Microfluidic isolation of extracellular vesicles using a short arcuated channel

• Main Author: Lim, Jia Jia
• Other Authors: Hou Han Wei
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Mechanical engineering::Fluid mechanics
• Online Access: https://hdl.handle.net/10356/158602
• Institution: Nanyang Technological University

Extracellular vesicles (EVs) are cell-derived nanoscale (~ 50 to 200 nm) membrane-bound particles which are important for cell-to-cell communication and are implicated in various diseases. While EVs present great potential as future disease biomarkers or drug delivery agents, it remains technically challenging to isolate EVs from complex biofluids like whole blood. Conventional EV isolation methods, such as ultracentrifugation (UC) and size exclusion chromatography (SEC) require manual centrifugation to remove cells and debris, which is labour intensive and time consuming. Therefore, there is an unmet need to develop a more robust, user-friendly and convenient EVs isolation method. In this paper, we report the development of a short arcuated microfluidic platform, ExoArc, to directly isolate EVs from whole blood in a label-free manner without manual centrifugation. Fluorescent imaging showed that 50 nm and 500 nm beads (representative of EV size range) could be efficiently separated from 1 μm beads at high flow rate (0.2 mL/min of whole blood), thus indicating minimal contamination of platelets and apoptotic bodies (~ 1 to 3 μm) in the isolated EVs. Nanoparticle tracking analysis (NTA) revealed that ExoArc had 2x and 500x higher particle yield than SEC and UC respectively. Protein level of ExoArc-eluted EVs was ~ 10 mg/mL which is 10x lower than plasma samples. To further reduce protein contamination, a 2-step EV isolation process (ExoArc + SEC) was proposed in which we demonstrated comparable EV yield of CD9+ as commercial SEC (using plasma), and 10 times higher yield than UC. Overall, ExoArc provides an easy-to-use, compact, and efficient method to isolate EVs, which can be readily automated for point-of-care application such as clinical diagnostics or process control of EVs manufacturing.