ABSTRACT: Background:Circulating small extracellular vesicles (sEVs) and its associated proteins are of great interest in the early detection of many diseases. However, there is no gold standard for plasma sEVs isolation, especially for proteomic profiling which could be largely affected by contamination such as lipoproteins and plasma proteins. Previous studies suggested combinations of different sEVs isolation methods could improve the yield and purity of the isolated fractions. Nevertheless, there is no systematic evaluation of size-exclusion chromatography (SEC), ultracentrifugation (UC), and their combination in a proteomic perspective. Results:Plasma samples were collected from healthy individuals, and sEVs were separated by one-step SEC, one-step UC, and combining SEC with UC, respectively. Here we exhibited that the purity of sEVs was improved by SEC in contrast to traditional UC. Furthermore, by conducting a SEC procedure followed by UC, we separated sEVs with the highest purity. In the proteomic analysis, 992 protein species were identified in the plasma sEVs isolated by our novel separation method, of which several proteins are sEVs-associated proteins but hitherto never been identified in the previous studies and database, much more than plasma sEVs isolated by UC (453) or SEC (682) alone. As compared to Vesiclepedia and Exocarta databases, plasma sEVs isolated by the new procedure kept 584 previously identified sEVs-associated proteins and 360 other proteins that have not been detected before. Detailed analysis suggested that more kinds of sEVs biomarkers, such as CD9, ALIX, and FLOT1, could be identified in plasma sEVs isolated by the novel isolation method as compared to one-step UC/SEC. Furthermore, the lower abundance ranks of common contaminants, such as lipoproteins and IgG chains, in the sEVs fractions obtained by our new method as compared to one-step UC/SEC also demonstrated the purity of sEVs had been improved. Conclusions:Combining SEC with UC could significantly improve the performance of mass spectrometry-based proteomic profiling in analyzing plasma-derived sEVs.
