Heidelberg University Hospital, Department of Neuroradiology, Heidelberg, Germany.
German Cancer Research Center, Department of Radiology, Heidelberg, Germany.
Methods Mol Biol. 2022;2399:261-274. doi: 10.1007/978-1-0716-1831-8_12.
Mitochondria are complex organelles with multifaceted roles in cell biology, acting as signaling hubs that implicate them in cellular physiology and pathology. Mitochondria are both the target and the origin of multiple signaling events, including redox processes and calcium signaling which are important for organellar function and homeostasis. One way to interrogate mitochondrial function is by live cell imaging. Elaborated approaches perform imaging of single mitochondrial dynamics in living cells and animals. Imaging mitochondrial signaling and function can be challenging due to the sheer number of mitochondria, and the speed, propagation, and potential short half-life of signals. Moreover, mitochondria are organized in functionally coupled interorganellar networks. Therefore, advanced analysis and postprocessing tools are needed to enable automated analysis to fully quantitate mitochondrial signaling events and decipher their complex spatiotemporal connectedness. Herein, we present a protocol for recording and automating analyses of signaling in neuronal mitochondrial networks.
线粒体是具有多方面作用的复杂细胞器,作为信号枢纽,参与细胞生理学和病理学。线粒体既是多种信号事件的靶点,也是其起源,包括氧化还原过程和钙信号,这些对于细胞器的功能和动态平衡都很重要。一种研究线粒体功能的方法是进行活细胞成像。详细的方法可以对活细胞和动物中的单个线粒体动态进行成像。由于线粒体数量众多,以及信号的速度、传播和潜在的短半衰期,因此对线粒体信号和功能进行成像具有挑战性。此外,线粒体在功能上被耦联的细胞器网络所组织。因此,需要先进的分析和后处理工具来实现自动分析,以充分量化线粒体信号事件,并解析其复杂的时空关联性。本文中,我们提出了一种记录和自动分析神经元线粒体网络中信号的方案。