The aim of this thesis was to explore the use of genome-scale metabolic models to predict metabolic fluxes in plant tissues. Results from this thesis showed that the application of constraint-based modelling, namely flux balance analysis, to an Arabidopsis genome-scale metabolic model gave accurate predictions of metabolic fluxes in heterotrophic cell culture and in photosynthetic leaves. Two major factors important for the accuracy of model predictions were highlighted from the study: 1) the inclusion of energetic costs for transports and cellular maintenance in terms of ATP and NADPH; 2) consideration of the interactions between light and dark metabolism in modelling photosynthetic leaves. This study began with the construction of a well-curated and compartmented genome-scale metabolic model of Arabidopsis. Using the model, cellular maintenance costs in a heterotrophic cell culture under control and two stress conditions were estimated in terms of ATP and reductant usage. The results suggested that the cells were not stressed under hyperosmotic conditions. Comparisons between model predictions and experimentally estimated flux maps showed that the inclusion of transport and maintenance costs was important for obtaining accurate model flux predictions. To model leaf metabolism over a day-night cycle, a diel modelling framework was developed which took into account the interactions between light and dark metabolism. Numerous known features of metabolism in a C₃ leaf were predicted such as the nocturnal accumulation of citrate utilised for diurnal glutamate and glutamine synthesis and the operation of an incomplete TCA cycle during the day. Using the Arabidopsis genome-scale metabolic model and the diel modelling framework, the operation of the CAM cycle was predicted as a direct consequence of blocking the CO₂ exchange with the external air during the day to simulate closure of the stomata. Comparisons between model predictions of C₃ and various subtypes of CAM leaves suggested that photon and nitrogen use efficiencies are unlikely to be the driving forces for the evolution of CAM plants under the current atmospheric CO₂ concentration. Finally, the model was utilised to predict the changes in metabolic fluxes, in particular fluxes through various routes of alternative electron flow, in a C₃ leaf with varying light intensity, nitrogen availability and at different stages of leaf development. From the model flux predictions, it was shown that constraint-based modelling can be utilised to elucidate the distinct metabolic roles of enzymes in different subcellular compartments and the tissue-specific use of distinct forms of enzymes with different coenzyme specificities.

The development of human society, which is highly dependent on fossil fuels, is now facing a range of global issues, such as rising energy prices, energy security and climate changes. To successfully tackle the resultant issues, the energy transition from fossil fuels to renewable energy sources, such as solar energy, tide energy, hydroelectric power, geothermal heat and biofuels, is under way. Biodiesel, as an important type of biofuels, has been increasingly produced from vegetable oil or used cooking oil, especially in Europe. Nevertheless, considering the high production cost of biodiesel, there is still much to be done to improve the economics of biodiesel industry. Utilisation of crude glycerol, the main by-product of the biodiesel industry, to produce value-added products appears to be a promising solution. Poly(3-hydroxybutyric acid) (PHB), a biodegradable plastic, can be converted from glycerol by Cupriavidus necator DSM 545 under unbalanced growth conditions, such as nitrogen limitation. One way to enhance the batch production of PHB is to genetically engineer the strain of C. necator, which requires insights of the dynamic impact of extracellular environment on cell phenotypes. Hence in this thesis, we aim to perform metabolic modelling based on experimental measurements to gain a better understanding of the behaviour of the metabolic network of Cupriavidus necator DSM 545 and identify potential bottlenecks of the process. Initially, C. necator DSM 545 is a strain that hardly grows on glycerol, so in a preliminary study, we investigate the process by which the strain was adapted to consume glycerol through serial subcultivation. It is found that the adaptation can be achieved within 15 cell generations over three passages in basal mineral medium, and the acquired phenotype is sufficiently stable upon further passage. The study of metabolism started with the reconstruction of the cell's metabolic network, followed by a thermodynamic analysis to check the feasibility and reversibility of all the biochemical reactions included. Then the static flux balance analysis was extended and applied to analyse the shift of metabolic states during the microbial fermentation in different batch conditions. The resulting patterns of flux distribution reveal the TCA cycle to be the major competitor for PHB synthesis at the ACCoA node. Cells have the potential to enter an efficient PHB-production phase that features minimal TCA/PHB flux split ratio, and the length of the phase can be manipulated by aeration. Although low aeration rate favours optimal flux split ratio, such condition that limits respiration also limits nutrient uptake, leading to low PHB productivity overall. To identify the actual limiting factors of PHB synthesis in the system, we further performed metabolic control analysis based on the calculated flux distributions. The analysis demonstrated how the distribution of the metabolic control can vary widely, depending on the aeration conditions used and the flux split ratios. Glycerolipid pathway, glycolysis, PHB metabolism, as well as the electron transport chain are revealed to be potential engineering targets as they contribute to the great majority of the positive control of PHB flux.

O metabolismo das células S2 (Schneider 2) de Drosophila melanogaster ainda não é totalmente conhecido. Existem poucos estudos específicos sobre o metabolismo de células S2, sejam elas selvagens ou recombinantes (rS2), como por exemplo aquelas transfectadas para a expressão da glicoproteína do vírus da raiva (GPV). Como o genoma da Drosophila melanogaster já foi mapeado, as principais enzimas que atuam nos processos metabólicos em geral já foram identificadas e estão à disposição no KEGG (Kyoto Encyclopedia of Genes and Genomes). Assim, o KEGG apresenta todas as possíveis vias metabólicas com as enzimas que podem ser codificadas. Diante deste quadro, foi proposto um modelo metabólico baseado em um conjunto de vias de assimilação de glicose e glutamina e foram encontrados os modos elementares característicos do sistema através do programa Metatool. Em seguida, foi definido o modelo matemático mediante o equacionamento desses modos elementares. Esse processo se repetiu até se encontrar um conjunto de vias metabólicas que, através da modelagem matemática, respondesse coerentemente a um conjunto de dez ensaios em diferentes condições de concentrações iniciais de glicose, glutamina e oxigênio dissolvido. Chegou-se então, a um metabolismo básico para a rS2 contendo 33 vias metabólicas englobando a glicólise, a via das pentoses, o ciclo de Krebs e a fosforilação oxidativa. Dados anteriores indicavam elevada flexibilidade metabólica dessa célula, o que foi prevista através de algumas reações propostas como reversíveis nas vias de degradação e síntese de glutamina. Essa proposta de metabolismo resultou em 37 modos elementares. Outra característica interessante da modelagem foi a utilização da produção de purinas e pirimidinas para a estimativa do crescimento celular. Depois de realizada a modelagem, as mesmas condições iniciais dos ensaios foram simuladas através de um programa de simulação do comportamento cinético das células rS2 desenvolvido em MATLAB. Esse simulador foi utilizado também para simulação com diferentes meios e condições iniciais de cultivo. Chegando-se a um ajuste geral entre valores experimentais e simulados com coeficiente de correlação de 0,88. / The metabolism of the S2 cells (Schneider 2) Drosophila melanogaster is not yet fully known. There have been few specific studies on the metabolism of S2 cells, whether recombinant or wild (rS2), such as those transfected for expressing the rabies virus glycoprotein (RVGP). As the genome of Drosophila melanogaster have been mapped, the key enzymes that act on the metabolic processes in general have been identified and are available in the KEGG (Kyoto Encyclopedia of Genes and Genomes). Thus, KEGG presents all possible pathways with the enzymes that can be encoded. Given this context, it was proposed a metabolic model based on a set metabolic glucose and glutamine assimilation pathways and were found characteristic elementary modes of the system through the Metatool program. Then the mathematical model was defined by addressing these elementary modes. This process was repeated until a set of metabolic pathways, by mathematical modelling, consistently responded to a set of ten experiments (in various conditions). We came to a basic metabolism for rS2 containing 33 pathways comprising glycolysis, pentose, Krebs cycle and oxidative phosphorylation. Previous data indicate that rS2 is a cell with high metabolic flexibility, which was confirmed by some reactions in the process proposed as reverse breakdown and synthesis of glutamine. The proposed metabolism resulted in 37 elementary modes. Another interesting model characteristic was the use of the production of purines and pyrimidines for the estimation of cell growth. After the modelling performed, the same initial runs conditions were simulated using a software of Simulation of the Kinetic behaviour of rS2 cells, developed in MATLAB. This simulator was also used for simulation of other experiments with different initial conditions and methods of cultivation. Coming to a general adjustment of experimental and simulated values with correlation coefficient of 0.88.

O metabolismo das células S2 (Schneider 2) de Drosophila melanogaster ainda não é totalmente conhecido. Existem poucos estudos específicos sobre o metabolismo de células S2, sejam elas selvagens ou recombinantes (rS2), como por exemplo aquelas transfectadas para a expressão da glicoproteína do vírus da raiva (GPV). Como o genoma da Drosophila melanogaster já foi mapeado, as principais enzimas que atuam nos processos metabólicos em geral já foram identificadas e estão à disposição no KEGG (Kyoto Encyclopedia of Genes and Genomes). Assim, o KEGG apresenta todas as possíveis vias metabólicas com as enzimas que podem ser codificadas. Diante deste quadro, foi proposto um modelo metabólico baseado em um conjunto de vias de assimilação de glicose e glutamina e foram encontrados os modos elementares característicos do sistema através do programa Metatool. Em seguida, foi definido o modelo matemático mediante o equacionamento desses modos elementares. Esse processo se repetiu até se encontrar um conjunto de vias metabólicas que, através da modelagem matemática, respondesse coerentemente a um conjunto de dez ensaios em diferentes condições de concentrações iniciais de glicose, glutamina e oxigênio dissolvido. Chegou-se então, a um metabolismo básico para a rS2 contendo 33 vias metabólicas englobando a glicólise, a via das pentoses, o ciclo de Krebs e a fosforilação oxidativa. Dados anteriores indicavam elevada flexibilidade metabólica dessa célula, o que foi prevista através de algumas reações propostas como reversíveis nas vias de degradação e síntese de glutamina. Essa proposta de metabolismo resultou em 37 modos elementares. Outra característica interessante da modelagem foi a utilização da produção de purinas e pirimidinas para a estimativa do crescimento celular. Depois de realizada a modelagem, as mesmas condições iniciais dos ensaios foram simuladas através de um programa de simulação do comportamento cinético das células rS2 desenvolvido em MATLAB. Esse simulador foi utilizado também para simulação com diferentes meios e condições iniciais de cultivo. Chegando-se a um ajuste geral entre valores experimentais e simulados com coeficiente de correlação de 0,88. / The metabolism of the S2 cells (Schneider 2) Drosophila melanogaster is not yet fully known. There have been few specific studies on the metabolism of S2 cells, whether recombinant or wild (rS2), such as those transfected for expressing the rabies virus glycoprotein (RVGP). As the genome of Drosophila melanogaster have been mapped, the key enzymes that act on the metabolic processes in general have been identified and are available in the KEGG (Kyoto Encyclopedia of Genes and Genomes). Thus, KEGG presents all possible pathways with the enzymes that can be encoded. Given this context, it was proposed a metabolic model based on a set metabolic glucose and glutamine assimilation pathways and were found characteristic elementary modes of the system through the Metatool program. Then the mathematical model was defined by addressing these elementary modes. This process was repeated until a set of metabolic pathways, by mathematical modelling, consistently responded to a set of ten experiments (in various conditions). We came to a basic metabolism for rS2 containing 33 pathways comprising glycolysis, pentose, Krebs cycle and oxidative phosphorylation. Previous data indicate that rS2 is a cell with high metabolic flexibility, which was confirmed by some reactions in the process proposed as reverse breakdown and synthesis of glutamine. The proposed metabolism resulted in 37 elementary modes. Another interesting model characteristic was the use of the production of purines and pyrimidines for the estimation of cell growth. After the modelling performed, the same initial runs conditions were simulated using a software of Simulation of the Kinetic behaviour of rS2 cells, developed in MATLAB. This simulator was also used for simulation of other experiments with different initial conditions and methods of cultivation. Coming to a general adjustment of experimental and simulated values with correlation coefficient of 0.88.

Chlamydia trachomatis (Ct) is an obligate intracellular human pathogen. It causes blinding trachoma and sexually transmitted disease such as chlamydia, pelvic inflammatory disease and lymphogranuloma venereum. Ct has a unique biphasic development cycle and replicates in an intracellular vacuole called inclusion. Normally it has two forms: the infectious form, elementary body (EB); and the non-infectious form, reticulate body (RB). Ct is not easily amenable to genetic manipulation. Hence, to understand the infection process, it is crucial to study how the metabolic activity of Ct exactly evolves in the host cell and what roles of EB and RB play differentially in Ct metabolism during infection. In addition, Ct was found regularly coinfected with other pathogens in patients who got sexually transmitted diseases (STDs). A lack of powerful methods to culture Ct outside of the host cell makes the detailed molecular mechanisms of coinfection difficult to study. In this work, a genome-scale metabolic model with 321 metabolites and 277 reactions was first reconstructed by me to study Ct metabolic adaptation in the host cell during infection. This model was calculated to yield 84 extreme pathways, and metabolic flux strength was then modelled regarding 20hpi, 40hpi and later based on a published proteomics dataset. Activities of key enzymes involved in target pathways were further validated by RT-qPCR in both HeLa229 and HUVEC cell lines. This study suggests that Ct's major active pathways involve glycolysis, gluconeogenesis, glycerolphospholipid biosynthesis and pentose phosphate pathway, while Ct's incomplete tricarboxylic acid cycle and fatty acid biosynthesis are less active. EB is more activated in almost all these carbohydrate pathways than RB. Result suggests the survival of Ct generally requires a lot of acetyl-CoA from the host. Besides, both EB and RB can utilize folate biosynthesis to generate NAD(P)H but may use different pathways depending on the demands of ATP. When more ATP is available from both host cell and Ct itself, RB is more activated by utilizing energy providing chemicals generated by enzymes associated in the nucleic acid metabolism. The forming of folate also suggests large glutamate consumption, which is supposed to be converted from glutamine by the glutamine-fructose-6-phosphate transaminase (glmS) and CTP synthase (pyrG). Then, RNA sequencing (RNA-seq) data analysis was performed by me in a coinfection study. Metatranscriptome from patient RNA-seq data provides a realistic overview. Thirteen patient samples were collected and sequenced by our collaborators. Six male samples were obtained by urethral swab, and seven female samples were collected by cervicovaginal lavage. All the samples were Neisseria gonorrhoeae (GC) positive, and half of them had coinfection with Ct. HISAT2 and Stringtie were used for transcriptomic mapping and assembly respectively, and differential expression analysis by DESeq2, Ballgown and Cuffdiff2 are parallelly processed for comparison. Although the measured transcripts were not sufficient to assemble Ct's transcriptome, the differential expression of genes in both the host and GC were analyzed by comparing Ct positive group (Ct+) against Ct-uninfected group. The results show that in the Ct+ group, the host MHC class II immune response was highly induced. Ct infection is associated with the regulation of DNA methylation, DNA double-strand damage and ubiquitination. The analysis also shows Ct infection enhances host fatty acid beta oxidation, thereby inducing mROS, and the host responds to reduce ceramide production and glycolysis. The coinfection upregulates GC's own ion transporters and amino acid uptake, while it downregulates GC's restriction and modification systems. Meanwhile, GC has the nitrosative and oxidative stress response and also increases the ability for ferric uptake especially in the Ct+ group compared to Ct-uninfected group. In conclusion, methods in bioinformatics were used here in analyzing the metabolism of Ct itself, and the responses of the host and GC respectively in a coinfection study with and without Ct. These methods provide metabolic and metatranscriptomic details to study Ct metabolism during infection and Ct associated coinfection in the human microbiota. / Chlamydia trachomatis (Ct) ist ein obligater intrazellulärer Pathogen des Menschen. Er verursacht Trachoma und sexuell übertragbare Krankheiten, wie Chlamydiose, Unterleibsentzündung und Lymphogranuloma venereum. Ct besitzt einen biphasischen Entwicklungszyklus und vermehrt sich in intrazellulären Vakuolen, sogenannten Einschlusskörperchen. Normalerweise können zwei Formen beobachtete werden: Die infektiöse Form, Elementarkörperchen (EK); und die nicht-infektiöse Form, Retikularkörperchen (RK). Ct ist nicht einfach genetisch zu manipulieren. Um den Infektionsablauf besser zu verstehen, ist es wichtig, zu untersuchen, wie sich genau die metabolische Aktivität von Ct in der Wirtszelle entwickelt und welche Rolle EK und RK im Metabolismus von Ct während der Infektion spielen. Zusätzlich wurde Ct häufig bei Patienten mit sexuell übertragbaren Krankheiten (STD) in Co-Infektion mit anderen Erregern gefunden. Ein Mangel an leistungsfähigen Methoden zur Kultivierung von Ct außerhalb der Wirtszelle macht es schwierig die genauen molekularen Mechanismen von Co-Infektionen zu untersuchen. In dieser Arbeit wurde erstmals ein genomweites metabolisches Model mit 321 Metaboliten und 277 Reaktionen aufgebaut, um die metabolische Adaption von Ct in der Wirtzelle während der Infektion zu untersuchen. Dieses Model wurde erstellt und umfasst 84 „extreme pathways“ (Grenz-Stoffwechselwege). Darauf aufbauend wurde die metabolische Fluss-Stärke berechnet. Die Zeitpunkte 20 hpi (20 Stunden nach der Infektion), 40 hpi und die anschließende Infektionsphase wurden durch Nutzung von Proteom-Daten modelliert. Die Aktivitäten von Schlüsselenzymen, welche in wichtigen Stoffwechselwegen involviert sind, wurden zusätzlich durch RT-qPCR überprüft. Dabei wurden die Ergebnisse sowohl für HeLA229- als auch HUVEC-Zellen nachgemessen. Diese Untersuchungen zeigten, dass Ct’s wichtigste aktive Stoffwechselwege die Glykolyse, die Gluconeogenese und der Pentosephosphatweg sind, während der unvollständige Zitronensäurezyklus und die Fettsäuresynthese weniger aktiv sind. Gegenüber RK sind bei EK fast alle diese Kohlenhydratwege stärker aktiviert. Im Allgemeinen benötigt Ct eine größere Menge an Acetyl-CoA. Außerdem können sowohl EK, als auch RK die Folsäurebiosynthese nutzen, um NAD(P)H zu generieren. Dabei werden möglicherweise unterschiedliche Pathways genutzt, abhängig vom Bedarf an ATP. Sobald mehr ATP sowohl durch die Wirtszellen als auch von der Ct-Zelle selbst zur Verfügung steht, wird die Nutzung von Energieträgern, produziert durch Enzyme des Nukleinsäurestoffwechsels, in RK stärker aktiviert. Die Bildung von Folsäure lässt den Schluss zu, dass große Mengen von Glutamat umgesetzt werden, welches vermutlich aus der Umwandlung von Glutamin durch die Glutamine-fructose-6-phosphate-transaminase (glmS) und CTP-Syntase (pyrG) stammt. Anschließend wurde eine Analyse von RNA-Sequenzierungsdaten (RNA-seq) aus einer Co-Infektions-Studie (Chlamydien und andere Keime, insbesondere Gonokokken (GC)) durchgeführt. Dafür wurden Proben von dreizehn Patienten gesammelt und von Kollaborationspartnern sequenziert. Sechs Proben männlicher Patienten wurden durch Abstrich der Harnröhre und sieben Proben weiblicher Patientinnen durch cervicovaginale Lavage gewonnen. Alle Proben waren Neisseria gonorrhoeae (GC) positiv, wobei die Hälfte eine Co-Infektion mit Ct aufwies. Die Programme HISAT2 and Stringtie wurden zum Abbilden der transgenomischen Reads beziehungsweise zur Assemblierung des Genoms verwendet, und eine Analyse der differentiellen Expression wurde jeweils mit DESeq2, Ballgown und Cuffdiff2 durchgeführt und die Ergebnisse verglichen. Obwohl nicht ausreichend viele Transkripte von Ct gewonnen werden konnten, um das Transkriptom komplett assemblieren zu können, wurde die differentielle Expression der Gene sowohl von Wirt als auch von GC durch den Vergleich zwischen der Gruppe der Ct-positiven (Ct+) der Gruppe der Ct-unifizierten Patienten analysiert. Die Ergebnisse zeigten, dass in der (Ct+)-Gruppe die auf der MHC-Klasse-II basierte Immunantwort stark induziert war. Die Infektion von Ct ist mit der Regulation der DNA-Methylierung, DNA-Doppel-Strang-Schädigung und Ubiquitinierung verbunden. Die Analyse zeigte zusätzlich, dass die Infektion mit Ct die Fettsäure β-Oxidation des Wirts steigert, dadurch mROS induziert, und sowohl die Ceramid-Produktion als auch die Glycolyse reduziert. Die Co-Infektion reguliert GC’s eigene Eisentransporter und Aminosäureaufnahme hoch, während Restriktions- und Modifikationssysteme herunterreguliert werden. Gleichzeitig zeigt GC sowohl eine stickstoffsensitve Stress Antwort als auch eine oxidative. Dies verstärkt zusätzlich die Fähigkeit für die Aufnahme von Eisen, insbesondere in der (Ct+)-Gruppe. Zusammenfassend wurden Methoden der Bioinformatik genutzt, um den Metabolismus von Ct selbst, und die Antwort des Wirtes respektive GC‘s in einer Co-Infektionsstudie mit und ohne Ct zu analysieren. Diese Methoden lieferten wichtige metabolische und metatranskriptomische Details, um den Metabolismus von Ct während der Infektion, aber auch das Mikrobiom während einer Ct assoziierter Co-Infektion zu untersuchen.

The present thesis is devoted to the development of models and algorithms to improve metabolic simulations of cyanobacterial metabolism. Cyanobacteria are photosynthetic bacteria of great biotechnological interest to the development of sustainable bio-based manufacturing processes. For this purpose, it is fundamental to understand metabolic behaviour of these organisms, and constraint-based metabolic modelling techniques offer a platform for analysis and assessment of cell's metabolic functionality. Reliable simulations are needed to enhance the applicability of the results, and this is the main goal of this thesis. This dissertation has been structured in three parts. The first part is devoted to introduce needed fundamentals of the disciplines that are combined in this work: metabolic modelling, cyanobacterial metabolism and multi-objective optimisation. In the second part the reconstruction and update of metabolic models of two cyanobacterial strains is addressed. These models are then used to perform metabolic simulations with the application of the classic Flux Balance Analysis (FBA) methodology. The studies conducted in this part are useful to illustrate the uses and applications of metabolic simulations for the analysis of living organisms. And at the same time they serve to identify important limitations of classic simulation techniques based on mono-objective linear optimisation that motivate the search of new strategies. Finally, in the third part a novel approach is defined based on the application of multi-objective optimisation procedures to metabolic modelling. Main steps in the definition of multi-objective problem and the description of an optimisation algorithm that ensure the applicability of the obtained results, as well as the multi-criteria analysis of the solutions are covered. The resulting tool allows the definition of non-linear objective functions and constraints, as well as the analysis of multiple Pareto-optimal solutions. It avoids some of the main drawbacks of classic methodologies, leading to more flexible simulations and more realistic results. Overall this thesis contributes to the advance in the study of cyanobacterial metabolism by means of definition of models and strategies that improve plasticity and predictive capacities of metabolic simulations. / La presente tesis está dedicada al desarrollo de modelos y algoritmos para mejorar las simulaciones metabólicas de cianobacterias. Las cianobacterias son bacterias fotosintéticas de gran interés biotecnológico para el desarrollo de bioprocesos productivos sostenibles. Para este propósito, es fundamental entender el comportamiento metabólico de estos organismos, y el modelado metabólico basado en restricciones ofrece una plataforma para el análisis y la evaluación de las funcionalidades metabólicas de las células. Se necesitan simulaciones fidedignas para aumentar la aplicabilidad de los resultados, y este es el objetivo principal de esta tesis. Esta disertación se ha estructurado en tres partes. La primera parte está dedicada a introducir los fundamentos necesarios de las disciplinas que se combinan en este trabajo: el modelado metabólico, el metabolismo de cianobacterias, y la optimización multiobjetivo. En la segunda parte, se encara la reconstrucción y la actualización de los modelos metabólicos de dos cepas de cianobacterias. Estos modelos se usan después para llevar a cabo simulaciones metabólicas con la aplicación de la metodología clásica Flux Balance Analysis (FBA). Los estudios realizados en esta parte son útiles para ilustrar los usos y aplicaciones de las simulaciones metabólicas para el análisis de los organismos vivos. Y al mismo tiempo sirven para identificar importantes limitaciones de las técnicas clásicas de simulación basadas en optimización lineal mono-objetivo que motivan la búsqueda de nuevas estrategias. Finalmente, en la tercera parte, se define una nueva aproximación basada en la aplicación al modelado metabólico de procedimientos de optimización multiobjetivo. Se cubren los principales pasos en la definición de un problema multiobjetivo y la descripción de un algoritmo de optimización que aseguren la aplicabilidad de los resultados obtenidos, así como el análisis multi-criterio de las soluciones. La herramienta resultante permite la definición de funciones objetivo y restricciones no lineales, así como el análisis de múltiples soluciones en el sentido de Pareto. Esta herramienta evita algunos de los principales inconvenientes de las metodologías clásicas, lo que lleva a obtener simulaciones más flexibles y resultados más realistas. En conjunto, esta tesis contribuye al avance en el estudio del metabolismo de cianobacterias por medio de la definición de modelos y estrategias que mejoran la plasticidad y las capacidades predictivas de las simulaciones metabólicas. / La present tesi està dedicada al desenvolupament de models i algorismes per a millorar les simulacions metabòliques de cianobacteris. Els cianobacteris són bacteris fotosintètics de gran interés biotecnològic per al desenvolupament de bioprocessos productius sostenibles. Per a aquest propòsit, és fonamental entendre el comportament metabòlic d'aquests organismes, i el modelatge metabòlic basat en restriccions ofereix una plataforma per a l'anàlisi i l'avaluació de les funcionalitats metabòliques de les cèl·lules. Es necessiten simulacions fidedignes per a augmentar l'aplicabilitat dels resultats, i aquest és l'objectiu principal d'aquesta tesi. Aquesta dissertació s'ha estructurat en tres parts. La primera part està dedicada a introduir els fonaments necessaris de les disciplines que es combinen en aquest treball: el modelatge metabòlic, el metabolisme de cianobacteris i l'optimització multiobjectiu. En la segona part, s'adreça la reconstrucció i l'actualització dels models metabòlics de dos soques de cianobacteris. Aquests models s'empren després per a portar a terme simulacions metabòliques amb l'aplicació de la metodologia clàssica Flux Balance Analysis (FBA). Els estudis realitzats en aquesta part són útils per a il·lustrar els usos i aplicacions de les simulacions metabòliques per a l'anàlisi dels organismes vius. I al mateix temps serveixen per a identificar importants limitacions de les tècniques clàssiques de simulació basades en optimització lineal mono-objectiu que motiven la cerca de noves estratègies. Finalment, en la tercera part, es defineix una nova aproximació basada en l'aplicació al modelatge metabòlic de procediments d'optimització multiobjectiu. Es cobreixen els principals passos en la definició d'un problema multiobjectiu i la descripció d'un algorisme d'optimització que asseguren l'aplicabilitat dels resultats obtinguts, així com l'anàlisi multi-criteri de les solucions. La ferramenta resultant permet la definició de funcions objectiu i restriccions no lineals, així com l'anàlisi de múltiples solucions òptimes en el sentit de Pareto. Aquesta ferramenta evita alguns dels principals inconvenients de les metodologies clàssiques, el que porta a obtenir simulacions més flexibles i resultats més realistes. En conjunt, aquesta tesi contribueix a l'avanç en l'estudi del metabolisme de cianobacteris per mitjà de la definició de models i estratègies que milloren la plasticitat i les capacitats predictives de les simulacions metabòliques. / Siurana Paula, M. (2017). Modelling and multiobjective optimization for simulation of cyanobacterial metabolism [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90578

Tomatoes are the fourth most valuable commodity in agriculture after rice, wheat and soybeans globally with 151 million tonnes of fruit being produced in 2012. The tomato fruit is also a model system for fleshy fruit development. During ethylene-regulated fruit ripening there are complex changes in fruit chemical composition due to degradation and synthesis of a number of soluble and volatile metabolites. Ultimately, these changes control the composition of the ripe fruit and dictate its flavour and texture. It is known that ripening can proceed when mature green fruit are removed from the plant (and indeed this is standard commercial practice) but the extent to which metabolic changes are sustained when fruit are ripened in this way has yet to be established. A modelling approach such as constraints-based modelling can provide system-level insights into the workings of the complex tomato metabolic network during ripening. The first aim of this thesis was therefore to construct a genome-scale metabolic network model for tomato and to use this model to explore metabolic network flux distributions during the transitions between the stages of fruit ripening. The flux distributions predicted provided insight into the production and usage of energy and reductants, into routes for climacteric CO₂ release, and the metabolic routes underlying metabolite conversions during ripening. The second aim of this thesis was to use the model to explore metabolic engineering strategies for increased production of lycopene in tomato fruit. The model predictions showed that rearrangement of dominant metabolic fluxes were required to cope with the increased demand for reductants at high lycopene accumulation, which came at a cost of a lower accumulation of other secondary metabolites. Overall the thesis provides an approach to connect underlying metabolic mechanisms to the known metabolic processes that happen during ripening.

In dieser Arbeit wurden verschiedene Ansätze verfolgt, um das Verständnis des Saccharose-zu-Stärke Stoffwechselweges in sich entwickelnden Kartoffelknollen zu untersuchen. Zunächst wurde ein induzierbares Genexpressions-System aus dem Schimmelpilz Aspergillus nidulans für die Untersuchung des Metabolismus von Kartoffelknollen optimiert. Es wurde herausgefunden, dass dieses sogenannte alc system schneller auf Acetaldehyd reagiert als auf Ethanol, und dass Acetaldehyd weniger Seiteneffekte auf den Metabolismus hat. Die optimalen Induktionsbedingungen wurden dann benutzt um die Effekte einer zeitlich kontrollierten zytosolischen Expression einer Hefe-Invertase auf den Metabolismus der Kartoffelknolle zu untersuchen. Die beobachteten Unterschiede zwischen induzierter und konstitutiver Expression der Invertase führten zu der Feststellung, dass die Glycolyse erst induziert wird nachdem ein ATP-Mangel durch erhöhtes Saccharose-Cycling kreiert wurde. Weiterhin lassen die Ergebnisse darauf schließen, dass Maltose in der Kartoffelknolle eher ein Produkt der Kondensation zweier Glucose-Einheiten ist statt ein Produkt des Stärke-Abbaus zu sein. Im zweiten Teil dieser Arbeit wurde gezeigt, dass die Expression einer Hefe-Invertase in der Vakuole von Kartoffelknollen ähnliche Effekte auf deren Metabolismus hat wie die Expression des gleichen Enzymes im Apoplasten. Diese Beobachtung ist ein weiterer Beleg für die Präsenz eines Mechanismus, bei dem Saccharose mittels Endozytose in die Vakuole aufgenommen wird anstatt über Transporter direkt ins Zytosol aufgenommen zu werden. Zum Schluß wird ein kinetisches Modell des Saccharose-Abbaus vorgestellt, das in der Lage ist diesen Teil des Stoffwechsels der Kartoffelknolle quantitativ zu simulieren. Weiterhin kann dieses Modell die metabolischen Effekte der Einführung einer Hefe-Invertase in das Zytosol von Kartoffelknollen mit erstaunlicher Präzision vorhersagen. Zusammengefasst zeigen die Ergebnisse dieser Arbeit, dass induzierbare Genexpression sowie Computermodelle von Stoffwechselwegen nützliche Hilfsmittel für eine Verbesserung des Verständnisses des Pflanzenmetabolismus sind. / In this work different approaches are undertaken to improve the understanding of the sucrose-to-starch pathway in developing potato tubers. At first an inducible gene expression system from fungal origin is optimised for the use of studying metabolism in the potato tuber. It is found that the alc system from Aspergillus nidulans responds more rapidly to acetaldehyde than ethanol, and that acetaldehyde has less side-effects on metabolism. The optimal induction conditions then are used to study the effects of temporally controlled cytosolic expression of a yeast invertase on metabolism of potato tubers. The observed differences between induced and constitutive expression of the invertase lead to the conclusion that glycolysis is induced after an ATP demand has been created by an increase in sucrose cycling. Furthermore, the data suggest that in the potato tuber maltose is a product of glucose condensation rather than starch degradation. In the second part of the work it is shown that the expression of a yeast invertase in the vacuole of potato tubers has similar effects on metabolism than the expression of the same enzyme in the apoplast. These observations give further evidence to the presence of a mechanism by which sucrose is taken up via endocytosis to the vacuole rather than via transporters directly to the cytosol. Finally, a kinetic in silico model of sucrose breakdown is presented that is able to simulate this part of potato tuber metabolism on a quantitative level. Furthermore, it can predict the metabolic effects of the introduction of a yeast invertase in the cytosol of potato tubers with an astonishing precision. In summary, these data prove that inducible gene expression and kinetic computer models of metabolic pathways are useful tools to greatly improve the understanding of plant metabolism.

Gaining a quantitative understanding of metabolic behaviour has long been a major scientific goal. Beginning with crude mass balance experiments and progressing through enzyme kinetics, single-pathway models and collaborative efforts such as a community- based yeast reconstruction and onwards to the digital human. The primary goal of this research was to generate a large-scale kinetic metabolic model of yeast metabolism. As a community our ability to produce large-scale dynamic metabolic models has typically been limited by the time and cost involved in obtaining exact measurements of all relevant kinetic parameters. Attempts have been made to bring about a greater understanding by using computational approaches such as flux balance analysis, and also laboratory approaches such as metabolic profiling. Unfortunately these approaches alone do not go far enough to allow for a rich understanding of the metabolic behaviour.Methods were developed that allowed known data such as fluxes, equilibrium constants and metabolite concentrations to be used in first-approximation strategies. These made possible the construction of a thermodynamically consistent model that was reflective of the organism and growth conditions under which the known data were measured. Efforts were made to improve the strategy by developing already known dynamic flux measurement techniques so they were more reflective of the type of data required for constructing the metabolic model. The model constructed, using data from a specific yeast strain in a continuous culture environment, and included 284 reactions. The model showed a reasonable reproduction of system behaviour after perturbations of extracellular glucose above and below the operating conditions, after identification and substitution of just two exact rate laws of reactions that showed high control over the system. The methods developed require little knowledge beyond the stoichiometric matrix in the first instance, and as such, are applicable to any organism that has a reasonably comprehensive network reconstruction available.

Approximately 10% of sequenced bacterial genomes are multipartite, consisting of two or more large chromosome-sized replicons. This genome organization can be found in many plant, animal, and human pathogens and symbionts. However, the advantage of harbouring multiple replicons remains unclear. One species with a multipartite genome is Sinorhizobium meliloti, a model rhizobium that enters into N2-fixing symbioses with various legume crops. In this work, S. meliloti derivatives lacking one or both of the secondary replicons (termed pSymA and pSymB) were constructed. Phenotypic characterization of these strains, including growth rate, metabolic capacity, and competitive fitness, provided some of the first experimental evidence that secondary replicons evolved to provide a niche specific advantage, improving fitness in a newly colonized environment. These results were further supported by characterizing the symbiotic phenotypes of 36 large-scale pSymA and pSymB deletion mutants. To further this analysis, an in silico S. meliloti genome-scale metabolic network reconstruction was developed and flux balance analysis used to examine the contribution of each replicon to fitness in three niches. These simulations were consistent with the hypothesis that metabolic pathways encoded by pSymB improve fitness specifically during growth in the plant-associated rhizosphere. Phylogenetic analysis of a pSymB region containing two essential genes provided a clean example of how a translocation from the primary chromosome to a secondary replicon can render the secondary replicon essential. Moreover, an experimental analysis of genetic redundancy indicated that 10-15% of chromosomal genes are functionally redundant with a pSymA or pSymB encoded gene, providing an alternative method for how secondary replicons can become essential and influence the evolution of the primary chromosome. Finally, the work presented here provides a novel framework for forward genetic analysis of N2-fixing symbiosis and the identification of the minimal N2-fixing symbiotic genome, which will help facilitate the development of synthetic symbioses. / Thesis / Doctor of Philosophy (PhD) / Many bacteria that enter into symbiotic or pathogenic relationships with plants, animals, and humans contain a genome that is divided into multiple chromosome-like molecules. One example is the N2-fixing legume symbiont Sinorhizobium meliloti, whose genome contains three chromosome-sized molecules. Here, the functions associated with each molecule in the S. meliloti genome were examined through a combination of experimental genetic analyses and computer based simulations. Results from these approaches suggested that adaptation to unique environments selected for the evolution of secondary chromosome-like molecules, with each predominately contributing to growth in a specific environment, including environments associated with an eukaryotic host. The genes on these replicons are therefore prime targets for manipulation of bacterium-host interactions, and represent reservoirs of valuable genes for use in synthetic biology applications. Additionally, the genome reduction approach employed in this study laid out a ground work for identification of the minimal N2-fixing symbiotic genome. This represents a crucial step towards successfully engineering improved nitrogen fixation, and the engineering of synthetic N2-fixing symbioses involving non-legumes and/or non-rhizobia.