TY - GEN A1 - Zwaag, Jelle A1 - Horst, Rob ter A1 - Blaženović, Ivana A1 - Stößel, Daniel A1 - Ratter, Jacqueline A1 - Worseck, Josephine M. A1 - Schauer, Nicolas A1 - Stienstra, Rinke A1 - Netea, Mihai G. A1 - Jahn, Dieter A1 - Pickkers, Peter A1 - Kox, Matthijs T1 - Involvement of lactate and pyruvate in the anti-inflammatory effects exerted by voluntary activation of the sympathetic nervous system T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1413 KW - metabolomics KW - LPS KW - endotoxin KW - pyruvate KW - lactate KW - cytokines KW - inflammation KW - human endotoxemia KW - cori cycle KW - warburg effect Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517784 SN - 1866-8372 IS - 4 ER - TY - JOUR A1 - Zwaag, Jelle A1 - Horst, Rob ter A1 - Blaženović, Ivana A1 - Stößel, Daniel A1 - Ratter, Jacqueline A1 - Worseck, Josephine M. A1 - Schauer, Nicolas A1 - Stienstra, Rinke A1 - Netea, Mihai G. A1 - Jahn, Dieter A1 - Pickkers, Peter A1 - Kox, Matthijs T1 - Involvement of lactate and pyruvate in the anti-inflammatory effects exerted by voluntary activation of the sympathetic nervous system JF - Metabolites N2 - We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects. KW - metabolomics KW - LPS KW - endotoxin KW - pyruvate KW - lactate KW - cytokines KW - inflammation KW - human endotoxemia KW - cori cycle KW - warburg effect Y1 - 2020 U6 - https://doi.org/10.3390/metabo10040148 SN - 2218-1989 VL - 10 IS - 4 SP - 1 EP - 18 PB - MDPI CY - Basel ER - TY - THES A1 - Zhang, Baichen T1 - Dissection of phloem transport in cucurbitaceae by metabolomic analysis T1 - Analyse des Phloemtransports bei Cucurbitaceae mittels Metabolomics N2 - This thesis aimed to investigate several fundamental and perplexing questions relating to the phloem loading and transport mechanisms of Cucurbita maxima, by combining metabolomic analysis with cell biological techniques. This putative symplastic loading species has long been used for experiments on phloem anatomy, phloem biochemistry, phloem transport physiology and phloem signalling. Symplastic loading species have been proposed to use a polymer trapping mechanism to accumulate RFO (raffinose family oligosaccharides) sugars to build up high osmotic pressure in minor veins which sustains a concentration gradient that drives mass flow. However, extensive evidence indicating a low sugar concentration in their phloem exudates is a long-known problem that conflicts with this hypothesis. Previous metabolomic analysis shows the concentration of many small molecules in phloem exudates is higher than that of leaf tissues, which indicates an active apoplastic loading step. Therefore, in the view of the phloem metabolome, a symplastic loading mechanism cannot explain how small molecules other than RFO sugars are loaded into phloem. Most studies of phloem physiology using cucurbits have neglected the possible functions of vascular architecture in phloem transport. It is well known that there are two phloem systems in cucurbits with distinctly different anatomical features: central phloem and extrafascicular phloem. However, mistaken conclusions on sources of cucurbit phloem exudation from previous reports have hindered consideration of the idea that there may be important differences between these two phloem systems. The major results are summarized as below: 1) O-linked glycans in C.maxima were structurally identified as beta-1,3 linked glucose polymers, and the composition of glycans in cucurbits was found to be species-specific. Inter-species grafting experiments proved that these glycans are phloem mobile and transported uni-directionally from scion to stock. 2) As indicated by stable isotopic labelling experiments, a considerable amount of carbon is incorporated into small metabolites in phloem exudates. However, the incorporation of carbon into RFO sugars is much faster than for other metabolites. 3) Both CO2 labelling experiments and comparative metabolomic analysis of phloem exudates and leaf tissues indicated that metabolic processes other than RFO sugar metabolism play an important role in cucurbit phloem physiology. 4) The underlying assumption that the central phloem of cucurbits continuously releases exudates after physical incision was proved wrong by rigorous experiments including direct observation by normal microscopy and combined multiple-microscopic methods. Errors in previous experimental confirmation of phloem exudation in cucurbits are critically discussed. 5) Extrafascicular phloem was proved to be functional, as indicated by phloem-mobile carboxyfluorescein tracer studies. Commissural sieve tubes interconnect phloem bundles into a complete super-symplastic network. 6) Extrafascicular phloem represents the main source of exudates following physical incision. The major transported metabolites by these extrafacicular phloem are non-sugar compounds including amino acids, O-glycans, amines. 7) Central phloem contains almost exclusively RFO sugars, the estimated amount of which is up to 1 to 2 molar. The major RFO sugar present in central phloem is stachyose. 8) Cucurbits utilize two structurally different phloem systems for transporting different group of metabolites (RFO sugars and non-RFO sugar compounds). This implies that cucurbits may use spatially separated loading mechanisms (apoplastic loading for extrafascicular phloem and symplastic loading for central phloem) for supply of nutrients to sinks. 9) Along the transport systems, RFO sugars were mainly distributed within central phloem tissues. There were only small amounts of RFO sugars present in xylem tissues (millimolar range) and trace amounts of RFO sugars in cortex and pith. The composition of small molecules in external central phloem is very different from that in internal central phloem. 10) Aggregated P-proteins were manually dissected from central phloem and analysed by both SDS-PAGE and mass spectrometry. Partial sequences of peptides were obtained by QTOF de novo sequencing from trypsin digests of three SDS-PAGE bands. None of these partial sequences shows significant homology to known cucurbit phloem proteins or other plant proteins. This proves that these central phloem proteins are a completely new group of proteins different from those in extrafascicular phloem. The extensively analysed P-proteins reported in literature to date are therefore now shown to arise from extrafascicular phloem and not central phloem, and therefore do not appear to be involved in the occlusion processes in central phloem. N2 - Phloem transportiert ein ausgedehntes Spektrum an Molekülen zwischen Pflanzenorganen, um Wachstum und Entwicklung zu koordinieren. Folglich ist eine umfassende und unvoreingenommene Metabolom-Analyse notwendig, um unser Verständnis über den Transport von Stoffwechselprodukten sowie über Phloemtransport zu vertiefen. Phloemexsudate von Kürbispflanzen werden unter Verwendung der Metabolom-Analyse analysiert. Bei diesen Pflanzen wird angenommen, dass sie symplastische Beladungswege verwenden, um Photoassmilate als Ausgangsschritt des Phloemtransportes zu konzentrieren. Zwei neue Familien Callose-verwandter Substanzen, 1,3-Overknüpfte Glycane, sowie eine Reihe anderer kleinerer Metabolite werden in den Phloemexsudaten detektiert. Metabolom-Daten und physiologische Experimente widersprechen früher berichtetem Verständnis des Phloemexsudationsprozesses in Kürbispflanzen. Folglich bestätigt sich der Phloemexsudationsprozeß durch Kombination unterschiedlicher mikroskopischer Techniken. Kürbispflanzen besitzen zwei Phloemsysteme mit eindeutigen anatomischen Eigenschaften. Es zeigt sich, daß Phloemexsudate in Kürbissen hauptsächlich vom extrafaszikulären Phloem, nicht vom zentralen Phloem, stammen. In den letzten Jahrzehnten wurde gewöhnlich mißverstanden, daß Phloemexsudate vom zentralen Phloem stammen. Die eindeutigen metabolischen Profile der unterschiedlichen Phloemsysteme, die durch Metabolom-Analysen in der räumlichen Auflösung beobachtet werden, bestätigen die unterschiedlichen physiologischen Funktionen der zwei unterschiedlichen Phloemsysteme: das zentrale Phloem transportiert hauptsächlich Zucker, während das extrafaszikuläre Phloem ein ausgedehntes Spektrum von Metaboliten transportiert. Es kann auch ein unterschiedliches metabolisches Profil kleiner Moleküle zwischen internem und externem zentralem Phloem beobachtet werden. Von Strukturproteinen des zentralen Phloems wurden auch Proben genommen und mittels Massenspektrometrie analysiert. Diese Proteine erweisen sich als neuartige Proteine, die sich zu denen im extrafaszikulären Phloem unterscheiden. Dies bestätigt ferner den Funktionsunterschied der unterschiedlichen Phloemsysteme in Kürbispflanzen. Basierend auf diesen neuartigen Entdeckungen des Phloem-Metaboloms und dem vorhergehenden Wissen über den Phloemtransport in Kürbispflanzen, wird ein neues Modell vorgeschlagen, um den Mechanismus des Phloemtransports in der symplastischen Beladung zu verstehen. KW - phloem KW - metabolomics KW - cucurbits KW - phloem proteins KW - phloem KW - symplastic loading KW - metabolomic analysis KW - p-proteins KW - phloem architecture Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-6644 ER - TY - GEN A1 - Witzel, Katja A1 - Neugart, Susanne A1 - Ruppel, Silke A1 - Schreiner, Monika A1 - Wiesner, Melanie A1 - Baldermann, Susanne T1 - Recent progress in the use of ‘omics technologies in brassicaceous vegetables T2 - Frontiers in plant science N2 - Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub optimal irradiation. This review covers recent applications of omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 429 KW - genomics KW - transcriptomics KW - metabolomics KW - proteomics KW - crop KW - microbiomics Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-406479 ER - TY - JOUR A1 - Witzel, Katja A1 - Neugart, Susanne A1 - Ruppel, Silke A1 - Schreiner, Monika A1 - Wiesner, Melanie A1 - Baldermann, Susanne T1 - Recent progress in the use of 'omics technologies in brassicaceous vegetables JF - Frontiers in plant science N2 - Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub optimal irradiation. This review covers recent applications of omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality. KW - genomics KW - transcriptomics KW - metabolomics KW - proteomics KW - crop KW - microbiomics Y1 - 2015 U6 - https://doi.org/10.3389/fpls.2015.00244 SN - 1664-462X VL - 6 PB - Frontiers Research Foundation CY - Lausanne ER - TY - THES A1 - Wittenbecher, Clemens T1 - Linking whole-grain bread, coffee, and red meat to the risk of type 2 diabetes T1 - Der Einfluss von Vollkornbrot, Kaffee, und rotem Fleisch auf das Typ 2 Diabetesrisiko BT - using metabolomics networks to infer potential biological mechanisms BT - Verwendung von Metabolomics-Netzwerken, um auf biologische Mechanismen zu schließen N2 - Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles. Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations. Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years. Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect. Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication. Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified. Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk. Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures. Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes. N2 - Hintergrund: Evidenz aus prospektiven Kohortenstudien belegt, dass der gewohnheitsmäßige Verzehr von Vollkorn, Kaffee und rotem Fleisch mit dem Risiko an Typ 2 Diabetes zu erkranken assoziiert ist. Dieser Risikobeziehung eventuell zugrunde liegende Mechanismen sind allerdings noch weitgehend unklar. Des Weiteren wurde gezeigt, dass Metabolitenprofile im Blut durch die oben genannten Ernährungs-expositionen beeinflusst werden und außerdem in Zusammenhang mit dem Typ 2 Diabetesrisiko stehen. Zusätzlich wurde beschrieben, dass grafische Netzwerkmodelle von Metabolitenprofilen die zugrunde liegenden Stoffwechselprozesse gut abbilden. Zielstellung: Das Ziel dieser Arbeit war es, Hypothesen bezüglich biologischer Mechanismen zu generieren, die die Assoziationen des Vollkornverzehrs, des Kaffeekonsums und des Fleischverzehrs mit dem Typ 2 Diabetesrisiko erklären könnten. Im speziellen sollten Aminosäure- und Lipidprofile als mögliche Mediatoren des Risikozusammenhangs untersucht werden. Studienpopulation: Analysen wurden auf Grundlage von Daten aus der prospektiven EPIC-Potsdam Kohortenstudie (n=27,548) durchgeführt, wobei ein Fall-Kohorten-Design verwendet wurde (n=2317, darunter 692 inzidente Typ 2 Diabetesfälle). Ernährungsgewohnheiten wurden mit einem validierten, semiquantitativen Verzehrshäufigkeitsfragebogen erfasst. Die Konzentrationen von 126 Metaboliten (Aminosäuren, Acylcarnitine, Sphingomyeline und Phosphatidylcholine) wurden zur Basiserhebung genommen Blutproben gemessen. Inzidente Typ 2 Diabetesfälle wurden im Rahmen einer aktiven Folgeerhebung detektiert und verifiziert. Die mediane Dauer des berücksichtigten prospektiven Erhebungszeitraums lag für diese Studie bei 6,6 Jahren. Aufbau der Analysen: Die theoretische Grundlage für den methodischen Ansatz dieser Arbeit bildete die kontrafaktische Theorie der Kausalinferenz. Die in Netzwerken kodierte konditionale Unabhängigkeitsstruktur wurde genutzt, um den Raum möglicher Modelle zu begrenzen, die die beobachteten Zusammenhänge zwischen den Metaboliten erklären könnten. Unter Annahme weniger grundlegender Effektrichtungen (von der Ernährung auf die Netzwerke gerichtete Effekte; von den Netzwerken auf das Diabetesrisiko gerichtete Effekte) genügt die Adjustierung für eine Teilmenge der direkten Nachbarn im Netzwerk, um netzwerkunabhängige direkte Effekte konsistent zu schätzen. Eine weitere Spezifizierung der Modelle war allerdings aufgrund fehlender Richtungsinformationen zu den Metaboliten-abhängigkeiten nicht möglich. Deshalb wurde ein Multi-Modellierungsansatz gewählt, um die Grenzen möglicher Effekte zu schlussfolgern. Alle möglichen Ernährungs-Metaboliten-Beziehungen und Metaboliten-Typ 2 Diabetesrisiko-Beziehungen wurden dadurch in eine der folgenden drei Kategorien klassifiziert: Direkter Effekt, Unklar, Kein Effekt. Querschnittsbeziehungen wurden in multivariabel adjustierten linearen Regressionsmodellen untersucht. Longitudinale Zusammenhänge wurden mit Cox-Regressionsmodellen geschätzt. Alle Modelle wurden für Alter, Geschlecht, Body-Mass-Index, prävalente Hypertonie, Ernährungs- und Lebensstilfaktoren und die Einnahme von Medikamenten adjustiert. Ergebnisse: Der Verzehr von Vollkornbrot stand im Zusammenhang mit niedrigeren Konzentrationen gesättigter und einfach ungesättigter Fettsäuren. Kaffee stand in Beziehung zu niedrigeren Konzentrationen verzweigtkettiger und aromatischer Aminosäuren und hatte potentielle Effekte auf das Fettsäureprofil in den Lipidmetaboliten. Rotes Fleisch zeigte einen Zusammenhang mit niedrigeren Glyzinspiegeln und mit höheren Konzentrationen verzweigtkettiger Aminosäuren. Außerdem stand das Fettsäureprofil in den verschieden Gruppen von Lipidmetaboliten in Zusammenhang mit dem Fleischverzehr. Des Weiteren wurden potentielle Effekte der Metabolite auf das Typ 2 Diabetesrisiko gefunden. Aromatische Aminosäuren und Lipidmetabolite mit geradzahligen, gesättigten (C14-C16) und mit spezifischen mehrfach ungesättigten Fettsäureseitenketten standen mit einem erhöhten Typ 2 Diabetesrisiko in Beziehung. Glyzin, Glutamin und Lipidmetabolite mit einfach ungesättigten und anderen mehrfach ungesättigten Fettsäureseitenketten zeigten einen günstigen Zusammenhang mit dem Diabetesrisiko. Mögliche Mediatoren der Beziehung der Ernährungsexpositionen wurden identifiziert, indem diese Informationen in gemeinsamen grafischen Modellen integriert wurden. Mediationsanalysen zeigten, dass die möglichen Effekte von Vollkornverzehr auf die Lipidmetabolite ungefähr ein Viertel des günstigen Einflusses von Vollkornverzehr auf das Diabetesrisikos erklären könnten. Die möglichen Effekte von Kaffeekonsum und von Fleischverzehr auf Aminosäuren und Lipidmetabolite könnten jeweils ungefähr zwei Drittel der Zusammenhänge mit dem Diabetesrisiko erklären. Schlussfolgerung: Grundlage für die Ergebnisse dieser Arbeit war die Entwicklung eines Algorithmus, der externe Faktoren (kontinuierlich Expositionsvariablen, Ereigniszeit-Daten) und hochdimensionale Metabolitenprofile in einem gemeinsamen grafischen Modell integriert. Die Anwendung dieses Algorithmus auf Daten aus der EPIC-Potsdam Kohortenstudie hat gezeigt, dass die beobachteten konditionalen Unabhängigkeitsstrukturen mit der a priori Mediationshypothese konsistent waren. Der frühe Einfluss auf den Aminosäure- und Lipidstoffwechsel könnte die beobachteten Zusammenhänge zwischen drei wichtigen Ernährungsfaktoren und dem Risiko an Typ 2 Diabetes zu erkranken zu großen Teilen erklären. KW - type 2 diabetes KW - nutrition KW - lipid metabolism KW - metabolomics KW - epidemiology KW - networks KW - graphical models KW - mediation analysis KW - red meat KW - whole-grain KW - Diabetes mellitus Typ 2 KW - Ernährung KW - Fettstoffwechsel KW - Metabolomics KW - Epidemiologie KW - Netzwerke KW - grafische Modelle KW - Mediationsanalyse KW - rotes Fleisch KW - Vollkorn KW - Kaffee KW - coffee Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-404592 ER - TY - THES A1 - Stößel, Daniel T1 - Biomarker Discovery in Multiple Sclerosis and Parkinson’s disease T1 - Biomarkerentwicklung in Multiple Sklerose und der Parkinson-Krankheit BT - novel insights into metabolic disease mechanisms N2 - Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression. By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS. In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation. N2 - Neuroinflammatorische and neurodegenerative Erkrankungen wie Parkinson (PD) und Multiple Sklerose (MS) gehen oft mit einer starken Beeinträchtigung der Lebensqualität einher. Effektive Therapien für die Behandlung sind derzeit nicht verfügbar, was nicht zuletzt eine hohe sozioökonomische Last zur Folge hat. Aufgrund der Heterogenität der Krankheitsbilder ist eine Stratifizierung gerade in der Frühphase der Erkrankung schwierig und basiert hauptsächlich auf klinischen Parametern wie bspw. neurophysiologischen Tests und bildgebenden Verfahren. Aufgrund ihrer guten Zugänglichkeit und Stabilität könnten bestimmte Blut- und Liquor-Metabolitenmarker als Surrogat für neurodegenerative Prozesse dienen, zu einem verbesserten mechanistischen Verständnis dieser Krankheiten führen und nicht zuletzt als “treatment response“ Biomarker in präklinischen und klinischen Entwicklungsprogrammen herangezogen werden. In dieser Arbeit sollten deshalb Plasma- und CSF-Metabolitprofile identifiziert werden, die eine Differenzierung von PD zu gesunden Kontrollen, Assoziierung zu PD mit Demenz (PDD) sowie eine Abgrenzung zu unterschiedlichen PD-Subtypen wie akinetisch-rigiden sowie tremor-dominanten PD-Patienten ermöglichen. Weiterhin wurden in dieser Arbeit Plasmametabolite zur Diagnose von primär-progressiver MS (PPMS) erforscht und auf ihre Spezifität gegenüber schubförmig remittierender MS (RRMS) und PD geprüft sowie deren Verlauf während der PPMS Progression getestet. Hierbei konnten durch “untargeted Metabolomics“ in Kombination mit statistischen Modellen mehrere Plasma- und CSF-Metabolite in PD-Patienten/Erkrankten ermittelt werden, die mit Hilfe von statistischen Diagnosemodellen eine Differenzierung zu gesunden Personen ermöglichen. Darüber hinaus wurden in dieser Arbeit PDD-spezifische Serummetabolite identifiziert, die wiederum genutzt werden können, um diesen PD-Typen von gesunden Individuen und PD-Patienten ohne Demenz abzugrenzen. Des Weiteren konnten bei akinetisch-rigiden PD-Patienten spezifische Metabolite entdeckt werden, die im Vergleich zu tremor-dominanten PD-Patienten eine stärkere metabolische Krankheitssymptomatik suggerieren. Im Zusammenhang mit PPMS wurden in dieser Arbeit spezifische Plasma-Metabolite entdeckt, die zur Diagnose gegen RRMS, PD und gesunden Kontrollen genutzt werden können. Interessanterweise zeigte dabei ein spezifisches Lipid geringere Werte im PPMS Krankheitsverlauf, wodurch sich dieses als möglicher Marker zur Progressionsdiagnostik dieser Krankheit qualifiziert. Abschließend konnten in dieser Arbeit im humanen Stoffwechsel bisher unbekannte Angriffspunkte des Medikaments Dimethylfumarat, das zur Behandlung von RRMS verwendet wird, ermittelt werden. Durch diese Ergebnisse kann der bis jetzt gänzlich unbekannte Wirkungsmechanismus dieses neuen Medikaments besser beschrieben und verstanden, sowie zur Weiterentwicklung neuer Medikamente gegen RRMS genutzt werden. KW - metabolomics KW - biomarker KW - multiple sclerosis KW - Parkinson's disease KW - neurodegeneration KW - neuroinflammation KW - machine-learning KW - Parkinson-Krankheit KW - Biomarker KW - Maschinelles-Lernen KW - Metabolomics KW - Multiple-Sklerose Y1 - 2018 ER - TY - JOUR A1 - Stobiecki, Maciej A1 - Skirycz, Aleksandra A1 - Kerhoas, L. A1 - Kachlicki, P. A1 - Muth, D. A1 - Einhorn, J. A1 - Mueller-Roeber, Bernd T1 - Profiling of phenolic glycosidic conjugates in leaves of Arabidopsis thaliana using LC/MS JF - Metabolomics : the official journal of the Metabolomics Society N2 - Profiling of plant secondary metabolites is still a very difficult task. Liquid chromatography (LC) or capillary electrophoresis hyphenated with different kinds of detectors are methods of choice for analysis of polar, thermo labile compounds with high molecular masses. We demonstrate the applicability of LC combined with UV diode array or/and mass spectrometric detectors for the unambiguous identification and quantification of flavonoid conjugates isolated from Arahidopsis thaliana leaves of different genotypes and grown in different environmental conditions. During LC/UV/MS/MS analyses we were able to identify tetra-, tri, and di-glycosides of kaempferol, quercetin and isorhamnetin. Based on our results we can conclude that due to the co-elution of different chemical compounds in reversed phase H PLC systems the application of UV detectors does not allow to precisely profile all flavonoid conjugates existing in A. thaliana genotypes. Using MS detection it was possible to unambiguously recognize the glycosylation patterns of the aglycones. However, from the mass spectra we could not conclude neither the anomeric form of the C-1 carbon atoms of sugar moieties in glycosidic bonds between sugars or sugar and aglycone nor the position of the second carbon involved in disaccharides. The applicability of collision induced dissociation techniques (CID MS/MS) for structural analyses of the studied group of plant secondary metabolites with two types of analyzers (triple quadrupole or ion trap) was demonstrated. KW - liquid chromatography-mass spectrometry KW - metabolite profiling KW - metabolomics KW - flavonoid glycosides Y1 - 2006 U6 - https://doi.org/10.1007/s11306-006-0031-5 SN - 1573-3882 VL - 2 SP - 197 EP - 219 PB - Springer CY - New York ER - TY - JOUR A1 - Steuer, Ralf A1 - Gross, Thilo A1 - Selbig, Joachim A1 - Blasius, Bernd T1 - Structural kinetic modeling of metabolic networks JF - Proceedings of the National Academy of Sciences of the United States of America N2 - To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle. KW - systems biology KW - computational biochemistry KW - metabolomics KW - metabolic regulation KW - biological robustness Y1 - 2006 U6 - https://doi.org/10.1073/pnas.0600013103 SN - 0027-8424 SN - 1091-6490 VL - 103 IS - 32 SP - 11868 EP - 11873 PB - National Academy of Sciences CY - Washington ER - TY - JOUR A1 - Schwahn, Kevin A1 - Nikoloski, Zoran T1 - Data reduction approaches for dissecting transcriptional effects on metabolism JF - Frontiers in plant science N2 - The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coil, Saccharomycies cerevisiae, and Arabidopsis thaliana. KW - E. coil KW - S. cerevisiae KW - A. thaliana KW - partial correlation KW - principal component analysis KW - metabolomics KW - data reduction KW - regulation Y1 - 2018 U6 - https://doi.org/10.3389/fpls.2018.00538 SN - 1664-462X VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - THES A1 - Schwahn, Kevin T1 - Data driven approaches to infer the regulatory mechanism shaping and constraining levels of metabolites in metabolic networks T1 - Entwicklung von datengestützten Verfahren, um regulatorischen Mechanismen zu untersuchen, die die Metabolitmengen in Stoffwechselnetzwerken beeinflussen N2 - Systems biology aims at investigating biological systems in its entirety by gathering and analyzing large-scale data sets about the underlying components. Computational systems biology approaches use these large-scale data sets to create models at different scales and cellular levels. In addition, it is concerned with generating and testing hypotheses about biological processes. However, such approaches are inevitably leading to computational challenges due to the high dimensionality of the data and the differences in the dimension of data from different cellular layers. This thesis focuses on the investigation and development of computational approaches to analyze metabolite profiles in the context of cellular networks. This leads to determining what aspects of the network functionality are reflected in the metabolite levels. With these methods at hand, this thesis aims to answer three questions: (1) how observability of biological systems is manifested in metabolite profiles and if it can be used for phenotypical comparisons; (2) how to identify couplings of reaction rates from metabolic profiles alone; and (3) which regulatory mechanism that affect metabolite levels can be distinguished by integrating transcriptomics and metabolomics read-outs. I showed that sensor metabolites, identified by an approach from observability theory, are more correlated to each other than non-sensors. The greater correlations between sensor metabolites were detected both with publicly available metabolite profiles and synthetic data simulated from a medium-scale kinetic model. I demonstrated through robustness analysis that correlation was due to the position of the sensor metabolites in the network and persisted irrespectively of the experimental conditions. Sensor metabolites are therefore potential candidates for phenotypical comparisons between conditions through targeted metabolic analysis. Furthermore, I demonstrated that the coupling of metabolic reaction rates can be investigated from a purely data-driven perspective, assuming that metabolic reactions can be described by mass action kinetics. Employing metabolite profiles from domesticated and wild wheat and tomato species, I showed that the process of domestication is associated with a loss of regulatory control on the level of reaction rate coupling. I also found that the same metabolic pathways in Arabidopsis thaliana and Escherichia coli exhibit differences in the number of reaction rate couplings. I designed a novel method for the identification and categorization of transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approach determines the partial correlation of metabolites with control by the principal components of the transcript levels. The principle components contain the majority of the transcriptomic information allowing to partial out the effect of the transcriptional layer from the metabolite profiles. Depending whether the correlation between metabolites persists upon controlling for the effect of the transcriptional layer, the approach allows us to group metabolite pairs into being associated due to post-transcriptional or transcriptional regulation, respectively. I showed that the classification of metabolite pairs into those that are associated due to transcriptional or post-transcriptional regulation are in agreement with existing literature and findings from a Bayesian inference approach. The approaches developed, implemented, and investigated in this thesis open novel ways to jointly study metabolomics and transcriptomics data as well as to place metabolic profiles in the network context. The results from these approaches have the potential to provide further insights into the regulatory machinery in a biological system. N2 - Die System Biologie ist auf die Auswertung biologischer Systeme in ihrer Gesamtheit gerichtet. Dies geschieht durch das Sammeln und analysieren von großen Datensätzen der zugrundeliegenden Komponenten der Systeme. Computergestützte systembiologische Ansätze verwenden diese großen Datensätze, um Modelle zu erstellen und Hypothesen über biologische Prozesse auf verschiedenen zellularen Ebenen zu testen. Diese Ansätze führen jedoch unweigerlich zu rechnerischen Herausforderungen, da die Daten über eine hohe Dimensionalität verfügen. Des Weiteren weisen Daten, die von verschiedenen zellulären Ebenen gewonnen werden, unterschiedliche Dimensionen auf. Diese Doktorarbeit beschäftigt sich mit der Untersuchung und Entwicklung von rechnergestützten Ansätzen, um Metabolit-Profile im Zusammenhang von zellulären Netzwerken zu analysieren und um zu bestimmen, welche Aspekte der Netzwerkfunktionalität sich in den Metabolit-Messungen widerspiegeln. Die Zielsetzung dieser Arbeit ist es, die folgenden Fragen, unter Berücksichtigung der genannten Methoden, zu beantworten: (1) Wie ist die Beobachtbarkeit von biologischen Systemen in Metabolit-Profilen manifestiert und sind diese für phänotypische Vergleiche verwendbar? (2) Wie lässt sich die Kopplung von Reaktionsraten ausschließlich durch Metabolit-Profile identifizieren? (3) Welche regulatorischen Mechanismen, die Metabolit-Niveaus beeinflussen, sind unterscheidbar, wenn transkriptomische und metabolische Daten kombiniert werden? Ich konnte darlegen, dass Sensormetabolite, die durch eine Methode „observability theory“ identifiziert wurden, stärker korrelieren als Nicht-Sensoren. Die stärkere Korrelation zwischen Sensormetaboliten konnte mit öffentlich zugänglichen Daten, als auch mit synthetischen Daten aus einer Simulation mit einem mittelgroßen kinetischen Modell gezeigt werden. Durch eine Robustheitsanalyse war es mir möglich zu demonstrieren, dass die Korrelation auf die Position der Sensormetabolite im Netzwerk zurückzuführen und unabhängig von den experimentellen Bedingungen ist. Sensormetabolite sind daher geeignete Kandidaten für phänotypische Vergleiche zwischen verschiedenen Bedingungen durch gezielte metabolische Analysen. Des Weiteren ergaben meine Untersuchungen, dass die Auswertung der Kopplung von Stoffwechselreaktionsraten von einer ausschließlich datengestützten Perspektive möglich ist. Dabei muss die Annahme getroffen werden, dass Stoffwechselreaktionen mit dem Massenwirkungsgesetz beschreibbar sind. Ich konnte zeigen, dass der Züchtungsprozess mit einem Verlust der regulatorischen Kontrolle auf der Ebene der gekoppelten Reaktionsraten einhergeht. Dazu verwendete ich Metabolit-Profile von gezüchteten, als auch wilden Weizen- und Tomatenspezies. Meine Ergebnisse belegen, dass die selben Stoffwechselwege in Arabidopsis thaliana und Escherichia coli eine unterschiedliche Anzahl an gekoppelten Reaktionsraten aufweisen. Darüber hinaus habe ich eine neue Methode zur Identifizierung und Kategorisierung von transkriptionellen Effekten auf den Metabolismus entwickelt. Dies erfolgt durch die Kombination von Genexpressionsdaten und Messungen von Metaboliten. Die Methode ermittelt die partielle Korrelation zwischen Metaboliten, wobei die Hauptkomponenten der Transkriptdaten als Kontrollvariablen dienen. Dadurch kann der Einfluss der Transkription auf Metabolit-Profile herausgerechnet werden. Dieser Ansatz ermöglicht die Einteilung von Metabolitpaaren in assoziiert durch transkriptionelle oder assoziiert durch posttranskriptionelle Regulation. Die Einteilung ist abhängig davon, ob die Korrelation zwischen Metaboliten bestehen bleibt, wenn für den Einfluss der Transkription kontrolliert wird. Ich konnte nachweisen, dass die zuvor genannten Klassifizierungen von Metabolitpaaren mit existierender Literatur und den Ergebnissen einer auf bayessche Statistik basierenden Studie übereinstimmen. Die Methoden, die in dieser Doktorarbeit entwickelt, implementiert und untersucht wurden, öffnen neue Wege um metabolische und transkriptomische Daten gemeinsam auszuwerten. Sie erlauben Metabolit-Profile in den Kontext von metabolischen Netzwerken zu stellen. Die Ergebnisse haben das Potential uns weitere Einblicke in die regulatorische Maschinerie in biologischen Systemen zu gewähren. KW - systems biology KW - metabolomics KW - metabolites KW - Systembiologie KW - Metabolomik KW - Metabolite Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-423240 ER - TY - THES A1 - Schlossarek, Dennis T1 - Identification of dynamic protein-metabolite complexes in saccharomyces cerevisiae using co-fractionation mass spectrometry T1 - Identifikation von dynamischen Protein-Metabolit Komplexes in Saccharomyces cerevisiae unter Nutzung der Co-Fraktionierungs Massenspektrometrie N2 - 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. N2 - Die Zelle besteht aus einer Vielzahl von großen und kleinen Molekülen, und sowohl das Proteom als auch das Metabolom passen sich dynamisch den vorherrschenden Umweltbedingungen oder zellulären Anforderungen an. Allerdings ist es nicht die bloße Menge an biologischen Molekülen, sondern deren Interaktionen miteinander, die das Leben erst ermöglichen. Protein-Protein (PPI) und Protein-Metabolit Interaktionen (PMI) vollbringen und regulieren alle Aspekte der Zelle, vom Stoffwechsel bis zur Mitose. Die Studie dieser Interaktionen ist daher von fundamentalem wissenschaftlichem Interesse. In dieser Dissertation strebe ich an, eine Karte der Protein-Protein und Protein-Metabolit Interaktionen zu zeichnen, die den Übergang vom fermentativen zum respiratioschen Stoffwechsel in der Hefe Saccharomyces cerevisiae umfasst. Zu diesem Zweck nutze ich PROMIS (egl. protein metabolite interactions using size separation), eine auf der co-Fraktionierungs Massensprektrometrie (CF-MS) aufbauende Methode. PROMIS, und ähnliche Methoden zur Untersuchung von Protein-Interkationen, werden ausgiebig in Kapitel 1 vorgestellt. Da PROMIS ursprünglich für die Modellpflanze Arabadopsis thaliana entwickelt wurde, beschreibe ich in Kapitel 2 zunächst die erste Anwendung der Methode in S. cerevisiae. Die Ergebnisse stellen eine Fülle an Protein-Metabolit Interaktionen dar, und 225 zuvor prognostizierte Interaktionen wurden das erste Mal experimentell beschrieben. Mit Hilfe orthogonaler Methoden wurde außerdem eine inhibitorische Interaktion zwischen dem proteinogenen Dipeptid Ser-Leu und einem Enzym der Glykolyse gefunden. In Kapitel 3 präsentiere ich PROMISed, eine neue Web-Anwendung zur Auswertung von Daten von PROMIS oder anderen CF-MS Experimente. PROMISed kann genutzt werden um in rohen Fraktionierungs-Profile lokale Maxima zu finden, aus denen ein Interaktions-Netzwerk basierend auf Korrelationen erstellt wird. Außerdem kann die Anwendung Unterschiede in den Profilen zwischen verschiedenen experimentellen Bedingungen bewerten. PROMISed umfasst eine benutzerfreundliche grafische Oberfläche und bedarf daher keiner Programmierkenntnisse zur Nutzung. In Kapitel 4 benutze ich schließlich PROMIS und ItSA (engl. isothermal shift assay) um PPI und PMI während des Übergangs vom fermentativen zum respiratorischen Stoffwechsel in Hefe zu untersuchen. Hier beschreibe ich eine zellweite Umbildung der Protein-Metabolit-Komplexe, bespielhaft beschrieben anhand des Auseinanderfallens des Proteasoms im respiratorischen Stoffwechsel, des Verlustes der Interaktion zwischen einem Enzym des Aminosäure Stoffwechsels mit seinem Cofaktor und spezifischen Interaktionen zwischen Dipeptiden und Enzymen des zentralen Stoffwechsels. In Kapitel 5 fasse ich die gefundenen Ergebnisse zusammen und stelle eine Strategie zur Untersuchung der Spezifität sowohl der Bildung als auch der Protein-Interaktionen von Dipeptiden vor. Zu aller letzt rekapituliere ich Richtlinien für CF-MS Experimente und gebe einen Ausblick auf die nahe Zukunft der Studien der Protein-Interkationen. KW - Protein KW - Metabolit KW - Interaktion KW - Interaktions Netzwerk KW - Stoffwechsel KW - Saccharomyces cerevisiae KW - protein KW - metabolite KW - interaction KW - interaction network KW - metabolism KW - saccharomyces cerevisiae KW - interactomics KW - proteomics KW - metabolomics Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-582826 ER - TY - THES A1 - Schaarschmidt, Stephanie T1 - Evaluation and application of omics approaches to characterize molecular responses to abiotic stresses in plants T1 - Evaluierung und Anwendung von Omics-Methoden zur Charakterisierung von abiotischem Stress in Pflanzen auf molekularer Ebene N2 - Aufgrund des globalen Klimawandels ist die Gewährleistung der Ernährungssicherheit für eine wachsende Weltbevölkerung eine große Herausforderung. Insbesondere abiotische Stressoren wirken sich negativ auf Ernteerträge aus. Um klimaangepasste Nutzpflanzen zu entwickeln, ist ein umfassendes Verständnis molekularer Veränderungen in der Reaktion auf unterschiedlich starke Umweltbelastungen erforderlich. Hochdurchsatz- oder "Omics"-Technologien können dazu beitragen, Schlüsselregulatoren und Wege abiotischer Stressreaktionen zu identifizieren. Zusätzlich zur Gewinnung von Omics-Daten müssen auch Programme und statistische Analysen entwickelt und evaluiert werden, um zuverlässige biologische Ergebnisse zu erhalten. Ich habe diese Problemstellung in drei verschiedenen Studien behandelt und dafür zwei Omics-Technologien benutzt. In der ersten Studie wurden Transkript-Daten von den beiden polymorphen Arabidopsis thaliana Akzessionen Col-0 und N14 verwendet, um sieben Programme hinsichtlich ihrer Fähigkeit zur Positionierung und Quantifizierung von Illumina RNA Sequenz-Fragmenten („Reads“) zu evaluieren. Zwischen 92% und 99% der Reads konnten an die Referenzsequenz positioniert werden und die ermittelten Verteilungen waren hoch korreliert für alle Programme. Bei der Durchführung einer differentiellen Genexpressionsanalyse zwischen Pflanzen, die bei 20 °C oder 4 °C (Kälteakklimatisierung) exponiert wurden, ergab sich eine große paarweise Überlappung zwischen den Programmen. In der zweiten Studie habe ich die Transkriptome von zehn verschiedenen Oryza sativa (Reis) Kultivaren sequenziert. Dafür wurde die PacBio Isoform Sequenzierungstechnologie benutzt. Die de novo Referenztranskriptome hatten zwischen 38.900 bis 54.500 hoch qualitative Isoformen pro Sorte. Die Isoformen wurden kollabiert, um die Sequenzredundanz zu verringern und danach evaluiert z.B. hinsichtlich des Vollständigkeitsgrades (BUSCO), der Transkriptlänge und der Anzahl einzigartiger Transkripte pro Genloci. Für die hitze- und trockenheitstolerante Sorte N22 wurden ca. 650 einzigartige und neue Transkripte identifiziert, von denen 56 signifikant unterschiedlich in sich entwickelnden Samen unter kombiniertem Trocken- und Hitzestress exprimiert wurden. In der letzten Studie habe ich die Veränderungen in Metabolitprofilen von acht Reissorten gemessen und analysiert, die dem Stress hoher Nachttemperaturen (HNT) ausgesetzt waren und während der Trocken- und Regenzeit im Feld auf den Philippinen angebaut wurden. Es wurden jahreszeitlich bedingte Veränderungen im Metabolitspiegel sowie für agronomische Parameter identifiziert und mögliche Stoffwechselwege, die einen Ertragsrückgang unter HNT-Bedingungen verursachen, vorgeschlagen. Zusammenfassend konnte ich zeigen, dass der Vergleich der RNA-seq Programme den Pflanzenwissenschaftler*innen helfen kann, sich für das richtige Werkzeug für ihre Daten zu entscheiden. Die de novo Transkriptom-Rekonstruktion von Reissorten ohne Genomsequenz bietet einen gezielten, kosteneffizienten Ansatz zur Identifizierung neuer Gene, die durch verschiedene Stressbedingungen reguliert werden unabhängig vom Organismus. Mit dem Metabolomik-Ansatz für HNT-Stress in Reis habe ich stress- und jahreszeitenspezifische Metabolite identifiziert, die in Zukunft als molekulare Marker für die Verbesserung von Nutzpflanzen verwendet werden könnten. N2 - Due to global climate change providing food security for an increasing world population is a big challenge. Especially abiotic stressors have a strong negative effect on crop yield. To develop climate-adapted crops a comprehensive understanding of molecular alterations in the response of varying levels of environmental stresses is required. High throughput or ‘omics’ technologies can help to identify key-regulators and pathways of abiotic stress responses. In addition to obtain omics data also tools and statistical analyses need to be designed and evaluated to get reliable biological results. To address these issues, I have conducted three different studies covering two omics technologies. In the first study, I used transcriptomic data from the two polymorphic Arabidopsis thaliana accessions, namely Col-0 and N14, to evaluate seven computational tools for their ability to map and quantify Illumina single-end reads. Between 92% and 99% of the reads were mapped against the reference sequence. The raw count distributions obtained from the different tools were highly correlated. Performing a differential gene expression analysis between plants exposed to 20 °C or 4°C (cold acclimation), a large pairwise overlap between the mappers was obtained. In the second study, I obtained transcript data from ten different Oryza sativa (rice) cultivars by PacBio Isoform sequencing that can capture full-length transcripts. De novo reference transcriptomes were reconstructed resulting in 38,900 to 54,500 high-quality isoforms per cultivar. Isoforms were collapsed to reduce sequence redundancy and evaluated, e.g. for protein completeness level (BUSCO), transcript length, and number of unique transcripts per gene loci. For the heat and drought tolerant aus cultivar N22, I identified around 650 unique and novel transcripts of which 56 were significantly differentially expressed in developing seeds during combined drought and heat stress. In the last study, I measured and analyzed the changes in metabolite profiles of eight rice cultivars exposed to high night temperature (HNT) stress and grown during the dry and wet season on the field in the Philippines. Season-specific changes in metabolite levels, as well as for agronomic parameters, were identified and metabolic pathways causing a yield decline at HNT conditions suggested. In conclusion, the comparison of mapper performances can help plant scientists to decide on the right tool for their data. The de novo reconstruction of rice cultivars without a genome sequence provides a targeted, cost-efficient approach to identify novel genes responding to stress conditions for any organism. With the metabolomics approach for HNT stress in rice, I identified stress and season-specific metabolites which might be used as molecular markers for crop improvement in the future. KW - Arabidopsis thaliana KW - Oryza sativa KW - RNA-seq KW - PacBio IsoSeq KW - metabolomics KW - high night temperature KW - combined heat and drought stress KW - natural genetic variation KW - differential gene expression KW - Arabidopsis thaliana KW - Oryza sativa KW - PacBio IsoSeq KW - RNA-seq KW - kombinierter Hitze- und Trockenstress KW - erhöhte Nachttemperaturen KW - Differenzielle Genexpression KW - Metabolomik KW - natürliche genetische Variation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-509630 ER - TY - JOUR A1 - Rohrmann, Johannes A1 - Tohge, Takayuki A1 - Alba, Rob A1 - Osorio, Sonia A1 - Caldana, Camila A1 - McQuinn, Ryan A1 - Arvidsson, Samuel Janne A1 - van der Merwe, Margaretha J. A1 - Riano-Pachon, Diego Mauricio A1 - Müller-Röber, Bernd A1 - Fei, Zhangjun A1 - Nesi, Adriano Nunes A1 - Giovannoni, James J. A1 - Fernie, Alisdair R. T1 - Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development JF - The plant journal N2 - Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes. KW - transcription factor KW - Solanum lycopersicum KW - quantitative RT-PCR KW - microarray KW - metabolomics KW - fleshy fruit ripening Y1 - 2011 U6 - https://doi.org/10.1111/j.1365-313X.2011.04750.x SN - 0960-7412 VL - 68 IS - 6 SP - 999 EP - 1013 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Omolaoye, Temidayo S. A1 - Omolaoye, Victor Adelakun A1 - Kandasamy, Richard K. A1 - Hachim, Mahmood Yaseen A1 - Du Plessis, Stefan S. T1 - Omics and male infertility BT - highlighting the application of transcriptomic data JF - Life : open access journal N2 - Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases. KW - male infertility KW - omics KW - genomics KW - transcriptomics KW - proteomics KW - metabolomics Y1 - 2022 U6 - https://doi.org/10.3390/life12020280 SN - 2075-1729 VL - 12 IS - 2 PB - MDPI CY - Basel ER - TY - GEN A1 - Lu, Yong-Ping A1 - Reichetzeder, Christoph A1 - Prehn, Cornelia A1 - Yin, Liang-Hong A1 - Yun, Chen A1 - Zeng, Shufei A1 - Chu, Chang A1 - Adamski, Jerzy A1 - Hocher, Berthold T1 - Cord blood Lysophosphatidylcholine 16:1 is positively associated with birth weight T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background/Aims: Impaired birth outcomes, like low birth weight, have consistently been associated with increased disease susceptibility to hypertension in later life. Alterations in the maternal or fetal metabolism might impact on fetal growth and influence birth outcomes. Discerning associations between the maternal and fetal metabolome and surrogate parameters of fetal growth could give new insight into the complex relationship between intrauterine conditions, birth outcomes, and later life disease susceptibility. Methods: Using flow injection tandem mass spectrometry, targeted metabolomics was performed in serum samples obtained from 226 mother/child pairs at delivery. Associations between neonatal birth weight and concentrations of 163 maternal and fetal metabolites were analyzed. Results: After FDR adjustment using the Benjamini-Hochberg procedure lysophosphatidylcholines (LPC) 14:0, 16:1, and 18:1 were strongly positively correlated with birth weight. In a stepwise linear regression model corrected for established confounding factors of birth weight, LPC 16: 1 showed the strongest independent association with birth weight (CI: 93.63 - 168.94; P = 6.94x10(-11)). The association with birth weight was stronger than classical confounding factors such as offspring sex (CI: - 258.81- -61.32; P = 0.002) and maternal smoking during pregnancy (CI: -298.74 - -29.51; P = 0.017). Conclusions: After correction for multiple testing and adjustment for potential confounders, LPC 16:1 showed a very strong and independent association with birth weight. The underlying molecular mechanisms linking fetal LPCs with birth weight need to be addressed in future studies. (c) 2018 The Author(s) Published by S. Karger AG, Basel T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 631 KW - metabolomics KW - Lysophosphatidylcholine KW - birth weight KW - DOHaD KW - hypertension KW - Type 2 Diabetes Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-424566 SN - 1866-8372 IS - 631 ER - TY - GEN A1 - Lu, Yong-Ping A1 - Reichetzeder, Christoph A1 - Prehn, Cornelia A1 - von Websky, Karoline A1 - Slowinski, Torsten A1 - Chen, You-Peng A1 - Yin, Liang-Hong A1 - Kleuser, Burkhard A1 - Yang, Xue-Song A1 - Adamski, Jerzy A1 - Hocher, Berthold T1 - Fetal serum metabolites are independently associated with Gestational diabetes mellitus T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background/Aims: Gestational diabetes (GDM) might be associated with alterations in the metabolomic profile of affected mothers and their offspring. Until now, there is a paucity of studies that investigated both, the maternal and the fetal serum metabolome in the setting of GDM. Mounting evidence suggests that the fetus is not just passively affected by gestational disease but might play an active role in it. Metabolomic studies performed in maternal blood and fetal cord blood could help to better discern distinct fetal from maternal disease interactions. Methods: At the time of birth, serum samples from mothers and newborns (cord blood samples) were collected and screened for 163 metabolites utilizing tandem mass spectrometry. The cohort consisted of 412 mother/child pairs, including 31 cases of maternal GDM. Results: An initial non-adjusted analysis showed that eight metabolites in the maternal blood and 54 metabolites in the cord blood were associated with GDM. After Benjamini-Hochberg (BH) procedure and adjustment for confounding factors for GDM, fetal phosphatidylcholine acyl-alkyl C 32:1 and proline still showed an independent association with GDM. Conclusions: This study found metabolites in cord blood which were associated with GDM, even after adjustment for established risk factors of GDM. To the best of our knowledge, this is the first study demonstrating an independent association between fetal serum metabolites and maternal GDM. Our findings might suggest a potential effect of the fetal metabolome on maternal GDM. (c) 2018 The Author(s) Published by S. Karger AG, Basel T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 637 KW - Gestational diabetes KW - metabolomics KW - phosphatidylcholine acyl-alkyl C 32:1 KW - proline Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-424585 SN - 1866-8372 IS - 637 ER - TY - THES A1 - Lopes Fernando, Raquel Sofia T1 - The impact of aging on proteolytic systems, transcriptome and metabolome of slow and fast muscle fiber types N2 - Aging is a complex process characterized by several factors, including loss of genetic and epigenetic information, accumulation of chronic oxidative stress, protein damage and aggregates and it is becoming an emergent drug target. Therefore, it is the utmost importance to study aging and agerelated diseases, to provide treatments to develop a healthy aging process. Skeletal muscle is one of the earliest tissues affected by age-related changes with progressive loss of muscle mass and function from 30 years old, effect known as sarcopenia. Several studies have shown the accumulation of protein aggregates in different animal models, as well as in humans, suggesting impaired proteostasis, a hallmark of aging, especially regarding degradation systems. Thus, different publications have explored the role of the main proteolytic systems in skeletal muscle from rodents and humans, like ubiquitin proteasomal system (UPS) and autophagy lysosomal system (ALS), however with contradictory results. Yet, most of the published studies are performed in muscles that comprise more than one fiber type, that means, muscles composed by slow and fast fibers. These fiber types, exhibit different metabolism and contraction speed; the slow fibers or type I display an oxidative metabolism, while fast fibers function towards a glycolytic metabolism ranging from fast oxidative to fast glycolytic fibers. To this extent, the aim of this thesis sought to understand on how aging impacts both fiber types not only regarding proteostasis but also at a metabolome and transcriptome network levels. Therefore, the first part of this thesis, presents the differences between slow oxidative (from Soleus muscle) and fast glycolytic fibers (Extensor digitorum longus, EDL) in terms of degradation systems and how they cope with oxidative stress during aging, while the second part explores the differences between young and old EDL muscle transcriptome and metabolome, unraveling molecular features. More specifically, the results from the present work show that slow oxidative muscle performs better at maintaining the function of UPS and ALS during aging than EDL muscle, which is clearly affected, accounting for the decline in the catalytic activity rates and accumulation of autophagy-related proteins. Strinkingly, transcriptome and metabolome analyses reveal that fast glycolytic muscle evidences significant downregulation of mitochondrial related processes and damaged mitochondria morphology during aging, despite of having a lower oxidative metabolism compared to oxidative fibers. Moreover, predictive analyses reveal a negative association between aged EDL gene signature and lifespan extending interventions such as caloric restriction (CR). Although, CR intervention does not alter the levels of mitochondrial markers in aged EDL muscle, it can reverse the higher mRNA levels of muscle damage markers. Together, the results from this thesis give new insights about how different metabolic muscle fibers cope with age-related changes and why fast glycolytic fibers are more susceptible to aging than slow oxidative fibers. N2 - Altern ist ein komplexer Prozess, der durch mehrere Faktoren gekennzeichnet ist, darunter der Verlust genetischer und epigenetischer Informationen, oxidativer Stress, sowie die Anhäufung von Proteinschäden und Aggregaten. Daher ist es von größter Bedeutung, das Altern und altersbedingte Krankheiten zu erforschen, um Arzneimittel und andere Behandlungen für einen gesunden Alterungsprozess zu entwickeln. Die Skelettmuskulatur ist eines der ersten Gewebe, das von altersbedingten Veränderungen betroffen ist. Ab einem Alter von 30 Jahren kommt es zu einem fortschreitenden Verlust der Muskelmasse und -funktion, der auch als Sarkopenie bezeichnet wird. Mehrere Studien haben die Anhäufung von Proteinaggregaten beim Altern in verschiedenen Tiermodellen und auch beim Menschen gezeigt, was auf eine gestörte Proteostase, insbesondere hinsichtlich der Abbauprozesse schließen lässt. Demnach wurde weiterführend die Rolle der wichtigsten proteolytischen Systeme, das Ubiquitin Proteasom System (UPS) und AutophagieLysosomale System (ALS), im alternden Skelettmuskel von Nagetieren und Menschen untersucht. Die Ergebnisse waren widersprüchlich, jedoch wurden die meisten der veröffentlichten Studien an Muskeln durchgeführt, die aus mehr als einem Muskelfasertyp bestehen, d.h. Muskeln, die aus langsamen und schnellen Muskelfasern zusammengesetzt sind. Diese Muskelfasertypen unterscheiden sich hinsichtlich des Stoffwechsels und der Kontraktionsgeschwindigkeit. Die langsamen Fasern oder der Typ I haben einen oxidativen Stoffwechsel, während die schnellen Fasern einen glykolytischen Stoffwechsel aufweisen und aus schnellen oxidativen bis zu schnellen glykolytischen Fasern bestehen können. Insofern war es das Ziel dieser Arbeit zu verstehen, wie sich das Altern auf beide Fasertypen auswirkt, und zwar nicht nur im Hinblick auf die Proteostase, sondern auch auf das Metabolom und Transkriptom. Im ersten Teil dieser Arbeit werden die Unterschiede zwischen langsamen oxidativen (Soleus-Muskel) und schnellen glykolytischen Fasern (Extensor digitorum longus-Muskel; EDL) in Bezug auf die Proteinabbausysteme und die Art und Weise, wie sie mit oxidativem Stress während des Alterns umgehen, dargestellt. Im zweiten Teil werden die Unterschiede zwischen dem Transkriptom und dem Metabolom des jungen und alten EDL-Muskels untersucht, um die molekularen Merkmale zu entschlüsseln. Im Einzelnen zeigen die Ergebnisse der vorliegenden Arbeit, dass der langsam oxidierende Muskel im Vergleich zum EDL-Muskel besser in der Lage ist, die Funktion von UPS und ALS während des Alterns aufrechtzuerhalten. Die Funktionalität des UPS und ALS ist im alternden EDL-Muskels vermindert, was durch den Rückgang der katalytischen Aktivitätsraten und die Anhäufung von mit Autophagie-assoziierten Proteinen gezeigt wurde. Transkriptom- und Metabolomanalysen zeigen, dass schnelle glykolytische Muskeln eine signifikante Herabregulierung mitochondrialer Prozesse und eine geschädigte Mitochondrienmorphologie während des Alterns aufweisen, obwohl sie im Vergleich zu oxidativen Fasern durch einen geringeren oxidativen Stoffwechsel charakterisiert sind. Darüber hinaus ergeben prädiktive Analysen einen negativen Zusammenhang zwischen der Gensignatur des gealterten EDL-Muskels und lebensverlängernden Maßnahmen wie der kalorischenRestriktion. Obwohl die kalorischen Restriktion Intervention die Werte der mitochondrialen Marker im gealterten EDL-Muskel nicht verändert, kann sie die höheren mRNA-Werte der Muskelschädigungsmarker umkehren. Zusammenfassend liefern die Ergebnisse dieser Arbeit neue Erkenntnisse darüber, wie verschiedene metabolische Muskelfasern mit altersbedingten. Veränderungen umgehen und warum schnelle glykolytische Fasern anfälliger für die Alterung als langsame oxidative Fasern sind. KW - skeletal muscle aging KW - proteostasis KW - slow and fast fiber types KW - transcriptomics KW - metabolomics KW - sarcopenia KW - Skelettmuskelalterung KW - Proteostase KW - langsame und schnelle Fasertypen KW - Transkriptom KW - Metabolom KW - ubiquitin proteasomal system KW - autophagy lysosomal system KW - Ubiquitin Proteasom System KW - Autophagie Lysosomale System Y1 - 2023 U6 - https://doi.org/10.25932/publishup-60579 ER - TY - JOUR A1 - Lisec, Jan A1 - Römisch-Margl, Lilla A1 - Nikoloski, Zoran A1 - Piepho, Hans-Peter A1 - Giavalisco, Patrick A1 - Selbig, Joachim A1 - Gierl, Alfons A1 - Willmitzer, Lothar T1 - Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns JF - The plant journal N2 - We conducted a comparative analysis of the root metabolome of six parental maize inbred lines and their 14 corresponding hybrids showing fresh weight heterosis. We demonstrated that the metabolic profiles not only exhibit distinct features for each hybrid line compared with its parental lines, but also separate reciprocal hybrids. Reconstructed metabolic networks, based on robust correlations between metabolic profiles, display a higher network density in most hybrids as compared with the corresponding inbred lines. With respect to metabolite level inheritance, additive, dominant and overdominant patterns are observed with no specific overrepresentation. Despite the observed complexity of the inheritance pattern, for the majority of metabolites the variance observed in all 14 hybrids is lower compared with inbred lines. Deviations of metabolite levels from the average levels of the hybrids correlate negatively with biomass, which could be applied for developing predictors of hybrid performance based on characteristics of metabolite patterns. KW - heterosis KW - Zea mays KW - metabolomics Y1 - 2011 U6 - https://doi.org/10.1111/j.1365-313X.2011.04689.x SN - 0960-7412 VL - 68 IS - 2 SP - 326 EP - 336 PB - Wiley-Blackwell CY - Malden ER - TY - GEN A1 - Kühn, Tilman A1 - Floegel, Anna A1 - Sookthai, Disorn A1 - Johnson, Theron A1 - Rolle-Kampczyk, Ulrike A1 - Otto, Wolfgang A1 - von Bergen, Martin A1 - Boeing, Heiner A1 - Kaaks, Rudolf T1 - Higher plasma levels of lysophosphatidylcholine 18:0 are related to a lower risk of common cancers in a prospective metabolomics study T2 - BMC medicine N2 - Background: First metabolomics studies have indicated that metabolic fingerprints from accessible tissues might be useful to better understand the etiological links between metabolism and cancer. However, there is still a lack of prospective metabolomics studies on pre-diagnostic metabolic alterations and cancer risk. Methods: Associations between pre-diagnostic levels of 120 circulating metabolites (acylcarnitines, amino acids, biogenic amines, phosphatidylcholines, sphingolipids, and hexoses) and the risks of breast, prostate, and colorectal cancer were evaluated by Cox regression analyses using data of a prospective case-cohort study including 835 incident cancer cases. Results: The median follow-up duration was 8.3 years among non-cases and 6.5 years among incident cases of cancer. Higher levels of lysophosphatidylcholines (lysoPCs), and especially lysoPC a C18:0, were consistently related to lower risks of breast, prostate, and colorectal cancer, independent of background factors. In contrast, higher levels of phosphatidylcholine PC ae C30:0 were associated with increased cancer risk. There was no heterogeneity in the observed associations by lag time between blood draw and cancer diagnosis. Conclusion: Changes in blood lipid composition precede the diagnosis of common malignancies by several years. Considering the consistency of the present results across three cancer types the observed alterations point to a global metabolic shift in phosphatidylcholine metabolism that may drive tumorigenesis. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 437 KW - metabolomics KW - epidemiology KW - breast cancer KW - prostate cancer KW - colorectal cancer Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-407258 ER - TY - JOUR A1 - Jüppner, Jessica A1 - Mubeen, Umarah A1 - Leisse, Andrea A1 - Caldana, Camila A1 - Brust, Henrike A1 - Steup, Martin A1 - Herrmann, Marion A1 - Steinhauser, Dirk A1 - Giavalisco, Patrick T1 - Dynamics of lipids and metabolites during the cell cycle of Chlamydomonas reinhardtii JF - The plant journal N2 - Metabolites and lipids are the final products of enzymatic processes, distinguishing the different cellular functions and activities of single cells or whole tissues. Understanding these cellular functions within a well-established model system requires a systemic collection of molecular and physiological information. In the current report, the green alga Chlamydomonas reinhardtii was selected to establish a comprehensive workflow for the detailed multi-omics analysis of a synchronously growing cell culture system. After implementation and benchmarking of the synchronous cell culture, a two-phase extraction method was adopted for the analysis of proteins, lipids, metabolites and starch from a single sample aliquot of as little as 10-15million Chlamydomonas cells. In a proof of concept study, primary metabolites and lipids were sampled throughout the diurnal cell cycle. The results of these time-resolved measurements showed that single compounds were not only coordinated with each other in different pathways, but that these complex metabolic signatures have the potential to be used as biomarkers of various cellular processes. Taken together, the developed workflow, including the synchronized growth of the photoautotrophic cell culture, in combination with comprehensive extraction methods and detailed metabolic phenotyping has the potential for use in in-depth analysis of complex cellular processes, providing essential information for the understanding of complex biological systems. KW - Chlamydomonas reinhardtii KW - synchronized cell cultures KW - photoautotrophic growth KW - cell cycle KW - metabolomics KW - lipidomics KW - systems biology KW - two-phase extraction KW - diurnal cycle KW - technical advance Y1 - 2017 U6 - https://doi.org/10.1111/tpj.13642 SN - 0960-7412 SN - 1365-313X VL - 92 SP - 331 EP - 343 PB - Wiley CY - Hoboken ER - TY - GEN A1 - Hische, Manuela A1 - Larhlimi, Abdelhalim A1 - Schwarz, Franziska A1 - Fischer-Rosinský, Antje A1 - Bobbert, Thomas A1 - Assmann, Anke A1 - Catchpole, Gareth S. A1 - Pfeiffer, Andreas F. H. A1 - Willmitzer, Lothar A1 - Selbig, Joachim A1 - Spranger, Joachim T1 - A distinct metabolic signature predictsdevelopment of fasting plasma glucose T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Background High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. Methods We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. Results We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. Conclusions We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 850 KW - prediction KW - fasting glucose KW - type 2 diabetes KW - metabolomics KW - plasma KW - random forest KW - metabolite KW - regression KW - biomarker Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427400 SN - 1866-8372 IS - 850 ER - TY - JOUR A1 - Catchpole, Gareth A1 - Platzer, Alexander A1 - Weikert, Cornelia A1 - Kempkensteffen, Carsten A1 - Johannsen, Manfred A1 - Krause, Hans A1 - Jung, Klaus A1 - Miller, Kurt A1 - Willmitzer, Lothar A1 - Selbig, Joachim A1 - Weikert, Steffen T1 - Metabolic profiling reveals key metabolic features of renal cell carcinoma JF - Journal of cellular and molecular medicine : a journal of translational medicine N2 - Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. alpha-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC. KW - kidney cancer KW - metabolism KW - metabolomics KW - metastasis Y1 - 2011 U6 - https://doi.org/10.1111/j.1582-4934.2009.00939.x SN - 1582-1838 VL - 15 IS - 1 SP - 109 EP - 118 PB - Wiley-Blackwell CY - Malden ER - TY - THES A1 - Bölling, Christian T1 - Comprehensive metabolite analysis in Chlamydomonas reinhardtii : method development and application to the study of environmental and genetic perturbations T1 - Multiparallele Metabolitenanalyse in Chlamydomonas reinhardtii N2 - 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. N2 - Entwicklung und Anwendung von Methoden zur multiparallelen Analyse von Metaboliten in der einzelligen Grünalge Chlamydomonas reinhardtii, einem der wichtigsten Modellorganismen der Zellbiologie, sind Gegenstand dieser Arbeit. Metabolomanalyse, die umfassende Analyse von Veränderungen der Konzentrationen von Stoffwechselprodukten durch Umweltreize oder genetische und entwicklungsbedingte Signale, ist ein wichtiges Komplement anderer Genomanalysemethoden, um die Integration von Genen, Proteinen und Metaboliten in ein nahtloses und dynamisches Netzwerk zur Aufrechterhaltung der Lebensfunktionen eines Organismus zu verstehen. Die Methode wurde im Hinblick auf schnelle Inaktivierung enzymatischer Aktivität, Maximierung der Extraktionskapazität und Behandlung großer Probenmengen optimiert. Im Ergebnis der Probenaufarbeitung, Extraktion und Analyse mittels Gaschromatographie und Time-Of-Flight-Massenspektrometrie konnten mehr als 800 analytische Signale in Einzelproben dargestellt werden, von denen über 100 identifiziert werden konnten. Die Arbeit stellt methodische Innovationen zur systematischen Erkennung von Artefakten in GC-MS Chromatogrammen und Werkzeuge zur Anwendung der Hauptkomponentenanalyse auf Metabolom-Daten vor. Zellen unter Stickstoff- (N), Phosphor- (P), Schwefel- (S), oder Eisen- (Fe) Mangel zeigen deutliche Unterschiede in ihrer Metabolitenausstattung. Die Anpassung an die einzelnen Nährstoffmangelsituationen ist durch spezifische Änderungen einer Reihe von Metaboliten zentraler Prozesse des Primärstoffwechsels gekennzeichnet. Die Konzentrationsänderungen von Substraten für die Stickstoffassimilation und den oxidativen Pentosephosphatweg deuten darauf hin, dass die Fähigkeit zur schnellen Aktivierung der N-Assimilation auch unter Bedingungen herabgesetzter Stoffwechsel- und Wachstumsaktivität aufrechterhalten wird. Die Akkumulation von 4-Hydroxyprolin unter Schwefelmangel könnte im Zusammenhang stehen mit der Degradation von Proteinen der Chlamydomonas-Zellwand, deren wesentlicher Bestandteil hydroxyprolinreiche Glykoproteine sind und die unter Schwefelmangel aktiv umgebaut wird. Die Anpassung an Schwefelmangel wurde mit größerer zeitlicher Auflösung in Wildtyp-Zellen und Zellen des sac1-Stammes untersucht. SAC1 ist ein zentraler Regulator der Schwefelmangelantwort in Chlamydomonas. Zeitgleiche Ab- und Zunahme von Metaboliten ist ein charakteristisches Element der Anpassung an Schwefelmangel in Wildtypzellen. Die Reaktion von SAC1-Mutanten auf Schwefelmangel ist durch weit reichenden Verlust zur Steuerung von Prozessen gekennzeichnet, die normalerweise zur vorübergehenden oder dauerhaften Anreicherung bestimmter Metabolite führen. Die Verfügbarkeit von Chlamydomonas-Stämmen mit fehlender Enzymaktivität für fast jeden der Schritte der Argininbiosynthese eröffnet die Möglichkeit, das Potential der Metabolitenanalyse zur Untersuchung der Regulation der Aminosäurebiosynthese in photosynthetischen Eukaryoten zur Anwendung zu bringen. Drei Stämme, mit fehlender Aktivität für N-Acetylglutamat-5-phosphat Reduktase (arg1), N2 Acetylornithin-Aminotransferase (arg9) beziehungsweise Argininosuccinat Lyase (arg2) wurden in Bezug auf die Aktivierung ihrer endogenen Argininbiosynthese nach Entzug externer Argininquellen analysiert. Die einzelnen enzymatischen Blocks konnten durch Precursor-Anreicherung, wie die Anhäufung von Argininosuccinat in arg2-Zellen, und Erschöpfung von Intermediaten nachgelagerter Reaktionen, beispielsweise die deutliche Abnahme von N2-Acetylornithin, Ornithin und Argininosuccinat in arg9-Zellen charakterisiert werden. Das unerwartete Vorhandensein von zum Teil das Wildtyp-Niveau überschreitender Mengen von N2-Acetylornithin, Citrullin und Argininosuccinat, die Produkte bzw. Substrate dem enzymatischen Block nachgelagerter Reaktionen in arg1-Zellen sind, bot eine Erklärung für eine noch vorhandene Restkapazität zum Wachstum des arg1-Stamms auch ohne äußere Arginingabe. Der Nachweis dieser Verbindungen sowie die ungewöhnliche Anreicherung von N-Acetylglutamat, der ersten Verbindung, die das Glutamat-Gerüst für die Ornithin- und Argininsynthese bindet, in arg1-Zellen könnte auf alternative Reaktionen, möglicherweise unter Beteiligung von Ornithin-Aminotransferase, zur Synthese von Ornithin hindeuten, die in Erscheinung treten, wenn die Synthesekette nach Acetylierung von Glutamat blockiert ist. KW - Chlamydomonas KW - Metabolite KW - Schwefel KW - Argininbiosynthese KW - Stoffwechsel KW - Chlamydomonas KW - metabolite profiling KW - metabolomics KW - sulfur KW - arginine biosynthesis Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-11329 ER - TY - THES A1 - Bulut, Mustafa T1 - Assessing the genetic architecture underlying systemic responses to variable environments in crops using multi-omics N2 - Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security. Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species. Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity. Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs. In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses. N2 - Der pflanzliche Stoffwechsel ist der wichtigste Mechanismus für die Umwandlung von assimiliertem Kohlenstoff in essenzielle Verbindungen, die für das Pflanzenwachstum und letztlich den Ernteertrag entscheidend sind. Dies macht ihn zu einem Schwerpunkt der Forschung mit erheblichen Auswirkungen. Trotz bemerkenswerter Fortschritte beim Verständnis der genetischen Prinzipien, die dem Stoffwechsel und den Erträgen zugrunde liegen, gibt es nach wie vor einen Mangel an Wissen über die genetischen Faktoren, die für die Variation von Merkmalen unter verschiedenen Umweltbedingungen verantwortlich sind. In Anbetracht der wachsenden Weltbevölkerung und der zunehmenden Herausforderungen durch den Klimawandel wird es immer wichtiger, die Feinheiten des Stoffwechsels und des Ertrags auf Wasserknappheit zu entschlüsseln, um die Ernährungssicherheit zu gewährleisten. Unsere Forschungsgruppe hat vor kurzem damit begonnen, sich mit den genetischen Ressourcen von Leguminosen zu befassen. Zu diesem Zweck untersucht die hier vorgestellte Studie die Stoffwechselvielfalt bei fünf verschiedenen Leguminosen auf Gewebeebene und identifiziert die artspezifische Biosynthese von Alkaloiden sowie Iso-/Flavonoiden mit verschiedenen funktionellen Gruppen, nämlich Prenylierung, Phenylacylierung sowie Methoxylierung, um eine Ressource für Folgestudien zu schaffen, die die Stoffwechselvielfalt in verschiedenen natürlichen Populationen von Leguminosen untersuchen. Im Anschluss daran wird in der zweiten Studie die genetische Architektur trockenheitsbedingter Veränderungen in einer globalen Bohnenpopulation untersucht. Hier wird eine Vielzahl von quantitativen Merkmalsloci (QTL) identifiziert, die mit verschiedenen Merkmalen assoziiert sind, darunter auch für die Lipidsignalübertragung, unter Durchführung genomweite Assoziationsstudien (GWAS). Die Überexpression von Kandidaten auf dieser Seite hat die Induktion mehrerer Oxylipine hervorgehoben, die Berichten zufolge für die Bewältigung rauer Umweltbedingungen wie Wasserknappheit von zentraler Bedeutung sind. Abweichend von der Bohne und der GWAS konzentriert sich die folgende Studie auf die Identifizierung trockenheitsbezogener QTL bei der Tomate unter Verwendung einer bi-elterlichen Zuchtpopulation. Diese deskriptive Studie hebt neuartige multi-omische QTL hervor, einschließlich für Stoffwechsel, Photosynthese und Fruchtansatz, von denen einige eindeutig dem Dürre-Stress zugeordnet werden. Im Vergleich zu herkömmlichen Ansätzen, bei denen die bi-elterliche IL-Population verwendet wird, verbessert die vorgestellte Studie die Auflösung, indem weitere rückgekreuzte ILs, so genannte sub-ILs, untersucht werden. In der letzten Studie wird ein photosynthetisches Gen, nämlich eine PetM-Untereinheit des Cytochrom b6fKomplexes, das am Elektronenfluss beteiligt ist, in einer für den Gartenbau wichtigen Pflanze charakterisiert. Während bei Modellorganismen bereits zahlreiche wissenschaftliche Fortschritte erzielt wurden, beleuchtet diese Studie den Übergang dieses grundlegenden Wissens auf wichtige Gartenbaupflanzen wie die Tomate und untersucht ihre Funktion unter verschiedenen Lichtbedingungen. Insgesamt werden in der vorliegenden Arbeit verschiedene Strategien kombiniert, um die genetischen Komponenten multi-omischer Merkmale bei Trockenheit aufzudecken, wobei sowohl konventionelle Zuchtpopulationen als auch eine vielfältige globale Population verwendet werden. Zu diesem Zweck ermöglicht sie einen Vergleich beider Ansätze und zeigt ihre Stärken und Schwächen auf. KW - genomics KW - metabolomics KW - phenomics KW - genome-wide association studies (GWAS) KW - genotype-by-Environmental interaction (GxE) KW - plasticity Y1 - 2023 ER - TY - JOUR A1 - Balazadeh, Salma A1 - Schildhauer, Joerg A1 - Araujo, Wagner L. A1 - Munne-Bosch, Sergi A1 - Fernie, Alisdair R. A1 - Proost, Sebastian A1 - Humbeck, Klaus A1 - Müller-Röber, Bernd T1 - Reversal of senescence by N resupply to N-starved Arabidopsis thaliana: transcriptomic and metabolomic consequences JF - Journal of experimental botany N2 - Leaf senescence is a developmentally controlled process, which is additionally modulated by a number of adverse environmental conditions. Nitrogen shortage is a well-known trigger of precocious senescence in many plant species including crops, generally limiting biomass and seed yield. However, leaf senescence induced by nitrogen starvation may be reversed when nitrogen is resupplied at the onset of senescence. Here, the transcriptomic, hormonal, and global metabolic rearrangements occurring during nitrogen resupply-induced reversal of senescence in Arabidopsis thaliana were analysed. The changes induced by senescence were essentially in keeping with those previously described; however, these could, by and large, be reversed. The data thus indicate that plants undergoing senescence retain the capacity to sense and respond to the availability of nitrogen nutrition. The combined data are discussed in the context of the reversibility of the senescence programme and the evolutionary benefit afforded thereby. Future prospects for understanding and manipulating this process in both Arabidopsis and crop plants are postulated. KW - Arabidopsis KW - gene expression KW - metabolomics KW - nitrogen limitation KW - senescence KW - transcriptome Y1 - 2014 U6 - https://doi.org/10.1093/jxb/eru119 SN - 0022-0957 SN - 1460-2431 VL - 65 IS - 14 SP - 3975 EP - 3992 PB - Oxford Univ. Press CY - Oxford ER -