22 resultados para Metabolômica


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O objetivo desta tese foi abordar a diversidade de Mycale Gray, 1867 sob um ponto de vista multidisciplinar. No Capítulo 1 foram realizadas reconstruções filogenéticas supra- e subgenéricas com base em dados moleculares, utilizando os marcadores 16S, 28S e cox1, a fim de estabelecer uma hipótese evolutiva para o grupo. No capítulo 2 são realizadas reconstruções ancestrais das características morfológicas do gênero dada a hipótese filogenética estabelecida no capítulo anterior, além de determinar limites na variação morfológica das anisoquelas tipo I por meio de análises morfométricas e estimar o padrão evolutivo das dimensões dos principais tipos espiculares de Mycale. No Capítulo 3 foi estimada a variabilidade genética do complexo Mycale (Carmia) microsigmatosa Arndt, 1927 por meio de análise de haplótipos do gene 16S do RNA ribossomal mitocondrial, além de correlacionar a sua variabilidade morfológica, estimada por meio de dimensões espiculares, com fatores genéticos e geográficos. No Capítulo 4 foram estabelecidas hipóteses biogeográficas para Mycale por meio de análise de três itens tendo como base as reconstruções filogenéticas moleculares e também foram determinados padrões de distribuição geográfica do gênero a partir da ocorrência de espécies em áreas de endemismo. Por fim, no Capítulo 5, os perfis metabólicos de três espécies do gênero Mycale foram obtidos por espectroscopia de ressonância magnética nuclear dos núcleos de hidrogênio (RMN 1H) e comparados estatisticamente, além de suas similaridades terem sido contrastadas com suas relações filogenéticas e suas diferenças entre grupos de indivíduos metabolicamente relacionados determinadas.

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[ES] Este trabajo consiste en la búsqueda de biomarcadores en esquizofrenia. Para ello se realiza una metabolómica dirigida a unas moléculas del metabolismo central del carbono y se comprueban las variaciones en la concentración entre individuos sanos e individuos diagnosticados de esquizofrenia.

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Brazilian biodiversity is a colossal source of secondary metabolites with remarkable structural features, which are valuable in further biodiscovery studies. In order to fully understand the relations and interactions of a living system with its surroundings, efforts in natural product chemistry are directed toward the challenge of detecting and identifying all the molecular components present in complex samples. It is plausible that this endeavor was born out of recent technological sophistication in secondary metabolite identification with sensitive spectroscopic instruments (MS and NMR) and higher resolving power of chromatographic systems, which allow a decrease in the amount of required sample and time to acquire data. Nevertheless, the escalation of data acquired in these analyses must be sorted with statistical and multi-way tools in order to select key information. Chromatography is also of paramount importance, more so when selected compounds need to be isolated for further investigation. However, in the course of pursuing a greener environment, new policies, with an aim to decrease the use of energy and solvents, are being developed and incorporated into analytical methods. Metabolomics could be an effective tool to answer questions on how living organisms in our huge biodiversity work and interact with their surroundings while also being strategic to the development of high value bio-derived products, such as phytotherapeutics and nutraceuticals. The incorporation of proper phytotherapeutics in the so-called Brazilian Unified Health System is considered an important factor for the urgent improvement and expansion of the Brazilian national health system. Furthermore, this approach could have a positive impact on the international interest toward scientific research developed in Brazil as well as the development of high value bio-derived products, which appear as an interesting economic opportunity in national and global markets. Thus, this study attempts to highlight the recent advances in analytical tools used in detection of secondary metabolites, which can be useful as bioproducts. It also emphasizes the potential avenues to be explored in Brazilian biodiversity, known for its rich chemical diversity.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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240 p. + anexos

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Chapter 1 introduces the scope of the work by identifying the clinically relevant prenatal disorders and presently available diagnostic methods. The methodology followed in this work is presented, along with a brief account of the principles of the analytical and statistical tools employed. A thorough description of the state of the art of metabolomics in prenatal research concludes the chapter, highlighting the merit of this novel strategy to identify robust disease biomarkers. The scarce use of maternal and newborn urine in previous reports enlightens the relevance of this work. Chapter 2 presents a description of all the experimental details involved in the work performed, comprising sampling, sample collection and preparation issues, data acquisition protocols and data analysis procedures. The proton Nuclear Magnetic Resonance (NMR) characterization of maternal urine composition in healthy pregnancies is presented in Chapter 3. The urinary metabolic profile characteristic of each pregnancy trimester was defined and a 21-metabolite signature found descriptive of the metabolic adaptations occurring throughout pregnancy. 8 metabolites were found, for the first time to our knowledge, to vary in connection to pregnancy, while known metabolic effects were confirmed. This chapter includes a study of the effects of non-fasting (used in this work) as a possible confounder. Chapter 4 describes the metabolomic study of 2nd trimester maternal urine for the diagnosis of fetal disorders and prediction of later-developing complications. This was achieved by applying a novel variable selection method developed in the context of this work. It was found that fetal malformations (FM) (and, specifically those of the central nervous system, CNS) and chromosomal disorders (CD) (and, specifically, trisomy 21, T21) are accompanied by changes in energy, amino acids, lipids and nucleotides metabolic pathways, with CD causing a further deregulation in sugars metabolism, urea cycle and/or creatinine biosynthesis. Multivariate analysis models´ validation revealed classification rates (CR) of 84% for FM (87%, CNS) and 85% for CD (94%, T21). For later-diagnosed preterm delivery (PTD), preeclampsia (PE) and intrauterine growth restriction (IUGR), it is found that urinary NMR profiles have early predictive value, with CRs ranging from 84% for PTD (11-20 gestational weeks, g.w., prior to diagnosis), 94% for PE (18-24 g.w. pre-diagnosis) and 94% for IUGR (2-22 g.w. pre-diagnosis). This chapter includes results obtained for an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) study of pre-PTD samples and correlation with NMR data. One possible marker was detected, although its identification was not possible. Chapter 5 relates to the NMR metabolomic study of gestational diabetes mellitus (GDM), establishing a potentially predictive urinary metabolic profile for GDM, 2-21 g.w. prior to diagnosis (CR 83%). Furthermore, the NMR spectrum was shown to carry information on individual phenotypes, able to predict future insulin treatment requirement (CR 94%). Chapter 6 describes results that demonstrate the impact of delivery mode (CR 88%) and gender (CR 76%) on newborn urinary profile. It was also found that newborn prematurity, respiratory depression, large for gestational age growth and malformations induce relevant metabolic perturbations (CR 82-92%), as well as maternal conditions, namely GDM (CR 82%) and maternal psychiatric disorders (CR 91%). Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the value of maternal or newborn urine metabolomics for pregnancy monitoring and disease prediction, towards the development of new early and non-invasive diagnostic methods.

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This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

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The global aim of this thesis was to evaluate and assess the effects of a pesticide (dimethoate) and a metal (nickel), as model chemicals, within different organization levels, starting at the detoxification pathways (enzymatic biomarkers) and energy costs associated (energy content quantification, energy consumption and CEA) along with the physiological alterations at the individual and population level (mortality), leading to a metabolomic analysis (using liquid 1H-NMR) and finally a gene expression analysis (transcriptome and RT-qPCR analysis). To better understand potential variations in response to stressors, abiotic factors were also assessed in terrestrial isopods such as temperature, soil moisture and UV radiation. The evaluation performed using biochemical biomarkers and energy related parameters showed that increases in temperature might negatively affect the organisms by generating oxidative stress. It also showed that this species is acclimated to environments with low soil moisture, and that in high moisture scenarios there was a short gap between the optimal and adverse conditions that led to increased mortality. As for UV-R, doses nowadays present have shown to induce significant negative impact on these organisms. The long-term exposure to dimethoate showed that besides the neurotoxicity resulting from acetylcholinesterase inhibition, this stressor also caused oxidative stress. This effect was observed for both concentrations used (recommended field dose application and a below EC50 value) and that its combination with different temperatures (20ºC and 25ºC) showed different response patterns. It was also observed that dimethoate’s degradation rate in soils was higher in the presence of isopods. In a similar study performed with nickel, oxidative stress was also observed. But, in the case of this stressor exposure, organisms showed a strategy where the energetic costs necessary for detoxification (biomarkers) seemed to be compensated by positive alterations in the energy related parameters. In this work we presented for the first time a metabolomic profile of terrestrial isopods exposed to stressors (dimethoate and niquel), since until the moment only a previous study was performed on a metabolomic evaluation in nonexposed isopods. In the first part of the study we identify 24 new metabolites that had not been described previously. On the second part of the study a metabolomic profile variation of abstract non-exposed organism throughout the exposure was presented and finally the metabolomic profile of organisms exposed to dimethoate and nickel. The exposure to nickel suggested alteration in growth, moult, haemocyanin and glutathione synthesis, energy pathways and in osmoregulation. As for the exposure to dimethoate alterations in osmoregulation, energy pathways, moult and neurotransmission were also suggested. In this work it was also presented the first full body transcriptome of a terrestrial isopod from the species Porcellionides pruinosus, which will complement the scarce information available for this group of organisms. This transcriptome also served as base for a RNA-Seq and a RT-qPCR analysis. The results of the RNA-Seq analysis performed in organisms exposed to nickel showed that this stressor negatively impacted at the genetic and epigenetic levels, in the trafficking, storage and elimination of metals, generates oxidative stress, inducing neurotoxicity and also affecting reproduction. These results were confirmed through RT-qPCR. As for the impact of dimethoate on these organisms it was only accessed through RT-qPCR and showed oxidative stress, an impact in neurotransmission, in epigenetic markers, DNA repair and cell cycle impairment. This study allowed the design of an Adverse Outcome Pathway draft that can be used further on for legislative purposes.

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The main scope of this work was to evaluate the metabolic effects of anticancer agents (three conventional and one new) in osteosarcoma (OS) cells and osteoblasts, by measuring alterations in the metabolic profile of cells by nuclear magnetic resonance (NMR) spectroscopy metabolomics. Chapter 1 gives a theoretical framework of this work, beginning with the main metabolic characteristics that globally describe cancer as well as the families and mechanisms of action of drugs used in chemotherapy. The drugs used nowadays to treat OS are also presented, together with the Palladium(II) complex with spermine, Pd2Spm, potentially active against cancer. Then, the global strategy for cell metabolomics is explained and the state of the art of metabolomic studies that analyze the effect of anticancer agents in cells is presented. In Chapter 2, the fundamentals of the analytical techniques used in this work, namely for biological assays, NMR spectroscopy and multivariate and statistical analysis of the results are described. A detailed description of the experimental procedures adopted throughout this work is given in Chapter 3. The biological and analytical reproducibility of the metabolic profile of MG-63 cells by high resolution magic angle spinning (HRMAS) NMR is evaluated in Chapter 4. The metabolic impact of several factors (cellular integrity, spinning rate, temperature, time and acquisition parameters) on the 1H HRMAS NMR spectral profile and quality is analysed, enabling the definition of the best acquisition parameters for further experiments. The metabolic consequences of increasing number of passages in MG-63 cells as well as the duration of storage are also investigated. Chapter 5 describes the metabolic impact of drugs conventionally used in OS chemotherapy, through NMR metabolomics studies of lysed cells and aqueous extracts analysis. The results show that MG-63 cells treated with cisplatin (cDDP) undergo a strong up-regulation of lipid contents, alterations in phospholipid constituents (choline compounds) and biomarkers of DNA degradation, all associated with cell death by apoptosis. Cells exposed to doxorubicin (DOX) or methotrexate (MTX) showed much slighter metabolic changes, without any relevant alteration in lipid contents. However, metabolic changes associated with altered Krebs cycle, oxidative stress and nucleotides metabolism were detected and were tentatively interpreted at the light of the known mechanisms of action of these drugs. The metabolic impact of the exposure of MG-63 cells and osteoblasts to cDDP and the Pd2Spm complex is described in Chapter 6. Results show that, despite the ability of the two agents to bind DNA, the metabolic consequences that arise from exposure to them are distinct, namely in what concerns to variation in lipid contents (absent for Pd2Spm). Apoptosis detection assays showed that, differently from what was seen for MG-63 cells treated with cDDP, the decreased number of living cells upon exposure to Pd2Spm was not due to cell death by apoptosis or necrosis. Moreover, the latter agent induces more marked alterations in osteoblasts than in cancer cells, while the opposite seemed to occur upon cDDP exposure. Nevertheless, the results from MG-63 cells exposure to combination regimens with cDDP- or Pd2Spm-based cocktails, described in Chapter 7, revealed that, in combination, the two agents induce similar metabolic responses, arising from synergy mechanisms between the tested drugs. Finally, the main conclusions of this thesis are summarized in Chapter 8, and future perspectives in the light of this work are presented.

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Pós-graduação em Química - IQ