Lipidomics and metabolomics are powerful tools for the examination of cellular metabolism and physiology. Methods for lipid analysis need to be developed that begin with small samples and do not overly dilute or disperse the sample in the separation process. Microchips provide a platform for interfacing lysis of small cell populations with on-chip solid phase extraction for isolating lipid samples to generate high quality mass spectra from very small samples. Chapter 1 of this dissertation presents a novel method for small scale lipidomics of bacterial cells by microchip based extraction coupled with untargeted profiling of glycerophospholipids using nanoelectrospray ionization mass spectrometry. Chapter 2 and 3 focus on the development of LC-MS/MS methods to study biological pathways. In Chapter 2, I describe a method for analysis of the phospholipids metabolite, GroPIns, in the medium of the pathogenic yeast Candida albicans. This method was applied to aid in the characterization of the GroPIns transport protein, Git1, in C. albicans. Chapter 3 extends the studies of part two and describes an efficient method based on HILIC-MS/MS for the separation and quantification of five lipid-related extracellular metabolites in yeast Saccharomyces cerevisiae. This newly developed methodology was successfully applied to determine the extracellualr levels of glycerophosphoinositol, glycerophosphocholine, glycerol 3-phosphate, inositol and choline in wild type and mutant strains. / Bayer School of Natural and Environmental Sciences / Chemistry and Biochemistry / PhD / Dissertation

Nous développons une approche générique pour comprendre comment différents régimes alimentaires peuvent influencer la qualité et la composition du lait. Cette question s'intègre dans le cadre du Flux Balance Analysis (FBA), qui consiste à analyser un réseau métabolique en optimisant un système de contraintes linéaires. Nous avons proposé une extension du FBA pour analyser la transformation des nutriments en intégrant des hypothèses biologiques utilisées par différents modèles numériques dans un modèle générique de la glande mammaire. Notre méthode permet de quantifier les précurseurs qui interviennent dans la composition des sorties du système, en calculant des contributions des entrées dans les sorties [AIO]. A l'aide de cette approche, nous avons montré que la transformation des nutriments du lait ne peut pas être modélisée par l'optimisation d'une combinaison linéaire des flux des réactions sur un modèle du métabolisme mammaire. Pour étudier plus précisément la flexibilité d'un réseau métabolique, nous avons proposé un algorithme efficace de recherche locale pour calculer les valeurs extrémales des coefficients des AIOs. Cette approche permet de discriminer les traitements sans formuler d'hypothèses sur le comportement interne du système. / This thesis proposes a generic approach to understanding how different diets affect the quality and composition of milk. This question is addressed in the framework of Flux Balance Analysis (FBA), which considers metabolic network analysis as an optimization issue on a system of linear constraints. In this work, we extended FBA to take into account nutrients transformation by incorporating general assumptions made by various numerical methods in a generic stoichiometric model of the mammary gland. Our method tries to quantify the precursor composition of each system output and to discuss the biological relevance of a set of flux in a given metabolic network. The composition is called contribution of inputs over outputs [AIO]. Using this method on the mammary metabolism, we could show that nutrients transformation cannot be properly modelled by optimizing a linear combination of reactions fluxes in the mammary gland model. In order to further investigate metabolic network flexibility, we have proposed an efficient local search algorithm computing the extremal values of AIO coefficients. This approach enables to discriminate diets without making any assumption on the internal behaviour of the system.

No description available.

Le diagnostic médical, se fait traditionnellement, par l'examen des symptômes cliniques, puis en cherchant sur des prélèvements (sang, urine, biopsies, etc.) la présence (ou l'absence) simultanée des bio-marqueurs des diverses pathologies envisagées par le médecin. La recherche des bio-marqueurs se fait a l'aide d'équipements importants, dans un laboratoire d'analyse; les résultats étant communiqués au médecin, qui va les interpréter en appliquant un algorithme de diagnostic médical.Nous avons voulu regrouper dans un seul dispositif, pour une pathologie donnée, la détection des bio-marqueurs et une implémentation de l'algorithme de diagnostic approprié. La présence ou l'absence d'un bio-marqueur peut être représentée par une variable booléenne, et l'algorithme de diagnostic par une fonction booléenne complexe dont la valeur indiquera la présence de la pathologie ciblée.Notre dispositif de diagnostic sera un nano-calculateur biochimique artificiel dans lequel les informations logiques seront représentées par des métabolites et les calculs effectués par un réseau enzymatique synthétique. Pour réaliser ce calculateur, il a été nécessaire d'établir un fondement théorique des réseaux logiques enzymatiques. Nous avons ensuite utilisé cette théorie pour définir ce qu'est un circuit logique enzymatique et comment il calcule correctement la fonction booléenne associée. Pour des raisons de modularité et de réutilisabilité, nous avons décidé de concevoir des bibliothèques de portes logiques enzymatiques implémentant les opérateurs booléens de base, puis d'assembler ces briques de base pour obtenir le réseau enzymatique complet. J'ai donc conçu et développé deux outils logiciels, NetGate et NetBuild, qui vont réaliser automatiquement ces opérations.NetGate, qui va créer des bibliothèques contenant des centaines de portes logiques enzymatiques obtenues à partir de réseaux métaboliques d'organismes existants. Auparavant, il était nécessaire d'analyser manuellement ces réseaux métaboliques pour extraire chaque porte.NetBuild, qui va utiliser une bibliothèque de portes (par exemple créée par NetGate) et les assembler pour construire des circuits qui calculent une fonction booléenne donnée. Ces circuits utilisent comme entrées des métabolites spécifiques (par exemple: bio-marqueurs d'une pathologie) et produisent en sortie une espèce moléculaire facilement détectable (par colorimétrie par exemple). / The medical diagnosis is traditionally done by examining the clinical symptoms and by searching in samples (blood, urine, biopsies, etc.) for the simultaneous presence (or absence) of biomarkers of the various pathologies considered by the doctor. The search for biomarkers is conducted using large equipments in a specialised laboratory; The results being communicated to the doctor, who will then interpret them by applying a medical diagnostic algorithm.We wanted to combine in a single device, for a given disease, the detection of its biomarkers and an implementation of the appropriate diagnostic algorithm. The presence or absence of a biomarker can be represented by a boolean variable, and the diagnostic algorithm by a complex boolean function whose value indicates the presence of the targeted disease. Our diagnostic device is an artificial biochemical nano-computer in which logical information is represented by metabolites and the computations performed by a synthetic enzymatic network. To build this computer, it has been necessary to establish a theoretical basis of enzymatic logical networks. We then used this theory to define what an enzymatic logic network is, and how it computes correctly the associated boolean function. For modularity and reusability reasons, we decided to design libraries of enzymatic logic gates that implement basic boolean operators, and then to assemble these building blocks to get the complete logic enzymatic network. So, I have designed and developed two software tools, NetGate and NetBuild, which will automatically perform these operations.NetGate creates libraries containing hundreds of enzymatic logic gates obtained from the metabolic networks of living organisms. Before that, it was necessary to manually analyse these metabolic networks in order to extract each logic gate.NetBuild uses a library of logic gates (for example created using NetGate) and assembles them to build circuits that compute a given boolean function. These circuits use specific metabolites for its inputs (for example the biomarkers of a pathology) and produce a readily detectable molecular species (using colorimetry for example).

The increasing spectrum of multidrug-resistant bacteria has caused a major global public health concern, necessitating the discovery of novel antimicrobial agents. Additionally, recent advancements in the use of microbial cells for the scalable production of industrial enzymes has encouraged the screening of new environments for efficient microbial cell factories. The unique ecological niche of the Red Sea points to the promising metabolic and biosynthetic potential of its microbial system. Here, ten sequenced Bacilli strains, that are isolated from microbial mat and mangrove mud samples from the Red Sea, were evaluated for their use as platforms for protein production and biosynthesis of bioactive compounds. Two of the species (B.paralicheniformis Bac48 and B. litoralis Bac94) were found to secrete twice as much protein as Bacillus subtilis 168, and B. litoralis Bac94 had complete Tat and Sec protein secretion systems. Additionally, four Red Sea Species (B. paralicheniformis Bac48, Virgibacillus sp. Bac330, B. vallismortis Bac111, B. amyloliquefaciens Bac57) showed capabilities for genetic transformation and possessed competence genes. More specifically, the distinctive biosynthetic potential evident in the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84 was assessed and compared to nine available complete genomes of B. licheniformis and three genomes of B. paralicheniformis. A uniquely-structured trans-acyltransferase (trans-AT) polyketide synthase/nonribosomal peptide synthetase (PKS/NRPS) cluster in strains of this species was identified in the genome of B. paralicheniformis 48. In total, the two B. paralicheniformis Red Sea strains were found to be more enriched in modular clusters compared to B. licheniformis strains and B. paralicheniformis strains from other environments. These findings provided more insights into the potential of B. paralicheniformis 48 as a microbial cell factory and encouraged further focus on the strain’s metabolism at the system level. Accordingly, a draft metabolic model for B. paralicheniformis Bac48 (iPARA1056) was reconstructed, refined, and validated using growth rate and growth phenotypes under different substrates, generated using high-throughput Phenotype Microarray technology. The presented studies indicate that several of the isolated strains represent promising chassis for the development of cell factories for enzyme production and also point to the richness of their genomes with specific modules of secondary metabolism that have likely evolved in Red Sea Bacilli due to environmental adaptation.

No description available.

The decreasing costs of next generation sequencing technologies and the increasing speeds at which they work have lead to an abundance of 'omic datasets. The need for tools and methods to analyze, annotate, and model these datasets to better understand biological systems is growing. Here we present a novel software pipeline to reconstruct the metabolic model of an organism in silico starting from its genome sequence and a novel compilation of biological databases to better serve the generation of metabolic models. We validate these methods using five Gardnerella vaginalis strains and compare the gene annotation results to NCBI and the FBA results to Model SEED models. We found that our gene annotations were larger and highly similar in terms of function and gene types to the gene annotations downloaded from NCBI. Further, we found that our FBA models required a minimal addition of transport reactions, sources, and escapes indicating that our draft pathway models were very complete. We also found that on average our solutions contained more reactions than the models obtained from Model SEED due to a large amount of baseline reactions and gene products found in ASGARD.

Made available in DSpace on 2016-12-23T13:48:27Z (GMT). No. of bitstreams: 1 Tatiane Lemos Perdigao.pdf: 4071467 bytes, checksum: 85c5c1063113c7af6b5b3131436fee6f (MD5) Previous issue date: 2012-02-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O estudo da influência do alumínio (Al) em duas cultivares da espécie Passiflora edulis foi apresentado para melhor compreensão deste trabalho em dois capítulos, sendo abordado o experimento com a cultivar (cv.) FB 100 e FB 200 respectivamente. O estudo com a cv. FB100 em casa de vegetação teve como objetivo verificar alterações morfofisiológicas após 15 dias de tratamento com Al. Para as plantas da cv. FB 200 avaliou-se a relação entre a ação mutagênica e a concentração de flavonoides produzidos por estas, quando cultivadas em solos com diferentes concentrações de Al. Foram realizadas análises de massa fresca e seca dos órgãos, comprimento do caule, área foliar, análise nutricional e verificação de Al nas folhas e raízes da cv. FB100. Para a prospecção fitoquímica dos extratos das folhas das cv. FB100 e FB200 utilizaram-se reações de coloração e precipitação para identificação das principais classes químicas presentes. A concentração de flavonoides foi determinada através da quantificação espectrométrica. Para o teste de mutagenicidade verificou-se a frequência de micronúcleos em 2000 eritrócitos policromáticos utilizando o extrato das folhas da cv. FB200. Todos os parâmetros morfológicos analisados para a cv. FB100 não diferiram estatisticamente dos controles. Entretanto foi observada maior concentração de Al nas raízes no tratamento de 5,32 mM. Todos os tratamentos indicaram a presença de alcaloides, flavonoides e esteroides nas folhas das plantas. No extrato hexano/diclorometano a maior concentração de flavonoides, foi observada no tratamento 0,33 mM de Al. Os resultados observados para a cv. FB200 apresentou maior concentração de Al foliar no campo com 0,33mM de Al (T2), os grupos majoritários encontrados foram saponinas, esteroides e flavonoides. O tratamento T2 apresentou a maior concentração de flavonoides e maior potencial mutagênico. Esses resultados indicam que o Al não promoveu alterações significativas nos parâmetros morfofisiológicos da cv. FB 100. Em P. edulis cv. FB 200 saponinas, esteróides e flavonoides ocorrem independentemente da concentração de Al disponível e provavelmente a maior concentração de flavonoide pode ter induzido a mutagenicidade em células de medula óssea de camundongos / The influence of aluminum (Al) in two cultivars of Passiflora edulis is presented in two chapters: first a discussion on the experiment with the cultivar (cv.) FB 100 and second with the cultivar (cv.) FB 200. The study with cv. FB100 in greenhouse aimed to verify morphophysiological changes after 15 days of treatment with Al. For cv. FB 200 plants was evaluated the relationship between the mutagenic and the concentration flavonoids produced by them, when grown in soils with different concentrations aluminum. Analyses of fresh and dry weight organs, stem length, leaf area, nutritional analysis and verification of Al in leaves and roots were studied on cv.FB100. For the leaves of cv. FB100 and cv. FB200 phytochemical screening of extracts were used staining and precipitation reactions for identification of the main chemical classes present. The concentration of the flavonoids was determined by spectrometric measurement. To mutagenicity test was found the frequency of micronucleus in 2000 polychromatic erythrocytes using the cv. FB200 leaves extract. All cv. FB100 morphological parameters analyzed did not differ from controls. However a higher Al concentration was presented in the treatment of 5.32 mM roots. All treatments showed the presence of alkaloids, flavonoids and steroids in leaves. The extract hexane/dichloromethane at a higher flavonoid concentration, has been observed in treating 0.33 mM Al. The cv. FB200 results showed higher foliar Al concentration in the field with 0.33 mM Al (T2), and saponins, steroids and flavonoids were the major groups found. The T2 treatment had the highest flavonoids concentration and higher mutagenic potential. These results indicate that Al did not promote significant changes in cv. FB 100 morphophysiological parameters. In P.edulis cv. FB 200 saponins, flavonoids and steroids occur regardless of the Al available and possibly the largest concentration of flavonoid mutagenicity can be induced in cells of mouse bone marrow