Single-step isolation of extracellular vesicles by size-exclusion chromatography

Background: Isolation of extracellular vesicles from plasma is a challenge due to the presence of proteins and lipoproteins. Isolation of vesicles using differential centrifugation or density-gradient ultracentrifugation results in co-isolation of contaminants such as protein aggregates and incomplete separation of vesicles from lipoproteins, respectively. Aim: To develop a single-step protocol to isolate vesicles from human body fluids. Methods: Platelet-free supernatant, derived from platelet concentrates, was loaded on a sepharose CL-2B column to perform size-exclusion chromatography (SEC; n=3). Fractions were collected and analysed by nanoparticle tracking analysis, resistive pulse sensing, flow cytometry and transmission electron microscopy. The concentrations of high-density lipoprotein cholesterol (HDL) and protein were measured in each fraction. Results: Fractions 9–12 contained the highest concentrations of particles larger than 70 nm and platelet-derived vesicles (46%±6 and 61%±2 of totals present in all collected fractions, respectively), but less than 5% of HDL and less than 1% of protein (4.8%±1 and 0.65%±0.3, respectively). HDL was present mainly in fractions 18–20 (32%±2 of total), and protein in fractions 19–21 (36%±2 of total). Compared to the starting material, recovery of platelet-derived vesicles was 43%±23 in fractions 9–12, with an 8-fold and 70-fold enrichment compared to HDL and protein. Conclusions: SEC efficiently isolates extracellular vesicles with a diameter larger than 70 nm from platelet-free supernatant of platelet concentrates. Application SEC will improve studies on the dimensional, structural and functional properties of extracellular vesicles

Biological reference materials for extracellular vesicle studies

LR: 20161010; CI: Copyright (c) 2016; JID: 9317982; OTO: NOTNLM; 2016/05/13 [received]; 2016/09/06 [revised]; 2016/09/06 [accepted]; aheadofprintExtracellular vesicles (EVs) mediate normal physiological homeostasis and pathological processes by facilitating intercellular communication. Research of EVs in basic science and clinical settings requires both methodological standardization and development of reference materials (RM). Here, we show insights and results of biological RM development for EV studies. We used a three-step approach to find and develop a biological RM. First, a literature search was done to find candidates for biological RMs. Second, a questionnaire was sent to EV researchers querying the preferences for RM and their use. Third, a biological RM was selected, developed, characterized, and evaluated. The responses to the survey demonstrated a clear and recognized need for RM optimized for the calibration of EV measurements. Based on the literature, naturally occurring and produced biological RM, such as virus particles and liposomes, were proposed as RM. However, none of these candidate RMs have properties completely matching those of EVs, such as size and refractive index distribution. Therefore, we evaluated the use of nanoerythrosomes (NanoE), vesicles produced from erythrocytes, as a potential biological RM. The strength of NanoE is their resemblance to EVs. Compared to the erythrocyte-derived EVs (eryEVs), NanoE have similar morphology, a similar refractive index (1.37), larger diameter (70% of the NanoE are over 200nm), and increased positive staining for CD235a and lipids (Di-8-ANEPPS) (58% and 67% in NanoE vs. 21% and 45% in eryEVs, respectively). Altogether, our results highlight the general need to develop and validate new RM with similar physical and biochemical properties as EVs to standardize EV measurements between instruments and laboratories.Extracellular vesicles (EVs) mediate normal physiological homeostasis and pathological processes by facilitating intercellular communication. Research of EVs in basic science and clinical settings requires both methodological standardization and development of reference materials (RM). Here, we show insights and results of biological RM development for EV studies. We used a three-step approach to find and develop a biological RM. First, a literature search was done to find candidates for biological RMs. Second, a questionnaire was sent to EV researchers querying the preferences for RM and their use. Third, a biological RM was selected, developed, characterized, and evaluated. The responses to the survey demonstrated a clear and recognized need for RM optimized for the calibration of EV measurements. Based on the literature, naturally occurring and produced biological RM, such as virus particles and liposomes, were proposed as RM. However, none of these candidate RMs have properties completely matching those of EVs, such as size and refractive index distribution. Therefore, we evaluated the use of nanoerythrosomes (NanoE), vesicles produced from erythrocytes, as a potential biological RM. The strength of NanoE is their resemblance to EVs. Compared to the erythrocyte-derived EVs (eryEVs), NanoE have similar morphology, a similar refractive index (137), larger diameter (70% of the NanoE are over 200 nm), and increased positive staining for CD235a and lipids (Di-8-ANEPPS) (58% and 67% in NanoE vs. 21% and 45% in eryEVs, respectively). Altogether, our results highlight the general need to develop and validate new RM with similar physical and biochemical properties as EVs to standardize EV measurements between instruments and laboratories. (C) 2016 The Authors. Published by Elsevier B.V.Peer reviewe

A review of applications of the Bayes factor in psychological research

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The paper is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines

Extracellular vesicles, tissue factor, cancer and thrombosis – discussion themes of the ISEV 2014 Educational Day

Although the association between cancer and venous thromboembolism (VTE) has long been known, the mechanisms are poorly understood. Circulating tissue factor–bearing extracellular vesicles have been proposed as a possible explanation for the increased risk of VTE observed in some types of cancer. The International Society for Extracellular Vesicles (ISEV) and International Society on Thrombosis and Haemostasis (ISTH) held a joint Educational Day in April 2014 to discuss the latest developments in this field. This review discusses the themes of that event and the ISEV 2014 meeting that followed

Identification of critical paralog groups with indispensable roles in the regulation of signaling flow

Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and ‘bowtieness’ when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis