One-Pot Analytical Pipeline for Efficient and Sensitive Proteomic Analysis of Extracellular Vesicles

Extracellular vesicle (EV) proteomics emerges as an effective tool for discovering potential biomarkers for disease diagnosis, monitoring, and therapeutics. However, the current workflow of mass spectrometry-based EV proteome analysis is not fully compatible in a clinical setting due to inefficient EV isolation methods and a tedious sample preparation process. To streamline and improve the efficiency of EV proteome analysis, here we introduce a one-pot analytical pipeline integrating a robust EV isolation approach, EV total recovery and purification (EVtrap), with in situ protein sample preparation, to detect urinary EV proteome. By incorporating solvent-driven protein capture and fast on-bead digestion, the one-pot pipeline enabled the whole EV proteome analysis to be completed within one day. In comparison with the existing workflow, the one-pot pipeline was able to obtain better peptide yield and identify the equivalent number of unique EV proteins from 1 mL of urine. Finally, we applied the one-pot pipeline to profile proteomes in urinary EVs of bladder cancer patients. A total of 2774 unique proteins were identified in 53 urine samples using a 15 min gradient library-free data-independent acquisition method. Taken altogether, our novel one-pot analytical pipeline demonstrated its potential for routine and robust EV proteomics in biomedical applications.

Automated summary

Extracellular vesicle proteomics is a useful tool for discovering biomarkers for disease diagnosis and treatment. However, the current workflow for analyzing EV proteomes using mass spectrometry is not suitable for clinical settings. In this study, we developed a one-pot analytical pipeline that combines a robust EV isolation method and in situ protein sample preparation to detect urinary EV proteomes. This streamlined pipeline enabled the analysis of the entire EV proteome in one day and yielded better results compared to existing methods.