Multifunctional Detection of Extracellular Vesicles with Surface Plasmon Resonance Microscopy

Area of Science:

• Biotechnology
• Nanotechnology
• Biomedical Engineering

Background:

• Extracellular vesicles (EVs), including exosomes, are crucial circulating biomarkers for disease diagnosis.
• Current methods for EV analysis are complex, requiring multiple instruments and limiting widespread application.
• Phenotypic characterization of EVs is essential for understanding their role in disease.

Purpose of the Study:

• To develop a multifunctional plasmonic biosensor for comprehensive EV analysis.
• To enable single-particle level capture, imaging, and characterization of EVs.
• To overcome the limitations of conventional EV analysis techniques.

Main Methods:

• A functionalized surface plasmon resonance (SPR) biosensor combined with advanced plasmonic microscopy was utilized.
• A deep learning algorithm was developed for automated EV identification and intensity quantification from SPR images.
• Immunosensing and single-particle analysis were integrated for physical and chemical characterization.

Main Results:

• The technology successfully captured and imaged EVs at the single-particle level.
• Deep learning enabled automated identification and quantification of EVs.
• Proof-of-concept analysis of EVs from human lung cancer cell lines demonstrated detection of size, concentration, and affinity constants.

Conclusions:

• The developed plasmonic biosensor offers multifunctional analysis of EVs with single-particle resolution.
• This technology provides a powerful tool for both physical and chemical characterization of EVs.
• The system holds significant potential for clinical diagnostics and scientific research applications.