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适配体功能化金属有机框架基静电纺丝纳米纤维复合涂层纤维用于水中痕量微囊藻毒素的特异性识别。

Aptamer-functionalized metal-organic framework-based electrospun nanofibrous composite coating fiber for specific recognition of ultratrace microcystin in water.

机构信息

Institute of Food Safety and Environment Monitoring, Fuzhou University, Fuzhou 350108, People's Republic of China.

Institute of Food Safety and Environment Monitoring, Fuzhou University, Fuzhou 350108, People's Republic of China; Engineering Technology Research Center on Reagent and Instrument for Rapid Detection of Product Quality and Food Safety, Fuzhou, Fujian 350108, People's Republic of China.

出版信息

J Chromatogr A. 2021 Oct 25;1656:462542. doi: 10.1016/j.chroma.2021.462542. Epub 2021 Sep 10.

DOI:10.1016/j.chroma.2021.462542
PMID:34543883
Abstract

A novel aptamer@AuNPs@UiO-66-NH electrospun nanofibrous coating fiber for specific recognition of microcystin-LR (MC-LR) was proposed by using electrospinning, metal-organic frameworks (MOF) seed growth and AuNPs bridging aptamer strategies. Characterization of morphology, structure and stability of the obtained affinity nanofibrous coating fiber were investigated. High loading of MOFs and aptamers on the nanofibrous fiber were achieved and successfully applied for accurate identification of MC-LR by solid-phase microextraction (SPME) coupled with LC-MS. Highly specific recognition of MC-LR with little interference of analogs was achieved with extremely low LOD (0.004 ng/mL), good precision (CV% < 11.0%) and low relative error (RE% = -1.5% to -10.0%), which was rather better than that of the traditional SPME or SPE protocols. Satisfactory recoveries of MC-LR were obtained in the range of 92.0-96.8% (n = 3) in fortified tap water, raw pond water and river water samples. This work revealed an attractive alternative access to specific recognition and super-sensitive analysis of MC-LR in water.

摘要

一种新型适体@AuNPs@UiO-66-NH 电纺纳米纤维涂层纤维,通过静电纺丝、金属有机骨架(MOF)种子生长和 AuNPs 桥连适体策略,用于特异性识别微囊藻毒素-LR(MC-LR)。研究了所获得的亲和纳米纤维涂层纤维的形态、结构和稳定性。实现了 MOFs 和适体在纳米纤维上的高负载,并成功应用于固相微萃取(SPME)结合 LC-MS 对 MC-LR 进行准确识别。该方法对 MC-LR 具有高度特异性识别,对类似物干扰较小,LOD(0.004ng/mL)极低,精密度好(CV%<11.0%),相对误差低(RE%=-1.5%至-10.0%),明显优于传统的 SPME 或 SPE 方法。在加标自来水中、原池塘水和河水样品中,MC-LR 的回收率在 92.0-96.8%(n=3)范围内令人满意。这项工作为水中 MC-LR 的特异性识别和超灵敏分析提供了一种有吸引力的替代方法。

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