Scientific Reports (Jun 2023)

Towards optimised extracellular vesicle proteomics from cerebrospinal fluid

  • Petra Kangas,
  • Tuula A. Nyman,
  • Liisa Metsähonkala,
  • Cameron Burns,
  • Robert Tempest,
  • Tim Williams,
  • Jenni Karttunen,
  • Tarja S. Jokinen

DOI
https://doi.org/10.1038/s41598-023-36706-z
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 13

Abstract

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Abstract The proteomic profile of extracellular vesicles (EVs) from cerebrospinal fluid (CSF) can reveal novel biomarkers for diseases of the brain. Here, we validate an ultrafiltration combined with size-exclusion chromatography (UF-SEC) method for isolation of EVs from canine CSF and probe the effect of starting volume on the EV proteomics profile. First, we performed a literature review of CSF EV articles to define the current state of art, discovering a need for basic characterisation of CSF EVs. Secondly, we isolated EVs from CSF by UF-SEC and characterised the SEC fractions by protein amount, particle count, transmission electron microscopy, and immunoblotting. Data are presented as mean ± standard deviation. Using proteomics, SEC fractions 3–5 were compared and enrichment of EV markers in fraction 3 was detected, whereas fractions 4–5 contained more apolipoproteins. Lastly, we compared starting volumes of pooled CSF (6 ml, 3 ml, 1 ml, and 0.5 ml) to evaluate the effect on the proteomic profile. Even with a 0.5 ml starting volume, 743 ± 77 or 345 ± 88 proteins were identified depending on whether ‘matches between runs’ was active in MaxQuant. The results confirm that UF-SEC effectively isolates CSF EVs and that EV proteomic analysis can be performed from 0.5 ml of canine CSF.