The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation
Open accessAbstract
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.
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Reassessment of exosome composition
Jeppesen, D. K., Fenix, A. M., Franklin, J. L., Higginbotham, J. N., Zhang, Q., Zimmerman, L. J., Liebler, D. C., Ping, J., Liu, Q., Evans, R., et al. (2019) · Cell · doi:10.1016/j.cell.2019.02.029 · Cited by 2,975
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Metadata
- Authors
- Zhang, H., Freitas, D., Kim, H. S., Fabijanic, K., Li, Z., Chen, H., Mark, M. T., Molina, H., Martin, A. B., Bojmar, L., Fang, J., Rampersaud, S., Hoshino, A., Matei, I., Kenific, C. M., Nakajima, M., Mutvei, A. P., Sansone, P., Buehring, W., Wang, H., Jimenez, J. P., Cohen-Gould, L., Paknejad, N., Brendel, M., Manova-Todorova, K., Magalhães, A., Ferreira, J. A., Osório, H., Silva, A. M., Massey, A., Cubillos-Ruiz, J. R., Galletti, G., Giannakakou, P., Cuervo, A. M., Blenis, J., Schwartz, R., Brady, M. S., Peinado, H., Bromberg, J., Matsui, H., Reis, C. A., & Lyden, D.
- Venue
- Nature Cell Biology
- Published
- 2018-02-19
- Volume
- 20
- Issue
- 3
- Pages
- 332-343
- ISSN
- 1465-7392 (ISSN-L)
- 1476-4679
- OpenAlex
- W2790701366
- Cited by
- 1,613
- References
- 12
- FWCI
- 47.79
- Type
- journal article
- Language
- en
- Open access
- green
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- Zhang, H., Freitas, D., Kim, H. S., Fabijanic, K., Li, Z., Chen, H., Mark, M. T., Molina, H., Martin, A. B., Bojmar, L., Fang, J., Rampersaud, S., Hoshino, A., Matei, I., Kenific, C. M., Nakajima, M., Mutvei, A. P., Sansone, P., Buehring, W., . . . Lyden, D. (2018). Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation. Nature Cell Biology. https://doi.org/10.1038/s41556-018-0040-4
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
