Decoding the genomes from organisms that encompass all taxonomies provides the foundation for extensive, large scale studies of biological molecules such as RNA, protein and carbohydrates. The high-throughput studies facilitated by the existence of these genome sequences necessitate the development of new analytic methods for the interpretation of large sets of results. The work herein focuses on the development of a novel clustering method for the analysis of protein array results and examines its utilization in the analysis of integrated interaction data sets. Sets of proteins that interact with a molecule of interest were clustered according to their functional similarity. The simUI distance metric in the statistical analysis package BioConductor was applied to measure the similarity of two proteins utilizing the assembly of their Gene Ontology annotation. Clusters were identified by partitioning around medoids and interpreted using the summary label provided by the Gene Ontology annotation of the medoid. The utility of the method was tested on two published yeast protein array data sets and shown to allow interpretation of the data to yield novel biological hypotheses. We performed a protein array screen using the E3 ubiquitin ligase and PDZ domain-containing protein LNX1. We combined these results with other published LNX1 interactors to produce a set of 220 proteins that was clustered according to Gene Ontology annotation. From the clustering results, 14 proteins were selected for subsequent examination by co-immunoprecipitation, of which 8 proteins were confirmed as LNX1 interactors. Recognition of 6 proteins by specific LNX1 PDZ domains was confirmed by fusion protein pull-downs. This work supports the role of LNX1 as a signalling scaffold. The interpretation of protein array results using our novel clustering method facilitated the identification of candidate molecules for subsequent experimental analysis. Thus our analytical method facilitates identification of biologically relevant molecules within a large data set, making this method an essential component of complex, high-throughput experimentation.

Decoding the genomes from organisms that encompass all taxonomies provides the foundation for extensive, large scale studies of biological molecules such as RNA, protein and carbohydrates. The high-throughput studies facilitated by the existence of these genome sequences necessitate the development of new analytic methods for the interpretation of large sets of results. The work herein focuses on the development of a novel clustering method for the analysis of protein array results and examines its utilization in the analysis of integrated interaction data sets. Sets of proteins that interact with a molecule of interest were clustered according to their functional similarity. The simUI distance metric in the statistical analysis package BioConductor was applied to measure the similarity of two proteins utilizing the assembly of their Gene Ontology annotation. Clusters were identified by partitioning around medoids and interpreted using the summary label provided by the Gene Ontology annotation of the medoid. The utility of the method was tested on two published yeast protein array data sets and shown to allow interpretation of the data to yield novel biological hypotheses. We performed a protein array screen using the E3 ubiquitin ligase and PDZ domain-containing protein LNX1. We combined these results with other published LNX1 interactors to produce a set of 220 proteins that was clustered according to Gene Ontology annotation. From the clustering results, 14 proteins were selected for subsequent examination by co-immunoprecipitation, of which 8 proteins were confirmed as LNX1 interactors. Recognition of 6 proteins by specific LNX1 PDZ domains was confirmed by fusion protein pull-downs. This work supports the role of LNX1 as a signalling scaffold. The interpretation of protein array results using our novel clustering method facilitated the identification of candidate molecules for subsequent experimental analysis. Thus our analytical method facilitates identification of biologically relevant molecules within a large data set, making this method an essential component of complex, high-throughput experimentation.

Dans le système nerveux central adulte, la glycine est principalement connue pour son rôle de transmission d’un signal inhibiteur à l'intérieur des neurones matures, régulant ainsi l'activité du réseau neuronal. Paradoxalement, durant l'embryogenèse, ce même neurotransmetteur génère une transmission excitatrice produisant ainsi le premier signal électrique dans les neurones immatures. Le rôle et la signification fonctionnelle de ce changement d’activité durant le développement neurologique restent toujours inconnus. En utilisant l’embryon du poisson-zèbre comme modèle, nous avons exploré les mécanismes moléculaires et cellulaires dépendants de la signalisation de glycine dans les cellules souches neuronales (CSNs). En premier lieu, nous avons développé un outil d’analyse basé sur une combinaison de deux éléments: une lignée transgénique qui exprime du GFP dans les CSNs et la technique de séquençage de l’ARN total. Nous avons utilisé cette technique pour isoler et déterminer les mécanismes moléculaires régulés par la glycine dans les CSNs. Ceci a permis d’identifier plusieurs gènes candidats dont l’expression est modulée par l’activité glycinergique. Ces gènes appartiennent principalement à cinq différentes voies de signalisation canoniques incluant la voie de signalisation du calcium, TGF-bêta, Shh, Wnt et p53. Pour en apprendre davantage sur ces mécanismes moléculaires, nous avons exploré l’un d’entre eux soit la régulation de la signalisation p53 par l’activité glycinergique. En effet, nous avons démontré que l’activité glycinergique favorise la survie des CSNs par la régulation de la signalisation de p53 et agit spécifiquement sur la sous-population CSN-nestin+ durant la neurogenèse. Dans un autre projet, nous avons examiné la régulation de l’expression de lnx1 par l’activité glycinergique. Nous avons démontré que la signalisation de glycine/lnx1 régule la prolifération des CSNs via la modulation de l’activité de Notch durant la neurogenèse. En conclusion, dans ce projet de thèse, j’ai mis en lumière plusieurs mécanismes moléculaires et cellulaires modulés par l’activité glycinergique dans les CSNs. Ceci peut contribuer dans le futur à la compréhension de la physiopathologie liée au dysfonctionnement de cette dernière ainsi qu’à l’identification de nouvelles cibles thérapeutiques. / In the adult central nervous system, glycine is mainly known as an inhibitory neurotransmitter in mature neurons, thereby regulating the neural network activity. Paradoxically, during embryogenesis, the same neurotransmitter generates excitatory transmission and induces the first electrical signal in immature neurons. The role and functional significance of this change in glycinergic activity during neurogenesis are still unknown. In this study, we used zebrafish embryos as a model to explore the glycine-dependent molecular and cellular mechanisms in neural stem cells (NSCs). First, we developed an in vivo analysis method based on two main elements: a transgenic line that expresses GFP within NSCs and the RNA sequencing technique. This method of analysis was used to determine glycine-dependent molecular mechanisms in NSCs. We identified several candidate genes whose expression is modulated by the glycinergic activity. These genes participate in five different canonical signaling pathways including the calcium signaling pathway, TGF-beta, Shh, Wnt and p53. To further understand these molecular mechanisms, we focused our investigation on the regulation of p53 signaling by the glycinergic activity. Indeed, we have demonstrated that glycinergic activity promotes the survival of NSCs by regulating p53 signaling and more specifically acting on NSC-nestin + subpopulation during neurogenesis. Finally, we explored the regulation of lnx1 expression by glycinergic activity. We have demonstrated that glycine/lnx1 signaling regulates the proliferation of NSCs via the modulation of Notch activity during neurogenesis. In conclusion, during this thesis project, I highlighted several molecular and cellular mechanisms modulated by the glycinergic activity in NSCs. These relevant results may contribute in the future to the understanding of the physiopathology related to glycinergic activity dysfunctions and the identification of new therapeutic targets.