A facile "one-material" strategy for tandem enrichment of small extracellular vesicles phosphoproteome

Small extracellular vesicles (SEVs), are cell-derived, membrane-enclosed nanometer-sized vesicles that play vital roles in many biological processes. Recent years, more and more evidences proved that small EVs have close relationship with many diseases such as cancers and Alzheimer's disease. The use of phosphoproteins in SEVs as potential biomarkers is a promising new choice for early diagnosis and prognosis of cancer. However, current techniques for SEVs isolation still facing many challenges, such as highly instrument dependent, time consuming and insufficient purity. Furthermore, complex enrichment procedures and low microgram amounts of proteins available from clinical sources largely limit the throughput and the coveage depth of SEVs phosphoproteome mapping. Here, we synthesized Ti⁴⁺-modified magnetic graphene-oxide composites (GFST) and developed a "one-material" strategy for facile and efficient phosphoproteome enrichment and identification in SEVs from human serum. By taking advantage of chelation and electrostatic interactions between metal ions and phosphate groups, GFST shows excellent performance in both SEVs isolation and phosphopeptide enrichment. Close to 85% recovery is achieved within a few minutes by simple incubation with GFST and magnetic separation. Proteome profiling of the isolated serum SEVs without phosphopeptide enrichment results in 515 proteins, which is approximately one-fold more than those otained by ultracentrifugation or coprecipitation kits. Further application of GFST in one-material-based enrichment led to identification of 859 phosphosites in 530 phosphoproteins. Kinase-substrate correlation analysis reveals enriched substrates of CAMK in serum SEVs phosphoproteome. Therefore, we expect that the low instrument dependency and the limited sample requirement of this new strategy may facilitate clinical investigations in SEV-based transportation of abnormal kinases and substrates for drug target discovery and cancer monitoring.