High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology with Cellos

Patience Mukashyaka, Pooja Kumar, David J. Mellert, Shadae Nicholas, Javad Noorbakhsh, Mattia Brugiolo, Elise T. Courtois, Olga Anczukow, Edison T. Liu () and Jeffrey H. Chuang ()
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Patience Mukashyaka: The Jackson Laboratory for Genomic Medicine
Pooja Kumar: The Jackson Laboratory for Genomic Medicine
David J. Mellert: The Jackson Laboratory for Genomic Medicine
Shadae Nicholas: The Jackson Laboratory for Genomic Medicine
Javad Noorbakhsh: The Jackson Laboratory for Genomic Medicine
Mattia Brugiolo: The Jackson Laboratory for Genomic Medicine
Elise T. Courtois: The Jackson Laboratory for Genomic Medicine
Olga Anczukow: The Jackson Laboratory for Genomic Medicine
Edison T. Liu: The Jackson Laboratory for Genomic Medicine
Jeffrey H. Chuang: The Jackson Laboratory for Genomic Medicine

Nature Communications, 2023, vol. 14, issue 1, 1-17

Abstract: Abstract Three-dimensional (3D) organoid cultures are flexible systems to interrogate cellular growth, morphology, multicellular spatial architecture, and cellular interactions in response to treatment. However, computational methods for analysis of 3D organoids with sufficiently high-throughput and cellular resolution are needed. Here we report Cellos, an accurate, high-throughput pipeline for 3D organoid segmentation using classical algorithms and nuclear segmentation using a trained Stardist-3D convolutional neural network. To evaluate Cellos, we analyze ~100,000 organoids with ~2.35 million cells from multiple treatment experiments. Cellos segments dye-stained or fluorescently-labeled nuclei and accurately distinguishes distinct labeled cell populations within organoids. Cellos can recapitulate traditional luminescence-based drug response of cells with complex drug sensitivities, while also quantifying changes in organoid and nuclear morphologies caused by treatment as well as cell-cell spatial relationships that reflect ecological affinity. Cellos provides powerful tools to perform high-throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.

Date: 2023
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DOI: 10.1038/s41467-023-44162-6

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