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 - 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 - 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 - 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 - 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 - 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 -