Dataset Information

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

ABSTRACT:

Background

Extracellular vesicles (EV) are extensively studied in human body fluids as potential biomarkers for numerous diseases. Major impediments of EV-based biomarker discovery include the specificity and reproducibility of EV sample preparation as well as intensive manual labor. We present an automated liquid handling workstation for the density-based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers.

Results

Automated versus manual density-based separation of trackable recombinant extracellular vesicles (rEV) spiked in PBS significantly reduces variability in rEV recovery as quantified by fluorescent nanoparticle tracking analysis and ELISA. To validate automated density-based EV separation from complex body fluids, including blood plasma and urine, we assess reproducibility, recovery, and specificity by mass spectrometry-based proteomics and transmission electron microscopy. Method reproducibility is the highest in the automated procedure independent of the matrix used. While retaining (in urine) or enhancing (in plasma) EV recovery compared to manual liquid handling, automation significantly reduces the presence of body fluid specific abundant proteins in EV preparations, including apolipoproteins in plasma and Tamm-Horsfall protein in urine.

Conclusions

In conclusion, automated liquid handling ensures cost-effective EV separation from human body fluids with high reproducibility, specificity, and reduced hands-on time with the potential to enable larger-scale biomarker studies.

SUBMITTER: Van Dorpe S

PROVIDER: S-EPMC10197845 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

Van Dorpe Sofie S Lippens Lien L Boiy Robin R Pinheiro Cláudio C Vergauwen Glenn G Rappu Pekka P Miinalainen Ilkka I Tummers Philippe P Denys Hannelore H De Wever Olivier O Hendrix An A

Journal of nanobiotechnology 20230519 1

<h4>Background</h4>Extracellular vesicles (EV) are extensively studied in human body fluids as potential biomarkers for numerous diseases. Major impediments of EV-based biomarker discovery include the specificity and reproducibility of EV sample preparation as well as intensive manual labor. We present an automated liquid handling workstation for the density-based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers.<h4>Results</h4 ...[more]

PMID: 37208684

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Dataset Information

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

Background

Results

Conclusions

Publications

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

Similar Datasets

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