标题： 单细胞分辨率的完整活组织三维成像与分割 显示英文标题

标题： Single cell resolution 3D imaging and segmentation within intact live tissues

摘要： 上皮细胞从扁平球形类器官到紧密排列的假层组织形成多种结构。 在这些情况下对细胞特性进行量化需要高分辨率的深层成像和计算技术，以实现真实的三维（3D）结构特征。 在这里，我们描述了一个详细的分步协议，用于样本制备、成像和深度学习辅助的细胞分割，以在活体组织中准确量化荧光标记的单个细胞。 我们分享了在解决果蝇翅膀盘的3D成像问题时学到的经验，包括关于显微镜模式和设置（物镜、样本装载）以及可用的分割方法的考虑因素。 此外，我们还包括一个计算流程以及自定义代码，以帮助复制该协议。 虽然我们专注于从膜标记中分割细胞轮廓，但该协议适用于各种样本，我们认为它对于需要复杂分析的其他组织的研究是有价值的。 显示英文摘要

摘要： Epithelial cells form diverse structures from squamous spherical organoids to densely packed pseudostratified tissues. Quantification of cellular properties in these contexts requires high-resolution deep imaging and computational techniques to achieve truthful three-dimensional (3D) structural features. Here, we describe a detailed step-by-step protocol for sample preparation, imaging and deep-learning-assisted cell segmentation to achieve accurate quantification of fluorescently labelled individual cells in 3D within live tissues. We share the lessons learned through troubleshooting 3D imaging of Drosophila wing discs, including considerations on the choice of microscopy modality and settings (objective, sample mounting) and available segmentation methods. In addition, we include a computational pipeline alongside custom code to assist replication of the protocol. While we focus on the segmentation of cell outlines from membrane labelling, this protocol applies to a wide variety of samples, and we believe it be valuable for studying other tissues that demand complex analysis in 3D.