Systems Biology Map for Advancing the Translation of Extracellular Vesicles
By Deborah Borfitz
January 7, 2026 | Extracellular vesicles (EVs) are the master communicators of multicellular life, key in orchestrating the complex signaling networks that define physiology. A new multiomics study has now revealed their molecular cargo via EVMap, a high-resolution blueprint of the proteins and lipids in human circulating EVs providing a practical pathway forward across basic, translational and clinical applications, according to David W. Greening, Ph.D., professor of biomedical and molecular proteomics at the Baker Heart and Diabetes Institute (Australia), who co-led the mapping exercise.
There has been no shortage of interest in the landmark study following its recent publication in Nature Cell Biology (DOI: 10.1038/s41556-025-01795-7). Greening and co-lead Alin Rai, Ph.D., developed high-throughput, quantitative technologies to overcome a significant, long-standing challenge in the biology and standardization of human plasma EVs—and, critically, their translational applications in cell biology, signaling, and human health and disease.
Creation of the EVMap opens new frontiers of exploration across a multitude of fields ranging from bioengineering technology to biomarker discovery and early disease detection, clinical management, and population health, says Greening. “By decoding these EV messages, we’re beginning to read the body’s own health reports.” The team is now expanding this work through diverse collaborations to integrate EV multiomics data from larger cohorts to evolve into liquid biopsy tools with real clinical impact.
At the core of this systems biology study, the team achieved unprecedented molecular resolution, identifying 182 proteins and 52 lipids that form the conserved hallmark features of human plasma EVs. This freely accessible molecular reference map provides a platform “to resolve and understand what an EV from circulation is, the network of proteins displayed on their membrane surface, and principal information on their cell, tissue and organ origins,” Greening says. The research “represents years of persistence in refining EV isolation, mass-spectrometry workflows, and data analytics,” adds Rai.
The discovery “transforms how scientists view these vesicles,” says Greening. Within each patient sample, researchers also defined 29 proteins and 114 lipids characteristic of non-EV particles, creating a molecular benchmark to distinguish what is and is not an EV. Such knowledge will guide future studies of intercellular communication and disease biomarkers directly in humans.
“By decoding this molecular language, we’ve discovered patterns that can identify people with early signs of coronary heart disease years before symptoms appear,” Greening says. “It’s a major step toward developing a simple blood test that can predict heart attack risk.”
Molecular Benchmarking
Over the last several decades, EV trafficking has emerged as a mechanism of how cells communicate, says Greening. With the advent of new concepts relating to the involvement of EVs in many physiological and pathological processes, and their presence in blood plasma, the field of EV research has “presented a new paradigm in exploring and translating EV-based targeted therapies, and their use as diagnostic, prognostic, and predictive biomarkers.”
Nevertheless, important questions remained, principle among them: their resolution from plasma, he continues. “Conventional and current EV markers are too inconsistent to reliably separate vesicles from other plasma components, such as abundant plasma proteins and aggregates and lipoproteins. Furthermore, few studies have performed high-quality EV isolation across large, diverse groups while simultaneously analyzing and integrating both protein and lipid data.”
With the present strategy, says Greening, “these signatures were validated across multiple independent cohorts and EV subtypes, providing not only a technical solution but also an enabling conceptual framework for the field.”
Early detection biomarkers are transforming risk prediction by moving from "population averages" to a liquid biopsy approach, he says. Instead of just measuring broad factors like age or total cholesterol in the context of cardiovascular disease, these new biomarkers detect the actual, ongoing biological processes that lead to heart disease, often years before a person develops symptoms.
The same exercise could be repeated for other types of diseases, Greening points out. “The big challenge here is not can we detect disease—the field is moving past this rapidly—it’s can we detect very early-stage disease ... [or] come up with risk markers, personalized risk scores, to create a fingerprint even before you have disease.”
Merging the molecular maps in this latest study with the clinical therapeutic frameworks outlined in a recent Nature Reviews Clinical Oncology article co-led by the same authors (DOI: 10.1038/s41571-025-01074-2), effectively introduces new methods for understanding the body’s covert communication system. “Such knowledge established today are the schematics for the ability to target and detect strategies designed for tomorrow,” remarks Greening.
By understanding the surfaceome (displayed surface barcode) of EVs, he adds, scientists can now engineer “designer vesicles” that mimic the body’s own communication system or permit real-time, dynamic therapeutic monitoring. “We are moving from a world where we treat diseases to a world where we eavesdrop on them, outsmart them, and, eventually, speak their language to potentially heal from within.”
Signaling Complexity
EVs are emerging and relevant clinical utility tools as diagnostic and prognostic biomarkers with the potential for minimally invasive sampling via blood plasma or other bodily fluids, Greening stresses. Their composition of complex biomolecules is reflective of their cells and tissues of origin.
Advances in the sensitivity of detection strategies enable the identification and monitoring of such molecular cargo, he says. In the latest study, various technologies were developed and employed, including high-sensitivity mass spectrometry for protein and lipid identity and single-vesicle flow cytometry, as well as multiple machine learning frameworks for comprehensive analysis and data integration and interrogation.
Density fractionation enrichment was used to physically separate cellular components based on their density. Lipid-based affinity capture, combined with extensive biophysical and biochemical characterisation, served to isolate proteins that interact with specific lipids.
Challenges remain, says Greening, but much active research is underway in the EV space. These include “evolving technologies in capture, detection, and reproducibility ... key and continued development in standardization and robust assessment workflows and deciphering the heterogeneity of diverse types of EVs, how we identify early drivers of disease and the complexity of new biological insights, and driving clinical translation of these signaling tools and their origins.”
The latest study “resolves a master map of EVs” by successfully separating these microscopic communication packages from the dense noise of human plasma, Greening says. “By offering biologically grounded criteria for defining EV identity … [we have addressed] the longstanding issue of the purity of EVs isolated from plasma” beyond simply cataloguing their contents or relying on a few universal markers to provide “a benchmark molecular criteria in their definition.”