Platelets, endothelial cells and leukocytes contribute to the exercise-triggered release of extracellular vesicles into the circulation
Platelets, endothelial cells and leukocytes contribute to the exercise-triggered release of extracellular vesicles into the circulation
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DOI：
10.1080/20013078.2019.1615820
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发表时间：
2019-12-01
影响因子：
16
通讯作者：
Kraemer-Albers, Eva-Maria
中科院分区：
文献类型：
--
作者：
Brahmer, Alexandra;Neuberger, Elmo;Kraemer-Albers, Eva-Maria
体力活动启动广泛的多系统适应，从而促进心理和身体健康。最近的研究表明，运动触发细胞外小泡(EVS)释放到循环中，可能有助于运动相关的适应性全身信号。循环中的EV包括从各种细胞类型释放的不同EV亚类的异质集合。到目前为止，对运动中释放的EV的亲本和靶细胞类型、EV亚群多样性和功能特性(ExerV)缺乏全面的了解。在这里，我们进行了详细的EV表型分析，以探索ExerV的细胞起源和潜在的亚型。健康的男性运动员接受了递增的自行车测试，直到在测试前、测试中和测试后立即抽血，直到筋疲力尽。EV芯片分析总血浆提示Exerv的内皮细胞和白细胞特征。我们进一步通过尺寸排除层析和CD9、CD63或CD81免疫小球分离从血浆中纯化ExerV，以检测ExerV亚类的动力学。EV标记物分析显示，在自行车运动中EV水平升高，所有EV亚类中在运动高峰时EV水平最高。利用多重流式细胞仪平台对ExerV进行表型分析，发现了ExerV相关的细胞表面标志物的模式，并确定淋巴细胞(CD4、CD8)、单核细胞(CD14)、血小板(CD41、CD42、CD62P)、内皮细胞(CD105、CD146)和抗原提呈细胞(MHC-II)为ExerV亲本细胞。我们得出结论，与循环系统相关的多种细胞类型有助于形成一个不同的Exerv池，这可能与运动相关的信号机制和组织串扰有关。
Physical activity initiates a wide range of multi-systemic adaptations that promote mental and physical health. Recent work demonstrated that exercise triggers the release of extracellular vesicles (EVs) into the circulation, possibly contributing to exercise-associated adaptive systemic signalling. Circulating EVs comprise a heterogeneous collection of different EV-subclasses released from various cell types. So far, a comprehensive picture of the parental and target cell types, EV-subpopulation diversity and functional properties of EVs released during exercise (ExerVs) is lacking. Here, we performed a detailed EV-phenotyping analysis to explore the cellular origin and potential subtypes of ExerVs. Healthy male athletes were subjected to an incremental cycling test until exhaustion and blood was drawn before, during, and immediately after the test. Analysis of total blood plasma by EV Array suggested endothelial and leukocyte characteristics of ExerVs. We further purified ExerVs from plasma by size exclusion chromatography as well as CD9-, CD63- or CD81-immunobead isolation to examine ExerV-subclass dynamics. EV-marker analysis demonstrated increasing EV-levels during cycling exercise, with highest levels at peak exercise in all EV-subclasses analysed. Phenotyping of ExerVs using a multiplexed flow-cytometry platform revealed a pattern of cell surface markers associated with ExerVs and identified lymphocytes (CD4, CD8), monocytes (CD14), platelets (CD41, CD42, CD62P), endothelial cells (CD105, CD146) and antigen presenting cells (MHC-II) as ExerV-parental cells. We conclude that multiple cell types associated with the circulatory system contribute to a pool of heterogeneous ExerVs, which may be involved in exercise-related signalling mechanisms and tissue crosstalk.