COMBin 可实现组织透明化的小鼠大脑中神经元和星形胶质细胞的自动检测和分类。
COMBINe enables automated detection and classification of neurons and astrocytes in tissue-cleared mouse brains.
机构信息
Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC, USA.
Comparative Medicine Institute, North Carolina State University, Raleigh, NC, USA.
出版信息
Cell Rep Methods. 2023 Apr 18;3(4):100454. doi: 10.1016/j.crmeth.2023.100454. eCollection 2023 Apr 24.
Tissue clearing renders entire organs transparent to accelerate whole-tissue imaging; for example, with light-sheet fluorescence microscopy. Yet, challenges remain in analyzing the large resulting 3D datasets that consist of terabytes of images and information on millions of labeled cells. Previous work has established pipelines for automated analysis of tissue-cleared mouse brains, but the focus there was on single-color channels and/or detection of nuclear localized signals in relatively low-resolution images. Here, we present an automated workflow (COMBINe, Cell detectiOn in Mouse BraIN) to map sparsely labeled neurons and astrocytes in genetically distinct mouse forebrains using mosaic analysis with double markers (MADM). COMBINe blends modules from multiple pipelines with RetinaNet at its core. We quantitatively analyzed the regional and subregional effects of MADM-based deletion of the epidermal growth factor receptor (EGFR) on neuronal and astrocyte populations in the mouse forebrain.
组织透明化技术可将整个器官变得透明，从而加速整个组织的成像；例如，采用光片荧光显微镜。然而，在分析由数太字节的图像和数百万个标记细胞的信息组成的大型 3D 数据集时，仍然存在挑战。以前的工作已经为自动分析组织透明化的小鼠大脑建立了管道，但重点是单通道颜色和/或在相对低分辨率的图像中检测核定位信号。在这里，我们提出了一种自动化工作流程（COMBINe，小鼠大脑中的细胞检测），使用双标记马赛克分析（MADM）来绘制遗传上不同的小鼠前脑中稀疏标记的神经元和星形胶质细胞。COMBINe 将来自多个管道的模块与 RetinaNet 融合在一起，作为其核心。我们定量分析了基于 MADM 的表皮生长因子受体（EGFR）缺失对小鼠前脑神经元和星形胶质细胞群体的区域性和亚区域性影响。
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