TY - JOUR T1 - Classification of Extracellular Vesicles based on Surface Glycan Structures by Spongy-like Separation Media JF - bioRxiv DO - 10.1101/2022.05.10.491426 SP - 2022.05.10.491426 AU - Eisuke Kanao AU - Shuntaro Wada AU - Hiroshi Nishida AU - Takuya Kubo AU - Tetsuya Tanigawa AU - Koshi Imami AU - Asako Shimoda AU - Kaori Umezaki AU - Yoshihiro Sasaki AU - Kazunari Akiyoshi AU - Jun Adachi AU - Koji Otsuka AU - Yasushi Ishihama Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/05/11/2022.05.10.491426.abstract N2 - 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.Competing Interest StatementThe authors have declared no competing interest. ER -