Multiscale 3D phenotyping of human cerebral organoids
Name
s41598-020-78130-7.pdf
Description
Published version
Size
8.83 MB
Format
Adobe PDF
Checksum (MD5)
692e572424456f1f465045185a7ccc04
Author(s)
Albanese, Alexandre
Swaney, Justin M
Yun, Dae Hee
Evans, Nicholas B
Antonucci, Jenna M
Velasco, Silvia
Sohn, Chang Ho
Arlotta, Paola
Gehrke, Lee
Chung, Kwanghun
Date Issued
2020
Journal
Scientific Reports
Publisher
Springer Science and Business Media LLC
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Picower Institute for Learning and Memory
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
10.1038/s41598-020-78130-7
https://doi.org/10.1038/s41598-020-78130-7
