Quantitative analysis of subcellular distributions with an open-source, object-based tool.
Quantitative analysis of subcellular distributions with an open-source, object-based tool.
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DOI：
10.1242/bio.055228
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发表时间：
2020-10-19
期刊：
影响因子：
2.4
通讯作者：
Lerit DA
中科院分区：
文献类型：
--
作者：
Ryder PV;Lerit DA
细胞器、蛋白质或其他分子等物体的亚细胞定位指示细胞的形式和功能。通过显微镜图像的共定位分析来理解对象之间的潜在空间关系是用于告知生物机制的基本方法。我们生成了一个自动化和可定制的计算工具，SubcellarDistribution管道，以促进基于对象的图像分析，从三维（3D）荧光显微镜图像。为了测试SubcellarDistribution管道的实用性，我们研究了合胞体果蝇胚胎中mRNA相对于中心体的亚细胞分布。中心体是微管的组织中心，RNA在中心体的富集越来越重要。我们的开源和免费软件检测到的RNA分布与商业上可用的图像分析软件相当。SubcellarDistribution管道旨在指导用户完成准备用于发布的图像分析数据的完整过程，从图像分割和数据处理到可视化。总结：SubcellarDistribution pipeline是一个开源、自动化和可定制的工具，可指导用户通过图像分割、数据处理和可视化来分析荧光显微镜图像中基于对象的共定位。
The subcellular localization of objects, such as organelles, proteins, or other molecules, instructs cellular form and function. Understanding the underlying spatial relationships between objects through colocalization analysis of microscopy images is a fundamental approach used to inform biological mechanisms. We generated an automated and customizable computational tool, the SubcellularDistribution pipeline, to facilitate object-based image analysis from three-dimensional (3D) fluorescence microcopy images. To test the utility of the SubcellularDistribution pipeline, we examined the subcellular distribution of mRNA relative to centrosomes within syncytial Drosophila embryos. Centrosomes are microtubule-organizing centers, and RNA enrichments at centrosomes are of emerging importance. Our open-source and freely available software detected RNA distributions comparably to commercially available image analysis software. The SubcellularDistribution pipeline is designed to guide the user through the complete process of preparing image analysis data for publication, from image segmentation and data processing to visualization. Summary: The SubcellularDistribution pipeline is an open-source, automated, and customizable tool that guides users through image segmentation, data processing and visualization to analyze object-based colocalization within fluorescence microscopy images.