This study develops a VISTA technology based on single-molecule confocal microscopy, enabling high-sensitivity and high-specificity detection of extracellular vesicles (EVs) without purification steps, directly analyzing them in biofluids. This method surpasses traditional techniques in detection limit and specificity, offering significant translational potential.
Literature Overview
This paper titled 'Fluorescence Characterization of Extracellular Vesicles Using Single-Molecule Confocal Microscopy', published in Small Methods, reviews and summarizes research on high-sensitivity, high-specificity detection of extracellular vesicles (EVs) using VISTA technology. It demonstrates the technique's accurate identification and quantification of EVs in complex biological samples, avoiding measurement biases caused by interfering particles in traditional methods. The text is coherent and logically structured with appropriate Chinese punctuation.
Background Knowledge
Extracellular vesicles (EVs) are small membrane-encapsulated particles secreted by cells that play critical roles in intercellular communication. They have recently gained significant attention as disease biomarkers. However, challenges arise in traditional detection methods due to EVs' low abundance and high heterogeneity. Current nanoparticle tracking analysis (NTA) relies on light scattering with low specificity, failing to distinguish EVs from similar particles like lipoproteins. Although methods like nano-flow cytometry offer specificity, they require expensive equipment and complex operations. VISTA technology combines dual fluorescently labeled antibodies with high-speed microfluidic chips, achieving high-sensitivity EV detection through single-molecule confocal microscopy. This approach effectively overcomes limitations of existing methods, holding significant value for biomarker research and disease diagnostics. It particularly enables direct analysis of serum and plasma samples without additional purification steps, reducing sample loss and improving detection efficiency. The study further compares recovery efficiency across different EV isolation methods, providing optimized strategies for EV analysis.
Research Methods and Experiments
The research team employed two fluorescently labeled antibodies (AF488 and AF647) targeting EV-specific surface marker CD9, combined with high-speed microfluidic chips and single-molecule confocal microscopy to achieve dual-color co-localization detection of EVs. This method relies on multiple CD9 molecules on EV surfaces binding multiple antibodies, whereas single antibodies or non-EV particles only exhibit singular fluorescence signals. Co-localized fluorescence signals enabled high-specificity EV identification.
Key Conclusions and Perspectives
Research Significance and Prospects
VISTA provides a high-sensitivity, high-specificity solution for EV research, applicable to fundamental studies and clinical diagnostics. Future developments could expand detection targets to other EV surface markers (e.g., CD63, CD81, PSMA), enhancing subpopulation identification. Additionally, VISTA's automation and standardization potential offer broad applications in liquid biopsy, disease biomarker screening, and drug delivery research.
Conclusion
VISTA technology presents an innovative and efficient strategy for EV detection and quantification. By integrating dual-color co-localization detection with high-speed microfluidic chips, it achieves high-sensitivity and high-specificity identification in complex biological samples. Compared to traditional methods, VISTA requires no purification steps, supports direct serum/plasma analysis, and reduces sample loss while improving measurement accuracy. The study also demonstrates broad applicability across multiple EV surface markers, showing excellent scalability and application flexibility. Future standardization of VISTA could establish it as a benchmark tool for EV research, advancing liquid biopsy and precision medicine while providing critical platform support for disease biomarker discovery and drug delivery system development.
