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Research in cell and developmental biology requires the application of three-dimensional model systems that reproduce the natural environment of cells. Processes in developmental biology are therefore studied in entire systems like insects or plants. In cell biology, three-dimensional cell cultures (e.g. spheroids or organoids) model the physiology and pathology of cells, tissues or organs. In all systems, the cellular neighborhood and interactions, but also physicochemical influences, are realistically presented. The production and handling of these model systems is rather simple and allows for reproducible characterization.
Confocal and light sheet-based fluorescence microscopy (LSFM) enable the observation of these systems while maintaining their three-dimensional integrity. LSFM is applicable to imaging live samples at high spatio-temporal resolution over long periods of time. The quality of the acquired datasets enables the extraction of quantitative features about morphology, functionality and dynamics in the context of the complete system. This approach is referred to as image-based systems biology. Exploiting the potential of the generated datasets requires an image analysis pipeline for data management, visualization and the retrieval of biologically meaningful values.
The goal of this thesis was to identify, develop and optimize modules of the image analysis pipeline. The modules cover data management and reduction, visualization, reconstruction of multiview image datasets, the segmentation and tracking of cell nuclei and the extraction of quantitative features. The modules were developed in an application-driven manner to test and ensure their applicability to real datasets from three-dimensional fluorescence microscopy. The underlying datasets were taken from research projects in developmental biology in insects and plants, as well as from cell biology.
The datasets acquired in fluorescence microscopy are typically complex and require common image processing steps in order to manage, visualize, and analyze the datasets. The first module accomplishes automatic structuring of large image datasets, reduces the data amount by image cropping and compression and computes maximum projection images along different spatial directions. The second module corrects for intensity variations in the generated maximum projection images that occur as a function of time. The program was published as a part of an article in Nature Protocols. Another developed module named BugCube provides a web-based platform to visualize and share the processed image datasets.
In LSFM, samples can be rotated in-between two acquisitions enabling the generation of multiview image datasets. Prior to my work, Frederic Strobl and Alexander Ross acquired the complete embryogenesis of the red flour beetle, Tribolium castaneum, and the field cricket, Gryllus bimaculatus, with LSFM. I evaluated a plugin for the software FIJI as a module for the reconstruction of such datasets. The plugin was optimized for automation and efficiency. We obtained the first high quality three-dimensional reconstructions of Tribolium and Gryllus datasets.
Optical clearing increases the penetration depth into samples, thus providing endpoint images of entire three-dimensional objects with cellular detail. This work contributes a quantitative characterization module that was applied to endpoint images of optically cleared spheroids. A program for the generation of ground truth datasets was developed in order to evaluate the cell nuclei segmentation performance. The program was part of a paper that was published in BMC Bioinformatics. Using the program, I could show that the cell nuclei segmentation is robust and accurate. Approaches from computational topology and graph theory complete the segmentation of cell nuclei. Thus, the developed module provides a comprehensive quantitative characterization of spheroids on the level of the individual cell, the cell neighborhood and the whole cell aggregate. The module was employed in four applications to analyze the influence of different stress conditions on the morphology and cellular arrangement of cells in spheroids. The module was accepted for publication in Scientific Reports along with the results for one application. The cell nuclei segmentation further provided a data source for simulation models that used correlation functions to identify structural zones in spheroids. These results were published in Royal Society Interface.
The final part of this work presents a module for cell tracking and lineage reconstruction. In collaboration with Dr. Alexis Maizel, Dr. Jens Fangerau and Dr. Daniel von Wangenheim, I developed a module to track the positions of all cells involved in lateral root formation in Arabidopsis thaliana and used the extracted positions for extensive data analysis. We reconstructed the cell lineages and established the first atlas of all founder cells that contribute to the formation. The analysis of the retrieved data allowed us to study conserved and individual patterns in lateral root formation. The atlas and parts of the analysis presented in this thesis were published in Current Biology.
In this thesis, I developed modules for an image analysis pipeline in three-dimensional fluorescence microscopy and applied them in interdisciplinary research projects. The modules enabled the organization, processing, visualization and analysis of the datasets. The perspective of the image analysis pipeline is not restricted to image-based systems biology. With ongoing development of the image analysis pipeline, it can also be a valuable tool for medical diagnostics or industrial high-throughput approaches.