Membrane-binding peptides for extracellular vesicles on-chip analysis. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Gori, Alessandro; Romanato, Alessandro; Bergamaschi, Greta; Strada, Alessandro; Gagni, Paola; Frigerio, Roberto; Brambilla, Dario; Vago, Riccardo; Galbiati, Silvia; Picciolini, Silvia; Bedoni, Marzia; Daaboul, George G.; Chiari, Marcella; Cretich, Marina
• Is Part Of: Journal of extracellular vesicles. Volume 9:Issue 1(2020)
• Publication Date: 2020-01-01
• Subjects: Extracellular vesicles -- peptides -- microarrays -- membrane binding -- membrane curvature; Cells -- Mechanical properties -- Periodicals; Transport Vesicles; Cells -- Mechanical properties; Periodicals; Fulltext; Internet Resources; Periodicals; Electronic journals; Periodicals; 571.63
• DOI: 10.1080/20013078.2020.1751428
• Languages: English
• ISSNs: 2001-3078

Abstract

ABSTRACT: Small extracellular vesicles (sEVs) present fairly distinctive lipid membrane features in the extracellular environment. These include high curvature, lipid-packing defects and a relative abundance in lipids such as phosphatidylserine and ceramide. sEV membrane could be then considered as a "universal" marker, alternative or complementary to traditional, characteristic, surface-associated proteins. Here, we introduce the use of membrane-sensing peptides as new, highly efficient ligands to directly integrate sEV capturing and analysis on a microarray platform. Samples were analysed by label-free, single-particle counting and sizing, and by fluorescence co-localisation immune staining with fluorescent anti-CD9/anti-CD63/anti-CD81 antibodies. Peptides performed as selective yet general sEV baits and showed a binding capacity higher than anti-tetraspanins antibodies. Insights into surface chemistry for optimal peptide performances are also discussed, as capturing efficiency is strictly bound to probes surface orientation effects. We anticipate that this new class of ligands, also due to the versatility and limited costs of synthetic peptides, may greatly enrich the molecular toolbox for EV analysis.