Whole Tissue Imaging of Cellular Boundaries at Sub-Micron Resolutions for Automatic Cell Segmentation: Applications...

For decades, biologists have relied on confocal microscopy to understand cellular morphology and fine details of tissue structure. However, traditional confocal microscopy of tissues faces limited light penetration, typically less than 100 µm, due to tissue opacity. To address this challenge, researchers have developed tissue clearing protocols compatible with confocal microscopy. Unfortunately, these protocols often struggle to retain cell boundary markers, especially at high resolutions necessary for precise cell segmentation. In this work, we introduce a method that preserves cell boundary markers and matches the refractive index of tissues with water. This technique enables the use of high-magnification, long working distance water-dipping objectives. The sub-micron resolutions achieved with this approach allows us to automatically segment each individual cell using a trained neural network segmentation model. These segmented images facilitate the quantification of cell properties and morphology of the entire three-dimensional tissue. As a demonstration of this methodology, we first examine mandibles of transgenic mice that express fluorescent proteins in their cell membranes. We then extend this technique to a non-model animal, the catshark, investigating the cellular properties of its dental lamina and dermal denticles - invaginating and evaginating ectodermal structures, respectively. Our technique thus provides a powerful tool to quantify in high throughput the 3D structures of cells and tissues during organ morphogenesis.