Different isolation approaches lead to diverse glycosylated extracellular vesicle populations

J Extracell Vesicles. 2019 Jun 3;8(1):1621131. doi: 10.1080/20013078.2019.1621131. eCollection 2019.


Extracellular vesicles (EVs) are a heterogeneous group of small secreted particles involved in intercellular communication and mediating a broad spectrum of biological functions. EVs cargo is composed of a large repertoire of molecules, including glycoconjugates. Herein, we report the first study on the impact of the isolation strategy on the EV populations' glycosylation profile. The use of different state-of-the-art protocols, namely differential ultracentrifugation (UC), total exosome isolation (TEI), OptiPrepTM density gradient (ODG) and size exclusion chromatography (SEC) resulted in EV populations displaying different sets of glycoconjugates. The EV populations obtained by UC, ODG and SEC methods displayed similar protein and glycan profiles, whereas TEI methodology isolated the most distinct EV population. In addition, ODG and SEC isolation protocols provided an enhanced EV glycoproteins detection. Remarkably, proteins displaying the tumour-associated glycan sialyl-Tn (STn) were identified as packaged cargo into EVs independently of the isolation methodology. STn carrying EV samples isolated by UC, ODG and SEC presented a considerable set of cancer-related proteins that were not detected in EVs isolated by TEI. Our work demonstrates the impact of using different isolation methodologies in the populations of EVs that are obtained, with consequences in the glycosylation profile of the isolated population. Furthermore, our results highlight the importance of selecting adequate EV isolation protocols and cell culture conditions to determine the structural and functional complexity of the EV glycoconjugates.

Keywords: Extracellular vesicles; OptiPrep density gradient; glycosylation; isolation protocols; size exclusion chromatography; total exosome isolation; ultracentrifugation.

Grant support

This work was funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE (POCI-01-0145-FEDER-016585; POCI-01-0145-FEDER-007274; POCI-01-0145-FEDER-028489) and National Funds through the Foundation for Science and Technology (FCT), under the projects: PTDC/BBB-EBI/0567/2014 (to CAR), PTDC/MED-ONC/28489/2017 (to AM) and UID/BIM/04293/2013; and the project NORTE-01-0145-FEDER-000029, supported by Norte Portugal Regional Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). DF acknowledges the FCT PhD Programmes and Programa Operacional Potencial Humano (POPH), specifically the Biotech Health Programme (Doctoral Programme on Cellular and Molecular Biotechnology Applied to Health Sciences), with the reference PD/0016/2012 funded by FCT and the grant SFRH/BD/110636/2015 from FCT, POPH and FSE (Fundo Social Europeu); MB acknowledges the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 748880; and JP acknowledges FCT (SFRH/BD/137319/2018). The authors acknowledge Rede Nacional de Espectrometria de Massa, ROTEIRO/0028/2013, ref. LISBOA-01-0145-FEDER-022125, supported by COMPETE and North Portugal Regional Operational Programme (Norte2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). SV acknowledges the Danish National Research Foundation (DNRF107).