↓ Skip to main content

Multiparametric Analysis of Circulating Exosomes and Other Small Extracellular Vesicles by Advanced Imaging Flow Cytometry

Overview of attention for article published in Frontiers in immunology, July 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
109 Dimensions

Readers on

mendeley
199 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Multiparametric Analysis of Circulating Exosomes and Other Small Extracellular Vesicles by Advanced Imaging Flow Cytometry
Published in
Frontiers in immunology, July 2018
DOI 10.3389/fimmu.2018.01583
Pubmed ID
Authors

Sotiris Mastoridis, Giuliana Minani Bertolino, Gavin Whitehouse, Francesco Dazzi, Alberto Sanchez-Fueyo, Marc Martinez-Llordella

Abstract

Extracellular vesicles (EVs) are responsible for a multitude of physiological functions, including immunomodulation. A heterogenous mixture of small EV (sEV) subsets, including putative exosomes, is derived when commonly used "exosome" isolation techniques are employed. Subset diversity relates in part to their different intracellular origins, and can be associated with distinct functional properties. Recent progress in the EV field has enabled the categorization of such subsets based on their surface composition. For the first time, we combine such emerging subset-specific markers with advanced imaging flow cytometry (iFCM) to perform high-throughput, multiparametric, vesicle-by-vesicle characterization, and functional assessment of specific small EV subsets, and exosomes in particular. The approach allows researchers to address three important applications. First, it is known that different isolation techniques result in the divergent recovery of particular vesicle subsets. Taking three commonly used "exosome" isolation techniques as test cases (ultracentrifugation, size-exclusion chromatography, and polymer-based precipitation), the capacity for convenient and accurate isolate compositional analysis by iFCM is demonstrated. The approach was able to corroborate and to quantify the known skewing of subtype recovery among different isolation approaches. Second, exosomes are a particularly widely studied EV subset. Applying exosome-specific markers to samples collected from an optimal clinical transplantation model, we verify the capacity for iFCM to detect exosomes in circulation, to establish their tissue of origin, and to provide insights as to their functional immunological potential. Finally, we describe a technique for establishing whether the transfer of a molecule of interest to a target cell is exosomally mediated. In so doing, we highlight the approach's utility in assessing the functional impact of circulating exosomes and in identifying their targets. In conclusion, we set out a new methodological approach by which small extracellular vesicle subsets, exosomes in particular, can be conveniently and comprehensively investigated, thereby offering novel phenotypic and functional insights.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 199 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 20%
Student > Ph. D. Student 36 18%
Student > Bachelor 16 8%
Student > Doctoral Student 15 8%
Student > Master 13 7%
Other 21 11%
Unknown 58 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 52 26%
Agricultural and Biological Sciences 17 9%
Medicine and Dentistry 16 8%
Immunology and Microbiology 14 7%
Engineering 11 6%
Other 25 13%
Unknown 64 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2018.
All research outputs
#17,292,294
of 25,385,509 outputs
Outputs from Frontiers in immunology
#20,310
of 31,537 outputs
Outputs of similar age
#221,108
of 341,012 outputs
Outputs of similar age from Frontiers in immunology
#536
of 736 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,537 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,012 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 736 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.