Multicolor Covalent Organic Framework-DNA Nanoprobe for Fluorescence Imaging of Biomarkers with Different Locations in Living Cells.
Peng GaoRuyue WeiYuanyuan ChenXiaohan LiuJie ZhangWei PanNa LiBo TangPublished in: Analytical chemistry (2021)
Precisely detecting biomarkers in living systems holds tremendous promise for disease diagnosis and monitoring. Herein, we developed a covalent organic framework (COF)-based tricolor fluorescent nanoprobe for simultaneously imaging biomarkers with different spatial locations in living cells. Briefly, a TAMRA-labeled survivin mRNA antisense nucleotide and a Cy5-labeled transmembrane glycoprotein mucin 1 (MUC1) aptamer were adsorbed on a nanoscale fluorescent COF. To enhance the interactions between COF nanoparticles (NPs) and nucleic acid molecules, a freezing method was employed for improving the nucleic acid loading density and ensuring detection performance. The fluorescence signals of dyes on DNAs were first quenched by the COF NPs. Internalization and distribution of the nanoprobes can be real-time visualized by the autofluorescence of COF NPs. In living cells, recognition between MUC1 with MUC1 aptamers causes fluorescence signal recovery of Cy5, while hybridization between survivin mRNA and its antisense DNA induces the signal recovery of TAMRA. Therefore, this COF-based multicolor nanoprobe could be employed for visualizing MUC1 on the cell membrane and survivin mRNA in the cytoplasm. Cancer cell-specific diagnostic imaging and monitoring of the process of cancer cell exosomes infecting normal cells using the nanoprobe were achieved. This work not only offers a versatile nanoprobe for bioanalysis but also provides new insights for developing novel COF-based nanoprobes.
Keyphrases
- living cells
- nucleic acid
- single molecule
- fluorescence imaging
- fluorescent probe
- atomic force microscopy
- photodynamic therapy
- high resolution
- binding protein
- mesenchymal stem cells
- gold nanoparticles
- induced apoptosis
- flow cytometry
- computed tomography
- cell proliferation
- deep learning
- big data
- artificial intelligence
- circulating tumor cells
- bone marrow