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Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT)

Zhou, F. Y.; Jacobs, B.-A.; Norton-Steele, A.; Han, X.; Zhou, L.; Carroll, T. M.; Ruiz Puig, C.; Chadwick, J.; Qin, X.; Lisle, R.; Marsh, L.; Byrne, H.; Harrington, H.; Lu, X.

2025-11-29 cancer biology
10.1101/2025.11.28.691111 bioRxiv
Show abstract

Live cells in tissue are plastic, phenotypically dynamic, and modify their function in response to genetic and environmental perturbations. To unleash the power of live-cell imaging to identify phenotype-genotype-function coupling over time, we report the development of a standardized Shape-Appearance-Motion (SAM) "phenome" and SAM-Phenotype-Observation-Tool (SPOT), that act as an image-"transcriptome" and image-"transcriptome analyzer" respectively, and provide unbiased and comprehensive description of morpho-dynamic phenotypes without prior knowledge. We developed and applied SAM-SPOT to our simulated organoids database with known ground-truth and >1.6 million mouse and human organoid instances with defined genetic and chemical perturbations. SAM-SPOT can effectively and robustly characterize 3D morpho-dynamics from 2D projection videos. Combined with single-cell RNA sequencing, SAM-SPOT revealed that altered WNT signaling, but not mutant RAS or p53, predisposes intestinal organoids to irregular morphogenesis. SAM-SPOT advances biomedical discovery by empowering live-cell imaging to identify phenotype-genotype-function relationships through large-scale and cost-effective label-free live-cell imaging.

Published in Nature Communications (predicted rank #1) · training set

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