Issue 7, 2018

Multiple advanced logic gates made of DNA-Ag nanocluster and the application for intelligent detection of pathogenic bacterial genes

Abstract

The integration of multiple DNA logic gates on a universal platform to implement advance logic functions is a critical challenge for DNA computing. Herein, a straightforward and powerful strategy in which a guanine-rich DNA sequence lighting up a silver nanocluster and fluorophore was developed to construct a library of logic gates on a simple DNA-templated silver nanoclusters (DNA-AgNCs) platform. This library included basic logic gates, YES, AND, OR, INHIBIT, and XOR, which were further integrated into complex logic circuits to implement diverse advanced arithmetic/non-arithmetic functions including half-adder, half-subtractor, multiplexer, and demultiplexer. Under UV irradiation, all the logic functions could be instantly visualized, confirming an excellent repeatability. The logic operations were entirely based on DNA hybridization in an enzyme-free and label-free condition, avoiding waste accumulation and reducing cost consumption. Interestingly, a DNA-AgNCs-based multiplexer was, for the first time, used as an intelligent biosensor to identify pathogenic genes, E. coli and S. aureus genes, with a high sensitivity. The investigation provides a prototype for the wireless integration of multiple devices on even the simplest single-strand DNA platform to perform diverse complex functions in a straightforward and cost-effective way.

Graphical abstract: Multiple advanced logic gates made of DNA-Ag nanocluster and the application for intelligent detection of pathogenic bacterial genes

Supplementary files

Article information

Article type
Edge Article
Submitted
11 Dec 2017
Accepted
05 Jan 2018
First published
08 Jan 2018
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2018,9, 1774-1781

Multiple advanced logic gates made of DNA-Ag nanocluster and the application for intelligent detection of pathogenic bacterial genes

X. Lin, Y. Liu, J. Deng, Y. Lyu, P. Qian, Y. Li and S. Wang, Chem. Sci., 2018, 9, 1774 DOI: 10.1039/C7SC05246D

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