High-dimensional cell-level analysis of tissues with Ce3D multiplex volume imaging.

Clicks: 354
ID: 2745
2019
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Abstract
Understanding the structure-function relationships between diverse cell types in a complex organ environment requires detailed in situ reconstruction of cell-associated molecular properties in the context of 3D, macro-scale tissue architecture. We recently developed clearing-enhanced 3D (Ce3D), a simple and effective method for tissue clearing that achieves excellent transparency; preserves cell morphology, tissue architecture, and reporter molecule fluorescence; and is robustly compatible with direct immunolabeling. These characteristics permit high-quality multiplex fluorescence microscopy of large tissue volumes, as well as image analysis using advanced platforms such as volumetric histocytometry, collectively allowing quantitative characterization of cells with respect to their spatial positioning within tissues on the basis of phenotypic and functional markers. Ce3D clearing is fast, achieving robust transparency of most tissues within 24 h, albeit still necessitating additional time for staining, imaging, and analysis (1-2 weeks). Here, we provide detailed procedures for tissue clearing using Ce3D, including optimized workflows for tissue processing and staining, as well as treatment of difficult-to-clear organs such as the brain. We also describe a new procedure for RNA detection in Ce3D-treated tissues, as well as provide additional details for the volumetric histocytometry data processing steps. Finally, we discuss limitations and work-around strategies for improving antibody-based tissue immunolabeling, fluorophore multiplexing, large-volume microscopy, and computational analysis of large image datasets. Together, these detailed procedures and solutions for high-resolution volumetric microscopy with Ce3D enable quantitative visualization of cells and tissues at a high level of detail, allowing exploration of cellular spatial relationships in a variety of tissue settings.
Reference Key
li2019highdimensionalnature Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Li, Weizhe;Germain, Ronald N;Gerner, Michael Y;
Journal nature protocols
Year 2019
DOI
10.1038/s41596-019-0156-4
URL
Keywords Keywords not found

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