Digitalized organoids: integrated pipeline for 3D high-speed analysis of organoid structures using multilevel segmentation and cellular topology

类有机物 管道(软件) 计算机科学 分割 拓扑(电路) 网络拓扑 人工智能 分布式计算 生物 细胞生物学 工程类 计算机网络 电气工程 程序设计语言
作者
Hui Ting Ong,Esra Karatas,Gianluca Grenci,Florian Dilasser,Saburnisha Binte Mohamad Raffi,D Blanc,Titouan Poquillon,Elise Drimaracci,Dimitri Mikec,Cora S. Thiel,Oliver Ullrich,Victor Racine,Anne Béghin
标识
DOI:10.1101/2023.11.08.566158
摘要

ABSTRACT Analysing the tissue morphogenesis and function is crucial for unravelling the underlying mechanisms of tissue development and disease. Organoids, 3D in vitro models that mimic the architecture and function of human tissues, offer a unique opportunity to study effects of external perturbators that are difficult to replicate in vivo . However, large-scale screening procedures for studying the effects of different ‘stress’ on cellular morphology and topology of these 3D tissue-like system face significant challenges, including limitations in high-resolution 3D imaging, and accessible 3D analysis platforms. These limitations impede the scale and throughput necessary to accurately quantify the effects of mechanical and chemical cues. Here, we present a novel, fine-tuned pipeline for screening morphology and topology modifications in 3D cell culture using multilevel segmentations and cellular topology, based on confocal microscopy and validated across different image qualities. Our pipeline incorporates advanced image analysis algorithms and artificial intelligence (AI) for multiscale 3D segmentation, enabling quantification of morphology changes at both the nuclear and cytoplasmic levels, as well as at the organoid scale. Additionally, we investigate cell relative position and employ neighbouring topology analysis to identify tissue patterning and their correlations with organoid microniches. Eventually, we have organized all the extracted features, 3D segmented masks and raw images into a single database to allow statistical and data mining approaches to facilitate data analysis, in a biologist-friendly way. We validate our approach through proof-of-concept experiments, including well-characterized conditions and poorly explored mechanical stressors such as microgravity, showcasing the versatility of our pipeline. By providing a powerful tool for discovery-like assays in screening 3D organoid models, our pipeline has wide-ranging interests from biomedical applications in development and aging-related pathologies to tissue engineering and regenerative medicine.
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