Proteomic Profiling Allows Unbiased Compositional Analysis of Extracellular Vesicle Subtypes

Cells release diverse types of extracellular vesicles (EVs), which can transfer complex signals to surrounding cells. Specific markers to distinguish different classes of EVs (e.g. exosomes, microvesicles, enveloped viruses) are still lacking. We have developed an unbiased quantitative proteomic profiling approach for characterizing EV subtypes, and applied it to human T lymphoma cells under two experimental conditions: uninfected or infected with HIV-1. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Comparing EVs from control and HIV-1-infected cells, we identified altered profiles of numerous cellular proteins including SPN and MOV10, specifically incorporated into virions, and SERINC3, in non-viral EVs. Our unbiased EV profile analysis tool is thus a powerful approach to identify common cargoes of given EV subtypes. Furthermore, it can be used in any in vitro experimental system to investigate physiological or pathological modifications of EV release.