@article{WatanabeBalazadehTohgeetal.2013, author = {Watanabe, Mutsumi and Balazadeh, Salma and Tohge, Takayuki and Erban, Alexander and Giavalisco, Patrick and Kopka, Joachim and M{\"u}ller-R{\"o}ber, Bernd and Fernie, Alisdair R. and H{\"o}fgen, Rainer}, title = {Comprehensive dissection of spatiotemporal metabolic shifts in primary, secondary, and lipid metabolism during developmental senescence in arabidopsis}, series = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants}, volume = {162}, journal = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants}, number = {3}, publisher = {American Society of Plant Physiologists}, address = {Rockville}, issn = {0032-0889}, doi = {10.1104/pp.113.217380}, pages = {1290 -- 1310}, year = {2013}, abstract = {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.}, language = {en} } @article{WatanabeTohgeBalazadehetal.2018, author = {Watanabe, Mutsumi and Tohge, Takayuki and Balazadeh, Salma and Erban, Alexander and Giavalisco, Patrick and Kopka, Joachim and Mueller-Roeber, Bernd and Fernie, Alisdair R. and Hoefgen, Rainer}, title = {Comprehensive Metabolomics Studies of Plant Developmental Senescence}, series = {Plant Senescence: Methods and Protocols}, volume = {1744}, journal = {Plant Senescence: Methods and Protocols}, publisher = {Humana Press}, address = {Totowa}, isbn = {978-1-4939-7672-0}, issn = {1064-3745}, doi = {10.1007/978-1-4939-7672-0_28}, pages = {339 -- 358}, year = {2018}, abstract = {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.}, language = {en} } @article{SchroederLissoObataetal.2014, author = {Schroeder, Florian and Lisso, Janina and Obata, Toshihiro and Erban, Alexander and Maximova, Eugenia and Giavalisco, Patrick and Kopka, Joachim and Fernie, Alisdair R. and Willmitzer, Lothar and Muessig, Carsten}, title = {Consequences of induced brassinosteroid deficiency in Arabidopsis leaves}, series = {BMC plant biology}, volume = {14}, journal = {BMC plant biology}, publisher = {BioMed Central}, address = {London}, issn = {1471-2229}, doi = {10.1186/s12870-014-0309-0}, pages = {14}, year = {2014}, abstract = {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.}, language = {en} } @article{SprengerErbanSeddigetal.2017, author = {Sprenger, Heike and Erban, Alexander and Seddig, Sylvia and Rudack, Katharina and Thalhammer, Anja and Le, Mai Q. and Walther, Dirk and Zuther, Ellen and Koehl, Karin I. and Kopka, Joachim and Hincha, Dirk K.}, title = {Metabolite and transcript markers for the prediction of potato drought tolerance}, series = {Plant Biotechnology Journal}, volume = {16}, journal = {Plant Biotechnology Journal}, number = {4}, publisher = {Wiley}, address = {Hoboken}, issn = {1467-7644}, doi = {10.1111/pbi.12840}, pages = {939 -- 950}, year = {2017}, abstract = {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.}, language = {en} } @misc{SprengerErbanSeddigetal.2018, author = {Sprenger, Heike and Erban, Alexander and Seddig, Sylvia and Rudack, Katharina and Thalhammer, Anja and Le, Mai Q. and Walther, Dirk and Zuther, Ellen and K{\"o}hl, Karin I. and Kopka, Joachim and Hincha, Dirk K.}, title = {Metabolite and transcript markers for the prediction of potato drought tolerance}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {673}, issn = {1866-8372}, doi = {10.25932/publishup-42463}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-424630}, pages = {12}, year = {2018}, abstract = {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.}, language = {en} } @article{MettlerMuehlhausHemmeetal.2014, author = {Mettler, Tabea and M{\"u}hlhaus, Timo and Hemme, Dorothea and Sch{\"o}ttler, Mark Aurel and Rupprecht, Jens and Idoine, Adam and Veyel, Daniel and Pal, Sunil Kumar and Yaneva-Roder, Liliya and Winck, Flavia Vischi and Sommer, Frederik and Vosloh, Daniel and Seiwert, Bettina and Erban, Alexander and Burgos, Asdrubal and Arvidsson, Samuel Janne and Schoenfelder, Stephanie and Arnold, Anne and Guenther, Manuela and Krause, Ursula and Lohse, Marc and Kopka, Joachim and Nikoloski, Zoran and M{\"u}ller-R{\"o}ber, Bernd and Willmitzer, Lothar and Bock, Ralph and Schroda, Michael and Stitt, Mark}, title = {Systems analysis of the response of photosynthesis, metabolism, and growth to an increase in irradiance in the photosynthetic model organism chlamydomonas reinhardtii}, series = {The plant cell}, volume = {26}, journal = {The plant cell}, number = {6}, publisher = {American Society of Plant Physiologists}, address = {Rockville}, issn = {1040-4651}, doi = {10.1105/tpc.114.124537}, pages = {2310 -- 2350}, year = {2014}, abstract = {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.}, language = {en} }