Abstract

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.

Details

Title
High-throughput formation and image-based analysis of basal-in mammary organoids in 384-well plates
Author
Lee, Soojung 1 ; Chang, Jonathan 1 ; Sung-Min, Kang 2 ; Parigoris, Eric 1 ; Ji-Hoon, Lee 1 ; Huh, Yun Suk 3 ; Takayama Shuichi 1 

 Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, USA (GRID:grid.213917.f) (ISNI:0000 0001 2097 4943); Georgia Institute of Technology, The Parker H. Petit Institute of Bioengineering and Bioscience, Atlanta, USA (GRID:grid.213917.f) (ISNI:0000 0001 2097 4943) 
 Sangmyung University, Department of Green Chemical Engineering, Cheonan, Republic of Korea (GRID:grid.263136.3) (ISNI:0000 0004 0533 2389) 
 Inha University, Department of Biological Engineering, NanoBio High-Tech Materials Research Center, Incheon, Republic of Korea (GRID:grid.202119.9) (ISNI:0000 0001 2364 8385) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2618381097
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.