Rapid methods for the evaluation of fluorescent reporters in tissue clearing and the segmentation of large vascular structures

作     者：Kirschnick, Nils Drees, Dominik Redder, Esther Erapaneedi, Raghu da Graca, Abel Pereira Schafers, Michael Jiang, Xiaoyi Kiefer, Friedemann 

作者机构：Univ Munster European Inst Mol Imaging Waldeyerstr 15 D-48149 Munster Germany Univ Munster Inst Comp Sci Einsteinstr 62 D-48149 Munster Germany Carl Zeiss Microscopy GmbH Zeiss Res Microscopy Solut Zeiss Microscopy Customer Ctr Europe Rudolf Eber Str 2 D-73447 Oberkochen Germany 

出 版 物：《ISCIENCE》 (iScience)

年 卷 期：2021年第24卷第6期

页      面：102650页

核心收录：

基　　金：Deutsche Forschungsgemeinschaft [SFB1348/1 -386797833, SFB1450/1 -431460824] Max Planck Society CiM-IMPRS, the joint graduate school of the Cells-in-Motion Cluster of Excellence, University of Munster, Germany [EXC 1003 -CiM] International Max Planck Research School -Molecular Biomedicine, Munster, Germany 

主　　题：Optical imaging computational bioinformatics 

摘      要：Light sheet fluorescence microscopy (LSFM) of large tissue samples does not require mechanical sectioning and allows efficient visualization of spatially complex or rare structures. Therefore, LSFMhas become invaluable in developmental and biomedical research. Because sample size may limit whole-mount staining, LSFM benefits from transgenic reporter organisms expressing fluorescent proteins (FPs) and, however, requires optical clearing and computational data visualization and analysis. The former often interferes with FPs, while the latter requires massive computing resources. Here, we describe 3D-polymerized cell dispersions, a rapid and straightforward method, based on recombinant FP expression in freely selectable tester cells, to evaluate and compare fluorescence retention in different tissue-clearing protocols. For the analysis of large LSFM data, which usually requires huge computing resources, we introduce a refined, interactive, hierarchical random walker approach that is capable of efficient segmentation of the vasculature in data sets even on a consumer grade PC.