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The Gram-negative, spiral-shaped, microaerophilic bacterium Helicobacter pylori is the causative agent of various disorders of the upper gastrointestinal tract, such as chronic superficial gastritis, chronic active gastritis, peptic ulceration and adenocarcinoma. Although many of the bacterial factors associated with disease development have been analysed in some detail in the recent years, very few studies have focused so far on the mechanisms that regulate expression of these factors at the molecular level. In an attempt to obtain an overview of the basic mechanisms of virulence gene expression in H. pylori, three important virulence factors of this pathogen, representative of different pathogenic mechanisms and different phases of the infectious process, are investigated in detail in the present thesis regarding their transcriptional regulation. As an essential factor for the early phase of infection, including the colonisation of the gastric mucosa, the flagella are analysed; the chaperones including the putative adhesion factors GroEL and DnaK are investigated as representatives of the phase of adherence to the gastric epithelium and persistence in the mucus layer; and finally the cytotoxin associated antigen CagA is analysed as representative of the cag pathogenicity island, which is supposed to account for the phenomena of chronic inflammation and tissue damage observed in the later phases of infection. RNA analyses and in vitro transcription demonstrate that a single promoter regulates expression of cagA, while two promoters are responsible for expression of the upstream divergently transcribed cagB gene. All three promoters are shown to be recognised by RNA polymerase containing the vegetative sigma factor sigma 80. Promoter deletion analyses establish that full activation of the cagA promoter requires sequences up to -70 and binding of the C-terminal portion of the alpha subunit of RNA polymerase to an UP-like element located between -40 and -60, while full activation of the major cagB promoter requires sequences upstream of -96 which overlap with the cagA promoter. These data suggest that the promoters of the pathogenicity island represent a class of minimum promoters, that ensure a basic level of transcription, while full activation requires regulatory elements or structural DNA binding proteins that provide a suitable DNA context. Regarding flagellar biosynthesis, a master transcriptional factor is identified that regulates expression of a series of flagellar basal body and hook genes in concert with the alternative sigma factor sigma 54. Evidence is provided that this regulator, designated FlgR (for flagellar regulatory protein), is necessary for motility and transcription of five promoters for seven basal body and hook genes. In addition, FlgR is shown to act as a repressor of transcription of the sigma 28-regulated promoter of the flaA gene, while changes in DNA topology are shown to affect transcription of the sigma 54-regulated flaB promoter. These data indicate that the regulatory network that governs flagellar gene expression in H. pylori shows similarities to the systems of both Salmonella spp. and Caulobacter crescentus. In contrast to the flagellar genes which are regulated by three different sigma factors, the three operons encoding the major chaperones of H. pylori are shown to be transcribed by RNA polymerase containing the vegetative sigma factor sigma 80. Expression of these operons is shown to be regulated negatively by the transcriptional repressor HspR, a homologue of a repressor protein of Streptomyces spp., known to be involved in negative regulation of heat shock genes. In vitro studies with purified recombinant HspR establish that the protein represses transcription by binding to large DNA regions centered around the transcription initiation site in the case of one promoter, and around -85 and -120 in the case of the the other two promoters. In contrast to the situation in Streptomyces, where transcription of HspR-regulated genes is induced in response to heat shock, transcription of the HspR-dependent genes in H. pylori is not inducible with thermal stimuli. Transcription of two of the three chaperone encoding operons is induced by osmotic shock, while transcription of the third operon, although HspR-dependent, is not affected by salt treatment. Taken together, the analyses carried out indicate that H. pylori has reduced its repertoire of specific regulatory proteins to a basic level that may ensure coordinate regulation of those factors that are necessary during the initial phase of infection including the passage through the gastric lumen and the colonisation of the gastric mucosa. The importance of DNA topology and/or context for transcription of many virulence gene promoters may on the other hand indicate, that a sophisticated global regulatory network is present in H. pylori, which influences transcription of specific subsets of virulence genes in response to changes in the microenvironment.
Cardiovascular disease is the leading cause of mortality in both men and women in the Western world. Earlier observations have pointed out that pre-menopausal women have a lower risk of developing cardiovascular disease than age-matched men, with an increase in risk after the onset of menopause. This observation has directed the attention to estrogen as a potential protective factor in the heart. So far the focus of research and clinical studies has been the vascular system, leaving the current knowledge on the role of estrogen in the myocardium itself rather scarce. Functional estrogen receptor-alpha as well as -beta have recently been identified in the myocardium, making the myocardium an estrogen target organ. The focus of this thesis was 1) to investigate the role of estrogen and estrogen receptors in modulating myocardial gene expression both in vivo in an animal model for cardiac hypertrophy (spontaneously hypertensive rats; SHR), as well as in vitro in isolated neonatal cardiomyocytes, 2) to investigate the mechanisms of the rapid induction of an estrogen target gene, the early growth response gene-1 (Egr-1) and 3) to initiate the search for novel estrogen target genes in the myocardium. 1) The effects of estrogen on the expression of one of the major myocardial specific contractile proteins, the alpha-myosin heavy chain (alpha-MHC) have been investigated. In ovarectomised animals treated either with 17beta-estradiol alone or in combination with a specific estrogen receptor antagonist, ICI 182780, it was shown that both alpha-MHC mRNA and protein were upregulated by estrogen in an estrogen receptor specific manner. The in vivo results were confirmed in vitro in isolated neonatal cardiomyocytes which showed that estrogen has a direct action on the myocardium potent enough to upregulate the expression of alpha-MHC. Furthermore it was shown that the alpha-MHC promoter is induced by estrogen in an estrogen receptor-dependent manner and first investigations into the mechanisms involved in this upregulation identified Egr-1 as a potential transcription factor which, upon induction by estrogen, drives the expression of the alpha-MHC promoter. 2) Previously it was shown that Egr-1 is rapidly induced by estrogen in an estrogen receptor-dependent manner which was mediated via 5 serum response elements (SREs) in the promoter region and surprisingly not via the estrogen response elements (EREs). In this study it was shown that estrogen-treatment of cardiomyocytes resulted in the recruitment of serum response factor (SRF), or an antigenically related protein, to the SREs in the Egr-1 promoter, which was specifically inhibited by the estrogen receptor antagonist ICI 182780. Transfection experiments showed that estrogen induced a heterologous promoter consisting only of 5 tandem repeats of the c-fos SRE in an ER-dependent manner, which identified SREs as promoter elements able to confer an estrogen response to target genes. 3) Potentially new target genes regulated by estrogen in vivo were analysed using hearts of ovarectomised animals as well as ovarectomised animals treated with estrogen. Analyses of cDNA microarray filters containing 1250 known genes identified 24 genes that were modified by estrogen in vivo. Among these genes, some might have potentially important functions in the heart and further analyses of these genes will create a more global picture of the role and function of estrogen in the myocardium. Taken together, the results showed that estrogen does have a direct action on the myocardium both by regulating the expression of myocardial specific genes in vivo, as well as exerting rapid non-nuclear effects in cardiac myocytes. It was shown that SREs in the promoter region of genes can confer an estrogen response to genes identifying SREs as important elements in regulation of genes by estrogen. Furthermore, 24 potentially new estrogen targets were identified in the myocardium, contributing to the general understanding of estrogen action in the myocardium.
DNA microarrays have become a standard technique to assess the mRNA levels for complete genomes. To identify significantly regulated genes from these large amounts of data a wealth of methods has been developed. Despite this, the functional interpretation (i.e. deducing biological hypothesis from the data) still remains a major bottleneck in microarray data analysis. Most available methods display the set of significant genes in long lists, from which common functional properties have to be extracted. This is not only a tedious and time-consuming task, which becomes less and less feasible with increasing numbers of experimental conditions, but is also prone to errors, since it is commonly done by eye. In the course of this work methods have been developed and tested, that allow for a computerbased analysis of functional properties being relevant in the given experimental setting. To this end the Gene Ontology was chosen as an appropriate source of annotation data, because it combines human-readability with computer-accessibility of the annotations term and thus allows for a statistical analysis of functional properties. Here the gene-annotations are integrated in a Correspondence Analysis which allows to visualize genes, hybridizations and functional categories in a single plot. Due to the increasing amounts of available annotations and the fact that in most settings only few functional processes are differentially regulated, several filter criteria have been developed to reduce the number of displayed annotations to a set being relevant in the given experimental setting. The applicability of the presented visualization and filtering have both been validated on datasets of varying complexity. Starting from the well studied glucose-pathway in S. cerevisiae up to the comparison of different tumor types in human. In both settings the method generated well interpretable plots, which allowed for an immediate identification of the major functional differences between the experimental conditions [90]. While the integration of annotation data like GO facilitates functional interpretation, it lacks the capability to identify key regulatory elements. To facilitate such an analysis, the occurrence of transcription factor binding sites in upstream regions of genes has been integrated to the analysis as well. Again this methodology was biologically validated on S. cerevisiae as well human cancer data sets. In both settings TFs known to exhibit central roles for the observed transcriptional changes were plotted in marked positions and thus could be immediately identified [206]. In essence, integration of supplementary information in Correspondence Analysis visualizes genes, hybridizations and annotation data in a single, well interpretable plot. This allows for an intuitive identification of relevant annotations even in complex experimental settings. The presented approach is not limited to the shown types of data, but is generalizable to account for the majority of the available annotation data.
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).
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.
The chick midbrain is subdivided into functionally distinct ventral and dorsal domains, tegmentum and optic tectum. In the mature tectum, neurons are organized in layers, while they form discrete nuclei in the tegmentum. An interesting characteristic of the embryonic brain is the development of a large optic tectum, of which the growth becomes obvious at embryonic day 3 (E3). Dorsoventral (DV) specification of the early midbrain should thus play a crucial role for the organization of the neuronal circuitry in optic tectum and tegmentum. In the first part of my thesis, I investigated regional commitment and establishment of cellular differences along the midbrain DV axis. I examined the commitment of gene expression patterns in isolated ventral and dorsal tissue in vivo and in vitro, and studied their cell mixing properties. Explant cultures, and grafting of dorsal midbrain into a ventral environment or vice versa, revealed a gradual increase in the autonomy of region-specific gene regulation between, which was accompanied by a gradual increase in differential adhesive properties from E2 to E3, once the DV axis polarity was fixed. These events happened at a time-point when the majority of midbrain cells are not yet differentiated. Long-term transplantation (6 - 9 days) using quail cells from ventral midbrain as grafts showed the same result. Hence, the results suggest that progressive specification of the midbrain DV axis is accompanied by progressively reduced cell mixing between dorsal and ventral precursors, leading to a partial regionalization of midbrain tissue into autonomous units of precursor cell populations. In the second part I investigated the genes that might be involved in regulating the growth of the tectum. In particular, I focused on the role of Pax7 transcription factor, a paired domain protein. The results suggested that Pax7 was involved in regulating the medial-lateral extension of the tectum. Over expression of Pax7 in dorsal midbrain led to an enlarged tectum accompanied by a raise in cell division, while Pax7 knockdown by shrank caused a reduction in tectum. The overall pattern of neuronal differentiation was not disturbed by an up or down regulation of Pax7. Pax7 also positively regulated Pax3, another pair-ruled gene expressed dorsally. These results suggest that Pax7 very likely together with Pax3 could facilitate or maintain neural cell proliferation in the midbrain at early stages and that a regulation of the size in that region does not influence the neuronal patterning of the developmental field. I further checked the expression and function of a GFPase Rab 23, that was suggested to be involved in the DV patterning in mouse neural tube as a negative regulator of Shh signaling. Overexpression of Rab23 indicated that it facilitated the expression of Pax7 and Pax3 in the neural tube and suppressed ventral genes like Nkx6.1 cell autonomously, however, it did not disturb neuronal patterning. Interestingly, a thorough expression study of Rab 23 during chick early development revealed that Rab23 is already expressed very early and asymmetrically during gastrulation, suggesting a possible role of Rab23 on the left-right determination of Hensen’s node. In combination with the result that Rab23 is expressed in the notochord early in development, I assume that both Rab23 and Shh exist in all neural progenitor cells initially, and when their expression patterns separate gradually the neural cells adopt a ventral or dorsal fate according to their location along the dorsoventral axis. The avian embryo is a classic system used widely to investigate questions of vertebrate development. The easy and cheap accessibility of the embryo for in ovo or ex ovo experiments all around the year make it an ideal animal model to work with. The only recently developed method of over expressing genes in specific cells or regions in the chick embryo by electroporation enabled me to study different ways of gene suppression using this way of gene transfection. Thus, I compared the effect of long-hairpin and short hairpin dsRNA in different vectors and antisense morpholino oligonucleotides. The results revealed that all hairpin dsRNA constructs did reduce gene and protein expression often accompanied by morphological changes. Most efficiently were shRNAi constructs cloned into a siRNA-specific vector – pSilencer 1.0-U6. Gene silencing was already well observed 36 hours after transfection. In comparison antisense morpholino oligonucleotides did not show such big gene reduction as the shRNA in pSilencer. Taken together, this methodical research proposes that the shRNA in the pSilencer vector was a good and effective tool to reduce gene and protein expression locally.
Recent progresses and developments in molecular biology provide a wealth of new but insufficiently characterised data. This fund comprises amongst others biological data of genomic DNA, protein sequences, 3-dimensional protein structures as well as profiles of gene expression. In the present work, this information is used to develop new methods for the characterisation and classification of organisms and whole groups of organisms as well as to enhance the automated gain and transfer of information. The first two presented approaches (chapters 4 und 5) focus on the medically and scientifically important enterobacteria. Its impact in medicine and molecular biology is founded in versatile mechanisms of infection, their fundamental function as a commensal inhabitant of the intestinal tract and their use as model organisms as they are easy to cultivate. Despite many studies on single pathogroups with clinical distinguishable pathologies, the genotypic factors that contribute to their diversity are still partially unknown. The comprehensive genome comparison described in Chapter 4 was conducted with numerous enterobacterial strains, which cover nearly the whole range of clinically relevant diversity. The genome comparison constitutes the basis of a characterisation of the enterobacterial gene pool, of a reconstruction of evolutionary processes and of comprehensive analysis of specific protein families in enterobacterial subgroups. Correspondence analysis, which is applied for the first time in this context, yields qualitative statements to bacterial subgroups and the respective, exclusively present protein families. Specific protein families were identified for the three major subgroups of enterobacteria namely the genera Yersinia and Salmonella as well as to the group of Shigella and E. coli by applying statistical tests. In conclusion, the genome comparison-based methods provide new starting points to infer specific genotypic traits of bacterial groups from the transfer of functional annotation. Due to the high medical importance of enterobacterial isolates their classification according to pathogenicity has been in focus of many studies. The microarray technology offers a fast, reproducible and standardisable means of bacterial typing and has been proved in bacterial diagnostics, risk assessment and surveillance. The design of the diagnostic microarray of enterobacteria described in chapter 5 is based on the availability of numerous enterobacterial genome sequences. A novel probe selection strategy based on the highly efficient algorithm of string search, which considers both coding and non-coding regions of genomic DNA, enhances pathogroup detection. This principle reduces the risk of incorrect typing due to restrictions to virulence-associated capture probes. Additional capture probes extend the spectrum of applications of the microarray to simultaneous diagnostic or surveillance of antimicrobial resistance. Comprehensive test hybridisations largely confirm the reliability of the selected capture probes and its ability to robustly classify enterobacterial strains according to pathogenicity. Moreover, the tests constitute the basis of the training of a regression model for the classification of pathogroups and hybridised amounts of DNA. The regression model features a continuous learning capacity leading to an enhancement of the prediction accuracy in the process of its application. A fraction of the capture probes represents intergenic DNA and hence confirms the relevance of the underlying strategy. Interestingly, a large part of the capture probes represents poorly annotated genes suggesting the existence of yet unconsidered factors with importance to the formation of respective virulence phenotypes. Another major field of microarray applications is gene expression analysis. The size of gene expression databases rapidly increased in recent years. Although they provide a wealth of expression data, it remains challenging to integrate results from different studies. In chapter 6 the methodology of an unsupervised meta-analysis of genome-wide A. thaliana gene expression data sets is presented, which yields novel insights in function and regulation of genes. The application of kernel-based principal component analysis in combination with hierarchical clustering identified three major groups of contrasts each sharing overlapping expression profiles. Genes associated with two groups are known to play important roles in Indol-3 acetic acid (IAA) mediated plant growth and development as well as in pathogen defence. Yet uncharacterised serine-threonine kinases could be assigned to novel functions in pathogen defence by meta-analysis. In general, hidden interrelation between genes regulated under different conditions could be unravelled by the described approach. HMMs are applied to the functional characterisation of proteins or the detection of genes in genome sequences. Although HMMs are technically mature and widely applied in computational biology, I demonstrate the methodical optimisation with respect to the modelling accuracy on biological data with various distributions of sequence lengths. The subunits of these models, the states, are associated with a certain holding time being the link to length distributions of represented sequences. An adaptation of simple HMM topologies to bell-shaped length distributions described in chapter 7 was achieved by serial chain-linking of single states, while residing in the class of conventional HMMs. The impact of an optimisation of HMM topologies was underlined by performance evaluations with differently adjusted HMM topologies. In summary, a general methodology was introduced to improve the modelling behaviour of HMMs by topological optimisation with maximum likelihood and a fast and easily implementable moment estimator. Chapter 8 describes the application of HMMs to the prediction of interaction sites in protein domains. As previously demonstrated, these sites are not trivial to predict because of varying degree in conservation of their location and type within the domain family. The prediction of interaction sites in protein domains is achieved by a newly defined HMM topology, which incorporates both sequence and structure information. Posterior decoding is applied to the prediction of interaction sites providing additional information of the probability of an interaction for all sequence positions. The implementation of interaction profile HMMs (ipHMMs) is based on the well established profile HMMs and inherits its known efficiency and sensitivity. The large-scale prediction of interaction sites by ipHMMs explained protein dysfunctions caused by mutations that are associated to inheritable diseases like different types of cancer or muscular dystrophy. As already demonstrated by profile HMMs, the ipHMMs are suitable for large-scale applications. Overall, the HMM-based method enhances the prediction quality of interaction sites and improves the understanding of the molecular background of inheritable diseases. With respect to current and future requirements I provide large-scale solutions for the characterisation of biological data in this work. All described methods feature a highly portable character, which allows for the transfer to related topics or organisms, respectively. Special emphasis was put on the knowledge transfer facilitated by a steadily increasing wealth of biological information. The applied and developed statistical methods largely provide learning capacities and hence benefit from the gain of knowledge resulting in increased prediction accuracies and reliability.
The Popeye domain containing (Popdc) gene family of membrane proteins is predominantly expressed in striated and smooth muscle tissues and has been shown to act as novel cAMP-binding proteins. In mice, loss of Popdc1 and Popdc2, respectively, affects sinus node function in the postnatal heart in an age and stress-dependent manner. In this thesis, I examined gene expression pattern and function of the Popdc gene family during zebrafish development with an emphasis on popdc2. Expression of the zebrafish popdc2 was exclusively present in cardiac and skeletal muscle during cardiac development, whereas popdc3 was expressed in striated muscle tissue and in distinct regions of the brain. In order to study the function of these genes, an antisense morpholino-based knockdown approach was used. Knockdown of popdc2 resulted in aberrant development of facial and tail musculature. In the heart, popdc2 morphants displayed irregular ventricular contractions with 2:1 and 3:1 ventricular pauses. Recordings of calcium transients using a transgenic indicator line Tg(cmlc2:gCaMP)s878 and selective plane illumination microscopy (SPIM) revealed the presence of an atrioventricular (AV) block in popdc2 morphants as well as a complete heart block. Interestingly, preliminary data revealed that popdc3 morphants developed a similar phenotype. In order to find a morphological correlate for the observed AV conduction defect, I studied the structure of the AV canal in popdc2 morphants using confocal analysis of hearts of the transgenic line Tg(cmlc2:eGFP-ras)s883, which outlines individual cardiac myocytes with the help of membrane-localized GFP. However, no evidence for morphological alterations was obtained. To ensure that the observed arrhythmia phenotype in the popdc2 morphant was based on a myocardial defect and not caused by defective valve development, live imaging was performed revealing properly formed valves. Thus, in agreement with the data obtained in knockout mice, popdc2 and popdc3 genes in zebrafish are involved in the regulation of cardiac electrical activity. However, both genes are not required for cardiac pacemaking, but they play essential roles in AV conduction. In order to elucidate the biological importance of cAMP-binding, wild type Popdc1 as well as mutants with a significant reduction in binding affinity for cAMP in vitro were overexpressed in zebrafish embryos. Expression of wild type Popdc1 led to a cardiac insufficiency phenotype characterized by pericardial edema and venous blood retention. Strikingly, the ability of the Popdc1 mutants to induce a cardiac phenotype correlated with the binding affinity for cAMP. These data suggest that cAMP-binding represents an important biological property of the Popdc protein family.
Applying microarray‐based techniques to study gene expression patterns: a bio‐computational approach
(2010)
The regulation and maintenance of iron homeostasis is critical to human health. As a constituent of hemoglobin, iron is essential for oxygen transport and significant iron deficiency leads to anemia. Eukaryotic cells require iron for survival and proliferation. Iron is part of hemoproteins, iron-sulfur (Fe-S) proteins, and other proteins with functional groups that require iron as a cofactor. At the cellular level, iron uptake, utilization, storage, and export are regulated at different molecular levels (transcriptional, mRNA stability, translational, and posttranslational). Iron regulatory proteins (IRPs) 1 and 2 post-transcriptionally control mammalian iron homeostasis by binding to iron-responsive elements (IREs), conserved RNA stem-loop structures located in the 5’- or 3‘- untranslated regions of genes involved in iron metabolism (e.g. FTH1, FTL, and TFRC). To identify novel IRE-containing mRNAs, we integrated biochemical, biocomputational, and microarray-based experimental approaches. Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Methods In this project response to the iron treatment was examined under different conditions using bioinformatical methods. This would improve our understanding of an iron regulatory network. For these purposes we used microarray gene expression data. To identify novel IRE-containing mRNAs biochemical, biocomputational, and microarray-based experimental approaches were integrated. IRP/IRE messenger ribonucleoproteins were immunoselected and their mRNA composition was analysed using an IronChip microarray enriched for genes predicted computationally to contain IRE-like motifs. Analysis of IronChip microarray data requires specialized tool which can use all advantages of a customized microarray platform. Novel decision-tree based algorithm was implemented using Perl in IronChip Evaluation Package (ICEP). Results IRE-like motifs were identified from genomic nucleic acid databases by an algorithm combining primary nucleic acid sequence and RNA structural criteria. Depending on the choice of constraining criteria, such computational screens tend to generate a large number of false positives. To refine the search and reduce the number of false positive hits, additional constraints were introduced. The refined screen yielded 15 IRE-like motifs. A second approach made use of a reported list of 230 IRE-like sequences obtained from screening UTR databases. We selected 6 out of these 230 entries based on the ability of the lower IRE stem to form at least 6 out of 7 bp. Corresponding ESTs were spotted onto the human or mouse versions of the IronChip and the results were analysed using ICEP. Our data show that the immunoselection/microarray strategy is a feasible approach for screening bioinformatically predicted IRE genes and the detection of novel IRE-containing mRNAs. In addition, we identified a novel IRE-containing gene CDC14A (Sanchez M, et al. 2006). The IronChip Evaluation Package (ICEP) is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip, but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls (Vainshtein Y, et al., 2010).
Switches in trypanosome differentiation: ALBA proteins acting on post-transcriptional mRNA control
(2011)
Trypanosoma brucei is a digenetic eukaryotic parasite that develops in different tissues of a mammalian host and a tsetse fly. It is responsible for sleeping sickness in sub-saharan Africa. The parasite cycle involves more than nine developmental stages that can be clearly distinguished by their general morphology, their metabolism and the relative positioning of their DNA-containing organelles. During their development, trypanosomes remain exclusively extracellular and encounter changing environments with different physico-chemical properties (nutritional availability, viscosity, temperature, etc.). It has been proposed that trypanosomes use their flagellum as a sensing organelle, in agreement with the established role of structurally-related cilia in metazoa and ciliates. Recognition of environmental triggers is presumed to be at the initiation of differentiation events, leading to the parasite stage that is the best suited to the new environment. These changes are achieved by the modification of gene expression programmes, mostly underlying post-transcriptional control of mRNA transcripts. We first demonstrate that the RNA-binding proteins ALBA3/4 are involved in specific differentiation processes during the parasite development in the fly. They are cytosolic and expressed throughout the parasite cycle with the exception of the stages found in the tsetse fly proventriculus, as shown by both immunofluorescence and live cell analysis upon endogenous tagging with YFP. Knock-down of both proteins in the developmental stage preceding these forms leads to striking modifications: cell elongation, cell cycle arrest and relocalization of the nucleus in a posterior position, all typical of processes acting in parasites found in the proventriculus region. When ALBA3 is over-expressed from an exogenous copy during infection, it interferes with the relocalization of the nucleus in proventricular parasites. This is not observed for ALBA4 over-expression that does not visibly impede differentiation. Both ALBA3/4 proteins react to starvation conditions by accumulating in cytoplasmic stress granules together with DHH1, a recognized RNA-binding protein. ALBA3/4 proteins also partially colocalize with granules formed by polyA+ RNA in these conditions. We propose that ALBA are involved in trypanosome differentiation processes where they control a subset of developmentally regulated transcripts. These processes involving ALBA3/4 are likely to result from the specific activation of sensing pathways. In the second part of the thesis, we identify novel flagellar proteins that could act in sensing mechanisms. Several protein candidates were selected from a proteomic analysis of intact flagella performed in the host laboratory. This work validates their flagellar localization with high success (85% of the proteins examined) and defines multiple different patterns of protein distribution in the flagellum. Two proteins are analyzed during development, one of them showing down-regulation in proventricular stages. The functional analysis of one novel flagellar membrane protein reveals its rapid dynamics within the flagellum but does not yield a visible phenotype in culture. This is coherent with sensory function that might not be needed in stable culture conditions, but could be required in natural conditions during development. In conclusion, this work adds new pieces to the puzzle of identifying molecular switches involved in developmental mRNA control and environmental sensing in trypanosome stages in the tsetse fly.