Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Fabián Segovia-Miranda
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Piotr Klukowski
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Kirstin Meyer
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Hidenori Nonaka
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany; Rohto Pharmaceutical, Tokyo, Japan
Giovanni Marsico
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Mikhail Chernykh
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Alexander Kalaidzidis
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Marino Zerial
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
Yannis Kalaidzidis
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany; Faculty of Bioengineering and Bioinformatics, Moscow State University, Moscow, Russia
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.
