A High-Throughput Platform for Culture and 3D Imaging of Organoids.

The characterization of a large number of three-dimensional (3D) organotypic cultures (organoids) at different resolution scales is currently limited by standard imaging approaches. This protocol describes a way to prepare microfabricated organoid culture chips, which enable multiscale, 3D live imaging on a user-friendly instrument requiring minimal manipulations and capable of up to 300 organoids/h imaging throughput. These culture chips are compatible with both air and immersion objectives (air, water, oil, and silicone) and a wide range of common microscopes (e.g., spinning disk, point scanner confocal, wide field, and brightfield). Moreover, they can be used with light-sheet modalities such as the single-objective, single-plane illumination microscopy (SPIM) technology (soSPIM). The protocol described here gives detailed steps for the preparation of the microfabricated culture chips and the culture and staining of organoids. Only a short length of time is required to become familiar with, and consumables and equipment can be easily found in normal biolabs. Here, the 3D imaging capabilities will be demonstrated only with commercial standard microscopes (e.g., spinning disk for 3D reconstruction and wide field microscopy for routine monitoring).

Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification.

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.