2D mapping of strongly deformable cell nuclei, based on contour matching

The spatiotemporal dynamics of protein complexes and genome loci are functionally linked to cellular health status. To study the inherent motion of subnuclear particles, it is essential to remove any superimposed component stemming from displacement and deformation of the nucleus. In this article, we propose a mapping of the nuclear interior, which is based on the deformation of the nuclear contour and has no shape constraints. This registration procedure enabled an accurate estimation of telomere mobility in living human cells undergoing dramatic nuclear deformations. Given the large variety of pathologies and cellular processes that are associated with strong nuclear shape changes, the contour mapping algorithm has generic value for improving the accuracy of mobility measurements of genome loci and intranuclear macromolecule complexes

Non-rigid Contour-Based Registration of Cell Nuclei in 2D Live Cell Microscopy Images Using a Dynamic Elasticity Model

International audienceThe analysis of the pure motion of subnuclear structures without influence of the cell nucleus motion and deformation is essential in live cell imaging. In this work, we propose a 2D contour-based image registration approach for compensation of nucleus motion and deformation in fluorescence microscopy time-lapse sequences. The proposed approach extends our previous approach which uses a static elasticity model to register cell images. Compared to that scheme, the new approach employs a dynamic elasticity model for forward simulation of nucleus motion and deformation based on the motion of its contours. The contour matching process is embedded as a constraint into the system of equations describing the elastic behavior of the nucleus. This results in better performance in terms of the registration accuracy. Our approach was successfully applied to real live cell microscopy image sequences of different types of cells including image data that was specifically designed and acquired for evaluation of cell image registration methods. An experimental comparison with existing contour-based registration methods and an intensity-based registration method has been performed. We also studied the dependence of the results on the choice of method parameters

Coupled Dictionary Learning for Image Analysis

Modern imaging technologies provide different ways to visualize various objects ranging from molecules in a cell to the tissue of a human body. Images from different imaging modalities reveal distinct information about these objects. Thus a common problem in image analysis is how to relate different information about the objects. For instance, relating protein locations from fluorescence microscopy and the protein structures from electron microscopy. These problems are challenging due to the difficulties in modeling the relationship between the information from different modalities. In this dissertation, a coupled dictionary learning based image analogy method is first introduced to synthesize images in one modality from images in another. As a result, using my method multi-modal registration (for example, registration between correlative microscopy images) is simplified to a mono-modal one. Furthermore, a semi-coupled dictionary learning based framework is proposed to estimate deformations from image appearances. Moreover, a coupled dictionary learning method is explored to capture the relationship between GTPase activations and cell protrusions and retractions. Finally, a probabilistic model is proposed for robust coupled dictionary learning to address learning a coupled dictionary with non-corresponding data. This method discriminates between corresponding and non-corresponding data thereby resulting in a "clean" coupled dictionary by removing non-corresponding data during the learning process.Doctor of Philosoph

Cloning in Cattle

In mammalian cell nuclei chromosome territories (CTs) occupy positions correlating with their gene-density and chromosome size. While this global radial order has been well documented, the question of whether a global neighborhood order is also maintained has remained a controversial matter. To answer this question I grew clones (of HeLa, HMEC and human diploid fibroblast cells) for up to 5 divisions (32 cells) and performed 3D FISH experiments to visualize the nuclear positions of 3 different CT pairs. Using different landmark-based registration approaches I assessed the similarity of CT arrangements in daughter cells and cousins. As expected from a symmetrical chromatid movement during mitotic anaphase and telophase, I was able to confirm previous findings of a pronounced similarity of CT arrangements between daughter cells. However, already after two cell cycles the neighborhood order in cousins was nearly completely lost. This loss indicates that a global neighborhood order is not maintained. Further, I could show in the present thesis that a gene density correlated distribution of CTs, which has already been shown in different cell types of various species appears to be independent of the cell cycle. Moreover I could provide evidence that the nuclear shape plays a major role in defining the extent of this gene-density correlated distribution, as nuclei of human, old world monkey and bovine fibroblasts showed an increased difference in the radial distribution of gene poor/dense CTs when their nuclei were artificially reshaped from a flat ellipsoid to a nearly spherical nucleus. The observation that a gene-density correlated distribution of CTs has been found in nuclei from birds to humans argues for a significant, yet undiscovered functional impact. So far CTs have been investigated mainly in cultured cells and to some extent in tissues, yet little is known about the origin and fate of CTs during early development. To gain insights into the very early organization of CTs in preimplantation embryos I have developed a fluorescence in situ hybridization (FISH) protocol, which enables the visualization of CTs in three dimensionally preserved embryos. Using this protocol I have investigated CTs of bovine chromosomes 19 and 20, representing the most gene-rich and gene-poor chromosomes, respectively. Equivalent to the distributions described in other species I could confirm a gene density related spatial CT arrangement in bovine fibroblasts and lymphocytes with CT 19 being localized more internally and CT 20 more peripherally. Importantly, I did not find a gene density related distribution of CTs 19 and 20 in early embryos up to the 8-cell stage. Only in embryos with more than 8 cells a significant difference in the distribution of both chromosomes became apparent that increased upon progression to the blastocyst stage. Since major genome activation in bovine embryos occurs during the 8- to 16-cell stage, my findings suggest an interrelation between higher order chromatin arrangements and transcriptional activation of the embryonic genome. Using another experimental set up I analyzed the topology of a developmentally regulated transgene utilizing bovine nuclear transfer (NT) embryos derived from fetal fibroblasts, which harbored a mouse Oct4/GFP reporter construct integrated at a single insertion site on bovine chromosome 13. I analyzed the intranuclear distribution of the transgene as well as its position in relation to its harboring chromosome in donor cell nuclei and day 2 NT embryos, where the transgene is still inactive as well as in day 4 NT embryos, where transgene expression starts, and day 7 NT embryos, where expression is highly increased. Compared to donor cell nuclei I found a more peripheral location of both BTA 13 CTs and the Oct4/GFP transgene in day 2, day 4 and day 7 NT embryos, although there was a trend of the transgene and both BTA 13 CTs to re-localize towards the nuclear interior from d2 to d7 embryos. Moreover, I found the transgene located at the surface of its harboring CT 13 in donor fibroblasts, whereas during preimplantation development of NT embryos it became increasingly internalized into the chromosome 13 territory, reaching a maximum in d7 NT embryos, i.e. at the developmental stage when its transcription levels are highest. These latter experiments show that the transfer of a somatic nucleus into a chromosome depleted oocyte triggers a large scale positional change of CTs 13 and of an Oct4/GFP transgene and indicate a redistribution of this developmentally regulated Oct4/GFP transgene during activation and upregulation in developing NT embryos

Biological image analysis

In biological research images are extensively used to monitor growth, dynamics and changes in biological specimen, such as cells or plants. Many of these images are used solely for observation or are manually annotated by an expert. In this dissertation we discuss several methods to automate the annotating and analysis of bio-images. Two large clusters of methods have been investigated and developed. A first set of methods focuses on the automatic delineation of relevant objects in bio-images, such as individual cells in microscopic images. Since these methods should be useful for many different applications, e.g. to detect and delineate different objects (cells, plants, leafs, ...) in different types of images (different types of microscopes, regular colour photographs, ...), the methods should be easy to adjust. Therefore we developed a methodology relying on probability theory, where all required parameters can easily be estimated by a biologist, without requiring any knowledge on the techniques used in the actual software. A second cluster of investigated techniques focuses on the analysis of shapes. By defining new features that describe shapes, we are able to automatically classify shapes, retrieve similar shapes from a database and even analyse how an object deforms through time