A two-layer circuit cascade-based DNA machine for highly sensitive miRNA imaging in living cells

Abstract

Sensitive detection of microRNA (miRNA), one of the most promising biomarkers, plays crucial roles in cancer diagnosis. However, the low expression level of miRNA makes it extremely urgent to develop ultrasensitive and highly selective strategies for quantification of miRNA. Herein, a DNA machine is rationally constructed for amplified detection and imaging of low-abundance miRNA in living cells based on the toehold-mediated strand displacement reaction (TMSDR). The isothermal and enzyme-free DNA machine with low background leakage is fabricated by integrating two DNA circuits into a cascade system, in which the output of one circuit serves as the input of the other one. Once the DNA machine is transfected into breast cancer cells, the overexpressed miRNA-203 initiates the first-layer circuit through TMSDR, leading to the concentration variation of fuel strands, which further influences the assembly of hairpin DNA in the second-layer circuit and the occurrence of fluorescence resonance energy transfer (FRET) for fluorescence imaging. Benefiting from the cascade of the two-layer amplification reaction, the proposed DNA machine acquires a detection limit down to 4 fM for quantification of miR-203 and a 10 000-fold improvement in amplification efficiency over the single circuit. Therefore, the two-layer circuit cascade-based DNA machine provides an effective platform for amplified analysis of low-abundance miRNA with high sensitivity, which holds great promise in biomedical and clinical research.

Graphical abstract: A two-layer circuit cascade-based DNA machine for highly sensitive miRNA imaging in living cells

Supplementary files

Article information

Article type
Paper
Submitted
21 Feb 2024
Accepted
14 Mar 2024
First published
23 Mar 2024

Analyst, 2024, Advance Article

A two-layer circuit cascade-based DNA machine for highly sensitive miRNA imaging in living cells

L. Yang, Y. Zang, P. Liu, X. Xing and Z. Mou, Analyst, 2024, Advance Article , DOI: 10.1039/D4AN00277F

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