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Nanostructured Affinity Membrane to Isolate Extracellular Vesicles from Body Fluids for Diagnostics and Regenerative
Monica Torsello1, Margherita Animini1, Chiara Gualandi1,2
1Department of Chemistry "G. Ciamician" and INSTM (National Interuniversity Consortium of Materials Science and Technology) UdR of Bologna, University of Bologna, Via Selmi 2, 40126 Bologna, Italy.
Membranes
|October 25, 2024
Summary
Researchers developed novel regenerated cellulose (RC) nanofiber membranes for extracellular vesicle (EV) isolation. These affinity membranes show high binding capacity, offering a promising approach for EV capture from biological samples.
Area of Science:
- Materials Science
- Biotechnology
- Nanotechnology
Background:
- Extracellular vesicles (EVs) are crucial biomarkers for disease diagnostics.
- Efficient and selective methods for EV isolation are needed for clinical applications.
- Regenerated cellulose (RC) offers a versatile platform for biomaterial development.
Purpose of the Study:
- To fabricate electrospun regenerated cellulose (RC) nanofiber membranes for EV capture.
- To functionalize RC membranes with anti-CD63 antibodies for targeted EV isolation.
- To evaluate the binding capacity of the affinity membranes for EVs.
Main Methods:
- Preparation of cellulose acetate (CA) electrospun membranes.
- Heat treatment and deacetylation to form RC membranes.
- Epoxy functionalization and bioconjugation with anti-CD63 antibody.
- EV adsorption experiments using human platelet lysate.
Main Results:
- Optimized electrospinning yielded uniform CA fibers, forming robust RC membranes after processing.
- Maximal anti-CD63 antibody density achieved at 6.4 µg/mL in carbonate buffer.
- The affinity membranes demonstrated high EV binding capacity exceeding 10 mg/mL.
Conclusions:
- Electrospun RC nanofiber membranes can be effectively functionalized for specific biomolecule capture.
- The anti-CD63 functionalized membranes show significant potential for extracellular vesicle isolation.
- This approach provides a promising strategy for developing advanced affinity-based separation technologies.
