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Ziel dieser Arbeit ist es ein besseres Verständinis der molekularen Prozesse der Melanomentstehung und Tumorprogression zu gewinnen. Hierfür wurde ein Tiermodell transgener Medakas (Oryzias latipes) verwendet, welche als stabiles Transgen das Konstrukt mitf::xmrk besitzen. Diese Fische entwickelten Pigmentzelltumore, welche für eine Microarrayanalyse herangezogen wurden. Aus diesem Microarraydatensatz wurden 11 Gene ausgewählt, welche in dieser Arbeit näher untersucht wurden. Beobachtungen haben ergeben, dass sich bei transgenen Medakas, welche Xmrk exprimieren, verschiedene pigmentierte Hauttumore entwickeln. Diese Tumore wurden je nach ihrem verschiedenen Histiotyp klassifiziert und untersucht. Um einen Eindruck zu gewinnen, wie Xmrk die Transkription verschiedener Gene, welche in der Krebsentstehung und –progression eine wichtige Rolle spielen, beeinflusst, wurden pigmentierte Hauttumore transgener Medakas, so wie zu Vergleichszwecken hyperpigmentierte Haut transgener Medakas und Lymphome und gesunde Organe von Wildtyp-Medakas, untersucht. Mit Hilfe von Real-time-PCR’s wurden die folgenden Gene untersucht: G6PC, GAMT, GM2A, MAPK3, NID1, SLC24A5, SPP1, PDIA4, RASL11B, TACC2 und ZFAND5. Dabei konnte festgestellt werden, dass die Expression der Gene GM2A, MAPK3, NID1, PDIA4, RASL11B, SLC24A5 und ZFAND5 von Xmrk beeinflusst wird, während dies für die Gene G6PC, GAMT, SPP1 und TACC2 nicht zutrifft. Im Vergleich zu gesunder Haut werden GM2A, MAPK3, PDIA4, RASL11B, SLC24A5 und ZFAND5 in Tumoren höher exprimiert. Die Gene G6PC, GAMT, NID1, SPP1 und TACC2 werden dagegen verglichen mit gesunder Haut unverändert oder niedriger exprimiert. Die Bedeutung der erhöhten Genexpression lässt sich in vielen Fällen zurzeit nur theoretisch erfassen. Eine höhere Expression von SLC24A5 beispielsweise lässt vermuten, dass ein Zusammenhang zwischen der Melaninproduktion und der Zellproliferation besteht. Die Überexpression von GM2A weist dagegen auf eine Rolle von GM2A als Tumormarker hin. Dahingegen scheint die erniedrigte Expression von GAMT und G6PC Auskunft über den veränderten Stoffwechsel in Tumoren zu geben. Um diese Ergebnisse zu bestätigen und zu entschlüsseln wie genau Xmrk die Expression der getesteten Gene beeinflusst, sind allerdings noch weitere funktionelle Studien nötig. Generell kommt man zu dem Schluss, dass die Genexpression sich in jedem Tumor unterscheidet. Daher scheint jeder Tumor seinen eigenen Evolutionsweg zu beschreiten.
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.
Synapsen als Stellen der Kommunikation zwischen Neuronen besitzen spezialisierte Bereiche – Aktive Zonen (AZs) genannt –, die aus einem hoch komplexen Netzwerk von Proteinen aufgebaut sind und die Maschinerie für den Prozess der Neurotransmitter-Ausschüttung und das Vesikel-Recycling beinhalten. In Drosophila ist das Protein Bruchpilot (BRP) ein wichtiger Baustein für die T-förmigen Bänder („T-Bars“) der präsynaptischen Aktiven Zonen. BRP ist notwendig für eine intakte Struktur der Aktiven Zone und eine normale Exocytose von Neurotransmitter-Vesikeln. Auf der Suche nach Mutationen, welche die Verteilung von Bruchpilot im Gewebe beeinträchtigen, wurde eine P-Element-Insertion im Gen CG11489 an der Position 79D identifiziert, welches eine Kinase kodiert, die einen hohen Grad an Homologie zur Familie der SR Proteinkinasen (SRPKs) von Säugern aufweist. Die Mitglieder dieser Familie zeichnen sich durch eine evolutionär hoch konservierte zweigeteilte Kinasedomäne aus, die durch eine nicht konservierte Spacer-Sequenz unterbrochen ist. SRPKs phosphorylieren SR-Proteine, die zu einer evolutionär hoch konservierten Familie Serin/Arginin-reicher Spleißfaktoren gehören und konstitutive sowie alternative Spleißprozesse steuern und damit auf post-transkriptioneller Ebene die Genexpression regulieren. Mutation des Srpk79D-Gens durch die P-Element-Insertion (Srpk79DP1) oder eine Deletion im Gen (Srpk79DVN Nullmutante) führt zu auffälligen BRP-Akkumulationen in larvalen und adulten Nerven. In der vorliegenden Arbeit wird gezeigt, dass diese BRP-Akkumulationen auf Ultrastruktur-Ebene ausgedehnten axonalen Agglomeraten elektronendichter Bänder entsprechen und von klaren Vesikeln umgeben sind. Charakterisierung durch Immuno-Elektronenmikroskopie ergab, dass diese Strukturen BRP-immunoreaktiv sind. Um die Bildung BRP-enthaltender Agglomerate in Axonen zu verhindern und damit eine intakte Gehirnfunktion zu gewährleisten, scheint die SRPK79D nur auf niedrigem Niveau exprimiert zu werden, da die endogene Kinase mit verschiedenen Antikörpern nicht nachweisbar war. Wie in anderen Arbeiten gezeigt werden konnte, ist die Expression der PB-, PC- oder PF-Isoform der vier möglichen SRPK79D-Varianten, die durch alternativen Transkriptionsstart in Exon eins beziehungsweise drei und alternatives Spleißen von Exon sieben zustande kommen, zur Rettung des Phänotyps der BRP-Akkumulation im Srpk79DVN Nullmutanten-Hintergrund ausreichend. Zur Charakterisierung der Rescue-Eigenschaften der SRPK79D-PE-Isoform wurde mit der Klonierung der cDNA in einen UAS-Vektor begonnen. Offenbar beruht die Bildung der axonalen BRP-Agglomerate nicht auf einer Überexpression von BRP in den betroffenen Neuronen, denn auch bei reduzierter Expression des BRP-Proteins im Srpk79DVN Nullmutanten-Hintergrund entstehen die BRP-Agglomerate. In Köpfen der Srpk79DVN Nullmutante ist die Gesamtmenge an Bruchpilot-Protein im Vergleich zum Wildtyp nicht deutlich verändert. Auch die auf Protein-Ebene untersuchte Expression der verschiedenen Isoformen der präsynaptischen Proteine Synapsin, Sap47 und CSP weicht in der Srpk79DVN Nullmutante nicht wesentlich von der Wildtyp-Situation ab, sodass sich keine Hinweise auf verändertes Spleißen der entsprechenden prä-mRNAs ergeben. Jedes der sieben bekannten SR-Proteine von Drosophila ist ein potentielles Zielprotein der SRPK79D. Knock-down-Experimente für die drei hier untersuchten SR-Proteine SC35, X16/9G8 und B52/SRp55 im gesamten Nervensystem durch RNA-Interferenz zeigten allerdings keinen Effekt auf die Verteilung von BRP im Gewebe. Hinsichtlich der Flugfähigkeit der Tiere hat die Srpk79DVN Nullmutation keinen additiven Effekt zum Knock-down des BRP-Proteins, denn die Doppelmutanten zeigten bei der Bestimmung des Anteils an flugunfähigen Tieren vergleichbare Werte wie die Einzelmutanten, die entweder die Nullmutation im Srpk79D-Gen trugen, oder BRP reduziert exprimierten. Vermutlich sind Bruchpilot und die SR Proteinkinase 79D somit Teil desselben Signalwegs. Durch Doppelfärbungen mit Antikörpern gegen BRP und CAPA-Peptide wurde abschließend entdeckt, dass Bruchpilot auch im Median- und Transvers-Nervensystem (MeN/TVN) von Drosophila zu finden ist, welche die Neurohämal-Organe beherbergen. Aufgabe dieser Organe ist die Speicherung und Ausschüttung von Neuropeptid-Hormonen. Daher ist zu vermuten, dass das BRP-Protein neben Funktionen bei der Neurotransmitter-Exocytose möglicherweise eine Rolle bei der Ausschüttung von Neuropeptiden spielt. Anders als in den Axonen der larvalen Segmental- und Intersegmentalnerven der Srpk79DVN Nullmutante, die charakteristische BRP-Agglomerate aufweisen, hat die Mutation des Srpk79D-Gens in den Axonen der Va-Neurone, die das MeN/TVN-System bilden, keinen sichtbaren Effekt auf die Verteilung von Brp, denn das Muster bei Färbung gegen BRP weist keine deutlichen Veränderungen zum Wildtyp auf.
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).
Die Popeye domain containing (Popdc)-Gene bilden eine evolutionär stark konservierte Genfamilie mit präferenzieller Expression im Herzen und in der Skelettmuskulatur. In dieser Arbeit konnte gezeigt werden, dass Popdc1 in kardialen Myozyten in Glanzstreifen, lateralen Membranen und im T-Tubuli-System exprimiert wird und mit Ionenkanälen und anderen myozytären Membranproteinen wie Cav1.2, Caveolin 3 und NCX1 kolokalisiert ist. Im ventrikulären Reizleitungssystem ist die Expression von Popdc1 gegenüber dem ventrikulären Arbeitsmyokard erhöht, während Atrium und Sinusknoten nahezu äquivalente Expressionsdomänen aufweisen. Mithilfe von elektrophysiologischen Untersuchungen konnte bei den Popdc1-Nullmutanten eine stressinduzierte Sinusbradykardie festgestellt werden, die altersabhängig auftritt und auf Sinuspausen zurückzuführen ist. Histologische Untersuchungen, unter Zuhilfenahme des Sinusknotenmarkers HCN4, zeigten einen Zellverlust im inferioren Teil des Sinusknotens. Popdc1 ist ein Transmembranprotein, das eine 150 Aminosäure umfassende, stark konservierte Popeye-Domäne aufweist. Für diese Domäne konnte auf struktureller Ebene eine Homologie zu zyklischen Nukleotid-Bindungsdomänen vorhergesagt und eine Bindung an cAMP und cGMP experimentell demonstriert werden. Es handelt sich bei den Popdc-Proteinen um einen neuen Zweig der Bindungsproteine für zyklische Nukleotidmonophosphate (cNMP). Die Bindungssequenz weist signifikante Unterschiede zu anderen bereits identifizierten cNMP-Bindungsproteinen auf. Weiterhin wurde die Interaktion von Popdc1 mit TREK1, einem Mitglied der Tandemporenkanäle untersucht. Es zeigte sich, dass Popdc1 nach Koexpression in Froschoozyten, den TREK1-Strom erhöht und dass die β-adrenerge Inhibition des TREK1 Kanals durch Popdc1 verstärkt wird. Im Arbeitsmyokard, im kardialen Reizleitungssystem und in kotransfizierten Cos7-Zellen werden beide Proteine überlappend exprimiert. Diese Daten zeigen, dass Popdc1 eine wichtige Funktion bei der Regulation der Schrittmacheraktivität, der Aufrechterhaltung der Sinusknotenmorphologie und der Modulation von Ionenkanälen aufweist. Interessanterweise wurden von unserer Arbeitsgruppe bereits die gleichen Phänotypen für die Popdc2 Maus beschrieben, sodass die Popdc Genfamilie überlappende und redundante Funktionen aufweist.
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.
Ameisen der Gattung Camponotus beherbergen bakterielle Symbionten der Gattung Blochmannia in spezialisierten Zellen des Mitteldarms (Blochmann, 1882; Buchner, 1965; Sauer, 2000; Schröder et al., 1996). Die Genomsequenzierung dieser Symbionten zeigte, dass Blochmannia, ähnlich den Symbionten von Blattläusen, hauptsächlich Gene der Aminosäurebiosynthese beibehalten hat (Degnan et al., 2005; Gil et al., 2003). Die Relevanz dieser nahrungsaufwertenden Funktion konnte experimentell bestätigt werden (Feldhaar et al., 2007). Ein Schwerpunkt der vorliegenden Arbeit war die Aufklärung der dynamischen Interaktion der beiden Partner während des komplexen Lebenszyklus des holometabolen Wirtes. Frühere Studien deuteten darauf hin, dass die Symbiose vor allem während der Larven- und Puppenphasen von Bedeutung sein könnte (Feldhaar et al., 2007; Wolschin et al., 2004; Zientz et al., 2006). Mit fluoreszenter in situ Hybridisierung (FISH) und konfokaler Laserscanning Mikroskopie konnte in der vorliegenden Arbeit die Lokalisierung von B. floridanus während der wichtigsten Entwicklungsstadien aufgeklärt werden. Hierbei konnte gezeigt werden, dass die Symbionten schon im ersten Larvenstadium in spezialisierten Zellen um den Darm angeordnet sind, aber in späteren Stadien nicht, wie bisher angenommen, auf diese Bakteriozyten beschränkt sind, sondern bis zum Schlupf der jungen Arbeiterinnen massiv andere Darmzellen infizieren. Übereinstimmend mit Bestimmungen der Zellzahl in den verschiedenen Wirtsstadien ist die Anzahl der Symbionten gegen Ende der Metamorphose am höchsten. Die Symbiose degeneriert in sehr alten Arbeiterinnen, gut gefüllte Bakteriozyten werden jedoch noch monatelang beibehalten. Mit Macroarray- und qRT- PCR- basierten Transkriptomanalysen wurde die Expression der bakteriellen Gene in charakteristischen Entwicklungsstadien des Wirtes untersucht. Allgemein zeigen vor allem Gene für molekulare Chaperons und bestimmte bakterielle Grundfunktionen eine hohe Expression. Aber auch viele Gene, die möglicherweise wichtige Funktionen in der Symbiose besitzen, wie die Biosynthese essentieller Aminosäuren und das Recycling von Stickstoffverbindungen, zeigen ein hohes absolutes Transkriptlevel. Zudem besteht eine positive Korrelation zwischen dem Expressionsniveau und dem GC- Gehalt der Gene, die in dem höheren Selektionsdruck und damit einer geringeren Mutationsrate der essentiellen Gene begründet liegt (Schaber et al., 2005). Durch Proteinanalysen konnte bestätigt werden, dass die Faktoren mit der höchsten absoluten Transkription die dominanten Proteine der Symbionten darstellen. In den unterschiedlichen Entwicklungsstadien zeigen viele Gene eine deutliche Dynamik, deren Ausmaß aber, verglichen mit freilebenden Bakterien, gering ist. Aus den Expressionsprofilen aufeinanderfolgender Gene lassen sich mögliche Transkriptionseinheiten ableiten, die teilweise auch experimentell bestätigt wurden. Oftmals zeigen auch Gene, die nicht in Transkriptionseinheiten angeordnet sind, aber verwandten Stoffwechselwegen angehören, ähnliche Muster. Dies deutet auf das Vorhandensein grundlegender Genregulations-mechanismen hin, obwohl im Genom von B. floridanus nur noch sehr wenige Transkriptionsfaktoren codiert sind (Gil et al., 2003). Auf übergeordneter Ebene zeigt sich, dass bei Symbionten aus späten Puppenstadien viele symbioserelevante Gene im Vergleich zu Genen des Grundmetabolismus eine erhöhte Expression zeigen. Dies betrifft besonders die Biosynthese aromatischer und verzweigter Aminosäuren, die in diesen Stadien vom Wirt in hoher Menge benötigt werden, während die internen Reserven gleichzeitig zur Neige gehen. Dies äußert sich auch im deutlichen Abfallen der Speicherproteinmenge des Wirts gegen Ende der Puppenphase. Die festgestellte Veränderung der Symbiontenzahl übertrifft das geringe Ausmaß der Genregulation um ein Vielfaches. Die Bakterien liegen in jedem Stadium polyploid mit bis zu 100 Genomkopien vor, dieser Polyploidiegrad bleibt jedoch während der gesamten Wirtsentwicklung weitestgehend konstant. Somit scheint die Kontrolle des Wirts über die bakterielle Vermehrung der entscheidende Faktor dieser Symbiose zu sein. Die verbleibenden regulatorischen Fähigkeiten der Bakterien stellen möglicherweise eine Feinjustierung von optimierten Produktionseinheiten dar, deren Anzahl nach den Bedürfnissen des Wirtes verändert wird. Insgesamt konnten in der vorliegenden Arbeit neue Einblicke in das komplexe Zusammenleben von Blochmannia und Camponotus gewonnen werden, die zu einem besseren Verständnis der biologischen Funktion und der grundlegenden Mechanismen dieser Symbiose führen. Eine der wichtigsten Fragestellungen nach dem Sinn einer nahrungsaufwertenden Symbiose für einen Nahrungsgeneralisten konnte mit starken Hinweisen auf eine stadienabhängige Relevanz der Symbiose beantwortet werden, die den enormen evolutionären Erfolg dieser Ameisengattung erklären könnte. 
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.
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.
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).