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@ARTICLE{Tzaridis:162811,
      author       = {Tzaridis, Theophilos and Bachurski, Daniel and Liu, Shu and
                      Surmann, Kristin and Babatz, Felix and Gesell Salazar,
                      Manuela and Völker, Uwe and Hallek, Michael and Herrlinger,
                      Ulrich and Vorberg, Ina and Coch, Christoph and Reiners,
                      Katrin S and Hartmann, Gunther},
      title        = {{E}xtracellular {V}esicle {S}eparation {T}echniques
                      {I}mpact {R}esults from {H}uman {B}lood {S}amples:
                      {C}onsiderations for {D}iagnostic {A}pplications.},
      journal      = {International journal of molecular sciences},
      volume       = {22},
      number       = {17},
      issn         = {1422-0067},
      address      = {Basel},
      publisher    = {Molecular Diversity Preservation International},
      reportid     = {DZNE-2021-01466},
      pages        = {9211},
      year         = {2021},
      note         = {CC BY},
      abstract     = {Extracellular vesicles (EVs) are reminiscent of their cell
                      of origin and thus represent a valuable source of
                      biomarkers. However, for EVs to be used as biomarkers in
                      clinical practice, simple, comparable, and reproducible
                      analytical methods must be applied. Although progress is
                      being made in EV separation methods for human biofluids, the
                      implementation of EV assays for clinical diagnosis and
                      common guidelines are still lacking. We conducted a
                      comprehensive analysis of established EV separation
                      techniques from human serum and plasma, including
                      ultracentrifugation and size exclusion chromatography (SEC),
                      followed by concentration using (a) ultracentrifugation, (b)
                      ultrafiltration, or (c) precipitation, and immunoaffinity
                      isolation. We analyzed the size, number, protein, and miRNA
                      content of the obtained EVs and assessed the functional
                      delivery of EV cargo. Our results demonstrate that all
                      methods led to an adequate yield of small EVs. While no
                      significant difference in miRNA content was observed for the
                      different separation methods, ultracentrifugation was best
                      for subsequent flow cytometry analysis. Immunoaffinity
                      isolation is not suitable for subsequent protein analyses.
                      SEC + ultracentrifugation showed the best functional
                      delivery of EV cargo. In summary, combining SEC with
                      ultracentrifugation gives the highest yield of pure and
                      functional EVs and allows reliable analysis of both protein
                      and miRNA contents. We propose this combination as the
                      preferred EV isolation method for biomarker studies from
                      human serum or plasma.},
      keywords     = {Biological Transport / Biomarkers / Cell Fractionation:
                      methods / Chemical Fractionation: methods / Extracellular
                      Vesicles: metabolism / Extracellular Vesicles:
                      ultrastructure / Flow Cytometry / Humans / Liquid Biopsy:
                      methods / Proteins: metabolism / extracellular vesicle
                      isolation (Other) / extracellular vesicles diagnostics
                      (Other) / methods in liquid biopsy (Other) / plasma
                      biomarker (Other) / serum biomarker (Other) / Biomarkers
                      (NLM Chemicals) / Proteins (NLM Chemicals)},
      cin          = {AG Vorberg},
      ddc          = {540},
      cid          = {I:(DE-2719)1013004},
      pnm          = {352 - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-352},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34502122},
      pmc          = {pmc:PMC8431127},
      doi          = {10.3390/ijms22179211},
      url          = {https://pub.dzne.de/record/162811},
}