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    Molecularly imprinted surface plasmon resonance (SPR) sensor for uric acid determination

    Year: 2017

    Journal: Sens. Actuator B-Chem., Volume 251, NOV, page 763–772

    Authors: Sarikaya, Asli Gocenoglu; Osman, Bilgen; Cam, Tulay; Denizli, Adil

    Organizations: Research Foundation of Uludag University [OUAP-2016/4]

    Keywords: Uric acid; SPR sensor; Molecular imprinting; Nanoparticle; Metal ion imprinting

    The main objective of this study was to prepare a surface plasmon resonance (SPR) sensor for uric acid (UA) detection by using molecularly imprinted nanoparticles as a molecular recognition element. For imprinting, metal ion mediated preorganization was performed to interact between template molecules (UA) and functional monomer by using Fe3+ ions. UA-imprinted poly (hydroxyethyl methacrylate methacryloyl-l-cysteine methyl ester)-Fe3+ [poly(HEMA-MAC)-Fe3+] nanoparticles were synthesized by emulsion polymerization in the presence of MAC-Fe3+-UA pre-polymerization complex. The characterization of UA-imprinted poly(HEMA-MAC)-Fe3+ nanoparticles was conducted by Fourier transform infrared spectroscopy (FTIR), elemental analysis, scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDS), transmission electron microscopy (TEM) and zeta size analysis. The SPR sensor was prepared by gold surface modification of the sensor with UA-imprinted poly(HEMA-MAC)-Fe3+ nanoparticles. Characterization of the SPR sensor surface was performed with atomic force microscopy (AFM), contact angle (CA) and optic profilometer measurements. UA sensing ability of the prepared sensor was determined by interacting UA solutions in different concentrations (0.5-40 mg/L) with the SPR sensor. The limit of detection (LOD) and limit of quantification (LOQ) values for the prepared SPR sensor were calculated as 0.247 and 0.825 mg/L for aqueous solution, respectively. The UA-imprinted sensor was also used for UA detection in urine. The results showed the SPR sensor has high selectivity and sensitivity for UA. (C) 2017 Elsevier B.V. All rights reserved.
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