发布: 2019年12月05日第9卷第23期 DOI: 10.21769/BioProtoc.3450 浏览次数: 3998
评审: Juan Facundo Rodriguez AyalaSamantha E. R. DundonGunjan Mehta
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一种基于流式细胞术的利用基因编码荧光报告测定酵母活细胞内pH值的方法
Catherine G. Triandafillou and D. Allan Drummond
2020年06月20日 3920 阅读
Abstract
Mitochondria are double-membraned organelles responsible for several functions in the cell including energy production, calcium signaling, and cellular metabolism. An equilibrium between fission and fusion events of mitochondria is required for their proper functioning. Mitochondrial morphologies have been quantified in yeast using image processing modules such as MitoGraph and MitoLoc. However, the dynamics of mitochondrial fission and fusion have not been analyzed in these methods. Here, we present a method for measuring mitochondrial morphologies, as well as estimation of fission and fusion frequencies of mitochondria in individual fission yeast cells whose mitochondria are fluorescently-tagged or stained. The latter relies on counting of individual mitochondria upon signal filtering in each frame of a time-lapse. Taken together, we present a simple protocol for analyzing mitochondrial dynamics, which can easily be adopted to other model systems.
Keywords: Mitochondria (线粒体)Background
Mitochondria are essential organelles present in the form of tubular networks within cells and constantly undergo fission and fusion events throughout the cell cycle. The rate of fission and fusion events determine the morphology of the mitochondria and this is a crucial determinant of their function (Mishra and Chan, 2016). Several factors contribute to the changes in morphology of the mitochondria. For instance, mitochondrial fission can be induced by stress, metabolic state, aging and in certain diseases (Sprenger and Langer, 2019). On the contrary, mitochondrial fusion can be induced to enhance cellular respiration in starved conditions and to dilute the effects of damaged mitochondrial DNA that may be present inside the cell (Westermann, 2010). Additionally, mitochondrial dynamics can drastically vary between cell types depending on the metabolic need of the given cell type. Since mitochondrial dynamics and thereby form are direct readouts for mitochondrial and cellular function, it is imperative to accurately measure these properties.
Early quantification efforts involved the use of qualitative descriptors to assess diverse mitochondrial morphologies. In recent times, computational image processing algorithms are being used to robustly quantify the differences in mitochondrial morphologies. For instance, the image processing module ‘MitoLoc’ uses the 3D reconstruction and analysis software, ‘MitoMap’ (a plugin for ImageJ) to define an object using Otsu thresholding and then calculates mitochondrial fragmentation, condensation and tubularity using mitochondrial shape descriptors such as mitochondrial size, position and integrity to differentiate the diverse mitochondrial phenotypes in budding yeast (Vowinckel et al., 2015). MitoLoc calculates the fragmentation of mitochondria using a fragmentation index f, which is defined as the sum of relative fragment volumes that individually constitute less than 20% of the total mitochondrial volume. Another open-source image analysis platform named ‘MitoGraph’ has been employed to quantify mitochondrial morphology in both yeast and mammalian cells (Viana et al., 2015; Harwig et al., 2018).
MitoGraph is an automated image processing software which performs graph theory-based quantitative analysis of mitochondrial networks by calculating the volumes of three-dimensional organelles in living cells. For both of these modules to provide accurate morphological data, it is imperative to utilize the best practices for imaging mitochondria by using the most optimal mitochondrial markers as well as high resolution imaging techniques. However, both of these modules do not provide quantitative measurements for mitochondrial fission and fusion dynamics. Here, we detail a simple method for quantifying both mitochondrial morphologies, as well as fission and fusion dynamics.
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版权信息
© 2019 The Authors; exclusive licensee Bio-protocol LLC.
如何引用
Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
分类
细胞生物学 > 细胞成像 > 活细胞成像
细胞生物学 > 细胞成像 > 荧光
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