4D cell biology: big data image analytics and lattice light-sheet imaging reveal dynamics of clathrin-mediated endocytosis in stem cell-derived intestinal organoids

4D 细胞生物学:大数据图像分析和晶格光片成像揭示干细胞衍生的肠道类器官中网格蛋白介导的内吞作用的动态

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作者:Johannes Schöneberg, Daphné Dambournet, Tsung-Li Liu, Ryan Forster, Dirk Hockemeyer, Eric Betzig, David G Drubin

Abstract

New methods in stem cell 3D organoid tissue culture, advanced imaging, and big data image analytics now allow tissue-scale 4D cell biology, but currently available analytical pipelines are inadequate for handing and analyzing the resulting gigabytes and terabytes of high-content imaging data. We expressed fluorescent protein fusions of clathrin and dynamin2 at endogenous levels in genome-edited human embryonic stem cells, which were differentiated into hESC-derived intestinal epithelial organoids. Lattice light-sheet imaging with adaptive optics (AO-LLSM) allowed us to image large volumes of these organoids (70 × 60 × 40 µm xyz) at 5.7 s/frame. We developed an open-source data analysis package termed pyLattice to process the resulting large (∼60 Gb) movie data sets and to track clathrin-mediated endocytosis (CME) events. CME tracks could be recorded from ∼35 cells at a time, resulting in ∼4000 processed tracks per movie. On the basis of their localization in the organoid, we classified CME tracks into apical, lateral, and basal events and found that CME dynamics is similar for all three classes, despite reported differences in membrane tension. pyLattice coupled with AO-LLSM makes possible quantitative high temporal and spatial resolution analysis of subcellular events within tissues.

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