Extracellular vesicles as a platform to study cell-surface membrane proteins

Vitamin D Modulates Lipid Composition of Adipocyte-Derived Extracellular Vesicles Under Inflammatory Conditions

SCOPE

Adipocyte-derived extracellular vesicles (AdEVs) convey lipids that can play a role in the energy homeostasis. Vitamin D (VD) has been shown to limit the metabolic inflammation as it decreases inflammatory markers expression in adipose tissue (AT). However, VD effect on adipocytes-derived EVs has never been investigated.

METHODS AND RESULTS

Thus, the aim of this study is to evaluate the AdEVs lipid composition by LC-MS/MS approach in 3T3-L1 cells treated with VD or/and pro-inflammatory factor (tumor necrosis factor α [TNFα]). Among all lipid species, four are highlighted (glycerolipids, phospholipids, lysophospholipids, and sphingolipids) with a differential content between small (sEVs) and large EVs (lEVs). This study also observes that VD alone modulates EV lipid species involved in membrane fluidity and in the budding of membrane. EVs treated with VD under inflammatory conditions have different lipid profiles than the control group, which is more pronounced in lEVs. Indeed, 25 lipid species are significantly modulated in lEVs, compared with only seven lipid species in sEVs.

CONCLUSIONS

This study concludes that VD, alone or under inflammatory conditions, is associated with specific lipidomic signature of sEVs and lEVs. These observations reinforce current knowledge on the anti-inflammatory effect of VD.

Current Advances in Technologies for Single Extracellular Vesicle Analysis and Its Clinical Applications in Cancer Diagnosis

Extracellular vesicles (EVs) have been regarded as one of the most potential diagnostic biomarkers for different cancers, due to their unique physiological and pathological functions. However, it is still challenging to precisely analyze the contents and sources of EVs, due to their heterogeneity. Herein, we summarize the advances in technologies for a single EV analysis, which may provide new strategies to study the heterogeneity of EVs, as well as their cargo, more specifically. Furthermore, the applications of a single EV analysis on cancer early diagnosis are also discussed.