Cell Reports: Methods (Jul 2021)

A size-exclusion-based approach for purifying extracellular vesicles from human plasma

  • Patrick M. Vanderboom,
  • Surendra Dasari,
  • Gregory N. Ruegsegger,
  • Mark W. Pataky,
  • Fabrice Lucien,
  • Carrie Jo Heppelmann,
  • Ian R. Lanza,
  • K. Sreekumaran Nair

Journal volume & issue
Vol. 1, no. 3
p. 100055

Abstract

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Summary: Extracellular vesicles (EVs) are released into blood from multiple organs and carry molecular cargo that facilitates inter-organ communication and an integrated response to physiological and pathological stimuli. Interrogation of the protein cargo of EVs is currently limited by the absence of optimal and reproducible approaches for purifying plasma EVs that are suitable for downstream proteomic analyses. We describe a size-exclusion chromatography (SEC)-based method to purify EVs from platelet-poor plasma (PPP) for proteomics profiling via high-resolution mass spectrometry (SEC-MS). The SEC-MS method identifies more proteins with higher precision than several conventional EV isolation approaches. We apply the SEC-MS method to identify the unique proteomic signatures of EVs released from platelets, adipocytes, muscle cells, and hepatocytes, with the goal of identifying tissue-specific EV markers. Furthermore, we apply the SEC-MS approach to evaluate the effects of a single bout of exercise on EV proteomic cargo in human plasma. Motivation: Extracellular vesicles (EVs) are detected in most body fluids including circulation, and emerging data indicate their potential role in inter-organ communications. Currently, a variety of approaches are used to purify EVs from plasma for molecular characterization; however, important parameters such as method precision and quantitative performance have not been described. To facilitate studies that characterize the function and composition of plasma EVs, there is a critical need for optimized methods that allow for reliable, reproducible, and efficient plasma EV isolation that are compatible with downstream molecular analysis, especially for proteins, EVs’ most abundant cargo.

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