TY  - JOUR
A1  - Scholz, Matthias
A1  - Kaplan, F.
A1  - Guy, C. L.
A1  - Kopka, Joachim
A1  - Selbig, Joachim
T1  - Non-linear PCA : a missing data approach
N2  - Motivation: Visualizing and analysing the potential non-linear structure of a dataset is becoming an important task in molecular biology. This is even more challenging when the data have missing values. Results: Here, we propose an inverse model that performs non-linear principal component analysis (NLPCA) from incomplete datasets. Missing values are ignored while optimizing the model, but can be estimated afterwards. Results are shown for both artificial and experimental datasets. In contrast to linear methods, non-linear methods were able to give better missing value estimations for non-linear structured data. Application: We applied this technique to a time course of metabolite data from a cold stress experiment on the model plant Arabidopsis thaliana, and could approximate the mapping function from any time point to the metabolite responses. Thus, the inverse NLPCA provides greatly improved information for better understanding the complex response to cold stress
Y1  - 2005
SN  - 1367-4803
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  - Sprenger, Heike
A1  - Erban, Alexander
A1  - Seddig, Sylvia
A1  - Rudack, Katharina
A1  - Thalhammer, Anja
A1  - Le, Mai Q.
A1  - Walther, Dirk
A1  - Zuther, Ellen
A1  - Koehl, Karin I.
A1  - Kopka, Joachim
A1  - Hincha, Dirk K.
T1  - Metabolite and transcript markers for the prediction of potato drought tolerance
JF  - Plant Biotechnology Journal
N2  - Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions.
KW  - drought tolerance
KW  - machine learning
KW  - metabolite markers
KW  - potato (Solanum tuberosum)
KW  - prediction models
KW  - transcript markers
Y1  - 2017
U6  - https://doi.org/10.1111/pbi.12840
SN  - 1467-7644
SN  - 1467-7652
VL  - 16
IS  - 4
SP  - 939
EP  - 950
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Rautengarten, Carsten
A1  - Steinhaeuser, Dirk
A1  - Bussis, D
A1  - Stintzi, A
A1  - Schaller, A
A1  - Kopka, Joachim
A1  - Altmann, Thomas
T1  - Inferring hypotheses on functional relationships of genes : Analysis of the Arabidopsis thaliana subtilase gene family
N2  - The gene family of subtilisin-like serine proteases (subtilases) in Arabidopsis thaliana comprises 56 members, divided into six distinct subfamilies. Whereas the members of five subfamilies are similar to pyrolysins, two genes share stronger similarity to animal kexins. Mutant screens confirmed 144 T-DNA insertion lines with knockouts for 55 out of the 56 subtilases. Apart from SDD1, none of the confirmed homozygous mutants revealed any obvious visible phenotypic alteration during growth under standard conditions. Apart from this specific case, forward genetics gave us no hints about the function of the individual 54 non-characterized subtilase genes. Therefore, the main objective of our work was to overcome the shortcomings of the forward genetic approach and to infer alternative experimental approaches by using an integrative biolinformatics and biological approach. Computational analyses based on transcriptional co-expression and co-response pattern revealed at least two expression networks, suggesting that functional redundancy may exist among subtilases with limited similarity. Furthermore, two hubs were identified, which may be involved in signalling or may represent higher-order regulatory factors involved in responses to environmental cues. A particular enrichment of co- regulated genes with metabolic functions was observed for four subtilases possibly representing late responsive elements of environmental stress. The kexin homologs show stronger associations with genes of transcriptional regulation context. Based on the analyses presented here and in accordance with previously characterized subtilases, we propose three main functions of subtilases: involvement in (i) control of development, (ii) protein turnover, and (iii) action as downstream components of signalling cascades
Y1  - 2005
ER  - 
TY  - JOUR
A1  - Lisso, Janina
A1  - Steinhaeuser, Dirk
A1  - Altmann, Thomas
A1  - Kopka, Joachim
A1  - Müssig, Carsten
T1  - Identification of brassinosteroid-related genes by means of transcript co-response analyses
N2  - The comprehensive systems-biology database (CSB.DB) was used to reveal brassinosteroid (BR)-related genes from expression profiles based on co-response analyses. Genes exhibiting simultaneous changes in transcript levels are candidates of common transcriptional regulation. Combining numerous different experiments in data matrices allows ruling out outliers and conditional changes of transcript levels. CSB.DB was queried for transcriptional co-responses with the BR-signalling components BRI1 and BAK1: 301 out of 9694 genes represented in the nasc0271 database showed co-responses with both genes. As expected, these genes comprised pathway-involved genes (e.g. 72 BR-induced genes), because the BRI1 and BAK1 proteins are required for BR-responses. But transcript co-response takes the analysis a step further compared with direct approaches because BR-related non BR-responsive genes were identified. Insights into networks and the functional context of genes are provided, because factors determining expression patterns are reflected in correlations. Our findings demonstrate that transcript co-response analysis presents a valuable resource to uncover common regulatory patterns of genes. Different data matrices in CSB.DB allow examination of specific biological questions. All matrices are publicly available through CSB.DB. This work presents one possible roadmap to use the CSB.DB resources
Y1  - 2005
SN  - 0305-1048
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  - 
TY  - JOUR
A1  - Schroeder, Florian
A1  - Lisso, Janina
A1  - Obata, Toshihiro
A1  - Erban, Alexander
A1  - Maximova, Eugenia
A1  - Giavalisco, Patrick
A1  - Kopka, Joachim
A1  - Fernie, Alisdair R.
A1  - Willmitzer, Lothar
A1  - Muessig, Carsten
T1  - Consequences of induced brassinosteroid deficiency in Arabidopsis leaves
JF  - BMC plant biology
N2  - Background: The identification of brassinosteroid (BR) deficient and BR insensitive mutants provided conclusive evidence that BR is a potent growth-promoting phytohormone. Arabidopsis mutants are characterized by a compact rosette structure, decreased plant height and reduced root system, delayed development, and reduced fertility. Cell expansion, cell division, and multiple developmental processes depend on BR. The molecular and physiological basis of BR action is diverse. The BR signalling pathway controls the activity of transcription factors, and numerous BR responsive genes have been identified. The analysis of dwarf mutants, however, may to some extent reveal phenotypic changes that are an effect of the altered morphology and physiology. This restriction holds particularly true for the analysis of established organs such as rosette leaves. Results: In this study, the mode of BR action was analysed in established leaves by means of two approaches. First, an inhibitor of BR biosynthesis (brassinazole) was applied to 21-day-old wild-type plants. Secondly, BR complementation of BR deficient plants, namely CPD (constitutive photomorphogenic dwarf)-antisense and cbb1 (cabbage1) mutant plants was stopped after 21 days. BR action in established leaves is associated with stimulated cell expansion, an increase in leaf index, starch accumulation, enhanced CO2 release by the tricarboxylic acid cycle, and increased biomass production. Cell number and protein content were barely affected. Conclusion: Previous analysis of BR promoted growth focused on genomic effects. However, the link between growth and changes in gene expression patterns barely provided clues to the physiological and metabolic basis of growth. Our study analysed comprehensive metabolic data sets of leaves with altered BR levels. The data suggest that BR promoted growth may depend on the increased provision and use of carbohydrates and energy. BR may stimulate both anabolic and catabolic pathways.
KW  - Brassinosteroids
KW  - Arabidopsis
KW  - Tricarboxylic acid cycle
KW  - Biomass
KW  - Cell expansion
KW  - Growth
Y1  - 2014
U6  - https://doi.org/10.1186/s12870-014-0309-0
SN  - 1471-2229
VL  - 14
PB  - BioMed Central
CY  - London
ER  - 
TY  - JOUR
A1  - Huege, Jan
A1  - Goetze, Jan
A1  - Schwarz, Doreen
A1  - Bauwe, Hermann
A1  - Hagemann, Martin
A1  - Kopka, Joachim
T1  - Modulation of the major Paths of Carbon in photorespiratory mutants of synechocystis
JF  - PLoS one
N2  - Background: Recent studies using transcript and metabolite profiles of wild-type and gene deletion mutants revealed that photorespiratory pathways are essential for the growth of Synechocystis sp. PCC 6803 under atmospheric conditions. Pool size changes of primary metabolites, such as glycine and glycolate, indicated a link to photorespiration.
 Methodology/Principal Findings: The (13)C labelling kinetics of primary metabolites were analysed in photoautotrophically grown cultures of Synechocystis sp. PCC 6803 by gas chromatography-mass spectrometry (GC-MS) to demonstrate the link with photorespiration. Cells pre-acclimated to high CO(2) (5%, HC) or limited CO(2) (0.035%, LC) conditions were pulse-labelled under very high (2% w/w) (13)C-NaHCO(3) (VHC) conditions followed by treatment with ambient (12)C at HC and LC conditions, respectively. The (13)C enrichment, relative changes in pool size, and (13)C flux of selected metabolites were evaluated. We demonstrate two major paths of CO(2) assimilation via Rubisco in Synechocystis, i.e., from 3PGA via PEP to aspartate, malate and citrate or, to a lesser extent, from 3PGA via glucose-6-phosphate to sucrose. The results reveal evidence of carbon channelling from 3PGA to the PEP pool. Furthermore, (13)C labelling of glycolate was observed under conditions thought to suppress photorespiration. Using the glycolate-accumulating Delta glcD1 mutant, we demonstrate enhanced (13)C partitioning into the glycolate pool under conditions favouring photorespiration and enhanced (13)C partitioning into the glycine pool of the glycine-accumulating Delta gcvT mutant. Under LC conditions, the photorespiratory mutants Delta glcD1 and Delta gcvT showed enhanced activity of the additional carbon-fixing PEP carboxylase pathway.
 Conclusions/Significance: With our approach of non-steady-state (13)C labelling and analysis of metabolite pool sizes with respective (13)C enrichments, we identify the use and modulation of major pathways of carbon assimilation in Synechocystis in the presence of high and low inorganic carbon supplies.
Y1  - 2011
U6  - https://doi.org/10.1371/journal.pone.0016278
SN  - 1932-6203
VL  - 6
IS  - 1
PB  - PLoS
CY  - San Fransisco
ER  - 
TY  - GEN
A1  - Sprenger, Heike
A1  - Erban, Alexander
A1  - Seddig, Sylvia
A1  - Rudack, Katharina
A1  - Thalhammer, Anja
A1  - Le, Mai Q.
A1  - Walther, Dirk
A1  - Zuther, Ellen
A1  - Köhl, Karin I.
A1  - Kopka, Joachim
A1  - Hincha, Dirk K.
T1  - Metabolite and transcript markers for the prediction of potato drought tolerance
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker‐assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT‐PCR and GC‐MS profiling, respectively. Transcript marker candidates were selected from a published RNA‐Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 673 
KW  - drought tolerance
KW  - machine learning
KW  - metabolite markers
KW  - potato (Solanum tuberosum)
KW  - prediction models
KW  - transcript markers
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-424630
SN  - 1866-8372
IS  - 673
ER  - 
TY  - JOUR
A1  - Sprenger, Heike
A1  - Rudack, Katharina
A1  - Schudoma, Christian
A1  - Neumann, Arne
A1  - Seddig, Sylvia
A1  - Peters, Rolf
A1  - Zuther, Ellen
A1  - Kopka, Joachim
A1  - Hincha, Dirk K.
A1  - Walther, Dirk
A1  - Koehl, Karin
T1  - Assessment of drought tolerance and its potential yield penalty in potato
JF  - Functional plant biology : an international journal of plant function
N2  - Climate models predict an increased likelihood of seasonal droughts for many areas of the world. Breeding for drought tolerance could be accelerated by marker-assisted selection. As a basis for marker identification, we studied the genetic variance, predictability of field performance and potential costs of tolerance in potato (Solanum tuberosum L.). Potato produces high calories per unit of water invested, but is drought-sensitive. In 14 independent pot or field trials, 34 potato cultivars were grown under optimal and reduced water supply to determine starch yield. In an artificial dataset, we tested several stress indices for their power to distinguish tolerant and sensitive genotypes independent of their yield potential. We identified the deviation of relative starch yield from the experimental median (DRYM) as the most efficient index. DRYM corresponded qualitatively to the partial least square model-based metric of drought stress tolerance in a stress effect model. The DRYM identified significant tolerance variation in the European potato cultivar population to allow tolerance breeding and marker identification. Tolerance results from pot trials correlated with those from field trials but predicted field performance worse than field growth parameters. Drought tolerance correlated negatively with yield under optimal conditions in the field. The distribution of yield data versus DRYM indicated that tolerance can be combined with average yield potentials, thus circumventing potential yield penalties in tolerance breeding.
KW  - performance prediction
KW  - Solanum tuberosum
KW  - tolerance index
KW  - target environment
Y1  - 2015
U6  - https://doi.org/10.1071/FP15013
SN  - 1445-4408
SN  - 1445-4416
VL  - 42
IS  - 7
SP  - 655
EP  - 667
PB  - CSIRO
CY  - Clayton
ER  - 
TY  - THES
A1  - Kopka, Joachim
T1  - Applied metabolome analysis : exploration, development and application of gas chromatography-mass spectrometry based metabolite profiling technologies
T1  - Angewandte Metabolom Analyse : Erforschung, Entwicklung und Anwendung von auf Gaschromatographie-Massenspektrometrie basierenden
N2  - The uptake of nutrients and their subsequent chemical conversion by reactions which provide energy and building blocks for growth and propagation is a fundamental property of life. This property is termed metabolism. In the course of evolution life has been dependent on chemical reactions which generate molecules that are common and indispensable to all life forms. These molecules are the so-called primary metabolites. In addition, life has evolved highly diverse biochemical reactions. These reactions allow organisms to produce unique molecules, the so-called secondary metabolites, which provide a competitive advantage for survival. The sum of all metabolites produced by the complex network of reactions within an organism has since 1998 been called the metabolome. The size of the metabolome can only be estimated and may range from less than 1,000 metabolites in unicellular organisms to approximately 200,000 in the whole plant kingdom. In current biology, three additional types of molecules are thought to be important to the understanding of the phenomena of life: (1) the proteins, in other words the proteome, including enzymes which perform the metabolic reactions, (2) the ribonucleic acids (RNAs) which constitute the so-called transcriptome, and (3) all genes of the genome which are encoded within the double strands of desoxyribonucleic acid (DNA). Investigations of each of these molecular levels of life require analytical technologies which should best enable the comprehensive analysis of all proteins, RNAs, et cetera. At the beginning of this thesis such analytical technologies were available for DNA, RNA and proteins, but not for metabolites. Therefore, this thesis was dedicated to the implementation of the gas chromatography – mass spectrometry technology, in short GC-MS, for the in-parallel analysis of as many metabolites as possible. Today GC-MS is one of the most widely applied technologies and indispensable for the efficient profiling of primary metabolites. The main achievements and research topics of this work can be divided into technological advances and novel insights into the metabolic mechanisms which allow plants to cope with environmental stresses. Firstly, the GC-MS profiling technology has been highly automated and standardized. The major technological achievements were (1) substantial contributions to the development of automated and, within the limits of GC-MS, comprehensive chemical analysis, (2) contributions to the implementation of time of flight mass spectrometry for GC-MS based metabolite profiling, (3) the creation of a software platform for reproducible GC-MS data processing, named TagFinder, and (4) the establishment of an internationally coordinated library of mass spectra which allows the identification of metabolites in diverse and complex biological samples. In addition, the Golm Metabolome Database (GMD) has been initiated to harbor this library and to cope with the increasing amount of generated profiling data. This database makes publicly available all chemical information essential for GC-MS profiling and has been extended to a global resource of GC-MS based metabolite profiles. Querying the concentration changes of hundreds of known and yet non-identified metabolites has recently been enabled by uploading standardized, TagFinder-processed data. Long-term technological aims have been pursued with the central aims (1) to enhance the precision of absolute and relative quantification and (2) to enable the combined analysis of metabolite concentrations and metabolic flux. In contrast to concentrations which provide information on metabolite amounts, flux analysis provides information on the speed of biochemical reactions or reaction sequences, for example on the rate of CO2 conversion into metabolites. This conversion is an essential function of plants which is the basis of life on earth. Secondly, GC-MS based metabolite profiling technology has been continuously applied to advance plant stress physiology. These efforts have yielded a detailed description of and new functional insights into metabolic changes in response to high and low temperatures as well as common and divergent responses to salt stress among higher plants, such as Arabidopsis thaliana, Lotus japonicus and rice (Oryza sativa). Time course analysis after temperature stress and investigations into salt dosage responses indicated that metabolism changed in a gradual manner rather than by stepwise transitions between fixed states. In agreement with these observations, metabolite profiles of the model plant Lotus japonicus, when exposed to increased soil salinity, were demonstrated to have a highly predictive power for both NaCl accumulation and plant biomass. Thus, it may be possible to use GC-MS based metabolite profiling as a breeding tool to support the selection of individual plants that cope best with salt stress or other environmental challenges.
N2  - Die Aufnahme von Nährstoffen und ihre chemische Umwandlung mittels Reaktionen, die Energie und Baustoffe für Wachstum und Vermehrung bereitstellen, ist eine grundlegende Eigenschaft des Lebens. Diese Eigenschaft wird Stoffwechsel oder, wie im Folgenden, Metabolismus genannt. Im Verlauf der Evolution war alles Leben abhängig von solchen Reaktionen, die essentielle und allen Lebensformen gemeinsame Moleküle erzeugen. Über diese sogenannten Primärmetabolite hinaus sind hochdiverse Reaktionen entstanden. Diese erlauben Organismen, einzigartige sogenannte Sekundärmetabolite zu produzieren, die in der Regel einen zusätzlichen Überlebensvorteil vermitteln. Die Gesamtheit aller Metabolite, die von dem komplexen Reaktionsnetzwerk in Organismen erzeugt werden, nennt man seit 1998 das Metabolom. Die Größe des Metaboloms kann nur geschätzt werden. Neben der Gesamtheit aller Metabolite werden heute drei weitere Arten an Molekülen als wesentlich betrachtet, um die Phänomene des Lebens zu verstehen: erstens die Proteine, deren Summe, das Proteom, auch die Enzyme einschließt, die die obigen metabolischen Reaktionen durchführen, zweitens die Ribonukleinsäuren (RNS), deren Gesamtheit als Transkriptom bezeichnet wird, und drittens die doppelsträngige Desoxyribonukleinsäure (DNS), die das Genom, die Summe aller Gene eines Organismus, ausmacht. Die Untersuchung aller dieser vier molekularen Ebenen des Lebens erfordert Technologien, die idealerweise die vollständige Analyse der Gesamtheit aller DNS-, RNS-, Protein-Moleküle, bzw. Metabolite erlauben. Zu Beginn meiner Arbeiten waren solche Technologien für DNS, RNS, und Proteine verfügbar, aber nicht für Metabolite. Aus diesem Grund habe ich meine Forschungstätigkeit auf das Ziel ausgerichtet, so viele Metabolite wie irgend möglich in einer gemeinsamen Analyse zu erfassen. Zu diesem Zweck habe ich mich auf eine einzelne Technik, nämlich die gekoppelte Gaschromatographie und Massenspektrometrie, kurz GC-MS, konzentriert. Nicht zuletzt durch meine Arbeiten ist GC-MS heute eine der am häufigsten angewandten Technologien und unverzichtbar für das breite Durchmustern der Metabolite. Neben der Etablierung der grundlegenden GC-MS-Profilanalyse-Technologie liegen die Haupterrungenschaften meiner Arbeiten sowohl in den technischen Neuerungen als auch in den Einsichten in metabolische Mechanismen, die es Pflanzen erlauben, erfolgreich auf Umwelteinflüsse zu reagieren. Die technologischen Errungenschaften waren erstens wesentliche Beiträge zur Labor-Automatisierung und zur Auswertung von modernen, auf Flugzeitmassenspektrometrie beruhenden, GC-MS-Profilanalysen, zweitens die Entwicklung einer entsprechenden Prozessierungs-Software, genannt TagFinder, und drittens die Etablierung einer internationalen Datensammlung zur Metabolitidentifizierung aus komplexen Mischungen. Diese massenspektralen und gaschromatographischen Daten haben seit 2005 Eingang in die von mir initiierte Entwicklung der Golm Metabolom Datenbank (GMD) gefunden, die die zunehmend wachsenden GC-MS-Referenzdaten wie auch die Metabolitprofildaten verwaltet und öffentlich zugänglich macht. Darüber hinaus wurden die langfristigen Ziele einer verbesserten Präzision für relative und absolute Quantifizierung wie auch einer Kopplung von Konzentrationsbestimmung und metabolischen Flussanalysen mittels GC-MS verfolgt. Sowohl die Stoffmengen als auch die Geschwindigkeit der Stoffaufnahme und der chemischen Umsetzung, d.h. der metabolische Fluss, sind wesentlich für neue biologische Einsichten. In diesem Zusammenhang wurde von mir die Aufnahme von CO2 durch Pflanzen, der Basis allen Lebens auf der Erde, untersucht. Angewandt auf das Temperaturstress- und Salzstressverhalten von Modell- und Kulturpflanzen, nämlich des Ackerschmalwands (Arabidopsis thaliana), des Hornklees (Lotus japonicus) und der global bedeutendsten Nutzpflanze Reis (Oryza sativa), wurden detaillierte und vergleichende neue metabolische Einsichten in den Zeitverlauf der Temperaturanpassung und die Anpassung an zunehmend salzhaltige Böden erzielt. Metabolismus verändert sich unter diesen Bedingungen allmählich fortschreitend und nicht in plötzlichen Übergängen. Am Beispiel des Hornklees konnte gezeigt werden, dass Metabolitprofilanalysen eine hohe Vorhersagekraft für die Biomasseerzeugung unter Salzeinfluss wie auch für die Aufnahme von Salz durch die Pflanze haben. So mag es in Zukunft möglich werden, GC-MS-Profilanaysen anzuwenden, um den Züchtungsprozess von Kulturpflanzen zu beschleunigen.
KW  - Metabolomics
KW  - Metaboliten
KW  - Profilanalysen
KW  - Gaschromatographie
KW  - Massenspektrometrie
KW  - Metabolomics
KW  - Metabolites
KW  - Profiling
KW  - Gas Chromatography
KW  - Mass Spectrometry
Y1  - 2008
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-40597
ER  - 
TY  - JOUR
A1  - Hemme, Dorothea
A1  - Veyel, Daniel
A1  - Muehlhaus, Timo
A1  - Sommer, Frederik
A1  - Jueppner, Jessica
A1  - Unger, Ann-Katrin
A1  - Sandmann, Michael
A1  - Fehrle, Ines
A1  - Schoenfelder, Stephanie
A1  - Steup, Martin
A1  - Geimer, Stefan
A1  - Kopka, Joachim
A1  - Giavalisco, Patrick
A1  - Schroda, Michael
T1  - Systems-wide analysis of acclimation responses to long-term heat stress and recovery in the photosynthetic model organism Chlamydomonas reinhardtii
JF  - The plant cell
N2  - We applied a top-down systems biology approach to understand how Chlamydomonas reinhardtii acclimates to long-term heat stress (HS) and recovers from it. For this, we shifted cells from 25 to 42 degrees C for 24 h and back to 25 degrees C for >= 8 h and monitored abundances of 1856 proteins/protein groups, 99 polar and 185 lipophilic metabolites, and cytological and photosynthesis parameters. Our data indicate that acclimation of Chlamydomonas to long-term HS consists of a temporally ordered, orchestrated implementation of response elements at various system levels. These comprise (1) cell cycle arrest; (2) catabolism of larger molecules to generate compounds with roles in stress protection; (3) accumulation of molecular chaperones to restore protein homeostasis together with compatible solutes; (4) redirection of photosynthetic energy and reducing power from the Calvin cycle to the de novo synthesis of saturated fatty acids to replace polyunsaturated ones in membrane lipids, which are deposited in lipid bodies; and (5) when sinks for photosynthetic energy and reducing power are depleted, resumption of Calvin cycle activity associated with increased photorespiration, accumulation of reactive oxygen species scavengers, and throttling of linear electron flow by antenna uncoupling. During recovery from HS, cells appear to focus on processes allowing rapid resumption of growth rather than restoring pre-HS conditions.
Y1  - 2014
U6  - https://doi.org/10.1105/tpc.114.130997
SN  - 1040-4651
SN  - 1532-298X
VL  - 26
IS  - 11
SP  - 4270
EP  - 4297
PB  - American Society of Plant Physiologists
CY  - Rockville
ER  - 
TY  - JOUR
A1  - Watanabe, Mutsumi
A1  - Tohge, Takayuki
A1  - Balazadeh, Salma
A1  - Erban, Alexander
A1  - Giavalisco, Patrick
A1  - Kopka, Joachim
A1  - Mueller-Roeber, Bernd
A1  - Fernie, Alisdair R.
A1  - Hoefgen, Rainer
T1  - Comprehensive Metabolomics Studies of Plant Developmental Senescence
JF  - Plant Senescence: Methods and Protocols
N2  - Leaf senescence is an essential developmental process that involves diverse metabolic changes associated with degradation of macromolecules allowing nutrient recycling and remobilization. In contrast to the significant progress in transcriptomic analysis of leaf senescence, metabolomics analyses have been relatively limited. A broad overview of metabolic changes during leaf senescence including the interactions between various metabolic pathways is required to gain a better understanding of the leaf senescence allowing to link transcriptomics with metabolomics and physiology. In this chapter, we describe how to obtain comprehensive metabolite profiles and how to dissect metabolic shifts during leaf senescence in the model plant Arabidopsis thaliana. Unlike nucleic acid analysis for transcriptomics, a comprehensive metabolite profile can only be achieved by combining a suite of analytic tools. Here, information is provided for measurements of the contents of chlorophyll, soluble proteins, and starch by spectrophotometric methods, ions by ion chromatography, thiols and amino acids by HPLC, primary metabolites by GC/TOF-MS, and secondary metabolites and lipophilic metabolites by LC/ESI-MS. These metabolite profiles provide a rich catalogue of metabolic changes during leaf senescence, which is a helpful database and blueprint to be correlated to future studies such as transcriptome and proteome analyses, forward and reverse genetic studies, or stress-induced senescence studies.
KW  - Senescence
KW  - Metabolomics
KW  - Arabidopsis
KW  - GC/MS
KW  - LC/MS
KW  - HPLC
KW  - IC
Y1  - 2018
SN  - 978-1-4939-7672-0
SN  - 978-1-4939-7670-6
U6  - https://doi.org/10.1007/978-1-4939-7672-0_28
SN  - 1064-3745
SN  - 1940-6029
VL  - 1744
SP  - 339
EP  - 358
PB  - Humana Press
CY  - Totowa
ER  - 
TY  - JOUR
A1  - Skirycz, Aleksandra
A1  - Reichelt, Michael
A1  - Burow, Meike
A1  - Birkemeyer, Claudia Sabine
A1  - Rolcik, Jacub
A1  - Kopka, Joachim
A1  - Zanor, Maria Ines
A1  - Gershenzon, Jonathan
A1  - Strnad, Miroslav
A1  - Szopa, Jan
A1  - Müller-Röber, Bernd
A1  - Witt, Isabell
T1  - DOF transcription factor AtDof1.1 (OBP2) is part of a regulatory network controlling glucosinolate biosynthesis in Arabidopsis
N2  - Glucosinolates are a group of secondary metabolites that function as defense substances against herbivores and micro-organisms in the plant order Capparales. Indole glucosinolates (IGS), derivatives of tryptophan, may also influence plant growth and development. In Arabidopsis thaliana, indole-3-acetaldoxime (IAOx) produced from tryptophan by the activity of two cytochrome P450 enzymes, CYP79B2 and CYP79B3, serves as a precursor for IGS biosynthesis but is also an intermediate in the biosynthetic pathway of indole-3-acetic acid (IAA). Another cytochrome P450 enzyme, CYP83B1, funnels IAOx into IGS. Although there is increasing information about the genes involved in this biochemical pathway, their regulation is not fully understood. OBP2 has recently been identified as a member of the DNA-binding-with-one- finger (DOF) transcription factors, but its function has not been studied in detail so far. Here we report that OBP2 is expressed in the vasculature of all Arabidopsis organs, including leaves, roots, flower stalks and petals. OBP2 expression is induced in response to a generalist herbivore, Spodoptera littoralis, and by treatment with the plant signalling molecule methyl jasmonate, both of which also trigger IGS accumulation. Constitutive and inducible over- expression of OBP2 activates expression of CYP83B1. In addition, auxin concentration is increased in leaves and seedlings of OBP2 over-expression lines relative to wild-type, and plant size is diminished due to a reduction in cell size. RNA interference-mediated OBP2 blockade leads to reduced expression of CYP83B1. Collectively, these data provide evidence that OBP2 is part of a regulatory network that regulates glucosinolate biosynthesis in Arabidopsis
Y1  - 2006
UR  - http://onlinelibrary.wiley.com/doi/10.1111/j.1365-313X.2006.02767.x/full
ER  - 
TY  - JOUR
A1  - Hilker, Monika
A1  - Schwachtje, Jens
A1  - Baier, Margarete
A1  - Balazadeh, Salma
A1  - Bäurle, Isabel
A1  - Geiselhardt, Sven
A1  - Hincha, Dirk K.
A1  - Kunze, Reinhard
A1  - Mueller-Roeber, Bernd
A1  - Rillig, Matthias G.
A1  - Rolff, Jens
A1  - Schmülling, Thomas
A1  - Steppuhn, Anke
A1  - van Dongen, Joost
A1  - Whitcomb, Sarah J.
A1  - Wurst, Susanne
A1  - Zuther, Ellen
A1  - Kopka, Joachim
T1  - Priming and memory of stress responses in organisms lacking a nervous system
JF  - Biological reviews
KW  - priming
KW  - stress signalling
KW  - epigenetics
KW  - memory
KW  - fitness
KW  - stress tolerance
KW  - defence
KW  - bet hedging
Y1  - 2016
U6  - https://doi.org/10.1111/brv.12215
SN  - 1464-7931
SN  - 1469-185X
VL  - 91
SP  - 1118
EP  - 1133
PB  - Wiley-Blackwell
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Watanabe, Mutsumi
A1  - Balazadeh, Salma
A1  - Tohge, Takayuki
A1  - Erban, Alexander
A1  - Giavalisco, Patrick
A1  - Kopka, Joachim
A1  - Müller-Röber, Bernd
A1  - Fernie, Alisdair R.
A1  - Höfgen, Rainer
T1  - Comprehensive dissection of spatiotemporal metabolic shifts in primary, secondary, and lipid metabolism during developmental senescence in arabidopsis
JF  - Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants
N2  - Developmental senescence is a coordinated physiological process in plants and is critical for nutrient redistribution from senescing leaves to newly formed sink organs, including young leaves and developing seeds. Progress has been made concerning the genes involved and the regulatory networks controlling senescence. The resulting complex metabolome changes during senescence have not been investigated in detail yet. Therefore, we conducted a comprehensive profiling of metabolites, including pigments, lipids, sugars, amino acids, organic acids, nutrient ions, and secondary metabolites, and determined approximately 260 metabolites at distinct stages in leaves and siliques during senescence in Arabidopsis (Arabidopsis thaliana). This provided an extensive catalog of metabolites and their spatiotemporal cobehavior with progressing senescence. Comparison with silique data provides clues to source-sink relations. Furthermore, we analyzed the metabolite distribution within single leaves along the basipetal sink-source transition trajectory during senescence. Ceramides, lysolipids, aromatic amino acids, branched chain amino acids, and stress-induced amino acids accumulated, and an imbalance of asparagine/aspartate, glutamate/glutamine, and nutrient ions in the tip region of leaves was detected. Furthermore, the spatiotemporal distribution of tricarboxylic acid cycle intermediates was already changed in the presenescent leaves, and glucosinolates, raffinose, and galactinol accumulated in the base region of leaves with preceding senescence. These results are discussed in the context of current models of the metabolic shifts occurring during developmental and environmentally induced senescence. As senescence processes are correlated to crop yield, the metabolome data and the approach provided here can serve as a blueprint for the analysis of traits and conditions linking crop yield and senescence.
Y1  - 2013
U6  - https://doi.org/10.1104/pp.113.217380
SN  - 0032-0889
VL  - 162
IS  - 3
SP  - 1290
EP  - 1310
PB  - American Society of Plant Physiologists
CY  - Rockville
ER  - 
TY  - JOUR
A1  - Pries, Christopher
A1  - Razaghi-Moghadam, Zahra
A1  - Kopka, Joachim
A1  - Nikoloski, Zoran
T1  - Integration of relative metabolomics and transcriptomics time-course data in a metabolic model pinpoints effects of ribosome biogenesis defects on Arabidopsis thaliana metabolism
JF  - Scientific reports
N2  - Ribosome biogenesis is tightly associated to plant metabolism due to the usage of ribosomes in the synthesis of proteins necessary to drive metabolic pathways. Given the central role of ribosome biogenesis in cell physiology, it is important to characterize the impact of different components involved in this process on plant metabolism. Double mutants of the Arabidopsis thaliana cytosolic 60S maturation factors REIL1 and REIL2 do not resume growth after shift to moderate 10 degrees C chilling conditions. To gain mechanistic insights into the metabolic effects of this ribosome biogenesis defect on metabolism, we developed TC-iReMet2, a constraint-based modelling approach that integrates relative metabolomics and transcriptomics time-course data to predict differential fluxes on a genome-scale level. We employed TC-iReMet2 with metabolomics and transcriptomics data from the Arabidopsis Columbia 0 wild type and the reil1-1 reil2-1 double mutant before and after cold shift. We identified reactions and pathways that are highly altered in a mutant relative to the wild type. These pathways include the Calvin-Benson cycle, photorespiration, gluconeogenesis, and glycolysis. Our findings also indicated differential NAD(P)/NAD(P)H ratios after cold shift. TC-iReMet2 allows for mechanistic hypothesis generation and interpretation of system biology experiments related to metabolic fluxes on a genome-scale level.
Y1  - 2021
U6  - https://doi.org/10.1038/s41598-021-84114-y
SN  - 2045-2322
VL  - 11
IS  - 1
PB  - Macmillan Publishers Limited, part of Springer Nature
CY  - London
ER  - 
TY  - JOUR
A1  - Mettler, Tabea
A1  - Mühlhaus, Timo
A1  - Hemme, Dorothea
A1  - Schöttler, Mark Aurel
A1  - Rupprecht, Jens
A1  - Idoine, Adam
A1  - Veyel, Daniel
A1  - Pal, Sunil Kumar
A1  - Yaneva-Roder, Liliya
A1  - Winck, Flavia Vischi
A1  - Sommer, Frederik
A1  - Vosloh, Daniel
A1  - Seiwert, Bettina
A1  - Erban, Alexander
A1  - Burgos, Asdrubal
A1  - Arvidsson, Samuel Janne
A1  - Schoenfelder, Stephanie
A1  - Arnold, Anne
A1  - Guenther, Manuela
A1  - Krause, Ursula
A1  - Lohse, Marc
A1  - Kopka, Joachim
A1  - Nikoloski, Zoran
A1  - Müller-Röber, Bernd
A1  - Willmitzer, Lothar
A1  - Bock, Ralph
A1  - Schroda, Michael
A1  - Stitt, Mark
T1  - Systems analysis of the response of photosynthesis, metabolism, and growth to an increase in irradiance in the photosynthetic model organism chlamydomonas reinhardtii
JF  - The plant cell
N2  - We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R-2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance.
Y1  - 2014
U6  - https://doi.org/10.1105/tpc.114.124537
SN  - 1040-4651
SN  - 1532-298X
VL  - 26
IS  - 6
SP  - 2310
EP  - 2350
PB  - American Society of Plant Physiologists
CY  - Rockville
ER  -