Quantification of mitochondrial morphology in neurites of dopaminergic neurons using multiple parameters.
Quantification of mitochondrial morphology in neurites of dopaminergic neurons using multiple parameters.
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DOI：
10.1016/j.jneumeth.2016.01.008
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发表时间：
2016-03-15
影响因子：
3
通讯作者：
Lee D
中科院分区：
文献类型：
--
作者：
Wiemerslage L;Lee D
线粒体形态学的研究在技术上各不相同。大多数使用一个形态学参数，而其他定性描述线粒体。由于线粒体是如此动态，单个参数无法捕捉网络的真实状态，并可能导致错误的结论。因此，一种完形的分析方法是必要的。这项工作描述了一种方法结合免疫荧光测定与计算机图像分析，以测量线粒体形态神经炎预测的一个特定的神经元群体。使用ImageJ检查线粒体形态的六个参数以分析共定位信号。使用原代培养的果蝇神经元，我们测试了多巴胺（DA）神经元的轴突线粒体形态。我们验证我们的模型使用已知缺陷的线粒体形态突变体。此外，我们显示了作为对照或用神经毒素诱导PD（人类帕金森病）样病理处理的细胞之间线粒体形态的差异。我们还显示了形态参数和实验治疗之间的相互作用。我们的方法是以前描述的方法的一个重大改进。六个形态参数进行量化，提供了一个完形分析的线粒体形态。它还可以使用免疫荧光测定和图像分析靶向特定的线粒体群体。我们发现，我们的方法充分检测处理组之间线粒体形态的差异。我们的结论是，一些参数可能是独特的突变或疾病状态，参数之间的关系被实验治疗改变。我们建议，当使用线粒体结构作为实验终点时，至少应考虑四个变量。
Studies of mitochondrial morphology vary in techniques. Most use one morphological parameter while others describe mitochondria qualitatively. Because mitochondria are so dynamic, a single parameter does not capture the true state of the network and may lead to erroneous conclusions. Thus, a gestalt method of analysis is warranted. This work describes a method combining immunofluorescence assays with computerized image analysis to measure the mitochondrial morphology within neuritic projections of a specific population of neurons. Six parameters of mitochondrial morphology were examined utilizing ImageJ to analyze colocalized signals. Using primary neuronal cultures from Drosophila, we tested mitochondrial morphology in neurites of dopaminergic (DA) neurons. We validate our model using mutants with known defects in mitochondrial morphology. Furthermore, we show a difference in mitochondrial morphology between cells treated as control or with a neurotoxin inducing PD (Parkinson's Disease in humans)-like pathology. We also show interactions between morphological parameters and experimental treatment. Our method is a significant improvement of previously described methods. Six morphometric parameters are quantified, providing a gestalt analysis of mitochondrial morphology. Also it can target specific populations of mitochondria using immunofluorescence assay and image analysis. We found that our method adequately detects differences in mitochondrial morphology between treatment groups. We conclude that some parameters may be unique to a mutation or a disease state, and the relationship between parameters is altered by experimental treatment. We suggest at least four variables should be considered when using mitochondrial structure as an experimental endpoint.