Emerging technologies for profiling extracellular vesicle heterogeneity.

Huang, G; Lin, G; Zhu, Y; Duan, W; Jin, D

Emerging technologies for profiling extracellular vesicle heterogeneity.

Huang, G Lin, G

Zhu, Y Duan, W Jin, D

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Publisher:: ROYAL SOC CHEMISTRY
Publication Type:: Journal Article
Citation:: Lab on a chip, 2020, 20, (14), pp. 2423-2437
Issue Date:: 2020-07

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Field	Value	Language
dc.contributor.author	Huang, G
dc.contributor.author	Lin, G https://orcid.org/0000-0001-9880-8478
dc.contributor.author	Zhu, Y
dc.contributor.author	Duan, W
dc.contributor.author	Jin, D https://orcid.org/0000-0003-1046-2666
dc.date.accessioned	2020-08-27T05:30:29Z
dc.date.available	2020-08-27T05:30:29Z
dc.date.issued	2020-07
dc.identifier.citation	Lab on a chip, 2020, 20, (14), pp. 2423-2437
dc.identifier.issn	1473-0197
dc.identifier.issn	1473-0189
dc.identifier.uri	http://hdl.handle.net/10453/142401
dc.description.abstract	Extracellular vesicles (EVs) are membrane-bound vesicles secreted by most cell types and exist in virtually all bodily fluids. They carry on a wealth of proteomic and genetic information including proteins, lipids, miRNAs, mRNA, non-coding RNA and other molecules from parental cells. Increasing evidence shows that within populations of EVs, their biogenesis, physical characteristics (e.g. size, density, morphology) and cargos (e.g. protein, lipid content, nucleic acids) may vary substantially, which accordingly change their biological properties. To fully exploit the potential of EVs, it requires qualified methods to profile EV heterogeneity. In this review, we survey recent approaches for EV isolation with innovative discoveries in heterogeneity. The main challenges in EV heterogeneity research are identified, and the roles of single cell EV profiling and single EV imaging are highlighted. We further discuss promising opportunities for resolving the underlying complexity of EV heterogeneity.
dc.format	Print
dc.language	eng
dc.publisher	ROYAL SOC CHEMISTRY
dc.relation	http://purl.org/au-research/grants/arc/IH150100028
dc.relation	http://purl.org/au-research/grants/nhmrc/GNT1160635
dc.relation	http://purl.org/au-research/grants/nhmrc/1160635
dc.relation.ispartof	Lab on a chip
dc.relation.isbasedon	10.1039/d0lc00431f
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	03 Chemical Sciences, 09 Engineering
dc.subject.classification	Analytical Chemistry
dc.title	Emerging technologies for profiling extracellular vesicle heterogeneity.
dc.type	Journal Article
utslib.citation.volume	20
utslib.location.activity	England
utslib.for	03 Chemical Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - IBMD - Initiative for Biomedical Devices
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-08-27T05:30:24Z
pubs.issue	14
pubs.publication-status	Published
pubs.volume	20
utslib.citation.issue	14

Abstract:

Extracellular vesicles (EVs) are membrane-bound vesicles secreted by most cell types and exist in virtually all bodily fluids. They carry on a wealth of proteomic and genetic information including proteins, lipids, miRNAs, mRNA, non-coding RNA and other molecules from parental cells. Increasing evidence shows that within populations of EVs, their biogenesis, physical characteristics (e.g. size, density, morphology) and cargos (e.g. protein, lipid content, nucleic acids) may vary substantially, which accordingly change their biological properties. To fully exploit the potential of EVs, it requires qualified methods to profile EV heterogeneity. In this review, we survey recent approaches for EV isolation with innovative discoveries in heterogeneity. The main challenges in EV heterogeneity research are identified, and the roles of single cell EV profiling and single EV imaging are highlighted. We further discuss promising opportunities for resolving the underlying complexity of EV heterogeneity.

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http://hdl.handle.net/10453/142401