@phdthesis{Scherling2009,
  author    = {Scherling, Christian},
  title     = {Environmental Metabolomics - Metabolomische Studien zu Biodiversit{\"a}t, ph{\"a}notypischer Plastizit{\"a}t und biotischen Wechselwirkungen von Pflanzen},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-32411},
  school      = {Universit{\"a}t Potsdam},
  year      = {2009},
  abstract  = {Ein genereller Ansatz zur Charakterisierung von biologischen Systemen bietet die Untersuchung des Metaboloms, dessen Analyse als „Metabolomics" bezeichnet wird. "Omics"- Technologien haben das Ziel, ohne Selektionskriterien m{\"o}glichst alle Bestandteile einer biologischen Probe zu detektieren (identifizieren und quantifizieren), um daraus R{\"u}ckschl{\"u}sse auf nicht vorhersehbare und somit neuartige Korrelationen in biologischen Systemen zu ziehen. Ein zentrales Dogma in der Biologie besteht in der Kausalit{\"a}t zwischen Gen - Enzym - Metabolite. Perturbationen auf einer Ebene rufen systemische Antworten hervor, die in einem ver{\"a}nderten Ph{\"a}notyp m{\"u}nden k{\"o}nnen. Metabolite sind die Endprodukte von zellul{\"a}ren regulatorischen Prozessen, deren Abundanz durch die Resonanz auf genetische Modifikationen oder Umwelteinfl{\"u}sse zur{\"u}ckzuf{\"u}hren ist. Zudem repr{\"a}sentieren Metabolite ultimativ den Ph{\"a}notyp eines Organismus und haben die F{\"a}higkeit als Biomarker zu fungieren. Die integrale Analyse verschiedenster Stoffwechselwegen wie Krebszyklus, Pentosephosphatzyklus oder Calvinzyklus offeriert die Identifikation von metabolischen Mustern. In dieser Arbeit wurden sowohl das targeted Profiling via GC-TOF-MS als auch das untargeted Profiling via GC-TOF-MS und LC-FT-MS als analytische Strategien genutzt, um biologische Systeme anhand ihrer Metabolite zu charakterisieren und um physiologische Muster als Resonanz auf endogene oder exogene Stimuli zu erkennen. Dabei standen die metabolische, ph{\"a}notypische und genotypische Plastizit{\"a}t von Pflanzen im Fokus der Untersuchungen. Metabolische Varianzen eines Ph{\"a}notyps reflektieren die genotyp-abh{\"a}ngige Resonanz des Organismus auf umweltbedingte Parameter (abiotischer und biotischer Stress, Entwicklung) und k{\"o}nnen mit sensitiven Metabolite Profiling Methoden determiniert werden. Diese Anwendungen haben unter anderem auch zum Begriff des „Environmental Metabolomics" gef{\"u}hrt. In Kapitel 2 wurde der Einfluss biotischer Interaktionen von endophytischen Bakterien auf den Metabolismus von Pappelklonen untersucht; Kapitel 3 betrachtet die metabolische Plastizit{\"a}t von Pflanzen im Freiland auf ver{\"a}nderte biotische Interaktionsmuster (Konkurrenz/Diversit{\"a}t/Artenzusammensetzung); Abschließend wurde in Kapitel 4 der Einfluss von spezifischen genetischen Modifikationen an Peroxisomen und den daraus resultierenden ver{\"a}nderten metabolischen Fluss der Photorespiration dargestellt. Aufgrund der sensitiven Analyse- Technik konnten metabolische Ph{\"a}notypen, die nicht zwingend in einen morphologischen Ph{\"a}notyp m{\"u}ndeten, in drei biologischen Systemen identifiziert und in einen stoffwechselphysiologischen Kontext gestellt werden. Die drei untersuchten biologischen Systeme - in vitro- Pappeln, Gr{\"u}nland- Arten (Arrhenatherion-Gesellschaft) und der Modellorganismus (Arabidopsis) - belegten anschaulich die Plastizit{\"a}t des Metabolismus der Arten, welche durch endogene oder exogene Faktoren erzeugt wurden.},
  language  = {de}
}
@phdthesis{Boelling2006,
  author    = {B{\"o}lling, Christian},
  title     = {Comprehensive metabolite analysis in Chlamydomonas reinhardtii : method development and application to the study of environmental and genetic perturbations},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-11329},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {This study introduces a method for multiparallel analysis of small organic compounds in the unicellular green alga Chlamydomonas reinhardtii, one of the premier model organisms in cell biology. The comprehensive study of the changes of metabolite composition, or metabolomics, in response to environmental, genetic or developmental signals is an important complement of other functional genomic techniques in the effort to develop an understanding of how genes, proteins and metabolites are all integrated into a seamless and dynamic network to sustain cellular functions. The sample preparation protocol was optimized to quickly inactivate enzymatic activity, achieve maximum extraction capacity and process large sample quantities. As a result of the rapid sampling, extraction and analysis by gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF) more than 800 analytes from a single sample can be measured, of which over a 100 could be positively identified. As part of the analysis of GC-TOF raw data, aliquot ratio analysis to systematically remove artifact signals and tools for the use of principal component analysis (PCA) on metabolomic datasets are proposed. Cells subjected to nitrogen (N), phosphorus (P), sulfur (S) or iron (Fe) depleted growth conditions develop highly distinctive metabolite profiles with metabolites implicated in many different processes being affected in their concentration during adaptation to nutrient deprivation. Metabolite profiling allowed characterization of both specific and general responses to nutrient deprivation at the metabolite level. Modulation of the substrates for N-assimilation and the oxidative pentose phosphate pathway indicated a priority for maintaining the capability for immediate activation of N assimilation even under conditions of decreased metabolic activity and arrested growth, while the rise in 4-hydroxyproline in S deprived cells could be related to enhanced degradation of proteins of the cell wall. The adaptation to sulfur deficiency was analyzed with greater temporal resolution and responses of wild-type cells were compared with mutant cells deficient in SAC1, an important regulator of the sulfur deficiency response. Whereas concurrent metabolite depletion and accumulation occurs during adaptation to S deprivation in wild-type cells, the sac1 mutant strain is characterized by a massive incapability to sustain many processes that normally lead to transient or permanent accumulation of the levels of certain metabolites or recovery of metabolite levels after initial down-regulation. For most of the steps in arginine biosynthesis in Chlamydomonas mutants have been isolated that are deficient in the respective enzyme activities. Three strains deficient in the activities of N-acetylglutamate-5-phosphate reductase (arg1), N2 acetylornithine-aminotransferase (arg9), and argininosuccinate lyase (arg2), respectively, were analyzed with regard to activation of endogenous arginine biosynthesis after withdrawal of externally supplied arginine. Enzymatic blocks in the arginine biosynthetic pathway could be characterized by precursor accumulation, like the amassment of argininosuccinate in arg2 cells, and depletion of intermediates occurring downstream of the enzymatic block, e.g. N2-acetylornithine, ornithine, and argininosuccinate depletion in arg9 cells. The unexpected finding of substantial levels of the arginine pathway intermediates N-acetylornithine, citrulline, and argininosuccinate downstream the enzymatic block in arg1 cells provided an explanation for the residual growth capacity of these cells in the absence of external arginine sources. The presence of these compounds, together with the unusual accumulation of N-Acetylglutamate, the first intermediate that commits the glutamate backbone to ornithine and arginine biosynthesis, in arg1 cells suggests that alternative pathways, possibly involving the activity of ornithine aminotransferase, may be active when the default reaction sequence to produce ornithine via acetylation of glutamate is disabled.},
  language  = {en}
}
@phdthesis{Schauer2006,
  author    = {Schauer, Nicolas},
  title     = {Quantitative trait loci (QTL) for metabolite accumulation and metabolic regulation : metabolite profiling of interspecific crosses of tomato},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7643},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {The advent of large-scale and high-throughput technologies has recently caused a shift in focus in contemporary biology from decades of reductionism towards a more systemic view. Alongside the availability of genome sequences the exploration of organisms utilizing such approach should give rise to a more comprehensive understanding of complex systems. Domestication and intensive breeding of crop plants has led to a parallel narrowing of their genetic basis. The potential to improve crops by conventional breeding using elite cultivars is therefore rather limited and molecular technologies, such as marker assisted selection (MAS) are currently being exploited to re-introduce allelic variance from wild species. Molecular breeding strategies have mostly focused on the introduction of yield or resistance related traits to date. However given that medical research has highlighted the importance of crop compositional quality in the human diet this research field is rapidly becoming more important. Chemical composition of biological tissues can be efficiently assessed by metabolite profiling techniques, which allow the multivariate detection of metabolites of a given biological sample. Here, a GC/MS metabolite profiling approach has been applied to investigate natural variation of tomatoes with respect to the chemical composition of their fruits. The establishment of a mass spectral and retention index (MSRI) library was a prerequisite for this work in order to establish a framework for the identification of metabolites from a complex mixture. As mass spectral and retention index information is highly important for the metabolomics community this library was made publicly available. Metabolite profiling of tomato wild species revealed large differences in the chemical composition, especially of amino and organic acids, as well as on the sugar composition and secondary metabolites. Intriguingly, the analysis of a set of S. pennellii introgression lines (IL) identified 889 quantitative trait loci of compositional quality and 326 yield-associated traits. These traits are characterized by increases/decreases not only of single metabolites but also of entire metabolic pathways, thus highlighting the potential of this approach in uncovering novel aspects of metabolic regulation. Finally the biosynthetic pathway of the phenylalanine-derived fruit volatiles phenylethanol and phenylacetaldehyde was elucidated via a combination of metabolic profiling of natural variation, stable isotope tracer experiments and reverse genetic experimentation.},
  subject      = {Tomate},
  language  = {en}
}
@phdthesis{Birkemeyer2005,
  author    = {Birkemeyer, Claudia Sabine},
  title     = {Signal-metabolome interactions in plants},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7144},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {From its first use in the field of biochemistry, instrumental analysis offered a variety of invaluable tools for the comprehensive description of biological systems. Multi-selective methods that aim to cover as many endogenous compounds as possible in biological samples use different analytical platforms and include methods like gene expression profile and metabolite profile analysis. The enormous amount of data generated in application of profiling methods needs to be evaluated in a manner appropriate to the question under investigation. The new field of system biology rises to the challenge to develop strategies for collecting, processing, interpreting, and archiving this vast amount of data; to make those data available in form of databases, tools, models, and networks to the scientific community. On the background of this development a multi-selective method for the determination of phytohormones was developed and optimised, complementing the profile analyses which are already in use (Chapter I). The general feasibility of a simultaneous analysis of plant metabolites and phytohormones in one sample set-up was tested by studies on the analytical robustness of the metabolite profiling protocol. The recovery of plant metabolites proved to be satisfactory robust against variations in the extraction protocol by using common extraction procedures for phytohormones; a joint extraction of metabolites and hormones from plant tissue seems practicable (Chapter II). Quantification of compounds within the context of profiling methods requires particular scrutiny (Chapter II). In Chapter III, the potential of stable-isotope in vivo labelling as normalisation strategy for profiling data acquired with mass spectrometry is discussed. First promising results were obtained for a reproducible quantification by stable-isotope in vivo labelling, which was applied in metabolomic studies. In-parallel application of metabolite and phytohormone analysis to seedlings of the model plant Arabidopsis thaliana exposed to sulfate limitation was used to investigate the relationship between the endogenous concentration of signal elements and the 'metabolic phenotype' of a plant. An automated evaluation strategy was developed to process data of compounds with diverse physiological nature, such as signal elements, genes and metabolites - all which act in vivo in a conditional, time-resolved manner (Chapter IV). Final data analysis focussed on conditionality of signal-metabolome interactions.},
  subject      = {Pflanzenhormon},
  language  = {en}
}