Related Experiment Video
Updated: Jun 24, 2025

Open-Source Miniature Fluorimeter to Monitor Real-Time Isothermal Nucleic Acid Amplification Reactions in Resource-Limited Settings
Published on: February 3, 2021
A highly sensitive fluorescence sensor for tobacco mosaic virus RNA based on DSN cycle and ARGET ATRP double signal
Zhenyu Jin1, Lele Ma1, Yuting Zhang1
1Pharmacy College, Henan University of Chinese Medicine, Zhengzhou, People's Republic of China.
Abstract:
Early and sensitive detection of tobacco mosaic virus (TMV) is of great significance for improving crop yield and protecting germplasm resources. Herein, we constructed a novel fluorescence sensor to detect TMV RNA (tRNA) through double strand specific nuclease (DSN) cycle and activator regenerative electron transfer atom transfer radical polymerization (ARGET ATRP) dual signal amplification strategy. The hairpin DNA complementarily paired with tRNA was used as a recognition unit to specifically capture tRNA. By the double-stranded DNA hydrolyzed with DSN, tRNA is released to open more hairpin DNA, and more complementary DNA (cDNA) is bound to the surface of the magnetic beads (MBs) to achieve the first amplification. After binding with the initiator, the cDNA employed ARGET ATRP to attach more fluorescent signal molecules to the surface of MBs, thus achieving the second signal amplification. Under the optimal experimental conditions, the logarithm of fluorescence intensity versus tRNA concentration showed a good linear relationship in the range of 0.01-100 pM, with a detection limit of 1.03 fM. The limit of detection (LOD) was calculated according to LOD = 3 N/S. Besides, the sensor showed good reproducibility and stability, which present provided new method for early and highly sensitive detection for plant viruses.
More Related Videos
06:18Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1
Published on: March 13, 2018
08:36Measuring Dengue Virus RNA in the Culture Supernatant of Infected Cells by Real-time Quantitative Polymerase Chain Reaction
Published on: November 1, 2018