A complexidade de alguns sistemas biotecnológicos impossibilita seu estudo sem o uso de técnicas de programação matemática avançadas. A quantificação de fluxos metabólicos e a síntese e projeto ótimos de plantas multiproduto são problemas com esta característica, abordados na presente tese. A quantificação de fluxos metabólicos empregando balanços de marcações é representada como um problema de otimização não-linear, o qual se resolve através da minimização da diferença entre as medidas experimentais e as predições do modelo da rede metabólica. Este problema surge da necessidade de se caracterizar o metabolismo mediante a estimação das velocidades das reações bioquímicas. O modelo matemático para problemas deste tipo é composto basicamente por balanços de metabólitos e de isótopos; os primeiros são lineares, enquanto os segundos introduzem não-linearidades ao problema e, neste trabalho, são modelados mediante uma modificação da técnica de matrizes de mapeamento de átomos. Para quantificar os fluxos metabólicos considerando a existência de ótimos locais, desenvolveu-se um algoritmo branch & bound espacial, no qual a busca global é feita mediante a divisão da região de busca (branching) e a geração de seqüências de limites (bounding) que convergem para a solução global. Como estudo de caso, estimaram-se os fluxos no metabolismo central de Saccharomyces cerevisiae. Os resultados confirmam a existência de soluções locais e a necessidade de desenvolver uma estratégia de busca global; a solução global obtida apresenta semelhanças, nos fluxos centrais, com a melhor solução obtida por um algoritmo evolucionário. Quanto aos problemas de síntese e projeto de sistemas biotecnológicos multiproduto, As abordagens mais empregadas para resolve-los são a definição e dimensionamento seqüencial das operações unitárias, e a fixação dos parâmetros de dimensionamento e de estimação do tempo de operação (com valores obtidos em laboratório ou planta piloto); porém ambas abordagens fornecem soluções subótimas. Por outro lado, a solução simultânea da síntese e projeto de sistemas biotecnológicos multiproduto gera modelos misto-inteiros não-lineares (MINLP) de grande porte, devido à combinação das decisões, ligadas à existência de alternativas no processo, com as restrições não-lineares geradas dos modelos das operações. Como estudo de caso considera-se uma planta para produção de insulina, vacina para hepatite B, ativador de plasminogênio tecidual (tissue plasminogen activator) e superóxido dismutase, mediante três hospedeiros diferentes: levedura (S. cerevisiae) com expressão extra ou intracelular, Escherichia coli e células de mamíferos. O projeto deve satisfazer a meta de produção para cada produto, minimizando os custos de capital e selecionando os hospedeiros, as operações e o arranjo dos equipamentos em cada estágio. Os resultados obtidos mostram que a formulação das decisões por abordagem big-M permite resolver o modelo MINLP gerado e que a consideração de múltiplos produtos com seqüências e condições de processamento diferentes gera grande ociosidade nos equipamentos e aumenta o custo total do projeto. Para o estudo de caso observou-se que a alocação de tanques intermediários tem um efeito limitado na diminuição do custo do projeto, porém a implementação simultânea da flexibilização do scheduling, do projeto de equipamentos auxiliares e tanques intermediários permite obter projetos satisfatórios. / The complexity of biotechnological systems does not allow their study without the use of advanced mathematical programming techniques. Metabolic flux quantification and optimal synthesis and design of multiproduct plants are problems with this characteristic, and are addressed in this thesis. The metabolic flux quantification employing labeling balances is formulated as a nonlinear optimization problem that is solved by the minimization of the difference between experimental measurements and predictions of the metabolic network model. This problem is generated by the necessity of estimating the rates of biochemical reactions that characterize the metabolism. The mathematical model for this class of problems is composed by balances of metabolites and isotopes; the former are linear whereas the latter are nonlinear and, in this work, are modeled by a modification of the atom mapping matrix technique. A spatial branch & bound algorithm was developed to quantify the metabolic fluxes, that considers the existence of local optima; in this algorithm, the global search is developed by the division of the searching region (branching) and the generation of sequences of bounds (bounding) that converge to the global solution. As a case study, fluxes in central metabolism of Saccharomyces cerevisiae were estimated. The results confirm the existence of local solutions and the necessity of develop a global search strategy; the central fluxes in the obtained global solution are similar to those ones obtained by an evolutionary algorithm. To solve problems of synthesis and design of multiproduct biotechnological systems, the most employed approaches are the sequential selection and sizing of the unit operations, and the fixing of sizing and time parameters (employing values from laboratory or pilot plants); nevertheless, both approaches generate suboptimal solutions. On the other hand, the simultaneous solution of the synthesis and design of multiproduct biotechnological systems generates large size mixed-integer nonlinear models (MINLP), due to the combination of options into the processing with nonlinear constraints from the operation models. As case study, a plant for production of insulin, hepatitis B vaccine, tissue plasminogen activator and superoxide dismutase was considered, by three hosts: yeast (S. cerevisiae) with extra or intracellular expression, Escherichia coli and mammalian cells. The design must satisfy the production target for each product, minimizing the capital cost and considering the selection of hosts, the operations and the number of parallel units in each stage. The obtained results show that the formulation of decisions by the big-M approach allows the solution of the generated MINLP model and that consideration of several products with different processing sequences and conditions generates large idleness at the equipment and increases the total cost of the design. In the case study it was observed that the allocation of storage tanks has a limited effect on cost reduction, but the simultaneous implementation of flexible scheduling, design of auxiliary equipments and intermediate storage tanks allow the generation of satisfactory designs.

O 1,3-propanodiol é um composto produzido a partir da fermentação do glicerol por bactérias como a do gênero Klebsiella e que pode ser utilizado para diversas aplicações na indústria, como a produção de PTT (politrimetileno tereftalato). Esse trabalho focou na produção de 1,3-propanodiol utilizando os genes que codificam as enzimas da via retirados de uma cepa de Klebsiella previamente isolada (GLC29). Os genes foram inseridos em um plasmídeo e este em cepa hospedeira de Escherichia coli com alteração na afinidade da enzima isocitrato desidrogenase pelo seu cofator. A enzima foi modificada no genoma da bactéria e utiliza como cofator NAD em vez do NADP original. Ensaios preliminares em agitador rotativo mostraram uma melhoria de produção da cepa mutada em comparação com a Escherichia coli selvagem. Em ensaios em biorreator, variando a concentração de oxigênio dissolvido no meio, a cepa mutante apresentou uma produção 25% maior que a cepa selvagem na condição de maior produção com 5% de oxigênio dissolvido. / The 1,3-propanediol is a compound produced from glycerol fermentation by bacteria such as Klebsiella and which can be used for various applications in industry, such as the production of PTT (polytrimethylene terephthalate). This work focused on the production of 1,3-propanediol using genes encoding the enzymes of the pathway taken from a Klebsiella strain previously isolated (GLC29). The genes were inserted into a plasmid and in the host strain of Escherichia coli with changes in the affinity of the enzyme isocitrate dehydrogenase for its cofactor. The enzyme was modified in the genome of the bacteria using the cofactor NAD instead of the original NADP. Preliminary tests on shaker showed an improvement of production by the mutated strains in comparison to the wild Escherichia coli. In biorreactor cultivation, varying the concentration of dissolved oxygen in the medium, the mutant strain showed a production 25% higher than the wild type strain in the condition with 5% of dissolved oxygen.

A complexidade de alguns sistemas biotecnológicos impossibilita seu estudo sem o uso de técnicas de programação matemática avançadas. A quantificação de fluxos metabólicos e a síntese e projeto ótimos de plantas multiproduto são problemas com esta característica, abordados na presente tese. A quantificação de fluxos metabólicos empregando balanços de marcações é representada como um problema de otimização não-linear, o qual se resolve através da minimização da diferença entre as medidas experimentais e as predições do modelo da rede metabólica. Este problema surge da necessidade de se caracterizar o metabolismo mediante a estimação das velocidades das reações bioquímicas. O modelo matemático para problemas deste tipo é composto basicamente por balanços de metabólitos e de isótopos; os primeiros são lineares, enquanto os segundos introduzem não-linearidades ao problema e, neste trabalho, são modelados mediante uma modificação da técnica de matrizes de mapeamento de átomos. Para quantificar os fluxos metabólicos considerando a existência de ótimos locais, desenvolveu-se um algoritmo branch & bound espacial, no qual a busca global é feita mediante a divisão da região de busca (branching) e a geração de seqüências de limites (bounding) que convergem para a solução global. Como estudo de caso, estimaram-se os fluxos no metabolismo central de Saccharomyces cerevisiae. Os resultados confirmam a existência de soluções locais e a necessidade de desenvolver uma estratégia de busca global; a solução global obtida apresenta semelhanças, nos fluxos centrais, com a melhor solução obtida por um algoritmo evolucionário. Quanto aos problemas de síntese e projeto de sistemas biotecnológicos multiproduto, As abordagens mais empregadas para resolve-los são a definição e dimensionamento seqüencial das operações unitárias, e a fixação dos parâmetros de dimensionamento e de estimação do tempo de operação (com valores obtidos em laboratório ou planta piloto); porém ambas abordagens fornecem soluções subótimas. Por outro lado, a solução simultânea da síntese e projeto de sistemas biotecnológicos multiproduto gera modelos misto-inteiros não-lineares (MINLP) de grande porte, devido à combinação das decisões, ligadas à existência de alternativas no processo, com as restrições não-lineares geradas dos modelos das operações. Como estudo de caso considera-se uma planta para produção de insulina, vacina para hepatite B, ativador de plasminogênio tecidual (tissue plasminogen activator) e superóxido dismutase, mediante três hospedeiros diferentes: levedura (S. cerevisiae) com expressão extra ou intracelular, Escherichia coli e células de mamíferos. O projeto deve satisfazer a meta de produção para cada produto, minimizando os custos de capital e selecionando os hospedeiros, as operações e o arranjo dos equipamentos em cada estágio. Os resultados obtidos mostram que a formulação das decisões por abordagem big-M permite resolver o modelo MINLP gerado e que a consideração de múltiplos produtos com seqüências e condições de processamento diferentes gera grande ociosidade nos equipamentos e aumenta o custo total do projeto. Para o estudo de caso observou-se que a alocação de tanques intermediários tem um efeito limitado na diminuição do custo do projeto, porém a implementação simultânea da flexibilização do scheduling, do projeto de equipamentos auxiliares e tanques intermediários permite obter projetos satisfatórios. / The complexity of biotechnological systems does not allow their study without the use of advanced mathematical programming techniques. Metabolic flux quantification and optimal synthesis and design of multiproduct plants are problems with this characteristic, and are addressed in this thesis. The metabolic flux quantification employing labeling balances is formulated as a nonlinear optimization problem that is solved by the minimization of the difference between experimental measurements and predictions of the metabolic network model. This problem is generated by the necessity of estimating the rates of biochemical reactions that characterize the metabolism. The mathematical model for this class of problems is composed by balances of metabolites and isotopes; the former are linear whereas the latter are nonlinear and, in this work, are modeled by a modification of the atom mapping matrix technique. A spatial branch & bound algorithm was developed to quantify the metabolic fluxes, that considers the existence of local optima; in this algorithm, the global search is developed by the division of the searching region (branching) and the generation of sequences of bounds (bounding) that converge to the global solution. As a case study, fluxes in central metabolism of Saccharomyces cerevisiae were estimated. The results confirm the existence of local solutions and the necessity of develop a global search strategy; the central fluxes in the obtained global solution are similar to those ones obtained by an evolutionary algorithm. To solve problems of synthesis and design of multiproduct biotechnological systems, the most employed approaches are the sequential selection and sizing of the unit operations, and the fixing of sizing and time parameters (employing values from laboratory or pilot plants); nevertheless, both approaches generate suboptimal solutions. On the other hand, the simultaneous solution of the synthesis and design of multiproduct biotechnological systems generates large size mixed-integer nonlinear models (MINLP), due to the combination of options into the processing with nonlinear constraints from the operation models. As case study, a plant for production of insulin, hepatitis B vaccine, tissue plasminogen activator and superoxide dismutase was considered, by three hosts: yeast (S. cerevisiae) with extra or intracellular expression, Escherichia coli and mammalian cells. The design must satisfy the production target for each product, minimizing the capital cost and considering the selection of hosts, the operations and the number of parallel units in each stage. The obtained results show that the formulation of decisions by the big-M approach allows the solution of the generated MINLP model and that consideration of several products with different processing sequences and conditions generates large idleness at the equipment and increases the total cost of the design. In the case study it was observed that the allocation of storage tanks has a limited effect on cost reduction, but the simultaneous implementation of flexible scheduling, design of auxiliary equipments and intermediate storage tanks allow the generation of satisfactory designs.

The natural ability of filamentous fungi to synthesize, glycosylate, and secrete high levels of protein products has made them potentially attractive hosts for heterologous protein production. Advances in fungal genetics enabled the expression of several high value proteins in filamentous fungi. Particularly the genus, Aspergillus has proven to be potentially useful for the expression of eukaryotic gene products. This thesis pertains to the optimization of recombinant protein production by the fungal host, Aspergillus niger. The target recombinant protein of interest is hen egg white lysozyme (HEWL). This protein encoded in the genome resulting in relatively stable gene construct; however, it is subject to extracellular protease attack. The objective of the proposed research is the development and application of engineering methodology for the analysis and optimization of a fungal bioprocess for recombinant protein production. The underlying hypothesis is that a significant improvement of target protein productivity is achievable by using appropriate optimization techniques. To accomplish this, during the first phase of this study a statistically based experimental method was used to systematically elucidate the effect of medium components (starch, peptone, ammonium sulfate, yeast extract, and CaCl₂.2H₂O) on hen egg white lysozyme production by Aspergillus niger HEWL WT-13-16. A 2⁵⁻¹ fractional factorial design augmented with center points revealed that peptone, starch, and ammonium sulfate were the most significant factors, whereas the other medium components were not important within the levels tested. Then, the method of steepest ascent was employed to approach the proximity of optimum. This task was followed by a central composite design to develop a response surface for medium optimization. The optimum medium composition for lysozyme production was found to be: starch 34 g/L, peptone 34 g/L, ammonium sulfate 11.9 g/L, yeast extract 0.5 g/L, and CaCl₂.2H₂O 0.5 g/L. This medium was projected to produce theoretically 212 mg/L lysozyme. Using this optimized medium, an experimentally observed maximum lysozyme concentration of 209±18 mg/L verified the applied methodology. A second optimization approach was based on metabolic flux analysis (MFA). A comprehensive metabolic network comprising three intracellular compartments (cytoplasm, mitochondrion and peroxisome) was developed for Aspergillus niger. The metabolic flux network included carbohydrate and amino acid metabolism in both anabolic and catabolic reactions. According to experimental observations, the time course of fermentation was divided into five phases, each with unique physiological properties. The network was used to form a set of linear algebraic equations based on the stoichiometry of the reactions by assuming pseudo-steady state for intracellular metabolites. The metabolic flux model consists of 137 metabolites and 287 processes, of which 181 represent biochemical conversions and 106 represent transport processes between the different compartments and the extracellular environment. In addition, due to the physiological evidence some biochemical reactions considered to be active only in one direction. Linear programming was used for optimizing of the specific growth rate as the objective function in combination with 37 measured input and output fluxes of the key metabolites to evaluate corresponding intracellular flux distributions throughout the batch fermentations. The general applicability of the methodology was evaluated by establishing commonality to optimize recombinant HEWL production. The proposed model was able to predict correctly the specific growth rate, oxygen uptake rate, and carbon dioxide evolution rate with good precision. The results of the metabolic flux and sensitivity analysis were employed for medium design. Growth was biphasic; glucose was utilized initially as the carbon source and was followed by its oxidation product, gluconate, later. Logarithmic sensitivity analysis revealed that the addition of proline, alanine and glutamate benefited growth in defined media. The experimental observations and flux analysis showed that tyrosine was a potential candidate for biomass production improvement. The two amino acids, namely proline and tyrosine benefited biomass production during the initial growth phases. Glutamate and alanine were particularly important during the latter stages of the batch process. A series of growth studies were conducted with the identified amino acids added in the medium. In these preliminary nutritional experiments the contribution to growth enhancement was 46% for proline, 23% for glutamate, and 22% for tyrosine. Model predictions were further verified by conducting batch and fed-batch fermentations in a 7- liter bioreactor. The programmed addition of four amino acids (proline, glutamate, alanine, and tyrosine) according to a predetermined schedule resulted in a 44% improvement in biomass and 41% improvement in recombinant protein production. The experiments also confirmed the model prediction that extra amount of amino acids besides the identified ones would not significantly enhance biomass and the recombinant protein production. A computer-based control system was developed for the on-line monitoring and control of the major state variables (e.g., temperature, pH, and DO) during the time course of fermentation. The graphical programming environment, LabVIEW was used to acquire and integrate these variables in a supervisor computer. The temperature of the bioreactor during sterilization and fermentation was controlled using a cascade methodology. The controller parameters of the master and slave loops were determined experimentally to yield a smooth response with minimum overshoot of both the bioreactor and jacket temperatures. The program scheduled various required steps in an established order during the fermentation. This feature of the software guarantees that every necessary operation will be met. The graphical representation of the process is displayed on the screen and helps the user to follow the process and perform the required adjustments. Furthermore, different variables can be observed simultaneously and saved in text or spreadsheet files for further analysis.

The natural ability of filamentous fungi to synthesize, glycosylate, and secrete high levels of protein products has made them potentially attractive hosts for heterologous protein production. Advances in fungal genetics enabled the expression of several high value proteins in filamentous fungi. Particularly the genus, Aspergillus has proven to be potentially useful for the expression of eukaryotic gene products. This thesis pertains to the optimization of recombinant protein production by the fungal host, Aspergillus niger. The target recombinant protein of interest is hen egg white lysozyme (HEWL). This protein encoded in the genome resulting in relatively stable gene construct; however, it is subject to extracellular protease attack. The objective of the proposed research is the development and application of engineering methodology for the analysis and optimization of a fungal bioprocess for recombinant protein production. The underlying hypothesis is that a significant improvement of target protein productivity is achievable by using appropriate optimization techniques. To accomplish this, during the first phase of this study a statistically based experimental method was used to systematically elucidate the effect of medium components (starch, peptone, ammonium sulfate, yeast extract, and CaCl₂.2H₂O) on hen egg white lysozyme production by Aspergillus niger HEWL WT-13-16. A 2⁵⁻¹ fractional factorial design augmented with center points revealed that peptone, starch, and ammonium sulfate were the most significant factors, whereas the other medium components were not important within the levels tested. Then, the method of steepest ascent was employed to approach the proximity of optimum. This task was followed by a central composite design to develop a response surface for medium optimization. The optimum medium composition for lysozyme production was found to be: starch 34 g/L, peptone 34 g/L, ammonium sulfate 11.9 g/L, yeast extract 0.5 g/L, and CaCl₂.2H₂O 0.5 g/L. This medium was projected to produce theoretically 212 mg/L lysozyme. Using this optimized medium, an experimentally observed maximum lysozyme concentration of 209±18 mg/L verified the applied methodology. A second optimization approach was based on metabolic flux analysis (MFA). A comprehensive metabolic network comprising three intracellular compartments (cytoplasm, mitochondrion and peroxisome) was developed for Aspergillus niger. The metabolic flux network included carbohydrate and amino acid metabolism in both anabolic and catabolic reactions. According to experimental observations, the time course of fermentation was divided into five phases, each with unique physiological properties. The network was used to form a set of linear algebraic equations based on the stoichiometry of the reactions by assuming pseudo-steady state for intracellular metabolites. The metabolic flux model consists of 137 metabolites and 287 processes, of which 181 represent biochemical conversions and 106 represent transport processes between the different compartments and the extracellular environment. In addition, due to the physiological evidence some biochemical reactions considered to be active only in one direction. Linear programming was used for optimizing of the specific growth rate as the objective function in combination with 37 measured input and output fluxes of the key metabolites to evaluate corresponding intracellular flux distributions throughout the batch fermentations. The general applicability of the methodology was evaluated by establishing commonality to optimize recombinant HEWL production. The proposed model was able to predict correctly the specific growth rate, oxygen uptake rate, and carbon dioxide evolution rate with good precision. The results of the metabolic flux and sensitivity analysis were employed for medium design. Growth was biphasic; glucose was utilized initially as the carbon source and was followed by its oxidation product, gluconate, later. Logarithmic sensitivity analysis revealed that the addition of proline, alanine and glutamate benefited growth in defined media. The experimental observations and flux analysis showed that tyrosine was a potential candidate for biomass production improvement. The two amino acids, namely proline and tyrosine benefited biomass production during the initial growth phases. Glutamate and alanine were particularly important during the latter stages of the batch process. A series of growth studies were conducted with the identified amino acids added in the medium. In these preliminary nutritional experiments the contribution to growth enhancement was 46% for proline, 23% for glutamate, and 22% for tyrosine. Model predictions were further verified by conducting batch and fed-batch fermentations in a 7- liter bioreactor. The programmed addition of four amino acids (proline, glutamate, alanine, and tyrosine) according to a predetermined schedule resulted in a 44% improvement in biomass and 41% improvement in recombinant protein production. The experiments also confirmed the model prediction that extra amount of amino acids besides the identified ones would not significantly enhance biomass and the recombinant protein production. A computer-based control system was developed for the on-line monitoring and control of the major state variables (e.g., temperature, pH, and DO) during the time course of fermentation. The graphical programming environment, LabVIEW was used to acquire and integrate these variables in a supervisor computer. The temperature of the bioreactor during sterilization and fermentation was controlled using a cascade methodology. The controller parameters of the master and slave loops were determined experimentally to yield a smooth response with minimum overshoot of both the bioreactor and jacket temperatures. The program scheduled various required steps in an established order during the fermentation. This feature of the software guarantees that every necessary operation will be met. The graphical representation of the process is displayed on the screen and helps the user to follow the process and perform the required adjustments. Furthermore, different variables can be observed simultaneously and saved in text or spreadsheet files for further analysis.

In this work an intersection between optimization methods and animal cell culture modeling is considered. We present optimization based methods for analyzing and building models of cell culture; models that could be used when designing the environment cells are cultivated in, i.e., medium. Since both the medium and cell line considered are complex, designing a good medium is not straightforward. Developing a model of cell metabolism is a step in facilitating medium design. In order to develop a model of the metabolism the methods presented in this work make use of an underlying metabolic reaction network and extracellular measurements. External substrates and products are connected via the relevant elementary flux modes (EFMs). Modeling from EFMs is generally limited to small networks, because the number of EFMs explodes when the underlying network size increases. The aim of this work is to enable modeling with more complex networks by presenting methods that dynamically identify a subset of the EFMs. In papers A and B we consider a model consisting of the EFMs along with the flux over each mode. In paper A we present how such a model can be decided by an optimization technique named column generation. In paper B the robustness of such a model with respect to measurement errors is considered. We show that a robust version of the underlying optimization problem in paper A can be formed and column generation applied to identify EFMs dynamically. In papers C and D a kinetic macroscopic model is considered. In paper C we show how a kinetic macroscopic model can be constructed from the EFMs. This macroscopic model is created by assuming that the flux along each EFM behaves according to Michaelis-Menten type kinetics. This modeling method has the ability to capture cell behavior in varied types of media, however the size of the underlying network is a limitation. In paper D this limitation is countered by developing an approximation algorithm, that can dynamically identify EFMs for a kinetic model. / I denna avhandling betraktar vi korsningen mellan optimeringsmetoder och modellering av djurcellodling.Vi presenterar optimeringsbaserade metoder för att analysera och bygga modeller av cellkulturer. Dessa modeller kan användas vid konstruktionen av den miljö som cellerna ska odlas i, dvs, medium.Eftersom både mediet och cellinjen är komplexa är det inte okomplicerat att utforma ett bra medium. Att utveckla en modell av cellernas ämnesomsättning är ett steg för att underlätta designen av mediet. För att utveckla en modell av metabolismen kommer de metoder som används i detta arbete att utnyttja ett underliggande metaboliskt reaktions\-nätverk och extracellulära mätningar. Externa substrat och produkter är sammankopplade via de relevanta elementära metaboliska vägarna (EFM).Modellering med hjälp av EFM är i allmänhet begränsad till små nätverk eftersom antalet EFM exploderar när de underliggande nätverket ökar i storlek. Målet med detta arbete är att möjliggöra modellering med mer komplexa nätverk genom att presentera metoder som dynamiskt identifierar en delmängd av EFM. I artikel A och B betraktar vi en modell som består av EFM och ett flöde över varje EFM.I artikel A presenterar vi hur en sådan modell kan bestämmas med hjälp av en optimeringsteknik som kallas kolumngenerering.I artikel A undersöker vi hur robust en sådan modell är med avseende till mätfel. Vi visar att en robust version av det underliggande optimeringsproblemet i artikel A kan konstrueras samt att kolumngenerering kan appliceras för att identifiera EFM dynamiskt. Artikel C och D behandlar en kinetisk makroskopisk modell. Vi visar i artikel C hur en sådan modell kan konstrueras från EFM.Denna makroskopiska modell är skapad genom att anta att flödet genom varje EFM beter sig enligt Michaelis-Menten-typ av kinetik. Denna modelleringsmetod har förmågan att fånga cellernas beteende i olika typer av media, men storleken på nätverket är en begränsning.I artikel D hanterar vi denna begränsing genom att utveckla en approximationsalgoritm som identifierar EFM dynamiskt för en kinetisk modell. / <p>QC 20150827</p>

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No. of bitstreams: 1 TeseCRS.pdf: 3506039 bytes, checksum: 68f4c5fe1c6ae3672adcedf3450e2f31 (MD5) Previous issue date: 2015-08-27 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / The genus Salmonella spp. has been extensively investigated because these bacteria are important pathogens that frequently cause severe diseases and gastrointestinal infections in humans and animals. Moreover, in recent years, Salmonella has called attention due to the excellent results in the production and in vivo delivery of various substances with potential application in Vaccinology. However, there is still little information available concerning aspects of its metabolism, which hampers both the development of new attenuated strains and the large-scale production of live cells and cellular components. Thus, this work aimed to study the S. typhimurium LT2 metabolism, using traditional and innovative approaches to investigate different carbon sources as well as different bioreactor operation modes and aeration conditions (aerobic and anaerobic). Results obtained in batch and chemostat cultivations indicated that S. typhimurium metabolism differs significantly from E. coli metabolism, closely related bacteria species with regard to the central carbon metabolism. The main difference observed between these bacteria was the high level of acetate production exhibited by S. typhimurium LT2 cells, which, differently from E. coli, occurred even at the lowest dilution rate evaluated. Currently, genome scale metabolic models are important tools for better understanding the phenotypic behavior of many organisms. Therefore the model STM_v1.0 reconstructed for S. typhimurium LT2 was evaluated, comparing experimental data, obtained in chemostat cultivations, with model predictions. Since this model was derived from E. coli model, the simulated results for biomass formation were overestimated and, consequently, predicted acetate fluxes were lower than those obtained experimentally. Therefore, to obtain experimental data useful to improve the model and to reach a better comprehension of S. typhimurium metabolism, the technique of metabolic flux analysis using isotopic labeled substrate was adopted, allowing determination of the fluxes for the main pathways of central carbon metabolism of Salmonella. This analysis revealed different preferred metabolic pathways depending on the specific growth rate. At the lowest dilution rate evaluated, D = 0.24 h-1, glucose was catabolized predominantly by the pentose phosphate and glycolysis pathways, while at the dilution rate of 0.48 h-1, the major pathway of glucose oxidation was Entner-Doudoroff. In addition, a relatively high flux through the citric acid cycle at the higher dilution rate studied was observed. / Bactérias do gênero Salmonella spp. são extensivamente estudadas por serem importantes patógenos, causando frequentemente graves doenças e infecções gastrointestinais em humanos e animais. Além disso, nos últimos anos, estas bactérias vêm ganhando um destaque ainda maior na área da biotecnologia por apresentarem ótimos resultados na produção e veiculação in vivo de diversas substâncias com fins vacinais. No entanto, ainda há poucas informações a respeito de seu metabolismo, dificultando tanto o desenvolvimento de novas linhagens atenuadas, como também a produção em larga escala de células vivas e de componentes celulares. Neste sentido, este trabalho se propôs a estudar o metabolismo de S. typhimurium LT2, utilizando inicialmente abordagens tradicionais para investigar seu comportamento na presença de diferentes fontes de carbono, em diferentes modos de operação de biorreator e de aeração (aeróbias e anaeróbias). Os resultados obtidos em cultivos em batelada e em quimiostatos evidenciaram que o metabolismo da S. typhimurium difere bastante do metabolismo da E. coli, espécies consideradas semelhantes com relação ao metabolismo do carbono central. A principal diferença observada entre essas duas bactérias foi a elevada produção de acetato pelas células de S. typhimurium LT2, mesmo em baixas velocidades de crescimento nas quais este metabólito não é produzido por diversas estirpes de E. coli. Atualmente, modelos metabólicos em escala genômica são ferramentas importantes para que o comportamento do fenótipo de diversos organismos sejam melhor compreendidos. Assim, avaliou-se o modelo STM_v1.0 reconstruído para S. typhimurium LT2, comparando-se dados obtidos experimentalmente, em quimiostatos, e os preditos pelo modelo. No entanto, como este modelo foi baseado no modelo da E. coli, os resultados simulados para produção de biomassa foram superestimados e, consequentemente, os fluxos de acetato foram inferiores aos obtidos experimentalmente. Sendo assim, para se obter dados experimentais úteis para aprimorar o modelo e para uma compreensão maior do metabolismo de S. typhimurium, utilizou-se a técnica de análise dos fluxos metabólicos com substrato isotopicamente marcado, permitindo a determinação dos fluxos das principais vias do metabolismo do carbono central da bactéria em estudo. Essa análise revelou diferenças na utilização das vias metabólicas em função da velocidade específica de crescimento, sendo que na menor taxa de diluição avaliada, D = 0,24 h-1, a glicose foi predominantemente catabolizada pelas vias pentose fosfato e glicólise, enquanto na taxa de diluição de 0,48 h-1, a via principal de oxidação da glicose foi a Entner- Doudoroff. Além disso, também observou-se um fluxo relativamente maior na via do ciclo do ácido cítrico na maior taxa de diluição estudada.

Made available in DSpace on 2014-12-17T15:01:50Z (GMT). No. of bitstreams: 1 AnaKCL_TESE.pdf: 1692215 bytes, checksum: a7d6bf1b824b71e2d8f2ccfcbbe55015 (MD5) Previous issue date: 2010-04-09 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Metabolic flux analysis (MFA) is a powerful tool for analyzing cellular metabolism. In order to control the growth conditions of a specific organism, it is important to have a complete understanding of its MFA. This would allowed us to improve the processes for obtaining products of interest to human and also to understand how to manipulate the genome of a cell, allowing optimization process for genetic engineering. Streptomyces olindensis ICB20 is a promising producer of the antibiotic cosmomycin, a powerful antitumor drug. Several Brazilian researchers groups have been developing studies in order to optimize cosmomycin production in bioreactors. However, to the best of our knowledge, nothing has been done on metabolic fluxes analysis field. Therefore, the aim of this work is to identify several factors that can affect the metabolism of Streptomyces olindensis ICB20, through the metabolic flux analysis. As a result, the production of the secondary metabolite, cosmomycin, can be increased. To achieve this goal, a metabolic model was developed which simulates a distribution of internal cellular fluxes based on the knowledge of metabolic pathways, its interconnections, as well as the constraints of microorganism under study. The validity of the proposed model was verified by comparing the computational data obtained by the model with the experimental data obtained from the literature. Based on the analysis of intracellular fluxes, obtained by the model, an optimal culture medium was proposed. In addition, some key points of the metabolism of Streptomyces olindensis were identified, aiming to direct its metabolism to a greater cosmomycin production. In this sense it was found that by increasing the concentration of yeast extract, the culture medium could be optimized. Furthermore, the inhibition of the biosynthesis of fatty acids was found to be a interesting strategy for genetic manipulation. Based on the metabolic model, one of the optimized medium conditions was experimentally tested in order to demonstrate in vitro what was obtained in silico. It was found that by increasing the concentration of yeast extract in the culture medium would induce to an increase of the cosmomycin production / A an?lise de fluxos metab?licos (AFM) ? uma importante ferramenta de an?lise do metabolismo celular. O seu conhecimento ? de extrema import?ncia para entender como deve ser conduzido ?s condi??es de cultivo de um organismo, no sentido de melhorar os processos de obten??o de produtos de interesse do homem, bem como para entender como deve ser manipulado o genoma de uma c?lula possibilitando a otimiza??o do processo para engenharia gen?tica. Streptomyces olindensis ICB20 ? um promissor produtor do antibi?tico cosmomicina, uma potente droga antitumoral, sendo de extrema relev?ncia estudar os fluxos metab?licos deste micro-organismo com o prop?sito de otimizar a s?ntese deste produto do metabolismo secund?rio. V?rios grupos de pesquisa brasileiros v?m desenvolvendo estudos na tentativa de otimizar esta produ??o em biorreatores. Entretanto, nada foi realizado ainda relativo ? an?lise de fluxos metab?licos. Este trabalho teve como objetivo verificar os fatores que afetam o metabolismo de Streptomyces olindensis ICB20, atrav?s da an?lise de fluxos metab?licos de forma que possa ser aumentada a produ??o do metab?lito secund?rio, cosmomicina. Para alcan?ar esse objetivo foi desenvolvido um modelo metab?lico que simula uma distribui??o dos fluxos internos celulares com base no conhecimento das vias metab?licas, de suas interliga??es, como tamb?m das restri??es do micro-organismo em estudo. A validade do modelo proposto foi verificada atrav?s da compara??o dos dados obtidos pelo modelo com dados experimentais da literatura. A partir da an?lise dos fluxos intracelulares, obtidos pelo modelo, foi proposto um meio de cultivo ?timo, como tamb?m, identificado pontos chaves do metabolismo com o direcionando o metabolismo de Streptomyces olindensis para uma maior produ??o de cosmomicina. Nesse sentido foi verificado que o incremento na concentra??o de extrato de levedura ? uma proposta de otimiza??o do meio de cultivo e que a inibi??o da via biossint?tica de ?cidos graxos ? uma estrat?gia interessante para manipula??o gen?tica. Com o objetivo de comprovar in vitro o que foi obtido in silico foi testada uma das condi??es de otimiza??o de meio proposta pelo modelo metab?lico atrav?s de ensaios experimentais em incubador rotativo onde foi constatado que o incremento na concentra??o de extrato de levedura no meio de cultivo induziu a um aumento na produ??o de cosmomicina

This thesis is devoted to the study and application of constraint-based metabolic models. The objective was to find simple ways to handle the difficulties that arise in practice due to uncertainty (knowledge is incomplete, there is a lack of measurable variables, and those available are imprecise). With this purpose, tools have been developed to model, analyse, estimate and predict the metabolic behaviour of cells. The document is structured in three parts. First, related literature is revised and summarised. This results in a unified perspective of several methodologies that use constraint-based representations of the cell metabolism. Three outstanding methods are discussed in detail, network-based pathways analysis (NPA), metabolic flux analysis (MFA), and flux balance analysis (FBA). Four types of metabolic pathways are also compared to clarify the subtle differences among them. The second part is devoted to interval methods for constraint-based models. The first contribution is an interval approach to traditional MFA, particularly useful to estimate the metabolic fluxes under data scarcity (FS-MFA). These estimates provide insight on the internal state of cells, which determines the behaviour they exhibit at given conditions. The second contribution is a procedure for monitoring the metabolic fluxes during a cultivation process that uses FS-MFA to handle uncertainty. The third part of the document addresses the use of possibility theory. The main contribution is a possibilistic framework to (a) evaluate model and measurements consistency, and (b) perform flux estimations (Poss-MFA). It combines flexibility on the assumptions and computational efficiency. Poss-MFA is also applied to monitoring fluxes and metabolite concentrations during a cultivation, information of great use for fault-detection and control of industrial processes. Afterwards, the FBA problem is addressed. / Llaneras Estrada, F. (2011). Interval and Possibilistic Methods for Constraint-Based Metabolic Models [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10528

The supply of precursors from primary metabolism is often overlooked when engineering secondary metabolism for increased product yields. This is because precursor supply may be assumed to be non-limiting, and it is considered difficult to engineer primary metabolism, because control of carbon flow (flux) is generally distributed among most enzymes of the pathway. The aim of this thesis was to increase the production of sterols, part of the isoprenoid class of secondary metabolites, in tobacco (Nicotiana tabacum) Bright Yellow 2 (BY-2) cell cultures. This was achieved by genetically engineering increased activity of mitochondrial citrate synthase, an enzyme of the tricarboxylic acid (TCA) cycle that is involved in the provision of cytosolic acetyl coenzyme A, the primary metabolite precursor to sterols. Metabolic flux analysis revealed that citrate synthase exerts significant control over cyclic TCA cycle flux in BY-2 cells and suggested that increasing the activity of downstream enzymes within secondary metabolism could lead to a further redirection of TCA-cycle-derived precursors into sterol biosynthesis. Attempts were made to achieve this by genetically engineering increased activity of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR), a key enzyme of secondary metabolism involved in sterol biosynthesis. Consistent with previous research, transgenic lines had increased sterol levels. However, the high sterol phenotype was unstable, and attempts to co-express HMGR and citrate synthase genes were unsuccessful. The thesis demonstrates that increasing the provision of precursors to secondary metabolites can result in increased yields of those secondary metabolites but suggests that in most cases the activity of enzymes within secondary metabolism has a greater effect on those yields. It also reveals that single enzymes can exert significant control of flux within primary metabolism, although the control exerted by specific enzymes probably changes with the demands placed on metabolism.