Micro- and Nanopillar Chips for Continuous Separation of Extracellular Vesicles

Hattori, Yuya; Shimada, Taisuke; Yasui, Takahiro; Kaji, Noritada; Baba, Yoshinobu

doi:10.1021/acs.analchem.8b05538

Cited by 39 publications

(38 citation statements)

References 33 publications

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“…Hattori et al successfully separated 50 and 200 nm NPs using micro-and nano-pillar chips on an electroosmotic flow (EOF)-driven DLD, and also roughly separated EVs below and above 400 nm in size. Similarly, those authors could not change the size distribution of the exosomes so much before and after sorting, either [26]. Zeming et al also reported the separation of 51 and 190 nm NPs using DLD devices under different ionic concentrations.…”

Section: Introductionmentioning

confidence: 89%

Size Sorting of Exosomes by Tuning the Thicknesses of the Electric Double Layers on a Micro-Nanofluidic Device

et al. 2020

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Exosomes, a type of extracellular vesicle with a diameter of 30–150 nm, perform key biological functions such as intercellular communication. Recently, size sorting of exosomes has received increasing attention in order to clarify the correlation between their size and components. However, such sorting remains extremely difficult. Here, we propose to sort their size by controlling their electrokinetic migration in nanochannels in a micro-nanofluidic device, which is achieved by tuning the thickness of the electric double layers in the nanochannels. This approach was demonstrated experimentally for exosomes smaller than 250 nm. Using different running buffer concentrations (1 × 10−3, 1 × 10−4, and 1 × 10−5 M), most of the exosomes larger than 140, 110, and 80 nm were successfully cut off at the downstream of the nanochannels, respectively. Therefore, it is clarified that the proposed method is applicable for the size sorting of exosomes.

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Section: Introductionmentioning

confidence: 89%

Size Sorting of Exosomes by Tuning the Thicknesses of the Electric Double Layers on a Micro-Nanofluidic Device

et al. 2020

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“…invented an electroosmotic flow‐driven DLD method to isolate EVs continuously (Figure 2e ), which possessed an easy‐to‐operate flow control compared to the traditional DLD procedure. [ 64 ] The DLD procedures showed good potential for size‐based EV isolation. However, other characteristics of EVs, such as density and stiffness, are non‐negligible interference factors in DLD‐based EV isolation.…”

Section: Advanced Nanotechnologies For Ev Isolationmentioning

confidence: 99%

mentioning

confidence: 99%

Advanced Nanotechnologies for Extracellular Vesicle‐Based Liquid Biopsy

et al. 2021

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Extracellular vesicles (EVs) are emerging as a new source of biomarkers in liquid biopsy because of their wide presence in most body fluids and their ability to load cargoes from disease-related cells. Owing to the crucial role of EVs in disease diagnosis and treatment, significant efforts have been made to isolate, detect, and analyze EVs with high efficiency. A recent overview of advanced EV detection nanotechnologies is discussed here. First, several key challenges in EV-based liquid biopsies are introduced. Then, the related pivotal advances in nanotechnologies for EV isolation based on physical features, chemical affinity, and the combination of nanostructures and chemical affinity are summarized. Next, a summary of high-sensitivity sensors for EV detection and advanced approaches for single EV detection are provided. Later, EV analysis is introduced in practical clinical scenarios, and the application of machine learning in this field is highlighted. Finally, future opportunities for the development of next-generation nanotechnologies for EV detection are presented.

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“…Current methodologies for EV separation are mainly divided into three groups: 82 density-based separation using ultracentrifugation; 83 size-based separation using size exclusion chromatography; and immunoaffinity-based separation (for specific membrane proteins, e.g., CD9, CD63, and CD81). As emerging alternatives, microfluidicbased platforms (density-, immunoaffinity-, and size-based separations) 84,85 have been reported. The EV subsets obtained through density-, size-, and immunoaffinity-based separations have been extensively studied, but fewer efforts have been devoted to investigating the correlation between EV subsets obtained through surface charge-based separation and encapsulated miRNAs or expressed membrane proteins.…”

Section: Ev Separation Using Nanowiresmentioning

confidence: 99%