The objective of the field of Synthetic Biology is to implement novel functionalities in a biological context or redesign existing biological systems. To achieve this, it employs tried and tested engineering principles, such as standardisation and the design-build-test cycle. A crucial part of this process is the convergence of modelling and experiment. The aim of this thesis is to improve the design principles employed by Synthetic Biology in the context of Gene Regulatory Networks (GRNs). Small Ribonucleic Acids (sRNAs), in particular, are focussed on as a mechanism for post-transcriptional expression regulation, as they present great potential as a tool to be harnessed in GRNs. Modelling sRNA regulation and its interaction with its associated chaperone Host-Factor of Bacteriophage Qβ (Hfq) is investigated. Inclusion of Hfq is found to be necessary in stochastic models, but not in deterministic models. Secondly, feedback is core to the thesis, as it presents a means to scale-up designed systems. A linear design framework for GRNs is then presented, focussing on Transcription Factor (TF) interactions. Such frameworks are powerful as they facilitate the design of feedback. The framework supplies a block diagram methodology for visualisation and analysis of the designed circuit. In this context, phase lead and lag controllers, well-known in the context of Control Engineering, are presented as genetic motifs. A design example, employing the genetic phase lag controller, is then presented, demonstrating how the developed framework can be used to design a genetic circuit. The framework is then extended to include sRNA regulation. Four GRNs, demonstrating the simplest forms of genetic feedback, are then modelled and implemented. The feedback occurs at three different levels: autoregulation, through an sRNA and through another TF. The models of these GRNs are inspired by the implemented biological topologies, focussing on steady state behaviour and various setups. Both deterministic and stochastic models are studied. Dynamic responses of the circuits are also briefly compared. Data is presented, showing good qualitative agreement between models and experiment. Both culture level data and cell population data is presented. The latter of these is particularly useful as the moments of the distributions can be calculated and compared to results from stochastic simulation. The fit of a deterministic model to data is attempted, which results in a suggested extension of the model. The conclusion summarises the thesis, stating that modelling and experiment are in good qualitative agreement. The required next step is to be able to predict behaviour quantitatively.

Colorectal cancer is the third most common cancer and the leading cause of cancer deaths in Western industrialised countries. Despite recent advances in the screening, diagnosis, and treatment of colorectal cancer, an estimated 608,000 people die every year due to colon cancer. Our current knowledge of colorectal carcinogenesis indicates a multifactorial and multi-step process that involves various genetic alterations and several biological pathways. The identification of molecular markers with early diagnostic and precise clinical outcome in colon cancer is a challenging task because of tumour heterogeneity. This Ph.D.-thesis presents the molecular and cellular mechanisms leading to colorectal cancer. A systematical review of the literature is conducted on Microarray Gene expression profiling, gene ontology enrichment analysis, microRNA and system Biology and various bioinformatics tools. We aimed this study to stratify a colon tumour into molecular distinct subtypes, identification of novel diagnostic targets and prediction of reliable prognostic signatures for clinical practice using microarray expression datasets. We performed an integrated analysis of gene expression data based on genetic, epigenetic and extensive clinical information using unsupervised learning, correlation and functional network analysis. As results, we identified 267-gene and 124-gene signatures that can distinguish normal, primary and metastatic tissues, and also involved in important regulatory functions such as immune-response, lipid metabolism and peroxisome proliferator-activated receptors (PPARs) signalling pathways. For the first time, we also identify miRNAs that can differentiate between primary colon from metastatic and a prognostic signature of grade and stage levels, which can be a major contributor to complex transcriptional phenotypes in a colon tumour.

As respostas das plantas ao ambiente são orquestradas por fatores genéticos, bem como sua flexibilidade metabólica, uma vez que essas são sésseis. As respostas das plantas ao ambiente são regidas por fatores genéticos, bem como sua flexibilidade metabólica, uma vez que essas são sésseis. A forma com que os padrões gênicos e metabólicos redundam entre as células, refletem nos diferentes níveis organizacionais (célula, tecido, órgão e até o organismo como um todo). Por isso, para entendermos as respostas das plantas em determinados estágios de desenvolvimento ou condições é importante explorarmos ao máximo os diferentes níveis de regulação. Neste sentido, tem crescido a quantidade de dados biológicos obtidos através de métodos que produzem dados em larga escala, visando um estudo de forma sistêmica. Embora existam várias ferramentas para a integração de dados biológicos, elas estão desenvolvidas para organismos modelos, inviabilizando análises para outros, como a cana-de-açúcar, que possui vários dados biológicos disponíveis, mas com genoma complexo e incompleto. Tendo em vista a importância econômica da cana-de-açúcar e o interesse em entendermos o processo de degradação da parede celular, desenvolvemos a ferramenta SIT (Systems Integration Tool), para integração dos dados disponíveis (transcritoma, proteoma e atividade enzimática). A implementação da ferramenta foi realizada utilizando as linguagens de programação Perl e Java. SIT possui uma interface gráfica, podendo ser executada localmente, a qual possibilita a integração de até seis diferentes conjuntos de dados. A visualização do resultado é obtida na forma de redes complexas, permitindo ao usuário a visualização e edição dinâmica da integração. O uso da SIT permitiu no presente estudo, entre outros, a identificação de elementos chave na degradação da parede celular, presentes nos diferentes conjuntos de dados explorados, apontando portanto, potenciais alvos de estudos experimentais. SIT pode ser aplicada à diferentes conjuntos de dados, a qual poderá auxiliar em estudos futuros em várias áreas do conhecimento. / Plant are sessile organisms, and their responses to environmental stimuli are orchestrated by genetic factors, as well as by their metabolic flexibility. Inside the cell, there are genetic and metabolic patterns responsible for cell redundancy, and that reflects on different organizational levels (cell, tissue, organ, until a whole organism). Thus, to understand plant responses to certain conditions, it is important to understanding different regulatory levels. Recently, there was a large increase in availability of biological data. This happened due to the advance in next-generation sequencing techniques, which now enables more profound system biology studies. Despite the availability of several integration tools for analysis of biological data, these were developed for organism modeling. However, such tools are partially effective for sugarcane, for which there are large amounts of data, but has incomplete genome data. Due to the economic importance of sugarcane and aiming at understanding cell wall degradation process, we develop the software Systems Integration Tool (SIT). The tool integrates available data (transcriptomics, proteomics, and enzymatic activity). The implementation was performed in Perl and Java. SIT has a graphical interface, standalone execution, enabling integration until six layers of data. Integration results are generated as complex networks, allowing the users to visualize and dynamically edit the networks. The present study allowed the identification of key cell wall regulatory elements present on different data sets pointing out to potential targets for experimental validation. SIT can be applied to various data sets being capable of helping future studies in different areas of knowledge.

Kalzium ist ein wichtiger intrazelluläre Botenstoff, der extrazelluläre Signale in zelluläre Antworten übersetzt. Oft werden externen Signale in wiederholte Anstiege der zytosolischen Kalziumkonzentration übersetzt, die als Oszillationen bezeichnet werden. Diese interdisziplinäre Arbeit kombiniert biologische Experimente, analytische Methoden der theoretischen Physik und Computersimulationen, um den Oszillationsmechanismus zu charakterisieren. Von wesentlicher Bedeutung ist dabei die räumlich inhomogene Verteilung der Kanäle, die Kanalcluster bilden. Dies induziert zusammen mit Pumpen große Konzentrationsgradienten in der Nähe von offenen Clustern, was zu einer hierarchischen Organisation führt. Unter diesem Gesichtspunkt erwartet man, dass Kalziumoszillationen stochastisch sind und auf räumlicher Wechselwirkung beruhen. Diese Hypothese wird im ersten Teil der Arbeit experimentell verifiziert, indem Oszillationen vier verschiedener Zellarten analysiert werden. Der Kalziumsignalweg nutzt thermisches Rauschen konstruktiv um globale Signale zu bilden. Dabei werden molekulare Fluktuationen durch die hierarchische Struktur auf die zelluläre Ebene gehoben. Dies steht im Gegensatz zu der jahrzehntelang weitläufigen Auffassung, dass Kalzium ein repräsentatives Beispiel eines zellulären Oszillators ist. Des weiteren macht dieses Ergebnis Kalzium zu einem ersten natürlichen Beispiel für "array enhanced coherent resonance". Im Modellierungsteil dieser Arbeit wird ein physiologisches Modell für die intrazelluläre Kalziumdynamik entwickelt, das die dreidimensionale Struktur von Zellen berücksichtigt. Es verwendet ein detailliertes Kanalmodell und berücksichtigt sowohl Diffusion als auch Reaktionen mit Puffern. Der entwickelte parallele Green''s cell Algorithmus generiert in Abhängigkeit von physiologischen Parametern das gesamte Spektrum der experimentell bekannten Kalziumsignale und spiegelt die experimentellen Daten des ersten Teils in nahezu perfekter Weise wider. / Calcium is an important second messenger in cells serving as a critical link between extracellular stimuli and their cellular responses. The external signals are translated often into repeated increases of the cytosolic calcium concentration what is referred as oscillations. This work uses an interdisciplinary approach combining experimental techniques from biology, analytical tools from theoretical physics and computer simulations to clarify the question of the oscillation mechanism and how cells can generate globally coordinated calcium signals originated from local stochastic channel dynamics. In this context, the spatial inhomogeneous distribution of channels forming channel clusters plays a key role. Together with calcium pumps and buffers, this induces huge functional concentration gradients close to open clusters, leading to a hierarchical organization of calcium signals. Thus, calcium oscillations are predicted to be stochastic and to have a spatial character. This hypothesis is justified experimentally in the first part of this thesis by analyzing calcium oscillations of four different cell types. Hence, calcium signaling constructively uses thermal noise to build global signals. This contradicts the current opinion of the last decades of calcium being a representative cellular oscillator. Moreover, this makes calcium a first natural example of array enhanced coherent resonance. In the modeling part of this work, a physiological model for intracellular calcium dynamics in three spatial dimensions is developed that takes the spatial arrangement of cells seriously. It uses a detailed channel model for the discrete release sites and takes into account diffusion and buffer interaction of calcium. In dependence on physiologic parameters, the developed parallel Green''s cell algorithm generates in a natural way the whole spectrum of experimentally known calcium signals and fits the experimental data of the first part in an almost perfect manner.

The content of the thesis is a description of intracellular processes responsible for cell cycle regulation and reactions of cells to external and internal stimuli. Thoroughly described are important signaling pathways with appropriate methods, which can be used to simulate them in silico. From these cellular processes, a cell cycle model is created and implemented in a tool programmed in C ++ with OpenGL used for visualization. The model is then tested for various cell processes including HeLa cells growth. Finally, the results are compared with the behavior of living cells.

This article focuses on a systems biology approach to studying the pathophysiology of cigarette smoking during pregnancy. Particular emphasis is given to the damaging role of oxidative stress. Cigarette smoking exerts multiple adverse affects but abundant evidence, mostly in adults, suggests that oxidative stress and free radical damage is a major pathophysiological factor. Smoking during pregnancy is known to contribute to numerous poor birth outcomes, such as low birth weight, preterm birth as well as life-long health and developmental problems. It is clinically important to know the separate contributions that cigarette derived-nicotine and smoking-induced free oxidative stress make to these poor outcomes. Surprisingly, the extent to which smoking dependent oxidative stress contributes to these poor outcomes is not well studied but the application of redox proteomics should be useful. Considerable biochemical evidence suggests that antioxidants, such as tocopherols and ascorbate, could be useful in minimizing oxidative stress induced pathology to the developing fetus in those women who, despite medical advice, continue to smoke. Nevertheless, this suggestion has yet to be tested in well-designed clinical studies.

La régulation de l’expression génique chez les bactéries résulte d’un processus complexe comprenant deux étapes majeures, la transcription des gènes en ARNm et leur traduction en protéines. Les études qui allient les données de transcription et de traduction sont rares et l’importance de chacun de ces deux mécanismes dans un processus global d’adaptation n’est pas encore clairement définie. Or, les faibles corrélations entre les niveaux d’ARNm et de protéines chez les bactéries et, plus particulièrement chez la bactérie modèle Lactococcus lactis, suggèrent l’importance des régulations traductionnelles.Aujourd’hui des exemples de mécanismes de régulation de la traduction à l’échelle moléculaire se multiplient, néanmoins il n’existe que très peu de méthodes systémiques permettant d’étudier ces régulations à l’échelle globale. Dans cette thèse, l’état de traduction de chacun des ARNm de la cellule a été estimé par la mesure du traductome. Ainsi, pour chaque ARNm, le pourcentage de molécules en traduction et sa densité en ribosomes ont été déterminés. Pour la première fois, une image complète de l’état de traduction de la bactérie a été obtenue montrant une grande variabilité traductionnelle au sein de la population des transcrits. De plus, il a été démontré que cet état traductionnel était très régulé. De fait, lors d’une carence nutritionnelle, la machinerie de traduction est globalement diminuée et il est observé une redistribution de l’efficacité de traduction vers des gènes nécessaires à la bactérie pour être adaptée au stress imposé. D’autre part, cette forte variabilité de l’état de traduction au sein des ARNm a pu être reliée à des différences au niveau du mécanisme propre de la traduction. En effet, les coefficients de contrôle des trois grandes étapes de la traduction, estimés par modélisation à partir des données de traductome, dépendent fortement de la nature des gènes. Ainsi un contrôle au niveau de l’étape d’initiation a été démontré comme attendu pour la majorité des gènes. Mais pour un grand nombre de gènes, un contrôle par l’élongation (et pour un nombre plus restreint par la terminaison) a été aussi mis en évidence chez L. lactis. Dans le contrôle global de l’expression génique, il a d’autre part été mis en évidence que les processus de traduction et de dégradation des ARNm étaient impliqués et associés à des régulations coordonnées ou non en fonction des conditions de croissance.En conclusion, ces travaux de thèse ont montré l’importance des régulations de la traduction. Plus largement, ils ont souligné la nécessité de caractériser les différents niveaux de régulations de l’expression génique afin de mieux appréhender la physiologie de la cellule / In bacteria, regulation of gene expression results from a complex program composed of two main steps: transcription of genes into mRNA and their translation into proteins. Few studies integrate both transcription and translation, so their relative importance in the global process of bacterial adaptation is not yet well defined. However, weak correlations between mRNA and protein levels were found in bacteria, in particular in the lactic acid bacteria model Lactococcus lactis, suggesting significant translation regulations in this bacterium.Nowadays, translation regulation mechanisms are mainly investigated at the molecular level since only few systemic methods exist to study these regulations at a genome-wide scale. During this PhD, translation state of all mRNA was estimated by translatome measurement. For each mRNA in the cell, percentage of its molecules in translation and its ribosome density were determined. For the first time in bacteria, a detailed picture of the translation state of all transcripts was obtained. Large variation of translation state was observed within the transcript population demonstrating a high diversity of translational regulations in a given physiological state. In addition, during nutrient starvation, the global translation machinery was decreased and associated with a redistribution of the translation efficiency towards genes required to stress adaptation.Changes in translation state were related to specific kinetics of the three elementary steps of translation. From translatome data, control coefficients of initiation, elongation and termination on the global translation process were modeled. The translation limiting step was strongly dependent on gene function. Although a control by initiation was observed for most of the genes of L. lactis, a large set of genes was elongation limited, and even few genes were limited by termination.In the global control of gene expression, both translation and mRNA decay were involved and led to coupled or uncoupled regulations according to growth conditions.Finally, this work has demonstrated the importance of translation regulations in bacteria. This result strengthens the necessity to include all the different layers of gene expression regulation in order to better understand cell physiology

Ce projet de thèse, dans le cadre d’une collaboration entre le LIMOS et le LPC, s’inscrit dans une démarche de recherche permettant la mise en synergie des domaines de la biologie, de la physique et de l’informatique par la proposition d’une démarche de simulation permettant la réalisation d’expériences in silico. Pour cela, nous nous proposons de développer une plateforme logicielle dédiée à la modélisation multiéchelle des systèmes biologiques qui pourra par la suite être interfacée avec les outils de simulation de physique des particules. Nous proposons également un modèle individu-centré de cellule biologique paramétrable à l’aide de données obtenues d’expériences in vitro. Nous présentons l’élaboration de cette plateforme et une démarche de validation de ses fonctionnalités à travers l’implémentation de modèles d’automates cellulaires de la littérature. Nous présentons ensuite la construction du modèle de cellule biologique en prenant le temps d’expliquer comment est pris en compte le système biologique, comment nous le modélisons puis comment nous paramétrons le modèle. Nous modélisons les processus internes de la cellule, dont les caractéristiques sont liées à l’information génétique qu’elle porte. Ce modèle de cellule permet de reproduire le comportement d’une cellule isolée, et à partir de là, d’un ensemble de cellules via l'automate. Le modèle est ensuite utilisé pour retrouver les courbes de croissance d'une population de bactéries Escherichia coli. Des valeurs de données de fluxomique ont été exploitées et ont permis la reproduction in silico des expériences in vitro dont elles étaient issues. / This PhD thesis project is part of a research program in the fields of biology, physics and computer science aiming to propose a simulation approach for performing experiments in silico. For this, we propose to develop a software platform dedicated to multi-scale modeling of biological systems that can be combined with particle physics simulation tools. We also propose a general individual-based model of biological cell in which data obtained from in vitro experiments can be used. We present the development of this platform and the validation process of its functionalities through the implementation of cellular automata from the literature. We then present the design of the biological cell model by giving the hypothesis we made, how we model and how we parameterize the model. Starting from a simple biological system, bacteria, observed in liquid culture, our model uses a multi-scale middle-out approach. We focus on the cell and we model internal processes, assuming that all their properties come from genetic information carried out by the cell’s genome. This model allows to consider the cell behavior, and then to obtain the behavior of a cell population. Data from fluxomic experiments have been used in this model to parameterize the biochemical processes. The results we obtain allow us to consider the model as validated as simulation results match the experimental data.

DieMenschheit ist vielfältigen chemischenWirkstoffen ausgesetzt – zum Beispiel durch Kosmetika und Pharmazeutika sowie durch viele andere chemische Quellen. Es wird angenommen, dass diese stetige Exposition mit Chemikalien gesundheitliche Beeinträchtigungen bei Menschen hervorruft. Zudem haben Regulierungsbehörden aus Europa und den USA festgestellt, dass es ein Risiko gibt, welches mit der kombinierten Exposition durch mehrere Chemikalien im Zusammenhang steht. Mögliche Kombinationen von Tausenden Wirkstoffen zu testen, ist sehr zeitaufwendig und nicht praktikabel. Das Hauptanliegen dieser Arbeit ist es, die Probleme von Off-target-Effekten chemischer Strukturen zu benennen – mit den Mitteln der Chemieinformatik, der strukturellen Bioinformatik sowie unter Berücksichtigung von computerbasierten, systembiologischen Ansätzen. Diese Dissertation ist in vier Hauptprojekte eingeteilt. ImProjekt I (Kapitel 3)wurde ein neuartiger Ensemble-Ansatz basierend auf der strukturellen Ähnlichkeit von chemischenWirkstoffen und Bestimmungen von toxischen Fragmenten implementiert,um die orale Toxizität bei Nagetieren vorherzusagen. Im Projekt II (Kapitel 4) wurden – auf der Grundlage von Daten des Tox21 Wettbewerbs – unterschiedliche Machine-Learning Modelle entwickelt und verglichen, um die Komponenten vorherzusagen, die in den toxikologischen Stoffwechselwegen mit Zielmolekülen interagieren von target-spezifischenWirkstoffen vorherzusagen. In Projekt III (Kapitel 5) wird ein neuartiger Ansatz beschrieben, welcher das dreigliedrige Konzept aus computerbasierter Systembiologie, Chemieinformatik und der strukturellen-Bioinformatik nutzt, um Medikamente zu bestimmen, welche das metabolische Syndrom hervorrufen. In Projekt IV (Kapitel 6) wurde in silico ein Screening Protokoll entwickelt, welches die strukturelle Ähnlichkeit, die pharmakophorischen Eigenschaften und die Überprüfung von computerbasierten Docking Studien berücksichtigt. / Exposure to various chemicals agents through cosmetics, medications, preserved food, environments and many other sources have resulted in serious health issues in humans. Additionally, regulatory authorities from Europe and United States of America have recognized the risk associated with combined exposure to multiple chemicals. Testing all possible combinations of these thousands of compounds is impractical and time consuming. The main aim of the thesis is to address the problem of off-targets effects of chemical structures by applying and developing cheminformatics, structural bioinformatics and computational systems biology approaches. This dissertation is divided into four main projects representing four different computational methods to aid different level of toxicological investigations. In project I (chapter 3) a novel ensemble approach based on the structural similarity of the chemical compounds and identifications of toxic fragments was implemented to predict rodent oral toxicity. In project II (chapter 4) different machine learning models were developed and compared using Tox 21 challenge 2014 data, to predict the outcomes of the compounds that have the potential to interact with the targets active in toxicological pathways. In project III (chapter 5) a novel approach integrating the trio concept of ’computational system biology, cheminformatics and structural bioinformatics’ to predict drugs induced metabolic syndrome have been described. In project IV (chapter 6) a in silico screening protocol was established taking into the structurally similarity, pharmacophoric features and validation using computational docking studies. This approach led to the identification of novel binding site for acyclovir in the peptide binding groove of the human leukocyte antigen (HLA) specific allele.

As an important endogenous source of reactive oxygen species (ROS), NADPH oxidase 1 (Nox1) has received tremendous attention in the past few decades. It has been identified to play a key role as the initial "kindle," whose activation is crucial for amplifying ROS production through several propagation mechanisms in the vascular system. As a consequence, Nox1 has been implicated in the initiation and genesis of many cardiovascular diseases and has therefore been the subject of detailed investigations. The literature on experimental studies of the Nox1 system is extensive. Numerous investigations have identified essential features of the Nox1 system in vasculature and characterized key components, possible regulatory signals and/or signaling pathways, potential activation mechanisms, a variety of Nox1 stimuli, and its potential physiological and pathophysiological functions. While these experimental studies have greatly enhanced our understanding of the Nox1 system, many open questions remain regarding the overall functionality and dynamic behavior of Nox1 in response to specific stimuli. Such questions include the following. What are the main regulatory and/or activation mechanisms of Nox1 systems in different types of vascular cells? Once Nox1 is activated, how does the system return to its original, unstimulated state, and how will its subunits be recycled? What are the potential disassembly pathways of Nox1? Are these pathways equally important for effectively reutilizing Nox1 subunits? How does Nox1 activity change in response to dynamic signals? Are there generic features or principles within the Nox1 system that permit optimal performance? These types of questions have not been answered by experiments, and they are indeed quite difficult to address with experiments. I demonstrate in this dissertation that one can pose such questions and at least partially answer them with mathematical and computational methods. Two specific cell types, namely endothelial cells (ECs) and vascular smooth muscle cells (VSMCs), are used as "templates" to investigate distinct modes of regulation of Nox1 in different vascular cells. By using a diverse array of modeling methods and computer simulations, this research identifies different types of regulation and their distinct roles in the activation process of Nox1. In the first study, I analyze ECs stimulated by mechanical stimuli, namely shear stresses of different types. The second study uses different analytical and simulation methods to reveal generic features of alternative disassembly mechanisms of Nox1 in VSMCs. This study leads to predictions of the overall dynamic behavior of the Nox1 system in VSMCs as it responds to extracellular stimuli, such as the hormone angiotensin II. The studies and investigations presented here improve our current understanding of the Nox1 system in the vascular system and might help us to develop potential strategies for manipulation and controlling Nox1 activity, which in turn will benefit future experimental and clinical studies.