A quantitative model of the initiation of DNA replication in Saccharomyces cerevisiae predicts the effects of system perturbations.

BackgroundEukaryotic cell proliferation involves DNA replication, a tightly regulated process mediated by a multitude of protein factors. In budding yeast, the initiation of replication is facilitated by the heterohexameric origin recognition complex (ORC). ORC binds to specific origins of replication and then serves as a scaffold for the recruitment of other factors such as Cdt1, Cdc6, the Mcm2-7 complex, Cdc45 and the Dbf4-Cdc7 kinase complex. While many of the mechanisms controlling these associations are well documented, mathematical models are needed to explore the network's dynamic behaviour. We have developed an ordinary differential equation-based model of the protein-protein interaction network describing replication initiation.ResultsThe model was validated against quantified levels of protein factors over a range of cell cycle timepoints. Using chromatin extracts from synchronized Saccharomyces cerevisiae cell cultures, we were able to monitor the in vivo fluctuations of several of the aforementioned proteins, with additional data obtained from the literature. The model behaviour conforms to perturbation trials previously reported in the literature, and accurately predicts the results of our own knockdown experiments. Furthermore, we successfully incorporated our replication initiation model into an established model of the entire yeast cell cycle, thus providing a comprehensive description of these processes.ConclusionsThis study establishes a robust model of the processes driving DNA replication initiation. The model was validated against observed cell concentrations of the driving factors, and characterizes the interactions between factors implicated in eukaryotic DNA replication. Finally, this model can serve as a guide in efforts to generate a comprehensive model of the mammalian cell cycle in order to explore cancer-related phenotypes

Development and application of computational methodologies in qualitative modeling

La présente thèse s'intitule "Développent et Application des Méthodologies Computationnelles pour la Modélisation Qualitative". Elle comprend tous les différents projets que j'ai entrepris en tant que doctorante. Plutôt qu'une mise en oeuvre systématique d'un cadre défini a priori, cette thèse devrait être considérée comme une exploration des méthodes qui peuvent nous aider à déduire le plan de processus regulatoires et de signalisation. Cette exploration a été mue par des questions biologiques concrètes, plutôt que par des investigations théoriques. Bien que tous les projets aient inclus des systèmes divergents (réseaux régulateurs de gènes du cycle cellulaire, réseaux de signalisation de cellules pulmonaires) ainsi que des organismes (levure à fission, levure bourgeonnante, rat, humain), nos objectifs étaient complémentaires et cohérents. Le projet principal de la thèse est la modélisation du réseau de l'initiation de septation (SIN) du S.pombe. La cytokinèse dans la levure à fission est contrôlée par le SIN, un réseau signalant de protéines kinases qui utilise le corps à pôle-fuseau comme échafaudage. Afin de décrire le comportement qualitatif du système et prédire des comportements mutants inconnus, nous avons décidé d'adopter l'approche de la modélisation booléenne. Dans cette thèse, nous présentons la construction d'un modèle booléen étendu du SIN, comprenant la plupart des composantes et des régulateurs du SIN en tant que noeuds individuels et testable expérimentalement. Ce modèle utilise des niveaux d'activité du CDK comme noeuds de contrôle pour la simulation d'évènements du SIN à différents stades du cycle cellulaire. Ce modèle a été optimisé en utilisant des expériences d'un seul "knock-out" avec des effets phénotypiques connus comme set d'entraînement. Il a permis de prédire correctement un set d'évaluation de "knock-out" doubles. De plus, le modèle a fait des prédictions in silico qui ont été validées in vivo, permettant d'obtenir de nouvelles idées de la régulation et l'organisation hiérarchique du SIN. Un autre projet concernant le cycle cellulaire qui fait partie de cette thèse a été la construction d'un modèle qualitatif et minimal de la réciprocité des cyclines dans la S.cerevisiae. Les protéines Clb dans la levure bourgeonnante présentent une activation et une dégradation caractéristique et séquentielle durant le cycle cellulaire, qu'on appelle communément les vagues des Clbs. Cet évènement est coordonné avec la courbe d'activation inverse du Sic1, qui a un rôle inhibitoire dans le système. Pour l'identification des modèles qualitatifs minimaux qui peuvent expliquer ce phénomène, nous avons sélectionné des expériences bien définies et construit tous les modèles minimaux possibles qui, une fois simulés, reproduisent les résultats attendus. Les modèles ont été filtrés en utilisant des simulations ODE qualitatives et standardisées; seules celles qui reproduisaient le phénotype des vagues ont été gardées. L'ensemble des modèles minimaux peut être utilisé pour suggérer des relations regulatoires entre les molécules participant qui peuvent ensuite être testées expérimentalement. Enfin, durant mon doctorat, j'ai participé au SBV Improver Challenge. Le but était de déduire des réseaux spécifiques à des espèces (humain et rat) en utilisant des données de phosphoprotéines, d'expressions des gènes et des cytokines, ainsi qu'un réseau de référence, qui était mis à disposition comme donnée préalable. Notre solution pour ce concours a pris la troisième place. L'approche utilisée est expliquée en détail dans le dernier chapitre de la thèse. -- The present dissertation is entitled "Development and Application of Computational Methodologies in Qualitative Modeling". It encompasses the diverse projects that were undertaken during my time as a PhD student. Instead of a systematic implementation of a framework defined a priori, this thesis should be considered as an exploration of the methods that can help us infer the blueprint of regulatory and signaling processes. This exploration was driven by concrete biological questions, rather than theoretical investigation. Even though the projects involved divergent systems (gene regulatory networks of cell cycle, signaling networks in lung cells), as well as organisms (fission yeast, budding yeast, rat, human), our goals were complementary and coherent. The main project of the thesis is the modeling of the Septation Initiation Network (SIN) in S.pombe. Cytokinesis in fission yeast is controlled by the SIN, a protein kinase signaling network that uses the spindle pole body as scaffold. In order to describe the qualitative behavior of the system and predict unknown mutant behaviors we decided to adopt a Boolean modeling approach. In this thesis, we report the construction of an extended, Boolean model of the SIN, comprising most SIN components and regulators as individual, experimentally testable nodes. The model uses CDK activity levels as control nodes for the simulation of SIN related events in different stages of the cell cycle. The model was optimized using single knock-out experiments of known phenotypic effect as a training set, and was able to correctly predict a double knock-out test set. Moreover, the model has made in silico predictions that have been validated in vivo, providing new insights into the regulation and hierarchical organization of the SIN. Another cell cycle related project that is part of this thesis was to create a qualitative, minimal model of cyclin interplay in S.cerevisiae. CLB proteins in budding yeast present a characteristic, sequential activation and decay during the cell cycle, commonly referred to as Clb waves. This event is coordinated with the inverse activation curve of Sic1, which has an inhibitory role in the system. To generate minimal qualitative models that can explain this phenomenon, we selected well-defined experiments and constructed all possible minimal models that, when simulated, reproduce the expected results. The models were filtered using standardized qualitative ODE simulations; only the ones reproducing the wave-like phenotype were kept. The set of minimal models can be used to suggest regulatory relations among the participating molecules, which will subsequently be tested experimentally. Finally, during my PhD I participated in the SBV Improver Challenge. The goal was to infer species-specific (human and rat) networks, using phosphoprotein, gene expression and cytokine data and a reference network provided as prior knowledge. Our solution to the challenge was selected as in the final chapter of the thesis

A Quantitative Model of the Initiation of DNA Replication in Saccharomyces cerevisiae

A crucial step in eukaryotic cell proliferation is the initiation of DNA replication, a tightly regulated process mediated by a multitude of protein factors. In Saccharomyces cerevisiae, this occurs as a result of the concerted action of an assembly of proteins acting at origins of replication, known as the pre-replicative complex (pre-RC). While many of the mechanisms pertaining to the functions of these proteins and the associations amongst them have been explored experimentally, mathematical models are needed to effectively explore the network’s dynamic behaviour. An ordinary differential equation (ODE)-based model of the protein-protein interaction network describing DNA replication initiation was constructed. The model was validated against quantified levels of protein factors determined in vivo and from the literature over a range of cell cycle timepoints. The model behaviour conforms to perturbation trials previously reported in the literature and accurately predicts the results of knockdown experiments performed herein. Furthermore, the DNA replication model was successfully incorporated into an established model of the entire yeast cell cycle, thus providing a comprehensive description of these processes. A screen for novel DNA damage response proteins was investigated using a unique proteomics approach that uses chromatin fractionation samples to enrich for factors bound to the DNA. This form of sub-cellular fractionation was combined with differential-in-gel-electrophoresis (DIGE) to detect and quantify low abundance chromatin proteins in the budding yeast proteome. The method was applied to analyze the effect of the DNA damaging agent methyl methanesulfonate (MMS) on levels of chromatin-associated proteins. Up-regulation of several previously characterized DNA damage checkpoint-regulated proteins, such as Rnr4, Rpa1 and Rpa2, was observed. In addition, several novel DNA damage responsive proteins were identified and assessed for genotoxic sensitivity. A strain in which the expression of the Ran-GTPase binding protein Yrb1 was reduced was found to be hypersensitive to genotoxic stress, pointing to a role for this nuclear import-associated protein in DNA damage response. The model presented in this thesis provides a tool for exploring the biochemical network of DNA replication. This is germane to the exploration of new cancer therapeutics considering the link between this disease (and others) and errors in proper cell cycle regulation. The high functional conservation between cell cycle mechanisms in humans and yeast allows predictive analyses of the model to be extrapolated towards understanding aberrant human cell proliferation. Importantly, the model is useful in identifying potential targets for cancer treatment and provides insights into developing highly specific anti-cancer drugs. Finally, the characterization of factors in the proteomic screen opens the door to further investigation of the roles of potential DNA damage response proteins

Regulation of eukaryotic Mcm2-7 activity

The transfer of genetic material from one cell generation to the next requires precise genome duplication. Aberrant DNA replication can lead to genomic instability and contribute to diseases arising from an unregulated cell cycle, such as cancer. Replicative DNA polymerases require a single-stranded (ssDNA) template from which to produce newly synthesized DNA. In eukaryotes, ssDNA is generated by the heterohexameric minichromosome maintenance 2 through 7 (Mcm2-7) replicative helicase that unwinds duplex DNA. Strict temporal separation of helicase loading and activation at multiple replication origins ensures once per cell cycle replication. The processes involved in activating Mcm2-7 to unwind DNA during S phase are poorly understood. Through in vivo and in vitro analyses, the current study examines the factors involved in modulating S. cerevisiae Mcm2-7 activity. Mec1, a member of the PIKK (phosphoinositide three-kinase-related kinase) family of proteins, is involved in the response to replicative stress and DNA damage. It also plays a role during an unperturbed cell cycle and is required to phosphorylate Mcm2-7 prior to helicase activation. We characterized alleles of S. cerevisiae mec1 that alter the conserved FATC domain. Mutants of Mec1 resulted in temperature sensitive growth, sensitivity to hydroxyurea and reduced kinase activity in vitro. These mutants were also less stable than wild-type Mec1 and demonstrated reduced nuclear localization. We also identified rpn3-L140P, which encodes a component of the 19S proteasomal regulatory particle of the 26S proteasome, as a suppressor of the temperature-sensitive growth caused by mec1-W2368A. As Cdt1 is required for the nuclear import and origin loading of Mcm2-7, we also sought to investigate the interaction between these two components in more detail. Using reconstituted Mcm2-7·Cdt1 complexes from bacterial-expressed proteins, we demonstrated that these complexes exhibit lower ATPase and helicase activity than Mcm2-7. We also showed that Mcm2-7 dissociates into subcomplexes, and that Mcm3, 5 and 7 bound origins in the absence of Cdt1. We propose that the reduced ATPase activity of Mcm2-7 by Cdt1 binding is induced by structural changes in the Mcm2-7 ring. We also suggest that Cdt1 helps to stabilize the Mcm2-7 hexamer. To investigate the role of phosphorylation on Mcm2-7, we utilized a phosphomimetic mutant of Mcm4 that when incorporated into Mcm2-7 can bypass the requirement for DDK. While phosphomimetic Mcm4 demonstrated slightly lower ATPase activity than the wildtype protein, phosphomimetic Mcm2-7 complexes exhibited wildtype ATPase, helicase and DNA binding activity. Taken together, our work identifies the functional role of the C-terminal residues of Mec1 and the protein’s turnover by the proteosome. Our studies also provide new insights into the factors and processes involved in the activation of Mcm2-7 to unwind DNA