In our society in the 21st century one of the greatest challenges is to provide raw materials to the industry in a sustainable way. This requires increased use of renewable raw materials such as wood. Wood is widely used in pulp, paper and textile industries and ongoing research efforts aim to extend the use of wood in e.g. liquid biofuels and green chemicals. At Umeå Plant Science Center (UPSC) poplar trees are used as model systems to study wood formation. The objective is to understand the function of the genes underlying the wood forming process. This knowledge could result in improved chemical and physical wood properties suitable for different industrial processes. This will in turn meet the demands for a sustainable development. This thesis presents tools and strategies to unravel information regarding genetic perturbations in poplar trees by the use of nuclear magnetic resonance (NMR) spectroscopy and multivariate analysis (MVA). Furthermore, gas chromatography/mass spectrometry (GC/MS) is briefly discussed in this context. Multivariate methods to find patterns and trends in NMR data have been used for more than 30 years. In the beginning MVA was applied in pattern recognition studies in order to characterize chemical structures with different ligands and in different solvents. Today, the multivariate methods have developed and the research have changed focus towards the study of biofluids from plant extracts, urine, blood plasma, saliva etc. NMR spectra of biofluids can contain thousands of resonances, originating from hundreds of different compounds. This type of complex data can be hard to summarize and interpret without appropriate tools and require sophisticated strategies for data evaluation. Related fields of research are rapidly growing and are here referred to as metabolomics. Five different research projects are presented which includes analysis of poplar samples where macromolecules such as pectin and also small molecules such as metabolites were analysed by high resolution magic angle spinning (HR/MAS) NMR spectroscopy, 1H-13C HSQC NMR and GC/MS. The discussion topics include modelling of metabolomic time dependencies in combination with genetic variation, validation of orthogonal projections to latent structures (OPLS) models, selection of putative biomarkers related to genetic modification from OPLS-discriminant analysis (DA) models, measuring one of the main components found in the primary cell-walls of poplar i.e. pectin, the use of Fourier transformed two-dimensional (2D) NMR data in OPLS modelling and model complexity in a PLS model.

The conditioning effect in metabolomic studies is the phenomenon of initial variation of analytical results in the first 5-10 injections of a biological sample in chromatographic systems. The deviation manifests itself as a drift in retention time, peak area and in multivariate analysis. It is a major quality assurance problem in the metabolomic field and if not accounted for would result in high analytical variance. The aim of this study was to investigate the conditioning effect and to gain further knowledge about it. The study was carried out on UPLC of hydrophilic liquid chromatography (HILIC) type coupled to quadrupole time of flight (QTOF) MS. A systematic study was designed to investigate the effects of the age of the analytical column. An investigation into certain matrix components as a possible cause of the conditioning effect was made. Different sample preparation methods were investigated. One result showed that no conditioning could be seen and the system appeared stable from the first injection. Differences in sample composition between samples with conditioning effect and samples without conditioning effect were investigated. No correlation between conditioning effect and levels of certain matrix compounds could be found. More studies of correlation between sample composition and the amount of conditioning occurring is needed. Some samples appear to have no retention time drift but have a significant drift in peak area and in multivariate analysis. This is an indication that the conditioning effect should be analysed in more ways than one before determining if a system is stable.

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La métabolomique propose une approche basée sur l’étude d’une réponse métabolique globale et dynamique d’un organisme à des stimuli biologiques ou à des mutations génétiques et ainsi constitue un outil de recherche translationnel à fort potentiel en oncologie. Nous avons appliqué l’approche métabonomique par RMN à haut champ à l’analyse d’échantillons sanguins issus d’études cliniques coordonnées par le Centre Léon Bérard et pour la cohorte prospective E3N (Etude Epidémiologique auprès de femmes de la MGEN) dans le but d’identifier de marqueurs systémiques du cancer à partir de fluides biologiques humains. Tout d’abord, l’analyse statistique des profils métaboliques de sérums de patientes atteintes d’un cancer du sein a permis de mettre en évidence une signature métabolique discriminant les patients ayant un cancer localisé des patientes métastatiques et de révéler des biomarqueurs associés à la sévérité de ce cancer. D’autre part, cette approche permet des investigations sur les effets de la chimiothérapie. Ainsi, lors de l’étude de sérums de patients atteints d’un cancer du rein métastatique traités par une chimiothérapie expérimentale, une signature métabolique caractéristique de la modification plus rapide du métabolisme de l’hôte a été mise en évidence pour ce traitement en comparaison à deux thérapies conventionnelles. Enfin, l’analyse de plasmas sanguins issus de la cohorte E3N s’intéresse à l’identification de biomarqueurs associés à la survenue du cancer du sein et de son étiologie. Après identification et quantification des sources de variations systématiques impactant les profils métaboliques obtenus, une analyse stratifiée de la cohorte « cas prospectifs »-contrôles est présentée dans cette thèse. / Metabolomics offers an approach based on the study of a comprehensive and dynamic metabolic response of an organism to biological stimuli or genetic mutations and thus constitutes a tool for translational research with a strong potential in oncology. We applied the metabonomic approach by high field NMR for the analysis of blood samples from clinical studies coordinated by the Centre Léon Bérard and for the prospective E3N cohort ( Etude Epidémiologique auprès de femmes de la MGEN ) in order to identify systemic cancer markers from human biological fluids . First, the statistical analysis of metabolic serum profiles from patients with breast cancer has highlighted a metabolic signature discriminating patients with localized cancer and metastatic patients and reveal biomarkers associated with severity of this cancer. Furthermore , this approach allows investigations on the effects of chemotherapy. Thus, during the study of sera from patients with metastatic renal cell carcinoma treated with experimental chemotherapy, a characteristic metabolic signature of faster modification of the host metabolism has been demonstrated for this treatment in comparison to two standard therapies. Finally, analysis of blood plasma from the E3N cohort interests the identification of biomarkers associated with the development of breast cancer and its etiology . After identification and quantification of sources of systematic variations affecting the metabolic profiles obtained, a stratified analysis of the "prospective case "- controls cohort is presented in this thesis.

Diss. (sammanfattning) Umeå : Umeå universitet, 2009. / Härtill 5 uppsatser. Även tryckt utgåva.

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