High-density kinetic analysis of the metabolomic and transcriptomic response of Arabidopsis to eight environmental conditions (original) (raw)
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Understanding metabolic acclimation of plants to challenging environmental conditions is essential for dissecting the role of metabolic pathways in growth and survival. As stresses involve simultaneous physiological alterations across all levels of cellular organization, a comprehensive characterization of the role of metabolic pathways in acclimation necessitates integration of genome-scale models with high-throughput data. Here, we present an integrative optimization-based approach, which, by coupling a plant metabolic network model and transcriptomics data, can predict the metabolic pathways affected in a single, carefully controlled experiment. Moreover, we propose three optimization-based indices that characterize different aspects of metabolic pathway behavior in the context of the entire metabolic network. We demonstrate that the proposed approach and indices facilitate quantitative comparisons and characterization of the plant metabolic response under eight different light and/or temperature conditions. The predictions of the metabolic functions involved in metabolic acclimation of Arabidopsis thaliana to the changing conditions are in line with experimental evidence and result in a hypothesis about the role of homocysteine-to-Cys interconversion and Asn biosynthesis. The approach can also be used to reveal the role of particular metabolic pathways in other scenarios, while taking into consideration the entirety of characterized plant metabolism.
Light has a specific role in modulating Arabidopsis gene expression at low temperature
BMC Plant Biology, 2008
Background: Light and temperature are the key abiotic modulators of plant gene expression. In the present work the effect of light under low temperature treatment was analyzed by using microarrays. Specific attention was paid to the up and down regulated genes by using promoter analysis. This approach revealed putative regulatory networks of transcription factors behind the induction or repression of the genes.
The Plant Journal, 2019
Stress responses in plants imply spatio-temporal changes in enzymes and metabolites, including subcellular compartment-specific reallocation processes triggered by sudden changes in environmental parameters. To investigate interactions of primary metabolism with abiotic stress, the gin2-1 mutant, defective in the sugar sensor hexokinase 1 (HXK1) was compared with its wildtype Landsberg erecta (Ler) based on time resolved, compartment-specific metabolome and proteome data obtained over a full diurnal cycle. The high light sensitive gin2-1 mutant was substantially delayed in subcellular redistribution of metabolites upon stress, and this correlated with a massive reduction in proteins belonging to the ATP producing electron transport chain under high light, while fewer changes occurred in the cold. In the wildtype, compounds specifically protecting individual compartments could be identified, e.g., maltose and raffinose in plastids, myo-inositol in mitochondria, but gin2-1 failed to recruit these substances to the respective compartments, or responded only slowly to high irradiance. No such delay was obtained in the cold. At the whole cell level, concentrations of the amino acids, glycine and serine, provided strong evidence for an important role of the photorespiratory pathway during stress exposure, and different subcellular allocation of serine may contribute to the slow growth of the gin2-1 mutant under high irradiance.
Classical flux balance analysis predicts steady-state flux distributions that maximize a given objective function. A recent study, demonstrated that competing objectives constrain the metabolic fluxes in E. coli. For plants, with multiple cell types, fulfilling different functions, the objectives remain elusive and, therefore, hinder the prediction of actual fluxes, particularly for changing environments. In our study, we presented a novel approach to predict flux capacities for a large collection of metabolic pathways under eight different temperature and light conditions. By integrating time-series transcriptomics data to constrain the flux boundaries of the metabolic model, we captured the time- and condition-specific state of the network. Although based on a single time-series experiment, the comparison of these capacities to a novel null model for transcript distribution allowed us to define a measure for differential behavior that accounts for the underlying network structure and the complex interplay of metabolic pathways.
Plant, Cell & Environment, 2008
This paper characterizes the transcriptional and metabolic response of a chilling-tolerant species to an increasingly large decrease of the temperature. Arabidopsis Col-0 was grown at 20°C and transferred to 17, 14, 12, 10 or 8°C for 6 and 78 h, before harvesting the rosette and profiling >22 000 transcripts, >20 enzyme activities and >80 metabolites. Most parameters showed a qualitatively similar response across the entire temperature range, with the amplitude increasing as the temperature decreased. Transcripts typically showed large changes after 6 h, which were often damped by 78 h. Genes were induced for sucrose, proline, raffinose, tocopherol and polyamine synthesis, phenylpropanoid and flavonoid metabolism, fermentation, non-phosphorylating mitochondrial electron transport, RNA processing, and protein synthesis, targeting and folding. Genes were repressed for carbonic anhydrases, vacuolar invertase, and ethylene and jasmonic acid signalling. While some enzyme activities and metabolites changed rapidly, most changed slowly. After 6 h, there was an accumulation of phosphorylated intermediates, a shift of partitioning towards sucrose, and a perturbation of glycine decarboxylation and nitrogen metabolism. By 78 h, there was an increase of the overall protein content and many enzyme activities, a general increase of carbohydrates, organic and amino acids, and an increase of many stress-responsive metabolites including raffinose, proline, tocopherol and polyamines. When the responses of transcripts and metabolism were compared, there was little agreement after 6 h, but considerable agreement after 78 h. Comparison with the published studies indicated that much, but not all, of the response was orchestrated by the CBF programme. Overall, our results showed that transcription and metabolism responded in a continuous manner across a wide range of temperatures.
Statistical mining and integration of complex molecular data including metabolites, proteins, and transcripts is one of the critical goals of systems biology (Ideker, T., Galitski, T., and Hood, L. (2001) A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343-372). A number of studies have demonstrated the parallel analysis of metabolites and large scale transcript expression. Protein analysis has been ignored in these studies, although a clear correlation between transcript and protein levels is shown only in rare cases, necessitating that actual protein levels have to be determined for protein function analysis. Here, we present an approach to investigate the combined covariance structure of metabolite and protein dynamics in a systemic response to abiotic temperature stress in Arabidopsis thaliana wild-type and a corresponding starch-deficient mutant (phosphoglucomutase-deficient). Independent component analysis revealed phenotype classification resolving genotype-dependent response effects to temperature treatment and genotype-independent general temperature compensation mechanisms. An observation is the stress-induced increase of raffinose-family-oligosaccharide levels in the absence of transitory starch storage/mobilization in temperature-treated phosphoglucomutase plants indicating that sucrose synthesis and storage in these mutant plants is sufficient to bypass the typical starch storage/mobilization pathways under abiotic stress. Eventually, sample pattern recognition and correlation network topology analysis allowed for the detection of specific metabolite-protein co-regulation and assignment of a circadian output regulated RNA-binding protein to these processes. The whole concept of high-dimensional profiling data integration from many replicates, subsequent multiva-
Journal of experimental botany, 2018
As a consequence of global change processes, plants will be increasingly challenged by extreme climatic events, against a background of elevated atmospheric CO2. We analysed responses of Arabidopsis thaliana to a combination of heat wave and water deficit at ambient and elevated CO2, and provided mechanistic insight on changes in primary metabolism. Climate extreme-induced metabolic changes are dynamic and molecule class-specific. Concentrations of soluble sugars and amino acids increased transiently after short (4 d) exposure to heat and drought, and readjusted to control levels under prolonged (8 d) stress. In contrast, fatty acids showed persistent changes during the stress period. Elevated CO2 reduced the stress impact on sugar and amino acid metabolism, but not on fatty acids. Integrating metabolite data with transcriptome results, revealed that some of the metabolic changes are regulated at the transcriptional level. Multivariate analyses grouped metabolites on the basis of st...
PLANT PHYSIOLOGY, 2013
Photosynthetic carbon assimilation including photorespiration is dynamically regulated during the day/night cycle. This includes transcriptional regulation, such as the light induction of corresponding genes, but little is known about the contribution of photorespiratory metabolites to the regulation of gene expression. Here, we examined diurnal changes in the levels of photorespiratory metabolites, of enzymes of the photorespiratory carbon cycle, and of corresponding transcripts in wild-type plants of Arabidopsis (Arabidopsis thaliana) and in a mutant with altered photorespiratory flux due to the absence of the peroxisomal enzyme Hydroxypyruvate Reductase1 (HPR1). Metabolomics of the wild type showed that the relative amounts of most metabolites involved in photorespiration increased after the onset of light, exhibited maxima at the end of the day, and decreased during the night. In accordance with those findings, both the amounts of messenger RNAs encoding photorespiratory enzymes...
Molecular & Cellular Proteomics, 2008
Statistical mining and integration of complex molecular data including metabolites, proteins, and transcripts is one of the critical goals of systems biology (Ideker, T., Galitski, T., and Hood, L. (2001) A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343-372). A number of studies have demonstrated the parallel analysis of metabolites and large scale transcript expression. Protein analysis has been ignored in these studies, although a clear correlation between transcript and protein levels is shown only in rare cases, necessitating that actual protein levels have to be determined for protein function analysis. Here, we present an approach to investigate the combined covariance structure of metabolite and protein dynamics in a systemic response to abiotic temperature stress in Arabidopsis thaliana wild-type and a corresponding starch-deficient mutant (phosphoglucomutase-deficient). Independent component analysis revealed phenotype classification resolving genotype-dependent response effects to temperature treatment and genotype-independent general temperature compensation mechanisms. An observation is the stress-induced increase of raffinose-family-oligosaccharide levels in the absence of transitory starch storage/mobilization in temperature-treated phosphoglucomutase plants indicating that sucrose synthesis and storage in these mutant plants is sufficient to bypass the typical starch storage/mobilization pathways under abiotic stress. Eventually, sample pattern recognition and correlation network topology analysis allowed for the detection of specific metabolite-protein co-regulation and assignment of a circadian output regulated RNA-binding protein to these processes. The whole concept of high-dimensional profiling data integration from many replicates, subsequent multiva-riate statistics for dimensionality reduction, and covariance structure analysis is proposed to be a major strategy for revealing central responses of the biological system under study.