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Tutorial: practical considerations for tissue clearing and imaging
Nature Protocols ( IF 14.8 ) Pub Date : 2021-05-21 , DOI: 10.1038/s41596-021-00502-8
Kurt R Weiss 1 , Fabian F Voigt 2, 3 , Douglas P Shepherd 4, 5 , Jan Huisken 1, 6
Affiliation  

Tissue clearing has become a powerful technique for studying anatomy and morphology at scales ranging from entire organisms to subcellular features. With the recent proliferation of tissue-clearing methods and imaging options, it can be challenging to determine the best clearing protocol for a particular tissue and experimental question. The fact that so many clearing protocols exist suggests there is no one-size-fits-all approach to tissue clearing and imaging. Even in cases where a basic level of clearing has been achieved, there are many factors to consider, including signal retention, staining (labeling), uniformity of transparency, image acquisition and analysis. Despite reviews citing features of clearing protocols, it is often unknown a priori whether a protocol will work for a given experiment, and thus some optimization is required by the end user. In addition, the capabilities of available imaging setups often dictate how the sample needs to be prepared. After imaging, careful evaluation of volumetric image data is required for each combination of clearing protocol, tissue type, biological marker, imaging modality and biological question. Rather than providing a direct comparison of the many clearing methods and applications available, in this tutorial we address common pitfalls and provide guidelines for designing, optimizing and imaging in a successful tissue-clearing experiment with a focus on light-sheet fluorescence microscopy (LSFM).



中文翻译:

教程:组织透明化和成像的实际考虑因素

组织透明化已成为研究从整个生物体到亚细胞特征的解剖学和形态学的强大技术。随着最近组织透明化方法和成像选项的激增,确定特定组织和实验问题的最佳透明化方案可能具有挑战性。存在如此多的透明化方案这一事实表明,没有一种通用的组织透明化和成像方法。即使在已经实现基本透明水平的情况下,也需要考虑许多因素,包括信号保留、染色(标记)、透明度的均匀性、图像采集和分析。尽管评论引用了清除协议的功能,但通常事先不知道协议是否适用于给定的实验,因此最终用户需要进行一些优化。此外,可用成像装置的功能通常决定需要如何制备样品。成像后,需要对清除方案、组织类型、生物标志物、成像模式和生物学问题的每种组合仔细评估体积图像数据。在本教程中,我们不是对许多可用的透明化方法和应用进行直接比较,而是解决常见的陷阱,并提供成功的组织透明化实验的设计、优化和成像指南,重点关注光片荧光显微镜 (LSFM) 。

更新日期:2021-05-22
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