类有机物
计算机科学
高含量筛选
稳健性(进化)
纳米技术
生物
细胞生物学
材料科学
遗传学
细胞
生物化学
基因
作者
Anne Béghin,Gianluca Grenci,Geetika Sahni,Su Guo,Harini Rajendiran,Tom Delaire,Saburnisha Binte Mohamad Raffi,D Blanc,Richard De Mets,Hui Ting Ong,Xareni Galindo,Anais Monet,Vidhyalakshmi Acharya,Victor Racine,Florian Levet,Rémi Galland,Jean‐Baptiste Sibarita,Virgile Viasnoff
出处
期刊:Nature Methods
[Springer Nature]
日期:2022-06-13
卷期号:19 (7): 881-892
被引量:67
标识
DOI:10.1038/s41592-022-01508-0
摘要
Current imaging approaches limit the ability to perform multi-scale characterization of three-dimensional (3D) organotypic cultures (organoids) in large numbers. Here, we present an automated multi-scale 3D imaging platform synergizing high-density organoid cultures with rapid and live 3D single-objective light-sheet imaging. It is composed of disposable microfabricated organoid culture chips, termed JeWells, with embedded optical components and a laser beam-steering unit coupled to a commercial inverted microscope. It permits streamlining organoid culture and high-content 3D imaging on a single user-friendly instrument with minimal manipulations and a throughput of 300 organoids per hour. We demonstrate that the large number of 3D stacks that can be collected via our platform allows training deep learning-based algorithms to quantify morphogenetic organizations of organoids at multi-scales, ranging from the subcellular scale to the whole organoid level. We validated the versatility and robustness of our approach on intestine, hepatic, neuroectoderm organoids and oncospheres.
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