Trichomes are hair-like structures found on the surface of virtually all terrestrial plants (Yang et al., 2015). They are epidermal outgrowths that can occur on all of the aerial parts of a plant, varying markedly in size, shape, distribution, and in their ability to produce secondary metabolites. About 30% of all vascular plants carry the glandular trichomes capable of producing secondary metabolites (Glas et al., 2012). Trichomes are vitally important to plants as a defence mechanism, they are highly significant commercially, and they are of interest to plant biologists in that they serve as an excellent model system to study all aspects of plant differentiation at the single-cell level (Hulskamp, 2004). The simple, non-glandular trichomes found in Arabidopsis have been studied extensively. However the glandular trichomes of the kind found on the surface of Antirrhinum are much less well understood. The primary aim of the research reported here is to identify the gene(s) responsible for variation in epidermal hair (trichome) distribution between Antirrhinum species. Following an introduction which provides essential background on trichomes and on Antirrhinum, the thesis is presented in four parts. The first part describes a RAD-seq experiment used to produce linkage maps for the eight chromosomes making up the Antirrhinum genome and estimates the position of the Hairy gene on linkage group 8. The results are cross-validated against maps produced independently by the Xue group. It also describes novel methods developed to address a number of problems that arose during the course of the analysis, and explores the value of imputation methods in helping to overcome gaps and inconsistencies in the data. The second part presents the findings from a fine-mapping Pool-seq experiment designed to estimate the position of Hairy more precisely. The findings suggest that Hairy lies on one of a small number of scaffolds, with Scaffold 1097 being the most likely candidate. Also covered are the findings of another experiment to estimate the position of the gene that determines whether flowers are pale or dark. In this case the results indicate that the gene lies on one of a small number of scaffolds on linkage group 5. The third part presents the results of an RNA-seq experiment which, when combined with the results of the Pool-seq experiment provides evidence that Hairy might be a glutaredoxin gene on Scaffold 1097. Finally the interim results of three experiments designed to confirm that the gene identified as Hairy controls the distribution of trichomes in Antirrhinum are presented.

<p>The human coronavirus NL63 was discovered in 2004 by a team of researchers in Amsterdam. Since its discovery it has been shown to have worldwide spread and affects mainly children, aged 0-5 years old, the immunocompromised and the elderly. Infection with HCoV-NL63 commonly results in mild upper respiratory tract infections and presents as the common cold, with symptoms including fever, cough, sore throat and rhinorrhoea. Lower respiratory tract findings are less common but may develop into more serious complications including bronchiolitis, pneumonia and croup. The primary function of the HCoV-NL63 nucleocapsid (N) protein is the formation of theprotective ribonucleocapsid core. For this particle to assemble, the N-protein undergoes N-N dimerization and then interacts with viral RNA. Besides the primary structural role of the Nprotein, it is also understood to be involved in viral RNA transcription, translation and replication, including several other physiological functions. The N-protein is also highly antigenic and elicits a strong immune response in infected patients. For this reason the N-protein may serve as a target for the development of diagnostic assays. We have used bioinformatic analysis to analyze the HCoV-NL63 N-protein and compared it to coronavirus N-homologues. This bioinformatic analysis provided the data to generate recombinant clones for expression in a bacterial system. We constructed recombinant clones of the N-protein of SARS-CoV and HCoV-NL63 and synthesized truncated clones corresponding to the N- and C-terminal of the HCoV-NL63 N-protein. These heterologously expressed proteins will serve the basis for several post-expression studies including characterizing the immunogenic epitope of the N-protein as well identifying any antibody crossreactivity between coronavirus species.</p>

<p>The human coronavirus NL63 was discovered in 2004 by a team of researchers in Amsterdam. Since its discovery it has been shown to have worldwide spread and affects mainly children, aged 0-5 years old, the immunocompromised and the elderly. Infection with HCoV-NL63 commonly results in mild upper respiratory tract infections and presents as the common cold, with symptoms including fever, cough, sore throat and rhinorrhoea. Lower respiratory tract findings are less common but may develop into more serious complications including bronchiolitis, pneumonia and croup. The primary function of the HCoV-NL63 nucleocapsid (N) protein is the formation of theprotective ribonucleocapsid core. For this particle to assemble, the N-protein undergoes N-N dimerization and then interacts with viral RNA. Besides the primary structural role of the Nprotein, it is also understood to be involved in viral RNA transcription, translation and replication, including several other physiological functions. The N-protein is also highly antigenic and elicits a strong immune response in infected patients. For this reason the N-protein may serve as a target for the development of diagnostic assays. We have used bioinformatic analysis to analyze the HCoV-NL63 N-protein and compared it to coronavirus N-homologues. This bioinformatic analysis provided the data to generate recombinant clones for expression in a bacterial system. We constructed recombinant clones of the N-protein of SARS-CoV and HCoV-NL63 and synthesized truncated clones corresponding to the N- and C-terminal of the HCoV-NL63 N-protein. These heterologously expressed proteins will serve the basis for several post-expression studies including characterizing the immunogenic epitope of the N-protein as well identifying any antibody crossreactivity between coronavirus species.</p>

>Magister Scientiae - MSc / Acute respiratory infections (ARI) continue to be the leading cause of acute illnesses worldwide and remain the most important cause of infant and young children mortality. Many viruses such as rhinoviruses, influenza viruses, parainfluenza viruses, respiratory syncytial viruses, adenoviruses and coronaviruses are deemed to be the etiological agents responsible for ARI’s in children. The recently discovered coronaviruses HCoV-HKU1 and HCoV-NL63 contribute significantly to the hospitalization of children with ARI’s. HCoV-NL63 was first identified in 2004, as the pathogen responsible for the hospitalization of a 7 month old child presenting with coryza, conjunctivitis and fever. Since then a significant amount of knowledge has been gained in the clinical spectrum on this virus, however HCoV-NL63 is still not well characterized on the molecular and proteomic level. This dissertation focuses on bringing about this characterization by cloning the HCoV-NL63 Nucleocapsid gene to be expressed in a bacterial system and transfecting the Nucleocapsid, Membrane and Envelope genes into a Mammalian cell culture system in order for its respective proteins to be expressed. With the use of Bioinformatic analytic tools certain characteristics of HCoV-NL63 Nucleocapsid, Membrane and Envelope proteins are able to be identified, as well as certain motifs and/or regions that are important in the functioning of these proteins. By comparing the results obtained for HCoV-NL63 N,M and E to other well studied coronavirus homologous will enlighten us on the potential role(s) of these proteins in determining HCoV-NL63 pathogenicity and infectivity. vi Although certain functions of these proteins can be deduced by the means of bioinformatics analysis, it is still imperative for it to be extensively characterized In Vitro. This will therefore form a fundamental step in the development of many other projects, which unfortunately fall outside the scope of this M.Sc thesis.

Magister Scientiae (Medical Bioscience) - MSc(MBS) / The human coronavirus NL63 was discovered in 2004 by a team of researchers in Amsterdam. Since its discovery it has been shown to have worldwide spread and affects mainly children, aged 0-5 years old, the immunocompromised and the elderly. Infection with HCoV-NL63 commonly results in mild upper respiratory tract infections and presents as the common cold, with symptoms including fever, cough, sore throat and rhinorrhoea. Lower respiratory tract findings are less common but may develop into more serious complications including bronchiolitis, pneumonia and croup. The primary function of the HCoV-NL63 nucleocapsid (N) protein is the formation of theprotective ribonucleocapsid core. For this particle to assemble, the N-protein undergoes N-N dimerization and then interacts with viral RNA. Besides the primary structural role of the Nprotein, it is also understood to be involved in viral RNA transcription, translation and replication, including several other physiological functions. The N-protein is also highly antigenic and elicits a strong immune response in infected patients. For this reason the N-protein may serve as a target for the development of diagnostic assays. We have used bioinformatic analysis to analyze the HCoV-NL63 N-protein and compared it to coronavirus N-homologues. This bioinformatic analysis provided the data to generate recombinant clones for expression in a bacterial system. We constructed recombinant clones of the N-protein of SARS-CoV and HCoV-NL63 and synthesized truncated clones corresponding to the N- and C-terminal of the HCoV-NL63 N-protein. These heterologously expressed proteins will serve the basis for several post-expression studies including characterizing the immunogenic epitope of the N-protein as well identifying any antibody crossreactivity between coronavirus species. / South Africa

<div> <div> <div> <p>Understanding protein-protein interactions (PPIs) in a cell is essential for learning protein functions, pathways, and mechanisms of diseases. This dissertation introduces the computational method to predict PPIs. In the first chapter, the history of identifying protein interactions and some experimental methods are introduced. Because interacting proteins share similar functions, protein function similarity can be used as a feature to predict PPIs. NaviGO server is developed for biologists and bioinformaticians to visualize the gene ontology relationship and quantify their similarity scores. Furthermore, the computational features used to predict PPIs are summarized. This will help researchers from the computational field to understand the rationale of extracting biological features and also benefit the researcher with a biology background to understand the computational work. After understanding various computational features, the computational prediction method to identify large-scale PPIs was developed and applied to Arabidopsis, maize, and soybean in a whole-genomic scale. Novel predicted PPIs were provided and were grouped based on prediction confidence level, which can be used as a testable hypothesis to guide biologists’ experiments. Since affinity chromatography combined with mass spectrometry technique introduces high false PPIs, the computational method was combined with mass spectrometry data to aid the identification of high confident PPIs in large-scale. Lastly, some remaining challenges of the computational PPI prediction methods and future works are discussed. </p> </div> </div> </div>

Les cellules endothéliales forment une couche semi-perméable entre le sang et les organes. La prolifération, la migration et la polarisation des cellules endothéliales sont essentielles à la formation de nouveaux vaisseaux à partir de vaisseaux préexistants, soit l’angiogenèse. Le facteur de croissance de l’endothélium vasculaire (VEGF) peut activer la synthase endothéliale du monoxyde d’azote (eNOS) et induire la production de monoxyde d’azote (NO) nécessaire pour la régulation de la perméabilité vasculaire et l’angiogenèse. β- caténine est une composante essentielle du complexe des jonctions d’ancrage ainsi qu’un régulateur majeur de la voie de signalisation de Wnt/β-caténine dans laquelle elle se joint au facteur de transcription TCF/LEF et module l’expression de nombreux gènes, dont certains sont impliqués dans l’angiogenèse. La S-nitrosylation (SNO) est un mécanisme de régulation posttraductionnel des protéines par l’ajout d’un groupement nitroso au niveau de résidus cystéines. Le NO produit par eNOS peut induire la S-nitrosylation de la β−caténine au niveau des jonctions intercellulaires et moduler la perméabilité de l’endothélium. Il a d’ailleurs été montré que le NO peut contrôler l’expression génique par la transcription. Le but de cette thèse est d’établir le rôle du NO au sein de la transcription des cellules endothéliales, spécifiquement au niveau de l’activité de β-caténine. Le premier objectif était de déterminer si la SNO de la β-caténine affecte son activité transcriptionnelle. Nous avons montré que le NO inhibe l’activité transcriptionnelle de β- caténine ainsi que la prolifération des cellules endothéliales induites par l’activation de la voie Wnt/β-caténine. Il est intéressant de constater que le VEGF, qui induit la production de NO via eNOS, réprime l’expression de AXIN2 qui est un gène cible de Wnt s’exprimant suite à la i i stimulation par Wnt3a et ce, dépendamment de eNOS. Nous avons identifié que la cystéine 466 de la β-caténine est un résidu essentiel à la modulation répressive de son activité transcriptionnelle par le NO. Lorsqu’il est nitrosylé, ce résidu est responsable de la perturbation du complexe de transcription formé de β-caténine et TCF-4 ce qui inhibe la prolifération des cellules endothéliales induite par la stimulation par Wnt3a. Puisque le NO affecte la transcription, nous avons réalisé l’analyse du transcriptome afin d’obtenir une vue d’ensemble du rôle du NO dans l’activité transcriptionnelle des cellules endothéliales. L’analyse différentielle de l’expression des gènes de cellules endothéliales montre que la répression de eNOS par siRNA augmente l’expression de gènes impliqués au niveau de la polarisation tels que : PARD3A, PARD3B, PKCZ, CRB1 et TJ3. Cette analyse suggère que le NO peut réguler la polarisation des cellules et a permis d’identifier des gènes responsables de l’intégrité des cellules endothéliales et de la réponse immunitaire. De plus, l’analyse de voies de signalisation par KEGG montre que certains gènes modulés par l’ablation de eNOS sont enrichis dans de nombreuses voies de signalisation, notamment Ras et Notch qui sont importantes lors de la migration cellulaire et la différenciation des cellules de têtes et de tronc (tip/stalk). Le regroupement des gènes exprimés chez les cellules traitées au VEGF (déplétées de eNOS ou non) révèle que le NO peut affecter l’expression de gènes contribuant au processus angiogénique, dont l’attraction chimiotactique. Notre étude montre que le NO module la transcription des cellules endothéliales et régule l’expression des gènes impliqués dans l’angiogenèse et la fonction endothéliale. / induce the production of nitric oxide (NO), which is critical for vascular permeability and angiogenesis. β-catenin is an essential component of the adherens junction as well as Wnt/β-catenin signaling pathway and it binds T-cell factor (TCF)/lymphoid enhancer factor, regulating expression of numerous genes including those involved in angiogenesis. S-nitrosylation (SNO) is a mechanism used by NO to regulate protein activity by adding a nitroso group to cysteine residues. eNOS derived-NO is capable to induce SNO of β-catenin at cell-cell junction and modulate endothelial permeability. Additionally, NO has been implicated in the transcriptional control of gene expression. Therefore, the goals of our studies were to investigate the regulatory roles of NO on transcription in endothelial cells, in particular to the modulation of the transcriptional activity of β-catenin. The objective of the first study is to investigate whether the SNO of β-catenin affect its transcriptional activity. We found that NO inhibits β-catenin transcriptional activity and endothelial cell proliferation induced by activation of Wnt/β-catenin signaling. Interestingly, VEGF, which can activate eNOS to produce NO in endothelial cells, repressed Wnt3a-induced expression of Wnt target gene AXIN2 in an eNOS-dependent manner. Moreover, we identified that Cys466 on β-catenin is a critical residue for the repressive effects of NO on β-catenin transcriptional activity. Furthermore, we showed that Cys466 is responsible for the disruption iv of β-catenin/TCF4 transcriptional complex, and NO-dependant inhibition of Wnt3a-simulated endothelial cell proliferation. Given the known effects of NO on transcription, whole transcriptome sequencing was performed in order to understand the transcriptional regulation of NO in endothelial cells. By analyzing gene differential expression in cells transfected with control and eNOS siRNA, we show that eNOS knockdown upregulates the expression of genes involved in cell polarization, such as PARD3A, PARD3B, PKCZ, CRB1 and TJ3. The up-regulation of these genes was confirmed by qRT-PCR analysis, suggesting that NO may regulate cell polarization. The analysis also showed that genes regulated by eNOS knockdown were involved in endothelial cell integrity and immune response. In addition, KEGG signaling pathway analysis showed that genes regulated by eNOS were enriched in many signal pathways including Ras signaling, which are important for endothelial cell migration. Moreover, clustering of differentially expressed genes in VEGF-treated cells and VEGF-treated eNOS-depleted cells revealed that NO may affect expression of genes in angiogenesis in response to VEGF, including those genes involved in chemotaxis. Our studies show that NO affects transcription in endothelial cells and regulates expression of genes involved in angiogenesis and endothelial cell function.

O diabetes mellitus tipo 1 (DM1) tem etiologia autoimune, enquanto o diabetes mellitus tipo 2 (DM2) e o diabetes mellitus gestacional (DMG) são considerados como distúrbios metabólicos. Neste trabalho, foi realizada análise do transcriptoma das células mononucleares do sangue periférico (do inglês, peripheral mononuclear blood cells - PBMCs), obtidas de pacientes com DM1, DM2 e DMG, realizando análises por module maps a fim de comparar características patogênicas e aspectos gerais do tratamento com anotações disponíveis de genes modulados, tais como: a) análises disponíveis a partir de estudos de associação em larga escala (do inglês genome-wide association studies GWAS); b) genes associados ao diabetes em estudos clássicos de ligação disponíveis em bancos de dados públicos; c) perfis de expressão de células imunológicas fornecidos pelo grupo ImmGen (Immunological Project). Foram feitos microarrays do transcriptoma total da plataforma Agilent (Whole genome onecolor Agilent 4x44k) para 56 pacientes (19 DM1, 20 DM2 e 17 DMG). Para a compreensão dos resultados foram aplicados filtros não-informativos e as listas de genes diferencialmente expressos foram obtidas por análise de partição e análise estatística não-paramétrica (rank products), respectivamente. Posteriormente, análises de enriquecimento funcional foram feitas pelo DAVID e os module maps construídos usando a ferramenta Genomica. As análises funcionais contribuíram para discriminar os pacientes a partir de genes envolvidos na inflamação, em especial DM1 e DMG. Os module maps de genes diferencialmente expressos revelaram: a) genes modulados exibiram perfis de transcrição típicos de macrófagos e células dendríticas, b) genes modulados foram associados com genes previamente descritos como genes de complicação ao diabetes a partir de estudos de ligação e de meta-análises; c) a duração da doença, obesidade, número de gestações, níveis de glicose sérica e uso de medicações, tais como metformina, influenciaram a expressão gênica em pelo menos um tipo de diabetes. Esse é o primeiro estudo de module maps mostrando a influência de padrões epidemiológicos, clínicos, laboratoriais, imunopatogênicos e de tratamento na modulação dos perfis transcricionais em pacientes com os três tipos clássicos de diabetes: DM1, DM2 e DMG. / Type 1 diabetes (T1D) is an autoimmune disease while type 2 (T2D) and gestational diabetes (GDM) are considered as metabolic disturbances. We performed a transcriptome analysis of peripheral mononuclear blood cells obtained from T1D, T2D and GDM patients, and we took advantage of the module map approach to compare pathogenic and treatment features of our patient series with available annotation of modulated genes from i) genome-wide association studies; ii) genes provided by diabetes meta-analysis in public databases, iii) immune cell gene expression profiles provided by the ImmGen project. Whole genome one-color Agilent 4x44k microarray was performed for 56 (19 T1D, 20 T2D, 17 GDM) patients. Noninformative filtered and differentially expressed genes were obtained by partitioning and rank product analysis, respectively. Functional analyses were carried out using the DAVID software and module maps were constructed using the Genomica tool. Functional analyses contributed to discriminate patients on the basis of genes involved in inflammation, primarily for T1D and GDM. Module maps of differentially expressed genes revealed that: i) modulated genes exhibited transcription profiles typical of macrophage and dendritic cells, ii) modulated genes were associated with previously reported diabetes complication genes disclosed by association and meta-analysis studies, iii) disease duration, obesity, number of gestations, glucose serum levels and the use of medications, such as metformin, influenced gene expression profiles in at least one type of diabetes. This is the first module map study to show the influence of epidemiological, clinical, laboratory, immunopathogenic and treatment features on the modulation of the transcription profiles of T1D, T2D and GDM patients.

O diabetes mellitus tipo 1 (DM1) tem etiologia autoimune, enquanto o diabetes mellitus tipo 2 (DM2) e o diabetes mellitus gestacional (DMG) são considerados como distúrbios metabólicos. Neste trabalho, foi realizada análise do transcriptoma das células mononucleares do sangue periférico (do inglês, peripheral mononuclear blood cells - PBMCs), obtidas de pacientes com DM1, DM2 e DMG, realizando análises por module maps a fim de comparar características patogênicas e aspectos gerais do tratamento com anotações disponíveis de genes modulados, tais como: a) análises disponíveis a partir de estudos de associação em larga escala (do inglês genome-wide association studies GWAS); b) genes associados ao diabetes em estudos clássicos de ligação disponíveis em bancos de dados públicos; c) perfis de expressão de células imunológicas fornecidos pelo grupo ImmGen (Immunological Project). Foram feitos microarrays do transcriptoma total da plataforma Agilent (Whole genome onecolor Agilent 4x44k) para 56 pacientes (19 DM1, 20 DM2 e 17 DMG). Para a compreensão dos resultados foram aplicados filtros não-informativos e as listas de genes diferencialmente expressos foram obtidas por análise de partição e análise estatística não-paramétrica (rank products), respectivamente. Posteriormente, análises de enriquecimento funcional foram feitas pelo DAVID e os module maps construídos usando a ferramenta Genomica. As análises funcionais contribuíram para discriminar os pacientes a partir de genes envolvidos na inflamação, em especial DM1 e DMG. Os module maps de genes diferencialmente expressos revelaram: a) genes modulados exibiram perfis de transcrição típicos de macrófagos e células dendríticas, b) genes modulados foram associados com genes previamente descritos como genes de complicação ao diabetes a partir de estudos de ligação e de meta-análises; c) a duração da doença, obesidade, número de gestações, níveis de glicose sérica e uso de medicações, tais como metformina, influenciaram a expressão gênica em pelo menos um tipo de diabetes. Esse é o primeiro estudo de module maps mostrando a influência de padrões epidemiológicos, clínicos, laboratoriais, imunopatogênicos e de tratamento na modulação dos perfis transcricionais em pacientes com os três tipos clássicos de diabetes: DM1, DM2 e DMG. / Type 1 diabetes (T1D) is an autoimmune disease while type 2 (T2D) and gestational diabetes (GDM) are considered as metabolic disturbances. We performed a transcriptome analysis of peripheral mononuclear blood cells obtained from T1D, T2D and GDM patients, and we took advantage of the module map approach to compare pathogenic and treatment features of our patient series with available annotation of modulated genes from i) genome-wide association studies; ii) genes provided by diabetes meta-analysis in public databases, iii) immune cell gene expression profiles provided by the ImmGen project. Whole genome one-color Agilent 4x44k microarray was performed for 56 (19 T1D, 20 T2D, 17 GDM) patients. Noninformative filtered and differentially expressed genes were obtained by partitioning and rank product analysis, respectively. Functional analyses were carried out using the DAVID software and module maps were constructed using the Genomica tool. Functional analyses contributed to discriminate patients on the basis of genes involved in inflammation, primarily for T1D and GDM. Module maps of differentially expressed genes revealed that: i) modulated genes exhibited transcription profiles typical of macrophage and dendritic cells, ii) modulated genes were associated with previously reported diabetes complication genes disclosed by association and meta-analysis studies, iii) disease duration, obesity, number of gestations, glucose serum levels and the use of medications, such as metformin, influenced gene expression profiles in at least one type of diabetes. This is the first module map study to show the influence of epidemiological, clinical, laboratory, immunopathogenic and treatment features on the modulation of the transcription profiles of T1D, T2D and GDM patients.

Next generation sequencing is a modern method applied in plant virology for sensitive detection of previously characterized and novel pathogens without any preceding knowledge of them. In this study three novel and two already described viruses were detected by de novo assembly of Illumina single-end reads ( Hi-Seq 2500 system) from total poly(A) enriched RNA of diseased red clover (Trifolium pratense) and indicator plant (Nicotiana occidentalis 37B). The complete genomic sequence of novel Red clover carlavirus A (RCCA) was determined from Illumina reads, 5´, 3´ RACE, cloning, RT-PCR and Sanger sequencing. The presence of RCCV was also confirmed in mechanically inoculated tobacco plant.