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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
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
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.
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.
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.
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.
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.
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.
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.
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.