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Protein Corona Modulates Extracellular Vesicle Recognition at Glycan-Based Nanobiointerfaces
Tomas Bertok1, Eduard Jane1, Veronika Solovicova1
1Institute of Chemistry, Slovak Academy of Sciences, Dubravska cesta 9, 845 38 Bratislava, Slovak Republic.
This study engineered nanobiointerfaces to characterize extracellular vesicles (EVs). Removing protein coronas and using glycan surfaces revealed distinct binding behaviors between cancer and normal EVs, aiding liquid biopsy development.
Area of Science:
- Biomaterials Science
- Nanotechnology
- Extracellular Vesicle Biology
Background:
- Precise surface engineering is crucial for characterizing extracellular vesicles (EVs) and their biological interactions.
- Gold substrates modified with self-assembled monolayers (SAMs) and gold nanoparticles (AuNPs) enhance surface area and functionality for nanostructure assembly.
Purpose of the Study:
- To develop and characterize novel glycan-based nanobiointerfaces for studying extracellular vesicle (EV) interactions.
- To investigate the impact of protein corona removal on EV surface marker accessibility and recognition.
- To differentiate malignant and non-malignant EVs based on their binding behavior to glycan interfaces.
Main Methods:
- Fabrication of gold substrates with C6 SAMs, AuNPs, and layer-by-layer assembly of glycan nanostructures.
- Electrochemical methods and atomic force microscopy (AFM) for interface monitoring.
- Affinity isolation, preconcentration, and protein corona removal of EVs (MDA-MB-231 and RWPE-1).
- ELISA for evaluating antibody-mediated recognition post-corona removal.
- Surface Plasmon Resonance (SPR) with a physics-informed neural network for analyzing EV-glycan interactions.
Main Results:
- Optimized SAMs and AuNP deposition created robust nanobiointerfaces.
- Protein corona removal significantly improved EV surface marker accessibility for antibody recognition.
- SPR analysis revealed distinct binding phenotypes of malignant EVs compared to non-malignant EVs on glycan surfaces.
- The physics-informed neural network model effectively reduced bulk refractive index interference in SPR data.
Conclusions:
- Glycan-based nanobiointerfaces enable sensitive characterization of EV binding.
- Protein corona composition and glycan interactions are critical factors in EV recognition.
- These findings support the potential of glycan-based nanobiointerfaces for advancing extracellular vesicle research and liquid biopsy development.
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