# Enabling isolation and characterization of single extracellular vesicles and their molecular contents using multi-marker surface signatures

> **NIH NIH UG3** · MESO SCALE DIAGNOSTICS, LLC · 2020 · $407,576

## Abstract

Abstract
 Extracellular vesicles (EVs) are believed to be an important means of transporting RNA
and other signaling molecules between cells. Most types of cells in the human body secrete
EVs which are each likely to have distinct biological functions. Studying different types of EVs
and their role in normal physiologic function and disease-related processes requires a reliable
means of capturing these particles from readily accessible body fluids, like blood or urine. Our
goal is to develop a new way to isolate specific types of EVs based on the molecules present on
their surface. Our hypothesis is that we can use the presence of two or more specific molecules
on the surface of select EVs secreted by a particular cell type. Once we isolate highly purified
populations we can more easily identify and measure their molecular contents.
 We will develop a new scalable approach to identifying combinations of surface
molecules present on EVs from particular cell types and use this to identify multi-marker
“surface signatures” for several types of cells known to secrete EVs directly into the
bloodstream. We will develop a new method to isolate the EVs with each of these surface
signatures. This approach, which will only capture the EVs having all of the targeted surface
markers, should greatly improve the capture specificity, thus, addressing one of the main
shortcomings of the existing EV isolation methods.
 We will verify the purity of the isolated EVs by measuring the presence of each of the
surface-signature markers on every EV using recently developed multi-marker assays and a
new high-sensitivity single-EV characterization instrument. Generating highly purified EVs from
specific cell types will enable more targeted studies of EVs than those that are presently
performed. For example, we will identify specific regulatory RNA molecules in the purified EVs
by next generation sequencing and measure the distribution of these molecules at the single EV
level using the new instrumentation and assay techniques. Lastly we will refine the isolation
methods to enable high-throughput isolation of EVs from several commonly used biofluids and
automate the single EV characterization instrumentation to enable large studies that presently
would be either impossible or too time-consuming to be cost-effective.

## Key facts

- **NIH application ID:** 10000244
- **Project number:** 5UG3TR002886-02
- **Recipient organization:** MESO SCALE DIAGNOSTICS, LLC
- **Principal Investigator:** David Aaron Routenberg
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $407,576
- **Award type:** 5
- **Project period:** 2019-08-21 → 2021-09-08

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10000244

## Citation

> US National Institutes of Health, RePORTER application 10000244, Enabling isolation and characterization of single extracellular vesicles and their molecular contents using multi-marker surface signatures (5UG3TR002886-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10000244. Licensed CC0.

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