Scientists use extracellular vesicles to track source of chronic inflammation

A new technique to diagnose chronic inflammation developed at Nagoya University can read information from the surface and within individual extracellular vesicles in blood and urine. This technique could be used to develop non-invasive tests that can not only detect chronic inflammation but also provide information about the tissues where it occurs.

Whenever our body faces damage from injury, illness, or toxins, it launches an inflammatory response that involves dilating blood vessels to rush fluid and nutrients to the affected site and sending inflammatory cells to destroy pathogens and repair tissue.

But sometimes, the body's immune system can keep sending inflammatory cells to attack tissues or organs over months or years, even in the absence of any threat. Known as chronic inflammation, it underlies cancers, brain disorders, autoimmune diseases and heart disease, and it gradually causes irreversible tissue damage.

Early detection of chronic inflammation is important because prolonged inflammation can cause irreversible tissue damage and contribute to disease progression.

"Currently, there are several conventional inflammatory biomarkers such as C-reactive protein," said Taiga Ajiri, an assistant professor at Nagoya University's Yasui Lab, part of the Department of Biomolecular Engineering. "These biomarkers can detect inflammation, but it is difficult to identify where it occurs."

To obtain clues about where inflammation occurs, the researchers turned to extracellular vesicles (EVs): tiny membrane-bound particles released by cells throughout the body that carry molecular information from their cells of origin.

EVs work like parcels with tracking labels. Proteins on their membranes can provide clues about which tissues they came from, while microRNAs inside EVs can reflect the condition of their cells of origin. The vesicle membrane protects this cargo as it travels through body fluids such as blood and urine.

Conventionally, measuring internal microRNAs often requires breaking open EV membranes, mixing molecules from many vesicles together. This makes it difficult to link information inside a vesicle to proteins on its surface.

But reading both internal microRNA and surface protein information without breaking the EV membrane could reveal previously hidden EV subpopulations.

Reading an EV package

The researchers used cellulose nanofiber (CNF) sheets made from wood-derived cellulose. Their mesh-like nanoscale pores can capture and retain EVs. Previous work by Professor Takao Yasui's group established the use of these sheets for EV capture and analysis.

The team found that the drying process on CNF sheets can bring membrane-bound particles into close contact and promote membrane fusion. They applied this property to combine EVs with lipid nanoparticles containing molecular beacons, which are probes that detect specific microRNAs.

"These lipid nanoparticles can deliver molecular beacons inside the EV without disrupting the EV," Ajiri said. These molecular beacons emit fluorescence when they bind to specific microRNAs, allowing researchers to detect the presence of these target molecules.

Clues to the source: kidney inflammation

To test the method, the team established a laboratory model of chronic active antibody-mediated rejection (CAAMR), a complication of kidney transplantation, by exposing human kidney cells to inflammatory signals. They identified 71 microRNAs with altered expression in released EVs and focused on the highly abundant miR-1246. They also selected DPYS, a kidney-associated membrane protein, to combine information on inflammation with information on tissue origin.

After accounting for detection efficiency, the researchers estimated that about one in ten EVs from unstimulated kidney cells contained miR-1246, compared with about four in ten after inflammatory stimulation. By contrast, qPCR analysis using equivalent sample inputs did not detect a statistically significant difference.

The team then analyzed urine from kidney transplant patients with CAAMR, patients with immune diseases not primarily involving the kidney, and healthy volunteers.

Neither DPYS nor miR-1246 alone clearly distinguished the patient groups. EVs carrying both miR-1246 and the general EV marker CD63 were increased in inflammatory disease groups, but this combination could not distinguish renal from non-renal inflammation. In contrast, EVs carrying both DPYS and miR-1246 were enriched in CAAMR patients, providing clues to inflammation associated with the transplanted kidney.

The team hopes to improve particle recovery and streamline the CNF-based procedure while testing the approach in larger clinical studies. Because urine and blood can be collected with relatively little burden, the method may contribute to less-invasive evaluation and monitoring of chronic inflammatory diseases.