Generation and Quantitative Characterization of Functional and Polarized Biliary Epithelial Cysts.

Cholangiocytes, the epithelial cells that line up the bile ducts in the liver, oversee bile formation and modification. In the last twenty years, in the context of liver diseases, 3-dimensional (3D) models based on cholangiocytes have emerged such as cysts, spheroids, or tube-like structures to mimic tissue topology for organogenesis, disease modeling, and drug screening studies. These structures have been mainly obtained by embedding cholangiocytes in a hydrogel. The main purpose was to study self-organization by addressing epithelial polarity, functional, and morphological properties. However, very few studies focus on cyst formation efficiency. When this is the case, the efficiency is often quantified from images of a single plane. Functional assays and structural analysis are performed without representing the potential heterogeneity of cyst distribution arising from hydrogel polymerization heterogeneities and side effects. Therefore, the quantitative analysis, when done, cannot be used for comparison from one article to another. Moreover, this methodology does not allow comparisons of 3D growth potential of different matrices and cell types. Additionally, there is no mention of the experimental troubleshooting for immunostaining cysts. In this article, we provide a reliable and universal method to show that the initial cell distribution is related to the heterogeneous vertical distribution of cyst formation. Cholangiocyte cells embedded in hydrogel are followed with Z-stacks analysis along the hydrogel depth over the time course of 10 days. With this method, a robust kinetics of cyst formation efficiency and growth is obtained. We also present methods to evaluate cyst polarity and secretory function. Finally, additional tips for optimizing immunostaining protocols are provided in order to limit cyst collapse for imaging. This approach can be applied to other 3D cell culture studies, thus opening the possibilities to compare one system to another.