Keitel, V. | Search bioRxiv

bioRxiv2023

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

Background & AimsExtracellular 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. MethodsAn 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. ResultsCirculating 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. ConclusionsThe 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. HighlightsO_LIEVs circulating in crude serum reflect the diseased stage of the donors. C_LIO_LIEnrichment of EVs with the approach presented here efficiently separates soluble proteins from EVs, providing optimal material for further characterization. C_LIO_LIExosomal markers are present in the EVs-enriched fraction. C_LIO_LIEnriched EVs are intact and are functionally taken up by acceptor cells. C_LIO_LIEnriched EVs are suitable, and have been used for, biomarkers identification both at RNA and protein level. C_LI

molecular biology↗

bioRxiv2022

Vasor: Accurate prediction of variant effects for amino acid substitutions in MDR3

Background / RationaleThe phosphatidylcholine floppase MDR3 is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time- and cost-intensive. Main resultsWe developed Vasor (Variant assessor of MDR3), a machine learning-based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the, to date, largest dataset specific for MDR3 of benign and pathogenic variants and uses general predictors, namely EVE, EVmutation, PolyPhen-2, I-Mutant2.0, MUpro, MAESTRO, PON-P2, and other variant properties such as half-sphere exposure, PTM site, and secondary structure disruption as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single-site missense variants (on an external test set: F1-score: 0.90, MCC: 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni-duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. ConclusionThe MDR3-specific prediction tool Vasor can provide reliable predictions of single site amino acid substitutions, giving users a fast way to assess initially whether a variant is benign or pathogenic.

bioinformatics↗