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 pre...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-05-01
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| Series: | Journal of Nanobiotechnology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12951-023-01917-z |
| _version_ | 1797822710000123904 |
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| author | Sofie Van Dorpe Lien Lippens Robin Boiy Cláudio Pinheiro Glenn Vergauwen Pekka Rappu Ilkka Miinalainen Philippe Tummers Hannelore Denys Olivier De Wever An Hendrix |
| author_facet | Sofie Van Dorpe Lien Lippens Robin Boiy Cláudio Pinheiro Glenn Vergauwen Pekka Rappu Ilkka Miinalainen Philippe Tummers Hannelore Denys Olivier De Wever An Hendrix |
| author_sort | Sofie Van Dorpe |
| collection | DOAJ |
| description | 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. Graphical Abstract |
| first_indexed | 2024-03-13T10:13:09Z |
| format | Article |
| id | doaj.art-fcf7955af27c4c0abe67e5929d4b42eb |
| institution | Directory Open Access Journal |
| issn | 1477-3155 |
| language | English |
| last_indexed | 2024-03-13T10:13:09Z |
| publishDate | 2023-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Nanobiotechnology |
| spelling | doaj.art-fcf7955af27c4c0abe67e5929d4b42eb2023-05-21T11:26:14ZengBMCJournal of Nanobiotechnology1477-31552023-05-0121111610.1186/s12951-023-01917-zIntegrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibilitySofie Van Dorpe0Lien Lippens1Robin Boiy2Cláudio Pinheiro3Glenn Vergauwen4Pekka Rappu5Ilkka Miinalainen6Philippe Tummers7Hannelore Denys8Olivier De Wever9An Hendrix10Laboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityDepartment of Life Technologies, University of TurkuBiocenter Oulu, University of OuluCancer Research Institute GhentCancer Research Institute GhentLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityLaboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent UniversityAbstract 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. Graphical Abstracthttps://doi.org/10.1186/s12951-023-01917-zExtracellular vesiclesSeparationDensity gradient centrifugationBloodUrineAutomation |
| spellingShingle | Sofie Van Dorpe Lien Lippens Robin Boiy Cláudio Pinheiro Glenn Vergauwen Pekka Rappu Ilkka Miinalainen Philippe Tummers Hannelore Denys Olivier De Wever An Hendrix Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility Journal of Nanobiotechnology Extracellular vesicles Separation Density gradient centrifugation Blood Urine Automation |
| title | Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| title_full | Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| title_fullStr | Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| title_full_unstemmed | Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| title_short | Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| title_sort | integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility |
| topic | Extracellular vesicles Separation Density gradient centrifugation Blood Urine Automation |
| url | https://doi.org/10.1186/s12951-023-01917-z |
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