Uricase biofunctionalized plasmonic sensor for uric acid detection with APTES-modified gold nanotopping

尿酸 化学 等离子体子 氯金酸 胶体金 纳米技术 材料科学 生物化学 纳米颗粒 光电子学
作者
Olabisi Abdullahi Onifade,Fatin Adriena Yusairie,M. H. Abu Bakar,Mohammed Thamer Alresheedi,Eng Khoon Ng,Mohd Adzir Mahdi,A. S. M. Noor
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:261: 116486-116486 被引量:11
标识
DOI:10.1016/j.bios.2024.116486
摘要

Current uric acid detection methodologies lack the requisite sensitivity and selectivity for point-of-care applications. Plasmonic sensors, while promising, demand refinement for improved performance. This work introduces a biofunctionalized sensor predicated on surface plasmon resonance to quantify uric acid within physiologically relevant concentration ranges. The sensor employs the covalent immobilization of uricase enzyme using 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) and N-Hydroxysuccinimide (NHS) crosslinking agents, ensuring the durable adherence of the enzyme onto the sensor probe. Characterization through atomic force microscopy and Fourier transform infrared spectroscopy validate surface alterations. The Langmuir adsorption isotherm model elucidates binding kinetics, revealing a sensor binding affinity of 298.83 (mg/dL)−1, and a maximum adsorption capacity of approximately 1.0751°. The biofunctionalized sensor exhibits a sensitivity of 0.0755°/(mg/dL), a linear correlation coefficient of 0.8313, and a limit of detection of 0.095 mg/dL. Selectivity tests against potentially competing interferents like glucose, ascorbic acid, urea, D-cystine, and creatinine showcase a significant resonance angle shift of 1.1135° for uric acid compared to 0.1853° for interferents at the same concentration. Significantly, at a low uric acid concentration of 0.5 mg/dL, a distinct shift of 0.3706° was observed, setting it apart from the lower values noticed at higher concentrations for all typical interferent samples. The uricase enzyme significantly enhances plasmonic sensors for uric acid detection, showcasing a seamless integration of optical principles and biological recognition elements. These sensors hold promise as vital tools in clinical and point-of-care settings, offering transformative potential in biosensing technologies and the potential to revolutionize healthcare outcomes in biomedicine.
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