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Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
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Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets

Published on: March 17, 2023

Integrated Multiomics Enabled by Sequential Extraction for Comprehensive Molecular Profiling of Small Extracellular

Andrew J Perciaccante1,2, Holden T Rogers1,2, Yanlong Zhu2,3

  • 1Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.

Analytical Chemistry
|June 22, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a mass spectrometry multiomics platform for analyzing small extracellular vesicles (sEVs). The method enables deep characterization of proteins, lipids, and metabolites from limited sEV samples for biomarker discovery.

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Extraction of Extracellular Vesicles from Whole Tissue
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Published on: February 7, 2019

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Last Updated: Jun 24, 2026

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
06:12

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets

Published on: March 17, 2023

Extraction of Extracellular Vesicles from Whole Tissue
09:03

Extraction of Extracellular Vesicles from Whole Tissue

Published on: February 7, 2019

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Biotechnology

Background:

  • Small extracellular vesicles (sEVs) contain biomarkers reflecting their cell of origin.
  • Characterizing sEVs is difficult due to limited sample material.
  • Existing methods struggle with comprehensive molecular profiling of sEVs.

Purpose of the Study:

  • To develop an integrated multiomics platform for simultaneous protein, lipid, and metabolite analysis from single sEV samples.
  • To maximize sample utilization and enhance analytical depth for low-input sEV analysis.
  • To establish a robust foundation for sEV biomarker discovery and therapeutic applications.

Main Methods:

  • An integrated mass spectrometry-based multiomics platform utilizing sequential extraction.
  • Iterative tandem mass spectrometry for enhanced small-molecule fragmentation.
  • Nanoflow proteomics with data-independent acquisition for deep molecular coverage.

Main Results:

  • Achieved deep and reproducible multiomic characterization of proteins, lipids, and metabolites from 10 million sEVs.
  • Demonstrated platform compatibility with sEVs isolated by ultracentrifugation, SEC-UF, and polymer precipitation.
  • Revealed purification-dependent molecular profile differences linked to yield-purity trade-offs.

Conclusions:

  • The integrated multiomics platform addresses a key challenge in low-input sEV analysis.
  • This strategy enables synergistic biomarker discovery and therapeutic development using sEVs.
  • The platform provides a robust analytical foundation for advancing sEV research.