Highly selective and sensitive chemiluminescence biosensor for adenosine detection based on carbon quantum dots catalyzing luminescence released from aptamers functionalized graphene@magnetic β-cyclodextrin polymers

Abstract

In this work, a highly selective and sensitive chemiluminescence (CL) biosensor was prepared for adenosine (AD) detection based on carbon quantum dots (CQDs) catalyzing the CL system of luminol-H2O2 under alkaline environment and CQDs was released from the surface of AD aptamers functionalized graphene @ magnetic β-cyclodextrin polymers (GO@Fe3O4@β-CD@A-Apt). Firstly, GO@Fe3O4@β-CD and CQDs were prepared and characterized by transmission electron microscopy (TEM), scanning electron microscope (SEM), UV–Vis absorption spectra (UV), fluorescence spectra (FL), fourier transform infrared (FTIR) and X-ray powder diffraction (XRD). For GO@Fe3O4@β-CD, Fe3O4 was easy to separate, GO had good biocompatibility and large specific surface area, and β-CD further increased the specific surface area of the adenosine polymers (A-Apt) to provided larger binding sites to A-Apt. Then, A-Apt was modified on the surface of GO@Fe3O4@β-CD while CQDs was modified by ssDNA (a single stranded DNA partially complementary to A-Apt). The immobilization property (GO@Fe3O4@β-CD to A-Apt) and the adsorption property (GO@Fe3O4@β-CD@A-Apt to CQDs-ssDNA) were sequentially researched. The base-supported chain-like polymers – GO@Fe3O4@β-CD@A-Apt/CQDs-ssDNA was successfully obtained. When AD existed, CQDs-ssDNA was released from the surface of GO@Fe3O4@β-CD@A-Apt and catalyzed CL. After that, under optimized CL conditions, AD could be measured with the linear concentration range of 5.0 × 10−13–5.0 × 10−9 mol/L and the detection limit of 2.1 × 10−13 mol/L (3δ) while the relative standard deviation (RSD) was 1.4%. Finally, the GO@Fe3O4@β-CD@A-Apt/CQDs-ssDNA-CL biosensor was used for the determination of AD in urine samples and recoveries ranged from 98.6% to 101.0%. Those satisfactory results illustrated the proposed CL biosensor could achieve highly selective, sensitive and reliable detection of AD and revealed potential application for AD detection in monitoring and diagnosis of human cancers.