Comprehensive evaluation of methods for small extracellular vesicles separation from human plasma, urine and cell culture medium.
Comprehensive evaluation of methods for small extracellular vesicles separation from human plasma, urine and cell culture medium.
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DOI:
10.1002/jev2.12044
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发表时间:
2020-12
影响因子:
16
通讯作者:
Xue W
中科院分区:
文献类型:
--
作者:
Dong L;Zieren RC;Horie K;Kim CJ;Mallick E;Jing Y;Feng M;Kuczler MD;Green J;Amend SR;Witwer KW;de Reijke TM;Cho YK;Pienta KJ;Xue W
One of the challenges that restricts the evolving extracellular vesicle (EV) research field is the lack of a consensus method for EV separation. This may also explain the diversity of the experimental results, as co‐separated soluble proteins and lipoproteins may impede the interpretation of experimental findings. In this study, we comprehensively evaluated the EV yields and sample purities of three most popular EV separation methods, ultracentrifugation, precipitation and size exclusion chromatography combined with ultrafiltration, along with a microfluidic tangential flow filtration device, Exodisc, in three commonly used biological samples, cell culture medium, human urine and plasma. Single EV phenotyping and density‐gradient ultracentrifugation were used to understand the proportion of true EVs in particle separations. Our findings suggest Exodisc has the best EV yield though it may co‐separate contaminants when the non‐EV particle levels are high in input materials. We found no 100% pure EV preparations due to the overlap of their size and density with many non‐EV particles in biofluids. Precipitation has the lowest sample purity, regardless of sample type. The purities of the other techniques may vary in different sample types and are largely dependent on their working principles and the intrinsic composition of the input sample. Researchers should choose the proper separation method according to the sample type, downstream analysis and their working scenarios.
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DOI:
10.1007/s00018-018-2773-4
发表时间:
2018-08
期刊:
Cellular and molecular life sciences : CMLS
影响因子:
--
作者:
Karimi N;Cvjetkovic A;Jang SC;Crescitelli R;Hosseinpour Feizi MA;Nieuwland R;Lötvall J;Lässer C
通讯作者:
Lässer C
影响因子:
16
作者:
Lötvall J;Hill AF;Hochberg F;Buzás EI;Di Vizio D;Gardiner C;Gho YS;Kurochkin IV;Mathivanan S;Quesenberry P;Sahoo S;Tahara H;Wauben MH;Witwer KW;Théry C
通讯作者:
Théry C
DOI:
10.1126/science.aau6977
发表时间:
2020-02-07
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Kalluri R;LeBleu VS
通讯作者:
LeBleu VS
DOI:
10.1073/pnas.1521230113
发表时间:
2016-02-23
影响因子:
11.1
作者:
Kowal, Joanna;Arras, Guillaume;Thery, Clotilde
通讯作者:
Thery, Clotilde
影响因子:
3.7
作者:
Helwa I;Cai J;Drewry MD;Zimmerman A;Dinkins MB;Khaled ML;Seremwe M;Dismuke WM;Bieberich E;Stamer WD;Hamrick MW;Liu Y
通讯作者:
Liu Y