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Lisowska, Beata. "Genomic analysis and metabolic modelling of Geobacillus thermoglucosidasius NCIMB 11955." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690738.
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Geobacillus thermoglucosidasius is a Gram-positive thermophilic eubacterium (45-70‰) that has the ability to convert pre-treated lignocellulosic material LCM into ethanol. This organism has been genetically engineered such that its yield of ethanol production is in excess of 90% of the theoretical maximum [38]. There remains considerable scope to develop G.thermoglucosidasius to produce alternative fuels and chemicals of industrial importance. For such a useful bacterium the understanding of the global metabolism remains poorly characterised. To gain a better insight into the metabolic pathways and capabilities of G. thermoglucosidasius a bottom-up approach to construct a comprehensive metabolic model of the organism was applied. The model was build from manually annotated genome and incorporates data from wet lab experiments for accurate in silico analyses. The model simulations has highlighted a potential experimental design for the in silico production of succinate and butane-2,3-diol. PathwayBooster is also introduced in this study as a tool for curating metabolic pathways. The methodology is based on the assumption that the core metabolic capabilities are shared among evolutionarily closely related species [80]. This approach led to the further analysis of members of the genus Geobacillus with respect to their core metabolic capabilities, genome re-arrangements and shared unique features. Theoretical route for the biosynthesis of Vitamin B12 is presented here, which is novel to the canonical aerobic and anaerobic pathways known to date and ubiquitous amongst Geobacillus spp. The analysis of the gene assignment for this bacterium has highlighted the presence of NADP-dependent GAPDH. The theoretical function of this novel and previously uncategorised enzyme in the genus Geobacillus has been confirmed through enzymatic assays.
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Williams, H. E. "Mathematical modelling of metabolic pathways in pig muscle." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/42536/.
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Improving efficiency within the agricultural industry is vital to maintain the food demands of the increasing population, as well the current preference for a more protein rich diet. One avenue for addressing these issues is to study animal-based growth to determine if the efficiency of the production system can be improved by increasing lean muscle mass. The aim of this thesis is to provide an alternative exploration to experimental work to provide an insight into how muscle metabolism in pigs is altered by the administration of a beta-agonist which induces muscle hypertrophy. This will be incorporated into a wider body of work to determine specific pathways to target for improving feed conversion efficiency, contributing to the necessary research into global food security. We begin by compiling a selection of statistical methods to analyse muscle microarray data, which enables the identification of a selection of genes whose expressions are altered by the exposure to a beta-agonist. These differentially expressed transcripts are then grouped via a k-means algorithm, with log likelihood and the Bayesian Inference Criterion calculations providing an optimal selection of clusters. This results in selecting a group of 51 transcripts and partitioning them into 9 clusters, and identifying several pathways which appear key to the regulation of muscle metabolism in the presence of beta-agonist. We have proceeded to incorporate this information into a mathematical model for glycolysis and the TCA cycle, in an effort to analyse biological hypotheses about how the promoters work. The equations describe the concentrations of metabolites within the cytosolic and mitochondrial compartments of a cell using mass balance ODEs. An initial model is presented, which is then increased in complexity, to keep up with developments in the experimental side of the overarching project. We make use of a selection of methods to analyse the model in an attempt to determine the effects that the different parameters cause. Through steady state analysis, we determine parameter ranges which permit positive steady states. In finding these regions, we also determine the existence of time dependent solutions, which occur when critical values of certain parameters are exceeded, and result in the build up of specific metabolites. We use asymptotic analysis to generate approximate solutions when steady states do not exist. The model parameters of most interest are those which were identified through the microarray work, namely the upregulated transcripts of PCK2 and those within the serine synthesis pathway, the control mechanism for the first half of the TCA cycle, the proportion of GTP producing enzyme from the second half of the TCA cycle, and the flux into the glycolytic pathway. We find that critical values for the glycolytic flux, and the GTP production parameter exist, determining whether the model lies within the steady state regime. In a large number of cases, the parameters we choose to represent the beta-agonist case push the system into the time dependent state. The model does not exhibit any interesting behaviour when the parameter controlling the PCK2 pathway is studied, indicating that initial intuition of the key controlling reaction mechanisms were incomplete. Whilst there are shortfalls in the model, which highlight areas for investigation, the system is set up for validation and parameter fitting when appropriate experimental data become available. We have been able to determine specific metabolic pathways within the cell which may be of significance to improving feed efficiency.
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Sakakibara, Norikazu. "Metabolic analysis of the cinnamate/monolignol and lignan pathways." Kyoto University, 2005. http://hdl.handle.net/2433/145058.
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Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(農学)<br>甲第11658号<br>農博第1514号<br>新制||農||911(附属図書館)<br>学位論文||H17||N4051(農学部図書室)<br>23301<br>UT51-2005-D407<br>京都大学大学院農学研究科応用生命科学専攻<br>(主査)教授 島田 幹夫, 教授 關谷 次郎, 教授 坂田 完三<br>学位規則第4条第1項該当
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Jaques, Colin Mark. "Modelling of metabolic pathways for Saccharopolyspora erythraea using flux balance analysis." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446668/.
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The objective of this thesis is to use metabolic modelling techniques to investigate primary and secondary metabolism in S. erythraea and from this to identify key factors controlling flux distribution during secondary metabolism. S. erythraea is a member of the actinomycetes a group of bacteria responsible for the production of a number of commercially important small molecules. Actinomycete physiology is considerably more complicated than that seen in "simple" bacteria such as E. coli. The conjecture investigated in this thesis is that metabolic modelling techniques that take into account this extra complexity should be more useful in designing strategies for overproduction of desired metabolites than simpler models. The thesis gives the first detailed description of the dynamic changes in biomass composition seen during the batch cultivation of S. erythraea. It further shows that incorporation of this information into a flux balance model of the organism's metabolism significantly improves the flux distributions generated especially in the stationary phase. Using this improved technique growth phase and stationary phase metabolism are investigated. Some of the unusual stationary phase behaviour is shown to be the result of glucose uptake being independent of demand. Rigid control of branch points in the metabolic network is not found suggesting that the organism's metabolism is flexible. A reverse metabolic engineering strategy is applied, two variants of the wild type organism are compared with an industrial strain. The industrial strain is found to have a considerably lower glucose uptake rate than the parental strain. The relationship between TCA cycle flux, oxidative phosphorylation and organic acid secretion is investigated using an uncoupler. This project demonstrates that applied correctly flux balance analysis is a powerful tool for investigating actinomycete physiology. The insights gained are of direct relevance to the commercial production of secondary metabolites in S. erythraea.
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Goel, Gautam. "Dynamic flux estimation a novel framework for metabolic pathway analysis /." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31769.
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Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Voit, Eberhard O.; Committee Member: Butera, Robert; Committee Member: Chen, Rachel; Committee Member: Kemp, Melissa; Committee Member: Neves, Ana Rute. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Cunha, Oberdam de Lima. "SAMPA (System for Comparative Analysis of Metabolic PAthways) - uma comparação de vias metabólicas." Laboratório Nacional de Computação Científica, 2008. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=161.
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Com o advento das tecnologias que propiciaram os seqüenciamentos e as análises de genomas completos em tempo relativamente curto, muitos dados sobre vias metabólicas de procariotos e eucariotos puderam ser gerados. Análises comparativas de vias metabólicas de diferentes genomas podem auxiliar no entendimento das relações organizacionais dentre e fora das espécies. Com base em tais perspectivas, este trabalho tem como finalidade implementar um sistema que permita comparar, através de diferentes critérios, vias metabólicas de bactérias.
O sistema SAMPA (System for comparative Analysis of Metabolic PAthways) é composto por um banco de dados, com informações sobre vias metabólicas de diversos organismos, e um conjunto de 5 ferramentas utilizadas para comparar estas vias metabólicas e agrupar os organismos que possuam vias metabólicas relacionadas. Como estudo de caso para teste da ferramenta, foi utilizada a família Mycoplasmataceae.<br>The advent of genome sequencing technology and complete genome analysis has provided new data on prokaryote and eukaryote metabolic pathways. The comparative analysis of metabolic pathways from different organisms can help us understand inter and intra species organizational relationships. Having this in mind, this work focused on building a system that allows for comparing the bacterial metabolic pathways, according to a set of pre-established criteria.
SAMPA (System for comparative Analysis of Metabolic PAthways) comprises a database containing information on metabolic pathways in many organisms, and a set of five tools that can be used to compare these metabolic pathways and to group organisms carrying metabolic pathways that are related. As a case study to validate the tool, we the Mycoplasmataceae family of organisms was used.
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Antoniewicz, Maciek Robert. "Comprehensive analysis of metabolic pathways through the combined use of multiple isotopic tracers." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37457.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2006.<br>Includes bibliographical references (p. 287-294).<br>Metabolic Flux Analysis (MFA) has emerged as a tool of great significance for metabolic engineering and the analysis of human metabolic diseases. An important limitation of MFA, as carried out via stable isotope labeling and GC/MS measurements, is the large number of isotopomer equations that need to be solved. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of complex biological networks. Here, we present a novel framework for modeling isotopic distributions that significantly reduces the number of system variables without any loss of information. The elementary metabolite units (EMU) framework is based on a highly efficient decomposition algorithm identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using knowledge of atomic transitions occurring in the network reactions. The developed computational and experimental methodologies were applied to two biological systems of major industrial and medical significance. First, we describe the analysis of metabolic fluxes in E. coli in a fed-batch fermentation for overproduction of 1,3-propanediol (PDO).<br>(cont.) A dynamic 13C-labeling experiment was performed and nonstationary intracellular fluxes (with confidence intervals) were determined by fitting labeling patterns of 191 cellular amino acids and 8 external fluxes to a detailed network model of E. coli. We established for the first time detailed time profiles of in vivo fluxes. Flux results confirmed the genotype of the organism and provided further insight into the physiology of PDO overproduction in E. coli. Second, we describe the analysis of metabolic fluxes in the pathway of gluconeogenesis in cultured primary hepatocytes, i.e. isolated liver cells. We applied multiple 13C and 2H-labeled tracers and measured isotopomer distributions of glucose fragments. From this overdetermined data set we estimated net and exchange fluxes in the gluconeogenesis pathway. We identified limitations in current methods to estimate gluconeogenesis in vivo, and developed a novel [U-13C,2Hs]glycerol method that allows accurate analysis of gluconeogenesis fluxes independent of the assumption of isotopic steady-state and zonation of tracers. The developed methodologies have wide implications for in vivo studies of glucose metabolism in Type II diabetes, and other metabolic diseases.<br>by Maciek Robert Antoniewicz.<br>Ph.D.
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Beltrame, L. "Indentification of disregulated metabolic pathways by transcriptomic analysis in renal cell carcinoma samples." Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/44738.
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Microarray analysis, with its ability of simultaneously assessing the expression of thousands of genes, has always attracted interest in cancer research. However, traditional microarray studies suffer from many shortcomings, which result often in poor reproducibility of the studies. Recently, a new approach called group testing, targeting deregulated groups of genes (such as pathways) rather than single entities, has been proposed. This work focuses on the use of group testing techniques towards the identification of deregulated pathways in renal cell carcinoma over three publicly available microarray data sets, compared to more estabilished methods.
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Henderson, David Allen. "Reconstruction of metabolic pathways by the exploration of gene expression data with factor analysis." Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/30089.
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Microarray gene expression data for thousands of genes in many organisms is quickly becoming available. The information this data can provide the experimental biologist is powerful. This data may provide information clarifying the regulatory linkages between genes within a single metabolic pathway, or alternative pathway routes under different environmental conditions, or provide information leading to the identification of genes for selection in animal and plant genetic improvement programs or targets for drug therapy. Many analysis methods to unlock this information have been both proposed and utilized, but not evaluated under known conditions (e.g. simulations). Within this dissertation, an analysis method is proposed and evaluated for identifying independent and linked metabolic pathways and compared to a popular analysis method. Also, this same analysis method is investigated for its ability to identify regulatory linkages within a single metabolic pathway. Lastly, a variant of this same method is used to analyze time series microarray data.
In Chapter 2, Factor Analysis is shown to identify and group genes according to membership within independent metabolic pathways for steady state microarray gene expression data. There were cases, however, where the allocation of all genes to a pathway was not complete. A competing analysis method, Hierarchical Clustering, was shown to perform poorly when negatively correlated genes are assumed unrelated, but performance improved when the sign of the correlation coefficient was ignored.
In Chapter 3, Factor Analysis is shown to identify regulatory relationships between genes within a single metabolic pathway. These relationships can be explained using metabolic control analysis, along with external knowledge of the pathway structure and activation and inhibition of transcription regulation. In this chapter, it is also shown why factor analysis can group genes by metabolic pathway using metabolic control analysis.
In Chapter 4, a Bayesian exploratory factor analysis is developed and used to analyze microarray gene expression data. This Bayesian model differs from a previous implementation in that it is purely exploratory and can be used with vague or uninformative priors. Additionally, 95% highest posterior density regions can be calculated for each factor loading to aid in interpretation of factor loadings. A correlated Bayesian exploratory factor analysis model is also developed in this chapter for application to time series microarray gene expression data. While this method is appropriate for the analysis of correlated observation vectors, it fails to group genes by metabolic pathway for simulated time series data.<br>Ph. D.
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Zychlinski-Kleffmann, Anne Kathrin von. "Rice etioplast proteome analysis: Novel insights into the complexity of metabolic and regulatory pathways /." Zürich : ETH, 2005. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=16120.
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Sander, Guy William. "Quantitative analysis of metabolic pathways in Catharanthus roseus hairy roots metabolically engineered for terpenoid indole alkaloid overproduction." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3369886.
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Mahout, Maxime. "Logic programming tools for metabolic fluxes analysis and biological applications." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG086.
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En biologie des systèmes, l'analyse des voies métaboliques est une méthode essentielle pour étudier le métabolisme et améliorer la compréhension du fonctionnement des systèmes vivants. Deux concepts clés sont l'analyse des modes élémentaires de flux (EFMs), qui permet de décrire les réseaux métaboliques en termes de voies minimales, et les Minimal Cut Sets (MCSs), représentant les coupures minimales de flux du réseau en termes de réactions. Dans le cadre de cette thèse, nous avons développé une méthode de programmation logique pour le calcul des modes élémentaires de flux: aspefm. L'outil est une méthode de raisonnement automatique à base de Answer Set Programming (ASP), étendue par des contraintes linéaires. Cette approche permet de récupérer des voies lorsque les méthodes classiques ne le peuvent pas, d'interroger directement le réseau et d'éviter l'explosion en mémoire. La méthode peut prendre en compte des contraintes biologiques importantes de tous types, ce que nous avons illustré sur un réseau central d'Escherichia coli. Elle est aussi applicable aux réseaux à l'échelle du génome, et calcule plus aisément des solutions de large taille que les méthodes à base de programmation linéaire. Notre méthode a été appliquée, à la bactérie pathogène Pseudomonas aeruginosa (PA) qui est présente dans 80% des plaies chroniques. PA utilise des stratégies écologiques différentes de celles des bactéries modèles comme E. coli. Elle est retrouvée généralement dans les plaies chroniques avec une autre bactérie infectieuse, Staphylococcus aureus (SA). Nous supposons que leurs deux métabolismes sont complémentaires, ce qui permet une production de biomasse plus élevée conduisant à des mauvais pronostics pour les patients. L'extension de notre outil aspefm à l'analyse des MCSs sur un modèle de consortium de ces deux bactéries nous a permis de retrouver des métabolites dont l'échange entre les deux bactéries permettrait de compenser des phénotypes prédits létaux, ainsi que d'explorer des cibles thérapeutiques potentielles contre les bactéries. Par ailleurs, dans un autre cadre, nous avons appliqué notre méthode de calcul au métabolisme de la cellule cancéreuse humaine et à la formation du stroma tumoral<br>In systems biology, metabolic pathways analysis is an essential method to study metabolism and improve the understanding of biological systems. Key concepts include Elementary Flux Modes (EFMs), describing metabolic networks in terms of minimal pathways, and Minimal Cut Sets (MCSs), representing minimal cutting sets of reactions affecting network flux. In the scope of this thesis, we developed a logic programming method for the computation of Elementary Flux Modes: aspefm. The tool is an automatic reasoning method based on Answer Set Programming (ASP), extended by linear constraints. This approach allows one to get minimal pathways when classical methods are unable to, and to directly query the network, helping with memory usage considerations. Important biological constraints of many different kinds can be integrated into the program, which we illustrated on a central metabolic model of Escherichia coli. The method is also applicable to genome-scale metabolic models, showing better performance than linear programming-based methods on enumeration of large-size solutions. The method was applied to the pathogenic bacterium Pseudomonas aeruginosa (PA) found in 80% of chronic wounds. PA uses different ecological strategies than model bacteria. PA is commonly co-isolated from wounds with another opportunistic pathogen, Staphylococcus aureus (SA), and it is hypothesized the metabolisms of the two bacteria are complementary enabling higher biomass production and increasing wound bioburden leading to poor patient outcomes. We extended our tool aspefm to the analysis of MCSs on a consortium model of these two bacteria, permitting us to retrieve exchanged metabolites involved in the recovery of growth after several intervention strategies, and leading to insights about potential therapeutic targets against the two bacteria. Furthermore, in an other context, we applied our computation method to cancer cell metabolism and tumoural stroma formation
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Tuttle, Matthew Alan. "In silico analysis of zebrafish leptin-a knockdown gene expression data reveals enrichment for metabolic and developmental pathways including morpholino artifacts." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1492641073183086.
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Sehr, Christiana Verena [Verfasser], Andreas [Akademischer Betreuer] [Gutachter] Kremling, Alberto [Gutachter] Marín-Sanguino, and Eberhard [Gutachter] Voit. "Model based analysis of central metabolic pathways of Halomonas elongata / Christiana Verena Sehr ; Gutachter: Andreas Kremling, Alberto Marin-Sanguino, Eberhard Voit ; Betreuer: Andreas Kremling." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/1120013828/34.
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Schulz, Maike [Verfasser], Enno [Akademischer Betreuer] Klußmann, Jens [Gutachter] Kurreck, Roland [Gutachter] Lauster, and Enno [Gutachter] Klußmann. "Analysis of metabolic pathways controlling cAMP-regulated aquaporin-2 trafficking in renal principal cells / Maike Schulz ; Gutachter: Jens Kurreck, Roland Lauster, Enno Klußmann ; Betreuer: Enno Klußmann." Berlin : Technische Universität Berlin, 2018. http://d-nb.info/1168324017/34.
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Shehabi, Haleem Ziad. "In-vitro Evidence for Novel, Non-Classical, Alternative P450scc-Initiated Vitamin D Metabolic Pathways in Human Placenta via HPLC-UV/DAD and LC-ESI-MS/MS Analysis." Thesis, Curtin University, 2020. http://hdl.handle.net/20.500.11937/89121.
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Current findings identify and substantiate existence of previously unrecognised, likely, in-vivo alternative, non-classical P450scc-initiated vitamin D3/D2 metabolic pathways within in-vitro human placenta models. These pathways are further modified by CYP27A1 or CYP27B1 activity in human placenta and confirmed where required by purified human enzyme studies. This data was closely verified using equivalent in-vitro bovine adrenal cortex models and where necessary by purified bovine enzyme studies. Profiling was achieved by newly developed HPLC-UV/DAD and LC-ESI-MS/MS methodology.
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Planes, Francisco J. "Metabolic pathway analysis via integer linear programming." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/6134.
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The understanding of cellular metabolism has been an intriguing challenge in classical cellular biology for decades. Essentially, cellular metabolism can be viewed as a complex system of enzyme-catalysed biochemical reactions that produces the energy and material necessary for the maintenance of life. In modern biochemistry, it is well-known that these reactions group into metabolic pathways so as to accomplish a particular function in the cell. The identification of these metabolic pathways is a key step to fully understanding the metabolic capabilities of a given organism. Typically, metabolic pathways have been elucidated via experimentation on different organisms. However, experimental findings are generally limited and fail to provide a complete description of all pathways. For this reason it is important to have mathematical models that allow us to identify and analyze metabolic pathways in a computational fashion. This is precisely the main theme of this thesis. We firstly describe, review and discuss existent mathematical/computational approaches to metabolic pathways, namely stoichiometric and path finding approaches. Then, we present our initial mathematical model named the Beasley-Planes (BP) model, which significantly improves on previous stoichiometric approaches. We also illustrate a successful application of the BP model to optimally disrupt metabolic pathways. The main drawback of the BP model is that it needs as input extra pathway knowledge. This is especially inappropriate if we wish to detect unknown metabolic pathways. As opposed to the BP model and stoichoimetric approaches, this issue is not found in path finding approaches. For this reason a novel path finding approach is built and examined in detail. This analysis serves us as inspiration to build the Improved Beasley-Planes (IBP) model. The IBP model incorporates elements of both stoichometric and path finding approaches. Though somewhat less accurate than the BP model, the IBP model solves the issue of extra pathway knowledge. Our research clearly demonstrates that there is a significant chance of developing a mathematical optimisation model that underlies many/all metabolic pathways.
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Zhang, Rui. "Metabolic Disorder leads to Retinal degeneration: Function, morphology and metabolic pathway analysis." Thesis, The University of Sydney, 2020. https://hdl.handle.net/2123/25459.
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INTRODUCTION
The retina prefers to metabolize glucose through glycolysis rather than oxidative phosphorylation (OXPHOS) to meet their energy demand even when oxygen is abundant, known as the “Warburg effect”, despite having abundant functional mitochondria. We created transgenic mice with selective knockdowns of key enzymes in glycolysis and OXPHOS including hexokinase (HK) 2, lactate dehydrogenase (LDH) A and pyruvate dehydrogenase (PDH) E1α in rods to study the importance of glycolysis and OXPHOS in retinal metabolism and the role of metabolic derangement in the pathogenesis of retinal diseases.
MATERIALS AND METHODS
Immunohistochemistry and Western blots were performed to study the changes in protein expression and regulation. Scotopic electroretinography and optical coherence tomography were performed to study the retinal function and structure. Gas and liquid chromatography-mass spectrometry were employed to study the changes in13C-glucose-derived metabolites in the retina.
RESULTS
Knockdown of HK2 in rods led to photoreceptor degeneration, with reduction in the thickness of the retina and impaired retinal function. Knockdown of HK2 decreased pyruvate production but promoted the tricarboxylic acid (TCA) cycle in the retina.
Knockdown of LDHA and PDHE1α in rods also led to retinal degeneration, with thinning of the retina and impaired retinal function. Deletion of LDHA and PDHE1α suppressed glycolysis and the TCA cycle in the retina.
CONCLUSION
We found that HK2/LDHA-mediated glycolysis and PDHE1α mediated-OXPHOS in rods are indispensable for the maintenance of photoreceptor structure and function. Disturbance in aerobic glycolysis or OXPHOS leads to metabolic remodelling in the retina and photoreceptor degeneration.
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Ullah, Ehsan. "Pathway Analysis of Metabolic Networks using Graph Theoretical Approaches." Thesis, Tufts University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3640954.
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<p> Cellular pathways defining biochemical transformational routes are often utilized as engineering targets to achieve industrial-scale production of commercially useful biomolecules including polyesters, building blocks for polymers, biofuels, and therapeutics derived from isoprenoids, polyketides, and non-ribosomal peptides. Identifying target pathways can be expedited using computational tools, leading to reduced development cost, time, and effort, and enabling new discoveries with potential positive impact on human health and the environment. </p><p> This thesis addresses three cellular pathway identification problems within metabolic networks. In the first problem, we identify all stoichiometrically balanced, thermodynamically feasible and genetically independent pathways, known as Elementary Flux Modes (EFMs), that can be used to express flux distributions and characterize cellular function. We develop an algorithm, <i> gEFM</i>, that incorporates structural information of the underlying network to enumerate all EFMs. The results show that <i>gEFM</i> is competitive with state-of-the art EFM computation techniques for several test cases, but less so for networks with larger number of EFMs. In the second and third problems, we identify individual target pathways with pre-specified characteristics. We develop an algorithm, <i>PreProPath</i>, for identifying a target pathway for up-regulation such that the path is predictable in behavior, exhibiting small flux ranges, and profitable, containing the least restrictive flux-limiting reaction in the network. The results show that <i>PreProPath</i> can successfully identify high ethanol production pathways across multiple growth rates, and for succinate production in <i> Escherichia coli</i> (<i>E. coli</i>) as published in the literature. We also develop an algorithm, <i>Dominant-Edge Pathway</i>, that identifies thermodynamically-favored reactions along a pathway within the network from a given source metabolite to the desired destination. The algorithm is used to identify thermodynamically-limiting pathways in <i>Zymomonas mobilis</i> (<i>Z. mobilis</i>), <i>E. coli</i> and rat liver cell. </p><p> The novelty of this thesis is in utilizing graph-based methods to enumerate EFMs and to efficiently explore the pathway design space. Overall, the thesis advances the state-of-the-art techniques for metabolic pathway analysis.</p>
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Goel, Gautam. "Biochemical Systems Toolbox." Thesis, Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14509.
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The field of biochemical systems modeling and analysis is faced with an unprecedented flood of data from experimental methodologies of molecular biology. While these techniques continue to leapfrog ahead in the speed, volume and finesse with which they generate data, the methods of data analysis and interpretation, however, are still playing the catch-up game. The notions of systems analysis have found a new foothold, under the banner of Systems Biology, with the promise of uncovering the rationale for the designs of biological systems from their parts lists, as they are generated by experimentation and sorted and managed by bioinformatics tools. With an aim to complement hypothesis-driven and reductionistic biological research, and not replace it, a systems biologist relies on the tools of mathematical and computational modeling to be able to contribute meaningfully to any ongoing bio-molecular systems research. These systems analysis tools, however, should not only have their roots steeped well in the theoretical foundations of biochemistry, mathematics and numerical computation, but they should be married to a framework that facilitates the required systems way of thought for all its users computational scientists, experimentalists and molecular biologists alike. Hopefully, such framework-based tools would go beyond just providing fancy GUIs, numerical packages for integrating ODEs and/or optimization libraries. The intent of this thesis is to present a framework and toolbox for biochemical systems modeling, with an application in metabolic pathway analysis and/or metabolic engineering.
The research presented here builds upon the tenets of a very well established and generic approach to biological systems modeling and analysis, called Biochemical Systems Theory (BST), which is almost forty years old. The nuances of modeling and practical hurdles to analysis are presented in the context of a real-time case study of analyzing the glucolytic pathway in the bacterium Lactococcus lactis. Alongside, the thesis presents the features of a MATLAB-based software application that has been built upon the framework of BST and is aptly named as Biochemical Systems Toolbox (BSTBox). The thesis presents novel contributions, made by the author during the course of his research, to state-of-the-art techniques in parameter estimation, and robustness and sensitivity analysis topics that, as this thesis will show, remain to be the most restrictive bottlenecks in the world of biological systems modeling and analysis.
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Schilling, Christophe Heinz. "On systems biology and the pathway analysis of metabolic networks /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2000. http://wwwlib.umi.com/cr/ucsd/fullcit?p9981956.
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Liu, Ensheng Yuan Jian-Min. "Sensitivity, non-equilibrium thermodynamic and control analyses of insulin metabolic signaling pathways /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1862.
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Magnus, Jørgen Barsett. "Metabolic egineering of the valine pathway in corynebacterium glutamicum analysis and modelling /." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-34007.
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Perera, Munasinhage Venura Lakshitha. "Metabolic profiling of plant disease : from data alignment to pathway predictions." Thesis, University of Exeter, 2011. http://hdl.handle.net/10036/3906.
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Understanding the complex metabolic networks present in organisms, through the use of high throughput liquid chromatography coupled mass spectrometry, will give insight into the physiological changes responding to stress. However the lack of a proper work flow and robust methodology hinders verifiable biological interpretation of mass profiling data. In this study a novel workflow has been developed. A novel Kernel based feature alignment algorithm, which outperformed Agilent’s Mass profiler and showed roughly a 20% increase in alignment accuracy, is presented for the alignment of mass profiling data. Prior to statistical analysis post processing of data is carried out in two stages, noise filtering is applied to consensus features which were aligned at a 50% or higher rate. Followed by missing value imputation a method was developed that outperforms both at model recovery and false positive detection. The use of parametric methods for statistical analysis is inefficient and produces a large number of false positives. In order to tackle this three non-parametric methods were considered. The histogram method for statistical analysis was found to yield the lowest false positive rate. Data is presented which was analysed using these methods to reveal metabolomic changes during plant pathogenesis. A high resolution time series dataset was produced to explore the infection of Arabidopsis thaliana by the (hemi) biotroph Pseudomonas syringe pv tomato DC3000 and its disarmed mutant DC3000hrpA, which is incapable of causing infection. Approximately 2000 features were found to be significant through the time series. It was also found that by 4h the plants basal defence mechanism caused the significant ‘up-regulation’ of roughly 400 features, of which 240 were found to be at a 4-fold change. The identification of these features role in pathogenesis is supported by the fact that of those features found to discriminate between treatments a number of pathways were identified which have previously been documented to be active due to pathogenesis
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Strickland, Natalie Judith. "In silico and functional analyses of the iron metabolism pathway." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79871.
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Thesis (PhD)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: Iron is an essential micronutrient that is an absolute requirement for correct cellular
function in all eukaryotic organisms. However, ferrous iron has the ability to catalyze the
formation of potentially toxic reactive oxygen species and regulation of iron metabolism is
therefore of critical importance. Currently, there is little known about the co-ordinated
regulation of the plethora of genes coding for proteins involved in this biochemical pathway,
with the exception of the well characterized post-transcriptional IRE/IRP system. Regulation
of gene expression in eukaryotic organisms is a highly intricate process. Transcriptional
regulation is the first step and is controlled by the presence of specific cis-regulatory regions
(cis-motifs), residing within the promoter region of genes, and the functional interactions
between the products of specific regulatory genes (transcription factors) and these cismotifs.
A combinatorial bioinformatic and functional approach was designed and utilized in
this study for the analysis of the promoter architecture of genes of the iron metabolic
pathway. The upstream non-coding region (~2 kb) of 18 genes (ACO1, CP, CYBRD1, FTH1, FTL, HAMP,
HEPH, HFE, HFE2, HMOX1, IREB2, LTF, SLC11A2, SLC40A1, STEAP3, TF, TFRC, TFR2), known to
be involved in the iron metabolism pathway, was subjected to computational analyses to
identify regions of conserved nucleotide identity utilizing specific software tools. A subset of nine (CYBRD1, FTH1, HAMP, HFE, HFE2, HMOX1, IREB2, LTF, TFRC) of the genes
were found to contain a genomic region that demonstrated over 75% sequence identity
between the genes of interest. This conserved region (CR) is approximately 140 bp in size
and was identified in each of the promoters of the nine genes. The CR was subjected to
further detailed examination with comparative algorithms from different software for motif
detection. Four specific cis-motifs were discovered within the CR, which were found to be in
the same genomic position and orientation in each of the CR-containing genes. In silico
prediction of putative transcription factor binding sites revealed the presence of numerous
binding motifs of interest that could credibly be associated with a biological function in this
pathway, including a novel MTF-1 binding site in five of the genes of interest. Validation of the bioinformatic predictions was performed in order to fully assess the
relevance of the results in an in vitro setting. Luciferase reporter constructs for the nine CRcontaining
genes were designed containing: 1) the 2 kb promoter, 2) a 1.86 kb promoter
with the CR removed and 3) the 140 bp CR element. The expression levels of these three
reporter gene constructs were monitored with a dual-luciferase reporter assay under
standard culture conditions and simulated iron overload conditions in two different
mammalian cell lines. Results of the luciferase assays indicate that the CR promoter
constructs displayed statistically significant variation in expression values when compared to
the untreated control constructs. Further, the CR appears to mediate transcriptional
regulatory effects via an iron-independent mechanism. It is therefore apparent that the
bioinformatic predictions were shown to be functionally relevant in this study and warrant
further investigation.
Results of these experiments represent a unique and comprehensive overview of novel
transcriptional control elements of the iron metabolic pathway. The findings of this study
strengthen the hypothesis that genes with similar promoter architecture, and involved in a
common pathway, may be co-regulated. In addition, the combinatorial strategy employed in
this study has applications in alternate pathways, and could serve as a refined approach for
the prediction and study of regulatory targets in non-coding genomic DNA.<br>AFRIKAANSE OPSOMMING: Yster is ‘n noodsaaklike mikrovoedingstof wat ‘n vereiste is vir korrekte sellulêre funksie in
alle eukariotiese organismes. Yster (II) of Fe2+ het egter die vermoë om die vorming van
potensiële toksies reaktiewe suurstof spesies te kataliseer en dus is die regulasie van die
yster metaboliese padweg van kardinale belang. Tans is daar beperkte inligting oor
koördineerde regulasie van die gene, en dus proteïene waarvoor dit kodeer, in hierdie
padweg. ‘n Uitsondering is die goed gekarakteriseerde na-transkripsionele “IRE/IRP”
sisteem. Regulasie van geenuitdrukking in eukariotiese organismes is ‘n ingewikkelde
proses. Transkripsionele regulasie is die eerste stap en word beheer deur die
teenwoordigheid van spesefieke cis-regulatoriese elemente (cis-motiewe), geleë in die
promotor area van gene, en die funksionele interaksies wat plaasvind tussen die produkte
van spesifieke regulatoriese faktore (of transkripsie faktore) en hierdie cis-motiewe. ‘n
Gekombineerde bioinformatiese en funksionele benadering was ontwerp en daarna gebruik
in dié studie vir die analise van die promotor argitektuur van gene wat ‘n rol speel in die
yster metaboliese padweg.
Die stroomop nie-koderende streek (~2 kb) van 18 gene (ACO1, CP, CYBRD1, FTH1, FTL,
HAMP, HEPH, HFE, HFE2, HMOX1, IREB2, LTF, SCL11A2, SLC40A1, STEAP3, TF, TFRC, TFR2),
bekend vir hul betrokkenheid in die yster metabolisme padweg, was bloodgestel aan
bioinformatiese analises om die streke van konservering te identifiseer met die hulp van
spesifieke sagteware.
Slegs nege (CYBRD1, FTH1, HAMP, HFE, HFE2, HMOX1, IREB2, LTF, TFRC) van die
geanaliseerde gene het ‘n genomiese area bevat wat meer as 75% konservering getoon het.
Hierdie gekonserveerde area (GA) is 140 bp in lengte en is geïdentifiseer in elk van die
promotors van die nege gene. Die GA was verder bloodgestel aan analises, met die hulp van
spesifieke sgateware, wat gebruik maak van vergelykende algoritmes vir motief
karakterisering. Vier cis-motiewe is identifiseer en kom voor in dieselfde volgorde en
oriëntasie in elk van die gene. In silico voorspelling van moontlike transkripsie faktor
bindingsplekke het getoon dat daar talle bindingsmotiewe van belang teenwoordig is en dié motiewe kan gekoppel word aan biologiese funksies in hierdie padweg, insluitend ‘n nuwe
MTF-1 bindingsplek in vyf van die gene van belang.
Die bioinformatiese analises is verder gevalideer om die relevansie van die resultate in ‘n in
vitro sisteem ten volle te assesseer. Luciferase rapporteerder konstrukte is vir die nege gene
ontwerp wat die volgende bevat: 1) die 2 kb promotor, 2) ‘n 1.86 kb promotor met die GA
verwyder en 3) die 140 bp GA element. Die vlakke van uitdrukking van hierdie drie
rapporteerder konstrukte was genormaliseer met ‘n dubbele-luciferase rapporteerder assay
onder standaard kultuur kondisies en gesimuleerde ysteroorlading kondisies in twee
verskillende soogdier sellyne. Resultate van die luciferase assays dui aan dat die GA
promotor konstrukte statisties betekenisvolle variasie toon in vergelyking met die
onbehandelde kontrole konstrukte. Verder, die GA blyk om transkipsionele regulatoriese
effekte te medieer via ‘n yster-onafhanklike meganisme. Dit blyk duidelik dat die
bioinformatiese voorspellings ook funksioneel getoon kon word en was dus relevant in dié
studie en regverdig verdere ondersoek.
Hierdie eksperimentele ontwerp verteenwoordig ‘n unieke en omvattende oorsig van nuwe
transkripsionele beheer elemente wat voorkom in die yster metaboliese padweg. Die
resultate van dié studie versterk die hipotese dat gene met soortgelyke promotor argitektuur en wat betrokke is in ‘n gemene padweg saam gereguleer kan word.
Daarbenewens, die gekombineerde strategie wat in hierdie studie gebruik is het toepassings
in alternatiewe metaboliese paaie, en kan dien as ‘n verfynde benadering vir die
voorspelling en studie van die regulerende teikens in nie-koderende genomiese DNS.<br>National Research Foundation (Thuthuka)<br>Stellenbosch University
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CHUNG, Sook Hyun. "Genomic analysis of a transgenic model of selective Müller cell ablation: morphology, microarray and metabolic pathway analysis." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9985.
Full textAbstract:
Müller cell dysfunction has been found in many retinal diseases such as diabetic retinopathy and macular telengiectasia. To investigate their potential role in the pathogenesis of retinal diseases, we have created a novel transgenic mouse model of conditional Müller cells ablation. The aim of this study was to perform genomic analysis with the whole retinal samples, then to examine metabolic dysfunction in patches of Müller cell loss that were isolated by laser capture microdissection (LCM). Microarray analysis with whole retinal samples revealed increased transcription of genes responsible for neuronal apoptosis, neurotrophic factors and their related pathways in the early stage of ablation, while retinal metabolism and tight junction pathways were downregulated later. The qRT-PCR and western blot analysis successfully validated the microarray results. qRT-PCR analysis of LCM-directed samples revealed significantly reduced transcriptions of metabolic pathways (glycolytic and mTOR pathways) related genes. Immunohistofluorescent studies revealed that Enolase 1 clearly colocalised with Müller cells whereas other metabolic pathway related proteins we studied were expressed mainly in the photoreceptor segments, where they were lost from degenerated photoreceptors in areas of Müller cell loss. Further studies of the consequences of Müller cell dysfunction are warranted to identify the specific mechanisms of photoreceptor degeneration and it may potentially lead to a greater understanding of the role of Müller cell dysfunction in retinal disease.
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D'Souza, Arun. "PathCaseMAW: A Workbench for Metabolomic Analysis." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1222895452.
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Magnus, Jørgen Barsett [Verfasser]. "Metabolic egineering of the valine pathway in Corynebacterium glutamicum : analysis and modelling / Jørgen Barsett Magnus." Jülich : Forschungszentrum, Zentralbibliothek, 2007. http://d-nb.info/997058552/34.
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Kitami, Toshimori. "GENETIC, EVOLUTIONARY, AND GENOMIC ANALYSIS OF HOMOCYSTEINE AND FOLATE PATHWAY REGULATION." Connect to text online, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1127865525.
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Singh, Sumit Kumar. "Pathway Pioneer: A Web-Based Graphical Tool for the Organization and Flux Analysis of Metabolic Networks." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/2796.
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As stoichiometric metabolic models increase in complexity and delity, design and reconstruction tools are urgently needed to increase the productivity of this time-consuming process. Engineers require software for the exploration, evaluation, and rapid analysis of model alternatives within an intuitive visualization and data management framework. This thesis introduces such a tool: Pathway Pioneer (www.pathwaypioneer.org), a web based system built as a front-end graphical user interface to the ux balance analysis tool COBRA. Pathway Pioneer adds additional functionality for customized network layout and model-engineering collaboration through shared models and model version control. Pathway Pioneer is a dynamic, clickable, browser-based visualization system for metabolic network models retrieved from databases such as BiGG or developed in-house as SBML or XLS compliant les. The user can customize the network layout to visually organize the metabolites and reactions into functional modules. The tool supports zooming and panning, level-of-detail control, ux visualization, keyword searching, and hierarchical subsystem organization. A reaction may be knocked out, set as an objective, looked up in a database or many other operations by a single click on the visualized network. Following each operation the visualization is refreshed with the new ux values. The system supports model revision control to manage alternative network congurations and supports sharing of models and layouts to the broader community. By moving the computationally intensive model analysis from the user computer to remote servers, Pathway Pioneer enables the application of high performance cloud-based resources for greater eciency and scalability. I demonstrate the utility of Pathway Pioneer through application in model reconstruction and analysis of many standard models and also two new models under development: Eukaryotic multicompartment Chinese Hamster Ovary (Cho) cells and in a large-scale Escherichia coli system for bio-manufacturing.
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Dupont, Pierre-Yves. "Conception d'outils bioinformatiques pour la modélisation de voies métaboliques et de leur régulation." Thesis, Clermont-Ferrand 1, 2011. http://www.theses.fr/2011CLF1MM27/document.
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La biologie des systèmes actuelle s’appuie sur des techniques d’analyse biologique à haut débit comme la transcriptomique ou la métabolomique. Cependant, ces techniques haut débit ont leurs limites et peuvent générer des erreurs. En croisant les résultats de différentes techniques d’analyse biologique, nous espérons pallier une partie de leurs limites. À cet effet, nous avons commencé à développer une plateforme de modélisation, MPSA (Metabolic Pathways Software Analyzer), permettant d’intégrer les données générées à des réseaux métaboliques. MPSA permet de représenter les graphes de voies métaboliques, d’effectuer des simulations basées sur la résolution de systèmes d’équations différentielles et d’étudier la structure des réseaux métaboliques par le calcul et la représentation des modes élémentaires. Nous avons développé différentes applications web permettant, d’une part, l’interprétation des résultats biologiques en utilisant des bases de données et, d’autre part, leur export vers MPSA. La base de données centrale de ce développement est myKegg, incluant l’ensemble des voies métaboliques humaines de la base de données publique KEGG ainsi qu’une base de synonymes construite elle aussi à partir de KEGG. Cette base permet d’identifier des voies métaboliques et de les importer dans MPSA. Une base de données de métabolomique, BioNMR, a aussi été construite spécifiquement pour organiser les résultats générés à partir de spectres de RMN. Une autre application web, GeneProm, a été développée pour l’analyse de promoteurs de gènes ou promotologie. Un protocole d’étude a été mis au point et testé sur un groupe de 4 gènes codant pour les isoformes 1 à 4 de la protéine ANT, transporteur mitochondrial d’ATP, chacune ayant un rôle et un profil d’expression spécifique dans la bioénergétique cellulaire. L’étude par promotologie de ces 4 gènes a permis d’identifier des éléments de régulation spécifiques dans leurs séquences promotrices et d’identifier des gènes potentiellement co-régulés. Ces gènes peuvent ensuite être exportés vers notre plateforme MPSA. L’ensemble de ce développement sera inclus au projet de plateforme intégrative de l’Unité de Nutrition Humaine de l’INRA<br>Current systems biology relies on high-throughput biological analysis techniques such as transcriptomics or metabolomics. However, these techniques may generate errors. By crossing results from different analysis techniques, we hope to avoid at least part of these limits. For that purpose, we started to develop a modeling platform, MPSA (Metabolic Pathways Software Analyzer). MPSA allows integrating biological data on metabolic pathways. MPSA also ensures the display of metabolic pathways graphs, the simulation of models based on ordinary differential equations systems solving and the study of network structures using elementary flux modes. We have developed several web applications allowing on the one hand to interpret biological results by using databases, and on the other hand to export these data to MPSA. The main database of this work is myKegg. It includes all human KEGG metabolic pathways and a list of synonyms for human KEGG entries. This base allows to identify metabolic pathways from a list of biological compounds and to import them in MPSA. Another database, BioNMR, has been developed to organize the data extracted from NMR spectra. Another web application named GeneProm has been developed to analyze gene promoters. A promotology protocol was developed and tested on a set of four genes coding for the four ANT (adenine nucleotide translocator) protein isoforms. Each ANT isoform has a specific expression profile and role in cell bioenergetics. The promotology study of these four genes led us to construct specific regulatory models from identified regulatory elements in their promoter sequence. Potentially co-regulated genes were deduced from these models. Then they can be exported to our MPSA platform. This whole development will be included in the project of Integrative Biology platform in the INRA Human Nutrition Unit
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Wilson, Emma. "Analysis of phosphatidylinositol metabolism and ER-mitochondria contact sites in the PINK1/Parkin pathway." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/19741/.
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Guo, Weihua. "Computational Modeling of Planktonic and Biofilm Metabolism." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/79669.
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Most of microorganisms are ubiquitously able to live in both planktonic and biofilm states, which can be applied to dissolve the energy and environmental issues (e.g., producing biofuels and purifying waste water), but can also lead to serious public health problems. To better harness microorganisms, plenty of studies have been implemented to investigate the metabolism of planktonic and/or biofilm cells via multi-omics approaches (e.g., transcriptomics and proteomics analysis). However, these approaches are limited to provide the direct description of intracellular metabolism (e.g., metabolic fluxes) of microorganisms.
Therefore, in this study, I have applied computational modeling approaches (i.e., 13C assisted pathway and flux analysis, flux balance analysis, and machine learning) to both planktonic and biofilm cells for better understanding intracellular metabolisms and providing valuable biological insights. First, I have summarized recent advances in synergizing 13C assisted pathway and flux analysis and metabolic engineering. Second, I have applied 13C assisted pathway and flux analysis to investigate the intracellular metabolisms of planktonic and biofilm cells. Various biological insights have been elucidated, including the metabolic responses under mixed stresses in the planktonic states, the metabolic rewiring in homogenous and heterologous chemical biosynthesis, key pathways of biofilm cells for electricity generation, and mechanisms behind the electricity generation. Third, I have developed a novel platform (i.e., omFBA) to integrate multi-omics data with flux balance analysis for accurate prediction of biological insights (e.g., key flux ratios) of both planktonic and biofilm cells. Fourth, I have designed a computational tool (i.e., CRISTINES) for the advanced genome editing tool (i.e., CRISPR-dCas9 system) to facilitate the sequence designs of guide RNA for programmable control of metabolic fluxes. Lastly, I have also accomplished several outreaches in metabolic engineering.
In summary, during my Ph.D. training, I have systematically applied computational modeling approaches to investigate the microbial metabolisms in both planktonic and biofilm states. The biological findings and computational tools can be utilized to guide the scientists and engineers to derive more productive microorganisms via metabolic engineering and synthetic biology. In the future, I will apply 13C assisted pathway analysis to investigate the metabolism of pathogenic biofilm cells for reducing their antibiotic resistance.<br>Ph. D.
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Goerner-Potvin, Patricia. "Transcriptomic analysis of Sinorhizobium meliloti 1021 focusing on tricarboxylic acid cycle, nitrogen fixation, and carbon metabolism pathways." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123171.
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Sinorhizobium meliloti 1021 is a nitrogen-fixing symbiont of legume plants Medicago, Melilotus and Trigonella. This bacterium is a model organism for tricarboxylic acid (TCA) cycle, and other genetic studies. The complete S. meliloti 1021 bacteroid transcriptome was sequenced and was compared to the complete sequenced transcriptome of free-living cells grown on malate a as sole carbon source. Twenty-seven genes were downregulated more than 20 folds when compared to the control treatment malate. Most of these downregulated genes were of unknown function or part of the carbohydrate transport and metabolism COG group. Genes involved in the TCA cycle, including the mdh-sucCDAB operon, were mostly upregulated in bacteroids; the mdh-sucCDAB genes showed increased transcription by 12.9 fold change (FC), 10.4 FC, 12.2 FC, 8.35 FC, and 8.66 FC, respectively. Nitrogen fixation nif and fix genes underwent the highest transcription FC increase with 1085, 1538, 3060, 449, and 219 FC respectively for the nifKDHEF genes. Over half of the pentose phosphate pathway genes were downregulated as expected, while edd, deoC, zwf, pgl, and tkt2 were upregulated indicating some glucose availability in root nodules. A majority of the glycolysis pathway genes were also downregulated in bacteroids. qRT-PCR experiments were conducted on mdh, sucC and sucA in various carbon treatments. The presence of a second promoter within the mdh-sucCDAB operon located in an intergenic region upstream of sucA (the first being upstream of mdh) was suggested by a decreased expression of sucC but not of downstream sucA in succinate-grown cells. A potential mdh mutant was obtained via EZ-Tn5 transposon insertion mutagenesis; but this strain requires further confirmation and characterization.<br>Sinorhizobium meliloti 1021 est une bactérie symbiotique fixant l'azote pour les légumineuses Medicago, Melilotus et Trigonella. Cette bactérie est un organisme modèle pour Krebs (TCA) cycle, ainsi que pour d'autres études génétiques Le transcriptome complet de la bactérie Sinorhizobium meliloti 1021 sous sa forme de bactéroïde a été séquencé pour trois réplicas biologiques et comparé au transcriptome complet du traitement contrôle, ce dernier étant S. meliloti 1021 traité avec le malate comme seule source de carbone (dont le transcriptome complet fut aussi séquencé pour cette thèse). 27 gènes ont été régulés à la baisse par plus de 20 fois part rapport au contrôle le traitement malate. La plupart de ces gènes régulés à la baisse sont de fonction inconnue ou font partie du groupe COG de transport et de métabolisme des hydrates de carbone. Les gènes impliqués dans le cycle Krebs (TCA) ont été principalement régulés à la hausse dans les bactéroïdes, y compris l'opéron mdh-sucCDAB avec 12,94 FC pour mdh, 10,37 pour sucC, 12,22 pour sucD, 8,35 pour sucA, et une moyenne de 8.66 facteur de variation (FC) pour sucB. Les gènes nif et fix impliqués dans la fixation de l'azote ont subi l a plus haute augmentation de FC de transcription avec 1085,25; 1537,98; 3059,52; 448,91; et 218,98 FC moyens respectivement pour les gènes nifKDHEF. Plus de la moitié des gènes du métabolisme du pentoses phosphates ont été régulée à la baisse comme prévu, tandis que edd, deoC, zwf, pgl, et tkt2 ont été régulés à la hausse, ce qui indique une certaine disponibilité du glucose dans les nodules des racines. La majorité des gènes du métabolisme de glucose ont été également régulée à la baisse dans les bactéroïdes. Des expériences de qRT -PCR ont été réalisées sur mdh, sucC et sucA traités avec diverses sources de carbone. La présence d'un second promoteur à l'intérieur de l'opéron situé dans une région intergénique entre sucD et sucA a été suggérée par une diminution de l'expression de sucC mais pas sucA dans les bactéries cultivés avec du succinate. Un potentiel mdh mutant a été obtenue par l'insertion d'un transposon pour le gène mdh, mais nécessite encore caractérisation et confirmation.
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Zheng, Lianqing. "Statistical identification of metabolic reactions catalyzed by gene products of unknown function." Diss., Kansas State University, 2013. http://hdl.handle.net/2097/15594.
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Doctor of Philosophy<br>Department of Statistics<br>Gary L. Gadbury<br>High-throughput metabolite analysis is an approach used by biologists seeking to identify the functions of genes. A mutation in a gene encoding an enzyme is expected to alter the level of the metabolites which serve as the enzyme’s reactant(s) (also known as substrate) and product(s). To find the function of a mutated gene, metabolite data from a wild-type organism and a mutant are compared and candidate reactants and products are identified. The screening principle is that the concentration of reactants will be higher and the concentration of products will be lower in the mutant than in wild type. This is because the mutation reduces the reaction between the reactant and the product in the mutant organism.
Based upon this principle, we suggest a method to screen the possible lipid reactant and product pairs related to a mutation affecting an unknown reaction. Some numerical facts are given for the treatment means for the lipid pairs in each treatment group, and relations between the means are found for the paired lipids. A set of statistics from the relations between the means of the lipid pairs is derived. Reactant and product lipid pairs associated with specific mutations are used to assess the results.
We have explored four methods using the test statistics to obtain a list of potential reactant-product pairs affected by the mutation. The first method uses the parametric bootstrap to obtain an empirical null distribution of the test statistic and a technique to identify a family of distributions and corresponding parameter estimates for modeling the null distribution. The second method uses a mixture of normal distributions to model the empirical bootstrap null. The third method uses a normal mixture model with multiple components to model the entire distribution of test statistics from all pairs of lipids. The argument is made that, for some cases, one of the model components is that for lipid pairs affected by the mutation while the other components model the null distribution. The fourth method uses a two-way ANOVA model with an interaction term to find the relations between the mean concentrations and the role of a lipid as a reactant or product in a specific lipid pair. The goal of all methods is to identify a list of findings by false discovery techniques. Finally a simulation technique is proposed to evaluate properties of statistical methods for identifying candidate reactant-product pairs.
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Maleki-Yazdi, Keon. "The genetic determinants of small-for-gestational-age infants in thrombophilia and folate metabolism pathways investigated through meta-analysis." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121509.
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Background: Previous data have demonstrated associations for an increased risk of the small-for-gestational-age (SGA) outcome in offspring of pregnant women with thrombophilia and folate metabolism gene polymorphisms. However, these results have not been consistent.Methods: The objective of this thesis is to review genetic association studies in thrombophilia and folate metabolism pathways for the SGA outcome (defined as birth weight below the 10th percentile for gestational age and sex according to national standards). We performed a series of meta-analyses for commonly studied maternal and newborn gene variants within the two pathways: prothrombin G20210A and factor V G1691A (Leiden) in the thrombophilia pathway, as well as methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C in the folate metabolism pathway. Results: In the thrombophilia pathway, the meta-analysis indicated an increased odds of SGA births among mothers carrying prothrombin G20210A (odds ratio=1.39 [95% confidence interval, 1.10 to 1.76]). Non-significant findings were found for maternal carriage of factor V Leiden, as well as prothrombin G20210A and factor V Leiden among newborn carriers. With respect to the folate metabolism pathway, maternal carriers of MTHFR C677T (odds ratio=1.22 [95% confidence interval, 1.05 to 1.42]), maternal homozygous MTHFR C677T (odds ratio=1.18 [95% confidence interval, 1.03 to 1.35]), and maternal homozygous A1298C (odds ratio=0.70 [95% confidence interval, 0.50 to 0.98]) were the only genotypes that reached statistical significance.Conclusion: To our knowledge, this is the first meta-analysis to indicate significant associations between an increased risk of SGA and maternal prothrombin G20210A carriers, maternal MTHFR C677T carriers, and homozygous mothers for MTHFR C677T. We also reported that pregnant women homozygous for MTHFR A1298C were at a decreased risk of SGA births.<br>Contexte: La variation d'un seul élément du code moléculaire dite polymorphisme du nucléotide simple ou SNP peut contribuer à l'incidence de maladies dites complexes. Certains SNPs sur des gènes de thrombophilie et du métabolisme de l'acide folique dans le génome de la mère ont été associés avec un risque accru pour leurs bébés de naître petits pour leur âge gestationnel (PAG). Cependant, ces résultats ne sont pas uniformes. Méthodes: Cette thèse recense les études portant sur les SNPs dans les voies métaboliques de thrombophilie et du cycle du folate et l'issue de grossesse PAG (définie par un poids à la naissance inférieur au 10e percentile pour le sexe et l'âge gestationnel selon les normes nationales). Nous avons effectué une série de méta-analyses sur les SNPs nommés prothrombine G20210A et facteur V Leiden G1691A dans la voie de thrombophilie, ainsi que sur deux SNPs du gène méthylènetétrahydrofolate réductase (MTHFR) soient C677T et A1298C impliqués dans le métabolisme du folate. Résultats: Notre méta-analyse sur les voies de la thrombophilie a montré un risque accru de naissances PAG quand les mères portent le SNP G20210A (odds ratio=1,39 [intervalle de confiance à 95%: 1,10 à 1,76]. Des résultats non significatifs ont été trouvés lorsque la mère porte le facteur V Leiden, ainsi que lorsque le nouveau-né est porteur des SNP G20210A et facteur V Leiden. En ce qui concerne la voie du métabolisme du folate, les seuls résultats qui ont atteint la signification statistique étaient les suivants : lorsque les mères portaient la variation en une copie de C677T (odds ratio=1,22 [intervalle de confiance à 95%: 1,05 à 1,42]), étaient homozygotes (2 copies) pour C677T (odds ratio=1,18 [intervalle de confiance à 95%: 1,03 à 1,35]) ou homozygotes pour A1298C (odds ratio=0,70 [intervalle de confiance à 95%: 0,50 à 0,98]). Conclusion: À notre connaissance, cette étude est la première à décrire dans une méta-analyse des associations significatives entre un risque accru de naissances PAG et le fait que les mères portent une copie des SNPs prothrombine G20210A et MTHFR C677T ou deux copies de MTHFR C677T. Aussi, nous avons trouvé qu'il y avait une diminution du risque de PAG chez les femmes porteuses du SNP MTHFR A1298C.
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Figueiredo, Luís Filipe Domingos Pereira de [Verfasser], Stefan Akademischer Betreuer] Schuster, Peter [Akademischer Betreuer] [Dittrich, and Marie-France [Akademischer Betreuer] Sagot. "Metabolic Pathway Analysis : from small to genome-scale networks / Luis F. D. P. de Figueiredo. Gutachter: Stefan Schuster ; Peter Dittrich ; Marie-France Sagot." Jena : Thüringer Universitäts- und Landesbibliothek Jena, 2011. http://d-nb.info/1016368283/34.
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Momin, Amin Altaf. "Application of bioinformatics in studies of sphingolipid biosynthesis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34842.
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The studies in this dissertation demonstrate that the gene expression pathway maps are useful tools to notice alteration in different branches of sphingolipid biosynthesis pathway based on microarray and other transcriptomic analysis. To facilitate the integrative analysis of gene expression and sphingolipid amounts, updated pathway maps were prepared using an open access visualization tool, Pathvisio v1.1. The datasets were formatted using Perl scripts and visualized with the aid of color coded pathway diagrams. Comparative analysis of transcriptomics and sphingolipid alterations from experimental studies and published literature revealed 72.8 % correlation between mRNA and sphingolipid differences (p-value < 0.0001 by the Fisher's exact test).The high correlation between gene expression differences and sphingolipid alterations highlights the application of this tool to evaluate molecular changes associate with sphingolipid alterations as well as predict differences in specific metabolites that can be experimentally verified using sensitive approaches such as mass spectrometry. In addition, bioinformatics sequence analysis was used to identify transcripts for sphingolipid biosynthesis enzyme 3-ketosphinganine reductase, and homology modeling studies helped in the evaluation of a cell line defective in sphingolipid metabolism due to mutation in the enzyme serine palmitoyltransferase, the first enzyme of de novo biosynthesis pathway. Hence, the combination of different bioinformatics approaches, including protein and DNA sequence analysis, structure modeling and pathway diagrams can provide valuable inputs for biochemical and molecular studies of sphingolipid metabolism.
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Halama, Anna Maria [Verfasser], Jerzy [Akademischer Betreuer] Adamski, Karsten [Akademischer Betreuer] Suhre, and Johann Josef [Akademischer Betreuer] Hauner. "Analyses of metabolic pathways of cellular processes in apoptosis and adipogenesis / Anna Maria Halama. Gutachter: Karsten Suhre ; Jerzy Adamski ; Johann Josef Hauner. Betreuer: Jerzy Adamski." München : Universitätsbibliothek der TU München, 2013. http://d-nb.info/1063090520/34.
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Celton, Magalie. "Etude de la réponse de Saccharomyces cerevisiae à une perturbation NADPH par une approche de biologie des systèmes." Thesis, Montpellier, SupAgro, 2011. http://www.theses.fr/2011NSAM0023/document.
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L'élucidation des propriétés du réseau métabolique est fondamentale pour la compréhension du fonctionnement cellulaire et pour l'élaboration de stratégies d'ingénierie métabolique. L'objectif de cette thèse était de mieux comprendre la régulation du métabolisme du NADPH, un métabolite "hub" qui joue un rôle central dans de nombreux processus cellulaires, chez Saccharomyces cerevisiae en fermentation. Nous avons utilisé une démarche systématique couplant modélisation et approches multi-“omics” pour étudier de façon quantitative la réponse à une perturbation de la demande en NADPH. Un système expérimental original, basé sur l'expression d'une butanediol déshydrogénase modifiée NADPH-dépendante a été utilisé pour augmenter de façon contrôlée la demande en NADPH. L'utilisation de ce dispositif, le développement et l'utilisation d'un modèle stœchiométrique de la levure dédié à la fermentation ont permis de prédire la répartition des flux pour différents niveaux de perturbation. Ces analyses ont montré, en premier lieu, la très grande capacité de la levure à faire face à des demandes très importantes de NADPH représentant jusqu'à 40 fois la demande anabolique. Pour des demandes modérées (allant jusqu'à 20 fois la demande anabolique), la perturbation est principalement compensée par une augmentation du flux à travers la voie des pentoses phosphate (VPP) et à moindre titre à travers la voie acétate (Ald6p). Pour une forte demande en NADPH, correspondant à 40 fois la demande anabolique, le modèle prédit la saturation de la VPP ainsi que la mise en place du cycle glycérol-DHA, qui permet l'échange du NADH en NADPH. Des analyses fluxomique (13C), métabolomique et transcriptomique, ont permis de valider ces hypothèses et de les compléter. Nous avons mis en évidence différents niveaux de régulation selon l'intensité de la perturbation : pour les demandes modérées, les flux sont réajustés par un contrôle au niveau enzymatique ; pour de fortes demandes, un contrôle transcriptionnel de plusieurs gènes de la VPP ainsi que de certains gènes des voies de biosynthèse des acides aminés est observé, cet effet résultant probablement de la moindre disponibilité en NADPH. Dans l'ensemble, ce travail a apporté un nouvel éclairage sur les mécanismes impliqués dans l'homéostasie du NADPH et plus généralement dans l'équilibre redox intracellulaire<br>The elucidation of the properties of metabolic network is essential to increase our understanding of cellular function and to design metabolic engineering strategies. The objective of this thesis was to better understand the regulation of the metabolism of NADPH, a “hub” metabolite which plays a central role in many cellular processes in Saccharomyces cerevisiae during fermentation. We used a systematic approach combining modeling and multi-“omics” analyses to study quantitatively the response to a perturbation of the NADPH demand. An original experimental system, based on the expression of a modified NADPH-dependent butanediol dehydrogenase was used to increase the demand for NADPH in a controlled manner. Through the use of this device and the development and use of a stoichiometric model of yeast dedicated to the fermentation, we predicted the flux distribution for different levels of perturbation. These experiments showed, first, the overwhelming ability of yeast to cope with very high NADPH demand, up to 40 times the anabolic demand. For a moderate level (up to 20 times the anabolic demand), the perturbation is mainly compensated by increased flux through the pentose phosphate pathway (PPP) and to a lesser extent through the acetate pathway (Ald6p). For a high NADPH demand, corresponding to 40 times the anabolic demand, the model predicts the saturation of the PPP as well as the operation of the glycerol-DHA cycle, which allows the exchange of NADH to NADPH. Fluxomics (13C), metabolomics and transcriptomics data were used to validate and to complement these hypotheses. We showed different levels of control depending on the intensity of the perturbation: for moderate demands, flux remodeling is mainly achieved by enzymatic control; for a high demand, a transcriptional control is observed for several genes of the PPP as well as some genes of the amino acids biosynthetic pathways, this latter effect being likely due to the low NADPH availability. Overall, this work has shed new light on the mechanisms governing NADPH homeostasis and more generally the intracellular redox balance
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Cubuk, Cankut. "Modeling Functional Modules Using Statistical and Machine Learning Methods." Doctoral thesis, Universitat Politècnica de València, 2020. http://hdl.handle.net/10251/156175.
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[ES] La comprensión de los aspectos de la funcionalidad de las células que cuentan para los mecanismos de las enfermedades es el mayor reto de la medicina personalizada. A pesar de la disponibilidad creciente de los datos de genómica y transcriptómica, sigue existiendo una notable brecha entre la detección de las perturbaciones en la expresión de genes y la comprensión de su contribución en los mecanismos moleculares que últimamente tienen relación importante con el fenotipo estudiado. A lo largo de la última década, distintos modelos computacionales y matemáticos se han propuesto para el análisis de las rutas. Sin embargo, estos modelos no toman en cuenta los mecanismos dinámicos de las rutas como la estructura y las interacciones entre genes y proteínas. En esta tesis doctoral, presento dos modelos matemáticos ligeramente distintos, para integrar los datos transcriptómicos masivos de humano con un conocimiento previo de de las rutas de señalización y metabólicas para estimar las actividades mecánicas que están detrás de esas rutas (MPAs). Las MPAs son variables continuas con valores de nivel individual que pueden ser usadas con los modelos de aprendizaje de máquinas y métodos estadísticos para determinar los biomarcadores que podemos usar para los diagnósticos tempranos y la clasificación de subtipos de enfermedades, además de poder sugerir las dianas terapéuticas potenciales para las intervenciones individualizadas.
El objetivo global es desarrollar nuevos y avanzados enfoques de la biología de sistemas para proponer unas hipótesis funcionales que nos ayuden a entender e interpretar los mecanismos complejos de las enfermedades. Estos mecanismos son cruciales para mejorar los tratamientos personalizados y predecir los resultados clínicos. En primer lugar, contribuí al desarrollo de un método que está diseñado para extraer las subrutas elementales desde la ruta de señalización con sus actividades estimadas. Posteriormente, este algoritmo se ha adaptado a los módulos metabólicos y se ha implementado como una herramienta web. Finalmente , el método ha revelado un panorama metabólico para una lista completa de diferentes tipos de cánceres. En este estudio, analicé el perfil metabólico de 25 tipos de cáncer distintos y se validó el método usando varios enfoques computacionales y experimentales. Cada método desarrollado en esta tesis ha sido enfrentado a otros métodos similares existentes, evaluados por sus sensibilidades y especificidades, experimentalmente validados cuando fue posible y usados para predecir resultados clínicos de varios tipos de cánceres. La investigación descrita en esta tesis y los resultados obtenidos fueron publicados en distintas revistas arbitradas que están relacionadas con el cáncer y biología de sistemas, y también en los periódicos nacionales.<br>[CA] La comprensió dels aspectes de la funcionalitat de les cèl·lules que compten per als mecanismes de les malalties és el major repte de la medicina personalitzada. Malgrat la disponibilitat creixent de les dades de genòmica i transcriptómica, continua existint una notable bretxa entre la detecció de les pertorbacions en l'expressió de gens i la comprensió de la seua contribució en els mecanismes moleculars que últimament tenen relació important amb el fenotip estudiat. Al llarg de l'última dècada, diferents models computacionals i matemàtics s'han proposat per a l'anàlisi de les rutes. No obstant això, aquests models no tenen en compte els mecanismes dinàmics de les rutes com l'estructura i les interaccions entre gens i proteïnes. En aquesta tesi doctoral, presente dos models matemàtics lleugerament diferents, per a integrar les dades transcriptómicos massius d'humà amb un coneixement previ de de les rutes de senyalització i metabòliques per a estimar les activitats mecàniques que estan darrere d'aqueixes rutes (MPAs). Les MPAs són variables contínues amb valors de nivell individual que poden ser usades amb els models d'aprenentatge de màquines i mètodes estadístics per a determinar els biomarcadores que podem usar per als diagnòstics primerencs i la classificació de subtipus de malalties, a més de poder suggerir les dianes terapèutiques potencials per a les intervencions individualitzades.
L'objectiu global és desenvolupar nous i avançats enfocaments de la biologia de sistemes per a proposar unes hipòtesis funcionals que ens ajuden a entendre i interpretar els mecanismes complexos de les malalties. Aquests mecanismes són crucials per a millorar els tractaments personalitzats i predir els resultats clínics. En primer lloc, vaig contribuir al desenvolupament d'un mètode que està dissenyat per a extraure les subrutas elementals des de la ruta de senyalització amb les seues activitats estimades. Posteriorment, aquest algorisme s'ha adaptat als mòduls metabòlics i s'ha implementat com una eina web. Finalment, el mètode ha revelat un panorama metabòlic per a una llista completa de diferents tipus de càncers. En aquest estudi, vaig analitzar el perfil metabòlic de 25 tipus de càncer diferents i es va validar el mètode usant diversos enfocaments computacionals i experimentals. Cada mètode desenvolupat en aquesta tesi ha sigut enfrontat a altres mètodes similars existents, avaluats per les seues sensibilitats i especificitats, experimentalment validats quan va ser possible i usats per a predir resultats clínics de diversos tipus de càncers. La investigació descrita en aquesta tesi i els resultats obtinguts van ser publicats en diferents revistes arbitrades que estan relacionades amb el càncer i biologia de sistemes, i també en els periòdics nacionals.<br>[EN] Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is the main challenge for precision medicine. In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Over the last decade, different computational and mathematical models have been proposed for pathway analysis. However, they are not taking into account the dynamic mechanisms contained by pathways as represented in their layout and the interactions between genes and proteins. In this thesis, I present two slightly different mathematical models to integrate human transcriptomic data with prior knowledge of signalling and metabolic pathways to estimate the Mechanistic Pathway Activities (MPAs). MPAs are continuous and individual level values that can be used with machine learning and statistical methods to determine biomarkers for the early diagnosis and subtype classification of the diseases, and also to suggest potential therapeutic targets for individualized therapeutic interventions.
The overall objective is, developing new and advanced systems biology approaches to propose functional hypotheses that help us to understand and interpret the complex mechanism of the diseases. These mechanisms are crucial for robust personalized drug treatments and predict clinical outcomes. First, I contributed to the development of a method which is designed to extract elementary sub-pathways from a signalling pathway and to estimate their activity. Second, this algorithm adapted to metabolic modules and it is implemented as a webtool. Third, the method used to reveal a pan-cancer metabolic landscape. In this study, I analyzed the metabolic module profile of 25 different cancer types and the method is also validated using different computational and experimental approaches. Each method developed in this thesis was benchmarked against the existing similar methods, evaluated for their sensitivity and specificity, experimentally validated when it is possible and used to predict clinical outcomes of different cancer types. The research described in this thesis and the results obtained were published in different systems biology and cancer-related peer-reviewed journals and also in national newspapers.<br>Cubuk, C. (2020). Modeling Functional Modules Using Statistical and Machine Learning Methods [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/156175<br>TESIS
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Abily-Donval, Lénaïg. "Exploration des mécanismes physiopathologiques des mucopolysacharidoses et de la maladie de Fabry par approches "omiques" et modulation de l'autophagie. Urinary metabolic phenotyping of mucopolysaccharidosis type I combining untargeted and targeted strategies with data modeling Unveiling metabolic remodeling in mucopolysaccharidosis type III through integrative metabolomics and pathway analysis." Thesis, Normandie, 2019. http://www.theses.fr/2019NORMR108.
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Les pathologies lysosomales sont des maladies liées au déficit quantitatif ou qualitatif d’une hydrolase ou d’un transporteur à l’origine d’une atteinte multiviscérale potentiellement sévère. Certaines de ces pathologies sont accessibles à des traitements mais ces thérapeutiques sont uniquement symptomatiques et ne guérissent pas les patients. Même si le phénomène de surcharge peut expliquer entre autres la symptomatologie observée, la physiopathologie de ces maladies est complexe et non précisément connue. Une meilleure connaissance de ces pathologies pourrait permettre d’améliorer leur prise en charge globale. L’objectif de ce travail était dans un premier temps d’appliquer des techniques « omiques » dans deux groupes de maladies : les mucopolysaccharidoses et la maladie de Fabry. Cette étude a permis la mise en place d’une méthodologie métabolomique non ciblée basée sur une stratégie analytique multidimensionnelle comportant la spectrométrie de masse à haute résolution couplée à la chromatographie liquide ultra-haute performance et la mobilité ionique. Dans les mucopolysaccharidoses, l’étude des voies métaboliques a mis en évidence des modifications dans le métabolisme de plusieurs acides aminés et du système oxydatif du glutathion. Dans la maladie de Fabry, des modifications ont été observées dans l’expression de l’interleukine 7 et du facteur de croissance FGF2. La deuxième partie du travail s’est intéressée à la modulation de l’autophagie dans la maladie de Fabry. Notre étude a montré une diminution du flux autophagique avec un retard d’adressage de l’enzyme au lysosome dans les cellules Fabry. L’inhibition de l’autophagie permet de diminuer l’accumulation du substrat accumulé (Gb3) et améliore l’efficacité de l’enzymothérapie substitutive. En conclusion ce travail a permis une meilleure compréhension des mécanismes physiopathologiques des pathologies lysosomales et a montré la complexité du fonctionnement du lysosome. Ces données permettent d’espérer l’amélioration des stratégies thérapeutiques et diagnostiques dans ces maladies<br>Lysosomal diseases caused by quantitative or qualitative hydrolase or transporter defect induce multiorgan features. Some specific symptomatic treatments are available but they do not cure patients. Pathophysiological bases of lysosomal disease are poorly understood and cannot be due to storage only. A better knowledge of these pathologies could improve their management. The first aim of this study was to apply “omics” strategies in mucopolysaccharidosis and in Fabry disease. This thesis allowed the implementation of an untargeted metabolomic methodology based on a multidimensional analytical strategy including high-resolution mass spectrometry coupled with ultra-high-performance liquid chromatography and ion mobility. Analysis of metabolic pathways showed a major remodeling of the amino acid metabolisms as well as oxidative stress via glutathione metabolism. In Fabry disease, changes were observed in expression of interleukin 7 and FGF2. The second study focused on modulation of autophagy in Fabry disease. In this work, we have shown a disruption of the autophagic process and a delay in enzyme targeting to the lysosome in Fabry disease. Autophagic inhibition reduced accumulation of accumulated substrate (Gb3) and improved the efficiency of enzyme replacement therapy. This work allowed a better knowledge of the physiopathological mechanisms implicated in lysosomal diseases and showed the complexity of lysosome. These data could ameliorate management of these disease and are associated with hope for patients
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Ronconi, Silvia [Verfasser], Ulrich [Akademischer Betreuer] Genschel, and Alfons [Akademischer Betreuer] Gierl. "The Pantothenic Acid and Coenzyme A Pathway in Plants and Archaea : Analysis of Metabolite Levels in Arabidopsis thaliana and Characterization of Archaeal Enzymes for the Synthesis of 4'-phosphopantetheine / Silvia Ronconi. Gutachter: Alfons Gierl. Betreuer: Ulrich Genschel." München : Universitätsbibliothek der TU München, 2006. http://d-nb.info/1058141473/34.
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Darney, Keyvin. "Towards next generation risk assessment of chemicals : bayesian meta-analysis of human variability in metabolism and transporters and application for the derivation of pathway-related uncertainty factors Aggregate exposure of the adult French population to pyrethroids, in Toxicology and Applied Pharmacology 351, July 2018 Inter-ethnic differences in CYP3A4 metabolism: A Bayesian meta-analysis for the refinement of uncertainty factors in chemical risk assessment, in Computational Toxicology 12, November 2019 Bayesian meta-analysis of inter-phenotypic differences in human serum paraoxonase-1 activity for chemical risk assessment, in Environment International 138, May 2020 Human variability in influx and efflux transporters in relation to uncertainty factors for chemical risk assessment, in Food and Chemical Toxicology 140, June 2020." Thesis, Brest, 2020. http://www.theses.fr/2020BRES0013.
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Dans le monde moderne, les humains sont exposés à une vaste gamme de produits chimiques tout au long de leur vie. L'évaluation des risques des substances chimiques pour l'homme revêt une importance capitale pour la santé publique et permet de calculer des niveaux sûrs d'exposition aiguë et chronique pour des sous-groupes de la population humaine, notamment les nouveau-nés, les enfants, les personnes âgées et les populations d’origine géographique et de polymorphismes génétiques différents. L'application des données cinétiques liées aux voies métaboliques pour tenir compte de la variabilité humaine dans la quantification du danger a le potentiel de réduire l'incertitude et de mieux caractériser la variabilité par rapport à l'utilisation traditionnelle des facteurs d'incertitude par défaut. Cette thèse vise à : 1) Quantifier la variabilité humaine au moyen d'une méta-analyse Bayésienne pour plusieurs voies métaboliques de phase I, phase II et transporteurs en utilisant des marqueurs pharmacocinétiques d'exposition aiguë et chronique ou des données d'activité enzymatique pour les substrats spécifiques disponible. 2) Estimer les distributions de variabilité liées aux voies métaboliques et les facteurs d’incertitudes liés à ces voies pour leur intégration future dans les modèles physiologiques basés sur la cinétique pour l'évaluation des risques des produits chimiques pour l'Homme<br>In the modern world, humans are exposed to a wide range of chemicals throughout their life. Human risk assessment of chemicals is of considerable public health importance and provides means to derive safe levels of acute and chronic exposure for subgroups of the human population including neonates, children, elderly and populations of different geographical ancestry and genetic polymorphisms. The application of pathway-related kinetic data to address human variability in the quantification of hazard has potential to reduce uncertainty and better characterize variability compared with the use of traditional default uncertainty factors. This thesis aims to 1) quantify human variability by means of Bayesian meta-analysis for a range of phase I, phase II metabolic pathways and transporters using pharmacokinetic markers of acute and chronic exposure or enzyme activity data from available probe substrate, 2) derive pathway-related variability distributions and pathway-related uncertainty factors for their future integration in physiologically based kinetic models for human risk assessment of chemicals
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"Computational discovery and analysis of metabolic pathways." Thesis, 2010. http://hdl.handle.net/1911/61991.
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Finding novel or non-standard metabolic pathways, possibly spanning multiple species, has important applications in fields such as metabolic engineering, metabolic network analysis, and metabolic network reconstruction. Traditionally, this has been a manual process, but the large volume of metabolic data now available has created a need for computational tools to automatically identify biologically relevant pathways. This thesis presents new algorithms for automatically finding biologically meaningful linear and branched metabolic pathways in multi-genome scale metabolic networks. These algorithms utilize atom mapping data, which provides the correspondence between atoms in the substrates to atoms in the products of a chemical reaction, to find pathways which conserve a given number of atoms between desired start and target compounds.
The first algorithm presented identifies atom conserving linear pathways by explicitly tracking atoms during an exploration of a graph structure constructed from the atom mapping data. The explicit tracking of atoms enables finding branched pathways because it provides automatic identification of the reactions and compounds through which atoms are lost or gained. The thesis then describes two algorithmic approaches for identifying branched metabolic pathways based upon atom conserving linear pathways. One approach takes one linear pathway at a time and attempts to add branches that connect loss and gain compounds. The other approach takes a group of linear pathways and attempts to merge pathways that move mutually exclusive sets of atoms from the start to the target compounds. Comparisons to known metabolic pathways demonstrate that atom tracking causes the algorithms to avoid many unrealistic connections, often found in previous approaches, and return biologically meaningful pathways. While the theoretical complexity of finding even linear atom conserving pathways is high, by choosing the appropriate representations and heuristics, and perhaps due to the structure of the underlying data, the algorithms in this thesis have practical running times on real data. The results also demonstrate the potential of the algorithms to find novel or non-standard pathways that may span multiple organisms.
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CHAN, LUNG-YI, and 湛隆誼. "Metabolic Flux Analysis for Metabolic Pathways of Acetate and Propionate in UASB Anaerobic Tank." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/06223038823611352887.
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碩士<br>國立臺中教育大學<br>科學教育與應用學系環境教育及管理碩士班<br>104<br>In this study, the metabolic flux analysis (MFA) was employed to explore the metabolic pathway and metabolic flux in the Up-flow Anaerobic Sludge Blanket (UASB) asnaerobic tank.
It was found that when the extra addition of acetic acid, acetic acid concentration changes from the starting 9769.04 mg/L, eventually becomes 6930.67 mg/L, acetic acid utilization was 29%; when adding additional acid, a propionic acid concentration changes by the start 6580.98 mg/L, eventually becomes 4704.79 mg/L, acid utilization rate of 28.5%. Metabolism acetic path total 4 reactive, substances involved in the reaction 16; propionic acid metabolic path of a total of 12 reaction formula, which reacted substances 27. Metabolic flux as acetic acid, in the first day, the metabolic flux is the maximum, and later leveled off in the 5th day, have slightly increased metabolic flux at the 6th day, their metabolic flux Min. Propionic acid metabolic flux, when the time for the first day, the maximum value of metabolic flux, the first two days after leveling off at 5th day, the metabolic flux to a minimum. When comparing unit while the starting concentration of organic acids and organic acid concentration units, additional acetic acid and propionic acid, which are flux is maximum at one day and began to fall dramatically, in the first two days of decline slowing ; energy carrier side, the initial concentration of units and unit bacteria, in addition to the fifth of the world outside, ATP propionic acid, AMP and Pathway 3 in H+, metabolic flux and ion energy carrier of between 1.3 to 2.61 times as acetic acid, displayed energy carrier and three ions metabolic flux path is greater than acetic acid. The other units in the unit and the initial concentration of the organic acid decomposing bacteria concentrations, in addition to Article 6 of the world outside, NADH propionic acid, Pathway 3 in H+ and NAD+, between 0.48 to 0.84 acetic metabolic flux of ions as an energy carrier and, the three show the path of the acid ion energy carrier and metabolic flux less than acetic acid.
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Morgan, John Allen. "Analysis of metabolic flux of secondary metabolite pathways in Catharanthus roseus hairy root cultures." Thesis, 1999. http://hdl.handle.net/1911/19420.
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Catharanthus roseus, a tropical plant, produces the valuable anti-cancer compounds, vincristine and vinblastine in extremely low amounts. My research objectives were to examine the response of plant secondary metabolism to various metabolic perturbations, and indicate limitations in the reaction network.
In hairy roots, tabersonine is an important intermediate in the synthesis of vindoline, a monomer in the formation of the anti-cancer compounds that are generally absent from cell and hairy root cultures. To understand how much metabolic flux is directed toward the tabersonine branchpoint, transient profiles of lochnericine and horhammericine in relation to tabersonine in both dark and light-adapted cultures were quantified. The results demonstrated that the accumulation of lochnericine was growth related, similar to tabersonine, and that light repressed the formation of all three alkaloids. Using enzyme inhibitors, the involvement of separate P-450 mononoxygenase dependent enzymes in the biosynthesis of horhammericine and lochnericine was demonstrated. Furthermore, horhammericine and lochnericine were observed to be turned over.
A search for rate limiting regions of the pathway was accomplished through precursor feeding studies. By identifying precursors, which after feeding, significantly enhance the production of alkaloids, the specific precursor branch that is limiting flux to alkaloids can be elucidated. Precursors fed from the terpenoid portion of the pathway at 21 days in the culture cycle were found to enhance the specific yield of tabersonine. This result suggests that during the early stationary phase period (21--24 days) flux limitations may occur upstream of geraniol. On the other hand, the rate-limiting pathway could not be identified during the late growth phase (17--21 days). In part, this was due to the fact that tryptophan served as a precursor of indole acetic acid (IAA), a plant growth regulator. Therefore, changes in indole alkaloid accumulation and root growth due to tryptophan feeding were similar to those induced by exogenously added IAA. Since feeding tryptamine or terpenoid precursors did not significantly enhance indole alkaloid accumulation the rate-limitation may be downstream of loganin.
The metabolic flux distribution between separate alkaloid branches was quantified by monitoring the transient profiles of multiple alkaloids. The flux towards the Iboga alkaloids decreased while the flux to the Aspidosperma alkaloids increased between 12 and 26 days. In contrast, the flux distribution between the Corynanthe branch and the sum of the Iboga and Aspidosperma branches remained unchanged during this period. Despite significant changes in extracellular nutrient levels during this period, the total flux to the alkaloids remained constant between 12 and 26 days.
Through the precursor feeding and biogenetic flux analysis studies, flux limitations to alkaloids likely exist in the terpenoid pathway leading to secologanin. With the tools developed to quantify metabolic flux through a simple model, metabolic flux in metabolically engineered plant cell and tissue cultures can be routinely analyzed.
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"Analysis and engineering of metabolic pathways of Lactobacillus panis PM1." Thesis, 2014. http://hdl.handle.net/10388/ETD-2014-04-1504.
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Lactobacillus panis PM1 is a novel microorganism isolated from thin stillage (TS), a major by-product resulting from bioethanol fermentation, and was selected as the focus of this thesis due to its ability to produce 1,3-propanediol (1,3-PDO) from glycerol. The purpose of this thesis was to understand the central and auxiliary metabolic pathways of L. panis PM1 and to metabolically-engineer strain PM1 based on the improved metabolic knowledge for industrial applications. The 16S rRNA sequence and carbohydrate fermentation pattern were used to classify L. panis PM1 as belonging to the group III lactobacilli; thus, strain PM1 exclusively fermented glucose to lactate, acetate, and/or ethanol, clearly suggesting that its primary metabolism occurred via the 6-phosphogluconate/phosphoketolase (6-PG/PK) pathway. In contrast to typical group III lactobacilli, for fructose fermentation, L. panis PM1 utilized both the 6-PG/PK and the Embden-Meyerhof pathways, showing distinct strain-specific characteristics (more lactate, less acetate, no mannitol, and sporadic growth). In the PM1 strain, auxiliary metabolic pathways governed end-product formation patterns along with central metabolism. Under aerobic conditions, a coupled NADH oxidase-NADH peroxidase system was a determinant for NAD+ regeneration and was regulated by oxygen availability; however, the accumulation of its major end-product, hydrogen peroxide, eventually resulted in oxidative stress. The citrate-to-succinate route was another important auxiliary pathway in L. panis PM1. This route was directly connected to central energy metabolism, producing extra ATP for survival during the stationary phase, and was regulated by the presence of citrate, acetate, and succinate and a transcriptional repressor (PocR). Lactobacilli panis PM1 produced 1,3-PDO via the glycerol reductive route; however, the absence of the glycerol oxidative route restricted the utilization of glycerol to solely that of electron acceptor. Lower ratio of glucose to glycerol, in combination with PocR, repressed the glycerol reductive route, resulting in less 1,3-PDO production. In an effort to metabolically engineer L. panis PM1, an artificial glycerol oxidative pathway was introduced, and the engineered PM1 strain successfully produced a significant amount of important platform chemicals, including 1,3-PDO, lactate, and ethanol, solely from TS. Overall, this thesis reveals the significant feasibility of utilizing L. panis PM1 for industrial fermentative applications.
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CHIA-FU, LIN, and 林嘉福. "Metabolic Flux Analysis for Metabolic Pathways of Butyric in UASB Anaerobic sludge and its Power generation Performance." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/cc9qj4.
Full textAbstract:
碩士<br>國立臺中教育大學<br>科學教育與應用學系環境教育及管理碩士班<br>105<br>With instant development of industry and technology, people's life is convenient, but numerous environmental pollutions have a severe effect on the earth's environment, including industrial waste, water pollution, air pollution, soil pollution and noise pollution. At present, all kinds of environmental problems are paid increasing attention to.
This study uses the anaerobic sludge reclaimed by Up-flow Anaerobic Sludge Blanket (UASB) for experiment, which is mixed with 4 g/L butyric acid to discuss the metabolic pathway and generating efficiency of butyric acid. Secondly, the concentration changes and reaction rate of reactants and intermediate products in the metabolic pathway are analyzed by using metabolic flux, and the metabolic flux is discussed. The results show that after the addition of butyric acid, the butyric acid concentration changes from initial 4138.89 mg/L to final 3086.72 mg/L, the butyric acid utilization rate is 34%. On the metabolic pathway of butyric acid discussed in this study, the initial reactant is butyric acid, the end product is valeric acid, and there are 30 reacting substances. The results show that the metabolic flux of various materials on the metabolic pathway of butyric acid is 0.0038 to 3.3 g/day on Day 1, that decreases to 0.0014 to 1.21 g/day on Day 6. The experimentally measured butyric acid concentration is substituted in the quantitative equation for organic acid decomposing bacteria, the initial concentration of butyric acid decomposing bacteria is 8.91 mg/L, and it increases day after day, it is 87.15 mg/L on Day 6. On Day 0 of experiment with additional butyric acid, the current is maximum 84μA, the average current is 49.1±17.7μA in the experiment with additional butyric acid. The maximum voltage is 140.2 mV on Day 0 of experiment with additional butyric acid, the average voltage is 79.8±33.5 mV.
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Temate, Tiagueu Yvette Charly B., and Tiagueu Yvette C. B. Temate. "Methods for Differential Analysis of Gene Expression and Metabolic Pathway Activity." 2016. http://scholarworks.gsu.edu/cs_diss/102.
Full textAbstract:
RNA-Seq is an increasingly popular approach to transcriptome profiling that uses the capabilities of next generation sequencing technologies and provides better measurement of levels of transcripts and their isoforms. In this thesis, we apply RNA-Seq protocol and transcriptome quantification to estimate gene expression and pathway activity levels. We present a novel method, called IsoDE, for differential gene expression analysis based on bootstrapping. In the first version of IsoDE, we compared the tool against four existing methods: Fisher's exact test, GFOLD, edgeR and Cuffdiff on RNA-Seq datasets generated using three different sequencing technologies, both with and without replicates. We also introduce the second version of IsoDE which runs 10 times faster than the first implementation due to some in-memory processing applied to the underlying gene expression frequencies estimation tool and we also perform more optimization on the analysis.
The second part of this thesis presents a set of tools to differentially analyze metabolic pathways from RNA-Seq data. Metabolic pathways are series of chemical reactions occurring within a cell. We focus on two main problems in metabolic pathways differential analysis, namely, differential analysis of their inferred activity level and of their estimated abundance. We validate our approaches through differential expression analysis at the transcripts and genes levels and also through real-time quantitative PCR experiments. In part Four, we present the different packages created or updated in the course of this study. We conclude with our future work plans for further improving IsoDE 2.0.