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Quantification of Small Extracellular Vesicles by Size Exclusion Chromatography with Fluorescence Detection.

ABSTRACT: Chemical analysis of small extracellular vesicles (sEVs) circulating in body fluids holds potentials in noninvasive diagnosis of diseases and evaluation of therapeutic treatments. However, quantification of sEVs remains a challenge due to lacking of cost-effective analytical protocols. Herein we report a facile method based on size exclusion chromatography with fluorescence detection (SEC-FD) for sEVs quantification. After removal of cells and cell debris, a 0.50 mL sample (e.g., cell culture medium) is incubated with CM-Dil dye to fluorescently label sEVs. The incubation solution is then separated on a SEC column packed with Sepharose CL-4B. The eluent is monitored fluorescently at Ex553 nm/Em570 nm by using a fluorometer equipped with a 50-?L flow through cuvette. Separation efficiency of the proposed SEC-FD method was evaluated by analyzing 100 nm liposomes and albumin-FITC conjugate. Liposomes were eluted out in less than 6 min, about 10 min before albumin-FITC. A separation repeatability (RSD in retention time) of 1.4% (n = 5) was obtained for liposomes. In analysis of cell culture media, linear calibration curves based on SEC-FD peak height versus sEVs concentration were obtained with r2 value of 0.996. Intraday quantification repeatability (RSD in peak height) was 3.2% (n = 5). The detection limit was estimated to be 2.9 × 107 exosome particles/mL. The proposed assay was applied to the first study of sEVs secretion from TK6 cells cultured in serum-free medium for a culturing period from 1 to 48 h.

SUBMITTER: Xu R

PROVIDER: S-EPMC5089915 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Quantification of Small Extracellular Vesicles by Size Exclusion Chromatography with Fluorescence Detection.

Xu Rui R Fitts Austin A Li Xiangtang X Fernandes Joseph J Pochampally Radhika R Mao Jinghe J Liu Yi-Ming YM

Analytical chemistry 20161010 21

Chemical analysis of small extracellular vesicles (sEVs) circulating in body fluids holds potentials in noninvasive diagnosis of diseases and evaluation of therapeutic treatments. However, quantification of sEVs remains a challenge due to lacking of cost-effective analytical protocols. Herein we report a facile method based on size exclusion chromatography with fluorescence detection (SEC-FD) for sEVs quantification. After removal of cells and cell debris, a 0.50 mL sample (e.g., cell culture me ...[more]

PMID: 27689436

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Project description:Extracellular vesicles (EVs) are involved in a wide range of physiological and pathological processes by shuttling material out of and between cells. Tissue EVs may thus lend insights into disease mechanisms and also betray disease when released into easily accessed biological fluids. Since brain-derived EVs (bdEVs) and their cargo may serve as biomarkers of neurodegenerative diseases, we evaluated modifications to a published, rigorous protocol for separation of EVs from brain tissue and studied effects of processing variables on quantitative and qualitative outcomes. To this end, size exclusion chromatography (SEC) and sucrose density gradient ultracentrifugation were compared as final separation steps in protocols involving stepped ultracentrifugation. bdEVs were separated from brain tissues of human, macaque. Effects of post-mortem interval (PMI) before final bdEV separation were probed. MISEV2018-compliant EV characterization was performed, and both small RNA and protein profiling were done. We conclude that the modified, SEC-employing protocol achieves EV separation efficiency roughly similar to a protocol using gradient density ultracentrifugation, while decreasing operator time and, potentially, variability. The protocol appears to yield bdEVs of higher purity for human tissues compared with macaque, suggesting opportunities for optimization. The interval between death/tissue storage/processing and final bdEV separation can also affect bdEV populations and composition and should thus be recorded for rigorous reporting. Different populations of EVs obtained through the modified method reported herein display characteristic RNA and protein content that hint at biomarker potential. To conclude, this study finds that the automatable and increasingly employed technique of SEC can be applied to tissue EV separation, and also reveals more about the importance of species-specific and technical considerations when working with tissue EVs. These results are expected to enhance the use of bdEVs in revealing and understanding brain disease.

Project description:BackgroundCirculating small extracellular vesicles (sEVs) and its associated proteins are of great interest in the early detection of many diseases. However, there is no gold standard for plasma sEVs isolation, especially for proteomic profiling which could be largely affected by contamination such as lipoproteins and plasma proteins. Previous studies suggested combinations of different sEVs isolation methods could improve the yield and purity of the isolated fractions. Nevertheless, there is no systematic evaluation of size-exclusion chromatography (SEC), ultracentrifugation (UC), and their combination in a proteomic perspective.ResultsPlasma samples were collected from healthy individuals, and sEVs were separated by one-step SEC, one-step UC, and combining SEC with UC, respectively. Here we exhibited that the purity of sEVs was improved by SEC in contrast to traditional UC. Furthermore, by conducting a SEC procedure followed by UC, we separated sEVs with the highest purity. In the proteomic analysis, 992 protein species were identified in the plasma sEVs isolated by our novel separation method, of which several proteins are sEVs-associated proteins but hitherto never been identified in the previous studies and database, much more than plasma sEVs isolated by UC (453) or SEC (682) alone. As compared to Vesiclepedia and Exocarta databases, plasma sEVs isolated by the new procedure kept 584 previously identified sEVs-associated proteins and 360 other proteins that have not been detected before. Detailed analysis suggested that more kinds of sEVs biomarkers, such as CD9, ALIX, and FLOT1, could be identified in plasma sEVs isolated by the novel isolation method as compared to one-step UC/SEC. Furthermore, the lower abundance ranks of common contaminants, such as lipoproteins and IgG chains, in the sEVs fractions obtained by our new method as compared to one-step UC/SEC also demonstrated the purity of sEVs had been improved.ConclusionsCombining SEC with UC could significantly improve the performance of mass spectrometry-based proteomic profiling in analyzing plasma-derived sEVs.

Dataset Information

Quantification of Small Extracellular Vesicles by Size Exclusion Chromatography with Fluorescence Detection.

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Quantification of Small Extracellular Vesicles by Size Exclusion Chromatography with Fluorescence Detection.

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