Affinity-Based Enrichment of Extracellular Vesicles with Lipid Nanoprobes.

Affinity-Based Enrichment of Extracellular Vesicles with Lipid Nanoprobes.
复制标题

使用脂质纳米探针基于亲和力富集细胞外囊泡。

DOI:
10.1007/978-1-0716-1811-0_12
复制
发表时间:
2022
期刊:
Methods in molecular biology (Clifton, N.J.)
影响因子:
--
通讯作者:
Zheng,Si-Yang
Zheng,Si-Yang
中科院分区:
--
文献类型:
--
作者:
Wan,Yuan;Maurer,Mackenzie;Zheng,Si-Yang

文献摘要

相似文献

细胞外囊泡是由多种细胞释放的亚微米大小的脂质双层囊泡。EV含有组织特异性特征,其中选择性地包装多种蛋白质和核酸。越来越多的证据表明EV在疾病中的重要生物学作用和临床相关性。为了使EV相关研究蓬勃发展,快速有效地分离纯EV是先决条件。然而,现有的分离方法存在分离过程长、产率低、通量低和污染物高等问题,阻碍了基础研究和大规模临床应用。我们已经表明,脂质纳米探针(LNP)能够通过与磁性富集耦合来自发标记和快速分离EV。最近,我们进一步开发了一个一步EV分离平台,该平台利用EV尺寸匹配的二氧化硅纳米结构和表面缀合的LNP与集成的微流体混合器。来自多达2 ml临床血浆的EV可以使用优化的流速用这种即时设备进行处理。随后,分离的EV的内容物可以在芯片上提取并从装置洗脱以用于下游分子分析。LNP功能化的微流体装置与最先进的分析平台相结合,在未来促进以EV为中心的研究和临床应用方面具有巨大的潜力。
Extracellular vesicles (EVs) are lipid-bilayer-enclosed vesicles with sub-micrometer size that are released by various cells. EVs contain a tissue-specific signature wherein a variety of proteins and nucleic acids are selectively packaged. Growing evidence has shown important biological roles and clinical relevance of EVs in diseases. For EV-related studies to thrive, rapid efficient isolation of pure EVs is a prerequisite. However, lengthy procedure, low yield, low throughput, and high contaminants stemmed from existing isolation approaches hamper both basic research and large-scale clinical implementation. We have shown that lipid nanoprobes (LNP) enable spontaneous labeling and rapid isolation of EVs by coupling with magnetic enrichment. Recently, we further developed a one-step EV isolation platform that utilizes EV size-matched silica nanostructures and surface-conjugated LNPs with an integrated microfluidic mixer. EVs, derived from up to 2-ml clinical plasma, can be processed with this point-of-care device using optimized flow rate. Subsequently, contents of isolated EVs can be extracted on-chip and eluted from the device for downstream molecular analyses. The LNP-functionalized microfluidic device combined with state-of-the-art analysis platforms could have great potential in promoting EV-centered research and clinical use in the future.