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High-Performance Detection of Exosomes Based on Synergistic Amplification of Amino-Functionalized Fe3O4 Nanoparticles and Two-Dimensional MXene Nanosheets
Zhuang, Linlin1,2; You, Qiannan1,2; Su, Xue1,2; Chang, Zhimin2; Ge, Mingfeng2; Mei, Qian2; Yang, Li3; Dong, Wenfei1,2; Li, Li1,2
2023-04-01
摘要Exosomes derived from cancer cells have been recognized as a promising biomarker for minimally invasive liquid biopsy. Herein, a novel sandwich-type biosensor was fabricated for highly sensitive detection of exosomes. Amino-functionalized Fe3O4 nanoparticles were synthesized as a sensing interface with a large surface area and rapid enrichment capacity, while two-dimensional MXene nanosheets were used as signal amplifiers with excellent electrical properties. Specifically, CD63 aptamer attached Fe3O4 nanoprobes capture the target exosomes. MXene nanosheets modified with epithelial cell adhesion molecule (EpCAM) aptamer were tethered on the electrode surface to enhance the quantification of exosomes captured with the detection of remaining protein sites. With such a design, the proposed biosensor showed a wide linear range from 102 particles mu L-1 to 10(7) particles mu L-1 for sensing 4T1 exosomes, with a low detection limit of 43 particles mu L-1. In addition, this sensing platform can determine four different tumor cell types (4T1, Hela, HepG2, and A549) using surface proteins corresponding to aptamers 1 and 2 (CD63 and EpCAM) and showcases good specificity in serum samples. These preliminary results demonstrate the feasibility of establishing a sensitive, accurate, and inexpensive electrochemical sensor for detecting exosome concentrations and species. Moreover, they provide a significant reference for exosome applications in clinical settings, such as liquid biopsy and early cancer diagnosis.
关键词exosomes Ti3C2 MXene magnetic nanoparticles electrochemical biosensor synergistic amplification
DOI10.3390/s23073508
发表期刊SENSORS
卷号23期号:7页码:14
通讯作者You, Qiannan(youqn@sibet.ac.cn) ; Yang, Li(ylyhp@126.com) ; Li, Li(lil@sibet.ac.cn)
收录类别SCI
WOS记录号WOS:000970431500001
语种英语