Development of a Novel Quantum Dots and Graphene Oxide Based FRET Assay for Rapid Detection of invA Gene of Salmonella.

Jiubiao Guo,Zhenling Zeng,Edward W C Chan,Sheng Chen

doi:10.3389/fmicb.2017.00008

Abstract

A novel, rapid and simple fluorescence resonance energy transfer (FRET) based Salmonella specific gene, invA, detection system was developed, in which quantum dots (QDs) and graphene oxide (GO) worked as fluorescent donor and quencher, respectively. By measuring the fluorescence intensity signal, the Salmonella specific invA gene could be sensitively and specifically detected with a limit of detection (LOD) of ∼4 nM of the invA gene in 20 min. The developed system has the potential to be used for Salmonella detection in food and environmental samples and further developed into a platform for detection of other bacterial pathogens.

Highlights

Salmonella, a major Gram-negative bacteria enteric pathogen, has evolved numerous strategies to infect and proliferate in a vast array of hosts, such as humans and animals, causing a wide range of food- and water-borne diseases (LaRock et al, 2015)
Upon the addition of the complementary invA oligo of Salmonella, the quantum dots (QDs) and graphene oxide (GO) conjugates could be brought into close proximity to make the fluorescence resonance energy transfer (FRET) pair work, the energy emitted from excited QDs would be quenched by GO
The invA gene of Salmonella can be detected via the measurement of the fluorescence intensity change in the developed system

Summary

Introduction

Salmonella, a major Gram-negative bacteria enteric pathogen, has evolved numerous strategies to infect and proliferate in a vast array of hosts, such as humans and animals, causing a wide range of food- and water-borne diseases (LaRock et al, 2015). The last decade has witnessed a rapid development of biosensing techniques and new biomaterials (Saikia et al, 2013; Jana et al, 2015; Unser et al, 2015; Zheng et al, 2015). They have been proven to be valid for various applications ranging from pathogens detection to cancers therapies (Alocilja and Radke, 2003; Liu et al, 2009; Chen et al, 2015; Shi et al, 2015).

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Conclusion