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

      , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,   ,
      Nature Cell Biology
      Springer Nature

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          Abstract

          <p class="first" id="P1">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 and specific pathways, such as glycolysis and mTOR signaling. Exo-S and Exo-L contained proteins involved in endosomal function and secretion pathways, and mitotic spindle and IL-2/STAT5 signaling pathways, respectively. Exo-S, Exo-L, and exomeres each had unique <i>N</i>-glycosylation, protein, lipid, and 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 and addressing the complexities of heterogeneous nanoparticle subpopulations. </p>

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          Most cited references28

          • Record: found
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          Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring

          T. Golub (1999)
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            Comparison of ultracentrifugation, density gradient separation, and immunoaffinity capture methods for isolating human colon cancer cell line LIM1863-derived exosomes.

            Exosomes are 40-100nm extracellular vesicles that are released from a multitude of cell types, and perform diverse cellular functions including intercellular communication, antigen presentation, and transfer of oncogenic proteins as well as mRNA and miRNA. Exosomes have been purified from biological fluids and in vitro cell cultures using a variety of strategies and techniques. However, all preparations invariably contain varying proportions of other membranous vesicles that co-purify with exosomes such as shed microvesicles and apoptotic blebs. Using the colorectal cancer cell line LIM1863 as a cell model, in this study we performed a comprehensive evaluation of current methods used for exosome isolation including ultracentrifugation (UC-Exos), OptiPrep™ density-based separation (DG-Exos), and immunoaffinity capture using anti-EpCAM coated magnetic beads (IAC-Exos). Notably, all isolations contained 40-100nm vesicles, and were positive for exosome markers (Alix, TSG101, HSP70) based on electron microscopy and Western blotting. We employed a proteomic approach to profile the protein composition of exosomes, and label-free spectral counting to evaluate the effectiveness of each method. Based on the number of MS/MS spectra identified for exosome markers and proteins associated with their biogenesis, trafficking, and release, we found IAC-Exos to be the most effective method to isolate exosomes. For example, Alix, TSG101, CD9 and CD81 were significantly higher (at least 2-fold) in IAC-Exos, compared to UG-Exos and DG-Exos. Application of immunoaffinity capture has enabled the identification of proteins including the ESCRT-III component VPS32C/CHMP4C, and the SNARE synaptobrevin 2 (VAMP2) in exosomes for the first time. Additionally, several cancer-related proteins were identified in IAC-Exos including various ephrins (EFNB1, EFNB2) and Eph receptors (EPHA2-8, EPHB1-4), and components involved in Wnt (CTNNB1, TNIK) and Ras (CRK, GRB2) signalling. Copyright © 2012 Elsevier Inc. All rights reserved.
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              GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans.

              Mass spectrometry is the main analytical technique currently used to address the challenges of glycomics as it offers unrivalled levels of sensitivity and the ability to handle complex mixtures of different glycan variations. Determination of glycan structures from analysis of MS data is a major bottleneck in high-throughput glycomics projects, and robust solutions to this problem are of critical importance. However, all the approaches currently available have inherent restrictions to the type of glycans they can identify, and none of them have proved to be a definitive tool for glycomics. GlycoWorkbench is a software tool developed by the EUROCarbDB initiative to assist the manual interpretation of MS data. The main task of GlycoWorkbench is to evaluate a set of structures proposed by the user by matching the corresponding theoretical list of fragment masses against the list of peaks derived from the spectrum. The tool provides an easy to use graphical interface, a comprehensive and increasing set of structural constituents, an exhaustive collection of fragmentation types, and a broad list of annotation options. The aim of GlycoWorkbench is to offer complete support for the routine interpretation of MS data. The software is available for download from: http://www.eurocarbdb.org/applications/ms-tools.
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                Author and article information

                Journal
                Nature Cell Biology
                Nat Cell Biol
                Springer Nature
                1465-7392
                1476-4679
                February 19 2018
                :
                :
                Article
                10.1038/s41556-018-0040-4
                2e9d252b-7892-42cc-a46a-f89c33c0965c
                © 2018

                http://www.springer.com/tdm

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