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Chemical Affinity-Based Isolation of Extracellular Vesicles from Biofluids for Proteomics and Phosphoproteomics Analysis

Extracellular vesicles (EVs) from biofluids have recently gained significant attention in the field of liquid biopsy. Released by almost every type of ...

Purdue University

Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated library, direct DIA (library-free), forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease, and healthy control individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2584 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.

Data-Independent Acquisition Phosphoproteomics of Urinary Extracellular Vesicles Enables Renal Cell Carcinoma Grade Differentiation.

Many biological processes are regulated through dynamic protein phosphorylation. Monitoring disease-relevant phosphorylation events in circulating biofluids is highly appealing but also technically challenging. We introduce here a functionally tunable material and a strategy, extracellular vesicles to phosphoproteins (EVTOP), which achieves one-pot extracellular vesicles (EVs) isolation, extraction, and digestion of EV proteins, and enrichment of phosphopeptides, with only a trace amount of starting biofluids. EVs are efficiently isolated by magnetic beads functionalized with Ti ions and a membrane-penetrating peptide, octa-arginine R  , which also provides the hydrophilic surface to retain EV proteins during lysis. Subsequent on-bead digestion concurrently converts EVTOP to Ti ion-only surface for efficient enrichment of phosphopeptides for phosphoproteomic analyses. The streamlined, ultra-sensitive platform enabled us to quantify 500 unique EV phosphopeptides with only a few μL of plasma and over 1200 phosphopeptides with 100 μL of cerebrospinal fluid (CSF). We explored its clinical application of monitoring the outcome of chemotherapy of primary central nervous system lymphoma (PCNSL) patients with a small volume of CSF, presenting a powerful tool for broad clinical applications.

Profiling Phosphoproteome Landscape in Circulating Extracellular Vesicles from Microliters of Biofluids through Functionally Tunable Paramagnetic Separation.

Reversible protein S-nitrosylation regulates a wide range of biological functions and physiological activities in plants. However, it is challenging to quantitively determine the S-nitrosylation targets and dynamics in vivo. In this study, we develop a highly sensitive and efficient fluorous affinity tag-switch (FAT-switch) chemical proteomics approach for S-nitrosylation peptide enrichment and detection. We quantitatively compare the global S-nitrosylation profiles in wild-type Arabidopsis and gsnor1/hot5/par2 mutant using this approach, and identify 2,121 S-nitrosylation peptides in 1,595 protein groups, including many previously unrevealed S-nitrosylated proteins. These are 408 S-nitrosylated sites in 360 protein groups showing an accumulation in hot5-4 mutant when compared to wild type. Biochemical and genetic validation reveal that S-nitrosylation at Cys337 in ER OXIDOREDUCTASE 1 (ERO1) causes the rearrangement of disulfide, resulting in enhanced ERO1 activity. This study offers a powerful and applicable tool for S-nitrosylation research, which provides valuable resources for studies on S-nitrosylation-regulated ER functions in plants.

FAT-switch-based quantitative S-nitrosoproteomics reveals a key role of GSNOR1 in regulating ER functions.

Extracellular vesicles (EVs) have emerged as a promising source of disease biomarkers for noninvasive early stage diagnoses, but a bottleneck in EV sample processing restricts their immense potential in clinical applications. Existing methods are limited by a low EV yield and integrity, slow processing speeds, low sample capacity, and poor recovery efficiency. We aimed to address these issues with a high-throughput automated workflow for EV isolation, EV lysis, protein extraction, and protein denaturation. The automation can process clinical urine samples in parallel, resulting in protein-covered beads ready for various analytical methods, including immunoassays, protein quantitation assays, and mass spectrometry. Compared to the standard manual lysis method for contamination levels, efficiency, and consistency of EV isolation, the automated protocol shows reproducible and robust proteomic quantitation with less than a 10% median coefficient of variation. When we applied the method to clinical samples, we identified a total 3,793 unique proteins and 40,380 unique peptides, with 992 significantly upregulated proteins in kidney cancer patients versus healthy controls. These upregulated proteins were found to be involved in several important kidney cancer metabolic pathways also identified with a manual control. This hands-free workflow represents a practical EV extraction and profiling approach that can benefit both clinical and research applications, streamlining biomarker discovery, tumor monitoring, and early cancer diagnoses.

Article	Year
Data-Independent Acquisition Phosphoproteomics of Urinary Extracellular Vesicles Enables Renal Cell Carcinoma Grade Differentiation. Molecular & cellular proteomics : MCP\| PubMed ID: 36997065	2023
Profiling Phosphoproteome Landscape in Circulating Extracellular Vesicles from Microliters of Biofluids through Functionally Tunable Paramagnetic Separation. Angewandte Chemie (International ed. in English)\| PubMed ID: 37216424	2023
FAT-switch-based quantitative S-nitrosoproteomics reveals a key role of GSNOR1 in regulating ER functions. Nature communications\| PubMed ID: 37277371	2023
Hands-Free Proteomic Profiling of Urinary Extracellular Vesicles with a High-Throughput Automated Workflow. Journal of the American Society for Mass Spectrometry\| PubMed ID: 37870912	2023

Zhuojun Luo

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