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Updated: Jun 22, 2025

Isolation and Characterization of RNA-Containing Exosomes

Isolation and Characterization of RNA-Containing Exosomes

Published on: January 9, 2012

MicroRNA profiling of low concentration extracellular vesicle RNA utilizing NanoString nCounter technology.

Rachel E Crossland¹, Anna Albiero², Clara Sanjurjo-Rodríguez^1,3

¹Translational and Clinical Research Institute, Faculty of Medical Sciences Newcastle University Newcastle upon Tyne UK.

Journal of Extracellular Biology

|June 28, 2024

Summary

This summary is machine-generated.

Extracellular vesicles (EVs) and their microRNAs are valuable biomarkers. NanoString nCounter technology successfully profiles low-abundance EV RNA, even below recommended levels, enabling biomarker discovery from limited samples.

Keywords:

NanoString extracellular vesicle microRNA profiling

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Isolation and Characterization of RNA-Containing Exosomes

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Published on: January 9, 2012

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Area of Science:

Biochemistry
Molecular Biology
Biomarker Discovery

Background:

Extracellular vesicles (EVs) contain microRNAs (miRNAs) that serve as informative biomarkers for pathological processes.
The low abundance of EV RNA in biofluids presents a significant challenge for clinical biomarker studies.
Accurate profiling of low-concentration EV RNA is crucial for advancing biomarker discovery.

Purpose of the Study:

To evaluate the NanoString nCounter technology for profiling low-abundance microRNA content from extracellular vesicles.
To determine if RNA concentrations significantly lower than recommended can be reliably analyzed.
To assess the feasibility of differential microRNA expression analysis in low-input samples.

Main Methods:

Utilized NanoString nCounter technology to profile microRNA from 64 low-concentration EV RNA samples (180-49125 pg).
EVs were isolated from serum and cell culture media using precipitation or ultracentrifugation.
Applied robust quality control and differential expression analysis to assess data quality and identify relevant miRNAs.

Main Results:

Successfully profiled RNA concentrations over 100 times lower than NanoString recommendations.
Observed acceptable output ranges for imaging, binding density, controls, and normalization.
Identified biologically relevant differentially expressed microRNAs despite low input RNA levels.

Conclusions:

NanoString nCounter technology is a sensitive method for detecting and profiling low-abundance EV-derived microRNAs.
This approach offers a viable solution for research utilizing limited sample material.
Enables robust biomarker discovery from challenging low-input biological samples.