Dynamics Analysis and Prediction of Genetic Regulation in Glycerol Metabolic Network via Structural Kinetic Modelling

Glycerol can be biologically converted to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae. In the synthesis pathway of 1,3-PD, the accumulation of an intermediary metabolite 3-hydroxypropionaldehyde (3-HPA) would cause an irreversible cessation of the dynamic system. Genetic manipulation on the key enzymes which control the formation rate and consumption rate of 3-HPA would decrease the accumulation of 3-HPA, resulting in nonlinear regulation on the dynamic system. The interest of this work is to focus on analyzing the influence of 3-HPA inhibition on the stability of the dynamic system. Due to the lack of intracellular knowledge, structural kinetic modelling is applied. On the basis of statistical account of the dynamical capabilities of the system inthe parameter space,we conclude that, underweak or no inhibition to the reaction of 3-HPAconsumption, the systemismuch easier to obtain a stable state, whereas strong inhibition to its formation is in favor of stabilizing the system. In addition, the existence of Hopf bifurcation in this systemis also verified. The obtained results are helpful for deeply understanding the metabolic and genetic regulations of glycerol fermentation by Klebsiella pneumoniae

Bacterias depredadoras para ser aplicadas en procesos biotecnológicos

Tesis de la Universidad Complutense de Madrid, Facultad de Ciencias Químicas, Departamento de Bioquímica y Biología Molecular, leída el 25-04-2019As with many findings in science, the Bdellovibrio group of predatory bacteria and like organisms (Bdellovibrio and like organisms, BALOs) was discovered by serendipity (Stolp and Starr, 1963). Since they were identified, the scientific community has striven to describe their biphasic growth cycle, investigating and characterizing the predation mechanism. Prey selectivity and the ecological role of the predators in their natural niches have also been studied. Another crucial factor to be addressed involves an understanding of the genotypic and phenotypic changes giving rise to host-independent (HI) mutant development (Jurkevitch, 2006; Sockett, 2009a). Progress made in the last few decades in the field of predatory bacteria involves both classical molecular genetics and biochemical characterization, such as central metabolism and TCA cycle (Hespell et al., 1973). Analyses at system level have also been performed, including -omic techniques, such as transcriptomic and proteomic analyses (Barabote et al., 2007; Karunker et al., 2013)...Como otros muchos descubrimientos en ciencia, las bacterias depredadoras del grupo Bdellovibrio and like organisms (BALOs) fueron halladas por serendipia (Stolp and Petzold, 1962 (Stolp and Starr, 1963). Desde su descubrimiento, la comunidad científica ha invertido un esfuerzo considerable en describir su ciclo de vida bifásico, investigar y caracterizar el mecanismo de depredación y la selectividad de presa, comprender los cambios genotípicos y fenotípicos que lideran la conversión de mutantes independientes de presa (HI), así como la relevancia ecológica que presentan estos microorganismos en su nicho natural (Jurkevitch, 2007; Sockett, 2009b). De esta forma, a lo largo de los años se han realizado numerosos avances en el campo, tanto a nivel bioquímico, por ejemplo la descripción de rutas del metabolismo central como el ciclo de Krebs (Hespell et al., 1973) y nivel sistémico con la implementación de las técnicas –ómicas, como por ejemplo análisis de transcriptómica o proteómica (Barabote et al., 2007; Karunker et al., 2013)...Depto. de Bioquímica y Biología MolecularFac. de Ciencias QuímicasTRUEunpu

Genome-scale metabolic modeling of cyanbacteria: network structure, interactions, reconstruction and dynamics

2016 Fall.Includes bibliographical references.Metabolic network modeling, a field of systems biology and bioengineering, enhances the quantitative predictive understanding of cellular metabolism and thereby assists in the development of model-guided metabolic engineering strategies. Metabolic models use genome-scale network reconstructions, and combine it with mathematical methods for quantitative prediction. Metabolic system reconstructions, contain information on genes, enzymes, reactions, and metabolites, and are converted into two types of networks: (i) gene-enzyme-reaction, and (ii) reaction-metabolite. The former details the links between the genes that are known to code for metabolic enzymes, and the reaction pathways that the enzymes participate in. The latter details the chemical transformation of metabolites, step by step, into biomass and energy. The latter network is transformed into a system of equations and simulated using different methods. Prominent among these are constraint-based methods, especially Flux Balance Analysis, which utilizes linear programming tools to predict intracellular fluxes of single cells. Over the past 25 years, metabolic network modeling has had a range of applications in the fields of model-driven discovery, prediction of cellular phenotypes, analysis of biological network properties, multi-species interactions, engineering of microbes for product synthesis, and studying evolutionary processes. This thesis is concerned with the development and application of metabolic network modeling to cyanobacteria as well as E. coli. Chapter 1 is a brief survey of the past, present, and future of constraint-based modeling using flux balance analysis in systems biology. It includes discussion of (i) formulation, (ii) assumption, (iii) variety, (iv) availability, and (v) future directions in the field of constraint based modeling. Chapter 2, explores the enzyme-reaction networks of metabolic reconstructions belonging to various organisms; and finds that the distribution of the number of reactions an enzyme participates in, i.e. the enzyme-reaction distribution, is surprisingly similar. The role of this distribution in the robustness of the organism is also explored. Chapter 3, applies flux balance analysis on models of E. coli, Synechocystis sp. PCC6803, and C. reinhardtii to understand epistatic interactions between metabolic genes and pathways. We show that epistatic interactions are dependent on the environmental conditions, i.e. carbon source, carbon/oxygen ratio in E. coli, and light intensity in Synechocystis sp. PCC6803 and C. reinhardtii. Cyanobacteria are photosynthetic organisms and have great potential for metabolic engineering to produce commercially important chemicals such as biofuels, pharmaceuticals, and nutraceuticals. Chapter 4 presents our new genome scale reconstruction of the model cyanobacterium, Synechocystis sp. PCC6803, called iCJ816. This reconstruction was analyzed and compared to experimental studies, and used for predicting the capacity of the organism for (i) carbon dioxide remediation, and (ii) production of intracellular chemical species. Chapter 5 uses our new model iCJ816 for dynamic analysis under diurnal growth simulations. We discuss predictions of different optimization schemes, and present a scheme that qualitatively matches observations

Functional genomics, analysis of adaptation in and applications of models to the metabolism of engineered Escherichia coli

In order to examine the metabolism of bacteria in the genus Enterobacteriaceae tools for gene complement comparison and stoichiometric model building have been developed to take advantage of both the number of complete bacterial genome sequences currently available and the relationship between genes and metabolism. A functional genomic approach to improving knowledge of the metabolism of Escherichia coli CFT073 (a uropathogen) has been undertaken taking into account not only its genome sequence, but its close relationship to E. coli MG1655. A fresh comparison of E. coli CFT073 has been done with E. coli MG1655 to identify all those genes in CFT073 that are not present in MG1655 and may have metabolic characteristics. These genes have further been bioinformatically assessed to determine whether they might encode enzymes for the metabolism of chemicals commonly found in human urine, and one set of such genes has been experimentally confirmed to encode an L-sorbose utilisation pathway. Little experimental work has been done as yet to elucidate how bacteria adaptively respond to the introduction of heterologous metabolic genes. To investigate how bacteria respond to such DNA, genes encoding the L-sorbose utilisation and uptake operon from CFT073 have been cloned and transformed into DH5 and a selective pressure (minimal medium with L-sorbose as sole carbon source) has been applied over 100 generations of growth of this strain in serial passage to investigate the change in its behaviour. The availability of large numbers of completely sequenced genomes, along with the development of a stoichiometric metabolic model with very high coverage of E. coli metabolism (iAF1260 [1]) have made possible the analysis of the core metabolism of large numbers of bacteria to investigate gene essentiality in these bacteria. A novel way of assessing gene complement has been developed using BLAST and DiagHunter to improve reliability of gene synteny comparisons with contextual information about the genes and to extend work by others to cover all E. coli and Shigella genome sequences with available sequences on GanBank (as of 1st June 2009) in order to bioinformatically investigate essential genes in these bacteria and the heterogeneity of their metabolic networks. Further to this a metabolic model has been constructed for DH5 with an added L-sorbose pathway and for CFT073 and these models have been used to investigate behavioural changes during adaptation of bacteria to novel heterologous genes

Metabolic engineering of Corynebacterium glutamicum for the production of succinate and 2,3-butanediol

The depletion of fossil raw materials and the environmental pollution associated with their processing motivated the development of alternative methods for production of fuels and bulk chemicals. The solution offered by White Biotechnology is to produce these chemicals from biomass, a renewable resource rich in carbohydrates, using microorganisms as biocatalysts. Corynebacterium glutamicum is a well-known industrial bacterium employed for decades in the large scale production of L-amino acids. In this work, the potential of C. glutamicum as a bio-platform for the production of succinate and 2,3-butanediol was explored.(...

\u3ci\u3eIn silico\u3c/i\u3e Driven Metabolic Engineering Towards Enhancing Biofuel and Biochemical Production

The development of a secure and sustainable energy economy is likely to require the production of fuels and commodity chemicals in a renewable manner. There has been renewed interest in biological commodity chemical production recently, in particular focusing on non-edible feedstocks. The fields of metabolic engineering and synthetic biology have arisen in the past 20 years to address the challenge of chemical production from biological feedstocks. Metabolic modeling is a powerful tool for studying the metabolism of an organism and predicting the effects of metabolic engineering strategies. Various techniques have been developed for modeling cellular metabolism, with the underlying principle of mass balance driving the analysis. In this dissertation, two industrially relevant organisms were examined for their potential to produce biofuels. First, Saccharomyces cerevisiae was used to create biodiesel in the form of fatty acid ethyl esters (FAEEs) through expression of a heterologous acyl-transferase enzyme. Several genetic manipulations of lipid metabolic and / or degradation pathways were rationally chosen to enhance FAEE production, and then culture conditions were modified to enhance FAEE production further. The results were used to identify the rate-limiting step in FAEE production, and provide insight to further optimization of FAEE production. Next, Clostridium thermocellum, a cellulolytic thermophile with great potential for consolidated bioprocessing but a weakly understood metabolism, was investigated for enhanced ethanol production. To accomplish the analysis, two models were created for C. thermocellum metabolism. The core metabolic model was used with extensive fermentation data to elucidate kinetic bottlenecks hindering ethanol production. The genome scale metabolic model was constructed and tuned using extensive fermentation data as well, and the refined model was used to investigate complex cellular phenotypes with Flux Balance Analysis. The work presented within provide a platform for continued study of S. cerevisiae and C. thermocellum for the production of valuable biofuels and biochemicals

Systems analysis of minimal metabolic networks In prokaryotes

PhD Thesis in Chemical and Biological EngineeringThe complexity of living cells is staggering, as a result of billions of years of evolution through natural selection in constantly changing environments. Systems biology emerges as the preferred approach to the disentangling of this complexity by looking at living cells and their responses to environments in a holistic manner. Complete annotated sequences of genomes are now available for thousands of species of the simplest unicellular life forms known, the prokaryotes. Together with other large-scale datasets as proteomes and phenotypic screenings and a careful analysis of the literature, genome annotations allow for the reconstruction of large constraint-based models of cellular metabolism. Here, genome-scale metabolic models (GSMs) of prokaryotes are used together with other disparate large-scale datasets and literature assessments to study and predict essential components in minimal metabolic networks. A conceptual clarification is presented in a review of systems biology perspectives on minimal and simpler cells. An assessment of the biomass compositions in 71 GSMs of prokaryotes was then performed, revealing heterogeneity that impacted predictions of reaction essentiality. The integration of 33 large-scale essentiality assays with other data and literature revealed universally and conditionally essential cofactors for prokaryotes. These were used to revise predictions of essential genes and in the prediction of one biosynthetic pathway in the GSM of M. tuberculosis. Additionally, a large-scale assessment of essentiality of different metabolic subsystems was performed with 15 comparable GSMs. The results were validated with 36 large-scale experimental assays of gene essentiality. The ancestry of metabolic genes and subsystems was estimated by blasting representative genomes of all the phyla in the prokaryotic tree of life. Ancestry was correlated with essentiality in general but not with non-essentiality. Finally, a method was devised to generate minimal viable metabolic networks based on a curated and diverse universe of prokaryotic metabolic reactions. Different growth media were tested and shown to generate different networks regarding size, cofactor requirements and maximum biomass production. The results of this work are expected to contribute for fundamental investigations of core and ancestral prokaryotic metabolism and the design of modularized and controllable chassis cells.A complexidade das células vivas é surpreendente, como resultado de milhares de milhões de anos de evolução através de seleção natural em ambientes em constante mudança. A Biologia de sistemas surge como a abordagem preferencial para analisar esta complexidade por examinar as células e as suas respostas ao meio de uma forma holística. Estão hoje disponíveis sequências completas e anotadas de genomas para milhares de espécies das formas de vida unicelulares mais simples conhecidas, os procariotas. Juntamente com outros conjuntos de dados de larga escala como proteomas e triagens fenotípicas e uma análise cuidadosa da literatura, os genomas anotados permitem a reconstrução de grandes modelos do metabolismo celular baseados em restrições. Neste trabalho utilizam-se modelos metabólicos à escala genómica (GSMs) de procariotas em conjunto com outros grandes conjuntos de dados díspares e avaliações da literatura para estudar e prever componentes essenciais em redes metabólicas mínimas. Um esclarecimento conceptual é apresentado numa revisão de perspectivas da biologia de sistemas sobre células mínimas e mais simples. Segue-se uma avaliação das composições de biomassa em 71 GSMs de procariotas, revelando a heterogeneidade que afecta as previsões de essencialidade de reações. Com a integração de 33 ensaios em grande escala de essencialidade com outros dados e literatura, revelam-se cofactores essenciais universais e condicionais em procariotas. Estes foram utilizados na revisão de previsões de genes essenciais e na previsão de uma via biossintética no GSM de M. tuberculosis. Adicionalmente, foi realizada uma avaliação em larga escala de essencialidade de diferentes subsistemas metabólicos com 15 GSMs comparáveis. Os resultados foram validados com 36 ensaios experimentais de essencialidade em larga escala. A ancestralidade de genes metabólicos e subsistemas foi estimada por blast a genomas representativos de todos os filos na árvore da vida procariota. A ancestralidade revelou-se correlacionada com a essencialidade em geral, mas não com a não essencialidade. Finalmente, concebeu-se um método para gerar redes metabólicas mínimas viáveis com base num universo curado e diversificado de reações metabólicas procariotas. Diferentes meios de crescimento foram testados, mostrando-se a geração de diferentes redes em relação ao tamanho, os requisitos de cofactores e a produção de biomassa máxima. Espera-se que os resultados deste trabalho contribuam para investigações fundamentais dos metabolismos essencial e ancestral de procariotas e para o desenho de células chassis modulares e controláveis.This work was funded by FCT, the Portuguese Foundation for Science and Technology, with the grant SFRH/BD/81626/201