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This thesis is concerned with the derivation of bioprocess models intended for engineering purposes. In contrast with other techniques, the methodology used to derive a macroscopic model is based on available intracellular information. This information is extracted from the metabolic network describing the intracellular metabolism. The aspects of metabolic regulation are modeled by representing the metabolism of cultured cells with several metabolic networks. Here we present a systematic methodology for deriving macroscopic models when such metabolic networks are known. A separate model is derived for each “phase” of the culture. Each of these models relies upon a set of macroscopic bioreactions that resumes the information contained in the corresponding metabolic network. Such a set of macroscopic bioreactions is obtained by translating the set of Elementary Flux Modes which are well-known tools in the System Biology community. The Elementary Flux Modes are described in the theory of Convex Analysis. They represent pathways across metabolic networks. Once the set of Elementary Flux Modes is computed and translated into macroscopic bioreactions, a general model could be obtained for the type of culture under investigation. However, depending on the size and the complexity of the metabolic network, such a model could contain hundreds, and even thousands, of bioreactions. Since the reaction kinetics of such bioreactions are parametrized with at least one parameter that needs to be identified, the reduction of the general model to a more manageable size is desirable. Convex Analysis provides further results that allow for the selection of a macroscopic bioreaction subset. This selection is based on the data collected from the available experiments. The selected bioreactions then allow for the construction of a model for the experiments at hand.

Cette thèse concerne le développement de nouvelles stratégies de contrôle d’unréfrigérateur cryogénique soumis à de fortes variations de charge thermique. De telles perturbationsvont se rencontrer lors du refroidissement des aimants supraconducteurs des futurs réacteurs defusion (tokamak JT-60SA par exemple).La modélisation d’un réfrigérateur de test, offrant une capacité de refroidissement de 800Wà 4.5K, a été effectuée sous le logiciel Matlab/Simulink. Celle-ci est basée sur les équationsthéoriques de la thermodynamique, de la thermique et de l’hydraulique et prend en compte lespropriétés non linéaire de l’hélium à basse température.A partir de ce modèle, une stratégie de contrôle multivariable a été proposée sur les deuxparties du réfrigérateur : la station de compression et la boîte froide. Les résultats expérimentauxmontrent de nettes améliorations et une plus grande stabilité du réfrigérateur en présence decharges pulsées par rapport à la stratégie initiale (PI).Un observateur de la charge thermique du bain d’hélium liquide a également été développé.Le modèle utilisé est construit par identification à partir de mesures internes au réfrigérateur. Ilpourrait servir comme outil de surveillance aux opérateurs. / This thesis is concerned with the development of a novel control scheme on a heliumrefrigerator subject to high pulsed loads. Such disturbance will happen during the cooling of thesuperconductive magnet, used in tokamak configuration.A dynamical model of a cryogenic station, which offers a cooling capacity of 800W at4.5K, has been produced. The modelling is based on the theoretical equations of thermodynamics,thermal physics and hydraulics and takes into account the non linear properties of helium at lowtemperature.Based on this model, a new control strategy has been developed for each of the two parts ofthe refrigerator: the warm compression system and the cold box. Experimental results showsignificant improvement with multivariable controllers as compared with the PIDs in the presenceof high pulsed loads.An observer of the thermal load of the helium bath has also been developed. The model isconstructed by identification using internal measures of the refrigerator. It can be used as conditionmonitoring tool for operators.

Les cellules immunitaires proviennent d'un ensemble commun de cellules souches hématopoïétiques qui se différencient hiérarchiquement en lignées myéloïdes et lymphoïdes. Ce processus est étroitement régulé par un réseau entrelacé de facteurs de transcription et de régulateurs épigénétiques, qui contrôlent l'activation et la répression des gènes impliqués. Les travaux récents sur la reprogrammation cellulaire ont montré que certaines protéines peuvent reprogrammer des cellules différenciées, comme le facteur de transcription C/EBPa qui peut induire la trans-differenciation de cellules B en macrophages. De plus, une courte induction de Cebpa suivie de l’expression des quatre facteurs de transcription Oct4-Sox2-Klf4-cMyc permet une reprogrammation extrêmement rapide en cellules pluripotentes. Afin de déchiffrer le réseau de régulation moléculaire contrôlant la spécification et la reprogrammation des cellules immunitaires, j’ai combiné différentes méthodes à haut débit pour analyser l’expression des gènes et leur régulation épigénétique, et ce au court de la reprogrammation des cellules B. J’ai découvert des interactions entre différents facteurs de transcription, au niveau des régions régulatrices de gènes des différents programmes génétiques impliqués (lymphoide, myeloide et pluripotence), et j’ai identifié des facteurs régulant l’état de la chromatine également impliqués dans la reprogrammation (notamment Lsd1, Hdac1, Brd4 et Tet2). Enfin, J’ai intégré ces données dans un modèle dynamique du réseau moléculaire régulant la spécification des cellules B et des macrophages à partir de progéniteurs multipotents. J’ai utilisé à la fois des méthodes analytiques (analyse des états stables) et des simulations (simulations logiques asynchrones, chaînes de Markov à temps continu) pour étudier in silico la différenciation et la reprogrammation cellulaire. Ces analyses ont révélés des régulations transcriptionelles encore inconnues, que nous avons pu confirmer expérimentalement. Nous avons ainsi obtenu une meilleure compréhension des circuits de régulation contrôlant le destin cellulaire. / Immune cells arise from a common set of hematopoietic stem cells, which differentiate hierarchically into the myeloid and lymphoid lineages. This process is tightly regulated by an intertwined network of transcription and epigenetic factors, which control both the activation and repression of gene programs, to ensure cell commitment. However, recent work on cellular reprogramminghas shown that the ectopic expression of some specific factors can enforce the trans-differentiation of committed cells. The transcription factor C/EBPa can induce the reprogramming of B-cells into macrophages. Furthermore, a pulse of Cebpa expression in B cells followed by the expression of the four transcription factors Oct4-Sox2-Klf4-cMyc leads to an extremely fast and efficient reprogramming into induced pluripotent stem cells. Despite the many data we have on the molecular mechanisms by which specific genes are regulated, we are still lacking a global understanding of the interplay between these factors and how theycontrol cell fate. In order to decipher the molecular regulatory network controlling immune cell specification and their reprogramming, I have combined a variety of high-throughput methods to measure changes in gene expression and epigenetic regulation during B cells reprogramming. I have revealed the interplay between different transcription factors at enhancers regulating genes of the different programs (B cells, macrophages and pluripotent cells) and identified epigenetic regulators forming complexes and controlling enhancers activities (such as Lsd1, Hdac1, Brd4 and Tet2) and consequently regulating cell fate. Finally, I integrated these data together with published data, in a computational model of the regulatory network controlling the specification of B-cells and macrophages from multipotent progenitors. I used both analytic tools (stable states analysis) and simulations (logical asynchronous simulations, continuous time Markov chains) to study in silico differentiation and reprogramming.These analyses have revealed previouslyunknown transcriptional regulations, which weconfirmed experimentally, and allowed us to get abetter understanding of the regulatory circuitscontrolling cell fate commitment.

Living cells are made up of networks of interacting genes, proteins and other bio-molecules. Simple interactions between network components in forms of feedback regulations can lead to complex collective dynamics. A key task in cell biology is to gain a thorough understanding of the dynamics of intracellular systems and processes. In this thesis, a combined approach of mathematical modelling, computational simulation and analytical techniques, has been used to obtain a deeper insight into the dynamical aspects of a variety of feedback systems commonly encountered in cells. These systems range from model system with detailed available molecular knowledge to general regulatory motifs with varying network structures. Deterministic as well as stochastic modelling techniques have been employed, depending primarily on the specific questions asked. The first part of the thesis focuses on dissecting the principles behind the regulatory design of the Tryptophan Operon system in Escherichia coli. It has evolved three negative feedback loops, namely repression, attenuation and enzyme inhibition, as core regulator mechanisms to control the intracellular level of tryptophan amino acid, which is taken up for protein synthesis. Despite extensive experimental knowledge, the roles of these seemingly redundant loops remain unclear from a dynamical point of view. We aim to understand why three loops, rather than one, have evolved. Using a large-scale perturbation/response analysis through modelling and simulations and novel metrics for transient dynamics quantification, it has been revealed that the multiple negative feedback loops employed by the tryptophan operon are not redundant. In fact, they have evolved to concertedly give rise to a much more efficient, adaptive and stable system, than any single mechanism would provide. Since even the full topology of feedback interactions within a network is insufficient to determine its behavioural dynamics, other factors underlying feedback loops must be characterised to better predict system dynamics. In the second part of the thesis, we aim to derive these factors and explore how they shape system dynamics. We develop an analytical approach for stability and bifurcation analysis and apply it to class of feedback systems commonly encountered in cells. Our analysis showed that the strength and the Hill coefficient of a feedback loop play key role in determining the dynamics of the system carrying the loop. Not only that, the position of the loop was also found to be crucial in this decision. The analytical method we developed also facilitates parameter sensitivity analysis in which we investigate how the production and degradation rates affect system dynamics. We find that these rates are quite different in the way they shape up system behaviour, with the degradation rates exhibiting a more intricate manner. We demonstrated that coupled-loop systems display greater complexity and a richer repertoire of behaviours in comparison with single-loop ones. Different combinations of the feedback strengths of individual loops give rise to different dynamical regimes. The final part of the thesis aims to understand the effects of molecular noise on dynamics of specific systems, in this case the Tryptophan Operon. We developed two stochastic models for the system and compared their predictions to those given by the deterministic model. By means of simulations, we have shown that noise can induce oscillatory behaviour. On the other hand, incorporating noise in an oscillatory system can alter the characteristics of oscillation by shifting the bifurcation point of certain parameters by a substantial amount. Measurement of fluctuations reveals that that noise at the transcript level is most significant while noise at the enzyme level is smallest. This study highlights that noise should not be neglected if we want to obtain a complete understanding of the dynamic behaviour of cells.

Differenzierungsentscheidungen von Zellen werden durch die Integration mehrerer Stimuli bestimmt. Die Differenzierung von Helfer-T-Zellen (Th-Zellen) ist hierfür ein gut untersuchtes Beispiel: reife Th-Zellen entwickeln sich beim Kontakt mit einem für sie spezifischen Antigen zu einem spezialisierten Subtyp, der von den in ihrer Umgebung vorhandenen Zytokinen abhängt und exprimieren dann einen spezifischen Mastertranskriptionsfaktor. Die häufigsten Th-Zell-Subtypen sind T-bet-exprimierende Th1-Zellen und GATA-3-exprimierende Th2-Zellen. Neuere Entdeckungen bezüglich der Plastizität von Th-Zell-Subtypen sowie die Existenz von T-bet+GATA-3+ Hybrid-Phänotypen haben die detaillierte Untersuchung vom Differenzierungsprozessen von Th-Zellen mit komplexer Zytokinsignale motiviert. Dazu haben wir systematisch die Zytokine IFN-g, IL-12 und IL-4 während der primären Differenzierung Th-Zellen titriert und Signaltransduktion und Zielgenexpression quantifiziert. Der Umfang und die Komplexität der Daten machten eine systematische Analyse notwendig, um involvierte Mechanismen genau zu identifizieren. Lineare Regressionsanalyse wurde verwendet, um die Netzwerktopologie zu extrahieren, wobei schon bekannte und zahlreiche neue Interaktionen vorausgesagt wurden. Die prognostizierte Netzwerktopologie wurde dann verwendet, um ein mechanistisches, mathematisches Modell der Zytokinsignalintegration zu entwickeln. Diese Methode hat ein hochgradig vernetztes regulatorisches Netzwerk inferiert. Bisher nicht beschriebene Funktionen von STAT-Proteine, die die Neuverkabelung des Netzwerkes während der Differenzierung vermitteln, wurden vorhergesagt. Ausgewählte neue Interaktionen wurden in gezielten genetischen Experimenten bestätigt. Während gegenseitige Inhibitionsmotive oft als kanonische digitale Schalter interpretiert werden, funktioniert das Th-Zell-Netwerk als ein Rheostat, der Variationen der Zytokinsignale in graduelle Expressionsänderungen der Mastertranskriptionsfaktoren übersetzt. Unsere Arbeit erklärt mechanistisch das beobachtete Kontinuum von Th-Zelldifferenzierungszuständen entlang der Th1-Th2-Achse und beschreibt eine quantitative Methode für die datenbasierte Inferenz zellulärer Netzwerke der Signalintegration. / Cell-fate decisions are governed by the integration of multiple stimuli. Th cell differentiation is a well-studied example thereof: mature Th cells differentiate into a specialised subtype upon encounter with their cognate antigen depending on the polarising cytokines present in their environment and start expressing specific master transcription factors. The most common Th cell subtypes are T-bet-expressing Th1 cells and GATA-3-expressing Th2 cells. Recent discoveries concerning the plasticity of Th cell subtypes as well as the existence of stable T-bet+GATA-3+ hybrid Th1/2 phenotypes have stimulated the detailed study of the differentiation process under different assumptions than the hitherto valid paradigm of single master transcription factor expression by using complex cytokine signals as inputs. Here, we developed a data-based approach for inferring the molecular network underlying the differentiation of T-bet- and/or GATA-3 expressing lymphocytes. We performed systematic titrations of the polarising cytokines IFN-g, IL-12 and IL-4 during primary differentiation of Th cells and quantified signal transduction as well as target-gene expression. The size and complexity of the dataset made a systematic analysis necessary to identify the mechanisms involved. To extract the network topology, we used linear regression analysis, retrieving known regulatory mechanisms and predicting numerous novel ones. This network topology was used to develop a mechanistic mathematical model of cytokine signal integration. This approach inferred a highly connected regulatory network. Previously undescribed functions of STAT proteins mediating network rewiring during differentiation were predicted. Selected new interactions were confirmed by experiments using gene-deficient cells. Importantly, while mutual-inhibition motifs are often considered canonical digital switches, the inferred Th-cell network acts as a rheostat, generating a continuum of differentiated states along the Th1-Th2 axis. This work explains the observed Th1-Th2 cell fate continuum mechanistically and provides a quantitative framework for the data-based inference of cellular signal integration networks.