Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification
Nat Methods. 2022-06-13; 19(7): 881-892
DOI: 10.1038/s41592-022-01508-0
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Beghin A(1)(2)(3), Grenci G(4)(5), Sahni G(4), Guo S(4), Rajendiran H(4), Delaire T(6), Mohamad Raffi SB(4), Blanc D(7), de Mets R(4), Ong HT(4), Galindo X(6), Monet A(4), Acharya V(4), Racine V(7), Levet F(6)(8), Galland R(6), Sibarita JB(9), Viasnoff V(10)(11)(12).
Author information:
(1)Mechanobiology Institute, National University of Singapore, Singapore, Singapore. .
(2)Immunology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. .
(3)Department of Microbiology and Immunology, National University of Singapore, Singapore, Singapore. .
(4)Mechanobiology Institute, National University of Singapore, Singapore, Singapore.
(5)Biomedical Engineering Department, National University of Singapore, Singapore, Singapore.
(6)University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, Bordeaux, France.
(7)QuantaCell, Pessac, France.
(8)University Bordeaux, CNRS, INSERM, Bordeaux Imaging Center, BIC, UAR 3420, US 4, Bordeaux, France.
(9)University of Bordeaux, CNRS, Interdisciplinary Institute for Neuroscience, IINS, UMR 5297, Bordeaux, France. .
(10)Mechanobiology Institute, National University of Singapore, Singapore, Singapore. .
(11)Department of Biological Sciences, National University of Singapore, Singapore, Singapore. .
(12)IRL 3639 CNRS, Singapore, Singapore. .
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.
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.