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In this thesis, the development of a phylogenetic DNA microarray, the analysis of several gene expression microarray datasets and new approaches for improved data analysis and interpretation are described. In the first publication, the development and analysis of a phylogenetic microarray is presented. I could show that species detection with phylogenetic DNA microarrays can be significantly improved when the microarray data is analyzed with a linear regression modeling approach. Standard methods have so far relied on pure signal intensities of the array spots and a simple cutoff criterion was applied to call a species present or absent. This procedure is not applicable to very closely related species with high sequence similarity because cross-hybridization of non-target DNA renders species detection impossible based on signal intensities alone. By modeling hybridization and cross-hybridization with linear regression, as I have presented in this thesis, even species with a sequence similarity of 97% in the marker gene can be detected and distinguished from related species. Another advantage of the modeling approach over existing methods is that the model also performs well on mixtures of different species. In principle, also quantitative predictions can be made. To make better use of the large amounts of microarray data stored in public databases, meta-analysis approaches need to be developed. In the second publication, an explorative meta-analysis exemplified on Arabidopsis thaliana gene expression datasets is presented. Integrating datasets studying effects such as the influence of plant hormones, pathogens and different mutations on gene expression levels, clusters of similarly treated datasets could be found. From the clusters of pathogen-treated and indole-3-acetic acid (IAA) treated datasets, representative genes were selected which pointed to functions which had been associated with pathogen attack or IAA effects previously. Additionally, hypotheses about the functions of so far uncharacterized genes could be set up. Thus, this kind of meta-analysis could be used to propose gene functions and their regulation under different conditions. In this work, also primary data analysis of Arabidopsis thaliana datasets is presented. In the third publication, an experiment which was conducted to find out if microwave irradiation has an effect on the gene expression of a plant cell culture is described. During the first steps, the data analysis was carried out blinded and exploratory analysis methods were applied to find out if the irradiation had an effect on gene expression of plant cells. Small but statistically significant changes in a few genes were found and could be experimentally confirmed. From the functions of the regulated genes and a meta-analysis with publicly available microarray data, it could be suspected that the plant cell culture somehow perceived the irradiation as energy, similar to perceiving light rays. The fourth publication describes the functional analysis of another Arabidopsis thaliana gene expression dataset. The gene expression data of the plant tumor dataset pointed to a switch from a mainly aerobic, auxotrophic to an anaerobic and heterotrophic metabolism in the plant tumor. Genes involved in photosynthesis were found to be repressed in tumors; genes of amino acid and lipid metabolism, cell wall and solute transporters were regulated in a way that sustains tumor growth and development. Furthermore, in the fifth publication, GEPAT (Genome Expression Pathway Analysis Tool), a tool for the analysis and integration of microarray data with other data types, is described. It consists of a web application and database which allows comfortable data upload and data analysis. In later chapters of this thesis (publication 6 and publication 7), GEPAT is used to analyze human microarray datasets and to integrate results from gene expression analysis with other datatypes. Gene expression and comparative genomic hybridization data from 71 Mantle Cell Lymphoma (MCL) patients was analyzed and allowed proposing a seven gene predictor which facilitates survival predictions for patients compared to existing predictors. In this study, it was shown that CGH data can be used for survival predictions. For the dataset of Diffuse Large B-cell lymphoma (DLBCL) patients, an improved survival predictor could be found based on the gene expression data. From the genes differentially expressed between long and short surviving MCL patients as well as for regulated genes of DLBCL patients, interaction networks could be set up. They point to differences in regulation for cell cycle and proliferation genes between patients with good and bad prognosis.
This research was aimed to evaluate the time-course of changes in the brain insulin and some elements of the insulin receptor (IR) signalling cascade in the streptozotocin-intracerebroventricullarly (STZ-icv) treated rats representing experimental model of sporadic Alzheimer’s disease (sAD) and to compare them with effects of chronically increased corticosterone on the brain insulin system. This study shows down-regulation in mRNA expression of insulin, insulin receptor (IR), and insulin degrading enzyme (IDE) but no changes were observed in the expression of tau mRNA in hippocampus of STZ-icv treated rats. Comparing these results to the ones found in corticosterone treated rats similarities at the level of insulin, IR and IDE mRNA expression can be assumed. In contrast tau mRNA expression in corticosterone treated rats were increased, data which are in line with sAD. Behavioural deficits were found in both STZ-icv and corticosterone treated rats. In conclusion, these results demonstrate that many of the characteristic features of sporadic Alzheimer’s disease (sAD) can be produced experimentally by impairing the insulin/IR signaling pathway combined with a chronic increase of corticosterone. This supports our hypothesis that sAD represents a neuro-endocrine disorder associated with brain-specific disregulation in insulin and IR signaling, caused in part by increased level of corticosterone. In line with that our study puts a question on the classical amyloid β (Aβ) hypothesis, supporting the view of brain insulin system dysfunction as a trigger for the Aβ pathology in an experimental sAD model.
Charcot-Marie-Tooth 1B (CMT1B) is a progressive inherited demyelinating disease of human peripheral nervous system leading to sensory and/or motor function disability and is caused by mutations in the P0 gene. Mice heterozygously deficient for P0 (P0+/-) are an adequate model of this human disorder showing myelin degeneration, formation of onion bulbs, remyelination and a reduced motor conduction velocity of around 30m/s similar to patients. Previously, it had been shown that T-lymphocytes and macrophages play a crucial role during pathogenesis in peripheral nerves of P0+/- mice. Both, T-lymphocytes and macrophages increase in number in the endoneurium and deletion of T-lymphocytes or deletion of a macrophage-directed cytokine ameliorates the disease. In this study the monocyte chemoattractant protein-1 (MCP-1) was identified as an early regulated cytokine before onset of disease is visible at the age of six months. MCP-1 mRNA and protein expression could be detected in femoral quadriceps and sciatic nerves of P0+/- mice already at the age of one month but not in cutaneous saphenous nerves which are never affected by the disease. MCP-1 was shown to be expressed by Schwann cells and to mediate the immigration of immune cells into peripheral nerves. Deletion of MCP-1 in P0+/- mice accomplished by crossbreeding P0 and MCP-1 deficient mice revealed a substantial reduction of immune cells in peripheral nerves of P0+/-/MCP-1+/- and P0+/-/MCP-1-/- mice at the age of six months. In twelve months old mice reduction of immune cells in peripheral nerves is accompanied by amelioration of demyelinating disease in P0+/-/MCP-1+/- and aggravation of demyelinating disease in lumbar ventral roots of P0+/ /MCP-1-/- mice in comparison to P0+/ /MCP 1+/+ mice. Furthermore, activation of the MEK1/2-ERK1/2 signalling cascade could be demonstrated to take place in Schwann cells of affected peripheral nerves of P0+/- mice overlapping temporarily and spatially with MCP-1 expression. An animal experiment using a MEK1/2-inhibitor in vivo, CI-1040, revealed that upon reduction of ERK1/2 phosphorylation MCP-1 mRNA expression is diminished suggesting that the activation of the MEK1/2-ERK1/2 signalling cascade is necessary for MCP-1 expression. Additionally, peripheral nerves of P0+/- mice showing reduced ERK1/2 phosphorylation and MCP-1 mRNA expression also show reduced numbers of macrophages in the endoneurium. This study shows a molecular link between a Schwann cell based mutation and immune cell function. Inhibition of the identified signalling cascade might be a putative target for therapeutic approaches.
Magnetic Resonance Imaging (MRI) is an imaging modality which provides anatomical or functional images of the human body with variable contrasts in an arbitrarily positioned slice without the need for ionizing radiation. In MRI, data are not acquired directly, but in the reciprocal image space (otherwise known as k-space) through the application of spatially variable magnetic field gradients. The k-space is made up of a grid of data points which are generally acquired in a line-by-line fashion (Cartesian imaging). After the acquisition, the k-space data are transformed into the image domain using the Fast Fourier Transformation (FFT). However, the acquisition of data is not limited to the rectilinear Cartesian sampling scheme described above. Non-Cartesian acquisitions, where the data are collected along exotic trajectories, such as radial and spiral, have been shown to be beneficial in a number of applications. However, despite their additional properties and potential advantages, working with non-Cartesian data can be complicated. The primary difficulty is that non-Cartesian trajectories are made up of points which do not fall on a Cartesian grid, and a simple and fast FFT algorithm cannot be employed to reconstruct images from non-Cartesian data. In order to create an image, the non-Cartesian data are generally resampled on a Cartesian grid, an operation known as gridding, before the FFT is performed. Another challenge for non-Cartesian imaging is the combination of unusual trajectories with parallel imaging. This thesis has presented several new non-Cartesian parallel imaging methods which simplify both gridding and the reconstruction of images from undersampled data. In Chapter 4, a novel approach which uses the concepts of parallel imaging to grid data sampled along a non-Cartesian trajectory called GRAPPA Operator Gridding (GROG) is described. GROG shifts any acquired k-space data point to its nearest Cartesian location, thereby converting non-Cartesian to Cartesian data. The only requirements for GROG are a multi-channel acquisition and a calibration dataset for the determination of the GROG weights. Chapter 5 discusses an extension of GRAPPA Operator Gridding, namely Self-Calibrating GRAPPA Operator Gridding (SC-GROG). SC-GROG is a method by which non-Cartesian data can be gridded using spatial information from a multi-channel coil array without the need for an additional calibration dataset, as required in standard GROG. Although GROG can be used to grid undersampled datasets, it is important to note that this method uses parallel imaging only for gridding, and not to reconstruct artifact-free images from undersampled data. Chapter 6 introduces a simple, novel method for performing modified Cartesian GRAPPA reconstructions on undersampled non-Cartesian k-space data gridded using GROG to arrive at a non-aliased image. Because the undersampled non-Cartesian data cannot be reconstructed using a single GRAPPA kernel, several Cartesian patterns are selected for the reconstruction. Finally, Chapter 7 discusses a novel method of using GROG to mimic the bunched phase encoding acquisition (BPE) scheme. In MRI, it is generally assumed that an artifact-free image can be reconstructed only from sampled points which fulfill the Nyquist criterion. However, the BPE reconstruction is based on the Generalized Sampling Theorem of Papoulis, which states that a continuous signal can be reconstructed from sampled points as long as the points are on average sampled at the Nyquist frequency. A novel method of generating the “bunched” data using GRAPPA Operator Gridding (GROG), which shifts datapoints by small distances in k-space using the GRAPPA Operator instead of employing zig-zag shaped gradients, is presented in this chapter. With the conjugate gradient reconstruction method, these additional “bunched” points can then be used to reconstruct an artifact-free image from undersampled data. This method is referred to as GROG-facilitated Bunched Phase Encoding, or GROG-BPE.
Chondrogenic differentiation of human mesenchymal stem cells and articular cartilage reconstruction
(2008)
Articular cartilage defects are still one of the major challenges in orthopedic and trauma surgery. Today, autologous chondrocyte transplantation (ACT), as a cell-based therapy, is an established procedure. However, one major limitation of this technique is the loss of the chondrogenic phenotype during expansion. Human mesenchymal stem cells (hMSCs) have an extensive proliferation potential and the capacity to differentiate into chondrocytes when maintained under specific conditions. They are therefore considered as candidate cells for tissue engineering approaches of functional cartilage tissue substitutes. First in this study, hMSCs were embedded in a collagen type I hydrogel to evaluate the cartilaginous construct in vitro. HMSC collagen hydrogels cultivated in different culture media showed always a marked contraction, most pronounced in chondrogenic differentiation medium supplemented with TGF-ß1. After stimulation with chondrogenic factors (dexamethasone and TGF-ß1) hMSCs were able to undergo chondrogenesis when embedded in the collagen type I hydrogel, as evaluated by the temporal induction of cartilage-specific gene expression. Furthermore, the cells showed a chondrocyte-like appearance and were homogeneously distributed within a proteoglycan- and collagen type II-rich extracellular matrix, except a small area in the center of the constructs. In this study, chondrogenic differentiation could not be realized with every hMSC preparation. With the improvement of the culture conditions, e.g. the use of a different FBS lot in the gel fabrication process, a higher amount of cartilage-specific matrix deposition could be achieved. Nevertheless, the large variations in the differentiation capacity display the high donor-to-donor variability influencing the development of a cartilaginous construct. Taken together, the results demonstrate that the collagen type I hydrogel is a suitable carrier matrix for hMSC-based cartilage regeneration therapies which present a promising future alternative to ACT. Second, to further improve the quality of tissue-engineered cartilaginous constructs, mechanical stimulation in specific bioreactor systems are often employed. In this study, the effects of mechanical loading on hMSC differentiation have been examined. HMSC collagen hydrogels were cultured in a defined chondrogenic differentiation medium without TGF-ß1 and subjected to a combined mechanical stimulation protocol, consisting of perfusion and cyclic uniaxial compression. Bioreactor cultivation neither affected overall cell viability nor the cell number in collagen hydrogels. Compared with non-loaded controls, mechanical loading promoted the gene expression of COMP and biglycan and induced an up-regulation of matrix metalloproteinase 3. These results circumstantiate that hMSCs are sensitive to mechanical forces, but their differentiation to chondrocytes could not be induced. Further studies are needed to identify the specific metabolic pathways which are altered by mechanical stimulation. Third, for the development of new cell-based therapies for articular cartilage repair, a reliable cell monitoring technique is required to track the cells in vivo non-invasively and repeatedly. This study aimed at analyzing systematically the performance and biological impact of a simple and efficient labeling protocol for hMSCs. Very small superparamagnetic iron oxide particles (VSOPs) were used as magnetic resonance (MR) contrast agent. Iron uptake was confirmed histologically with prussian blue staining and quantified by mass spectrometry. Compared with unlabeled cells, VSOP-labeling did neither influence significantly the viability nor the proliferation potential of hMSCs. Furthermore, iron incorporation did not affect the differentiation capacity of hMSCs. The efficiency of the labeling protocol was assessed with high resolution MR imaging at 11.7 Tesla. VSOP-labeled hMSCs were visualized in a collagen type I hydrogel indicated by distinct hypointense spots in the MR images, resulting from an iron specific loss of signal intensity. This was confirmed by prussian blue staining. In summary, this labeling technique has great potential to visualize hMSCs and track their migration after transplantation for articular cartilage repair with MR imaging.
Steps involved in the progression of non-small cell lung cancer (NSCLC) to metastasis are poorly understood. Expression of oncogenic C-RAF in lung epithelial cells has yielded a model for non-small cell lung cancer (NSCLC). The induced adenomas are characterised by high genomic stability, a lack of tumor progression and pronounced cell-cell contacts raising the question whether disruption of E-cadherin complexes would promote progression to metastasis. Two genetic approaches were used to evaluate the role of adherens junctions in a C-RAF driven mouse model for NSCLC: conditional ablation of the Cdh1 gene and expression of dominant negative (dn) E-cadherin. Disruption of E-cadherin function caused massive formation of intratumoral vessels that was reversible in the early phase of induction. Vascularized tumors grew more rapidly, developed invasive fronts and gave rise to micrometastasis. ß-catenin was identified as a critical effector of E-cadherin disruption leading to up-regulation of angiogenic inducers (VEGF-A and VEGF-C) in mouse and human lung tumor cell lines. In vivo, lung tumor cells with disrupted E-cadherin expressed ß-catenin target genes of endodermal and other lineages suggesting that reprogramming may be involved in metastatic progression.