Van Dorpe, S., Lippens, L., Boiy, R. et al. Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility. J Nanobiotechnol 21, 157 (2023). https://doi.org/10.1186/s12951-023-01917-z
Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility
|Author:||Van Dorpe, Sofie1,2,3; Lippens, Lien1,2; Boiy, Robin1,2;|
1Laboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent, Ghent, Belgium
3Department of Gynecology, Ghent University Hospital, Ghent, Belgium
4Department of Life Technologies, University of Turku, Turku, Finland
5Biocenter Oulu, University of Oulu, Oulu, Finland
6Department of Medical Oncology, Ghent University Hospital, Ghent, Belgium
|Online Access:||PDF Full Text (PDF, 8.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe20230921135023
|Publish Date:|| 2023-09-21
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.
Journal of nanobiotechnology
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
1182 Biochemistry, cell and molecular biology
This work was supported by a project grant and starting PhD fellowship (SVD) from Stand up to Cancer (Kom Op Tegen Kanker), the Flemish cancer society; and a project grant and PhD fellowship (SVD) from Fund for Scientific Research Flanders (FWO).
© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.