Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.
Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation.
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DOI:
10.1038/s41556-018-0040-4
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发表时间:
2018-03
影响因子:
21.3
通讯作者:
Lyden D
中科院分区:
文献类型:
--
作者:
Zhang H;Freitas D;Kim HS;Fabijanic K;Li Z;Chen H;Mark MT;Molina H;Martin AB;Bojmar L;Fang J;Rampersaud S;Hoshino A;Matei I;Kenific CM;Nakajima M;Mutvei AP;Sansone P;Buehring W;Wang H;Jimenez JP;Cohen-Gould L;Paknejad N;Brendel M;Manova-Todorova K;Magalhães A;Ferreira JA;Osório H;Silva AM;Massey A;Cubillos-Ruiz JR;Galletti G;Giannakakou P;Cuervo AM;Blenis J;Schwartz R;Brady MS;Peinado H;Bromberg J;Matsui H;Reis CA;Lyden D
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 N-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.
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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:
16
作者:
Gardiner C;Harrison P;Belting M;Böing A;Campello E;Carter BS;Collier ME;Coumans F;Ettelaie C;van Es N;Hochberg FH;Mackman N;Rennert RC;Thaler J;Rak J;Nieuwland R
通讯作者:
Nieuwland R
影响因子:
56.9
作者:
Golub, TR;Slonim, DK;Lander, ES
通讯作者:
Lander, ES
影响因子:
21.3
作者:
Costa-Silva B;Aiello NM;Ocean AJ;Singh S;Zhang H;Thakur BK;Becker A;Hoshino A;Mark MT;Molina H;Xiang J;Zhang T;Theilen TM;García-Santos G;Williams C;Ararso Y;Huang Y;Rodrigues G;Shen TL;Labori KJ;Lothe IM;Kure EH;Hernandez J;Doussot A;Ebbesen SH;Grandgenett PM;Hollingsworth MA;Jain M;Mallya K;Batra SK;Jarnagin WR;Schwartz RE;Matei I;Peinado H;Stanger BZ;Bromberg J;Lyden D
通讯作者:
Lyden D
影响因子:
14.8
作者:
Jensen, Pia H.;Karlsson, Niclas G.;Packer, Nicolle H.
通讯作者:
Packer, Nicolle H.