类有机物
高含量筛选
计算机科学
移液管
精密医学
工作流程
三维细胞培养
计算生物学
细胞
生物
化学
神经科学
病理
医学
物理化学
数据库
遗传学
作者
Suleyman B. Bozal,Greg Sjogren,António P. Costa,Joseph S. Brown,Shannon Roberts,Dylan Baker,Paul Gabriel,Benjamin T. Ristau,Michael L. Samuels,William F. Flynn,P. R. H. Robson,Elise T. Courtois
标识
DOI:10.1016/j.slasd.2024.100182
摘要
The use of organoid models in biomedical research has grown substantially since their inception. As they gain popularity among scientists seeking more complex and biologically relevant systems, there is a direct need to expand and clarify potential uses of such systems in diverse experimental contexts. Herein we outline a high-content screening (HCS) platform that allows researchers to screen drugs or other compounds against three-dimensional (3D) cell culture systems in a multi-well format (384-well). Furthermore, we compare the quality of robotic liquid handling with manual pipetting and characterize and contrast the phenotypic effects detected by confocal imaging and biochemical assays in response to drug treatment. We show that robotic liquid handling is more consistent and amendable to high throughput experimental designs when compared to manual pipetting due to improved precision and automated randomization capabilities. We also show that image-based techniques are more sensitive to detecting phenotypic changes within organoid cultures than traditional biochemical assays that evaluate cell viability, supporting their integration into organoid screening workflows. Finally, we highlight the enhanced capabilities of confocal imaging in this organoid screening platform as they relate to discerning organoid drug responses in single-well co-cultures of organoids derived from primary human biopsies and patient-derived xenograft (PDX) models. Altogether, this platform enables automated, imaging-based HCS of 3D cellular models in a non-destructive manner, opening the path to complementary analysis through integrated downstream methods.
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