# Single Extracellular Vesicle Sorting and Analysis

> **NIH NIH UH3** · UNIVERSITY OF WASHINGTON · 2021 · $1,017,765

## Abstract

Project Summary
Extracellular vesicles (EVs) are membrane-enclosed particles, which are secreted from various cell
types into the extracellular space. EVs are highly heterogeneous and comprise a diverse set of surface
protein markers as well as intra-vesicular cargoes, such as RNAs. Current approaches to the isolation
and study of EVs lack the necessary sensitivity and precision to fully characterize and understand the
make-up and the distribution of various EV subpopulations that may be present. In fact, most current
EV isolation methodologies, including differential centrifugation, affinity/immuno-magnetic isolation,
polymer-based precipitation, size-based exclusion, can be prone to contaminations; for example,
affinity/immuno-magnetic methods can be adversely affected by non-specific interactions that can
cause co-precipitation of contaminants with EVs.
Additionally, these bulk techniques can only report information that is averaged over many millions of
EVs, and thus cannot be used to understand the high degree of heterogeneity that exists among the
EVs. Yet, understanding the diversity of EVs and the cargos they carry is an essential step towards
gaining a better understanding of the precise roles EVs play in both physiological and
pathophysiological processes. This understanding, in turn, is important towards realizing the potentials
of EVs in diagnostics (e.g. as a new class of biomarkers) and therapeutics (e.g. as drug carriers).
To address the limitations of the current methodologies, we propose to develop and apply three sets of
new but related technologies for studying EVs with high-throughput at the single-EV level. These new
techniques include a nanoscale flow analyzer and flow sorter for the analysis and sorting of individual
EVs with high sensitivity and high throughput. Furthermore, we also plan to demonstrate an imaging
digital PCR platform for quantifying the RNA contents of single EVs as well as small groups of EVs.

## Key facts

- **NIH application ID:** 10376602
- **Project number:** 4UH3TR002874-03
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Daniel T Chiu
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,017,765
- **Award type:** 4N
- **Project period:** 2019-08-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10376602

## Citation

> US National Institutes of Health, RePORTER application 10376602, Single Extracellular Vesicle Sorting and Analysis (4UH3TR002874-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10376602. Licensed CC0.

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