Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
The Parker H. Petit Institute of Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA.
Sci Rep. 2022 Jan 10;12(1):317. doi: 10.1038/s41598-021-03739-1.
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.
本文描述了一种使用商业 384 孔超低附着（ULA）微孔板形成基底型 MCF10A 类器官的新方法，并开发了相关的活细胞成像和自动分析方案。与以前报道的悬滴系统相比，商业 384 孔 ULA 平台的使用使这种方法更广泛适用，并实现了孵育箱内的自动化成像。因此，可以更频繁地捕获时间点，以提高对早期类器官形成和生长的跟踪。然而，多孔板中活细胞成像的一个主要挑战是大量图像的快速积累。本文开发了一个自动 MATLAB 脚本来处理增加的图像负载。该分析方案利用形态图像处理来识别每个图像中的细胞结构，并量化其圆度和大小。使用此脚本，对聚集和非聚集培养条件的延时图像进行分析，以分析大小和圆度的早期变化。此外，该高通量平台广泛用于筛选基质胶和表皮生长因子（EGF）或肝素结合表皮生长因子样生长因子（HB-EGF）的浓度组合，以研究它们对类器官形成的影响。这些结果可以作为一个实用的资源，指导未来关于基底型 MCF10A 类器官的研究。
