Qiang [1 ]
Li, Hao [1 ]
Ma, Risheng [1 ]
Liang, Haixia [1 ,2 ]
机构
[1] Taiyuan Univ Technol, Coll Biomed Engn, Jinzhong 030600, Shanxi, Peoples R China
[2] Taiyuan Univ Technol, Coll Ecol, Taiyuan 030024, Shanxi, Peoples R China
关键词
multitarget; living cell imaging; rolling circleamplification; aptamer; DNA nanoflowers; carbon quantum dots; NUCLEOLIN;
D O I
10.1021/acsami.4c09358
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Visualization of multiple targets in living cells is important for understanding complex biological processes, but it still faces difficulties, such as complex operation, difficulty in multiplexing, and expensive equipment. Here, we developed a nanoplatform integrating a nucleic acid aptamer and DNA nanotechnology for living cell imaging. Aptamer-based recognition probes (RPs) were synthesized through rolling circle amplification, which were further self-assembled into DNA nanoflowers encapsulated by an aptamer loop. The signal probes (SPs) were obtained by conjugation of multicolor emission carbon quantum dots with oligonucleotides complementary to RPs. Through base pairing, RPs and SPs were hybridized to generate aptamer sgc8-, AS1411-, and Apt-based imaging systems. They were used for individual/simultaneous imaging of cellular membrane protein PTK7, nucleolin, and adenosine triphosphate (ATP) molecules. Fluorescence imaging and intensity analysis showed that the living cell imaging system can not only specifically recognize and efficiently bind their respective targets but also provide a 5-10-fold signal amplification. Cell-cycle-dependent distribution of nucleolin and concentration-dependent fluorescence intensity of ATP demonstrated the utility of the system for tracking changes in cellular status. Overall, this system shows the potential to be a simple, low-cost, highly selective, and sensitive living cell imaging platform.
引用
收藏
页码:45327 / 45336
页数:10
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