Developing a DNA logic gate nanosensing platform for the detection of acetamiprid. Issue 42 (27th September 2022)

• Record Type: Journal Article
• Authors: Xi, Sunfan; Wang, Luhui; Cheng, Meng; Hu, Mengyang; Liu, Rong; Dong, Yafei
• Is Part Of: RSC advances. Volume 12:Issue 42(2022)
• Page Start: 27421
• Page End: 27430
• Publication Date: 2022-09-27
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d2ra04794b
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : A cyclic dual-signal biosensing device based on G-quadruplexes is developed for the detection of acetamiprid. Abstract : This paper reports a novel fluorescence and colorimetric dual-signal-output DNA aptamer based sensor for the detection of acetamiprid residue. Acetamiprid is a new systemic broad-spectrum insecticide with high insecticidal efficiency that is widely used worldwide, but there is a risk of adverse neurological reactions in humans and animals. The dual-mode output principle designed in this paper, consisting of a fluorescence signal and colorimetric signal, is based on the relevant reaction of the special domain of a G-quadruplex, bidding farewell to a classical single-signal output, with a target-recognition cycle used to complete signal amplification through a hybridization chain reaction. Upgraded detection sensitivity and the qualitative and semi-quantitative detection of acetamiprid are achieved based on the fluorescence signal output and visual discrimination observations during colorimetric experiments. This model was applied to the determination of acetamiprid residue in fruits and vegetables. The dual-detection platform further reduced systematic error, with a detection limit of 27.7 pM. When applied in a comparative detection study using three different pesticides, the system shows excellent discrimination specificity and it performs well in actual sample detection and has a fast response time. Designing DNA logic gates that operate in the presence of targets and molecular-switch-based detection platforms also involves the intersection of biology and computational modeling, providing new ideas for biological platforms.