This repository contains the code for the analysis performed in our work "Multiscale three-dimensional ultrastructural mapping of intestinal tissues and organoids", as well as the requirements to reproduce our work and engage with the beautiful imagery.
|
  
|
From Figure 4 | Volumetric segmentation of an entire intestinal organoid crypt.
Manual installation
The python environment was managed using the Poetry environment manager. Python and git are presumed to already be installed.
(1) First, install poetry.
(2) clone the SAM2 repository into the parent directory and follow their instructions on downloading the weights and config files.
(3) Clone this repository.
(4) In the terminal, navigate to the project folder run poetry install.
Installation using the terminal [Linux, macOS, Windows (Git Bash)]:
# install poetry
curl -sSL https://install.python-poetry.org | python3 -# install SAM2 (see their github for help)
git clone https://github.com/facebookresearch/sam2.git && cd sam2 &&\
cd checkpoints && ./download_ckpts.sh && cd .. && cd .. &&\# install this repository
git clone https://github.com/UU-cellbiology/Intestinal-ExM-Analysis.git &&\
cd Intestinal-ExM-Analysis && poetry installTBD: how to fork napari-bbox to store layer as csv.
In our work, we show that expansion microscopy enables the multiscale volumetric study of epithelial ultrastructure in tissue sections and organoid models. Using an optimized expansion microscopy workflow, we resolve epithelial tissue architecture, cell types and subcellular features within volumes across scales. The paper describes the sample preparation for nanoscale resolution, as well as acquisition to increase depth of field for whole organoid and tissue imaging, in great detail. The data will be available at: TBD
From Figure 2 | Ultrastructure expansion microscopy of mouse small intestine organoids.
TBD
Problems and questions regarding the code can best be raised as an issue. For questions regarding the data or the paper, contact the corresponding author.