Asako Shimoda

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 heterogeneous 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 mu m) of SPM compared to a typical agarose gel. Finally, lectin-immobilized SPMs are employed to classify EVs based on the surface glycan structures and demonstrate different subpopulations by proteome profiling. This is the first approach to clarify the variation of protein contents in EVs by the difference of surface glycans via lectin immobilized media.

Automated summary

Extracellular vesicles (EVs) are lipid bilayer vesicles enclosing various biomolecules, showing potential as sensitive biomarkers for disease detection. A novel lectin-based affinity chromatography method is demonstrated to classify EVs based on their glycan structures, utilizing a spongy-like monolithic polymer that allows efficient in situ protein reaction. This approach helps to overcome the obstacle of differing molecular compositions of EVs from same donor cells, showing promise for elucidating their biological functions objectively.