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Abstract
Brain organoids grown from human pluripotent stem cells self-organize into cytoarchitectures resembling the developing human brain. These three-dimensional models offer an unprecedented opportunity to study human brain development and dysfunction. Characterization currently sacrifices spatial information for single-cell or histological analysis leaving whole-tissue analysis mostly unexplored. Here, we present the SCOUT pipeline for automated multiscale comparative analysis of intact cerebral organoids. Our integrated technology platform can rapidly clear, label, and image intact organoids. Algorithmic- and convolutional neural network-based image analysis extract hundreds of features characterizing molecular, cellular, spatial, cytoarchitectural, and organoid-wide properties from fluorescence microscopy datasets. Comprehensive analysis of 46 intact organoids and ~ 100 million cells reveals quantitative multiscale “phenotypes" for organoid development, culture protocols and Zika virus infection. SCOUT provides a much-needed framework for comparative analysis of emerging 3D in vitro models using fluorescence microscopy.
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1 MIT, Institute for Medical Engineering and Science, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
2 MIT, Department of Chemical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
3 MIT, Institute for Medical Engineering and Science, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
4 MIT, Institute for Medical Engineering and Science, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
5 Harvard University, Department of Stem Cell and Regenerative Biology, Cambridge, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, USA (GRID:grid.66859.34)
6 MIT, Institute for Medical Engineering and Science, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Harvard Medical School, Department of Microbiology and Immunobiology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Harvard–MIT Program in Health Sciences and Technology, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786)
7 MIT, Institute for Medical Engineering and Science, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Department of Chemical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); MIT, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Institute for Basic Science (IBS), Center for Nanomedicine, Seoul, Republic of Korea (GRID:grid.410720.0) (ISNI:0000 0004 1784 4496); Yonsei University, Yonsei-IBS Institute, Seoul, Republic of Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454)