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The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549) and endothelium (human pulmonary artery epithelial cells, HPAEC) on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC), monocyte-derived DC (moDC) and myeloid DC (mDC), were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA.
In the present work, the objective has been to analyse the compatibility of plant and human transcriptional machinery. The experiments revealed that nuclear import and export are conserved among plants and mammals. Further it has been shown that transactivation of a human promoter occurs by human transcription factor NF-\(\kappa\) B in plant cells, demonstrating that the transcriptional machinery is highly conserved in both kingdoms. Functionality was also seen for regulatory elements of NF-\(\kappa\) B such as its inhibitor I\(\kappa\)B isoform \(\alpha\) that negatively regulated the transactivation activity of the p50/RelA heterodimer by interaction with NF-\(\kappa\)B in plant cells. Nuclear export of RelA could be demonstrated by FRAP-measurements so that RelA shows nucleo-cytoplasmic shuttling as reported for RelA in mammalian cells. The data reveals the high level of compatibility of human transcriptional elements with the plant transcriptional machinery. Thus, Arabidopsis thaliana mesophyll protoplasts might provide a new heterologous expression system for the investigation of the human NF-\(\kappa\)B signaling pathways. The system successfully enabled the controlled manipulation of NF-\(\kappa\)B activity. We suggest the plant protoplast system as a tool for reconstitution and analyses of mammalian pathways and for direct observation of responses to e. g. pharmaceuticals. The major advantage of the system is the absence of interference with endogenous factors that affect and crosstalk with the pathway.
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.
DNA Methylation Mediated Control of Gene Expression Is Critical for Development of Crown Gall Tumors
(2013)
Crown gall tumors develop after integration of the T-DNA of virulent Agrobacterium tumefaciens strains into the plant genome. Expression of the T-DNA–encoded oncogenes triggers proliferation and differentiation of transformed plant cells. Crown gall development is known to be accompanied by global changes in transcription, metabolite levels, and physiological processes. High levels of abscisic acid (ABA) in crown galls regulate expression of drought stress responsive genes and mediate drought stress acclimation, which is essential for wild-type-like tumor growth. An impact of epigenetic processes such as DNA methylation on crown gall development has been suggested; however, it has not yet been investigated comprehensively. In this study, the methylation pattern of Arabidopsis thaliana crown galls was analyzed on a genome-wide scale as well as at the single gene level. Bisulfite sequencing analysis revealed that the oncogenes Ipt, IaaH, and IaaM were unmethylated in crown galls. Nevertheless, the oncogenes were susceptible to siRNA–mediated methylation, which inhibited their expression and subsequently crown gall growth. Genome arrays, hybridized with methylated DNA obtained by immunoprecipitation, revealed a globally hypermethylated crown gall genome, while promoters were rather hypomethylated. Mutants with reduced non-CG methylation developed larger tumors than the wild-type controls, indicating that hypermethylation inhibits plant tumor growth. The differential methylation pattern of crown galls and the stem tissue from which they originate correlated with transcriptional changes. Genes known to be transcriptionally inhibited by ABA and methylated in crown galls became promoter methylated upon treatment of A. thaliana with ABA. This suggests that the high ABA levels in crown galls may mediate DNA methylation and regulate expression of genes involved in drought stress protection. In summary, our studies provide evidence that epigenetic processes regulate gene expression, physiological processes, and the development of crown gall tumors.
Background
The identification of additional prognostic markers to improve risk stratification and to avoid overtreatment is one of the most urgent clinical needs in prostate cancer (PCa). MicroRNAs, being important regulators of gene expression, are promising biomarkers in various cancer entities, though the impact as prognostic predictors in PCa is poorly understood. The aim of this study was to identify specific miRNAs as potential prognostic markers in high-risk PCa and to validate their clinical impact.
Methodology and Principal Findings
We performed miRNA-microarray analysis in a high-risk PCa study group selected by their clinical outcome (clinical progression free survival (CPFS) vs. clinical failure (CF)). We identified seven candidate miRNAs (let-7a/b/c, miR-515-3p/5p, -181b, -146b, and -361) that showed differential expression between both groups. Further qRT-PCR analysis revealed down-regulation of members of the let-7 family in the majority of a large, well-characterized high-risk PCa cohort (n = 98). Expression of let-7a/b/and -c was correlated to clinical outcome parameters of this group. While let-7a showed no association or correlation with clinical relevant data, let-7b and let-7c were associated with CF in PCa patients and functioned partially as independent prognostic marker. Validation of the data using an independent high-risk study cohort revealed that let-7b, but not let-7c, has impact as an independent prognostic marker for BCR and CF. Furthermore, we identified HMGA1, a non-histone protein, as a new target of let-7b and found correlation of let-7b down-regulation with HMGA1 over-expression in primary PCa samples.
Conclusion
Our findings define a distinct miRNA expression profile in PCa cases with early CF and identified let-7b as prognostic biomarker in high-risk PCa. This study highlights the importance of let-7b as tumor suppressor miRNA in high-risk PCa and presents a basis to improve individual therapy for high-risk PCa patients.
The anti-silencing function protein 1 (Asf1) is a chaperone that forms a complex with histones H3 and H4 facilitating dimer deposition and removal from chromatin. Most eukaryotes possess two different Asf1 chaperones but their specific functions are still unknown. Trypanosomes, a group of early-diverged eukaryotes, also have two, but more divergent Asf1 paralogs than Asf1 of higher eukaryotes. To unravel possible different functions, we characterized the two Asf1 proteins in Trypanosoma brucei. Asf1A is mainly localized in the cytosol but translocates to the nucleus in S phase. In contrast, Asf1B is predominantly localized in the nucleus, as described for other organisms. Cytosolic Asf1 knockdown results in accumulation of cells in early S phase of the cell cycle, whereas nuclear Asf1 knockdown arrests cells in S/G2 phase. Overexpression of cytosolic Asf1 increases the levels of histone H3 and H4 acetylation. In contrast to cytosolic Asf1, overexpression of nuclear Asf1 causes less pronounced growth defects in parasites exposed to genotoxic agents, prompting a function in chromatin remodeling in response to DNA damage. Only the cytosolic Asf1 interacts with recombinant H3/H4 dimers in vitro. These findings denote the early appearance in evolution of distinguishable functions for the two Asf1 chaperons in trypanosomes.
Bone Morphogenetic Proteins (BMPs) are important growth factors that regulate many cellular processes. During embryogenesis they act as morphogens and play a critical role during organ development. They influence cell fates via concentration-gradients in the embryos where cells transduce this extracellular information into gene expression profiles and cell fate decisions. How receiving cells decode and quantify BMP2/4 signals is hardly understood. There is little data on the quantitative relationships between signal input, transducing molecules, their states and location, and ultimately their ability to integrate graded systemic inputs and generate qualitative responses. Understanding this signaling network on a quantitative level should be considered a prerequisite for efficient pathway modulation, as the BMP pathway is a prime target for therapeutic invention. Hence, we quantified the spatial distribution of the main signal transducer of the BMP2/4 pathway in response to different types and levels of stimuli in c2c12 cells. We found that the subcellular localization of Smad1 is independent of ligand concentration. In contrast, Smad1 phosphorylation levels relate proportionally to BMP2 ligand concentrations and they are entirely located in the nucleus. Interestingly, we found that BMP2 stimulates target gene expression in non-linear, wave-like forms. Amplitudes showed a clear concentration-dependency, for sustained and transient stimulation. We found that even burst-stimulation triggers gene-expression wave-like modulations that are detectable for at least 30 h. Finally, we show here that target gene expression oscillations depend on receptor kinase activity, as the kinase drives further expression pulses without receptor reactivation and the target gene expression breaks off after inhibitor treatment in c2c12 cells.
Background: The frequency of the most observed cancer, Non Hodgkin Lymphoma (NHL), is further rising. Diffuse large B-cell lymphoma (DLBCL) is the most common of the NHLs. There are two subgroups of DLBCL with different gene expression patterns: ABC (“Activated B-like DLBCL”) and GCB (“Germinal Center B-like DLBCL”). Without therapy the patients often die within a few months, the ABC type exhibits the more aggressive behaviour. A further B-cell lymphoma is the Mantle cell lymphoma (MCL). It is rare and shows very poor prognosis. There is no cure yet. Methods: In this project these B-cell lymphomas were examined with methods from bioinformatics, to find new characteristics or undiscovered events on the molecular level. This would improve understanding and therapy of lymphomas. For this purpose we used survival, gene expression and comparative genomic hybridization (CGH) data. In some clinical studies, you get large data sets, from which one can reveal yet unknown trends. Results (MCL): The published proliferation signature correlates directly with survival. Exploratory analyses of gene expression and CGH data of MCL samples (n=71) revealed a valid grouping according to the median of the proliferation signature values. The second axis of correspondence analysis distinguishes between good and bad prognosis. Statistical testing (moderate t-test, Wilcoxon rank-sum test) showed differences in the cell cycle and delivered a network of kinases, which are responsible for the difference between good and bad prognosis. A set of seven genes (CENPE, CDC20, HPRT1, CDC2, BIRC5, ASPM, IGF2BP3) predicted, similarly well, survival patterns as proliferation signature with 20 genes. Furthermore, some bands could be associated with prognosis in the explorative analysis (chromosome 9: 9p24, 9p23, 9p22, 9p21, 9q33 and 9q34). Results (DLBCL): New normalization of gene expression data of DLBCL patients revealed better separation of risk groups by the 2002 published signature based predictor. We could achieve, similarly well, a separation with six genes. Exploratory analysis of gene expression data could confirm the subgroups ABC and GCB. We recognized a clear difference in early and late cell cycle stages of cell cycle genes, which can separate ABC and GCB. Classical lymphoma and best separating genes form a network, which can classify and explain the ABC and GCB groups. Together with gene sets which identify ABC and GCB we get a network, which can classify and explain the ABC and GCB groups (ASB13, BCL2, BCL6, BCL7A, CCND2, COL3A1, CTGF, FN1, FOXP1, IGHM, IRF4, LMO2, LRMP, MAPK10, MME, MYBL1, NEIL1 and SH3BP5; Altogether these findings are useful for diagnosis, prognosis and therapy (cytostatic drugs).
Background
Enteric glial cells (EGCs) are the main constituent of the enteric nervous system and share similarities with astrocytes from the central nervous system including their reactivity to an inflammatory microenvironment. Previous studies on EGC pathophysiology have specifically focused on mucosal glia activation and its contribution to mucosal inflammatory processes observed in the gut of inflammatory bowel disease (IBD) patients. In contrast knowledge is scarce on intestinal inflammation not locally restricted to the mucosa but systemically affecting the intestine and its effect on the overall EGC network.
Methods and Results
In this study, we analyzed the biological effects of a systemic LPS-induced hyperinflammatory insult on overall EGCs in a rat model in vivo, mimicking the clinical situation of systemic inflammation response syndrome (SIRS). Tissues from small and large intestine were removed 4 hours after systemic LPS-injection and analyzed on transcript and protein level. Laser capture microdissection was performed to study plexus-specific gene expression alterations. Upon systemic LPS-injection in vivo we observed a rapid and dramatic activation of Glial Fibrillary Acidic Protein (GFAP)-expressing glia on mRNA level, locally restricted to the myenteric plexus. To study the specific role of the GFAP subpopulation, we established flow cytometry-purified primary glial cell cultures from GFAP promotor-driven EGFP reporter mice. After LPS stimulation, we analyzed cytokine secretion and global gene expression profiles, which were finally implemented in a bioinformatic comparative transcriptome analysis. Enriched GFAP+ glial cells cultured as gliospheres secreted increased levels of prominent inflammatory cytokines upon LPS stimulation. Additionally, a shift in myenteric glial gene expression profile was induced that predominantly affected genes associated with immune response.
Conclusion and Significance
Our findings identify the myenteric GFAP-expressing glial subpopulation as particularly susceptible and responsive to acute systemic inflammation of the gut wall and complement knowledge on glial involvement in mucosal inflammation of the intestine.