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CiliaQ:一款简单的开源软件,用于在 2D、3D 和 4D 图像中自动定量分析纤毛形态和荧光。

CiliaQ: a simple, open-source software for automated quantification of ciliary morphology and fluorescence in 2D, 3D, and 4D images.

机构信息

Institute of Innate Immunity, Biophysical Imaging, Medical Faculty, University of Bonn, 53127, Bonn, Germany.

Department of Clinical and Molecular Medicine, The Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.

出版信息

Eur Phys J E Soft Matter. 2021 Mar 8;44(2):18. doi: 10.1140/epje/s10189-021-00031-y.

Abstract

Cilia are hair-like membrane protrusions that emanate from the surface of most vertebrate cells and are classified into motile and primary cilia. Motile cilia move fluid flow or propel cells, while also fulfill sensory functions. Primary cilia are immotile and act as a cellular antenna, translating environmental cues into cellular responses. Ciliary dysfunction leads to severe diseases, commonly termed ciliopathies. The molecular details underlying ciliopathies and ciliary function are, however, not well understood. Since cilia are small subcellular compartments, imaging-based approaches have been used to study them. However, tools to comprehensively analyze images are lacking. Automatic analysis approaches require commercial software and are limited to 2D analysis and only a few parameters. The widely used manual analysis approaches are time consuming, user-biased, and difficult to compare. Here, we present CiliaQ, a package of open-source, freely available, and easy-to-use ImageJ plugins. CiliaQ allows high-throughput analysis of 2D and 3D, static or time-lapse images from fluorescence microscopy of cilia in cell culture or tissues, and outputs a comprehensive list of parameters for ciliary morphology, length, bending, orientation, and fluorescence intensity, making it broadly applicable. We envision CiliaQ as a resource and platform for reproducible and comprehensive analysis of ciliary function in health and disease.

摘要

纤毛是从大多数脊椎动物细胞表面伸出的毛发状膜突,分为运动纤毛和初级纤毛。运动纤毛推动液体流动或推动细胞运动,同时还具有感觉功能。初级纤毛不运动,充当细胞天线,将环境信号转化为细胞反应。纤毛功能障碍会导致严重疾病,通常称为纤毛病。然而,纤毛病和纤毛功能的分子细节尚不清楚。由于纤毛是微小的亚细胞区室,因此基于成像的方法已被用于研究它们。然而,缺乏全面分析图像的工具。自动分析方法需要商业软件,并且仅限于 2D 分析和仅少数几个参数。广泛使用的手动分析方法既耗时、又容易受到用户偏见的影响,并且难以进行比较。在这里,我们提出了 CiliaQ,这是一个开源、免费且易于使用的 ImageJ 插件包。CiliaQ 允许对细胞培养或组织中的荧光显微镜下的纤毛的 2D 和 3D、静态或时间推移图像进行高通量分析,并输出用于纤毛形态、长度、弯曲、方向和荧光强度的综合参数列表,具有广泛的适用性。我们设想 CiliaQ 是一个资源和平台,用于在健康和疾病中对纤毛功能进行可重复和全面的分析。

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