Proteomic profiling of mesenchymal stem cell-derived extracellular vesicles: Impact of isolation methods on protein cargo.

Extracellular vesicles (EVs) are nanosized vesicles with a lipid bilayer that are secreted by cells and play a critical role in cell-to-cell communication. Despite the promising reports regarding their diagnostic and therapeutic potential, the utilization of EVs in the clinical setting is limited due to insufficient information about their cargo and a lack of standardization in isolation and analysis methods. Considering protein cargos in EVs as key contributors to their therapeutic potency, we conducted a tandem mass tag (TMT) quantitative proteomics analysis of three subpopulations of mesenchymal stem cell (MSC)-derived EVs obtained through three different isolation techniques: ultracentrifugation (UC), high-speed centrifugation (HS), and ultracentrifugation on sucrose cushion (SU). Subsequently, we checked EV marker expression, size distribution, and morphological characterization, followed by bioinformatic analysis. The bioinformatic analysis of the proteome results revealed that these subpopulations exhibit distinct molecular and functional characteristics. The choice of isolation method impacts the proteome of isolated EVs by isolating different subpopulations of EVs. Specifically, EVs isolated through the high-speed centrifugation (HS) method exhibited a higher abundance of ribosomal and mitochondrial proteins. Functional apoptosis assays comparing isolated mitochondria with EVs isolated through different methods revealed that HS-EVs, but not other EVs, induced early apoptosis in cancer cells. On the other hand, EVs isolated using the sucrose cushion (SU) and ultracentrifugation (UC) methods demonstrated a higher abundance of proteins primarily involved in the immune response, cell-cell interactions and extracellular matrix interactions. Our analyses unveil notable disparities in proteins and associated biological functions among EV subpopulations, underscoring the importance of meticulously selecting isolation methods and resultant EV subpopulations based on the intended application.