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Related Experiment Video

Updated: Mar 21, 2026

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Optimised untargeted metabolomics workflow for human urinary extracellular vesicles.

Cahyani Gita Ambarsari1,2,3, Sandra Martinez-Jarquin4, Jasper J R Koh1,5

  • 1School of Pharmacy, Biodiscovery Institute, University of Nottingham, University Park Campus, East Drive, Nottingham NG7 2RD, UK. anna.piccinini@nottingham.ac.uk.

Analytical Methods : Advancing Methods and Applications
|March 20, 2026
PubMed
Summary
This summary is machine-generated.

Optimizing urinary extracellular vesicle (uEV) isolation and metabolite extraction is crucial for biomarker discovery. A pH-adjustment with resin separation method for uEV isolation combined with the Liu et al. extraction protocol offers the most robust metabolomics analysis.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Biomarker Discovery

Background:

  • Extracellular vesicles (EVs), particularly urinary EVs (uEVs), are vital for understanding urogenital tract health and disease.
  • Current uEV metabolomics research is hindered by inconsistent isolation and extraction methods, leading to variability.
  • Standardized protocols are needed to unlock the full potential of uEVs in biomarker discovery.

Purpose of the Study:

  • To systematically evaluate and optimize experimental conditions for untargeted metabolite profiling of human uEVs.
  • To compare different EV isolation techniques and metabolite extraction protocols for improved uEV cargo analysis.
  • To establish a validated workflow for robust metabolomics analysis of human uEVs.

Main Methods:

  • Compared three urinary EV isolation methods: precipitation, size-exclusion chromatography, and pH-adjustment with resin separation.
  • Evaluated two established and one in-house metabolite extraction protocols.
  • Utilized particle counting, nanoparticle tracking analysis, and transmission electron microscopy for characterization.
  • Performed untargeted metabolomics analysis to assess metabolite coverage and yield.

Main Results:

  • The pH-adjustment with resin separation method yielded the highest number of small EVs (30-150 nm) and broadest metabolite coverage.
  • The Liu et al. metabolite extraction protocol identified the highest number of metabolites.
  • The combined approach of pH-adjustment/resin separation for isolation and Liu et al. for extraction proved optimal for uEV metabolomics.

Conclusions:

  • A validated workflow combining specific uEV isolation and metabolite extraction methods enhances metabolomics analysis.
  • This optimized approach improves EV purity, reduces contamination, and maximizes metabolite yield.
  • The findings support the development of standardized protocols for reliable EV-based biomarker discovery.