Mechanobiology Institute, National University of Singapore, Singapore, Singapore.
Immunology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Nat Methods. 2022 Jul;19(7):881-892. doi: 10.1038/s41592-022-01508-0. Epub 2022 Jun 13.
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.
当前的成像方法限制了对大量三维(3D)器官型培养物(类器官)进行多尺度表征的能力。在这里,我们提出了一种自动化的多尺度 3D 成像平台,该平台将高密度类器官培养物与快速和实时的 3D 单目标光片成像相结合。它由一次性微加工的类器官培养芯片(称为 JeWells)组成,其中嵌入了光学组件和与商用倒置显微镜耦合的激光束转向单元。它允许在单个用户友好的仪器上简化类器官培养和高内涵 3D 成像,操作最少,每小时可处理 300 个类器官。我们证明,通过我们的平台可以收集大量的 3D 堆栈,这使得可以训练基于深度学习的算法来定量分析多尺度的类器官形态发生组织,范围从亚细胞尺度到整个类器官水平。我们在肠、肝、神经外胚层类器官和oncospheres 上验证了我们方法的多功能性和鲁棒性。