High-throughput formation and image-based analysis of basal-in mammary organoids in 384-well plates

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作者
Soojung Lee
Jonathan Chang
Sung-Min Kang
Eric Parigoris
Ji-Hoon Lee
Yun Suk Huh
Shuichi Takayama
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[1] Georgia Institute of Technology,Wallace H. Coulter Department of Biomedical Engineering
[2] Georgia Institute of Technology,The Parker H. Petit Institute of Bioengineering and Bioscience
[3] Sangmyung University,Department of Green Chemical Engineering
[4] Inha University,Department of Biological Engineering, NanoBio High
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This manuscript describes a new method for forming basal-in MCF10A organoids using commercial 384-well ultra-low attachment (ULA) microplates and the development of associated live-cell imaging and automated analysis protocols. The use of a commercial 384-well ULA platform makes this method more broadly accessible than previously reported hanging drop systems and enables in-incubator automated imaging. Therefore, time points can be captured on a more frequent basis to improve tracking of early organoid formation and growth. However, one major challenge of live-cell imaging in multi-well plates is the rapid accumulation of large numbers of images. In this paper, an automated MATLAB script to handle the increased image load is developed. This analysis protocol utilizes morphological image processing to identify cellular structures within each image and quantify their circularity and size. Using this script, time-lapse images of aggregating and non-aggregating culture conditions are analyzed to profile early changes in size and circularity. Moreover, this high-throughput platform is applied to widely screen concentration combinations of Matrigel and epidermal growth factor (EGF) or heparin-binding EGF-like growth factor (HB-EGF) for their impact on organoid formation. These results can serve as a practical resource, guiding future research with basal-in MCF10A organoids.
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