Extracellular vesicles (EVs) are thought to mediate the transport of proteins and RNAs involved in intercellular communication. Here, we show dynamic changes in the buoyant density and abundance of EVs that are secreted by PC12 cells stimulated with nerve growth factor (NGF), N2A cells treated with retinoic acid to induce neural differentiation, and mouse embryonic stem cells (mESCs) differentiated into neuronal cells. EVs secreted from in vitro differentiated cells promote neural induction of mESCs. Cyclin D1 enriched within the EVs derived from differentiated neuronal cells contributes to this induction. EVs purified from cells overexpressing cyclin D1 are more potent in neural induction of mESC cells. Depletion of cyclin D1 from the EVs reduced the neural induction effect. Our results suggest that EVs regulate neural development through sorting of cyclin D1.

Extracellular vesicles (EVs) are thought to mediate intercellular communication through the delivery of cargo proteins and RNA to target cells. The uptake of EVs is often followed visually using lipophilic-dyes or fluorescently-tagged proteins to label membrane constituents that are then internalized into recipient cells ( Christianson et al., 2013 ; De Jong et al., 2019 ). However, these methods do not probe the exposure of EV cargo to intracellular compartments, such as the cytoplasm and nucleus, where protein or RNA molecules could elicit functional changes in recipient cells. In this protocol, we employ an EV cargo protein-APEX fusion to detect proximity interactions with recipient cell cytoplasmic/nuclear targets. This approach results in the biotinylation of proteins in close contact with the reporter fusion and thus permits profiling of biotinylated proteins affinity purified on immobilized streptavidin beads. Graphic abstract: Schematic showing three steps of APEX-mediated proximity labeling of proteins in cells targeted by EVs.

Background: Recent data suggested that the osmolal gap attributed to ethanol as determined by the difference between measured serum osmolality and calculated serum osmolarity is greater than its molar concentration. The increased osmotic activity of ethanol is thought to be due to its binding to water molecules. This study is conducted to determine the true osmotic contribution of ethanol to serum osmolality. Methods: Baseline serum osmolality and ethanol concentration were measured on each serum sample. Varying amounts of ethanol were added to aliquots of serum in which the baseline serum ethanol concentration was undetectable. Repeat serum osmolality and serum ethanol concentration were measured after addition of ethanol. Results: The range of serum ethanol concentration was 27.3-429.8 mg/dL. The serum osmolal gap attributed solely to ethanol is calculated based on the difference between measured serum osmolality before and measured serum osmolality after addition of ethanol. Our results demonstrated that the contribution of ethanol to serum osmolality can be calculated by dividing the serum ethanol level in mg/dl by 4.6. In addition, the relationship between serum ethanol concentration and osmolal gap due to ethanol was assessed by linear regression analysis. Linear regression analysis relating the osmolal gap due to ethanol and ethanol concentration yielded the following equation: Osmolal Gap (mOsm/kg H2O) = 0.23 (Ethanol [mg/dL]) - 1.43. Conclusion: The osmolal concentration of ethanol can be calculated based on its molar concentration. We found no evidence for ethanol binding to water molecules over the range of ethanol concentration in this study.