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Related Experiment Video

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Single Extracellular Vesicle Transmembrane Protein Characterization by Nano-Flow Cytometry
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Identifying extracellular vesicle populations from single cells.

Jonas M Nikoloff1, Mario A Saucedo-Espinosa1, André Kling1

  • 1Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zürich, 4058 Basel, Switzerland.

Proceedings of the National Academy of Sciences of the United States of America
|September 14, 2021
PubMed
Summary

Researchers developed a microfluidic platform to capture and classify single-cell extracellular vesicles (EVs). This technology reveals diverse EV phenotypes and their secretion patterns, offering insights into cell signaling and disease.

Keywords:
extracellular vesiclesmicrofluidicssingle-cell analysis

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Area of Science:

  • Cell Biology
  • Biotechnology
  • Nanotechnology

Background:

  • Extracellular vesicles (EVs), including exosomes, are released by cells and play roles in cell signaling and disease.
  • Understanding EV heterogeneity at the single-cell level is crucial but challenging.

Purpose of the Study:

  • To introduce a novel microfluidic platform for capturing, quantifying, and phenotypically classifying EVs secreted from individual cells.
  • To analyze the heterogeneity of EV phenotypes at the single-cell level.

Main Methods:

  • Utilizing microfluidic chambers (300 pL) to isolate single cells.
  • Capturing secreted EVs using surface-immobilized monoclonal antibodies (mAbs).
  • Employing multicolor total internal reflection fluorescence microscopy and immunostaining for phenotypic characterization.

Main Results:

  • The platform enabled the classification of EVs into 15 unique populations, demonstrating high phenotypic heterogeneity even from single cells.
  • Different mAbs isolated distinct EV populations, with CD63 showing higher immobilization efficiency than CD81.
  • Inhibition of neutral sphingomyelinase led to heterogeneous suppression of secreted EVs.

Conclusions:

  • The developed platform provides a powerful tool for dissecting single-cell EV heterogeneity.
  • EVs exhibit diverse phenotypes, and their secretion can be modulated by specific molecular targets.
  • This technology has implications for understanding cell communication and disease mechanisms involving EVs.