Dataset Information

Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.

ABSTRACT: The heterogeneity of exosomal populations has hindered our understanding of their biogenesis, molecular composition, biodistribution and functions. By employing asymmetric flow field-flow fractionation (AF4), we identified two exosome subpopulations (large exosome vesicles, Exo-L, 90-120?nm; small exosome vesicles, Exo-S, 60-80?nm) and discovered an abundant population of non-membranous nanoparticles termed 'exomeres' (~35?nm). Exomere proteomic profiling revealed an enrichment in metabolic enzymes and hypoxia, microtubule and coagulation proteins as well as specific pathways, such as glycolysis and mTOR signalling. Exo-S and Exo-L contained proteins involved in endosomal function and secretion pathways, and mitotic spindle and IL-2/STAT5 signalling pathways, respectively. Exo-S, Exo-L and exomeres each had unique N-glycosylation, protein, lipid, DNA and RNA profiles and biophysical properties. These three nanoparticle subsets demonstrated diverse organ biodistribution patterns, suggesting distinct biological functions. This study demonstrates that AF4 can serve as an improved analytical tool for isolating extracellular vesicles and addressing the complexities of heterogeneous nanoparticle subpopulations.

SUBMITTER: Zhang H

PROVIDER: S-EPMC5931706 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.

Zhang Haiying H Freitas Daniela D Kim Han Sang HS Fabijanic Kristina K Li Zhong Z Chen Haiyan H Mark Milica Tesic MT Molina Henrik H Martin Alberto Benito AB Bojmar Linda L Fang Justin J Rampersaud Sham S Hoshino Ayuko A Matei Irina I Kenific Candia M CM Nakajima Miho M Mutvei Anders Peter AP Sansone Pasquale P Buehring Weston W Wang Huajuan H Jimenez Juan Pablo JP Cohen-Gould Leona L Paknejad Navid N Brendel Matthew M Manova-Todorova Katia K Magalhães Ana A Ferreira José Alexandre JA Osório Hugo H Silva André M AM Massey Ashish A Cubillos-Ruiz Juan R JR Galletti Giuseppe G Giannakakou Paraskevi P Cuervo Ana Maria AM Blenis John J Schwartz Robert R Brady Mary Sue MS Peinado Héctor H Bromberg Jacqueline J Matsui Hiroshi H Reis Celso A CA Lyden David D

Nature cell biology 20180219 3

The heterogeneity of exosomal populations has hindered our understanding of their biogenesis, molecular composition, biodistribution and functions. By employing asymmetric flow field-flow fractionation (AF4), we identified two exosome subpopulations (large exosome vesicles, Exo-L, 90-120 nm; small exosome vesicles, Exo-S, 60-80 nm) and discovered an abundant population of non-membranous nanoparticles termed 'exomeres' (~35 nm). Exomere proteomic profiling revealed an enrichment in metabolic enzy ...[more]

PMID: 29459780

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Project description:Particle size distribution and stability are key attributes for the evaluation of the safety and efficacy profile of medical nanoparticles (Med-NPs). Measuring particle average size and particle size distribution is a challenging task which requires the combination of orthogonal high-resolution sizing techniques, especially in complex biological media. Unfortunately, despite its limitations, due to its accessibility, low cost, and easy handling, batch mode dynamic light scattering (DLS) is still very often used as the only approach to measure particle size distribution in the nanomedicine field. In this work the use of asymmetric flow field flow fractionation coupled to multiangle light scattering and dynamic light scattering detectors (AF4-MALS-DLS) was evaluated as an alternative to batch mode DLS to measure the physical properties of lipid-based nanoparticles. A robust standard operating procedure (SOPs) developed by the Nanomedicine Characterization Laboratory (EUNCL) was presented and tested to assess size stability, batch to batch consistency, and the behavior of the lipid-based nanoparticles in plasma. Orthogonal sizing techniques, such as transmission electron microscopy (TEM) and particle tracking analysis (PTA) measurements, were performed to support the results. While batch mode DLS could be applied as a fast and simple method to provide a preliminary insight into the integrity and polydispersity of samples, it was unsuitable to resolve small modifications of the particle size distribution. The introduction of nanoparticle sorting by field-flow fractionation coupled to online DLS and MALS allowed assessment of batch to batch variability and changes in the size of the lipid nanoparticles induced by the interaction with serum proteins, which are critical for quality control and regulatory aspects. In conclusion, if a robust SOP is followed, AF4-MALS-DLS is a powerful method for the preclinical characterization of lipid-based nanoparticles.

Dataset Information

Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.

Publications

Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.

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