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      Technical challenges of working with extracellular vesicles

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          Abstract

          Extracellular Vesicles (EVs) are gaining interest as central players in liquid biopsies, with potential applications in diagnosis, prognosis and therapeutic guidance in most pathological conditions.

          Extracellular Vesicles (EVs) are gaining interest as central players in liquid biopsies, with potential applications in diagnosis, prognosis and therapeutic guidance in most pathological conditions. These nanosized particles transmit signals determined by their protein, lipid, nucleic acid and sugar content, and the unique molecular pattern of EVs dictates the type of signal to be transmitted to recipient cells. However, their small sizes and the limited quantities that can usually be obtained from patient-derived samples pose a number of challenges to their isolation, study and characterization. These challenges and some possible options to overcome them are discussed in this review.

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          featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

          , , (2013)
          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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            Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics.

            Vitali Matyash, Gerhard Liebisch, Teymuras Kurzchalia … (2008)
            Accurate profiling of lipidomes relies upon the quantitative and unbiased recovery of lipid species from analyzed cells, fluids, or tissues and is usually achieved by two-phase extraction with chloroform. We demonstrated that methyl-tert-butyl ether (MTBE) extraction allows faster and cleaner lipid recovery and is well suited for automated shotgun profiling. Because of MTBE's low density, lipid-containing organic phase forms the upper layer during phase separation, which simplifies its collection and minimizes dripping losses. Nonextractable matrix forms a dense pellet at the bottom of the extraction tube and is easily removed by centrifugation. Rigorous testing demonstrated that the MTBE protocol delivers similar or better recoveries of species of most all major lipid classes compared with the "gold-standard" Folch or Bligh and Dyer recipes.
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              Comparison of ultracentrifugation, density gradient separation, and immunoaffinity capture methods for isolating human colon cancer cell line LIM1863-derived exosomes.

              Bow Tauro, David W. Greening, Rommel Mathias … (2012)
              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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                Author and article information

                Journal
                Journal ID (publisher-id): NANOHL
                Title: Nanoscale
                Abbreviated Title: Nanoscale
                Publisher: Royal Society of Chemistry (RSC)
                ISSN (Print): 2040-3364
                ISSN (Electronic): 2040-3372
                Publication date Created: 2018
                Publication date (Print): 2018
                Volume:
                Issue:
                Article
                DOI: 10.1039/C7NR08360B
                PubMed ID: 29265147
                SO-VID: 995310c5-25e5-486c-a4ed-d04baaeaf53e
                Copyright © © 2018
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