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1
Leung, Shuen-yi, and 梁舜頤. "Predicting metabolic pathways from metabolic networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42664317.
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Leung, Shuen-yi. "Predicting metabolic pathways from metabolic networks." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42664317.
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Morrison, Erin S., and Alexander V. Badyaev. "Structuring evolution: biochemical networks and metabolic diversification in birds." BioMed Central, 2016. http://hdl.handle.net/10150/620926.
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Background
Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a “global” carotenoid network – comprising of all known enzymatic reactions among naturally occurring carotenoids – with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds.
Results
We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network – compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution.
Conclusions
The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.
4
Faust, Karoline. "Development, assessment and application of bioinformatics tools for the extraction of pathways from metabolic networks." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210054.
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Genes can be associated in numerous ways, e.g. by co-expression in micro-arrays, co-regulation in operons and regulons or co-localization on the genome. Association of genes often indicates that they contribute to a common biological function, such as a pathway. The aim of this thesis is to predict metabolic pathways from associated enzyme-coding genes. The prediction approach developed in this work consists of two steps: First, the reactions are obtained that are carried out by the enzymes coded by the genes. Second, the gaps between these seed reactions are filled with intermediate compounds and reactions. In order to select these intermediates, metabolic data is needed. This work made use of metabolic data collected from the two major metabolic databases, KEGG and MetaCyc. The metabolic data is represented as a network (or graph) consisting of reaction nodes and compound nodes. Interme- diate compounds and reactions are then predicted by connecting the seed reactions obtained from the query genes in this metabolic network using a graph algorithm.In large metabolic networks, there are numerous ways to connect the seed reactions. The main problem of the graph-based prediction approach is to differentiate biochemically valid connections from others. Metabolic networks contain hub compounds, which are involved in a large number of reactions, such as ATP, NADPH, H2O or CO2. When a graph algorithm traverses the metabolic network via these hub compounds, the resulting metabolic pathway is often biochemically invalid.
In the first step of the thesis, an already existing approach to predict pathways from two seeds was improved. In the previous approach, the metabolic network was weighted to penalize hub compounds and an extensive evaluation was performed, which showed that the weighted network yielded higher prediction accuracies than either a raw or filtered network (where hub compounds are removed). In the improved approach, hub compounds are avoided using reaction-specific side/main compound an- notations from KEGG RPAIR. As an evaluation showed, this approach in combination with weights increases prediction accuracy with respect to the weighted, filtered and raw network.
In the second step of the thesis, path finding between two seeds was extended to pathway prediction given multiple seeds. Several multiple-seed pathay prediction approaches were evaluated, namely three Steiner tree solving heuristics and a random-walk based algorithm called kWalks. The evaluation showed that a combination of kWalks with a Steiner tree heuristic applied to a weighted graph yielded the highest prediction accuracy.
Finally, the best perfoming algorithm was applied to a microarray data set, which measured gene expression in S. cerevisiae cells growing on 21 different compounds as sole nitrogen source. For 20 nitrogen sources, gene groups were obtained that were significantly over-expressed or suppressed with respect to urea as reference nitrogen source. For each of these 40 gene groups, a metabolic pathway was predicted that represents the part of metabolism up- or down-regulated in the presence of the investigated nitrogen source.
The graph-based prediction of pathways is not restricted to metabolic networks. It may be applied to any biological network and to any data set yielding groups of associated genes, enzymes or compounds. Thus, multiple-end pathway prediction can serve to interpret various high-throughput data sets.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
5
Amon, Johannes. "Mining the genomes of actinomycetes : identification of metabolic pathways and regulatory networks." kostenfrei, 2010. http://d-nb.info/1002175534/34.
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Meggiato, Alberto <1987>. "Comparing metabolic networks at pathway level." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8501.
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Metabolic pathway comparison between different species is important to discover the differences in a metabolic function developed during the evolutionary process. This kind of analysis may allow the detection of important information useful also in drug engineering and medical science.
In this thesis we propose a method for metabolic pathways comparison based on their representation as sets and multisets of chemical reactions. The information is taken from the KEGG database because it has a standardised representation of each pathway in the different organisms.
The pathway comparison technique is then used in the context of metabolic networks comparison in order to solve the problems due to the size of the compared networks.
The proposed methods have been implemented in Java as part of a tool for metabolic networks comparison.
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Dall'Olio, Giovanni Marco 1983. "Applications of network theory to human population genetics : from pathways to genotype networks." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/133454.
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In this thesis we developed two approaches to study positive selection and genetic
adaptation in the human genome. Both approaches are based on applications of
network theory.
In the first approach, we studied how the signals of selection are distributed among
the genes of a metabolic pathway. We use a network representation of the Asparagine
N-Glycosylation pathway, and determine if given positions are more likely to be
involved in selection events. We determined a different distribution of signals
between the upstream part of this pathway, which has a linear structure and is
involved in a conserved process, and the downstream part of the pathway, which has a
complex network structure and is involved in adaptation to the environment.
In the second approach, we applied a network representation of the set of genotypes
observed in a population (Genotype Network) to next-generation sequencing data.
The main result is a genome-wide picture of how the populations of the 1000
Genomes dataset have explored the genotype space. We found that the genotype
networks of coding regions tend to be more connected and more expanded in the
space than non coding regions, and that simulated sweeps have similar patterns
compared to simulated neutral regions.En esta tesis hemos desarrollado dos métodos para estudiar los patrones de selección positiva y adaptación genética en el genoma humano. Ambos métodos se basan en aplicaciones de teoría de redes. En la primera aplicación hemos investigado cómo las señales de selección están distribuidas a lo largo de una ruta metabólica. Hemos utilizado una representación de la ruta de N-Glicosilación, para estudiar si determinadas posiciones tienen más probabilidades de estar implicadas en eventos de selección positiva. Hemos comparado la distribución de las señales de selección entre la primera parte de la ruta metabólica, que tiene una estructura muy lineal y está involucrada en un proceso conservado, y la segunda parte de la ruta, que tiene una estructura de redes compleja y está involucrada en adaptación al ambiente. En la segunda aplicación hemos aplicado el concepto de redes de genotipos (Genotype Networks) a datos de secuencia de nueva generación. El resultado es un análisis completo de cómo las poblaciones de 1000 Genomas han explorado el espacio de genotipo. Las redes de genotipos de regiones codificantes suelen estar más conectadas y más expandidas que las regiones no-codificantes. Además, por medio de simulaciones hemos observado los patrones esperados para eventos de selección positiva.
8
Cakmak, Ali. "Mining Metabolic Networks and Biomedical Literature." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1223490345.
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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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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.
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, gEFM, that incorporates structural information of the underlying network to enumerate all EFMs. The results show that gEFM 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, PreProPath, 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 PreProPath can successfully identify high ethanol production pathways across multiple growth rates, and for succinate production in Escherichia coli (E. coli) as published in the literature. We also develop an algorithm, Dominant-Edge Pathway, 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 Zymomonas mobilis (Z. mobilis), E. coli and rat liver cell.
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.
10
Xiang, Lu, and 项路. "Finding phenotype related pathways via biological networks comparison." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B4715262X.
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Why some species (or strains of a species) exhibit certain phenotypes (e.g. aerobic, anaerobic, pathogenic etc.) while the others do not is an important question to be answered. Apart from the conventional genomic study, studying the metabolism of the two groups of species may discover the corresponding pathways that are conserved in one group but not in the other. However, only a few tools provide functions to compare two groups of metabolic networks which are usually limited to the reaction level, not the pathway level.
In this dissertation, a problem named DMP (Differentiating Metabolic Pathway) problem was formed. Given two groups of metabolic networks, it aims at finding conserved pathways exist in first group, but not the second group. The problem also captures the mutation in similar pathways and derives a measurement (p-value and e-score) for evaluating the significance of the pathways.
An algorithm, DMPFinder, was developed to solve the DMP problem. Experimental results show that DMPFinder is able to identify pathways that are critical for the first group to exhibit a certain phenotype which is absent in the other group. Some of these pathways cannot be identified by other tools which only consider reaction level or do not take into account possible mutations among species.published_or_final_version
Computer Science
Master
Master of Philosophy
11
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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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.
13
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.Ph. D.
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Ajjolli, Nagaraja Anamya. "Modelling of Metabolic Pathways for Biomolecule Production in Cell-Free Systems." Thesis, La Réunion, 2020. http://www.theses.fr/2020LARE0004.
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Les systèmes acellulaires sont en train de devenir une puissante plateforme de biofabrication. L'optimisation de systèmes acellulaires est importante pour obtenir un rendement maximal. L'optimisation expérimentale, en laboratoire humide, est longue et coûteuse. Différents types de modélisations permettant d'optimiser la voie d'intérêt, en un temps plus court et à moindre coût, sont apparus au cours des dernières décennies. Dans cette étude, nous avons testé deux approches : systémique à travers la mise en œuvre de réseaux de neurones, et analytique à travers l™utilisation d™équations différentielles. Dans une première étape, un modèle à réseau de neurones artificiels a été construit pour prédire le flux de métabolites à travers la voie. Dans une seconde étape, une nouvelle méthodologie, appelée GC-ANN, a été développée pour sélectionner des équilibres enzymatiques optimaux, et rentables, pour des valeurs de flux plus élevées. Cette approche a permis une amélioration inattendue du flux, jusqu'à 63%, validée in vitro. Dans une troisième étape, un modèle cinétique a été construit, et l™estimation des paramètres cinétiques pour les enzymes sélectionnées a été réalisée, afin de reproduire les conditions expérimentales. Enfin, liée à l'un des produits chimiques les plus exigeants en termes de production, la voie de synthèse du malate a été modélisée avec succès dans un système acellulaires. Même si de nombreuses études ont été réalisées, la biofabrication a grande échelle n'est pas encore possible pour le malate. La combinaison du système acellulaire et de la modélisation pourrait aider à réaliser la bioproduction du malate. De manière plus générale, cette thèse explore différentes approches de modélisations mathématiques, et leurs limites, pour l'optimisation de voies métaboliquesCell-free systems (CFS) are emerging as a powerful platform for biomanufacturing. The optimisation of the cell-free system is important to achieve maximum yield. The experimental optimisation is time-consuming and expensive. Different kinds of modelling emerged in the last decades, helping to optimise the pathway of interest in a shorter time at a low cost. In this study, we tested two approaches: systemic through the implementation of neural networks, and analytical through the use of differential equations. In the first step, an artificial neural network model was built to predict the flux through the pathway, and in the second step, a new methodology termed GC-ANN was developed to select optimum and cost-efficient enzyme balances for higher flux. This approach showed unexpected betterment of flux estimation, up to 63%. In the third step, a kinetic model was built and estimation of kinetic parameters for selected enzymes was achieved to replicate experimental conditions. Finally, linked to one of the most demanding chemicals, malate synthesis pathway was successfully modelled in the cell-free system. Even though many studies have been performed, biomanufacturing has not yet been possible for malate. The combination of the cell-free system and modelling could help achieve the biomanufacturing of malate. Overall, this thesis explores different mathematical modelling approaches, and their limits, for optimising metabolic pathways
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Brum, Itaraju Junior Baracuhy. "Ferramentas de bioinformática para proteômica." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/314739.
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Orientador: Eduardo GalembeckDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia
Made available in DSpace on 2018-08-18T00:57:48Z (GMT). No. of bitstreams: 1 Brum_ItarajuJuniorBaracuhy_M.pdf: 1893501 bytes, checksum: 59afb345a47fb8e963452a41b2327f1c (MD5) Previous issue date: 2007
Resumo: A área de proteômica visa estudar um conjunto completo de proteínas expressas por um organismo ou tecido numa dada situação, através da identificação e quantificação. Apesar de limitações nas técnicas disponíveis, vem se aumentando o volume de informações oriundos desta área, situação que exige o emprego de ferramentas computacionais para permitir o uso eficiente de dados disponíveis, além de buscar-se novas formas de análise destes. Este projeto visa o desenvolvimento de ferramentas de bioinformática para aplicação em proteômica. Estas ferramentas abrangem as seguintes aplicações: Cálculo Teórico de Ponto Isoelétrico e Peso Molecular de seqüências de aminoácidos, eletroforese-bidimensional teórica, digestão teórica e simulação de eletroforese e identificação de peptídeos, ferramenta para análise de Vias Metabólicas a partir de dados de proteômica
Abstract: The proteomics field aims to study sets of proteins expressed in a cell or tissue, according to a specific situation, through protein identification and quantification. Though technical limitations do exist, the amount of information derived from this field increases each day. And so, there is a need for employing computational tools that enable efficient analysis of data. This project aims developing bioinformatics tools for application in proteomics. The tools here presented comprehend the following tasks: theoretical computation of isoeletric point and molecular weight of aminoacid sequences, theoretical two-dimensional electrophoresis, theoretical triptic digestion and electrophoresis simulation for peptide identification, and analysis of metabolic pathways with proteomics data
Mestrado
Bioquimica
Mestre em Biologia Funcional e Molecular
16
Coimbra, Klein Cecilia. "Bioinformatic study of the metabolic dialog between a non-pathogenic trypanosomatid and its endosymbiont with evolutionary and functional goals." Phd thesis, Université Claude Bernard - Lyon I, 2013. http://tel.archives-ouvertes.fr/tel-01050338.
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In this thesis, we presented three main types of analyses of metabolism, most of which involved symbiosis: metabolic dialogue between a trypanosomatid and its symbiont, comparative analyses of metabolic networks and exploration of metabolomics data. All of them were essentially based on genomics data where metabolic capabilities were predicted from the annotated genes of the target organism, and were further refined with other types of data depending on the aim and scope of each investigation. The metabolic dialogue between a trypanosomatid and its symbiont was explored with functional and evolutionary goals which included analysing the classically defined pathways for the synthesis of essential amino acids and vitamins, exploring the genome-scale metabolic networks and searching for potential horizontal gene transfers from bacteria to the trypanosomatids. The comparative analyses performed focused on the common metabolic capabilities of different lifestyle groups of bacteria and we proposed a method to automatically establish the common and the group-specific activities. The application of our method on metabolic stories enumeration to the yeast response to cadmium exposure was a validation of this approach on a well-studied biological response to stress. We showed that the method captured well the underlying knowledge as it extracted stories allowing for further interpretations of the metabolomics data mapped into the genome-scale metabolic model of yeast
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Ritter, Ashlyn D. "The Influence of the Insulin-Like Gene Family and Diet-Drug Interactions on Caenorhabditis elegans Physiology: A Dissertation." eScholarship@UMMS, 2015. https://escholarship.umassmed.edu/gsbs_diss/872.
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Aging can be defined as the accumulation of changes affecting the maintenance of homeostatic processes over time, leading to functional decline and increased risk for disease and death. In its simplicity, aging is the systemwide deterioration of an organism. Genetic studies have identified many potential molecular mechanisms of aging including DNA damage, telomere shortening, mitochondrial dysfunction, increased oxidative stress, uncontrolled inflammation, and hormone dysregulation (reviewed in [1]). However, in reality, aging is likely to be a combination of some (or potentially all) of these mechanisms.
Interestingly, aging and metabolism are tightly coordinated. Aging is a major contributor to metabolic decline and related diseases, including type 2 diabetes, metabolic syndrome, and cancer. One of the best characterized metabolic pathways implicated in aging is the insulin/IGF-1 signaling (IIS) pathway. Downstream signaling components of the IIS pathway receptor have been well studied and include an interconnected network of signaling events that regulate many physiological outputs. However, less is known about the role of upstream signaling components and how intracellular pathways and physiology are regulated accordingly. In Part I, I present my work towards understanding upstream IIS pathway components using a systems biology approach. The goal of this study is to gain insight into the redundancy and specificity of the insulin gene family responsible for initiating IIS pathway activity in Caenorhabditis elegans. The information gained will serve as a foundation for future studies dissecting the molecular mechanisms of this pathway in efforts to uncouple the downstream signaling and physiological outputs.
The clear impact of metabolism on aging and disease stimulated questions regarding the potential of promoting health and longevity through diet and dietary mimetics. Recent findings indicate reduced food intake, meal timing and nutritional modulation of the gut microbiome can ameliorate signs of aging and age-associated diseases. Aging, therefore, is also the result of dynamic and complex interplay between genes of an organism and its environment. In Part II, I will discuss my efforts to gain insight into how diet influences aging. This preliminary study has demonstrated that diet can affect lifespan in the model organism, C. elegans. Additionally, we observe diet-specific effects on drug efficacy that, in turn, modulates C. elegans lifespan and reproduction. The implications of these experiments, while limited, illustrate a potentially greater role in diet- and drug-mediated effects on lifespan.
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Ritter, Ashlyn D. "The Influence of the Insulin-Like Gene Family and Diet-Drug Interactions on Caenorhabditis elegans Physiology: A Dissertation." eScholarship@UMMS, 2008. http://escholarship.umassmed.edu/gsbs_diss/872.
Full textAbstract:
Aging can be defined as the accumulation of changes affecting the maintenance of homeostatic processes over time, leading to functional decline and increased risk for disease and death. In its simplicity, aging is the systemwide deterioration of an organism. Genetic studies have identified many potential molecular mechanisms of aging including DNA damage, telomere shortening, mitochondrial dysfunction, increased oxidative stress, uncontrolled inflammation, and hormone dysregulation (reviewed in [1]). However, in reality, aging is likely to be a combination of some (or potentially all) of these mechanisms.
Interestingly, aging and metabolism are tightly coordinated. Aging is a major contributor to metabolic decline and related diseases, including type 2 diabetes, metabolic syndrome, and cancer. One of the best characterized metabolic pathways implicated in aging is the insulin/IGF-1 signaling (IIS) pathway. Downstream signaling components of the IIS pathway receptor have been well studied and include an interconnected network of signaling events that regulate many physiological outputs. However, less is known about the role of upstream signaling components and how intracellular pathways and physiology are regulated accordingly. In Part I, I present my work towards understanding upstream IIS pathway components using a systems biology approach. The goal of this study is to gain insight into the redundancy and specificity of the insulin gene family responsible for initiating IIS pathway activity in Caenorhabditis elegans. The information gained will serve as a foundation for future studies dissecting the molecular mechanisms of this pathway in efforts to uncouple the downstream signaling and physiological outputs.
The clear impact of metabolism on aging and disease stimulated questions regarding the potential of promoting health and longevity through diet and dietary mimetics. Recent findings indicate reduced food intake, meal timing and nutritional modulation of the gut microbiome can ameliorate signs of aging and age-associated diseases. Aging, therefore, is also the result of dynamic and complex interplay between genes of an organism and its environment. In Part II, I will discuss my efforts to gain insight into how diet influences aging. This preliminary study has demonstrated that diet can affect lifespan in the model organism, C. elegans. Additionally, we observe diet-specific effects on drug efficacy that, in turn, modulates C. elegans lifespan and reproduction. The implications of these experiments, while limited, illustrate a potentially greater role in diet- and drug-mediated effects on lifespan.
19
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.
20
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 tumoralIn 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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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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Olivieri, Bianca Ferreira. "Análise multivariada com dados genômicos e transcriptômicos para perfil de ácidos graxos da carne em bovinos Nelore terminados em confinamento /." Jaboticabal, 2019. http://hdl.handle.net/11449/183053.
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Orientador: Fernando Sebastián Baldi ReyResumo: A compreensão de processos regulatórios e organização molecular dos organismos vivos progrediram consideravelmente na última década. As metodologias também evoluíram com o sequenciamento de DNA e RNA e de ferramentas genômicas permitindo a análise de centenas ou milhares de genes, proteínas ou metabólitos. O uso simultâneo dessas informações auxilia na obteção de informações relevantes sobre as variáveis que envolvem as variações fenotípicas de características de interesse. O objetivo do presente estudo foi integrar dados fenotípicos, genotípicos e transcriptômicos em busca de aprimoramento sobre os mecanismos genéticos e metabólicos que determinam o perfil de ácidos graxos na carne de bovinos Nelore, a fim de contribuir para o melhoramento da composição de ácidos graxos da carne. Foram utilizados machos da raça Nelore terminados em confinamento, abatidos com média de idade 24 meses. Amostras do músculo L. thoracis, entre a 12ª a 13ª costela foram coletadas para as análises de perfil de ácidos graxos, extração de RNA e de DNA. Os resultados foram apresentados nos capítulos 2 e 3. No capítulo 2, o objetivo foi identificar genes diferencialmente expressos pelo método RNA-seq e perfil de ácidos graxos no músculo L. thoracis com uso de componentes principais (principal components: PC). Foram selecionados dois grupos de 10 animais, os quais possuíam valores de PC1 e PC2 extremos (Alto x Baixo) para os grupos somatórios de ácidos graxos (AG): ácidos graxos saturados (AGS), ácidos g... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: The understanding of regulatory processes and molecular organization of organisms has progressed considerably in the last 10 years.The methodologies also evolved with the sequencing of DNA, RNA and genomic tools allowing the analysis a lot of genes, proteins or metabolites. The simultaneous use of this information should help to obtain relevant information about the variables that result the phenotypic variations of traits of interest. The objective of the present study was to integrate phenotypic, genotypic and transcriptomic studies in order to clarify the genetic and metabolic mechanisms that determine the fatty acid profile in Nelore beef, in order to contribute to the improvement of the fatty acid composition of the meat. Nelore males were used in feedlot, coming from farms that integrate three breeding programs and slaughtered with an average of 24 months. Samples of the L. thoracis muscle between the 12th to 13th rib were collected for analysis of fatty acid profile, RNA and DNA extraction. The results were presented in chapters 2 and 3. In chapter 2, the objective was to identify genes differentially expressed by RNA-seq method and fatty acid profile in the L. thoracis muscle with the use of Principal Components (PC). Two groups of 10 animals were selected, which had PC1 and PC2 extreme values (High x Low) for the fatty acids (FA) groups: saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), omega 3 (n-3) and omega 6 (n-6... (Complete abstract click electronic access below)
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Chou, I.-Chun. "Parameter estimation and network identification in metabolic pathway systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26513.
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Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2009.Committee Chair: Voit, Eberhard O.; Committee Member: Borodovsky, Mark; Committee Member: Butera, Robert; Committee Member: Kemp, Melissa; Committee Member: Park, Haesun. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Liesecke, Franziska. ""Coupable par association" : exploitation de ressources transcriptomiques pour la construction de réseaux de co-expression de gènes dédiés à l'élucidation de voies cellulaires." Electronic Thesis or Diss., Tours, 2018. http://www.theses.fr/2018TOUR3802.
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Avec l’essor de technologies transcriptomiques à haut débit, une grande quantité de données a été générée.Ce travail est axé sur la réutilisation de ces données publiquement disponibles, pour la construction deréseaux de co-expression de gènes et leur exploitation dans l’élucidation de voies métaboliques et designalisation. Ce travail, dont l’objectif a été de fournir une méthodologie pour l’identification de gènescandidats, est axé autour de trois aspects : (i) le choix d’une distance appropriée pour évaluer la similarité deprofils d’expression entre gènes, (ii) l’identification du nombre d’échantillons minimal à inclure dans lamatrice d’expression, et (iii) la comparaison de réseaux, de type Pathway Level Co-expression (PLC) dedifférentes espèces et construits, avec les gènes codant les acteurs de la voie Multi Step Phosphorelay (MSP)comme guidesWith the rise of high throughput technologies able to provide a large-scale view of transcriptomes, a highamount data has been produced. This work focuses on publicly available data reuse to construct gene coexpressionnetworks for metabolic or signalling pathways elucidation. The final aim of this work, was toprovide a methodology for candidate gene identification and thus focuses on (i) the choice of an appropriateddistance to evaluate similarity between gene expression profiles, (ii) the identification of a minimal numberof samples to be included in the expression matrix in order to construct robust co-expression networks, andfinally (iii) the comparison of targeted co-expression networks built with the Pathway Level Co-expression(PLC) approach and using guide genes coding actors of the Multi Step Phosphorelay (MSP) among differentspecies
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Kaur, Dipendra. "Mapping and Filling Metabolic Pathway Holes." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/biology_theses/14.
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The network-mapping tool integrated with protein database search can be used for filling pathway holes. A metabolic pathway under consideration (pattern) is mapped into a known metabolic pathway (text), to find pathway holes. Enzymes that do not show up in the pattern may be a hole in the pattern pathway or an indication of alternative pattern pathway. We present a data-mining framework for filling holes in the pattern metabolic pathway based on protein function, prosite scan and protein sequence homology. Using this framework we suggest several fillings found with the same EC notation, with group neighbors (enzymes with same EC number in first three positions, different in the fourth position), and instances where the function of an enzyme has been taken up by the left or right neighboring enzyme in the pathway. The percentile scores are better when closely related organisms are mapped as compared to mapping distantly related organisms.
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Dosi, Harsh. "Patway Pioneer: A Web-Based Metabolic Network Layout Extension." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/2797.
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The number and complexity of genome-scale metabolic networks is increasing as new systems are characterized and existing models are extended. Tools for visualization of network topology and dynamics are not keeping pace and are becoming a bottleneck for advancement. Specically, visualization tools are not optimized for human comprehension and often produce layouts where important interactions and inherent organization are not apparent. Researchers seek visualizations in which the network is partitioned into functional modules and compartments, arranged in linear, cyclic, or branching schema as appropriate, and most importantly, can be customized to their needs and shared. Challenges include the wide diversity in the biological standards, layout schemas, and network formats. This work introduces a web-based tool that provides this functionality as an extension to the existing web-based tool called Pathway Pioneer (www.pathwaypioneer.org). Pathway Pioneer is a dynamic web-based system built as a front-end graphical user interface to the ux balance analysis tool COBRA-py. Full click-and-drag layout editing capabilities are added allowing each metabolite and reaction to be translated and rotated as connecting edges are automatically redrawn. Initial automated layouts for new models maximize planarity while clustering reactions based on subsystem module and compartment. The users are given maximum exibility to design specific layouts while details of convention, such as joined in and out of reaction edges, disconnected co-factors, and connected metabolites, are automatically handled. Layouts can be shared among researchers and explored to archival Symphony format, along with pdf and png images. This tool provides the user with a semi automatic layout algorithm along with graphical and interactive tools to fully customize the network layout for optimal comprehension. Export capabilities are compatible with COBRA-py and other visualization tools. It provides a platform for share model development and innovation to the community, sharpening the R&D curve, and improving the turn-around time of model reconstruction at the genome-scale. Pathway Pioneer provides unique capabilities in customization of metabolic networks that complements and overcomes limitations of the growing body of existing tools.
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McArthur, George Howard IV. "Orthogonal Expression of Metabolic Pathways." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3087.
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Microbial metabolism can be tailored to meet human specifications, but the degree to which these living systems can be repurposed is still unknown. Artificial biological control strategies are being developed with the goal of enabling the predictable implementation of novel biological functions (e.g., engineered metabolism). This dissertation project contributes genetic tools useful for modulating gene expression levels (extending promoters with UP elements) and isolating transcription and translation of engineered DNA from the endogenous cellular network (expression by orthogonal cellular machinery), which have been demonstrated in Escherichia coli for the production of lycopene, a 40-carbon tetraterpene carotenoid with antioxidant activity and a number of other desirable properties.
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Louca, Stilianos. "The ecology of microbial metabolic pathways." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/59313.
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Microbial metabolic activity drives biogeochemical cycling in virtually every ecosystem. Yet, microbial ecology and its role in ecosystem biochemistry remain poorly understood, partly because the enormous diversity found in microbial communities hinders their modeling. Despite this diversity, the bulk of global biogeochemical fluxes is driven by a few metabolic pathways encoded by a small set of genes, which through time have spread across microbial clades that can replace each other within metabolic niches. Hence, the question arises whether the dynamics of these pathways can be modeled regardless of the hosting organisms, for example based on environmental conditions. Such a pathway-centric paradigm would greatly simplify the modeling of microbial processes at ecosystem scales.
Here I investigate the applicability of a pathway-centric paradigm for microbial ecology. By examining microbial communities in replicate "miniature" aquatic environments, I show that similar ecosystems can exhibit similar metabolic functional community structure, despite highly variable taxonomic composition within individual functional groups. Further, using data from a recent ocean survey I show that environmental conditions strongly explain the distribution of microbial metabolic functional groups across the world's oceans, but only poorly explain the taxonomic composition within individual functional groups. Using statistical tools and mathematical models I conclude that biotic interactions, such as competition and predation, likely underlie much of the taxonomic variation within functional groups observed in the aforementioned studies. The above findings strongly support a pathway-centric paradigm, in which the distribution and activity of microbial metabolic pathways is strongly determined by energetic and stoichiometric constraints, whereas additional mechanisms shape the taxonomic composition within metabolic guilds.
These findings motivated me to explore concrete pathway-centric mathematical models for specific ecosystems. Notably, I constructed a biogeochemical model for Saanich Inlet, a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones. The model describes the dynamics of individual microbial metabolic pathways involved in carbon, nitrogen and sulfur cycling, and largely explains geochemical depth profiles as well as DNA, mRNA and protein sequence data. This work yields insight into ocean biogeochemistry and demonstrates the potential of pathway-centric models for microbial ecology.Science, Faculty of
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Semjonous, Nina M. "Metabolic characterisation of hypothalamic appetite pathways." Thesis, Imperial College London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486552.
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The Comprehensive Laboratory Animal Monitoring System (CLAMS) is an automated cage system that allows continuous and simultaneous measurements of food intake, activity, oxygen consumption, carbon dioxide production and respiratory exchange ratio. In this thesis, I have developed and optimised the CLAMS as a tool for measuring metabolic parameters within the laboratory. I have then used this system to characterise the effect of a single ICV injection of hypothalamic neuropeptides involved in energy balance. I examined the effect of the orexigenic neuropeptides neuropeptide Y (NPY), agouti-related protein (AgRP), melanin concentrating hormone (MCH), orexin-A and ghrelin in satiated male Wistar rats, whilst the anorexigenic neuropeptides a-melanocyte stimulating hormone (a-MSH), corticotrophin-releasing hormone (CRH) and neuromedin U (NMU) were given to overnight fasted animals. Some peptides exhibited a co-ordinated metabolic response. For example, NPY and orexin-A both stimulated food intake but had opposing effects on energy expenditure. Among the anorectic peptides examined, CRH and NMU showed contrasting temporal effects on feeding and activity, despite the effects of NMU being though to occur via the release of CRH. These studies demonstrate that the CLAMS are a useful tool in determining the roles of well characterised peptides in energy balance. I then went on to use the CLAMS to aid in the' characterisation of the recently discovered . hypothalamic neuropeptide neuromedin S (NMS). Centrally, NMS is specifically expressed in the hypothalamic suprachiasmatic nucleus and is structurally similar to the neuropeptide NMU. Both peptides bind to the NMU1R and NMU2R with comparable affinities. I have used the CLAMS to characterise the effects of intrahypothalamic injection of NMS on food intake, activity and energy expenditure. NMS dose dependently reduced food intake more potently than NMU. This inhibition of feeding was associated with an increase in stress-related behaviours, such as grooming. Microinjection of NMS directly into the PVN also activated the HPA axis at a similar magnitude to NMU, as demonstrated by elevated plasma ACTH and corticosterone. This work suggests that NMS may be involved in the regulation of energy homeostasis and the stress response.
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Favaro, Elena. "Cancer metabolic pathways regulated by hypoxia." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:a148c7a8-cb0c-4760-8073-678299fd837d.
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Metabolic reprogramming in cancer cells provides energy and important metabolites required to sustain tumour proliferation. Hypoxia represents a hostile environment that can encourage these transformations and other adaptive responses that contribute to poor prognosis and resistance to radiation and chemotherapy. Hypoxic signatures associated with worse prognosis were previously derived in different cancer types, and led to the selection of two candidates with potential metabolic implications, namely the mir210-putuative target iron-sulfur scaffold protein ISCU and glycogen phosphorylase (PYGL). Firstly, it was verified that the hypoxia-induced miR-210 targets ISCU. Iron-sulfur clusters represent cofactors for key enzymes involved in Krebs cycle and electron transport chain. Downregulation of ISCU was associated with the induction of reactive oxygen species (ROS) and reduced mitochondrial complex I and aconitase activity, caused a shift to glycolysis in normoxia and enhanced cell survival. This indicates that the induction of a single microRNA, miR-210, can mediate a new mechanism of adaptation to hypoxia, by regulating mitochondrial function via iron-sulfur cluster metabolism and free radical generation. Secondly, it was found that changes in PYGL expression reflect a characteristic upregulation of glycogen metabolism in hypoxia in both tumour xenografts and in cancer cell lines. More specifically, hypoxia stimulates glycogen accumulation and its utilisation, as well as the concurrent upregulation of several glycogen-metabolizing enzymes such as glycogen synthase (GYS1) and PYGL. PYGL depletion led to glycogen accumulation in hypoxic cells, increased intracellular levels of ROS, and a reduction in proliferation due to a p53-dependent induction of senescence. Furthermore, depletion of PYGL was associated with markedly impaired tumorigenesis in vivo. Finally, metabolic analyses indicated that glycogen degradation by PYGL is important for the optimal functioning of the pentose phosphate pathway. Collectively, this study shows the contribution of two important pathways to the metabolic adaptations induced by hypoxia.
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Oswal, Vipul Kantilal. "Pathway Pioneer: Heterogenous Server Architecture for Scientific Visualization and Pathway Search in Metabolic Network Using Informed Search." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/2775.
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There is a huge demand for analysis and visualization of the biological models. PathwayPioneer is a web-based tool to analyze and visually represent complex biological models. PathwayPioneer generates the initial layout of the model and allows users to customize it. It is developed using .net technologies (C#) and hosted on the Internet Information Service (IIS) server. At back-end it interacts with python-based COBRApy library for biological calculations like Flux Balance Analysis (FBA). We have developed a parallel processing architecture to accommodate processing of large models and enable message-based communication between the .net webserver and python engine. We compared the performance of our online system by loading a website with multiple concurrent dummy users and performed different time intensive operations in parallel.
Given two metabolites of interest, millions of pathways can be found between them even in a small metabolic network. Depth First Search or Breadth First search algorithm retrieves all the possible pathways, thereby requiring huge computational time and resources. In Pathway Search using Informed Method, we have implemented, compared, and analyzed three different informed search techniques (Selected Subsystem, Selected Compartment, and Dynamic Search) and traditional exhaustive search technique. We found that the Dynamic approach performs exceedingly well with respect to time and total number of pathways searches. During our implementation we developed a SBML parser which outperforms the commercial libSBML parser in C#.
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Lo, Ko-Yun. "Analysis of metabolic networks." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526488.
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Rohrschneider, Markus. "Visualization of Metabolic Networks." Doctoral thesis, Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-160528.
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The metabolism constitutes the universe of biochemical reactions taking place in
a cell of an organism. These processes include the synthesis, transformation, and
degradation of molecules for an organism to grow, to reproduce and to interact
with its environment. A good way to capture the complexity of these processes
is the representation as metabolic network, in which sets of molecules are transformed
into products by a chemical reaction, and the products are being processed
further. The underlying graph model allows a structural analysis of this network
using established graphtheoretical algorithms on the one hand, and a visual representation
by applying layout algorithms combined with information visualization
techniques on the other.
In this thesis we will take a look at three different aspects of graph visualization
within the context of biochemical systems: the representation and interactive
exploration of static networks, the visual analysis of dynamic networks, and the
comparison of two network graphs. We will demonstrate, how established infovis
techniques can be combined with new algorithms and applied to specific problems
in the area of metabolic network visualization.
We reconstruct the metabolic network covering the complete set of chemical reactions
present in a generalized eucaryotic cell from real world data available from
a popular metabolic pathway data base and present a suitable data structure. As
the constructed network is very large, it is not feasible for the display as a whole.
Instead, we introduce a technique to analyse this static network in a top-down
approach starting with an overview and displaying detailed reaction networks on
demand. This exploration method is also applied to compare metabolic networks
in different species and from different resources. As for the analysis of dynamic
networks, we present a framework to capture changes in the connectivity as well
as changes in the attributes associated with the network’s elements.
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Huda, Shahzya Shahnaz. "Metabolic pathways in normal and pre-eclamptic pregnancies." Thesis, University of Glasgow, 2011. http://theses.gla.ac.uk/2537/.
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Maternal metabolism undergoes dramatic changes in pregnancy in order to sustain and nourish the developing fetus. During healthy pregnancy the mother goes from an anabolic state in early pregnancy to a state of catabolism in late pregnancy with increased lipolysis together with a significant reduction in insulin sensitivity. Pre-eclampsia (PE) characterised by hypertension and proteinuria is a major cause of maternal and perinatal morbidity. There is acute ‘atherosis’ in PE placenta, and lipid accumulation within glomerular cells and liver. PE women have an early, excessive triglyceride and free fatty acid (FFA) rise and greater cardiovascular disease (CVD) risk in later life. The cause of these lipid abnormalities in PE is unknown but disordered adipocyte function including exaggerated lipolysis and aberrant release of adipokines (such as IL-6 and TNF alpha) is a major candidate pathway. Elevations in FFAs, and pro-inflammatory adipokines could underpin the oxidative stress, endothelial dysfunction, inflammation, and insulin resistance - characteristic features of PE. The aims of this thesis were to acquire a better understanding of lipid metabolism and function in normal pregnancy, to determine if adipocyte function was altered in PE and, if so, to establish mechanisms. In addition I planned to corroborate epidemiological evidence of increased future CVD risk and to establish which risk factors accounted for this increased risk. I collected subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) biopsies in non-labouring pregnant healthy (n=31) and PE (n=14) women who underwent caesarean section. Maternal blood was collected prior to delivery and phenotyping of the mother was performed including plasma assay for cholesterol, triglyceride, HDL-cholesterol, IL-6, TNF-α, leptin, adiponectin, high sensitivity CRP, glucose and insulin concentrations. Maternal BMI at booking, standardised blood pressure measurements and birth weight centile were also recorded. I determined ex vivo lipolytic activity (basal, isoprotenerol stimulated and insulin suppression of lipolysis) and adipokine production in response to lipopolysaccharide (LPS) stimulation from these biopsies. The gene expression of relevant target genes and macrophage densities in each adipose depot by immunocytochemistry (ICC) was also performed. In addition I performed carotid ultrasound assessment of women with a previous history of PE (n=31) and matched controls (n=29). Ethical approval was obtained from Glasgow Royal Infirmary LREC and all patients gave their informed consent. I found that in normal pregnancy, adipocyte lipolytic function is independent of maternal BMI. Adipocyte lipolytic function of SAT and VAT are also independent of each other. Adipose tissue is very metabolically flexible and the rate of whole body lipolysis is still insulin sensitive in late gestation. VAT is more closely related to markers of maternal insulin resistance (IR) and is more sensitive to catecholamine stimulation and less sensitive to insulin suppression of lipolysis than SAT, the basis of the “portal paradigm”. Increasing BMI is associated with an increase in VAT cell size, with increased lipolysis and an increase in pro-inflammatory adipokines, a potential mechanism through which increasing obesity could predispose to metabolic complications of pregnancy. In contrast SAT cell size is not closely related to BMI and this may reflect the adaptation of this depot to increasing fat mass through both hypertrophy and hyperplasia, a metabolically advantageous response. TNF alpha is an important correlate of basal lipolysis in SAT. In PE there is decreased insulin sensitivity of both SAT and VAT compared to controls as calculated by the fat cell insulin sensitivity index (or responsiveness to insulin once the tissue is stimulated by isoproterenol). This would potentially make a significant impact on total circulating FFA as almost 60% of circulating FFA are from these adipose depots. The rise in FFA in PE occurs early in pregnancy and contributes significantly to IR. Therefore the IR of adipose tissue could lead to a vicious cycle of increased lipolysis, increased FFA and further exacerbation of IR. In contrast to controls, SAT cell size is intimately related to BMI suggesting that adaptation to increasing fat mass is mainly through adipocyte hypertrophy which could lead to increased endoplasmic reticulum stress, increased IR and increased release of inflammatory adipokines. I have shown that SAT cell size does relate to adipokine release in PE, with increased release of leptin, CRP and PAI-1 and paradoxical increase in the anti-inflammatory IL-10. I had hypothesised that in addition to an inherent defect in adipocyte function there was an additional factor present in maternal serum of women with PE released from the placenta which excessively stimulated lipolysis. I failed to demonstrate any effect of maternal serum on adipocyte lipolysis in either controls or PE. I also found that after stimulation with LPS, there was increased release of TNF alpha and IL-6 in VAT in PE but not in controls, with higher gene expression of these adipokines. TNF alpha release also correlated negatively with the fat cell insulin sensitivity index (FCISI) of VAT implicating a paracrine effect in this tissue. I also demonstrated an increase in gene expression of cfms (activated macrophages) relative to control gene, and increased density of cfms+ macrophages/adipocytes in the VAT of PE women implicating activated adipose tissue macrophages as a potential source of the increased release of inflammatory adipokines. Lastly I attempted to corroborate epidemiological evidence for the increase future risk of CVD women with a history of PE by assessing two surrogate markers for atherosclerosis - carotid IMT and carotid plaque scores. Both were found to be increased, with plaque scores significantly so. Classic risk factors such as age, lipids, BP and smoking did not attenuate this effect and BMI only marginally attenuated it, therefore only partially explaining this increased risk. In summary the data presented in this thesis provides further evidence that PE is a “metabolic syndrome of pregnancy” with disordered adipocyte function and metabolism, with an increased future risk of CVD in later life. Further studies on adipose accumulation, function and composition in normal and complicated human pregnancy are warranted.
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Okonko, Darlington Obinnaya. "Anaemia and metabolic pathways in chronic heart failure." Thesis, Imperial College London, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549708.
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Background: Anaemia is a common and adverse comorbidity in chronic heart failure (CHF), but critical aspects of its epidemiology, pathogenesis and treatment remain unclear. Objectives: This thesis tested the hypotheses that temporal trends in haemoglobin (Hb) relate to outcome in CHF, that anaemia might be subsequent to immune-mediated erythroid cell suppression, erythropoietin (Epo) resistance, cellular iron transport dysregulation, and altered adrenal steroidogenesis, and that low Hb levels could be amenable to recombinant Epo and intravenous iron therapies separately. Methods and Results: A post hoc analysis revealed that new onset anaemia occurred in 14% of patients at 1 year, developed more frequently on carvedilol than metoprolol, and was associated with increased mortality. Using flow cytomtry and cell culture techniques, CHF patients with anaemia of unknown origin were shown to exhibit markedly low reticulocyte production indices, and globally attenuated circulating erythroid lineage pools (C034+ stem cells, erythroid progenitors [BFU-E] and precursors). Only the depletion of anaemic monocytes from cultures enhanced erythroid colony growth. Only the addition of anaemic monocytes or sera to cultures blunted autologous and allogenic erythroid colony formation. Anti-TNFa neutralizing antibody abrogated the effects of anaemic sera on erythroid colonies. In additional assays, the ex-vivo responsiveness of erythroid cells to escalating doses of Epo was diminished in anaemic patients. This was not associated with Epo receptor downregulation but with a profound blunting of Epo-induced intracellular signalling. In biochemical analyses, the cortisol/dihydroepiandrosterone ratio, a marker of adrenal steroid hormone imbalance, was shown to inversely correlate to Hb levels. More importantly, disorded iron homeostasis was highly prevalent in CHF patients and independently predictive of anaemia, exercise intolerance and impaired survival. Sera from iron deficient subjects exhibited elevated pro-inflammatory cytokine and pro-hepcidin levels. Such sera downregulated ferroportin (iron export protein) and upregulated divalent metal transport-l (iron import protein) expression on monocytes ex-vivo, a pattern that facilitates inflammatory hypoferremia in vivo. Co-incubation with anti- TNFa neutralising antibodies abolished these effects. Finally, in separate randomised controlled trials, recombinant Epo escalated Hb levels but not exercise tolerance in anaemic CHF patients, whilst intravenous iron improved symptoms and exercise capacity but not Hb levels in anaemic and non-anaemic CHF patients.
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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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Ebenhöh, Oliver. "Structural analysis of metabolic networks." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=967762499.
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Ebenhöh, Oliver. "Structural analysis of metabolic networks." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2003. http://dx.doi.org/10.18452/14853.
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In der vorliegenden Arbeit werden zwei Modelle zur strukturellen Analyse von Stoffwechselsystemen vorgestellt. Die Untersuchung basiert auf der Hypothese, dass heutzutage vorzufindende Stoffwechselsysteme als Ergebnis einer evolutionären Entwicklung, bestimmt durch Mutationsmechanismen und natürlicher Selektion, angesehen werden können. Es kann daher angenommen werden, dass kinetische Parameter sowie strukturelle Eigenschaften im Laufe der Evolution solche Werte angenommen haben, die eine gewisse Optimalität bezüglich ihrer biologischen Funktion darstellen. Das erste Modell untersucht das strukturelle Design ATP und NADH produzierender Systeme, so wie die Glykolyse und der Zitratzyklus. Eine Methode wird präsentiert, die die Beschreibung hypothetischer, chemisch denkbarer, alternativer Stoffwechselwege ermöglicht. Diese Wege werden bezüglich ihrer Effizienz, ATP zu produzieren, untersucht. Es stellt sich heraus, dass die meisten möglichen Wege eine niedrige ATP-Produktionsrate aufweisen und dass die effizientesten Wege einige strukturelle Gemeinsamkeiten besitzen. Die Optimierung bezüglich der ATP-Produktionsrate wird mit einem evolutionären Algorithmus durchgeführt. Folgende Resultate stehen mit dem tatsächlichen Design der Glykolyse und des Zitratzyklus in Einklang: (i) In allen effizienten Wegen befinden sich die ATP-verbrauchenden Reaktionen am Anfang. (ii) In allen effizienten Wegen befinden sich die sowohl die NADH- als auch die ATP-produzierenden Reaktionen am Ende. (iii) Die Anzahl der NADH-Moleküle, die aus einem energiereichen Molekül (Glukose) produziert werden, beläuft sich in allen effizienten Wegen auf vier. Im zweiten Modell werden vollständige Mengen metabolischer Netzwerke konstruiert, wobei von Reaktionen ausgegangen wird, die Änderungen des Kohlenstoffskeletts der beteiligten Metabolite beschreiben. Elementare Netzwerke werden dadurch definiert, dass eine bestimmte chemische Umwandlung durchgeführt werden kann und dass diese Fähigkeit verloren geht, wenn eine der beteiligten Reaktionen ausgeschlossen wird. Übergänge zwischen Netzwerken und Mutationen werden durch den Austausch einer einzigen Reaktion definiert. Es existieren verschiedene Mutationen, solche bei denen Funktionen verloren gehen, welche dazugewonnen werden, und neutrale Mutationen. Mutationen definieren Nachbarschaftsrelationen, die graphentheoretisch beschrieben werden. Eigenschaften wie Durchmesser, Konnektivität und die Abstandsverteilung der Vertizes werden berechnet. Ein Konzept zur Quantifizierung der Robustheit von Netzwerken gegenüber stöchiometrischen Veränderungen wird entwickelt, wobei zwischen starker und schwacher Robustheit unterschieden wird. Evolutionäre Algorithmen werden angewandt, um die Entwicklung von Netzwerkpopulationen unter konstanten und zeitlich veränderlichen Umweltbedingungen zu untersuchen. Es wird gezeigt, dass Populationen sich zu Gruppierungen von Netzwerken hinentwickeln, die gemeinsame Funktionen besitzen und nah benachbart sind. Unter zeitlich veränderlichen Umweltbedingungen zeigt sich, dass multifunktionelle Netzwerke optimal sind und sich im Selektionsprozess durchsetzen.In the present thesis two models are presented which study the structural design of metabolic systems. The investigation is based on the hypothesis that present day metabolic systems are the result of an evolutionary development governed by mutation mechanisms and natural selection principles. Therefore, it can be assumed that these parameters have reached, during the course of their evolution, values which imply certain optimal properties with respect to their biological function. The first model concerns the structural design of ATP and NADH producing systems such as glycolysis and the citric acid cycle. A method is presented to describe hypothetical, chemically feasible, alternative pathways. We analyse these pathways with respect to their capability to efficiently produce ATP. It is shown that most of the possible pathways result in a very low ATP production rate and that the very efficient pathways share common structural properties. Optimisation with respect to the ATP production rate is performed by an evolutionary algorithm. The following results of our analysis are in close correspondence to the real design of glycolysis and the TCA cycle: (i) In all efficient pathways the ATP consuming reactions are located near the beginning. (ii) In all efficient pathways NADH producing reactions as well as ATP producing reactions are located near the end. (iii) The number of NADH molecules produced by the consumption of one energy-rich molecule (glucose) amounts to four in all efficient pathways. In the second model complete sets of metabolic networks are constructed starting from a limited set of reactions describing changes in the carbon skeleton of biochemical compounds. Elementary networks are defined by the condition that a specific chemical conversion can be performed by a set of given reactions and that this ability will be lost by elimination of any of these reactions. Transitions between networks and mutations of networks are defined by exchanges of single reactions. Different mutations exist such as gain or loss of function mutations and neutral mutations. Based on these mutations neighbourhood relations between networks are established which are described in a graph theoretical way. Basic properties of these graphs are determined such as diameter, connectedness, distance distribution of pairs of vertices. A concept is developed to quantify the robustness of networks against changes in their stoichiometry where we distinguish between strong and weak robustness. Evolutionary algorithms are applied to study the development of network populations under constant and time dependent environmental conditions. It is shown that the populations evolve toward clusters of networks performing a common function and which are closely neighboured. Under changing environmental conditions multifunctional networks prove to be optimal and will be selected.
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Yong, Carmen. "Enhancing adoptive immunotherapy : redirecting immune subsets and metabolic pathways." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT059.
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Le transfert adoptif de cellules T exprimant un récepteur chimérique reconnaissant un antigène (CAR), est un traitement qui génère des réponses impressionnantes dans les cancers hématologiques mais est beaucoup moins efficace pour le traitement de tumeurs solides. Les tumeurs solides modulent leur microenvironnement induisant des formes multiples d’immunosuppression qui inhibent l’efficacité des fonctions effectrices des cellules T ayant infiltrées la tumeur. Au cours de ma thèse, j’ai évalué le potentiel de deux stratégies pour améliorer les réponses anti-tumorales des cellules T CAR. La première se focalise sur l’étude du rôle potentiel des cellules immunes non T, exprimant un CAR sur la stimulation des fonctions et de la persistance de cellules T CAR+ dans le microenvironnement tumoral. Afin d’étudier la fonction des cellules CAR non T, nous avons généré un modèle de souris transgénique (vav-CAR) dans lequel les cellules immunes expriment un CAR reconnaissant l’antigène tumoral Her2 (ErbB2). Comme attendu, les cellules T CAR+ possèdent des fonctions anti-tumorales, mais nous avons aussi mis en évidence que les macrophages et les cellules NK exprimant le CAR montraient une réponse cytokinique, cytotoxique et phagocytiques spécifiques de l’antigène. De plus, en utilisant le modèle vav-CAR, nous avons démontré le potentiel des cellules immunes CAR+ dans le rejet des tumeurs et cela indépendamment des cellules T CD8+. Les cellules T CD4+ sont essentielles puisque leur élimination réduit considérablement les réponses anti-tumorales dans notre modèle vav-CAR. Il a été démontré que certaines sous-populations de cellules T auxiliaires participent aux réponses anti-tumorales avec les cellules Th1 et Th17 démontrant une efficacité plus robuste que les autres sous-populations. Notre deuxième stratégie s’est focalisée sur l’étude de l’impact du métabolisme au cours de la polarisation des cellules T CD4+ et plus particulièrement lors de la différenciation des cellules T CAR+ en cellules Th1. En effet, l’activation et différenciation des cellules T sont fortement associées à une augmentation des besoins métaboliques. Dans le microenvironnement tumoral, en raison de la forte demande en ressources de la tumeur, la déprivation en nutriments ainsi générée peut limiter l’accès aux nutriments d’autres types cellulaires et ainsi altérer le devenir et les fonctions des cellules immunes greffés infiltrant la tumeur. En conséquence, modifier les cellules immunes CAR+ afin qu’elles puissent résister à la compétition métabolique du microenvironnement tumoral pourrait leur permettre de conserver leurs fonctions effectrices. En étudiant l’impact de la déprivation en nutriments sur la différenciation des cellules T, nous avons trouvé que des concentrations limitantes en glutamine, l’acide aminé le plus abondant du plasma, inhibaient le potentiel des cellules T à se différencier vers la voie Th1 associée à la production d’IFNγ. Au contraire, cette condition favorisait la conversion de cellules T CD4 naïves en cellules régulatrices Foxp3+ ayant des fonctions suppressives (Tregs). De plus, nous avons montré que la présence d’un seul métabolite dérivé de la glutamine, l’α-ketoglutarate (αKG), suffisait à augmenter les fonctions effectrices anti-tumorales de plusieurs sous-types de cellules T auxiliaires CAR+, augmentant la production d’IFNγ et diminuant l’expression de FOXP3. Ainsi, durant ma thèse, j’ai développé un modèle murin vav-CAR, générant un outil permettant d’étudier et manipuler les fonctions de multiples populations de cellules immunitaires exprimant un CAR. Ce modèle permettra de promouvoir l’utilisation de cellules immunes optimisées exprimant un CAR dans le cadre d’immunothérapies dirigées contre des tumeurs solides. De plus, en utilisant ce modèle, nous avons identifié un métabolite de la glutamine, qui orchestre les réponses immunitaires au moyen d’une reprogrammation métabolique des cellules T CD4The adoptive transfer of T cells expressing a chimeric antigen receptor (CAR) as a treatment for cancer has achieved impressive responses in haematological malignancies, but has been less successful in the treatment of solid tumors. The tumor microenvironment of solid tumors presents multiple forms of immunosuppression, inhibiting the efficient effector function of infiltrating anti-tumor T cells. During my PhD, we assessed the potential of two strategies to enhance the anti-tumor function of CAR T cells. The first focuses on the potential of other CAR-expressing immune subsets to stimulate CAR T cell function and persistence in the tumor microenvironment. To elucidate the function of CAR-expressing non-T lymphocytes, we generated a transgenic mouse model (vav-CAR) in which immune cells express a CAR against the Her2 (ErbB2) tumor antigen. As expected, CAR T cells harboured anti-tumor function but we also found that CAR-modified macrophages and natural killer cells (NKs) exhibited significant antigen specific cytokine secretion, cytotoxicity and phagocytosis. Moreover, using the vav-CAR model, we demonstrated the potential of CAR immune cells to mediate tumor rejection independently of CD8+ T cells. CD4+ T cells were critical for this response as their deletion severely abrogated the anti-tumor responses in our vav-CAR model. Distinct T helper subsets have been shown to participate to anti-tumor responses, with Th1 and Th17 cells demonstrating a more robust efficacy as compared to other T helper subsets. Our second strategy was focused on the impact of metabolism in the polarisation of CD4+ T cells, in particular the differentiation of CAR T cells to Th1 lineage. T cell activation and polarisation is highly associated with increased metabolic needs. Given that nutrient deprivation in the tumor microenvironment, due to a high demand of the tumor for resources, can limit the nutrients available for other cell types, the fate and function of adoptively transferred immune cells may be altered upon entering the tumor. Therefore, modifying CAR immune cells to resist metabolic suppression in the tumor microenvironment may help retain their effector functions. Upon assessing the effects of nutrient deprivation on T cell differentiation, we found that limiting concentrations of glutamine, the most abundant amino acid in the plasma, inhibited the potential of T cells to undergo Th1 differentiation with associated IFNγ secretion. Rather, this condition resulted in the conversion of naïve CD4+ T cells into suppressive Foxp3+ regulatory T cells (Tregs). Furthermore, we determined that a single glutamine-derived metabolite, α-ketoglutarate (αKG), enhanced the anti-tumor effector functions of multiple CAR T helper subsets, increasing the production of IFNγ and reducing FOXP3 expression.Thus, during my PhD, I generated a vav-CAR model, providing a platform in which the function of multiple CAR-bearing immune subsets can be studied and manipulated. This model will promote the utilisation of optimized CAR-bearing immune cells in adoptive immunotherapy for solid tumors. Furthermore, using the CAR model, we have identified a glutamine metabolite that orchestrates immune responses through the metabolic reprogramming of CD4 T cells
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Kalra, Paul Raj. "Natriuretic peptides and metabolic pathways in chronic heart failure." Thesis, Imperial College London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.503841.
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Richards, Jamie. "Investigation of metabolic pathways suitable for antimicrobial drug discovery." Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424092.
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Onyiaodike, Christopher C. "A study of metabolic and inflammatory pathways throughout gestation." Thesis, University of Glasgow, 2014. http://theses.gla.ac.uk/4979/.
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The effect of metabolic and inflammatory parameters on pregnancy success in terms of implantation, metabolic adaptation to pregnancy and fetal programming is yet to be fully understood. This thesis explores the activity of metabolic and inflammatory pathways in pregnancy, highlighting their importance throughout gestation. In a cell culture study, a model of in vivo blastocyst-uterine adhesion to study the effect of insulin during uterine implantation was explored. JAR spheroid-RL95-2 monolayer adhesion reached 98% by 24 hours in the absence of insulin. A low dose (0.03nM) of added insulin concentrations resulted in 26% adhesion, or 74% inhibition; a high level (0.24nM) inhibited the JAR spheroid-RL95-2 monolayer adhesion by 9%. Therefore insulin did not have a dose-dependent on JAR spheroid-RL95-2 monolayer adhesion in the cell culture model of implantation. Polymerase chain reaction (PCR) studies revealed laminin α1 RNA detection on JAR cells only, CD44 on RL95-2 cells only, no trophinin on both cell types, FBLN-1 and -2 on JAR and FBLN-1 on RL95-2 cells only and an insulin receptor in both cell types. Western blot and immunohistochemistry (IHC) studies showed laminin α1 detection and stains on the JAR cell extracellular matrix. In a prospective human study, the metabolites of lipid and carbohydrate metabolism and inflammatory mediators very early (between day 0 and day 45) in gestation and their link to successful pregnancy in women undergoing natural cycle frozen embryo transfer (FET) in assisted conception, was investigated. Plasma triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), glucose, c-reactive protein (CRP) and non-esterified fatty acid (NEFA) were measured on routine biochemistry; insulin, interleukin (IL)-6, plasminogen activated inhibitor (PAI)-1 and PAI-2 on ELISA; IL-8 (CXCL8), CCL2, CCL3, CCL4 and CCL11 on BioPlex; and human chronic gonadotrophin (hCG) on an Immulite system. For all 196 FET cycles, participants' demographics and plasma parameters of pregnant (n=36) and non-pregnant (n=106) women were explored. Neither obesity, the plasma parameters nor insulin resistance were predictive of successful pregnancy, but ICSI (predominately associated with male factor infertility) was. Overall, the hCG, insulin, rebound TG and HDL-C (except TC), homeostasis model assessment (HOMA), CRP and PAI-2 levels were higher, whereas CXCL8, CCL2, CCL11 and PAI-1 were significantly lower by day 45. Baseline obesity related to positive changes in plasma insulin, HDL-C and HOMA and negative changes in CXCL8, CCL3 and CCL4. In a cross-sectional study in late pregnancy, offspring's reflection of parameters in women with preeclampsia (PE) (n=29) and intrauterine growth restriction (IUGR) (n=14), compared to BMI-matched healthy groups (n=87) and (n=42), respectively, was explored. Fetal cord was found to be hyperlipidaemic, normoglycaemic and had reduced inflammatory response, while mothers who suffered PE had altered plasma TG, TC, NEFA, glucose, leptin and IL-10 compared to controls. IUGR babies were dyslipidaemic. The role of cholesterol transporters was assessed in PE (n=20) and IUGR (n=9) BMI-matched controls (n=20 and n=9) respectively. Among fifteen steroidogenic acute regulatory protein (STAR)-related lipid transfer domains, only STARD6 and STARD15 were not detected in the placenta via PCR. IHC studies were also explored on the placentae. The real-time PCR (RT-PCR) of messenger RNA of low-density lipoprotein receptor (LDLR), STARD3 and ATP-binding cassette A1 (ABCA1) without protein were higher in PE compared to controls. LDLR, STARD3 and ABCA1 localisation and detection were consistent to placental lipid (cholesterol) transport systems. In summary, all this led to the conclusion of the importance of metabolic and inflammatory pathways in all stages of pregnancy in leading to pregnancy success; these pathways may influence implantation, adaptation to pregnancy and, potentially, fetal programming of offspring.
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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)0048
新制・課程博士
博士(農学)
甲第11658号
農博第1514号
新制||農||911(附属図書館)
学位論文||H17||N4051(農学部図書室)
23301
UT51-2005-D407
京都大学大学院農学研究科応用生命科学専攻
(主査)教授 島田 幹夫, 教授 關谷 次郎, 教授 坂田 完三
学位規則第4条第1項該当
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Zamora, Jorge. "Lipid Metabolic Pathways in the Midgut of Manduca sexta." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195273.
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Insects such as Manduca sexta must be efficient in obtaining energy stores in order to survive. The main goal of the M. sexta larva is to eat and store enough energy to reach the adult stage, produce eggs (in the case of females), and reproduce. Triacylglycerol (TAG), the most important energy storage molecule, is stored mainly in adipose tissues in lipid droplets, although other tissues are also able to store TAG in similar organelle structures but to a lesser degree. The phosphatidic acid (PA) pathway and the 2-monoacylglycerol (MAG) pathway are both energy-dependant acyl-CoA processes and are the main synthetic pathways by which TAG is synthesized in adipose and other tissues. My research led to the discovery of an energy-independent pathway for the synthesis of TAG that was present in the M. sexta midgut. Based on partial purification, a transacylase/lipase enzyme is present and responsible for DAG and TAG synthesis in the M.sexta midgut. Lipogenesis and lipolysis in adipose tissue involves a series of enzymes. Adiponutrin and desnutrin, two proteins involved in fat homeostasis in humans and mice, have received a lot of attention since their activities are dependent on the fed or unfed state of the animal. In this study, bioinformatics analyses were performed, which allowed the identification of an insect gene that has an ortholog in human and mice that plays an important role in adipose tissue TAG hydrolysis and synthesis. Only one insect gene ortholog was found to be present in the Aedes aegypti (mosquito), Drosophila melanogaster (fruit fly), Anopheles gambiae (mosquito), Bombyx mori (silk worm), and Tribolium castaneum (red flour beetle) genomes corresponding to genes involved in the regulation of TAG metabolism in mice (adiponutrin, desnutrin) and humans (iPLA-epsilon, iPLA-zeta, and iPLA-eta). Expression of the M. sexta calcium-independent phospholipase A2 (iPLA) ortholog has demonstrated that the protein is able to transfer acyl groups between MAGs in an energy-independent manner, similar to that in human iPLAs. This is the first example of a transacylase identified in insects.
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Patel, Gajendra. "Implementing and Evaluating MQLAIP: A Metabolism Query Language." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1289591644.
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Woods, John Henry. "OOMPF : an Object-Oriented Metabolic Programming Framework." Thesis, Oxford Brookes University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264472.
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Pearcy, N. "Unravelling the complexity of metabolic networks." Thesis, Nottingham Trent University, 2015. http://irep.ntu.ac.uk/id/eprint/28040/.
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Network science provides an invaluable set of tools and techniques for improving our understanding of many important biological processes at the systems level. A network description provides a simplied view of such a system, focusing upon the interactions between a usually large number of similar biological units. At the cellular level, these units are usually interacting genes, proteins or small molecules, resulting in various types of biological networks. Metabolic networks, in particular, play a fundamental role, since they provide the building blocks essential for cellular function, and thus, have recently received a lot of attention. In particular, recent studies have revealed a number of universal topological characteristics, such as a small average path-length, large clustering coecient and a hierarchical modular structure. Relations between structure, function and evolution, however, for even the simplest of organisms is far from understood. In this thesis, we employ network analysis in order to determine important links between an organism's metabolic network structure and the environment under which it evolved. We address this task from two dierent perspectives: (i) a network classication approach; and (ii) a more physiologically realistic modelling approach, namely hypernetwork models. One of the major contributions of this thesis is the development of a novel graph embedding approach, based on low-order network motifs, that compares the structural properties of large numbers of biological networks simultaneously. This method was prototyped on a cohort of 383 bacterial networks, and provides powerful evidence for the role that both environmental variability, and oxygen requirements, play in the forming of these important networked structures. In addition to this, we consider a hypernetwork formalism of metabolism, in an attempt to extend complex network reasoning to this more complicated, yet physiologically more realistic setting. In particular, we extend the concept of network reciprocity to hypernetworks, and again evidence a signicant relationship between bacterial hypernetwork structure and the environment in which these organisms evolved. Moreover, we extend the concept of network percolation to undirected hypernetworks, as a technique for quantifying robustness and fragility within metabolic hypernetworks, and in the process nd yet further evidence of increased topological complexity within organisms inhabiting more uncertain environments. Importantly, many of these relationships are not apparent when considering the standard approach, thus suggesting that a hypernetwork formalism has the potential to reveal biologically relevant information that is beyond the standard network approach.
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Whitaker, John William. "On the evolution of metabolic networks." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511155.
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Balakrishnan, Achuthanunni Chokkathukalam. "Stoichiometric modelling of plant metabolic networks." Thesis, Oxford Brookes University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520929.
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Vassena, Nicola [Verfasser]. "Sensitivity of metabolic networks / Nicola Vassena." Berlin : Freie Universität Berlin, 2020. http://d-nb.info/1215099053/34.
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