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Cells within a tissue form highly complex, cellular interactions. This architecture is lost in twodimensional cell cultures. To close the gap between two-dimensional cell cultures and in vivo tissues, three-dimensional cell cultures were developed. Three-dimensional cellular aggregates such as spheroids, organoids, or embryoid bodies have been established as an essential tool in many different aspects of life science, including tumour biology, drug screening and embryonic development. To fully take advantage of the third dimension, imaging techniques are essential. The emerging field of “imagebased systems biology” exploits the information in images and builds a connection between experimental and theoretical investigation of biological processes at a spatio-temporal level. Such interdisciplinary approaches strongly depend on the development of protocols to establish threedimensional cell cultures, innovations in sample preparation, well-suited imaging techniques and quantitative segmentation methods.
Although three-dimensional cell cultures and image-based systems biology provide a great potential, two-dimensional methods are still not completely replaced by three-dimensional methods. The knowledge about many biological processes relies on two-dimensional experiments. This is mainly due to methodical and technical hurdles. Therefore, this thesis provides a significant contribution to overcome these hurdles and to further develop three-dimensional cell cultures. I established computational as well as experimental methods related to three-dimensional cellular aggregates and investigated fundamental, cellular processes such as adhesion, growth and differentiation.
Background: Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset.
Results: We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values.
Conclusion: We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.
Spheroids resemble features of tissues and serve as model systems to study cell–cell and cell–ECM interactions in non-adhesive three-dimensional environments. Although it is generally accepted that mature spheroids resemble tissue properties very well, no studies relate different phases in the spheroid formation processes that contribute to tissue integrity. Tissue integrity involves the cellular processes adhesion formation, adhesion reinforcement, rearrangement as well as proliferation. They maintain the structure and function of tissues and, upon dysregulation, contribute to malignancy. We investigated spheroid formation dynamics in cell lines of different metastatic potential. We dissected spheroid formation into phases of aggregation, compaction and growth to identify the respective contributions of E-cadherin, actin, microtubules and FAK. E-cadherin, actin and microtubules drive the first two phases. Microtubules and FAK are involved in the proliferation phase. FAK activity correlates with the metastatic potential of the cells. A robust computational model based on a very large number of experiments reveals the temporal resolution of cell adhesion. Our results provide novel hypotheses to unveil the general mechanisms that contribute to tissue integrity.
Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach
(2020)
During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.
Cells within a tissue form highly complex, cellular interactions. This architecture is lost in two-dimensional (2D) cell cultures. To close the gap between 2D cell cultures and in vivo tissues, three-dimensional (3D) cell cultures such as spheroids or embryoid bodies were developed. To fully take advantage of the third dimension, imaging techniques are essential. The emerging field of "image-based systems biology" exploits the information in images and builds a connection between experimental and theoretical investigation of biological processes. Such interdisciplinary approaches strongly depend on the development of protocols to establish 3D cell cultures, innovations in sample preparation, well-suited imaging techniques and quantitative segmentation methods.
Although 3D cell cultures and image-based systems biology provide a great potential, 2D methods are still not completely replaced by 3D methods. This is mainly due to methodical and technical hurdles. Therefore, this thesis provides a significant contribution to overcome these hurdles and to further develop 3D cell cultures. I established computational and experimental methods related to 3D aggregates and investigated fundamental, cellular processes such as adhesion, growth and differentiation.
The automatic segmentation method "PAS" and "LoS" were developed in the context of this thesis. They extract essential biological properties such as the projected area or features of cell nuclei from 2D or 3D images of 3D aggregates. Both algorithms show their accuracy robustly over image data from different samples and different microscopes. In addition, the superior performance of PAS and LoS was proven in a comparison with state-of-the-art methods.
The PAS approach served as an essential basis for investigating cellular processes such as adhesion and growth which are tightly regulated to contribute to tissue integrity. These processes are involved in the formation of spheroids. The temporally resolved data of spheroid formation of three mammary epithelial cell lines revealed differences in their formation dynamics as well as in the onset of spheroid formation phases (aggregation, compaction and growth). Despite these differences, adhesion- and growth-associated proteins such as E-cadherin, actin, microtubules, and the focal adhesion kinase show similar importance in a particular phase. Notably, certain proteins (e.g. E-Cadherin) contribute differently to spheroid formation of cells from different cell types in terms of cell adhesion and growth. Overall, analyses of the individual phases of spheroid formation revealed the temporal coordination of fundamental tissue-specific processes. The results contribute to a better understanding of the maintenance and disruption of tissue integrity.
An important but yet unknown process is how cells accomplish to arrange themselves against the gravitational force to form a spheroid. Live imaging with light sheet-based microscopy provides the best solution for a temporally and in particular spatially resolved investigation of spheroid formation. Although the imaging possibilities increase with this particular microscopy technique, available sample preparation methods are rare. Therefore, I have significantly optimized "agarose beaker" as preparation method for 3D long-term imaging of spheroid formation. The data show that upward movement of the cells takes place early. This movement is initiated in the centre of the initially flat cell layer. Subsequently, the cells move from the periphery of the cell layer toward the centre. Cells rearrange within the spheroid which is followed by growth. It is very likely that 3D aggregates form by adopting an energetically favoured, spherical shape by increasing cell-cell or cell-matrix contacts.
Besides the knowledge gained from the examination of the self-assembly process in different contexts, fully formed cellular aggregates can serve as basis to investigate differentiation processes. Differentiation guide cell fate specification during early embryonic development (i.e. preimplantation) and is not fully understood yet. Due to the lack of an in vitro system for preimplantation, I have developed "blastoids". These are 3D multicellular aggregates of mouse embryonic stem cells which represent important phases of preimplantation and beyond. In qualitative and quantitative analyses, a strong similarity was proven between blastoids and the inner cell mass of in vivo mouse embryos. Further results strongly suggest that both, the cell number and the trophectoderm play a subordinate role for cell fate decision during preimplantation. Furthermore, 3D neighbourhood analyses have shown that both, blastoids and mouse embryos, do not show a random "salt-and-pepper" pattern during differentiation. Instead, they show a yet unknown local clustering of cells with identical fates, suggesting local cell interactions that influence cell fate decision. Furthermore, the data indicate that the maturation of the epiblast in the later stages of preimplantation is initiated by an interaction between cells of the epiblast and the primitive endoderm.
Using image-based systems biology, I have investigated fundamental cellular processes such as adhesion, growth and differentiation in the context of tissue integrity and early embryonic development using 3D cellular aggregates. This highly interdisciplinary work is a major contribution to 3D cell biology and demonstrates how cells bind and interact within a complex system. The main methods developed in this thesis as well as the biological findings can be used not only in further biological but also in medical and pharmacological studies. They have the potential to advance our understanding of complex biological systems and to provide new opportunities for practical applications.