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Cerebral Organoid Arrays for Batch Phenotypic Analysis in Sections and Three Dimensions.

Authors :
Chen, Juan
Ma, Haihua
Deng, Zhiyu
Luo, Qingming
Gong, Hui
Long, Ben
Li, Xiangning
Source :
International Journal of Molecular Sciences. Sep2023, Vol. 24 Issue 18, p13903. 16p.
Publication Year :
2023

Abstract

Organoids can recapitulate human-specific phenotypes and functions in vivo and have great potential for research in development, disease modeling, and drug screening. Due to the inherent variability among organoids, experiments often require a large sample size. Embedding, staining, and imaging each organoid individually require a lot of reagents and time. Hence, there is an urgent need for fast and efficient methods for analyzing the phenotypic changes in organoids in batches. Here, we provide a comprehensive strategy for array embedding, staining, and imaging of cerebral organoids in both agarose sections and in 3D to analyze the spatial distribution of biomarkers in organoids in situ. We constructed several disease models, particularly an aging model, as examples to demonstrate our strategy for the investigation of the phenotypic analysis of organoids. We fabricated an array mold to produce agarose support with microwells, which hold organoids in place for live/dead imaging. We performed staining and imaging of sectioned organoids embedded in agarose and 3D imaging to examine phenotypic changes in organoids using fluorescence micro-optical sectioning tomography (fMOST) and whole-mount immunostaining. Parallel studies of organoids in arrays using the same staining and imaging parameters enabled easy and reliable comparison among different groups. We were able to track all the data points obtained from every organoid in an embedded array. This strategy could help us study the phenotypic changes in organoids in disease models and drug screening. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16616596
Volume :
24
Issue :
18
Database :
Academic Search Index
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
172424152
Full Text :
https://doi.org/10.3390/ijms241813903