Living organisms throughout evolution have developed desired properties, such as the ability of maintaining functionality despite changes in the environment or their inner structure, the formation of functional modules, from metabolic pathways to organs, and most essentially the capacity to adapt and evolve in a process called natural selection. It can be observed in the metabolic networks of modern organisms that many key pathways such as the citric acid cycle, glycolysis, or the biosynthesis of most amino acids are common to all of them. Understanding the evolutionary mechanisms behind this development of complex biological systems is an intriguing and important task of current research in biology as well as artificial life. Several competing hypotheses for the formation of metabolic pathways and the mecha- nisms that shape metabolic networks have been discussed in the literature, each of which finds support from comparative analysis of extant genomes. However, while being powerful tools for the investigation of metabolic evolution, these traditional methods do not allow to look back in evolution far enough to the time when metabolism had to emerge and evolve to the form we can observe today. To this end, simulation studies have been introduced to discover the principles of metabolic evolution and the sources for the emergence of metabolism prop- erties. These approaches differ considerably in the realism and explicitness of the underlying models. A difficult trade-off between realism and computational feasibility has to be made and further modeling decisions on many scales have to be taken into account, requiring the combination of knowledge from different fields such as chemistry, physics, biology and last but not least also computer science. In this thesis, a novel computational model for the in silico evolution of early metabolism is introduced. It comprises all the components on different scales to resemble a situation of evolving metabolic protocells in an RNA-world. Therefore, the model contains a minimal RNA-based genetics and an evolving metabolism of catalytic ribozymes that manipulate a rich underlying chemistry. To allow the metabolic organization to escape from the confines of the chemical space set by the initial conditions of the simulation and in general an open- ended evolution, an evolvable sequence-to-function map is used. At the heart of the metabolic subsystem is a graph-based artificial chemistry equipped with a built-in thermodynamics. The generation of the metabolic reaction network is realized as a rule-based stochastic simulation. The necessary reaction rates are calculated from the chemical graphs of the reactants on the fly. The selection procedure among the population of protocells is based on the optimal metabolic yield of the protocells, which is computed using flux balance analysis. The introduced computational model allows for profound investigations of the evolution of early metabolism and the underlying evolutionary mechanisms. One application in this thesis is the study of the formation of metabolic pathways. Therefore, four established hypothe- ses, namely the backwards evolution, forward evolution, patchwork evolution and the shell hypothesis, are discussed within the realms of this in silico evolution study. The metabolic pathways of the networks, evolved in various simulation runs, are determined and analyzed in terms of their evolutionary direction. The simulation results suggest that the seemingly mutually exclusive hypotheses may well be compatible when considering that different pro- cesses dominate different phases in the evolution of a metabolic system. Further, it is found that forward evolution shapes the metabolic network in the very early steps of evolution. In later and more complex stages, enzyme recruitment supersedes forward evolution, keeping a core set of pathways from the early phase. Backward evolution can only be observed under conditions of steady environmental change. Additionally, evolutionary history of enzymes and metabolites were studied on the network level as well as for single instances, showing a great variety of evolutionary mechanisms at work. The second major focus of the in silico evolutionary study is the emergence of complex system properties, such as robustness and modularity. To this end several techniques to analyze the metabolic systems were used. The measures for complex properties stem from the fields of graph theory, steady state analysis and neutral network theory. Some are used in general network analysis and others were developed specifically for the purpose introduced in this work. To discover potential sources for the emergence of system properties, three different evolutionary scenarios were tested and compared. The first two scenarios are the same as for the first part of the investigation, one scenario of evolution under static conditions and one incorporating a steady change in the set of ”food” molecules. A third scenario was added that also simulates a static evolution but with an increased mutation rate and regular events of horizontal gene transfer between protocells of the population. The comparison of all three scenarios with real world metabolic networks shows a significant similarity in structure and properties. Among the three scenarios, the two static evolutions yield the most robust metabolic networks, however, the networks evolved under environmental change exhibit their own strategy to a robustness more suited to their conditions. As expected from theory, horizontal gene transfer and changes in the environment seem to produce higher degrees of modularity in metabolism. Both scenarios develop rather different kinds of modularity, while horizontal gene transfer provides for more isolated modules, the modules of the second scenario are far more interconnected.

With advances in high-throughput technologies and next-generation sequencing, the amount of genomic and proteomic data is dramatically increasing in the post-genomic era. One of the biggest challenges that has arisen is the connection of sequences to their activities and the understanding of their cellular functions and interactions. In this dissertation, I present three different strategies for mining, predicting and visualizing biological functions. In the first part, I present the COMputational Bridges to Experiments (COMBREX) project, which facilitates the functional annotation of microbial proteins by leveraging the power of scientific community. The goal is to bring computational biologists and biochemists together to expand our knowledge. A database-driven web portal has been built to serve as a hub for the community. Predicted annotations will be deposited into the database and the recommendation system will guide biologists to the predictions whose experimental validation will be more beneficial to our knowledge of microbial proteins. In addition, by taking advantage of the rich content, we develop a web service to help community members enrich their genome annotations. In the second part, I focus on identifying the genes for enzyme activities that lack genetic details in the major biological databases. Protein sequences are unknown for about one-third of the characterized enzyme activities listed in the EC system, the so-called orphan enzymes. Our approach considers the similarities between enzyme activities, enabling us to deal with broad types of orphan enzymes in eukaryotes. I apply our framework to human orphan enzymes and show that we can successfully fill the knowledge gaps in the human metabolic network. In the last part, I construct a platform for visually analyzing the eco-system level metabolic network. Most microbes live in a multiple-species environment. The underlying nutrient exchange can be seen as a dynamic eco-system level metabolic network. The complexity of the network poses new visualization challenges. Using the data predicted by Computation Of Microbial Ecosystems in Time and Space (COMETS), I demonstrate that our platform is a powerful tool for investigating the interactions of the microbial community. We apply it to the exploration of a simulated microbial eco-system in the human gut. The result reflects both known knowledge and novel mutualistic interactions, such as the nutrients exchanges between E. coli, C. difficile and L. acidophilus.

Orientador: Eduardo Galembeck / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-18T00:57:48Z (GMT). No. of bitstreams: 1 Brum_ItarajuJuniorBaracuhy_M.pdf: 1893501 bytes, checksum: 59afb345a47fb8e963452a41b2327f1c (MD5) Previous issue date: 2007 / Resumo: A área de proteômica visa estudar um conjunto completo de proteínas expressas por um organismo ou tecido numa dada situação, através da identificação e quantificação. Apesar de limitações nas técnicas disponíveis, vem se aumentando o volume de informações oriundos desta área, situação que exige o emprego de ferramentas computacionais para permitir o uso eficiente de dados disponíveis, além de buscar-se novas formas de análise destes. Este projeto visa o desenvolvimento de ferramentas de bioinformática para aplicação em proteômica. Estas ferramentas abrangem as seguintes aplicações: Cálculo Teórico de Ponto Isoelétrico e Peso Molecular de seqüências de aminoácidos, eletroforese-bidimensional teórica, digestão teórica e simulação de eletroforese e identificação de peptídeos, ferramenta para análise de Vias Metabólicas a partir de dados de proteômica / Abstract: The proteomics field aims to study sets of proteins expressed in a cell or tissue, according to a specific situation, through protein identification and quantification. Though technical limitations do exist, the amount of information derived from this field increases each day. And so, there is a need for employing computational tools that enable efficient analysis of data. This project aims developing bioinformatics tools for application in proteomics. The tools here presented comprehend the following tasks: theoretical computation of isoeletric point and molecular weight of aminoacid sequences, theoretical two-dimensional electrophoresis, theoretical triptic digestion and electrophoresis simulation for peptide identification, and analysis of metabolic pathways with proteomics data / Mestrado / Bioquimica / Mestre em Biologia Funcional e Molecular

Lors de cette thèse, nous avons présenté trois principaux types d'analyses du métabolisme, dont la plupart impliquaient la symbiose : dialogue métabolique entre un trypanosomatide et son symbiote, analyses comparatives de réseaux métaboliques et exploration de données métabolomiques. Tous ont été essentiellement basés sur des données de génomique où les capacités métaboliques ont été prédites à partir des gènes annotés de l'organisme cible, et ont été affinées avec d'autres types de données en fonction de l'objectif et de la portée de chaque analyse. Le dialogue métabolique entre un trypanosomatide et son symbiote a été explorée avec des objectifs fonctionnels et évolutifs qui comprenaient une analyse des voies de synthèse des acides aminés essentiels et des vitamines telles que ces voies sont classiquement définies, une exploration de réseaux complets métaboliques et une recherche de potentiels transferts horizontaux de gènes des bactéries vers les trypanosomatides. Les analyses comparatives effectuées ont mis l'accent sur les capacités métaboliques communes de bactéries appartenant à différents groupes de vie, et nous avons proposé une méthode pour établir automatiquement les activités métaboliques communes ou spécifiques à chaque groupe. Nous avons appliqué notre méthode d'énumération d'histoires métaboliques à la réponse de la levure à une exposition au cadmium comme une validation de cette approche sur une réaction au stress bien étudiée. Nous avons montré que la méthode a bien capté la connaissance que nous avons de cette réponse en plus de permettre de nouvelles interprétations des données métabolomiques mappées sur le réseau métabolique complet de la levure / In this thesis, we presented three main types of analyses of metabolism, most of which involved symbiosis: metabolic dialogue between a trypanosomatid and its symbiont, comparative analyses of metabolic networks and exploration of metabolomics data. All of them were essentially based on genomics data where metabolic capabilities were predicted from the annotated genes of the target organism, and were further refined with other types of data depending on the aim and scope of each investigation. The metabolic dialogue between a trypanosomatid and its symbiont was explored with functional and evolutionary goals which included analysing the classically defined pathways for the synthesis of essential amino acids and vitamins, exploring the genome-scale metabolic networks and searching for potential horizontal gene transfers from bacteria to the trypanosomatids. The comparative analyses performed focused on the common metabolic capabilities of different lifestyle groups of bacteria and we proposed a method to automatically establish the common and the group-specific activities. The application of our method on metabolic stories enumeration to the yeast response to cadmium exposure was a validation of this approach on a well-studied biological response to stress. We showed that the method captured well the underlying knowledge as it extracted stories allowing for further interpretations of the metabolomics data mapped into the genome-scale metabolic model of yeast

L'appareil respiratoire des porcs est colonisé par plusieurs bactéries, parmi lesquelles trois espèces de mycoplasmes : Mycoplasma flocculare, Mycoplasma hyopneumoniae et Mycoplasma hyorhinis. Lors de ce doctorat, notre principal objectif était de mieux comprendre le métabolisme différentiel dans chacune des espèces à l'aide de différentes approches. Nous avons reconstruit les réseaux métaboliques complets pour toutes les souches séquencées de ces trois espèces de mycoplasmes afin d'y détecter des caractéristiques distinctes. Nous avons pu montrer que, bien que les trois espèces de mycoplasmes du porc ont des capacités métaboliques semblables, certaines différences existent qui incluent, d'une part, le catabolisme de myo-inositol et un système plus complet pour l'absorption du glycérol, et d'autre part, une large gamme de moyens d'absorption de carbohydrates chez M. hyorhinis. L'utilisation de glycérol comme source de carbone, une activité qui est absente uniquement dans M. flocculare, produit du peroxyde d'hydrogène qui est toxique, ce qui peut expliquer l'absence de pathogénicité de cette espèce. L'absorption d'un plus large éventail de sources de carbone chez M. hyorhinis peut également expliquer pourquoi cette espèce est un contaminant largement connu des cultures cellulaires. Des expériences de croissance ont montré que les milieux définis décrits pour d'autres espèces de mycoplasmes ne sont pas appropriés pour la croissance de mycoplasmes du tractues respiratoire de porcs, et que la peptone est essentielle pour le maintien de la viabilité des cellules à la fois de M. hyopneumoniae et de M. flocculare dans des milieux définis. Dans ce travail, nous proposons également de nouveaux média définis qui, in silico, sont extrêmement appropriés pour les mycoplasmes du porc. Les données de métabolomique suggèrent que même si ces espèces sont extrêmement similaires du point de vue de leurs génomes et des métabolismes, les produits et les taux de réaction diffèrent et la régulation des gènes peuvent interférer directement dans le métabolisme. Pour expliquer ces différences ainsi que d'autres décrits dans la littérature qui suggèrent que certains types de régulation de l'expression du gène existent en effet dans ces espèces, nous avons également essayé de recueillir des informations sur de nouvelles séquences promotrices. Ainsi, cette thèse servira de base pour l'étude du métabolisme différentiel et des pathologies causées par les mycoplasmes du tractus respiratoire du porc et pourra aider à proposer des façons de prévenir à l'avenir le développement des maladies associées / In this PhD thesis, we presented three main types of analyses of metabolism, and in most cases involving symbiosis: metabolic dialogue between a trypanosomatid and its symbiont, comparative analyses of metabolic networks and exploration of metabolomics data. The respiratory tract of swines is colonized by several pathogenic bacteria, among which are three mycoplasma species: Mycoplasma flocculare, Mycoplasma hyopneumoniae, and Mycoplasma hyorhinis. In this work, we created whole-genome metabolic network reconstructions for all sequenced strains from these three Mycoplasma species. Similar to other Mycoplasma models all reconstructed networks exhibit low connectivity due to the simplicity of the biological model. We were able to show that the three swine mycoplasma species have similar metabolic capabilities. Interesting metabolic differences include the myo-inositol catabolism and a more complete system for glycerol uptake in M. hyopneumoniae and a wide range of carbohydrate uptake in M. hyorhinis. Glycerol conversion to DHAP, a missing activity only in M. flocculare, produces toxic hydrogen peroxide and may explain the lack of pathogenicity of this species. The uptake of a wider range of carbon sources in M. hyorhinis may also explain why this species is a wide-known contaminant in cell cultures. Growth experiments showed that defined media described for other Mycoplasma species are not suitable for the growth of respiratory tract swine mycoplasmas and that peptone is essential for the maintenance of cell viability of both M. hyopneumoniae and M. flocculare in defined media. Metabolomic data suggests that even though these species are extremely similar from a genomic and metabolic point of views, the products and reaction rates differ and gene regulation may interfere directly in metabolism. This, in turn, may account for many aspects still unknown that influence directly different levels of pathogenicity in each of them

The central vertices in complex networks are of particular interest because they might play the role of organizational hubs. Here, we consider three different geometric centrality measures, excentricity, status, and centroid value, that were originally used in the context of resource placement problems. We show that these quantities lead to useful descriptions of the centers of biological networks which often, but not always, correlate with a purely local notion of centrality such as the vertex degree. We introduce the notion of local centers as local optima of a centrality value “landscape” on a network and discuss briefly their role.

As stoichiometric metabolic models increase in complexity and delity, design and reconstruction tools are urgently needed to increase the productivity of this time-consuming process. Engineers require software for the exploration, evaluation, and rapid analysis of model alternatives within an intuitive visualization and data management framework. This thesis introduces such a tool: Pathway Pioneer (www.pathwaypioneer.org), a web based system built as a front-end graphical user interface to the ux balance analysis tool COBRA. Pathway Pioneer adds additional functionality for customized network layout and model-engineering collaboration through shared models and model version control. Pathway Pioneer is a dynamic, clickable, browser-based visualization system for metabolic network models retrieved from databases such as BiGG or developed in-house as SBML or XLS compliant les. The user can customize the network layout to visually organize the metabolites and reactions into functional modules. The tool supports zooming and panning, level-of-detail control, ux visualization, keyword searching, and hierarchical subsystem organization. A reaction may be knocked out, set as an objective, looked up in a database or many other operations by a single click on the visualized network. Following each operation the visualization is refreshed with the new ux values. The system supports model revision control to manage alternative network congurations and supports sharing of models and layouts to the broader community. By moving the computationally intensive model analysis from the user computer to remote servers, Pathway Pioneer enables the application of high performance cloud-based resources for greater eciency and scalability. I demonstrate the utility of Pathway Pioneer through application in model reconstruction and analysis of many standard models and also two new models under development: Eukaryotic multicompartment Chinese Hamster Ovary (Cho) cells and in a large-scale Escherichia coli system for bio-manufacturing.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18405号 / 情博第520号 / 新制||情||92(附属図書館) / 31263 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 阿久津 達也, 教授 山本 章博, 教授 永持 仁 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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Mathematical modeling of biological systems is a powerful tool to systematically investigate the functions of biological processes and their relationship with the environment. To obtain accurate and biologically interpretable predictions, a modeling framework has to be devised whose assumptions best approximate the examined scenario and which copes with the trade-off of complexity of the underlying mathematical description: with attention to detail or high coverage. Correspondingly, the system can be examined in detail on a smaller scale or in a simplified manner on a larger scale. In this thesis, the role of photosynthesis and its related biochemical processes in the context of plant metabolism was dissected by employing modeling approaches ranging from kinetic to stoichiometric models. The Calvin-Benson cycle, as primary pathway of carbon fixation in C3 plants, is the initial step for producing starch and sucrose, necessary for plant growth. Based on an integrative analysis for model ranking applied on the largest compendium of (kinetic) models for the Calvin-Benson cycle, those suitable for development of metabolic engineering strategies were identified. Driven by the question why starch rather than sucrose is the predominant transitory carbon storage in higher plants, the metabolic costs for their synthesis were examined. The incorporation of the maintenance costs for the involved enzymes provided a model-based support for the preference of starch as transitory carbon storage, by only exploiting the stoichiometry of synthesis pathways. Many photosynthetic organisms have to cope with processes which compete with carbon fixation, such as photorespiration whose impact on plant metabolism is still controversial. A systematic model-oriented review provided a detailed assessment for the role of this pathway in inhibiting the rate of carbon fixation, bridging carbon and nitrogen metabolism, shaping the C1 metabolism, and influencing redox signal transduction. The demand of understanding photosynthesis in its metabolic context calls for the examination of the related processes of the primary carbon metabolism. To this end, the Arabidopsis core model was assembled via a bottom-up approach. This large-scale model can be used to simulate photoautotrophic biomass production, as an indicator for plant growth, under so-called optimal, carbon-limiting and nitrogen-limiting growth conditions. Finally, the introduced model was employed to investigate the effects of the environment, in particular, nitrogen, carbon and energy sources, on the metabolic behavior. This resulted in a purely stoichiometry-based explanation for the experimental evidence for preferred simultaneous acquisition of nitrogen in both forms, as nitrate and ammonium, for optimal growth in various plant species. The findings presented in this thesis provide new insights into plant system's behavior, further support existing opinions for which mounting experimental evidences arise, and posit novel hypotheses for further directed large-scale experiments. / Mathematische Modellierung biologischer Systeme eröffnet die Möglichkeit systematisch die Funktionsweise biologischer Prozesse und ihrer Wechselwirkungen mit der Umgebung zu untersuchen. Um präzise und biologisch relevante Vorhersagen treffen zu können, muss eine Modellierungsstrategie konzipiert werden, deren Annahmen das untersuchte Szenario bestmöglichst widerspiegelt und die dem Trade-off der Komplexität der zugrunde liegenden mathematischen Beschreibung gerecht wird: Detailtreue gegenüber Größe. Dementsprechend kann das System detailliert, in kleinerem Umfang oder in vereinfachter Darstellung im größeren Maßstab untersucht werden. In dieser Arbeit wird mittels verschiedener Modellierungsansätze, wie kinetischen und stöchiometrischen Modellen, die Rolle der Photosynthese und damit zusammenhängender biochemischer Prozesse im Rahmen des Pflanzenstoffwechsels analysiert. Der Calvin-Benson-Zyklus, als primärer Stoffwechselweg der Kohlenstofffixierung in C3-Pflanzen, ist der erste Schritt der Stärke- und Saccharoseproduktion, welche maßgeblich für das Wachstum von Pflanzen sind. Basierend auf einer integrativen Analyse zur Modellklassifizierung wurden aus der größten bekannten Sammlung von (kinetischen) Modellen des Calvin-Benson-Zyklus diejenigen ermittelt, die für die Entwicklung von Metabolic-Engineering-Strategien geeignet sind. Angeregt von der Fragestellung warum Kohlenstoff transitorisch vorwiegend in Form von Stärke anstatt Saccharose gespeichert wird, wurden die metabolischen Kosten beider Syntheseprozesse genauer betrachtet. Die Einbeziehung der Bereitstellungskosten der beteiligten Enzyme stützt die Tatsache, dass bevorzugt Stärke als temporärer Kohlenstoffspeicher dient. Die entprechende Untersuchung erfolgte einzig auf Grundlage der Stöchiometrie der Synthesewege. In vielen photosynthetisch-aktiven Organismen findet zudem Photorespiration statt, die der Kohlenstofffixierung entgegenwirkt. Die genaue Bedeutung der Photorespiration für den Pflanzenmetabolismus ist noch umstritten. Eine detaillierte Einschätzung der Rolle dieses Stoffwechselweges bezüglich der Inhibierung der Kohlenstofffixierungsrate, der Verknüpfung von Kohlenstoff- und Stickstoffmetabolismus, der Ausprägung des C1-Stoffwechsels sowie die Einflussnahme auf die Signaltransduktion wurde in einer modell-basierten, kritischen Analyse vorgenommen. Um die Photosynthese in ihrem metabolischen Kontext verstehen zu können, ist die Betrachtung der angrenzenden Prozesse des primären Kohlenstoffmetabolismus unverzichtbar. Hierzu wurde in einem Bottom-up Ansatz das Arabidopsis core Modell entworfen, mittels dessen die Biomasseproduktion, als Indikator für Pflanzenwachtum, unter photoautotrophen Bedingungen simuliert werden kann. Neben sogenannten optimalen Wachstumsbedingungen kann dieses großangelegte Modell auch kohlenstoff- und stickstofflimitierende Umweltbedingungen simulieren. Abschließend wurde das vorgestellte Modell zur Untersuchung von Umwelteinflüssen auf das Stoffwechselverhalten herangezogen, im speziellen verschiedene Stickstoff-, Kohlenstoff- und Energiequellen. Diese auschließlich auf der Stöchiometrie basierende Analyse bietet eine Erklärung für die bevorzugte, gleichzeitige Aufnahme von Nitrat und Ammonium, wie sie in verschiedenen Spezies für optimales Wachstum experimentell beobachtet wurde. Die Resultate dieser Arbeit liefern neue Einsichten in das Verhalten von pflanzlichen Systemen, stützen existierende Ansichten, für die zunehmend experimentelle Hinweise vorhanden sind, und postulieren neue Hypothesen für weiterführende großangelegte Experimente.