Classification of Extracellular Vesicles based on Surface Glycan Structures by Spongy-like Separation Media

Abstract

Extracellular vesicles (EVs) are lipid bilayer vesicles that enclose various biomolecules. EVs hold promise as sensitive biomarkers to detect and monitor various diseases. However, they have heterogenous molecular compositions. The compositions of EVs from identical donor cells obtained using the same purification methods may differ, which is a significant obstacle for elucidating objective biological functions. Herein the potential of a novel lectin-based affinity chromatography (LAC) method to classify EVs based on their glycan structures is demonstrated. The proposed method utilizes a spongy-like monolithic polymer (spongy monolith, SPM), which consists of poly(ethylene-co-glycidyl methacrylate) with continuous micropores and allows an efficient in-situ protein reaction with epoxy groups. Two distinct lectins with different specificities, Sambucus sieboldiana agglutinin and concanavalin A, are effectively immobilized on SPM without impacting the binding activity. Moreover, high recovery rates of liposomal nanoparticles as a model of EVs are achieved due to the large flow-through pores (>10 μm) of SPM. Finally, lectin-immobilized SPMs are employed to classify EVs based on the surface glycan structures and demonstrate different subpopulations by proteome profiling.