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BiochemistrybioRxiv
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Enhanced Workflow for Urinary Extracellular Vesicle Isolation Using Membrane-Sensing Peptides

Roberto FrigerioiD, Adele TanziiD, Angelo MusicòiD, Cristina GrangeiD, Paola GagniiD, Vincenza DoloiD, Ilaria GiustiiD, Paolo ArosioiD, Alessandro GoriiD, Benedetta BussolatiiD

Abstract

Urinary extracellular vesicles (uEVs) represent a promising source of non-invasive biomarkers; however, their clinical translation is still limited by suboptimal isolation strategies, which often suffer from poor scalability, co-isolation of abundant urinary proteins, and bias toward specific EV subpopulations. Here, we employ a membrane-sensing peptide (MSP)-based affinity approach for uEVs isolation, that exploits the highly lipid membranes curvature of EV as universal target, enabling pan-specific capture independent of surface marker expression. MSP-functionalized beads were applied to minimally processed urine samples and benchmarked against differential ultracentrifugation (dUC) and size-exclusion chromatography (SEC). Comprehensive characterization by nanoparticle tracking analysis, transmission electron microscopy, high-sensitivity flow cytometry, single-molecule array (SiMoA), and fluorescence nanoparticle tracking analysis, demonstrated that MSP-based isolation preserves vesicle integrity and maintains the native distribution of canonical tetraspanins (CD9, CD63, CD81), without evidence of subpopulation bias. Notably, MSP-based isolation significantly reduced co-isolated contaminants, such as uromodulin, resulting in improved sample purity. By combining high recovery, improved purity, and operational simplicity, MSP workflow offers practical advantages, including reduced processing time, scalability, and compatibility with standard laboratory equipment, without the need for extensive pre-processing. These properties characterize MSP-based affinity capture as a robust and versatile alternative to conventional uEVs isolation approaches, with strong potential for translational and clinical applications.

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02 /Specification & Classification

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