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Comparison of methods to isolate proteins from extracellular vesicles for mass spectrometry-based proteomic analyses.

Anal. Biochem. 584:113390 (2019)
Postprint Research data DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
Extracellular vesicles (EVs) are cell-derived membrane-bound organelles that have generated interest as they reflect the physiological condition of their source. Mass spectrometric (MS) analyses of protein cargo of EVs may lead to the discovery of biomarkers for diseases. However, for a comprehensive MS-based proteomics analysis, an optimal lysis of the EVs is required. Six methods for the protein extraction from EVs secreted by the head and neck cell line BHY were compared. Commercial radioimmunoprecipitation assay (RIPA) buffer outperformed the other buffers investigated in this study (Tris-SDS, Tris-Triton, GuHCl, urea-thiourea, and commercial Cell-lysis buffer). Following lysis with RIPA buffer, 310 proteins and 1469 peptides were identified using LTQ OrbitrapXL mass spectrometer. Among these, 86% of proteins and 72% of peptides were identified in all three replicates. In the case of other buffers, Tris-Triton identified on average 277 proteins, Cell-lysis buffer 257 proteins, and Tris-SDS, GuHCl and urea-thiourea each 267 proteins. In total, 399 proteins including 74 of the top EV markers (Exocarta) were identified, the most of the latter (73) using RIPA. The proteins exclusively identified using RIPA represented all Gene Ontology cell compartments. This study suggests that RIPA is an optimal lysis buffer for EVs in combination with MS.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Label-free; Exosomes; Microvesicles; Strategies; Tissue; Lipids; Cargo
ISSN (print) / ISBN 0003-2697
e-ISSN 1096-0309
Quellenangaben Volume: 584, Issue: , Pages: , Article Number: 113390 Supplement: ,
Publisher Elsevier
Publishing Place 525 B St, Ste 1900, San Diego, Ca 92101-4495 Usa
Non-patent literature Publications
Reviewing status Peer reviewed