Periostin shows increased evolutionary plasticity in its alternatively spliced region

Background Periostin (POSTN) is a secreted extracellular matrix protein of poorly defined function that has been related to bone and heart development as well as to cancer. In human and mouse, it is known to undergo alternative splicing in its C-terminal region, which is devoid of known protein domains. Differential expression of periostin, sometimes of specific splicing isoforms, is observed in a broad range of human cancers, including breast, pancreatic, and colon cancer. Here, we combine genomic and transcriptomic sequence data from vertebrate organisms to study the evolution of periostin and particularly of its C-terminal region. Results We found that the C-terminal part of periostin is markedly more variable among vertebrates than the rest of periostin in terms of exon count, length, and splicing pattern, which we interpret as a consequence of neofunctionalization after the split between periostin and its paralog transforming growth factor, beta-induced (TGFBI). We also defined periostin's sequential 13-amino acid repeat units - well conserved in teleost fish, but more obscure in higher vertebrates - whose secondary structure is predicted to be consecutive beta strands. We suggest that these beta strands may mediate binding interactions with other proteins through an extended beta-zipper in a manner similar to the way repeat units in bacterial cell wall proteins have been reported to bind human fibronectin. Conclusions Our results, obtained with the help of the increasingly large collection of complete vertebrate genomes, document the evolutionary plasticity of periostin's C-terminal region, and for the first time suggest a basis for its functional role.Helmholtz Alliance on Systems Biolog

Designer Exons Inform a Biophysical Model for Exon Definition

Pre-mRNA molecules in humans contain mostly short internal exons flanked by long introns. To explain the removal of such introns, recognition of the exons instead of recognition of the introns has been proposed. This thesis studies this exon definition mechanism using a bottom-up approach. To reduce the complexity of the system under study, this exon definition mechanism was addressed using designer exons made up of prototype sequence modules of our own design (including an exonic splicing enhancer or silencer). Studies were performed in vitro with a set of DEs obtained from random combinations of the exonic splicing enhancer and the exonic splicing silencer modules. The results showed considerable variability both in terms of the composition and size of the DEs and in terms of their inclusion level. To understand how different DEs generated different inclusion levels, the problem was divided into understanding separately parameters varied between DEs. Subsequent studies focused on each of three parameters: size, ESE composition and ESS composition. The final objective was to be able to combine their effects to predict the inclusion levels obtained for the "random" DEs mentioned previously. To complement this experimental approach an equation was generated in two stages. First a general "framework" equation was obtained modeling a necessary exon definition complex that enabled commitment to inclusion. This equation used rates for the formation and dissociation of this complex without elaborating on the details for how those rates came about. In the second stage, however, formation and dissociation were modeled using novel but intuitive ideas and these models were combined into a final equation. This equation using the single-parameter perturbation data obtained previously performed well in predicting the inclusion levels of the "random" DEs. Additionally, both the final equation and the mechanisms proposed align well with results published by other groups. In order to make these results more accessible and to open more opportunities to extend them, an initial attempt is presented to identify the proteins involved in the functionality observed for each of the sequences used

Development of an intrabody capable of activating interferon regulatory factor-1 [IRF-1] and identification of IRF-1-binding peptide motifs

Interferon regulatory factor 1 (IRF-1) is a tumour suppressor protein and transcription factor. It has been shown to modulate target gene expression in response to stimuli, which include viral infection and DNA damage, and to be down- regulated in several forms o f cancer. This thesis details the development o f an intrabody, an intracellular antibody, that binds specifically to endogenous IRF-1. The binding o f the intrabody to ERF-1 enhanced transcription from ERF-1-responsive reporter gene constructs and endogenous promoters, thus it was shown to activate IRF-1. Intrabody binding also increased the rate at which IRF-1 was degraded, suggesting that the intrabody epitope may be regulating both IRF-1 activity and turnover. These results were supported point mutation within the intrabody epitope (P325 to A ) as the resultant mutant also displayed both a higher transcriptional activity and increased rate o f degradation.In an effort to understand the mechanisms which regulate IRF-1 activity a search for novel IRF-1-interacting proteins was carried out using phage peptide display. This invitro technique enables the identification o f peptides able to bind a specific target protein. The sequence o f these peptides can then be used to search protein databases for homologous, full-length proteins that could also bind the target protein. This led to the identification o f an IRF-1-binding peptide that held sequence similar to a region o f Zinc Finger 350 (ZNF350), a transcription factor involved in regulating the D N A damage response. Subsequently, endogenous ZNF350 and IRF-1 were co- immunoprecipitated from a human cancer cell line. The extreme C-terminus o f ERF-1 was shown to be sufficient for an interaction with ZNF350, although a second, more N-terminal site was also shown to be essential for a stable intracellular interaction.This data sheds new light on the role o f the extreme C-terminus o f IRF-1 in modulating the protein’s activity. This study also provides new and IRF-1-specific molecular tools, in the form o f intrabodies and IRF-1-binding peptides, which could be used in the future to further characterise the activity and regulation o f this tumour suppressor protein

Exploring new biological frontiers in hypertrophic cardiomyopathy

Tese de doutoramento, Ciências Biomédicas (Biologia Celular e Molecular), Universidade de Lisboa, Faculdade de Medicina, 2018Hypertrophic Cardiomyopathy (HCM) is the most common hereditary disease of the heart (1:500 individuals), and a cause of sudden cardiac death in young adults and athletes. The disease is inherited as an autosomal dominant trait caused by mutations in genes of the cardiac sarcomere. It is a disease with a widely variable genotype and phenotype. At present there is no effective treatment for this genetic disorder. The goal of my work was to explore applications of recent molecular genetics tools to improve patient diagnosis and develop potential new treatment strategies. Inspired by recent reports demonstrating the feasibility of performing “molecular RNA surgery” by using a double trans-splicing approach that results in the specific substitution of a given mutated exon, I investigated whether transsplicing could efficiently correct the expression of a mutant TNNT2 gene in cardiac cells. The TNNT2 gene codes for cardiac troponin T, one of the first sarcomeric proteins to be linked to HCM with more than 30 mutations identified to date. Because there is a significant mutational clustering on TNNT2 exon 9 associated with poor prognosis, I designed a strategy to specifically correct this exon. As a model system I used murine HL-1 cardiomyocytes. Given architectural differences between the human TNNT2 and mouse Tnnt2 genes, human exon 9 corresponds to mouse exon 8. The human TNNT2 exon 9 was used to replace the homologous mouse exon 8, which encodes the same amino acid sequence but differs in nucleotide composition, thus creating unique restriction sites and also a unique binding site for a primer that only hybridizes to the human TNNT2 exon 9. These unique restriction sites or the specific primer were further used to check the efficiency of trans-splicing events. Briefly, double trans-splicing molecules were constructed containing the replacing exon flanked by artificial intronic sequences with strong splice sites and splicing enhancers connected by a spacer linker to antisense sequences designed to anneal the two introns flanking exon 8 in the target murine Tnnt2 pre-mRNA. Cells were transfected with the exon exchange constructions cloned under the control of different promoters. The efficiency of trans-splicing was determined by RT-PCR followed by restriction analysis or, alternatively, by RT-PCR using the primer that only hybridizes to the human TNNT2 exon 9 and thus only amplifying trans-spliced transcripts. An RT-PCR assay using a radioactive γ-32P labelled primer indicated the presence of only residual amounts of the trans-splicing product. In order to improve efficiency, I designed an alternative strategy that involves a single 3' trans-splicing reaction. In brief, the goal was to replace mouse exon 8 and all exons downstream (exons 8 to 15) with a human cDNA containing the nucleotide sequence corresponding to exons 9 to 16. I constructed a 3' trans-splicing vector containing the human cDNA and upstream an artificial intronic sequence with a strong splice site and splicing enhancers connected by a spacer linker to an antisense sequence designed to anneal to intron 7 upstream of the mouse Tnnt2 exon 8 in the target pre-mRNA. After transfection, no trans-splicing product was detected. All together, these results argue that trans-splicing does not ensure efficient correction of expression of a TNNT2 gene in cardiac cells. This could be due to inefficiency of trans-splicing reactions in general, or a particular resistance to trans-splicing of the targeted region in the Tnnt2 pre-mRNA. High throughput sequencing technologies have revolutionized the identification of mutations responsible for HCM. Detection of pathogenic mutations has important implications for the medical management of patients and their families. However, approximately 50% of individuals with a clinical diagnosis of HCM have no causal mutation identified. In my host lab, we hypothesized that this may be due to the presence of pathogenic mutations located deep within the introns, which are not detected by conventional sequencing analysis restricted to exons and exonintron boundaries. The aim of my study was to develop a whole-gene sequencing strategy to prioritize deep intronic variants that may play a role in HCM pathogenesis. In collaboration with other members of the host lab, the full genomic DNA sequence of 26 genes previously associated with HCM was analysed in 16 unrelated patients. We identified likely pathogenic deep intronic variants in VCL, PRKAG2 and TTN genes. These variants, which are predicted to act through disruption of either splicing or transcription factor binding sites, were 3-fold more frequent in our cohort of probands than in normal European populations. Moreover, we found a patient that is compound heterozygous for a splice site mutation in MYBPC3 and the deep intronic VCL variant. Analysis of family members revealed that carriers of the MYBPC3 mutation alone do not manifest the disease, while family members that are compound heterozygous are clinically affected. In conclusion, we developed a framework for scrutinizing variation along the complete sequence of HCM-associated genes and our results suggest that deep intronic variation contributes to HCM phenotype. In order to translate the novel genetic information that we found to clinical decision taking requires further functional analysis. To date, mechanistic and functional studies of HCM mutations have been largely restricted to animal models in part due to difficulties in obtaining human tissue from patients. However, the recent emergence of patient-derived induced pluripotent stem cells (iPSCs) that can be differentiated into functional cardiomyocytes that recapitulate HCM-specific characteristics holds great promise as an exciting new approach to study how gene mutations relate to clinical outcomes and might be applied to test our hypothesisgenerating data. Thus, I decided to use the CRISPR-Cas9 genome-editing technology to introduce patient mutations in the genome of embryonic stem (ES) cells that were subsequently differentiated in cardiomyocytes. In collaboration with other members of the host lab, I generated sets of isogenic ES cells that differ exclusively by the presence of HCM-causing mutations in the TNNT2 gene. We used mouse ES cells, which are easier to manipulate and differentiate than human cells. In conclusion, during my PhD training I explored the feasibility of inducing trans-splicing as an RNA-targeted therapy to correct the expression of mutant sarcomeric genes in cardiomyocytes, I contributed to the development of a bioinformatics pipeline to identify novel mutations located within intronic regions of sarcomeric genes that may contribute to HCM pathogenesis, and I constructed new genome-edited cellular models of HCM.Instituto de Medicina Molecular (IMM), projeto LISBOA-01-0145-FEDER-007391; Merck Sharp & Dohme (MSD

Expression data dnalysis and regulatory network inference by means of correlation patterns

With the advance of high-throughput techniques, the amount of available data in the bio-molecular field is rapidly growing. It is now possible to measure genome-wide aspects of an entire biological system as a whole. Correlations that emerge due to internal dependency structures of these systems entail the formation of characteristic patterns in the corresponding data. The extraction of these patterns has become an integral part of computational biology. By triggering perturbations and interventions it is possible to induce an alteration of patterns, which may help to derive the dependency structures present in the system. In particular, differential expression experiments may yield alternate patterns that we can use to approximate the actual interplay of regulatory proteins and genetic elements, namely, the regulatory network of a cell. In this work, we examine the detection of correlation patterns from bio-molecular data and we evaluate their applicability in terms of protein contact prediction, experimental artifact removal, the discovery of unexpected expression patterns and genome-scale inference of regulatory networks. Correlation patterns are not limited to expression data. Their analysis in the context of conserved interfaces among proteins is useful to estimate whether these may have co-evolved. Patterns that hint on correlated mutations would then occur in the associated protein sequences as well. We employ a conceptually simple sampling strategy to decide whether or not two pathway elements share a conserved interface and are thus likely to be in physical contact. We successfully apply our method to a system of ABC-transporters and two-component systems from the phylum of Firmicute bacteria. For spatially resolved gene expression data like microarrays, the detection of artifacts, as opposed to noise, corresponds to the extraction of localized patterns that resemble outliers in a given region. We develop a method to detect and remove such artifacts using a sliding-window approach. Our method is very accurate and it is shown to adapt to other platforms like custom arrays as well. Further, we developed Padesco as a way to reveal unexpected expression patterns. We extract frequent and recurring patterns that are conserved across many experiments. For a specific experiment, we predict whether a gene deviates from its expected behaviour. We show that Padesco is an effective approach for selecting promising candidates from differential expression experiments. In Chapter 5, we then focus on the inference of genome-scale regulatory networks from expression data. Here, correlation patterns have proven useful for the data-driven estimation of regulatory interactions. We show that, for reliable eukaryotic network inference, the integration of prior networks is essential. We reveal that this integration leads to an over-estimate of network-wide quality estimates and suggest a corrective procedure, CoRe, to counterbalance this effect. CoRe drastically improves the false discovery rate of the originally predicted networks. We further suggest a consensus approach in combination with an extended set of topological features to obtain a more accurate estimate of the eukaryotic regulatory network for yeast. In the course of this work we show how correlation patterns can be detected and how they can be applied for various problem settings in computational molecular biology. We develop and discuss competitive approaches for the prediction of protein contacts, artifact repair, differential expression analysis, and network inference and show their applicability in practical setups.Mit der Weiterentwicklung von Hochdurchsatztechniken steigt die Anzahl verfügbarer Daten im Bereich der Molekularbiologie rapide an. Es ist heute möglich, genomweite Aspekte eines ganzen biologischen Systems komplett zu erfassen. Korrelationen, die aufgrund der internen Abhängigkeits-Strukturen dieser Systeme enstehen, führen zu charakteristischen Mustern in gemessenen Daten. Die Extraktion dieser Muster ist zum integralen Bestandteil der Bioinformatik geworden. Durch geplante Eingriffe in das System ist es möglich Muster-Änderungen auszulösen, die helfen, die Abhängigkeits-Strukturen des Systems abzuleiten. Speziell differentielle Expressions-Experimente können Muster-Wechsel bedingen, die wir verwenden können, um uns dem tatsächlichen Wechselspiel von regulatorischen Proteinen und genetischen Elementen anzunähern, also dem regulatorischen Netzwerk einer Zelle. In der vorliegenden Arbeit beschäftigen wir uns mit der Erkennung von Korrelations-Mustern in molekularbiologischen Daten und schätzen ihre praktische Nutzbarkeit ab, speziell im Kontext der Kontakt-Vorhersage von Proteinen, der Entfernung von experimentellen Artefakten, der Aufdeckung unerwarteter Expressions-Muster und der genomweiten Vorhersage regulatorischer Netzwerke. Korrelations-Muster sind nicht auf Expressions-Daten beschränkt. Ihre Analyse im Kontext konservierter Schnittstellen zwischen Proteinen liefert nützliche Hinweise auf deren Ko-Evolution. Muster die auf korrelierte Mutationen hinweisen, würden in diesem Fall auch in den entsprechenden Proteinsequenzen auftauchen. Wir nutzen eine einfache Sampling-Strategie, um zu entscheiden, ob zwei Elemente eines Pathways eine gemeinsame Schnittstelle teilen, berechnen also die Wahrscheinlichkeit für deren physikalischen Kontakt. Wir wenden unsere Methode mit Erfolg auf ein System von ABC-Transportern und Zwei-Komponenten-Systemen aus dem Firmicutes Bakterien-Stamm an. Für räumlich aufgelöste Expressions-Daten wie Microarrays enspricht die Detektion von Artefakten der Extraktion lokal begrenzter Muster. Im Gegensatz zur Erkennung von Rauschen stellen diese innerhalb einer definierten Region Ausreißer dar. Wir entwickeln eine Methodik, um mit Hilfe eines Sliding-Window-Verfahrens, solche Artefakte zu erkennen und zu entfernen. Das Verfahren erkennt diese sehr zuverlässig. Zudem kann es auf Daten diverser Plattformen, wie Custom-Arrays, eingesetzt werden. Als weitere Möglichkeit unerwartete Korrelations-Muster aufzudecken, entwickeln wir Padesco. Wir extrahieren häufige und wiederkehrende Muster, die über Experimente hinweg konserviert sind. Für ein bestimmtes Experiment sagen wir vorher, ob ein Gen von seinem erwarteten Verhalten abweicht. Wir zeigen, dass Padesco ein effektives Vorgehen ist, um vielversprechende Kandidaten eines differentiellen Expressions-Experiments auszuwählen. Wir konzentrieren uns in Kapitel 5 auf die Vorhersage genomweiter regulatorischer Netzwerke aus Expressions-Daten. Hierbei haben sich Korrelations-Muster als nützlich für die datenbasierte Abschätzung regulatorischer Interaktionen erwiesen. Wir zeigen, dass für die Inferenz eukaryotischer Systeme eine Integration zuvor bekannter Regulationen essentiell ist. Unsere Ergebnisse ergeben, dass diese Integration zur Überschätzung netzwerkübergreifender Qualitätsmaße führt und wir schlagen eine Prozedur - CoRe - zur Verbesserung vor, um diesen Effekt auszugleichen. CoRe verbessert die False Discovery Rate der ursprünglich vorhergesagten Netzwerke drastisch. Weiterhin schlagen wir einen Konsensus-Ansatz in Kombination mit einem erweiterten Satz topologischer Features vor, um eine präzisere Vorhersage für das eukaryotische Hefe-Netzwerk zu erhalten. Im Rahmen dieser Arbeit zeigen wir, wie Korrelations-Muster erkannt und wie sie auf verschiedene Problemstellungen der Bioinformatik angewandt werden können. Wir entwickeln und diskutieren Ansätze zur Vorhersage von Proteinkontakten, Behebung von Artefakten, differentiellen Analyse von Expressionsdaten und zur Vorhersage von Netzwerken und zeigen ihre Eignung im praktischen Einsatz

Genome-wide analysis of dMi-2 binding sites

ATP-dependent chromatin remodelers regulate gene expression. The actions of chromatin remodelers on the nucleosome removal and assembly, the histone variants exchange and the modifications of the nucleosome array modify the accessibility of the transcriptional machinery to DNA. Transcription is also influenced by the chromatin context. Indeed, the presence of transcription factors, nucleosome-depleted regions and histone modifications, facilitate the recruitment of specific histone modifying enzymes, chromatin modifying enzymes and chromatin remodelers. Thus, several chromatin features influence the transcription outcome. The ATP-dependent chromatin remodeler dMi-2 is typically associated with transcription repression, but its implication in active transcription has also been reported. The dMi-2 binding sites on polytene chromosomes suggest that dMi-2 binds mainly in open chromatin regions. However, the resolution of polytene staining is approximate and does not give any information about the chromatin context surrounding dMi-2. Thus, the genome-wide dMi-2 binding sites have been identified by ChIP-sequencing and correlated with existing data of histone modifications, RNA polymerase II, nucleosome-depleted regions, transcription, transcription factors and chromatin states. All in all, dMi-2 is located in open chromatin regions and in vicinity of developmental genes. Although dMi-2 mainly represses the expression of its associated genes, it binds close to features linked to active transcription and it is enriched in promoters and in potential regulatory regions. Upon heat shock, the inducible hsp70 gene is actively transcribed, and dMi-2 is important for its expression. To investigate the factors influencing the recruitment of dMi-2 in a context of active transcription, the dMi-2 genome-wide binding sites in un-induced and heat shock conditions have been identified by ChIP-sequencing. dMi-2 is selectively enriched on 7 hsp genes. The chromatin features associated to the hsp70 promoter or a nucleosome-depleted region does not suffice to recruit dMi-2. Moreover, a strong transcription is not sufficient to recruit dMi-2, even though its recruitment on the heat shock genes is transcription dependent. Notably, dMi-2 distribution encompasses the gene body and extent beyond the polyadenylation site of the heat shock genes. Thus, the results suggest that dMi-2 follow the transcriptional activity

Expression data dnalysis and regulatory network inference by means of correlation patterns

With the advance of high-throughput techniques, the amount of available data in the bio-molecular field is rapidly growing. It is now possible to measure genome-wide aspects of an entire biological system as a whole. Correlations that emerge due to internal dependency structures of these systems entail the formation of characteristic patterns in the corresponding data. The extraction of these patterns has become an integral part of computational biology. By triggering perturbations and interventions it is possible to induce an alteration of patterns, which may help to derive the dependency structures present in the system. In particular, differential expression experiments may yield alternate patterns that we can use to approximate the actual interplay of regulatory proteins and genetic elements, namely, the regulatory network of a cell. In this work, we examine the detection of correlation patterns from bio-molecular data and we evaluate their applicability in terms of protein contact prediction, experimental artifact removal, the discovery of unexpected expression patterns and genome-scale inference of regulatory networks. Correlation patterns are not limited to expression data. Their analysis in the context of conserved interfaces among proteins is useful to estimate whether these may have co-evolved. Patterns that hint on correlated mutations would then occur in the associated protein sequences as well. We employ a conceptually simple sampling strategy to decide whether or not two pathway elements share a conserved interface and are thus likely to be in physical contact. We successfully apply our method to a system of ABC-transporters and two-component systems from the phylum of Firmicute bacteria. For spatially resolved gene expression data like microarrays, the detection of artifacts, as opposed to noise, corresponds to the extraction of localized patterns that resemble outliers in a given region. We develop a method to detect and remove such artifacts using a sliding-window approach. Our method is very accurate and it is shown to adapt to other platforms like custom arrays as well. Further, we developed Padesco as a way to reveal unexpected expression patterns. We extract frequent and recurring patterns that are conserved across many experiments. For a specific experiment, we predict whether a gene deviates from its expected behaviour. We show that Padesco is an effective approach for selecting promising candidates from differential expression experiments. In Chapter 5, we then focus on the inference of genome-scale regulatory networks from expression data. Here, correlation patterns have proven useful for the data-driven estimation of regulatory interactions. We show that, for reliable eukaryotic network inference, the integration of prior networks is essential. We reveal that this integration leads to an over-estimate of network-wide quality estimates and suggest a corrective procedure, CoRe, to counterbalance this effect. CoRe drastically improves the false discovery rate of the originally predicted networks. We further suggest a consensus approach in combination with an extended set of topological features to obtain a more accurate estimate of the eukaryotic regulatory network for yeast. In the course of this work we show how correlation patterns can be detected and how they can be applied for various problem settings in computational molecular biology. We develop and discuss competitive approaches for the prediction of protein contacts, artifact repair, differential expression analysis, and network inference and show their applicability in practical setups.Mit der Weiterentwicklung von Hochdurchsatztechniken steigt die Anzahl verfügbarer Daten im Bereich der Molekularbiologie rapide an. Es ist heute möglich, genomweite Aspekte eines ganzen biologischen Systems komplett zu erfassen. Korrelationen, die aufgrund der internen Abhängigkeits-Strukturen dieser Systeme enstehen, führen zu charakteristischen Mustern in gemessenen Daten. Die Extraktion dieser Muster ist zum integralen Bestandteil der Bioinformatik geworden. Durch geplante Eingriffe in das System ist es möglich Muster-Änderungen auszulösen, die helfen, die Abhängigkeits-Strukturen des Systems abzuleiten. Speziell differentielle Expressions-Experimente können Muster-Wechsel bedingen, die wir verwenden können, um uns dem tatsächlichen Wechselspiel von regulatorischen Proteinen und genetischen Elementen anzunähern, also dem regulatorischen Netzwerk einer Zelle. In der vorliegenden Arbeit beschäftigen wir uns mit der Erkennung von Korrelations-Mustern in molekularbiologischen Daten und schätzen ihre praktische Nutzbarkeit ab, speziell im Kontext der Kontakt-Vorhersage von Proteinen, der Entfernung von experimentellen Artefakten, der Aufdeckung unerwarteter Expressions-Muster und der genomweiten Vorhersage regulatorischer Netzwerke. Korrelations-Muster sind nicht auf Expressions-Daten beschränkt. Ihre Analyse im Kontext konservierter Schnittstellen zwischen Proteinen liefert nützliche Hinweise auf deren Ko-Evolution. Muster die auf korrelierte Mutationen hinweisen, würden in diesem Fall auch in den entsprechenden Proteinsequenzen auftauchen. Wir nutzen eine einfache Sampling-Strategie, um zu entscheiden, ob zwei Elemente eines Pathways eine gemeinsame Schnittstelle teilen, berechnen also die Wahrscheinlichkeit für deren physikalischen Kontakt. Wir wenden unsere Methode mit Erfolg auf ein System von ABC-Transportern und Zwei-Komponenten-Systemen aus dem Firmicutes Bakterien-Stamm an. Für räumlich aufgelöste Expressions-Daten wie Microarrays enspricht die Detektion von Artefakten der Extraktion lokal begrenzter Muster. Im Gegensatz zur Erkennung von Rauschen stellen diese innerhalb einer definierten Region Ausreißer dar. Wir entwickeln eine Methodik, um mit Hilfe eines Sliding-Window-Verfahrens, solche Artefakte zu erkennen und zu entfernen. Das Verfahren erkennt diese sehr zuverlässig. Zudem kann es auf Daten diverser Plattformen, wie Custom-Arrays, eingesetzt werden. Als weitere Möglichkeit unerwartete Korrelations-Muster aufzudecken, entwickeln wir Padesco. Wir extrahieren häufige und wiederkehrende Muster, die über Experimente hinweg konserviert sind. Für ein bestimmtes Experiment sagen wir vorher, ob ein Gen von seinem erwarteten Verhalten abweicht. Wir zeigen, dass Padesco ein effektives Vorgehen ist, um vielversprechende Kandidaten eines differentiellen Expressions-Experiments auszuwählen. Wir konzentrieren uns in Kapitel 5 auf die Vorhersage genomweiter regulatorischer Netzwerke aus Expressions-Daten. Hierbei haben sich Korrelations-Muster als nützlich für die datenbasierte Abschätzung regulatorischer Interaktionen erwiesen. Wir zeigen, dass für die Inferenz eukaryotischer Systeme eine Integration zuvor bekannter Regulationen essentiell ist. Unsere Ergebnisse ergeben, dass diese Integration zur Überschätzung netzwerkübergreifender Qualitätsmaße führt und wir schlagen eine Prozedur - CoRe - zur Verbesserung vor, um diesen Effekt auszugleichen. CoRe verbessert die False Discovery Rate der ursprünglich vorhergesagten Netzwerke drastisch. Weiterhin schlagen wir einen Konsensus-Ansatz in Kombination mit einem erweiterten Satz topologischer Features vor, um eine präzisere Vorhersage für das eukaryotische Hefe-Netzwerk zu erhalten. Im Rahmen dieser Arbeit zeigen wir, wie Korrelations-Muster erkannt und wie sie auf verschiedene Problemstellungen der Bioinformatik angewandt werden können. Wir entwickeln und diskutieren Ansätze zur Vorhersage von Proteinkontakten, Behebung von Artefakten, differentiellen Analyse von Expressionsdaten und zur Vorhersage von Netzwerken und zeigen ihre Eignung im praktischen Einsatz

The role of Arabidopsis transcription factors WRKY18 and WRKY40 in plant immunity

Two related Arabidopsis thaliana transcription factors, WRKY18 and WRKY40, are induced upon infection with the obligate biotrophic powdery mildew, Golovinomyces orontii (G. orontii), during early stages of infection. WRKY18 and WRKY40 negatively regulate host resistance as wrky18wrky40 double mutants are resistant towards this fungus. Differential expression of hormone biosynthesis and response genes between susceptible wildtype and resistant wrky18wrky40 plants suggested a crucial role of hormone signaling during G. orontii infection. Investigating the potential contribution of hormonal changes to resistance during this plant-pathogen-interaction is one focus of this thesis. Although hormone measurements did not reveal major differences between susceptible wildtype and resistant wrky18wrky40 plants, genetic studies demonstrated that SA biosynthesis is indispensable for resistance. Besides hormone-dependent defense responses, secondary metabolites, such as the indol-glucosinolate 4MI3G (4-Methoxyindol-3-ylmethylglucosinolat), have been shown to contribute to antifungal defense. Elevated levels of 4MI3G in infected wrky18wrky40 plants indicate a potential role of this compound in resistance towards G. orontii. Whereas WRKY18 and WRKY40 are negative regulators of resistance towards G. orontii, this was not the case for other powdery mildews. Hence, wrky18wrky40 mutants do not exhibit a broad-spectrum but rather specific resistance towards G. orontii infection. Furthermore, comprehensive wrky18wrky40 infection studies including different biotrophic, hemi-biotrophic and necrotrophic pathogens revealed a positive role of WRKY18 and WRKY40 in effector-triggered resistance towards avirulent Pseudomonas syringae DC3000 expressing the AvrRPS4 effector gene. This response appears to be highly specific since it was not observed with bacteria expressing other tested Avr genes. To further dissect roles of WRKY18 and WRKY40 in plant immunity and to uncover potential direct target genes of these transcription factors, global expression analyses of wrky18 and wrky40 single mutants upon G. orontii were performed. Overall, WRKY18 and WRKY40 function partly redundantly, but regulate highly diverse sets of genes. Direct binding of potential direct target genes will be analyzed by ChIP-PCR employing the newly generated WRKY18-HA complementation line. First results demonstrated WRKY18 feedback regulation on its own gene and the WRKY40 gene during G. orontii infection. In addition, a yeast 2-hybrid screen against a pathogen-induced cDNA-library revealed potential interaction partners of WRKY18 and WRKY40 that co-localize to the plant cell nucleus. In conclusion, this thesis contributes to further understanding the roles of WRKY18 and WRKY40 in plant immunity

The role of telomerase on cell proliferation in zebrafish (Danio rerio)

Tese de mestrado. Biologia (Biologia Molecular e Genética). Universidade de Lisboa, Faculdade de Ciências, 2010Os telómeros são as extremidades dos cromossomas lineares dos organismos eucarióticos. São regiões de cromatina com propriedades específicas, conferidas pela estrutura do seu ADN e pelas proteínas que a ele estão associadas. Em vertebrados, o ADN telomérico é constituído pela sequência TTAGGG, repetida lado-a-lado um número variável de vezes. Para além de uma região extensa em cadeia dupla, a parte terminal dos telómeros contém uma extermidade projectada a 3’, rica em guanosinas, e as proteínas teloméricas estão associadas de forma específica a cada uma destas regiões. Estas estruturas são essenciais para a manutenção da integridade do genoma, já que conferem protecção face à acção de exonucleases e à acção de enzimas de reparação de danos no ADN. Impedem também a perda de informação genética com a ocorrência da replicação, algo que está relacionado com o ‘problema da replicação terminal’. Devido à incapacidade de as polimerases de ADN polimerisarem nucleótidos na ausência de um ‘primer’, é impossível sintetizar a parte final da cadeia descontínua durante a replicação de moléculas lineares. Isto levaria a que a cadeia de ADN encurtasse, com cada ciclo replicativo, o que conduziria à perda progressiva de informação genética. Os telómeros, sendo estruturas não-génicas, impedem que tal aconteça. Sabe-se que os telómeros encurtam devido não só ao problema da replicação terminal mas também à ressecção adicional, regulada, que dá origem à extremidade 3’ projectada. Para que tal não aconteça, as células apresentam mecanismos para alongar os telómeros que podem ser baseados em recombinação entre telómeros (chamados de Alternative Lengthening Mechanisms ou ALT) ou na acção da telomerase. A telomerase é constituída por uma componente proteica com actividade de transcritase reversa (Tert) e uma componente de ARN (Terc). Esta nucleoproteína, bastante conservada entre os eucariotas, sintetiza repetições teloméricas a partir do molde que se encontra na componente de ARN, alongando telómeros curtos. A sua produção e actividade são controlados pelas proteínas e demais constituintes dos telómeros e a sua acção depende do estado celular. No Homem, a maioria das células somáticas não a expressa e existe uma correlação entre o tamanho dos telómeros e a idade, sendo os telómeros de pessoas de maior idade mais curtos do que os de pessoas mais jovens. A telomerase é expressa nas células da linha germinal, permitindo a manutenção do comprimento dos telómeros e a transmissão do genoma estável à próxima geração. Esta é também expressa nas células proliferativas de nichos de células estaminais em níveis que não são, porém, suficientes para impedir o encurtamento dos telómeros. As células somáticas não podem ser propagadas em cultura indefinidamente. Sabe-se que em cultura dividem um limitado número de vezes após o qual entram num estado de senescência. Este ‘limite de Hayflick’ está relacionado com o facto de os telómeros encurtarem com cada divisão celular. Os telómeros criticamente curtos conduzem à activação de ‘checkpoints’ dependentes de P53 e outros supressores de tumores, de modo a impedir a progressão do ciclo celular. Deste modo, as células sofrem uma série de alterações que caracterizam a senescência celular ou entram num processo apoptótico. Se tal não acontece, desencadeia-se uma resposta de reparação de danos no ADN, o que leva a instabilidade cromossómica, com a ocorrência de ciclos de fusões entre cromossomas e quebras no ADN e, em último caso, contribui para o surgimento de tumores. É possível encontrar células senescentes em tecidos. Dado que a maioria das células somáticas não expressa telomerase é possível que o declínio na manutenção do funcionamento dos órgãos e funções biológicas, característico do processo do envelhecimento, esteja relacionado com a incapacidade de proliferação causada pelo encurtamento dos telómeros. Existem algumas doenças humanas que se manifestam em problemas na manutenção dos tecidos, envelhecimento precoce e tempo de vida diminuído. Uma destas doenças, a Disqueratose Congénita, é causada por mutações em componentes da telomerase, o que apoia o papel do encurtamento dos telómeros no processo do envelhecimento, juntamente com o facto de algumas variantes da proteína Tert estarem relacionadas com maior longevidade. Longevidade é o tempo em que é possível a um organismo manter as funções celulares, prevenindo alterações associadas com o envelhecimento. Apesar de o papel dos telómeros na senescência celular ser já reconhecido como importante, o seu papel no envelhecimento e longevidade permanece em investigação. Estudos em ratinho, com vista a compreender o papel dos telómeros nestes processos, mostraram que a ausência da telomerase causa fenótipos de envelhecimento, como a degeneração de tecidos proliferativos, infertilidade e incapacidade de cicatrização de feridas, acompanhados de alterações citogenéticas de fusões e aneuploidias. No entanto, o ratinho apresenta várias características específicas que o afastam da realidade no Homem. São precisas gerações de cruzamentos entre ratinhos knock out, em que os seus telómeros são artificialmente encurtados a um ponto crítico, para que surjam fenótipos. Assim, o eixo telómeros/telomerase não parece ser fundamental para o controlo da proliferação celular e manutenção dos tecidos, ao contrário do que parece acontecer em humanos. O peixe-zebra (Danio rerio) tem sido apresentado como um novo modelo de envelhecimento, e neste âmbito, poderá ser um bom modelo vertebrado alternativo para estudar o papel dos telómeros e da telomerase na proliferação celular e homeostasia de tecidos com o envelhecimento. Este modelo possui várias vantagens específicas: é fácil e barato de manter, o que permite seguir muitos indivíduos; envelhece gradualmente e manifesta características semelhantes às dos humanos; expressa vários marcadores celulares de senescência que permitem a procura de genes relacionados com o envelhecimento em larga escala; e é um modelo de excelência para manipulação genética e criação de transgénicos para microscopia em tempo real. O peixe tem a capacidade de regenerar quase todos os seus órgãos, ao contrário dos humanos, num processo que depende altamente de proliferação celular, e a expressão da telomerase tem sido apontada como uma das características necessárias para que tal aconteça. Tem também telómeros mais curtos que o ratinho, menor actividade da telomerase e várias observações apontam para um papel da manutenção dos telómeros na proliferação celular e sua implicação no processo de envelhecimento do peixe-zebra. Neste contexto, pretendeu-se caracterizar um mutante em peixe-zebra, em que a actividade da telomerase foi abolida (terthu3430). Determinou-se o tamanho médio dos telómeros de mutantes, em comparação com indivíduos selvagens, através da técnica de restrição dos fragmentos terminais seguida de hibridação Southern. O peixe-zebra parece ter, de facto, telómeros curtos, de cerca de 7 Kb, e o mutante apresenta logo aos 6 meses de idade uma diminuição significativa do tamanho dos telómeros no tecido da barbatana caudal, que não é especialmente proliferativo. Isto indica que a telomerase pode ser um mecanismo fundamental para a manutenção dos telómeros neste organismo. Os fenótipos apresentados são consistentes com um papel da telomerase e dos telómeros na proliferação celular e manutenção dos tecidos proliferativos do adulto (intestino, retina, músculo esquelético, brânquias, intestino e gónadas) com o tempo. Uma das primeiras consequências, associada à degeneração das gónadas, é a infertilidade dos machos e, mais tarde, das fêmeas. Embriões homozigóticos mutantes sem contribuição maternal são inviáveis, e apresentam fenótipos variados consistentes com problemas na proliferação celular e/ou apoptose. Assim, a telomerase parece ser fundamental em vários fenómenos que dependem da proliferação celular, em peixe-zebra. Estes resultados aproximam-se da realidade em humanos, e apoiam a utilização do peixe-zebra como modelo vertebrado alternativo para compreender qual o papel dos telómeros no processo de envelhecimento, determinação de longevidade, e também para modelação do papel dos telómeros e da telomerase no cancro e no processo regenerativo.Telomeres, the tips of linear eukaryotic chromosomes, are responsible for protecting chromosome ends from exonucleases and DNA repair events. Together with the enzyme telomerase, they provide a way to elongate telomeres, preventing loss of genetic information with replication due to the end-replication problem and to additional resection of the 5’ end. The progressive shortening of telomeres in the absence of telomerase, or other recombination-based mechanisms, leads to cellular senescence and it is hypothesized that this could be responsible for organismal ageing. Zebrafish has been proposed as a promising vertebrate ageing model. It ages gradually and display many cellular features common to human senescence. It is currently used for the study of age-dependent changes in various organs, such as the muscle, skeleton and the eye. In contrast to inbred mice, they possess shorter telomeres of the same length of humans (5-10kb), which suggests similar mechanisms in the regulation of cell proliferation by telomeres. An early nonsense mutation in telomerase component gene tert (terthu3430) results in fish that exhibit shorter telomeres observable by 6 months of age. This points telomerase as a fundamental mechanism for telomere maintenance in this organism, in contrast to inbred mice models. The phenotypes are consistent with a role of telomerase in cell proliferation and tissue maintenance in the adult, with impaired organ renewal and function leading to infertility and a decline in health status and precocious death by 1 year of age. A role for telomerase on cell proliferation is also evident on the developmental defects of maternal zygotic mutant embryos that make them unviable. These results support the use of zebrafish as an alternative animal model for the role of telomeres and telomerase on cell proliferation events like development and regeneration, and tissue turn-over degeneration, which occurs during the ageing process