GliaMorph: a modular image analysis toolkit to quantify Müller glial cell morphology.
GliaMorph: a modular image analysis toolkit to quantify Müller glial cell morphology.
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DOI：
10.1242/dev.201008
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发表时间：
2023-02-15
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影响因子：
--
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中科院分区：
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细胞形态对所有细胞功能都至关重要。这对于神经胶质细胞尤其如此，因为它们依赖于复杂的形状来接触和支持神经元。然而，方法来量化复杂的胶质细胞形状准确和可重复的是缺乏的。为了解决这个问题，我们开发了图像分析管道“GliaMorph”。GliaMorph是一个模块化分析工具包，用于执行（1）图像预处理，（2）半自动感兴趣区域选择，（3）顶基底纹理分析，（4）神经胶质分割和（5）细胞特征量化。Müller神经胶质（MG）具有与其成熟和生理状态相关的刻板形状。在这里，我们在三个层次上表征MG：（1）全局图像级，（2）顶基底纹理，和（3）区域顶基底垂直到水平对齐。使用GliaMorph，我们在全球和单细胞水平上量化了MG的发展，显示了斑马鱼视网膜中增加的功能阐述和亚细胞形态重排。作为原理的证明，我们分析了小鼠青光眼模型中的表达变化，鉴定了MG中的亚细胞蛋白定位变化。总之，这些数据表明，GliaMorph能够深入了解发育和患病视网膜中的MG形态。摘要：GliaMorph允许进行多维Muller神经胶质细胞分析，实现图像级以及亚细胞形态评估，这些评估具有鲁棒性，适应性强且易于使用。
Cell morphology is crucial for all cell functions. This is particularly true for glial cells as they rely on complex shape to contact and support neurons. However, methods to quantify complex glial cell shape accurately and reproducibly are lacking. To address this, we developed the image analysis pipeline ‘GliaMorph’. GliaMorph is a modular analysis toolkit developed to perform (1) image pre-processing, (2) semi-automatic region-of-interest selection, (3) apicobasal texture analysis, (4) glia segmentation, and (5) cell feature quantification. Müller glia (MG) have a stereotypic shape linked to their maturation and physiological status. Here, we characterized MG on three levels: (1) global image-level, (2) apicobasal texture, and (3) regional apicobasal vertical-to-horizontal alignment. Using GliaMorph, we quantified MG development on a global and single-cell level, showing increased feature elaboration and subcellular morphological rearrangement in the zebrafish retina. As proof of principle, we analysed expression changes in a mouse glaucoma model, identifying subcellular protein localization changes in MG. Together, these data demonstrate that GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina. Summary: GliaMorph allows for multi-dimensional Muller glial cell analysis, enabling image-level as well as subcellular morphological assessments that are robust, adaptable and easy to use.
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DOI：
10.1002/cpz1.654
发表时间：
2023-01
期刊：
Current protocols
影响因子：
--
作者：
Kugler, Elisabeth;Breitenbach, Eva-Maria;MacDonald, Ryan
通讯作者：
MacDonald, Ryan
影响因子：
5.5
作者：
Angueyra JM;Kindt KS
通讯作者：
Kindt KS
影响因子：
4.6
作者：
Kimura, Yukiko;Satou, Chie;Higashijima, Shin-ichi
通讯作者：
Higashijima, Shin-ichi
影响因子：
6.2
作者：
Charlton-Perkins, Mark;Almeida, Alexandra D.;Harris, William A.
通讯作者：
Harris, William A.
影响因子：
4.5
作者：
Borgefors, G
通讯作者：
Borgefors, G