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Sci Rep. 2018 Mar 28;8(1):5319. doi: 10.1038/s41598-017-18815-8.

Automated brightfield morphometry of 3D organoid populations by OrganoSeg.

Author information

1
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
2
Hubrecht Institute for Developmental Biology and Stem Cell Research, 3584 CT, Utrecht, The Netherlands.
3
Department of Gastroenterology, Keio University School of Medicine, Tokyo, Japan.
4
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA. kjanes@virginia.edu.

Abstract

Spheroid and organoid cultures are powerful in vitro models for biology, but size and shape diversity within the culture is largely ignored. To streamline morphometric profiling, we developed OrganoSeg, an open-source software that integrates segmentation, filtering, and analysis for archived brightfield images of 3D culture. OrganoSeg is more accurate and flexible than existing platforms, and we illustrate its potential by stratifying 5167 breast-cancer spheroid and 5743 colon and colorectal-cancer organoid morphologies. Organoid transcripts grouped by morphometric signature heterogeneity were enriched for biological processes not prominent in the original RNA sequencing data. OrganoSeg enables complete, objective quantification of brightfield phenotypes, which may give insight into the molecular and multicellular mechanisms of organoid regulation.

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