Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning
Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning
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DOI：
10.7554/elife.40946
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发表时间：
2019-01
期刊：
影响因子：
7.7
通讯作者：
S. Urata;T. Iida;Masamichi Yamamoto;Y. Mizushima;C. Fujimoto;Yu Matsumoto;T. Yamasoba;S. Okabe
中科院分区：
文献类型：
--
作者：
S. Urata;T. Iida;Masamichi Yamamoto;Y. Mizushima;C. Fujimoto;Yu Matsumoto;T. Yamasoba;S. Okabe
Corti器官中感觉毛细胞的高度组织化的空间排列对内耳功能至关重要。在这里，我们报告了一个新的分析管道，基于组织的光学清除，用于构建Corti器官的单细胞分辨率图。一种基于甲醇的光学透明方法能够以亚细胞分辨率对整个耳蜗进行成像。通过基于机器学习的模式识别，自动执行沿Corti器官的整个纵轴沿着的所有毛细胞位置的高保真检测和分析。应用这种方法从年轻，成年和噪声暴露的小鼠样本提取细胞病理学的基本信息，包括纵向和径向的空间特征的细胞损失，这意味着多个机制的基础群集细胞损失。我们的细胞定位方法是有效的生理和病理条件下的Corti器官的系统级表型。
The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution map of the organ of Corti. A sorbitol-based optical clearing method enabled imaging of the entire cochlea at subcellular resolution. High-fidelity detection and analysis of all hair cell positions along the entire longitudinal axis of the organ of Corti were performed automatically by machine learning–based pattern recognition. Application of this method to samples from young, adult, and noise-exposed mice extracted essential information regarding cellular pathology, including longitudinal and radial spatial characteristics of cell loss, implying that multiple mechanisms underlie clustered cell loss. Our method of cellular mapping is effective for system-level phenotyping of the organ of Corti under both physiological and pathological conditions.