The extensive agricultural usage of organohalogenated pesticides has raised many concerns about their potential hazards especially in the soil environment. Environmental metabolomics is an emerging field that investigates the changes in the metabolic profile of native organisms in their environment due to the presence of an environmental stressor. Research presented here explores the potential of Nuclear Magnetic Resonance (NMR)-based metabolomics to examine the sub-lethal exposure of the earthworm, Eisenia fetida to sub-lethal concentrations of organohalogenated pesticides. Various one-dimensional (1-D) and two dimensional (2-D) NMR techniques were compared in a contact filter paper test earthworm metabolomic study using endosulfan, a prevalent pesticide in the environment. The results determined that both the 1H Presaturation Utilizing Gradients and Echos (PURGE) and the 1H-13C Heteronuclear Single Quantum Coherence (HSQC) NMR techniques were most effective in discriminating and identifying significant metabolites in earthworms due to contaminant exposure. These two NMR techniques were further explored in another metabolomic study using various sub-lethal concentrations of endosulfan and an organofluorine pesticide, trifluralin to E. fetida. Principal component analysis (PCA) tests showed increasing separation between the exposed and unexposed earthworms as the concentrations for both contaminants increased. A neurotoxic mode of action (MOA) for endosulfan and a non-polar narcotic MOA for trifluralin were delineated as many significant metabolites, arising from exposure, were identified. The earthworm tissue extract is commonly used as the biological medium for metabolomic studies. However, many overlapping resonances are apparent in an earthworm tissue extract NMR spectrum due to the abundance of metabolites present. To mitigate this spectral overlap, the earthworm’s coelomic fluid (CF) was tested as a complementary biological medium to the tissue extract in an endosulfan exposure metabolomic study to identify additional metabolites of stress. Compared to tests on the tissue extract, a plethora of different metabolites were identified in the earthworm CF using 1-D PURGE and 2-D HSQC NMR techniques. In addition to the neurotoxic MOA identified previously, an apoptotic MOA was also postulated due to endosulfan exposure. This thesis also explored the application of 1-D and 2-D NMR techniques in a soil metabolomic study to understand the exposure of E. fetida to sub-lethal concentrations of endosulfan and its main degradation product, endosulfan sulfate. The earthworm’s CF and tissue extract were both analyzed to maximize the significant metabolites identified due to contaminant exposure. The PCA results identified similar toxicity for both organochlorine contaminants as the same separation, between exposed to the unexposed earthworms, were detected at various concentrations. Both neurotoxic and apopotic MOAs were observed as identical fluctuations of significant metabolites were found. This research demonstrates the potential of NMR-based metabolomics as a powerful environmental monitoring tool to understand sub-lethal organohalogenated pesticide exposure in soil using earthworms as living probes.

This thesis is dedicated to developments and applications of metabolomics, exploiting high field NMR spectroscopy. The first part is dedicated to a general presentation of metabolomics. We also report results about the introduction of reduced dimensionality techniques for the characterization of complex mixtures, coined targeted projection NMR spectroscopy. The second part of this manuscript reports results about three different metabolomic studies carried out in human populations. The first analysis demonstrates the suitability for metabolomics of serum samples collected in the framework of the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The second study investigates a serum metabolic signature of metastatic breast cancer. The last analysis establishes potential plasma metabolic signatures for different liver pathologies, like hepatocellular carcinoma. The third part of this thesis is dedicated to the characterization of various model organisms. The first study presents a characterization of plasma and urine metabolic differences between four rat strains commonly used as controls in genetic studies. In the second study, we investigate the effects of physiological aging in Caenorhabditis elegans (C. elegans) and observe that dietary restriction buffers metabolic changes associated with aging. We further identify that perturbations in phosphocholine metabolism correlate with life expectancy. The third analysis of this part characterizes the ahr-1 C. elegans mutant, showing strong metabolic changes in ahr-1 mutants, which suggest an involvement in development and aging processes. We finally investigate in the last study the effects at the metabolic level of the interaction between an endogenous protein E4F1 and a viral protein HBx in liver cells infected by hepatitis B virus.

The extensive agricultural usage of organohalogenated pesticides has raised many concerns about their potential hazards especially in the soil environment. Environmental metabolomics is an emerging field that investigates the changes in the metabolic profile of native organisms in their environment due to the presence of an environmental stressor. Research presented here explores the potential of Nuclear Magnetic Resonance (NMR)-based metabolomics to examine the sub-lethal exposure of the earthworm, Eisenia fetida to sub-lethal concentrations of organohalogenated pesticides. Various one-dimensional (1-D) and two dimensional (2-D) NMR techniques were compared in a contact filter paper test earthworm metabolomic study using endosulfan, a prevalent pesticide in the environment. The results determined that both the 1H Presaturation Utilizing Gradients and Echos (PURGE) and the 1H-13C Heteronuclear Single Quantum Coherence (HSQC) NMR techniques were most effective in discriminating and identifying significant metabolites in earthworms due to contaminant exposure. These two NMR techniques were further explored in another metabolomic study using various sub-lethal concentrations of endosulfan and an organofluorine pesticide, trifluralin to E. fetida. Principal component analysis (PCA) tests showed increasing separation between the exposed and unexposed earthworms as the concentrations for both contaminants increased. A neurotoxic mode of action (MOA) for endosulfan and a non-polar narcotic MOA for trifluralin were delineated as many significant metabolites, arising from exposure, were identified. The earthworm tissue extract is commonly used as the biological medium for metabolomic studies. However, many overlapping resonances are apparent in an earthworm tissue extract NMR spectrum due to the abundance of metabolites present. To mitigate this spectral overlap, the earthworm’s coelomic fluid (CF) was tested as a complementary biological medium to the tissue extract in an endosulfan exposure metabolomic study to identify additional metabolites of stress. Compared to tests on the tissue extract, a plethora of different metabolites were identified in the earthworm CF using 1-D PURGE and 2-D HSQC NMR techniques. In addition to the neurotoxic MOA identified previously, an apoptotic MOA was also postulated due to endosulfan exposure. This thesis also explored the application of 1-D and 2-D NMR techniques in a soil metabolomic study to understand the exposure of E. fetida to sub-lethal concentrations of endosulfan and its main degradation product, endosulfan sulfate. The earthworm’s CF and tissue extract were both analyzed to maximize the significant metabolites identified due to contaminant exposure. The PCA results identified similar toxicity for both organochlorine contaminants as the same separation, between exposed to the unexposed earthworms, were detected at various concentrations. Both neurotoxic and apopotic MOAs were observed as identical fluctuations of significant metabolites were found. This research demonstrates the potential of NMR-based metabolomics as a powerful environmental monitoring tool to understand sub-lethal organohalogenated pesticide exposure in soil using earthworms as living probes.

Orientador: Gabriela Castellano / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Fisica Gleb Wataghin. / Made available in DSpace on 2018-08-12T12:39:12Z (GMT). No. of bitstreams: 1 CuellarBaena_SandraPatricia_M.pdf: 2971806 bytes, checksum: 993051b37ed11a93fc4c48a83e24003d (MD5) Previous issue date: 2008 / Resumo: Este trabalho visou o estudo e validação de técnicas de pre-processamento e quantificação de dados provenientes da técnica de Espectroscopia por Ressonância Magnética (MRS, do inglês Magnetic Resonance Spectroscopy), obtidos do cérebro humano in vivo, para a extração de informação que fosse clinicamente relevante para o estudo e diagnostico de tumores cerebrais. Para isso, foi feito o estudo da técnica com base na literatura, incluindo a revisão dos aspectos físicos envolvidos, estudando os métodos computacionais utilizados para o pre-processamento e quantificação dos dados, e os aspectos bioquímicos dos metabólicos de interesse presentes no cérebro humano, passiveis de serem quantificados através da técnica. Especificamente, foi estudado um método de quantificação de dados de MRS, o método. AMARES (Advanced Method for Accurate, Robust and Efficient Spectral fitting of MRS data), aplicado na quantificação de dados de MRS adquiridos de sujeitos controles e pacientes portadores de tumores cerebrais, provenientes de uma base de dados do Laboratório de Neuroimagem (LNI - Hospital das Clinicas - UNICAMP). Isso foi feito utilizando o software de domínio público jMRUI (http://sermn02.uab.es/mrui/)[1], que possui o método AMARES já implementado. Estes resultados foram comparados com resultados provenientes de uma quantificação manual desses mesmos dados, realizada previamente como parte do projeto de doutorado da Dra. Andréia Vasconcellos (atual docente do Depto. de Radiologia da FCM/UNICAMP)[2]. Foi verificada a concordância entre os dois métodos de quantificação, e também a viabilidade de usar os resultados da quantificação com o método automático para alem de diferenciar entre os grupos de pacientes e controles, realizar a separação dos Pacientes com tumores em diferentes grupos. Obteve-se que os resultados obtidos com o método automático foram mais precisos e consistentes que os obtidos com o método manual, e permitiram uma melhor classificação dos tipos de tumores. Adicionalmente, foram incluídos neste trabalho os resultados do estudo de perfis metabólicos ex vivo em tumores cerebrais pediátricos através da técnica HR-MAS (do inglês High Resolution Magic Angle Spinning). Este estudo adicional foi realizado no Laboratório de Imagem Molecular da Faculdade de Medicina da Universidade de Valencia (Espanha) através do Programa Santander de Mobilidade Internacional e financiado através de uma bolsa do Banco Santander-Banespa. / Abstract: The aim of this work was to study and validate techniques for pre-processing and quantificating Magnetic Resonance Spectroscopy data, obtained in vivo from the human brain, in order to get information clinically useful for the study and diagnosis of brain tumors. Therefore, a literature-based study of the technique was made, including a review of the Physics concepts involved, the data acquisition process in the scanner and the computational methods used to pre-process and quantificate the spectral data, as well as the biochemical aspects of the metabolites of interest in the human brain that can be detected by this technique. Special attention was given to the AMARES (Advanced Method for Accurate, Robust and Efficient Spectral fitting of MRS data) method for MRS data quantification, which was studied and applied to the quantification of data from control subjects and patients with brain tumors. The data came from a database of the Neuroimaging Laboratory (LNI - Hospital das Clinicas - UNICAMP). The quantification with AMARES was made through the jMRUI software (http://sermn02.uab.es/mrui/) [1], a public domain software for processing and quantification of MRS data. These results were compared to the results obtained with a manual quantification of the same data, previously done as part of the PhD thesis work of Dr. Andreia Vasconcellos (lecturer from the Radiology Department of the School of Medicine, UNICAMP) [2]. The agreement between the results from both quantification methods was verified, as well as the feasibility of using the automatic quantification results to differentiate among tumor types, besides differentiating between patients and controls. Results obtained by the automatic method were more accurate and consistent than those obtained by the manual method allowing a better classification. Additionally, in this work were included the results of the study of ex vivo and in vivo metabolic profiling in pediatric brain tumors using the HR-MAS (High Resolution Magic Angle Spinning) technique. This study was carried out in the Molecular Imaging Laboratory, School of Medicine at the University of Val¿encia (Spain), within the Santander-Banespa Bank International Exchange Program. / Mestrado / Física / Mestre em Física

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Cette thèse est dédiée aux développements méthodologiques et applications de la métabolomique par Résonance Magnétique Nucléaire (RMN) à très hauts champs. La première partie de ce manuscrit est dédiée à une présentation générale de la métabolomique par RMN. Nous décrivons ensuite les résultats obtenus concernant l’introduction d’une technique à dimensionnalité réduite pour la caractérisation des mélanges complexes, dénommée spectroscopie RMN par projections ciblées. La seconde partie de ce manuscrit décrit les résultats de trois études métabolomiques portant sur des populations humaines. La première analyse démontre que les échantillons de sérum collectés dans le cadre de la cohorte européenne prospective internationale EPIC sont appropriés pour une étude métabolomique. Les deux études suivantes recherchent une signature métabolique dans le sérum du cancer du sein métastatique et une signature plasmatique potentielle pour différentes pathologies hépatiques comme le carcinome hépatocellulaire. La troisième partie de cette thèse est dédiée à l’étude d’organismes modèles. La première étude caractérise les différences métaboliques systémiques entre quatre souches de rats couramment utilisées comme contrôles en génétique. Dans la seconde analyse, nous étudions les effets du vieillissement physiologique chez Caenorhabditis elegans (C. elegans), observons que le processus de restriction alimentaire tamponne les modifications métaboliques associées au vieillissement et que des perturbations du métabolisme de la phosphocholine corrèlent avec l’espérance de vie. La troisième étude caractérise des modifications métaboliques importantes chez un mutant de C. elegans, pour le gène ahr-1, suggérant un rôle dans le développement et le vieillissement. Enfin, nous étudions les effets au niveau métabolique de l’interaction entre la protéine endogène E4F1 et la protéine virale HBx dans des cellules hépatiques infectées par le virus de l’hépatite B. / This thesis is dedicated to developments and applications of metabolomics, exploiting high field NMR spectroscopy. The first part is dedicated to a general presentation of metabolomics. We also report results about the introduction of reduced dimensionality techniques for the characterization of complex mixtures, coined targeted projection NMR spectroscopy. The second part of this manuscript reports results about three different metabolomic studies carried out in human populations. The first analysis demonstrates the suitability for metabolomics of serum samples collected in the framework of the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The second study investigates a serum metabolic signature of metastatic breast cancer. The last analysis establishes potential plasma metabolic signatures for different liver pathologies, like hepatocellular carcinoma. The third part of this thesis is dedicated to the characterization of various model organisms. The first study presents a characterization of plasma and urine metabolic differences between four rat strains commonly used as controls in genetic studies. In the second study, we investigate the effects of physiological aging in Caenorhabditis elegans (C. elegans) and observe that dietary restriction buffers metabolic changes associated with aging. We further identify that perturbations in phosphocholine metabolism correlate with life expectancy. The third analysis of this part characterizes the ahr-1 C. elegans mutant, showing strong metabolic changes in ahr-1 mutants, which suggest an involvement in development and aging processes. We finally investigate in the last study the effects at the metabolic level of the interaction between an endogenous protein E4F1 and a viral protein HBx in liver cells infected by hepatitis B virus.

La métabonomique est une approche de choix pour l’identification de biomarqueurs d’intérêts pour le diagnostic de pathologies mais aussi pour l’amélioration de notre compréhension des processus physiopathologiques. La métabonomique offre de nouvelles perspectives en épidémiologie moléculaire, objet principale de cette thèse. Nous avons appliqué l’approche métabonomique par RMN à haut champ à l’analyse de sérums sanguins issus de la cohorte prospective EPIC (European Prospective Investigation into Cancer and nutrition) dans le but d’identifier des biomarqueurs de la survenue du cancer du foie et du cancer du pancréas. L’analyse statistique des profiles métaboliques des sérums obtenus par RMN à 800MHz a permis de mettre en évidence une signature métabolique associée à l’occurrence des hépatocarcinomes (HCC) à cinq ans avant diagnostic en moyenne. L’analyse stratifiée des données a révélé des biomarqueurs précoces mais aussi des biomarqueurs de l’étiologie des HCC. L’analyse métabonomique portée sur le cancer du pancréas n’a à l’inverse pas été concluante. Des méthodes pertinentes pour l’analyse des cohortes épidémiologiques par métabonomique ont été développées, telle qu’une méthode de correction d’effet batch rendant possible la comparaison de données RMN acquises au cours d’une longue période de temps. La méthode statistique PCPR2 développée permet de quantifier l’impact de différents facteurs sur les données métabonomique afin d’en révéler les sources de variations systématiques. D’autre part, l’approche métabonomique permet également l’investigation de questions biologiques plus fondamentales. Cette thèse offre une approche de génomique fonctionnelle à l’étude des cibles métaboliques du récepteur aux hormones thyroïdiennes TRβ dans le foie. L’analyse des données HR-MAS de tissus de foie intacts complémentée par l’analyse d’extraits hépatiques sur un modèle de souris a permis d’éclaircir le rôle de ce récepteur nucléaire. / Metabonomics is a recent approach that enables not only to identify relevant biomarkers for disease diagnosis but also to improve our understanding of biological processes by gaining insight into metabolism. This thesis is mainly dedicated to the application of metabonomics to molecular epidemiology. High-field NMR metabonomic approach was applied to the analysis of serum samples from the large prospective cohort EPIC (European Prospective Investigation into Cancer and nutrition) to identify biomarkers of liver cancer and pancreatic cancer occurrence. The statistical analysis of NMR serum metabolic profiles obtained at 800 MHz enabled to highlight a metabolic signature associated with the occurrence of hepatocellular carcinoma (HCC), in average five years before diagnosis. The stratified analysis revealed both early and etiologic biomarkers of HCC. The NMR metabonomic analysis of the pancreatic cancer did not reveal any metabolic signature of this cancer. Moreover, relevant methods to allow the NMR metabonomic analysis of epidemiological cohort were developed. This thesis proposes a method to correct data for batch effect, making possible the comparison of NMR data recorded in a long period of time. The statistical method PC-PR2 developed enables the quantification of the contribution of different factors onto metabonomic data to reveal systematic variation sources. In addition, the metabonomic approach is also suitable to address specific biological questions by providing a new read-out of the metabolism. Functional genomics by NMR metabonomics was used in this thesis to study the metabolic targets of the thyroid hormone nuclear receptor TRβ in the liver. The analysis of HR-MAS data obtained on intact liver tissue in addition to the analysis of NMR data of liver extracts from a mice model enabled to better understand the role of this nuclear receptor.

Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease, motor neuron disease (MND) and Lou Gehrig’s disease, is a deadly, adult-onset neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons, resulting in evolving paresis of the linked muscles. ALS is defined by classical features of the disease, but may present as a wide spectrum of phenotypes. About 10% of all ALS cases have been reported as familial, of which about 20% have been associated with mutations in the gene encoding for CuZn superoxide dismutase (SOD1). The remaining cases are regarded as sporadic. Research has advanced our understanding of the disease, but the cause is still unknown, no reliable diagnostic test exists, no cure has been found and the current therapies are unsatisfactory. Riluzole (Rilutek®) is the only registered drug for the treatment of ALS. The drug has shown only a modest effect in prolonging life and the mechanism of action of riluzole is not yet fully understood. ALS is diagnosed by excluding diseases with similar symptoms. At an early stage, there are numerous possible diseases that may present with similar symptoms, thereby making the diagnostic procedure cumbersome, extensive and time consuming with a significant risk of misdiagnosis. Biomarkers that can be developed into diagnostic test of ALS are therefore needed. The high number of unsuccessful attempts at finding a single diseasespecific marker, in combination with the complexity of the disease, indicates that a pattern of several markers is perhaps more likely to provide a diagnostic signature for ALS. Metabolomics, in combination with chemometrics, can be a useful tool with which to study human disease. Metabolomics can screen for small molecules in biofluids such as cerebrospinal fluid (CSF) and chemometrics can provide structure and tools in order to handle the types of data generated from metabolomics. In this thesis, ALS has been studied using a combination of metabolomics and chemometrics. Collection and storage of CSF in relation to metabolite stability have been extensively evaluated. Protocols for metabolomics on CSF samples have been proposed, used and evaluated. In addition, a new feature of data processing allowing new samples to be predicted into existing models has been tested, evaluated and used for metabolomics on blood and CSF. A panel of potential biomarkers has been generated for ALS and subtypes of ALS. An overall decrease in metabolite concentration was found for subjects with ALS compared to their matched controls. Glutamic acid was one of the metabolites found to be decreased in patients with ALS. A larger metabolic heterogeneity was detected among SALS cases compared to FALS. This was also reflected in models of SALS and FALS against their respective matched controls, where no significant difference from control was found for SALS while the FALS samples significantly differed from their matched controls. Significant deviating metabolic patterns were also found between ALS subjects carrying different mutations in the gene encoding SOD1.

Metabolism is the sum of all chemical processes with the purpose to maintain life, as well as enable reproduction, in a living organism. Through the study of metabolism, increased understanding of pharmacological mechanisms and diseases can be achieved. This thesis describes several ways of doing so, including targeted analysis of selected metabolites and investigations of systematic metabolic differences between selected groups through pattern recognition. A method for exploring metabolic patterns in urine samples after intake of coffee or tea was developed. The methodology was later used with the aim to find biomarkers for prostate cancer and urinary bladder cancer. Furthermore, a fully automated quantitative method was developed for concentration measurements of the double prodrug ximelagatran and its metabolites in pig liver. The method was then used to study the roll of active transporters in pig liver cells. Moreover, a fundamental study was conducted to investigate how monitoring of small, doubly charged analytes can improve the limit of detection and precision in a quantitative method. The techniques used for the experiments were liquid separation coupled to electrospray mass spectrometry. Extra efforts were made to make the separation and the ionization as compatible as possible to each other for increased quality of the collected data.