Using single-vesicle technologies to unravel the heterogeneity of extracellular vesicles

Guillermo Bordanaba-Florit, Félix Royo, Sergei G. Kruglik, Juan M. Falcón-Pérez

Published: 2021-06-15 DOI: 10.1038/s41596-021-00551-z

Extracellular Vesicles

Single-Vesicle Analysis

Heterogeneity

Microfluidic Devices

Disease Biomarkers

AI 解读

Fabrication of angstrom-scale two-dimensional channels for mass transport

Efficient and strand-specific profiling of replicating chromatin with enrichment and sequencing of protein-associated nascent DNA in mammalian cells

The eINTACT method for studying nuclear changes in host plant cells targeted by bacterial effectors in native infection contexts

Rapid reaction optimization by robust and economical quantitative benchtop19F NMR spectroscopy

Profiling native pulmonary basement membrane stiffness using atomic force microscopy

Photoimmunotechnology as a powerful biological tool for molecular-based elimination of target cells and microbes, including bacteria, fungi and viruses

Measuring key human carbohydrate digestive enzyme activities using high-performance anion-exchange chromatography with pulsed amperometric detection

Neural cell isolation from adult macaques for high-throughput analyses and neurosphere cultures

Preparation, validation and use of a vasoactive tryptophan-derived hydroperoxide and relevant control compounds

Neuronal subtype-specific growth cone and soma purification from mammalian CNS via fractionation and fluorescent sorting for subcellular analyses and spatial mapping of local transcriptomes and proteomes

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Sections

Figures

References

Extracellular vesicles (EVs) are heterogeneous lipid containers with a complex molecular cargo comprising several populations with unique roles in biological processes. These vesicles are closely associated with specific physiological features, which make
Main
- EV heterogeneity and biomarker discovery
- SVA techniques for biological characterization of EVs
Single-vesicle techniques
- Label-free methodologies
- Label-based methodologies
Recent advances in the EV field due to SVA
Future outlook
Concluding remarks
References
ACKNOWLEDGMENTS

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