微泡
同种类的
寄主(生物学)
化学
计算机科学
纳米技术
小RNA
材料科学
生物
生物化学
数学
生态学
基因
组合数学
作者
Haiyan Wang,Peng Liang,Lei Zhang,Liping Shi,Yitong Ge,Liyuan Zhang,Xiaoqiang Qiao
出处
期刊:Social Science Research Network
[Social Science Electronic Publishing]
日期:2022-01-01
摘要
Exosomes offer ideal biomarkers for liquid biopsies. However, high-efficient purification of exosomes has been proven to be extreme challenging. Here, we report a soluble pH-responsive host-guest-based nanosystem (pH-HGN) for homogeneous isolation of exosomes around physiological pH. The pH-HGN consists of two specifically functionalized modules. First, a pH-responsive module, poly-dimethylaminoethyl methacrylate (DMAEMA), provides homogeneous isolation circumstances and sharp pH-triggered self-assembly separation in aqueous solution to improve capture efficiency and antifouling capability. Second, a host-guest module, poly-acrylamide azobenzene (AAAB) and β-cyclodextrin linked with exosome-specific antibody, could act as the “cleavable bridge” to specific capture and subsequent rapid release of captured exosomes through host-guest interaction between β-cyclodextrin and AAAB moieties. The homogeneous isolation nature of pH-HGN achieved high-efficient isolation of intact exosomes with excellent antifouling ability. The nonspecific adsorption of pH-HGN in the presence of high concentration of protein (10 mg/mL) was under 0.02% after two washing with PBS buffer. Moreover, the pH-HGN offered high capture efficiencies for different sources of exosomes, which were 90.15±0.28% and 87.0±4.6% for H1299 and MCF-7 cell-derived exosomes, respectively. The purity of exosomes isolated by the pH-HGN reached 1.49±0.71 ×1011 P/μg, which was 4.1 times higher than that via the gold standard ultracentrifugation (UC) method. Furthermore, the captured exosomes via the pH-HGN can preserve well integrity and biological activity. The developed pH-HGN was further successfully applied to differentiate serum exosomes from healthy persons and lung cancer patients. These findings indicate that pH-HGN is a promising strategy to test exosome-based biomarkers for cancer diagnostics.
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