TY - JOUR A1 - Witzel, Katja A1 - Strehmel, Nadine A1 - Baldermann, Susanne A1 - Neugart, Susanne A1 - Becker, Yvonne A1 - Becker, Matthias A1 - Berger, Beatrice A1 - Scheel, Dierk A1 - Grosch, Rita A1 - Schreiner, Monika A1 - Ruppel, Silke T1 - Arabidopsis thaliana root and root exudate metabolism is altered by the growth-promoting bacterium Kosakonia radicincitans DSM 16656(T) JF - Plant and soil N2 - Plant growth-promoting bacteria (PGPB) affect host physiological processes in various ways. This study aims at elucidating the dependence of bacterial-induced growth promotion on the plant genotype and characterizing plant metabolic adaptations to PGPB. Eighteen Arabidopsis thaliana accessions were inoculated with the PGPB strain Kosakonia radicincitans DSM 16656(T). Colonisation pattern was assessed by enhanced green fluorescent protein (eGFP)-tagged K. radicincitans in three A. thaliana accessions differing in their growth response. Metabolic impact of bacterial colonisation was determined for the best responding accession by profiling distinct classes of plant secondary metabolites and root exudates. Inoculation of 18 A. thaliana accessions resulted in a wide range of growth responses, from repression to enhancement. Testing the bacterial colonisation of three accessions did not reveal a differential pattern. Profiling of plant secondary metabolites showed a differential accumulation of glucosinolates, phenylpropanoids and carotenoids in roots. Analysis of root exudates demonstrated that primary and secondary metabolites were predominantly differentially depleted by bacterial inoculation. The plant genotype controls the bacterial growth promoting traits. Levels of lutein and beta-carotene were elevated in inoculated roots. Supplementing a bacterial suspension with beta-carotene increased bacterial growth, while this was not the case when lutein was applied, indicating that beta-carotene could be a positive regulator of plant growth promotion. KW - Arabidopsis KW - Carotenoids KW - Glucosinolates KW - Plant growth promoting bacteria KW - Phenylpropanoids KW - Root exudates Y1 - 2017 U6 - https://doi.org/10.1007/s11104-017-3371-1 SN - 0032-079X SN - 1573-5036 VL - 419 SP - 557 EP - 573 PB - Springer CY - Dordrecht ER - TY - THES A1 - Strehmel, Nadine T1 - GC-TOF-MS basierte Analyse von niedermolekularen Primär- und Sekundärmetaboliten agrarwirtschaftlich bedeutsamer Nutzpflanzen T1 - GC-TOF-MS based metabolite profiling of low molecular weight primary and secondary metabolites of agricultural meaningful crops N2 - Die Qualität von Nutzpflanzen ist von zahlreichen Einflussfaktoren wie beispielsweise Lagerbedingungen und Sorteneigenschaften abhängig. Um Qualitätsmängel zu minimieren und Absatzchancen von Nutzpflanzen zu steigern sind umfangreiche Analysen hinsichtlich ihrer stofflichen Zusammensetzung notwendig. Chromatographische Techniken gekoppelt an ein Massenspektrometer und die Kernspinresonanzspektroskopie wurden dafür bislang verwendet. In der vorliegenden Arbeit wurde ein Gaschromatograph an ein Flugzeitmassenspektrometer (GC-TOF-MS) gekoppelt, um physiologische Prozesse bzw. Eigenschaften (die Schwarzfleckigkeit, die Chipsbräunung, das Physiologische Alter und die Keimhemmung) von Nutzpflanzen aufzuklären. Als Pflanzenmodell wurde dafür die Kartoffelknolle verwendet. Dazu wurden neue analytische Lösungsansätze entwickelt, die eine zielgerichtete Auswertung einer Vielzahl von Proben, die Etablierung einer umfangreichen Referenzspektrenbibliothek und die sichere Archivierung aller experimentellen Daten umfassen. Das Verfahren der Probenvorbereitung wurde soweit modifiziert, dass gering konzentrierte Substanzen mittels GC-TOF-MS analysiert werden können. Dadurch wurde das durch die Probenvorbereitung limitierte Substanzspektrum erweitert. Anhand dieser Lösungsansätze wurden physiologisch relevante Stoffwechselprodukte identifiziert, welche indikativ (klassifizierend) bzw. prädiktiv (vorhersagend) für die physiologischen Prozesse sind. Für die Schwarzfleckigkeitsneigung und die Chipseignung wurde jeweils ein biochemisches Modell zur Vorhersage dieser Prozesse aufgestellt und auf eine Züchtungspopulation übertragen. Ferner wurden für die Schwarzfleckigkeit Stoffwechselprodukte des Respirationsstoffwechsels identifiziert sowie Aminosäuren, Glycerollipide und Phenylpropanoide für das Physiologische Alter als relevant erachtet. Das physiologische Altern konnte durch die Anwendung höherer Temperaturen beschleunigt werden. Durch Anwendung von Keimhemmern (Kümmelöl, Chlorpropham) wurde eine Verzögerung des physiologischen Alterns beobachtet. Die Applikation von Kümmelöl erwies sich dabei als besonders vorteilhaft. Kümmelöl behandelte Knollen wiesen im Vergleich zu unbehandelten Knollen nur Veränderungen im Aminosäure-, Zucker- und Sekundärstoffwechsel auf. Chlorpropham behandelte Knollen wiesen einen ähnlichen Stoffwechsel wie die unbehandelten Knollen auf. Für die bislang noch nicht identifizierten Stoffwechselprodukte wurden im Rahmen dieser Arbeit das Verfahren der „gezielten An-/Abreicherung“, der „gepaarten NMR/GC-TOF-MS Analyse“ und das „Entscheidungsbaumverfahren“ entwickelt. Diese ermöglichen eine Klassifizierung von GC-MS Signalen im Hinblick auf ihre chemische Funktionalität. Das Verfahren der gekoppelten NMR/GC-TOF-MS Analyse erwies sich dabei als besonders erfolgversprechend, da es eine Aufklärung bislang unbekannter gaschromatographischer Signale ermöglicht. In der vorliegenden Arbeit wurden neue Stoffwechselprodukte in der Kartoffelknolle identifiziert, wodurch ein wertvoller Beitrag zur Analytik der Metabolomik geleistet wurde. N2 - Several factors influence the quality of crops. These include particular storage conditions and cultivar properties. Minimization of quality defects requires the employment of comprehensive metabolic analysis to enhance the marketing potential of crops. From this point of view chromatographic techniques coupled either with a mass spectrometer or the combination with nuclear magnetic resonance spectroscopy have been successfully applied to solve the main tasks. In the present work, a gas chromatograph was coupled to a time of flight mass spectrometer (GC-TOF-MS) to analyze physiological processes and attitudes of crops like black spot bruising, chips tanning, physiological aging, and sprouting inhibition. For this purpose the potato tuber was employed as a model plant. Therefore, new analytical approaches were developed comprising the targeted analysis of a multitude of samples, the establishment of a comprehensive mass spectral reference library and the built up of a secure archival storage system. Furthermore, the sample preparation protocol was modified to analyze trace components with the help of GC-TOF-MS as well. This helped to extend the discovery of more endogenous metabolites. These analytical approaches were required to identify physiological relevant indicative and predictive metabolites. Consequently, a biochemical model was build up for the process of black spot bruising and chips tanning respectively. These models could be applied to an unknown breeding progeny. Metabolites of the respiratory chain were identified as relevant for the process of black spot bruising whereas amino acids, lipids and phenylpropanoids were of high importance for the process of physiological aging.  The process of physiological aging could be accelerated while applying higher temperatures and could be delayed while applying sprouting inhibitors, like caraway oil and chlorpropham. Compared to chlorpropham, caraway oil exhibited more advantages with respect to storage attitudes although it caused significant changes in the amino acid, sugar and secondary metabolism during a common storage period. However, the chlorpropham treated tubers showed a similar phenotype in comparison to the control tubers. In addition, several methods were developed with respect to the classification of yet unidentified signals. These cover the decision tree process, the targeted enrichment and depletion of specific metabolites with the help of solid phase extraction and the paired NMR and GC-MS analyses. The paired NMR and GC-MS analysis appears very promising because it allows for the identification of unknown GC-MS signals. Thus, this work makes a valuable contribution to the analytics of the metabolome, as new metabolites could be identified which are of physiological relevance for the potato tuber. KW - Stoffwechselprodukt KW - Kartoffelknolle KW - Identifizierung KW - analytische Lösungsansätze KW - Biomarker KW - metabolite KW - potato tuber KW - identification KW - analytical approaches KW - biomarker Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-51238 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 - JOUR A1 - Kempa, Stefan A1 - Hummel, Jan A1 - Schwemmer, Thorsten A1 - Pietzke, Matthias A1 - Strehmel, Nadine A1 - Wienkoop, Stefanie A1 - Kopka, Joachim A1 - Weckwerth, Wolfram T1 - An automated GCxGC-TOF-MS protocol for batch-wise extraction and alignment of mass isotopomer matrixes from differential C-13-labelling experiments : a case study for photoautotrophic-mixotrophic grown Chlamydomonas reinhardtii cells N2 - Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of 13 C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/ RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (CO2)-C-13 and C-13- acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotrophic and mixotrophic growth conditions. Y1 - 2009 UR - http://www3.interscience.wiley.com/cgi-bin/jhome/5007687 U6 - https://doi.org/10.1002/jobm.200800337 SN - 0233-111X ER -