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Issue 21, 2020
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Sensitive detection of intracellular telomerase activity via double signal amplification and ratiometric fluorescence resonance energy transfer

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Abstract

As an important and universal tumor marker, the reliable and in situ detection of intracellular telomerase activity is crucial for cancer diagnosis. Herein, a ratiometric fluorescence resonance energy transfer (FRET) method was developed for detecting intracellular telomerase activity. It takes full advantage of manganese dioxide nanosheets (MnO2NS) that can carry DNA probes with different conformations into cells and then completely release the DNA probes via decomposition of MnO2NS by intracellular reduced glutathione (GSH). In the presence of telomerase, a telomere substrate (TS) could be extended to form long telomerase extension products (TEPs), which trigger the cycling strand displacement reaction (SDR) between two fluorophore-labeled hairpin DNA probes to form lots of DNA duplexes. The close contact of two fluorophores led to an effective ratiometric FRET for reliable detection of telomerase activity. Fluorescence confocal imaging demonstrated that the activity of telomerase in tumor cells was reliably detected. The inhibition of telomerase activity by an inhibitor resulted in a decrease in FRET signal. For extracellular detection, the FRET ratio (FA/FD) shows a good linear relationship with the number of HeLa cells in the range of 20–1000 cells. Therefore, it offers a more facile method for reliable and sensitive detection of intracellular telomerase activity.

Graphical abstract: Sensitive detection of intracellular telomerase activity via double signal amplification and ratiometric fluorescence resonance energy transfer

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Supplementary files

Article information


Submitted
30 Jun 2020
Accepted
27 Jul 2020
First published
27 Jul 2020

Analyst, 2020,145, 6992-6999
Article type
Paper

Sensitive detection of intracellular telomerase activity via double signal amplification and ratiometric fluorescence resonance energy transfer

B. Zhang, L. Shi, W. Liu, B. Li and Y. Jin, Analyst, 2020, 145, 6992
DOI: 10.1039/D0AN01291B

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