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Analytical methods for probing plant metabolism are taking on new significance in the era of functional genomics, metabolomics, and systems biology. Nuclear magnetic resonance (NMR) is becoming a key technology in plant metabolomics. Stable isotope labeling of cultured cells and higher organisms has been especially promising in that it allows the u...
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... The 13 C labeling method for plants described in several previous reports (Kikuchi et al. 2004;Kikuchi and Hirayama 2007;Tian et al. 2007) was utilized in the present study. Briefly, 2-week-old Arabidopsis seedlings assimilated either 10 mM of 13 C 2 -ethanol or non-labeled ethanol (Guaranteed reagent, FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan) via root-uptake for 24 h. ...
Key message
Ethanol priming induces heat stress tolerance by the stimulation of unfolded protein response.
Abstract
Global warming increases the risk of heat stress-related yield losses in agricultural crops. Chemical priming, using safe agents, that can flexibly activate adaptive regulatory responses to adverse conditions, is a complementary approach to genetic improvement for stress adaptation. In the present study, we demonstrated that pretreatment of Arabidopsis with a low concentration of ethanol enhances heat tolerance without suppressing plant growth. We also demonstrated that ethanol pretreatment improved leaf growth in lettuce (Lactuca sativa L.) plants grown in the field conditions under high temperatures. Transcriptome analysis revealed a set of genes that were up-regulated in ethanol-pretreated plants, relative to water-pretreated controls. Binding Protein 3 (BIP3), an endoplasmic reticulum (ER)-stress marker chaperone gene, was among the identified up-regulated genes. The expression levels of BIP3 were confirmed by RT-qPCR. Root-uptake of ethanol was metabolized to organic acids, nucleic acids, amines and other molecules, followed by an increase in putrescine content, which substantially promoted unfolded protein response (UPR) signaling and high-temperature acclimation. We also showed that inhibition of polyamine production and UPR signaling negated the heat stress tolerance induced by ethanol pretreatment. These findings collectively indicate that ethanol priming activates UPR signaling via putrescine accumulation, leading to enhanced heat stress tolerance. The information gained from this study will be useful for establishing ethanol-mediated chemical priming strategies that can be used to help maintain crop production under heat stress conditions.
... Quantitative metabolomics techniques for the detection of plant metabolites include liquid chromatography-electrochemistry-mass spectrometry (LC-EC-MS), gas/liquid chromatography-mass spectrometry (GC/LC-MS), thin-layer chromatography (TLC), Fourier transform infrared (FT-IR) spectroscopy, NMR, direct infusion mass spectrometry (DIMS), and capillary electrophoresis-LC-MS [72][73][74][75][76]. The LC-MS, GC-MS, NMR, and capillary electrophoresis MS techniques are most commonly used in plant metabolomics [77][78][79]. Compared with genomics, transcriptomics, and proteomics, the results of plant metabolomics techniques are more directly related to the plant phenotype. ...
Soybean is a major crop that provides essential protein and oil for food and feed. Since its origin in China over 5000 years ago, soybean has spread throughout the world, becoming the second most important vegetable oil crop and the primary source of plant protein for global consumption. From early domestication and artificial selection through hybridization and ultimately molecular breeding, the history of soybean breeding parallels major advances in plant science throughout the centuries. Now, rapid progress in plant omics is ushering in a new era of precision design breeding, exemplified by the engineering of elite soybean varieties with specific oil compositions to meet various end-use targets. The assembly of soybean reference genomes, made possible by the development of genome sequencing technology and bioinformatics over the past 20 years, was a great step forward in soybean research. It facilitated advances in soybean transcriptomics, proteomics, metabolomics, and phenomics, all of which paved the way for an integrated approach to molecular breeding in soybean. In this review, we summarize the latest progress in omics research, highlight novel findings made possible by omics techniques, note current drawbacks and areas for further research, and suggest that an efficient multi-omics approach may accelerate soybean breeding in the future. This review will be of interest not only to soybean breeders but also to researchers interested in the use of cutting-edge omics technologies for crop research and improvement.
... Several analytical techniques have been implemented in plant systems to quantify metabolites including thin layer chromatography (TLC), gas/liquidchromatography-mass spectrometry (GC/LC-MS), liquid chromatography-electrochemistry-mass spectrometry (LC-EC-MS), NMR, direct infusion mass spectrometry (DIMS), Fourier-transfer infrared (FT-IR), and capillary electrophoresisliquid-chromatography mass spectrometry (CE-MS; Fiehn et al., 2000;Weckwerth, 2003;Moco et al., 2007;Allwood and Goodacre, 2010;Saito and Matsuda, 2010;Duque et al., 2013;Jogaiah et al., 2013). The CE-MS, GC-MS, LC-MS, and NMR techniques are the most frequently used in plant metabolomics (Fiehn, 2002;Kikuchi and Hirayama, 2007;Moco et al., 2007;Allwood and Goodacre, 2010;Weckwerth, 2010;Kim et al., 2011). These techniques depend on the selectivity, sensitivity, speed, and accuracy of the approach. ...
Multiple “omics” approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the “phenotype to genotype” and “genotype to phenotype” concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.
... In metabolomics, also called as metabonomics for NMR-based applications, NMR has been used for biochemical and phytochemical analysis (Kikuchi and Hirayama 2007). NMR spectroscopy is an unbiased, non-destructive method that requires minimal sample preparation. ...
World’s population is increasing exponentially and it is expected to be doubled by the year 2050. In many developing countries and rural areas, malnourishment is also making the condition worse. Conventional crop improvemnt strategies e.g. breeding have been used by farmers since ages, but these approaches are not well efficient to get our targets of having more yield, high quality and nutritional food to feed the rapidly growing population. In this chapter, we have summarized the importance and use of Omics-based strategies e.g. genomics, transcriptomics, proteomics, metabolomics and interactomics, for crop improvements. Omics based approaches have opened the doors to improve the varieties with high yield and enhanced nutritional value, together with herbicide and other stresses resistance ability By overcoming few challenges related to the application of Omics in agriculture, this could be the best option to confront with the current needs and future food demands of the exceeding population.
... Analytical technologies used in metabolomics include thin layer chromatography (TLC), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA), gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry (CE-MS), liquid chromatography-mass spectrometry (LC-MS), liquid chromatography-electrochemistry-mass spectrometry (LC-EC-MS), NMR, LC-NMR, direct infusion mass spectrometry (DIMS), and Fourier-transform infrared (FT-IR), etc. [16,25,43,45,46]. Of the abovementioned techniques, NMR, GC-MS, LC-MS, and CE-MS are the most widely used technologies today [24,45,[47][48][49][50]. Selection of the most suitable technology is based on speed, selectivity, sensitivity, and accuracy. ...
... The use of NMR in metabolomics has opened the areas of biochemistry and phytochemical analysis [47,52]. It is an unbiased, rapid, non-destructive technique that requires little sample preparation [48]. ...
Metabolomics is an essential technology for functional genomics and systems biology. It plays a key role in functional annotation of genes and understanding towards cellular and molecular, biotic and abiotic stress responses. Different analytical techniques are used to extend the coverage of a full metabolome. The commonly used techniques are NMR, CE-MS, LC-MS, and GC-MS. The choice of a suitable technique depends on the speed, sensitivity, and accuracy. This chapter provides insight into plant metabolomic techniques, databases used in the analysis, data mining and processing, compound identification, and limitations in metabolomics. It also describes the workflow of measuring metabolites in plants. Metabolomic studies in plant responses to stress are a key research topic in many laboratories worldwide. We summarize different approaches and provide a generic overview of stress responsive metabolite markers and processes compiled from a broad range of different studies.
... Sample preparation for solubilized cell-wall components from F. hygrometrica cells was like that described in previously published reports for land plants and macroalgae [23][24][25]. Sample solutions (4:1 dimethyl sulphoxide (DMSO)-d 6 :pyridine-d 5 ) were transferred into 5-mm ϕ NMR tubes and subjected to NMR analysis. The temperature of all NMR samples was maintained at 298 K. ...
Water contamination by heavy metals from industrial activities is a serious environmental concern. To mitigate heavy metal toxicity and to recover heavy metals for recycling, biomaterials used in phytoremediation and bio-sorbent filtration have recently drawn renewed attention. The filamentous protonemal cells of the moss Funaria hygrometrica can hyperaccumulate lead (Pb) up to 74% of their dry weight when exposed to solutions containing divalent Pb. Energy-dispersive X-ray spectroscopy revealed that Pb is localized to the cell walls, endoplasmic reticulum-like membrane structures, and chloroplast thylakoids, suggesting that multiple Pb retention mechanisms are operating in living F. hygrometrica. The main Pb-accumulating compartment was the cell wall, and prepared cell-wall fractions could also adsorb Pb. Nuclear magnetic resonance analysis showed that polysaccharides composed of polygalacturonic acid and cellulose probably serve as the most effective Pb-binding components. The adsorption abilities were retained throughout a wide range of pH values, and bound Pb was not desorbed under conditions of high ionic strength. In addition, the moss is highly tolerant to Pb. These results suggest that the moss F. hygrometrica could be a useful tool for the mitigation of Pb-toxicity in wastewater.
... The acquired spectra were manually phased and baseline-corrected. Two-dimensional (2D) 1 H-13 C-HSQC) spectra were recorded on a Bruker DRU-700 NMR spectrometer equipped with a 1 H inverse cryogenically cooled probe with a z-axis gradient as previously described [47][48][49][50] . All NMR spectra were processed using NMRPipe software 51 and assigned using the SpinAssign program on the PRIMe website 52,53 . ...
There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance (1 H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.
... After approximately 30 additional days, the rooted poplars were transferred to a container containing MS medium for plant culture (Combiness, Nazareth, Belgium). Stable isotope labeling of poplars using the above growing system was conducted using previously described methods 38,42 . The poplars were grown in the plant culture until they reached a height of approximately 10 cm, i.e., 35 days. ...
Lignocellulose, which includes mainly cellulose, hemicellulose, and lignin, is a potential resource for the production of chemicals and for other applications. For effective production of materials derived from biomass, it is important to characterize the metabolites and polymeric components of the biomass. Nuclear magnetic resonance (NMR) spectroscopy has been used to identify biomass components; however, the NMR spectra of metabolites and lignocellulose components are ambiguously assigned in many cases due to overlapping chemical shift peaks. Using our (13)C-labeling technique in higher plants such as poplar samples, we demonstrated that overlapping peaks could be resolved by three-dimensional NMR experiments to more accurately assign chemical shifts compared with two-dimensional NMR measurements. Metabolites of the (13)C-poplar were measured by high-resolution magic angle spinning NMR spectroscopy, which allows sample analysis without solvent extraction, while lignocellulose components of the (13)C-poplar dissolved in dimethylsulfoxide/pyridine solvent were analyzed by solution-state NMR techniques. Using these methods, we were able to unambiguously assign chemical shifts of small and macromolecular components in (13)C-poplar samples. Furthermore, using samples of less than 5 mg, we could differentiate between two kinds of genes that were overexpressed in poplar samples, which produced clearly modified plant cell wall components.
... 21 Advantages of the 13 C-labeling method also include the characterization of compounds in complex components, the determination of compound structures, and the tracking of microbial metabolic pathways using NMR or other analytical techniques. 20,21 We have previously successfully performed 13 C-labeling in plants 22,23 and microbial systems, 24 as well as metabolic profiling using two-and three-dimensional NMR techniques. 25−29 NMR-based metabolic profiling is helpful but not enough for evaluation of microbial community variations in microbial ecosystem. ...
A new metabolic dynamics analysis approach has been developed in which massive data sets from time-series of (1)H- and (13)C-NMR spectra are integrated in combination with microbial variability to characterize the biomass degradation process using field soil microbial communities. Based on correlation analyses that revealed relationships between various metabolites and bacteria, we efficiently monitored the metabolic dynamics of saccharides, amino acids, and organic acids, by assessing time-course changes in the microbial and metabolic profiles during biomass degradation. Specific bacteria were found to support specific steps of metabolic pathways in the degradation process of biomass to short chain fatty acids. We evaluated samples from agricultural and abandoned fields contaminated by the tsunami that followed the Great East earthquake in Japan. Metabolic dynamics and activities in the biomass degradation process differed considerably between soil from agricultural and abandoned fields. In particular, production levels of short chain fatty acids, such as acetate and propionate, which were considered to be produced by soil bacteria such as Sedimentibacter sp. and Coprococcus sp., were higher in the soil from agricultural fields than from abandoned fields. Our approach could characterize soil activity based on the metabolic dynamics of microbial communities in the biomass degradation process and should therefore be useful in future investigations of the environmental effects of natural disasters on soils.
... The two-dimensional (2D) 1 H-13 C heteronuclear single quantum coherence (HSQC) method for NMR measurements has been described previously. [20][21][22] Briefly, a total of 128 complex f1 ( 13 C) and 2048 complex f2 ( 1 H) points were recorded from 24 scans per f1 increment. The obtained spectral widths were 150 and 14 p.p.m. for f1 and f2, respectively, and the NMR spectra was processed using NMRPipe software (http://spin.niddk.nih.gov/NMRPipe/). ...
