bioRxivBiophysicsPreprint
High content 3D imaging method for quantitative characterization of organoid development and phenotype.
A. Beghin, G. Grenci, H. Rajendiran, T. Delaire, S. B. M. Raffi, D. Blanc, R. De Mets, H. T. Ong, V. Acharya, G. Sahni, V. Racine, R. Galland, J.-B. Sibarita, V. Viasnoff
Abstract
Quantitative analysis on a large number of organoids can provide meaningful information from the morphological variability observed in 3D organotypic cultures, called organoids. Yet, gathering statistics of growing organoids is currently limited by existing imaging methods and subsequent image analysis workflows that are either restricted to 2D, limited in resolution, or with a low throughput. Here, we present an automated high content imaging platform synergizing high density organoid cultures with 3D live light-sheet imaging. The platform is an add-on to a standard inverted microscope. We demonstrate our capacity to collect libraries of 3D images at a rate of 300 organoids per hour, enabling training of artificial intelligence-based algorithms to quantify the organoid morphogenetic organization at multiple scales with subcellular resolution. We validate our approach on different organotypic cell cultures (stem, primary, and cancer), and quantify the development of hundreds of neuroectoderm organoids (from human Embryonic Stem Cells) at cellular, multicellular and whole organoid scales.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- approach: deep learning
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