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  • Title: Isolation of anti-extra-cellular vesicle single-domain antibodies by direct panning on vesicle-enriched fractions.
    Author: Popovic M, Mazzega E, Toffoletto B, de Marco A.
    Journal: Microb Cell Fact; 2018 Jan 13; 17(1):6. PubMed ID: 29331148.
    Abstract:
    BACKGROUND: The thorough understanding of the physiological and pathological processes mediated by extracellular vesicles (EVs) is challenged by purification methods which are cumbersome, not reproducible, or insufficient to yield homogeneous material. Chromatography based on both ion-exchange and immune-capture can represent an effective method to improve EV purification and successive analysis. METHODS: Cell culture supernatant was used as a model sample for assessing the capacity of anion-exchange chromatography to separate distinct EV fractions and to isolate nanobodies by direct panning on whole EVs to recover binders specific for the native conformation of EV-surface epitopes and suitable to develop EV immune-capture reagents. RESULTS: Anion-exchange chromatography of cell culture supernatant separated distinct protein-containing fractions and all of them were positive for CD9, a biomarker associated to some EVs. This suggested the existence of several EV fractions but did not help in separating EVs from other contaminants. We further isolated several nanobodies instrumental for implementing immune-affinity protocols. These were able to immobilize EVs from both cell culture supernatant and biological samples, to be used in ELISA, flow-cytometry, and immune-purification. CONCLUSIONS: Here we report the first successful isolation of anti-EV nanobodies for the use in immunoaffinity-based EV capture by panning a phage library directly on partially purified EVs. This achievement paves the way for the application of direct EV panning for the discovery of novel antibody-vesicle surface biomarker pairs and represents the preliminary requirement for the development of selective immune-capture that, in combination with anion-exchange chromatography, can simplify the systematic stratification of EV sub-populations and their individual characterization.
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