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

外体 微泡 细胞生物学 小泡 化学 人口 胞外囊泡 生物 生物化学 基因 小RNA 社会学 人口学
作者
Haiying Zhang,Daniela Freitas,Han Sang Kim,Kristina Ivana Fabijanic,Zhong Li,Haiyan Chen,Milica Tešić Mark,Henrik Molina,Alberto Benito‐Martín,Linda Bojmar,Justin Fang,Sham Rampersaud,Ayuko Hoshino,Irina Matei,Candia M. Kenific,Miho Nakajima,Anders P. Mutvei,Pasquale Sansone,Weston Buehring,Huajuan Wang
出处
期刊:Nature Cell Biology [Nature Portfolio]
卷期号:20 (3): 332-343 被引量:1586
标识
DOI:10.1038/s41556-018-0040-4
摘要

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. Lyden and colleagues use asymmetric flow field-flow fractionation to classify nanoparticles derived from cell lines and human samples, including previously uncharacterized large, Exo-L and small, Exo-S, exosome subsets.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
专注若蕊发布了新的文献求助10
刚刚
上岸发布了新的文献求助10
1秒前
1秒前
2秒前
3秒前
酷波er应助mojomars采纳,获得10
5秒前
tongran发布了新的文献求助30
7秒前
7秒前
8秒前
Hello应助lllqqq采纳,获得10
11秒前
喽喽发布了新的文献求助10
12秒前
Leo完成签到,获得积分10
12秒前
14秒前
玄博元完成签到,获得积分10
15秒前
16秒前
kktwo应助小小鸟采纳,获得10
17秒前
张欢馨应助小小鸟采纳,获得10
17秒前
走走发布了新的文献求助10
19秒前
慕青应助喽喽采纳,获得10
19秒前
kento驳回了七听应助
20秒前
21秒前
李健应助东风采纳,获得10
21秒前
优秀夏天发布了新的文献求助10
23秒前
24秒前
思源应助球球采纳,获得10
24秒前
25秒前
传奇3应助阿羡采纳,获得10
25秒前
onlyone发布了新的文献求助10
26秒前
26秒前
黄药师完成签到,获得积分10
27秒前
27秒前
28秒前
药膳干发布了新的文献求助10
28秒前
30秒前
zoey发布了新的文献求助10
31秒前
31秒前
31秒前
核桃发布了新的文献求助10
32秒前
越凡发布了新的文献求助10
32秒前
科研通AI6.2应助杜欢采纳,获得10
33秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Mammalian Synthetic Biology 500
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7638018
求助须知:如何正确求助?哪些是违规求助? 9211365
关于积分的说明 19758586
捐赠科研通 7204977
什么是DOI,文献DOI怎么找? 3275778
关于科研通互助平台的介绍 2437385
邀请新用户注册赠送积分活动 2272936