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 - JOUR A1 - Stoessel, Daniel A1 - Schulte, Claudia A1 - dos Santos, Marcia C. Teixeira A1 - Scheller, Dieter A1 - Rebollo-Mesa, Irene A1 - Deuschle, Christian A1 - Walther, Dirk A1 - Schauer, Nicolas A1 - Berg, Daniela A1 - da Costa, Andre Nogueira A1 - Maetzler, Walter T1 - Promising Metabolite Profiles in the Plasma and CSF of Early Clinical JF - Frontiers in Aging Neuroscience N2 - Parkinson's disease (PD) shows high heterogeneity with regard to the underlying molecular pathogenesis involving multiple pathways and mechanisms. Diagnosis is still challenging and rests entirely on clinical features. Thus, there is an urgent need for robust diagnostic biofluid markers. Untargeted metabolomics allows establishing low-molecular compound biomarkers in a wide range of complex diseases by the measurement of various molecular classes in biofluids such as blood plasma, serum, and cerebrospinal fluid (CSF). Here, we applied untargeted high-resolution mass spectrometry to determine plasma and CSF metabolite profiles. We semiquantitatively determined small-molecule levels (<= 1.5 kDa) in the plasma and CSF from early PD patients (disease duration 0-4 years; n = 80 and 40, respectively), and sex-and age-matched controls (n = 76 and 38, respectively). We performed statistical analyses utilizing partial least square and random forest analysis with a 70/30 training and testing split approach, leading to the identification of 20 promising plasma and 14 CSF metabolites. The semetabolites differentiated the test set with an AUC of 0.8 (plasma) and 0.9 (CSF). Characteristics of the metabolites indicate perturbations in the glycerophospholipid, sphingolipid, and amino acid metabolism in PD, which underscores the high power of metabolomic approaches. Further studies will enable to develop a potential metabolite-based biomarker panel specific for PD KW - biomarker KW - untargeted metabolomics KW - neurodegeneration KW - plasma KW - CSF KW - machinelearning Y1 - 2018 U6 - https://doi.org/10.3389/fnagi.2018.00051 SN - 1663-4365 VL - 10 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Stoessel, Daniel A1 - Stellmann, Jan-Patrick A1 - Willing, Anne A1 - Behrens, Birte A1 - Rosenkranz, Sina C. A1 - Hodecker, Sibylle C. A1 - Stuerner, Klarissa H. A1 - Reinhardt, Stefanie A1 - Fleischer, Sabine A1 - Deuschle, Christian A1 - Maetzler, Walter A1 - Berg, Daniela A1 - Heesen, Christoph A1 - Walther, Dirk A1 - Schauer, Nicolas A1 - Friese, Manuel A. A1 - Pless, Ole T1 - Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring JF - Frontiers in human neuroscienc N2 - Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies. KW - untargeted metabolomics KW - biomarker KW - PPMS KW - MS neurodegeneration KW - LysoPC(20:0) Y1 - 2018 U6 - https://doi.org/10.3389/fnhum.2018.00226 SN - 1662-5161 VL - 12 PB - Frontiers Research Foundation CY - Lausanne ER - TY - GEN A1 - Stoessel, Daniel A1 - Stellmann, Jan-Patrick A1 - Willing, Anne A1 - Behrens, Birte A1 - Rosenkranz, Sina C. A1 - Hodecker, Sibylle C. A1 - Stürner, Klarissa H. A1 - Reinhardt, Stefanie A1 - Fleischer, Sabine A1 - Deuschle, Christian A1 - Maetzler, Walter A1 - Berg, Daniela A1 - Heesen, Christoph A1 - Walther, Dirk A1 - Schauer, Nicolas A1 - Friese, Manuel A. A1 - Pless, Ole T1 - Metabolomic profiles for primary progressive multiple sclerosis stratification and disease course monitoring T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 694 KW - untargeted metabolomics KW - biomarker KW - PPMS KW - MS neurodegeneration KW - LysoPC(20:0) Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-426307 SN - 1866-8372 IS - 694 ER - TY - JOUR A1 - Steinfath, Matthias A1 - Strehmel, Nadine A1 - Peters, Rolf A1 - Schauer, Nicolas A1 - Groth, Detlef A1 - Hummel, Jan A1 - Steup, Martin A1 - Selbig, Joachim A1 - Kopka, Joachim A1 - Geigenberger, Peter A1 - Dongen, Joost T. van T1 - Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach N2 - Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information. Y1 - 2010 UR - http://www3.interscience.wiley.com/cgi-bin/issn?DESCRIPTOR=PRINTISSN&VALUE=1467-7644 U6 - https://doi.org/10.1111/j.1467-7652.2010.00516.x SN - 1467-7644 ER - TY - THES A1 - Schauer, Nicolas T1 - Quantitative trait loci (QTL) for metabolite accumulation and metabolic regulation : metabolite profiling of interspecific crosses of tomato T1 - Metabolomische Analyse von interspezifischen Tomaten N2 - The advent of large-scale and high-throughput technologies has recently caused a shift in focus in contemporary biology from decades of reductionism towards a more systemic view. Alongside the availability of genome sequences the exploration of organisms utilizing such approach should give rise to a more comprehensive understanding of complex systems. Domestication and intensive breeding of crop plants has led to a parallel narrowing of their genetic basis. The potential to improve crops by conventional breeding using elite cultivars is therefore rather limited and molecular technologies, such as marker assisted selection (MAS) are currently being exploited to re-introduce allelic variance from wild species. Molecular breeding strategies have mostly focused on the introduction of yield or resistance related traits to date. However given that medical research has highlighted the importance of crop compositional quality in the human diet this research field is rapidly becoming more important. Chemical composition of biological tissues can be efficiently assessed by metabolite profiling techniques, which allow the multivariate detection of metabolites of a given biological sample. Here, a GC/MS metabolite profiling approach has been applied to investigate natural variation of tomatoes with respect to the chemical composition of their fruits. The establishment of a mass spectral and retention index (MSRI) library was a prerequisite for this work in order to establish a framework for the identification of metabolites from a complex mixture. As mass spectral and retention index information is highly important for the metabolomics community this library was made publicly available. Metabolite profiling of tomato wild species revealed large differences in the chemical composition, especially of amino and organic acids, as well as on the sugar composition and secondary metabolites. Intriguingly, the analysis of a set of S. pennellii introgression lines (IL) identified 889 quantitative trait loci of compositional quality and 326 yield-associated traits. These traits are characterized by increases/decreases not only of single metabolites but also of entire metabolic pathways, thus highlighting the potential of this approach in uncovering novel aspects of metabolic regulation. Finally the biosynthetic pathway of the phenylalanine-derived fruit volatiles phenylethanol and phenylacetaldehyde was elucidated via a combination of metabolic profiling of natural variation, stable isotope tracer experiments and reverse genetic experimentation. N2 - Die Einführung von Hochdurchsatzmethoden zur Analyse von biologischen Systemen, sowie die umfangreiche Sequenzierung von Genomen haben zu einer Verlagerung der Forschung „im Detail“ zu einer ganzheitlicheren Betrachtungsweise auf Systemebene geführt. Aus einer jahrhundertlangen, intensiven Züchtung und Selektion von Nutzpflanzen resultierte gleichzeitig eine Abnahme der genetischen Varianz. Daraus resultierend sind Nutzpflanzen anfälliger gegenüber Stressfaktoren, wie Pathogenen, hohen Salzkonzentrationen oder Trockenheit, als ihre Wildarten. Das Potential konventioneller Züchtung scheint somit heute an seine Grenzen gekommen zu sein. Daher versucht man mittels moderner Molekulartechnik, wie zum Beispiel Marker-gestützte Selektion, Gene oder ganze Genombereiche von Wildarten mit hoher genetischer Variation in Nutzpflanzen einzukreuzen, vornehmlich mit dem Ziel einer Ertrags- bzw. Resistenzsteigerung. Neueste medizinische Studien belegen, dass die Ernährung eine wesentliche Rolle für die menschliche Gesundheit spielt. Besonders wichtig sind hierbei die gesundheitsfördernden Substanzen in pflanzlichen Nahrungsmitteln. Aus diesem Grund kommt der Erforschung der biochemischen Zusammensetzung von biologischen Proben eine immer größere Bedeutung zu. Diese Untersuchung kann elegant durch Metabolitenprofile, welche die multivariate Analyse komplexer biologischer Proben erlauben, durchgeführt werden. In dieser Arbeit wurde zur Untersuchung der biochemischen Zusammensetzung von Tomatenwildarten und interspezifischen S. pennellii Tomatenintrogressionslinien (IL) eine GC/MS basierte Metabolitenanalyseplattform verwendet. Hierzu war es zunächst notwendig eine Massenspektrenbibliothek, zur Annotierung von Massenspektren und Retentionsindices von, in pflanzlichen Proben vorkommenden, Metaboliten anzulegen. Die Analyse der Tomatenwildarten ergab große Unterschiede gegenüber der Kulturtomate im Hinblick auf den Gehalt an Amino- und organischen Säuren, sowie der Zuckerzusammensetzung und den Gehalt an Sekundärmetaboliten. Die darauf folgende Analyse der ILs, von den jede ein genau definiertes genomisches Segment von S. pennellii beinhaltet, bestätigte diese enorme Variation mit 889 metabolischen und 326 ertragsassozierten-Veränderungen in den ILs. Die metabolischen Veränderungen zeichneten sich durch abnehmende bzw. steigende Gehalte von einzelnen Metaboliten, aber auch durch eine koordinierte Änderung aus. In dieser Arbeit wurde weiterhin der Biosyntheseweg der Volatilenstoffe Phenylethanol und Phenylacetaldehyd mit Hilfe einer IL untersucht. Hierbei konnten durch stabile Isotopenmarkierung und eines „reverse genetics“-Ansatzes Gene bzw. Enzyme identifiziert werden, die für die Dekarboxylierung des Eduktes Phenylalanin verantwortlich sind. Diese Arbeit beschreibt erstmals die umfassende Analyse von biochemischen Komponenten auf Genombasis in Tomatenintrogressionslinien und zeigt damit ein Werkzeug auf zur Identifizierung von qualitativen biochemischen Merkmalen in der modernen molekularen Züchtung. KW - Tomate KW - Metabolit KW - GC-MS KW - Introgression KW - Frucht KW - Metabolome KW - Züchtung KW - metabolic genomics KW - Tomato KW - metabolite profiling KW - metabolome KW - breeding KW - crops KW - fruit KW - metabolite breeding KW - metabolic genomics Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7643 ER -