@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} } @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{Schlossarek2023, author = {Schlossarek, Dennis}, title = {Identification of dynamic protein-metabolite complexes in saccharomyces cerevisiae using co-fractionation mass spectrometry}, doi = {10.25932/publishup-58282}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-582826}, school = {Universit{\"a}t Potsdam}, pages = {123}, year = {2023}, abstract = {Cells are built from a variety of macromolecules and metabolites. Both, the proteome and the metabolome are highly dynamic and responsive to environmental cues and developmental processes. But it is not their bare numbers, but their interactions that enable life. The protein-protein (PPI) and protein-metabolite interactions (PMI) facilitate and regulate all aspects of cell biology, from metabolism to mitosis. Therefore, the study of PPIs and PMIs and their dynamics in a cell-wide context is of great scientific interest. In this dissertation, I aim to chart a map of the dynamic PPIs and PMIs across metabolic and cellular transitions. As a model system, I study the shift from the fermentative to the respiratory growth, known as the diauxic shift, in the budding yeast Saccharomyces cerevisiae. To do so, I am applying a co-fractionation mass spectrometry (CF-MS) based method, dubbed protein metabolite interactions using size separation (PROMIS). PROMIS, as well as comparable methods, will be discussed in detail in chapter 1. Since PROMIS was developed originally for Arabidopsis thaliana, in chapter 2, I will describe the adaptation of PROMIS to S. cerevisiae. Here, the obtained results demonstrated a wealth of protein-metabolite interactions, and experimentally validated 225 previously predicted PMIs. Applying orthogonal, targeted approaches to validate the interactions of a proteogenic dipeptide, Ser-Leu, five novel protein-interactors were found. One of those proteins, phosphoglycerate kinase, is inhibited by Ser-Leu, placing the dipeptide at the regulation of glycolysis. In chapter 3, I am presenting PROMISed, a novel web-tool designed for the analysis of PROMIS- and other CF-MS-datasets. Starting with raw fractionation profiles, PROMISed enables data pre-processing, profile deconvolution, scores differences in fractionation profiles between experimental conditions, and ultimately charts interaction networks. PROMISed comes with a user-friendly graphic interface, and thus enables the routine analysis of CF-MS data by non-computational biologists. Finally, in chapter 4, I applied PROMIS in combination with the isothermal shift assay to the diauxic shift in S. cerevisiae to study changes in the PPI and PMI landscape across this metabolic transition. I found a major rewiring of protein-protein-metabolite complexes, exemplified by the disassembly of the proteasome in the respiratory phase, the loss of interaction of an enzyme involved in amino acid biosynthesis and its cofactor, as well as phase and structure specific interactions between dipeptides and enzymes of central carbon metabolism. In chapter 5, I am summarizing the presented results, and discuss a strategy to unravel the potential patterns of dipeptide accumulation and binding specificities. Lastly, I recapitulate recently postulated guidelines for CF-MS experiments, and give an outlook of protein interaction studies in the near future.}, language = {en} }