Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Michael A Borten; Sameer S Bajikar; Nobuo Sasaki; Hans Clevers; Kevin A Janes

doi:10.1038/s41598-017-18815-8

Automated brightfield morphometry of 3D organoid populations by OrganoSeg

Michael A Borten, Sameer S Bajikar, Nobuo Sasaki, Hans Clevers, Kevin A Janes

Hubrecht Institute

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

88 Citations (Scopus)

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.

Original language	English
Pages (from-to)	5319
Journal	Scientific Reports
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41598-017-18815-8
Publication status	Published - 28 Mar 2018

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AU - Janes, Kevin A

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Automated brightfield morphometry of 3D organoid populations by OrganoSeg

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