Electrochemical Immunosensor for Cardiac Troponin I Detection Based on Covalent Organic Framework and Enzyme-Catalyzed Signal Amplification

ANALYTICAL CHEMISTRY(2021)

引用 53|浏览7
暂无评分
摘要
Herein, a highly sensitive electrochemical immunosensor was presented for the cardiac troponin I (cTnI) determination using a multifunctional covalent organic framework-based nanocomposite (HRP-Ab2-Au-COF) as the signal amplification probe. The spherical COF with a large surface area was synthesized in a short time by a simple solution-based method at room temperature. The good biocompatibility, low toxicity, and high stability in water of the COF guarantee its application in biosensing. Besides, its high porosity makes it an excellent carrier for loading abundant horseradish peroxidase (HRP). The modified gold nanoparticles on the surface of COF not only provide a load platform for secondary antibody (Ab2) but also improve the conductivity of COF. Under the synergistic effect of the hydrogen peroxide (H2O2) and HRP, hydroquinone (HQ) in the solution is catalytically oxidized to benzoquinone (BQ), which is then reduced on the electrode surface to generate the electrochemical signal. The designed probes not only show the specific recognition behavior of Ab2 to cTnI but also improve the sensitivity of the biosensing system due to the signal amplification caused by the excellent enzyme catalytic performance of HRP. Based on the H2O2-HRP-HQ signal amplification system, the biosensor for cTnI was fabricated and exhibited a linear response as a function of logarithmic cTnI concentration ranging from 5 pg/mL to 10 ng/mL, and the detection limit was 1.7 pg/mL. Moreover, the biosensor exhibited excellent recovery and reproducibility in the actual sample testing. This work provided a simple approach to determine cTnI quantitatively in practical samples and broadened the utilization scope of the COF-based nanocomposite in the electrochemical immunosensor.
更多
查看译文
关键词
covalent organic framework,enzyme-catalyzed
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要