An optimized workflow for analyzing extracellular vesicles as biomarkers in liver diseases

Background & Aims Extracellular vesicles (EVs) play an important role in intercellular communication, serving as vehicles for the exchange of biological materials and being involved in the regulation of physiological processes. EVs and their associated cargoes are considered a promising source of disease-associated biomarkers. The purpose of this study was to establish an easy-to-use, reproducible, and scalable workflow to efficiently analyze EVs in the context of liver disease. Methods An optimized workflow was established for the pre-analytical processing and isolation of EVs from plasma and serum. Nanoparticle Tracking Analysis (NTA) was used to characterize circulating EVs in the serum of patients with nonalcoholic fatty liver disease (NAFLD), autoimmune liver disease (AIH), and animal models with impaired liver function. EVs were separated from soluble proteins by an optimized, polyethylene glycol (PEG)-based enrichment protocol. Enriched EVs were either labeled and functionally characterized by monitoring cellular uptake or lysed for biomarker identification. Results Circulating EVs in the serum of patients with NAFLD or AIH and in different animal models have been characterized by NTA. Here we show that both the quantity and size of EVs in the serum of patients/animal models are significantly different from those of healthy individuals. We show that isolated EVs are functional, and their uptake by acceptor cells can be quantified after fluorescence labelling. Enriched EVs were directly used to analyze RNA biomarkers. Several microRNAs, including miR-15b, -16, -21, -122 and -223, were found to be significantly up-regulated in EVs isolated from the sera of patients with NAFLD and AIH. We show that EVs transport cytokines, and that IL-2, IL-6 and IL-8 were significantly up-regulated in EVs enriched from patients with cholangiocarcinoma (CCA) compared to healthy controls. Conclusions The workflow presented here represents an accessible and easy-to-use approach that enables the analysis and enrichment of EVs from complex biological fluids and their preparation for functional characterization or downstream analysis. In this study, the levels of several miRNAs were found to be significantly increased in EVs isolated from AIH and NAFLD patients compared with healthy controls. Highlights ### Competing Interest Statement The authors have declared no competing interest. * miRNA : microRNA EVs : extracellular vesicles Exo : exosomes MVs : microvesicles AP : apoptotic bodies NAFLD : nonalcoholic fatty liver disease BTC : Billiary tract cancer HCC : Hepatocellular carcinoma CAA : Cholangiocarcinoma HSP70 : 70-kDa heat shock protein 70 TSG101 : Tumor susceptibility gene 101 CD63 : Cluster of differentiation 63 CD81 : Cluster of differentiation 81 HSP70 : heat shock protein 70 kDa LPC : lysophosphatidylcholine HSCs : hepatic stellate cells PCs : hepatocytes AIH : autoimmune hepatitis TACE : transarterial chemoembolization PEG : polyethylene glycol RCF : relative centrifugal force PPS : PEG precipitation solution TEI : Total Exosome Isolation PVF : particles per visual field NTA : nanoparticle tracking analysis FC : flow cytometry TEM : transmission electron microscopy DLS : dynamic light scattering GOT : glutamic-oxaloacetic transaminase GTP : glutamyl transpeptidase Br : bilirubin Hb : hemoglobin TCA : trichloroacetic acid NaCl : sodium chloride PTK : Proteinase K TX100 : Triton X-100 RBPs : RNA binding proteins CCA : cholangiocarcinoma WS : whole sera LyEVs : lysed EVs IL-2 : Interleukin 2 IL-6 : Interleukin 6 IL-8 : Interleukin 8 INFγ : Interferon gamma GM-CSF : Granulocyte-macrophage colony-stimulating factor.