Characterizing Extracellular Vesicles and Their Diverse RNA Contents

Abstract

Cells release nanometer-scale, lipid bilayer-enclosed biomolecular packages (extracellular vesicles; EVs) into their surrounding environment. EVs are hypothesized to be intercellular communication agents that regulate physiological states by transporting biomolecules between near and distant cells. The research community has consistently advocated for the importance of RNA contents in EVs by demonstrating that: (1) EV-related RNA contents can be detected in a liquid biopsy, (2) disease states significantly alter EV-related RNA contents, and (3) sensitive and specific liquid biopsies can be implemented in precision medicine settings by measuring EV-derived RNA contents. Furthermore, EVs have medical potential beyond diagnostics. Both natural and engineered EVs are being investigated for therapeutic applications such as regenerative medicine and as drug delivery agents. This review focuses specifically on EV characterization, analysis of their RNA content, and their functional implications. The NIH extracellular RNA communication (ERC) program has catapulted human EV research from an RNA profiling standpoint by standardizing the pipeline for working with EV transcriptomics data, and creating a centralized database for the scientific community. There are currently thousands of RNA-sequencing profiles hosted on the Extracellular RNA Atlas alone (Murillo et al., 2019), encompassing a variety of human biofluid types and health conditions. While a number of significant discoveries have been made through these studies individually, integrative analyses of these data have thus far been limited. A primary focus of the ERC program over the next five years is to bring higher resolution tools to the EV research community so that investigators can isolate and analyze EV sub-populations, and ultimately single EVs sourced from discrete cell types, tissues, and complex biofluids. Higher resolution techniques will be essential for evaluating the roles of circulating EVs at a level which impacts clinical decision making. We expect that advances in microfluidic technologies will drive near-term innovation and discoveries about the diverse RNA contents of EVs. Long-term translation of EV-based RNA profiling into a mainstay medical diagnostic tool will depend upon identifying robust patterns of circulating genetic material that correlate with a change in health status.

Keywords: RNA; biomarker; characterization; exosome; extracellular vesicle; gene expression; microvesicle; transcriptome.

Figure 1

Fifty years of historical landmarks in extracellular vesicle-related research.

Figure 2

An integrative model of extracellular vesicle (EV) biogenesis. A sample of plasma membrane and extracellular materials is internalized through the endocytic pathway, forming an endosome. The nucleus, endoplasmic reticulum, Golgi, and mitochondria generate an interconnected secretory network that can deliver cellular contents either to the endosome or to the plasma membrane. Secretory machinery localizes at either the endosome or at the plasma membrane and contents are loaded into the nascent EV while membrane budding away from the cytosol occurs. Membrane scission occurs, and at the plasma membrane, EVs are immediately released. In the endosomal pathway, nascent EVs are kept as intralumenal vesicles until the multivesicular endosome fuses with the plasma membrane to release its contents. Cell membrane topology and constituents are generally conserved. On release, EVs can either bind to or navigate through the extracellular milleu which can include matrix proteins. See Figure 4 for more detail on EV composition. The figure was prepared in part using BioRender.com.

Figure 3

Schematics of selected experimental approaches for extracellular vesicles (EVs). (A) Nano-deterministic lateral displacement (nano-DLD). EVs are passed through a regularly-interspaced micropillar array with laminar flow. The pillar size and spacing determines how EVs of a specific size will migrate through the array. Smaller EVs output at the zigzag channel while larger EVs output at the bump channel. (B) Viscoelastic flow. Particles flowing through a viscoelastic medium are forced to their equilibrium position in the fluid channel and can then be collected. (C) Asymmetric flow field-flow fractionation (AF4). Opposing parabolic flows and an orthogonal flow focus particles to the center of the channel and then particles migrate to an equilibrium position. Then, the opposing parabolic flow is removed and particles elute from small to large. (D) Size exclusion chromatography (SEC). A stationary phase is built by packing nanoporous beads into a column. The biofluid is eluted in the mobile phase. Small particles take a longer path through the column by traversing through the beads, while larger particles travel outside of the beads. (E) Cushioned density gradient centrifugation. The sample is layered over a high density medium, then spun. Particles collect at the cushion made by the interface of the high density medium and the sample medium. The particles are then transferred to the bottom of a tube and layered with a density gradient. Upon centrifugation, the particles float upward to their equilibrium density position. The density fractions can then be collected. (F). Polymer-based precipitation. Addition of a volume-excluding polymer to the sample induces aggregation and precipitation which then allows for low-speed centrifugation to collect the precipitated particles. The sample can then be cleaned of the volume-excluding polymer and other potential contaminants. (G) Nanoparticle tracking analysis (NTA). A laser is shone onto the sample and scattered photons are detected continuously by video. Brownian motion is traced and correlated with particle properties. (H) Resistive pulse sensing (RPS). A current is applied to a nanopore and recorded over time. EV motion through the pore results in a measurable current drop which can then be correlated with particle properties.

Figure 4

Extracellular vesicle (EV) composition in the context of biological solutions. EVs carry all biomolecule classes that have been associated with cells. DNA and RNAs (both coding and non-coding) are found within EVs. Proteins can be freely soluble, membrane-associated, membrane-anchored, and trans-membrane. Metabolites and other small molecules are also found within EVs. The membrane bilayer is composed of phospholipid and cholesterol derivatives. EVs cannot be purely isolated and other non-vesicular molecular chaperones such as RNA-binding proteins and lipoproteins often contaminate EV preparations. *Proteins derived from the cytosol of the parent cell. The figure was prepared in part using BioRender.com, including crystal structures from the following references Sopkova et al. (1993), Ding et al. (2018), Kitchen et al. (2015), Makyio et al. (2012), and the PDB accession ID: 2CRN (unpublished).