Schmied Christopher, Stamataki Evangelia, Tomancak Pavel
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
Methods Cell Biol. 2014;123:505-29. doi: 10.1016/B978-0-12-420138-5.00027-6.
Light sheet microscopy is an emerging technique allowing comprehensive visualization of dynamic biological processes, at high spatial and temporal resolution without significant damage to the sample by the imaging process itself. It thus lends itself to time-lapse observation of fluorescently labeled molecular markers over long periods of time in a living specimen. In combination with sample rotation light sheet microscopy and in particular its selective plane illumination microscopy (SPIM) flavor, enables imaging of relatively large specimens, such as embryos of animal model organisms, in their entirety. The benefits of SPIM multiview imaging come to the cost of image data postprocessing necessary to deliver the final output that can be analyzed. Here, we provide a set of practical recipes that walk biologists through the complex processes of SPIM data registration, fusion, deconvolution, and time-lapse registration using publicly available open-source tools. We explain, in plain language, the basic principles behind SPIM image-processing algorithms that should enable users to make informed decisions during parameter tuning of the various processing steps applied to their own datasets. Importantly, the protocols presented here are applicable equally to processing of multiview SPIM data from the commercial Zeiss Lightsheet Z.1 microscope and from the open-access SPIM platforms such as OpenSPIM.
光片显微镜是一种新兴技术，能够在高空间和时间分辨率下全面可视化动态生物过程，且成像过程本身对样本造成的损伤极小。因此，它适用于在活体样本中长时间对荧光标记的分子标记物进行延时观察。结合样本旋转，光片显微镜，尤其是其选择性平面照明显微镜（SPIM）模式，能够对相对较大的样本，如动物模式生物的胚胎进行整体成像。SPIM多视图成像的优势是以图像数据后处理为代价的，而这些后处理对于生成可分析的最终输出结果是必要的。在这里，我们提供了一套实用的方法，指导生物学家使用公开可用的开源工具，完成SPIM数据配准、融合、去卷积和延时配准的复杂过程。我们用通俗易懂的语言解释了SPIM图像处理算法背后的基本原理，这将帮助用户在对自己的数据集应用各种处理步骤进行参数调整时做出明智的决策。重要的是，这里介绍的协议同样适用于处理来自商业蔡司光片Z.1显微镜以及诸如OpenSPIM等开放获取的SPIM平台的多视图SPIM数据。
