L’un des objectifs principal de la biologie synthétique est de reprogrammer les organismes vivants pour résoudre des challenges mondiaux actuelles dans le domaine industriel, environnemental et de la santé. Tandis que de nombreux types de portes logiques génétiques ont été conçus, leur extensibilité reste limitée. Effectivement, la conception de portes logiques reste en grande partie un processus fastidieux et repose soit sur l’intuition humaine, soit sur des méthodes computationnelles de force brute. De plus, les circuits conçus sont généralement de grande taille et ne sont donc pas faciles à implémenter dans les organismes vivants.Durant ma thèse, mon objectif a été d’augmenter la puissance de calcul des circuits logiques utilisant des intégrases tout en permettant aux chercheurs d’implémenter simplement ces circuits à un large éventail d'organismes et d’entrées.Tout d’abord, j’ai développé un cadre extensible et composable pour le design systématique de systèmes multicellulaires implémentant de la logique Booléenne et histoire dépendent. Ce design est basé sur l'utilisation de sérine intégrases et peut intégrer un nombre arbitraire d’entrée. J’ai implémenté dans Escherichia coli des circuits logiques Booléens multicellulaires jusqu’à quatre entrées et des circuits histoire-dépendent jusqu’à 3 entrées. En raison de son extensibilité et de sa composabilité, ce design permet une implémentation simple et directe de circuits logiques dans des systèmes multicellulaires.J’ai également poussé le compactage des circuits logiques biologiques. Pour cela, j’ai généré une base de données complète de tous les circuits logiques unicellulaires possibles pour l’implémentation de fonctions booléennes à deux, trois et quatre entrées. La caractérisation d’un ensemble réduit des circuits de cette base de données devra être effectuée pour prouver la faisabilité de leur implémentation.Je pense que ces différentes stratégies de conception et les différents outils distribués (pièces biologiques et interface web) aideront les chercheurs et les ingénieurs à reprogrammer le comportement cellulaire de manière simple pour diverses applications. / A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, or healthcare. While many types of genetic logic gates have been engineered, their scalability remains limited. Indeed, gate design remains largely a tedious process and relies either on human intuition or on brute-force computational methods. Additionally, designed circuits are usually large and therefore not straightforward to implement in living organisms.Here, I aimed at increasing the computation power of integrase-based logic circuits while permitting researchers to simply implement these circuits to a large range of organisms and of inputs.First, I developed a scalable composition framework for the systematic design of multicellular systems performing integrase-based Boolean and history-dependent logic and integrating an arbitrary number of inputs. I designed multicell Boolean logic circuits in Escherichia coli to up to 4 inputs and History-dependent circuits to 3 inputs. Due to its scalability and composability, this design framework permits a simple and straightforward implementation of logic circuits in multicellular systems.I also pushed forward the compaction of biological logic circuits. I generated a complete database of single-cell integrase-based logic circuits to obtain all possible designs for the implementation of up to 4-input Boolean functions. Characterization of a reduced set of circuits will have to be performed to prove the feasibility of the implementation of these circuits.All these design strategies can be implemented via easily accessible web interfaces, and open collections of biological components that are made available to the scientific community. These tools will enable researchers and engineers to reprogram cellular behavior for various applications in a streamlined manner.

<p>Following the completion of the human genome sequence, post-genomic efforts have shifted the focus towards the analysis of the encoded proteome. Several different systematic proteomics approaches have emerged, for instance, antibody-based proteomics initiatives, where antibodies are used to functionally explore the human proteome. One such effort is HPR (the Swedish Human Proteome Resource), where affinity-purified polyclonal antibodies are generated and subsequently used for protein expression and localization studies in normal and diseased tissues. The antibodies are directed towards protein fragments, PrESTs (Protein Epitope Signature Tags), which are selected based on criteria favourable in subsequent laboratory procedures.</p><p>This thesis describes the development of novel software (Bishop) to facilitate the selection of proper protein fragments, as well as ensuring a high-throughput processing of selected target proteins. The majority of proteins were successfully processed by this approach, however, the design strategy resulted in a number ofnfall-outs. These proteins comprised alternative splice variants, as well as proteins exhibiting high sequence similarities to other human proteins. Alternative strategies were developed for processing of these proteins. The strategy for handling of alternative splice variants included the development of additional software and was validated by comparing the immunohistochemical staining patterns obtained with antibodies generated towards the same target protein. Processing of high sequence similarity proteins was enabled by assembling human proteins into clusters according to their pairwise sequence identities. Each cluster was represented by a single PrEST located in the region of the highest sequence similarity among all cluster members, thereby representing the entire cluster. This strategy was validated by identification of all proteins within a cluster using antibodies directed to such cluster specific PrESTs using Western blot analysis. In addition, the PrEST design success rates for more than 4,000 genes were evaluated.</p><p>Several genomes other than human have been finished, currently more than 300 genomes are fully sequenced. Following the release of the tree model organism black cottonwood (<i>Populus trichocarpa</i>), a bioinformatic analysis identified unknown cellulose synthases (CesAs), and revealed a total of 18 CesA family members. These genes are thought to have arisen from several rounds of genome duplication. This number is significantly higher than previous studies performed in other plant genomes, which comprise only ten CesA family members in those genomes. Moreover, identification of corresponding orthologous ESTs belonging to the closely related hybrid aspen (<i>P</i>. <i>tremula x tremuloides</i>) for two pairs of CesAs suggest that they are actively transcribed. This indicates that a number of paralogs have preserved their functionalities following extensive genome duplication events in the tree’s evolutionary history.</p>

Following the completion of the human genome sequence, post-genomic efforts have shifted the focus towards the analysis of the encoded proteome. Several different systematic proteomics approaches have emerged, for instance, antibody-based proteomics initiatives, where antibodies are used to functionally explore the human proteome. One such effort is HPR (the Swedish Human Proteome Resource), where affinity-purified polyclonal antibodies are generated and subsequently used for protein expression and localization studies in normal and diseased tissues. The antibodies are directed towards protein fragments, PrESTs (Protein Epitope Signature Tags), which are selected based on criteria favourable in subsequent laboratory procedures. This thesis describes the development of novel software (Bishop) to facilitate the selection of proper protein fragments, as well as ensuring a high-throughput processing of selected target proteins. The majority of proteins were successfully processed by this approach, however, the design strategy resulted in a number ofnfall-outs. These proteins comprised alternative splice variants, as well as proteins exhibiting high sequence similarities to other human proteins. Alternative strategies were developed for processing of these proteins. The strategy for handling of alternative splice variants included the development of additional software and was validated by comparing the immunohistochemical staining patterns obtained with antibodies generated towards the same target protein. Processing of high sequence similarity proteins was enabled by assembling human proteins into clusters according to their pairwise sequence identities. Each cluster was represented by a single PrEST located in the region of the highest sequence similarity among all cluster members, thereby representing the entire cluster. This strategy was validated by identification of all proteins within a cluster using antibodies directed to such cluster specific PrESTs using Western blot analysis. In addition, the PrEST design success rates for more than 4,000 genes were evaluated. Several genomes other than human have been finished, currently more than 300 genomes are fully sequenced. Following the release of the tree model organism black cottonwood (Populus trichocarpa), a bioinformatic analysis identified unknown cellulose synthases (CesAs), and revealed a total of 18 CesA family members. These genes are thought to have arisen from several rounds of genome duplication. This number is significantly higher than previous studies performed in other plant genomes, which comprise only ten CesA family members in those genomes. Moreover, identification of corresponding orthologous ESTs belonging to the closely related hybrid aspen (P. tremula x tremuloides) for two pairs of CesAs suggest that they are actively transcribed. This indicates that a number of paralogs have preserved their functionalities following extensive genome duplication events in the tree’s evolutionary history. / QC 20101021

Notre cerveau prend en charge différentes formes d’apprentissage dans ses diverses parties. C’est par exemple le cas des ganglions de la base, un ensemble de noyaux sous-corticaux qui est impliqué dans la sélection de l’action et une forme spécifique de l’apprentissage / mémoire, la mémoire procédurale (mémoire des compétences ou d’expertise). A l’échelle du neurone unique, le support le plus plausible de l’apprentissage et de la mémoire est la plasticité synaptique, le processus par lequel l’efficacité de la communication entre deux neurones change en réponse à un pattern spécifique de conditions environnementales. Parmi les différentes formes de plasticité synaptique, la plasticité dépendante du timing des spikes (STDP) représente le fait que le poids synaptique (l’efficacité de la connexion) change en fonction du temps écoulé entre l’émission des deux potentiels d’action (spikes) présynaptiques et postsynaptiques consécutifs. Si la STDP est une forme de plasticité qui a récemment attiré beaucoup d’intérêt, on ne comprend pas encore comment elle émerge des voies de signalisation / biochimiques qui la sous-tendent. Pour répondre à cette question, nous combinons les approches expérimentales de nos collaborateurs (pharmacologie et électrophysiologie) avec la modélisation de la dynamique des réseaux de signalisation impliquées (décrite par des équations différentielles ordinaires). Après estimation des paramètres, le modèle reproduit la quasi-totalité des données expérimentales, y compris la dépendance de la STDP envers le nombre stimulations pré- et post-synaptiques appariées et son exploration pharmacologique intensive (perturbation des voies de signalisation par des produits chimiques). En outre, contrairement à ce qui était largement admis dans la communauté des neurosciences, notre modèle indique directement que le système endocannabinoïde contrôle les changements du poids synaptique de façon bi-directionnelle (augmentation et diminution). De plus, nous étudions comment une série de facteurs comme la recapture du glutamate régule la STDP. Notre modèle représente une première étape pour l’élucidation de la régulation de l’apprentissage et de la mémoire au niveau du neurone unique dans les ganglions de la base. / Our brains support various forms of learning in their various subparts. This is for instance the case of the basal ganglia, a set of subcortical nuclei that is involved in action selection and a specific form of learning / memory, procedural memory (memory of skills or expertise). At the scale of single neurons, the most plausible support of learning and memory is synaptic plasticity, the process by which the efficiency of interneuronal communication changes in response to a pattern of environmental conditions. A recent focus of research is on spike-timing dependent plasticity (STDP), whereby the relative timing of activations (spikes) of connected pre- and postsynaptic neurons, determines the synaptic weight (the efficiency of synaptic connection). Notwithstanding, the dependence of STDP on underlying signaling pathways is not yet fully understood. To address this issue, we combine experimental approaches by our collaborators (pharmacology and electrophysiology) with modeling of the implicated signaling network (described by Ordinary-Differential Equations). After parameter estimation, the model reproduces much of experimental data, including the dependence of STDP on the number of paired stimuli of pre- and postsynaptic neurons and intensive pharmacological exploration (where signaling molecules are perturbed by chemicals). Furthermore, in opposition to what was widely believed in the neuroscience community, our model directly indicates that the endocannabinoid system supports bidirectional changes of the synaptic weight (increase and decrease). Moreover, we study how a range of factors including glutamate uptake regulates STDP. We expect our model to be a starting point to the elucidation of the regulation of learning and memory in the basal-ganglia at the single neuron level.

In dieser Arbeit wird ein Modell zum Aufzählen von DNA-Codes entwickelt. Indem eine Ordnung auf der Menge aller DNA-Codewörter eingeführt und auf die Menge aller Codes erweitert wird, erlaubt das Modell das Auffinden von DNA-Codes mit bestimmten Eigenschaften, wie Überlappungsfreiheit, Konformität, Kommafreiheit, Stickyfreiheit, Überhangfreiheit, Teilwortkonformität und anderer bezüglich einer gegebenen Involution auf der Menge der Codewörter. Ein auf Grundlage des geschaffenen Modells entstandenes Werkzeug erlaubt das Suchen von Codes mit beliebigen Kombinationen von Codeeigenschaften. Ein weiterer wesentlicher Bestandteil dieser Arbeit ist die Untersuchung der Optimalität von DNA-Codes bezüglich ihrer Informationsrate sowie das Finden solider DNA-Codes. / In this work a model for enumerating DNA codes is developed. By applying an order on the set of DNA codewords and extending this order on the set of codes, this model assists in the discovery of DNA codes with properties like non-overlappingness, compliance, comma-freeness, sticky-freeness, overhang-freeness, subword-compliance, solidness and others with respect to a given involution on the set of codewords. This tool can be used to find codes with arbitrary combinations of code properties with respect to the standard Watson-Crick-DNA involution. The work also investigates DNA codes with respect to the optimizing of the information rate, as well as finding solid DNA codes.

Biopolymer networks play a major role as part of the cytoskeleton. They provide stable structures and act as a medium for signal transport. These features encourage the application of such networks as organic computation devices. While research on this topic is not advanced yet, previous results are very promising. The protein actin in particular appears advantageous. It can be arranged to various stable structures and transmit several signals. In this study aster shaped networks were self-assembled via entropic forces by the crowding agent methyl cellulose. These networks are characterised by a regular and uniquely thick bundle structure, but have so far only been accounted in droplets of 100 μm diameter. We report now regular asters in an area of a few mm2 that could be observed even after months. Such stability outside of an organism is striking and underlines the great potential actin aster networks display.

Pendant les 20 dernières années, les astrocytes, un type de cellules cérébrales ayant été jusque là relativement ignoré des neuroscientifiques, ont peu à peu gagné en notoriété grâce à de multiples découvertes. Contrairement aux neurones, ces cellules ne transmettent pas de signaux électriques mais communiquent par des changements intracellulaires de leurs concentrations en calcium. Des découvertes récentes semblent indiquer que, loin d'agir en autarcie, les astrocytes répondent à l'activité neuronale et sembleraient, bien que cela soit plus débattu, moduler la transmission synaptique par le relargage de molécules spécifiques appelées `gliotransmetteurs' (en référence aux neurotransmetteurs). Comme les neurones, les astrocytes forment des réseaux et communiquent leur activité calcique par diffusion d'un astrocyte à l'autre, formant ainsi de véritables vagues de calcium intercellulaires. Deux réseaux, de neuronnes et d'astrocytes, cohabitent ainsi dans le cerveau ; mais, alors que les réseaux de neuronnes ont fait l'objet de recherches expérimentales et théoriques, les réseaux d'astrocytes restent encore mal connus. Ainsi, il n'a été découvert que très récement que la topologie de ces réseaux pourrait s'averer plus complexe que la vision qui dominait jusqu'alors : celle d'un syncitium astrocytaire dépourvu de spécificités topologiques. Les travaux présentés dans cette thèse portent principalement sur l'effet que ces différentes topologies pourraient avoir sur la signalisation calcique astrocytaire. En effet, autant au niveau subcellulaire qu'inter-cellulaire, les mécanismes gouvernant l'activité calcique des astrocytes restent mals connus. Même dans le cas le plus documenté de la réponse somatique des astrocytes à une stimulation neuronale, les caractéristiques précises que la stimulation doit avoir pour évoquer une réponse des astrocytes sont inconnues. Il en est de même pour la transmission de vagues de calcium dans des réseaux d'astrocytes : on ignore encore les possibles effets de la complexité récemment documentée des réseaux d'astrocytes sur la propagation de ces vagues. Enfin, au niveau subcelulaire, les astrocytes possèdent une morphologie ramifiée extrèmement complexe qui possède elle-même une activité calcique. Les travaux présentés dans cette thèse utilisent des outils de modélisation et de simulation afin de déterminer les répercussions que l'organisation en réseaux des astrocytes pourrait avoir sur leurs dynamiques calciques. En résumé, nous proposons que la topologie des réseaux d'astrocytes a (1) des répercussion au niveau cellulaire, modulant la réponse des astrocytes à des stimulations neuronales ; (2) contrôle la propagation de vagues de calcium inter-astrocytaire en la favorisant lorsque les réseau sont peu couplés ; (3) joue un rôle important dans l’apparition de phénomènes de résonance stochastique. / Over the last 20 years, astrocytes, a hitherto under-investigated type of brain cells, have gradually rose to prominence owing to multiple experimental discoveries. In contrast with neurons, these cells do not propagate electrical signals but communicate instead through changes in their intracellular calcium concentration. Recent discoveries indicate that, far from being isolated cells, astrocytes respond to neuronal activity and, although this is still controversial, seem to modulate synaptic transmission through the release of `gliotransmitter' molecules (in reference to neurotransmitters). Like neurons, astrocyte are organized in networks and communicate their calcium activity by intercellular diffusion of second messengers, forming intercellular calcium waves. Two networks, one of neurons and the other of astrocytes, thus coexist in the brain; while neuronal networks have been the subject of intense experimental and theoretical investigations, astrocyte networks have been much less investigated. Notably, it was only discovered recently that astrocyte network topology could be more complex than what the hitherto dominant view held (astrocytes organized in a syncytium deprived of any topological specificities). The work presented in this thesis is mainly related to the effect that different network topologies could have on astrocyte calcium signaling. The mechanisms that drive calcium signaling in astrocytes are, at both subcellular and intercellular levels, still not completely understood. Even in the best documented case of astrocyte somatic response to neuronal stimulation, the precise characteristic required from the stimulation to elicit an astrocytic response are still unknown. Similarly, the mechanisms governing intercellular calcium wave propagation in astrocyte networks are not fully known; notably, the effects of the recently documented network heterogeneity on calcium wave propagation have not been investigated. Finally, at the subcellular level, astrocytes display an extremely ramified and complex morphology that also hosts calcium activity. The work presented in this thesis make use of modeling and simulation in order to determine the possible effects of astrocyte network organization on their calcium signaling. We propose that astrocyte network topology: (1) controls single-cell responses to neuronal stimulation; (2) drives the propagation of intercellular calcium waves by favoring it when networks are weakly coupled; (3) can determine the appearance of stochastic resonance phenomena; (4) can be modulated by neuronal activity.

Estudos teóricos dos mecanismos moleculares responsáveis pela formação e estabilidade de complexos moleculares vêm ganhando relevância pelas possibilidades práticas que oferecem, por exemplo, na compreensão de diversas doenças e no desenho racional de fármacos. Neste projeto, nossa ênfase está no estudo de complexos de proteínas, extraídos do banco de dados de proteínas (PDB), onde desenvolvemos ferramentas computacionais as quais permitem efetuar análises em duas direções: 1) efetuar previsões básicas, através do emprego de propriedades eletrostáticas de proteínas, em diferentes condições e níveis preditivos e 2) realização de um conjunto de análises estatísticas, como freqüência de contato, em busca de preditores de complexos de proteínas e identificar padrões de interação entre seus aminoácidos em função da distância de separação. Com base nos resultados obtidos por ambos os estudos, objetivamos quantificar as forças físicas envolvidas na formação dos complexos protéicos. O foco do projeto, a longo prazo, é prever o fenômeno da complexação através da fusão dessas duas linhas de estudos: preditor básico de complexos protéicos e análise do potencial estatístico entre os aminoácidos que formam o complexo. O presente projeto é concluído com a construção de portais web que disponibilizarão os resultados obtidos por nossos trabalhos bem como a possibilidade de qualquer usuário, efetuar consultas por propriedades de proteínas e/ou grupo de proteínas. / Theoretical studies of the molecular mechanisms responsible for the formation and stability of molecular complexes are gaining relevance for the practical possibilities that they offer, for example, in the understanding of diverse diseases and rational drug design. In this project, our emphasis is on the study of protein complexes, extracted from protein data bank (PDB). We have developed computational tools which allow to perform analyses in two directions: 1) to make basic complexation forecasts, through the use of electrostatics properties of proteins, in different conditions and predictive levels, and 2) to carry out a set of statistical analyses, as contacts frequency, in order to build up predictor of protein complexes and to identify patters of interactions between the amino acids as a function of their separation distance. Based on the results obtained on both studies, we aim quantify the physical forces involved in the formation of protein complexes. The focus of the project, in the long run, is to foresee the phenomenon of the protein complexes through the fusing of these two study lines: a coarse-grained predictor of protein complexes and analysis of the statistical potentials between the amino acids that form the complex. The present project is concluded with the construction of web services where we make available the results obtained on our works. This server also has the possibility to be used by any computer user, that wishes to perform search on protein and/or protein group properties

No description available.

Estudos teóricos dos mecanismos moleculares responsáveis pela formação e estabilidade de complexos moleculares vêm ganhando relevância pelas possibilidades práticas que oferecem, por exemplo, na compreensão de diversas doenças e no desenho racional de fármacos. Neste projeto, nossa ênfase está no estudo de complexos de proteínas, extraídos do banco de dados de proteínas (PDB), onde desenvolvemos ferramentas computacionais as quais permitem efetuar análises em duas direções: 1) efetuar previsões básicas, através do emprego de propriedades eletrostáticas de proteínas, em diferentes condições e níveis preditivos e 2) realização de um conjunto de análises estatísticas, como freqüência de contato, em busca de preditores de complexos de proteínas e identificar padrões de interação entre seus aminoácidos em função da distância de separação. Com base nos resultados obtidos por ambos os estudos, objetivamos quantificar as forças físicas envolvidas na formação dos complexos protéicos. O foco do projeto, a longo prazo, é prever o fenômeno da complexação através da fusão dessas duas linhas de estudos: preditor básico de complexos protéicos e análise do potencial estatístico entre os aminoácidos que formam o complexo. O presente projeto é concluído com a construção de portais web que disponibilizarão os resultados obtidos por nossos trabalhos bem como a possibilidade de qualquer usuário, efetuar consultas por propriedades de proteínas e/ou grupo de proteínas. / Theoretical studies of the molecular mechanisms responsible for the formation and stability of molecular complexes are gaining relevance for the practical possibilities that they offer, for example, in the understanding of diverse diseases and rational drug design. In this project, our emphasis is on the study of protein complexes, extracted from protein data bank (PDB). We have developed computational tools which allow to perform analyses in two directions: 1) to make basic complexation forecasts, through the use of electrostatics properties of proteins, in different conditions and predictive levels, and 2) to carry out a set of statistical analyses, as contacts frequency, in order to build up predictor of protein complexes and to identify patters of interactions between the amino acids as a function of their separation distance. Based on the results obtained on both studies, we aim quantify the physical forces involved in the formation of protein complexes. The focus of the project, in the long run, is to foresee the phenomenon of the protein complexes through the fusing of these two study lines: a coarse-grained predictor of protein complexes and analysis of the statistical potentials between the amino acids that form the complex. The present project is concluded with the construction of web services where we make available the results obtained on our works. This server also has the possibility to be used by any computer user, that wishes to perform search on protein and/or protein group properties