Analysis of the compartmentation of glycolytic intermediates, nucleotides, sugars, organic acids, amino acids, and sugar alcohols in potato tubers using a nonaqueous fractionation method

The compartmentation of metabolism in heterotrophic plant tissues is poorly understood due to the lack of data on metabolite distributions and fluxes between subcellular organelles. The main reason for this is the lack of suitable experimental methods with which intracellular metabolism can be measured. Here, we describe a nonaqueous fractionation method that allows the subcellular distributions of metabolites in developing potato (Solanum tuberosum L. cv Desiree) tubers to be calculated. In addition, we have coupled this fractionation method to a recently described gas chromatography-mass spectrometry procedure that allows the measurement of a wide range of small metabolites. To calculate the subcellular metabolite concentrations, we have analyzed organelle volumes in growing potato tubers using electron microscopy. The relative volume distributions in tubers are very similar to the ones for source leaves. More than 60% of most sugars, sugar alcohols, organic acids, and amino acids were found in the vacuole, although the concentrations of these metabolites is often higher in the cytosol. Significant amounts of the substrates for starch biosynthesis, hexose phosphates, and ATP were found in the plastid. However, pyrophosphate was located almost exclusively in the cytosol. Calculation of the mass action ratios of sucrose synthase, UDP-glucose pyrophosphorylase, phosphoglucosisomerase, and phosphoglucomutase indicate that these enzymes are close to equilibrium in developing potato tubers. However, due to the low plastidic pyrophosphate concentration, the reaction catalyzed by ADP-glucose pyrophosphorylase was estimated to be far removed from equilibrium.     

Metabolic source isotopic pair labeling and genome-wide association are complementary tools for the identification of metabolite–gene associations in plants

The optimal extraction of information from untargeted metabolomics analyses is a continuing challenge. Here, we describe an approach that combines stable isotope labeling, liquid chromatography– mass spectrometry (LC–MS), and a computational pipeline to automatically identify metabolites produced from a selected metabolic precursor. We identified the subset of the soluble metabolome generated from phenylalanine (Phe) in Arabidopsis thaliana, which we refer to as the Phe-derived metabolome (FDM) In addition to identifying Phe-derived metabolites present in a single wild-type reference accession, the FDM was established in nine enzymatic and regulatory mutants in the phenylpropanoid pathway. To identify genes associated with variation in Phe-derived metabolites in Arabidopsis, MS features collected by untargeted metabolite profiling of an Arabidopsis diversity panel were retrospectively annotated to the FDM and natural genetic variants responsible for differences in accumulation of FDM features were identified by genome-wide association. Large differences in Phe-derived metabolite accumulation and presence/absence variation of abundant metabolites were observed in the nine mutants as well as between accessions from the diversity panel. Many Phe-derived metabolites that accumulated in mutants also accumulated in non-Col-0 accessions and was associated to genes with known or suspected functions in the phenylpropanoid pathway as well as genes with no known functions. Overall, we show that cataloguing a biochemical pathway’s products through isotopic labeling across genetic variants can substantially contribute to the identification of metabolites and genes associated with their biosynthesis.

An isotopic labeling and LC–MS pipeline to identify metabolites produced from Phe and its integration with genome-wide association identifies genes associated with the phenylpropanoid pathway.     

Profiling of Arabidopsis secondary metabolites by capillary liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry

Large-scale metabolic profiling is expected to develop into an integral part of functional genomics and systems biology. The metabolome of a cell or an organism is chemically highly complex. Therefore, comprehensive biochemical phenotyping requires a multitude of analytical techniques. Here, we describe a profiling approach that combines separation by capillary liquid chromatography with the high resolution, high sensitivity, and high mass accuracy of quadrupole time-of-flight mass spectrometry. About 2000 different mass signals can be detected in extracts of Arabidopsis roots and leaves. Many of these originate from Arabidopsis secondary metabolites. Detection based on retention times and exact masses is robust and reproducible. The dynamic range is sufficient for the quantification of metabolites. Assessment of the reproducibility of the analysis showed that biological variability exceeds technical variability. Tools were optimized or established for the automatic data deconvolution and data processing. Subtle differences between samples can be detected as tested with the chalcone synthase deficient tt4 mutant. The accuracy of time-of-flight mass analysis allows to calculate elemental compositions and to tentatively identify metabolites. In-source fragmentation and tandem mass spectrometry can be used to gain structural information. This approach has the potential to significantly contribute to establishing the metabolome of Arabidopsis and other model systems. The principles of separation and mass analysis of this technique, together with its sensitivity and resolving power, greatly expand the range of metabolic profiling.     

Analysis of metabolite profile data using batch-learning self-organizing maps

Novel tools are needed for efficient analysis and visualization of the massive data sets associated with metabolomics. Here, we describe a batch-learning self-organizing map (BL-SOM) for metabolome informatics that makes the learning process and resulting map independent of the order of data input. This approach was successfully used in analyzing and organizing the metabolome data forArabidopsis thaliana cells cultured under salt stress. Our 6 × 4 matrix presented patterns of metabolite levels at different time periods. A negative correlation was found between the levels of amino acids and metabolites related to glycolysis metabolism in response to this stress. Therefore, BL-SOM could be an excellent tool for clustering and visualizing high dimensional, complex metabolome data in a single map.     

Changes in the uterine metabolome of the cow during the first 7 days after estrus

The uterine microenvironment during the first 7 days after ovulation accommodates and facilitates sperm transit to the oviduct and constitutes the sole source of nutrients required for the development of preimplantation embryos. Knowledge of the composition of uterine fluid is largely incomplete. Using untargeted mass spectrometry, we characterized the uterine metabolome during the first 7 days of the estrous cycle. Bovine uteri were collected on Days 0 (N = 4), 3 ( N = 4), 5 ( N = 3), and 7 ( N = 4) relative to ovulation and flushed with Dulbecco’s phosphate‐buffered saline. A total of 1,993 molecular features were detected of which 184 peaks with putative identification represent 147 unique metabolites, including amino acids, benzoic acids, lipid molecules, carbohydrates, purines, pyrimidines, vitamins, and other intermediate and secondary metabolites. Results revealed changes in the uterine metabolome as the cow transitions from ovulation to Day 7 of the estrous cycle. The majority of metabolites that changed with day reached maximum intensity on either Day 5 or 7 relative to ovulation. Moreover, several metabolites found in the uterine fluid have signaling capabilities and some have been shown to affect preimplantation embryonic development. In conclusion, the metabolome of the bovine uterus changes during early stages of the estrous cycle and is likely to participate in the regulation of preimplantation embryonic development. Data reported here will serve as the basis for future studies aiming to evaluate maternal regulation of preimplantation embryonic development and optimal conditions for the culture of embryos.     

Microbial metabolomics: toward a platform with full metabolome coverage

Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.     

The human cerebrospinal fluid metabolome

With continuing improvements in analytical technology and an increased interest in comprehensive metabolic profiling of biofluids and tissues, there is a growing need to develop comprehensive reference resources for certain clinically important biofluids, such as blood, urine and cerebrospinal fluid (CSF). As part of our effort to systematically characterize the human metabolome we have chosen to characterize CSF as the first biofluid to be intensively scrutinized. In doing so, we combined comprehensive NMR, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC) Fourier transform-mass spectrometry (FTMS) methods with computer-aided literature mining to identify and quantify essentially all of the metabolites that can be commonly detected (with today's technology) in the human CSF metabolome. Tables containing the compounds, concentrations, spectra, protocols and links to disease associations that we have found for the human CSF metabolome are freely available at http://www.csfmetabolome.ca.     

Exploring the Arabidopsis sulfur metabolome

Sulfur plays a crucial role in protein structure and function, redox status and plant biotic stress responses. However, our understanding of sulfur metabolism is limited to identified pathways. In this study, we used a high‐resolution Fourier transform mass spectrometric approach in combination with stable isotope labeling to describe the sulfur metabolome of Arabidopsis thaliana. Databases contain roughly 300 sulfur compounds assigned to Arabidopsis. In comparative analyses, we showed that the overlap of the expected sulfur metabolome and the mass spectrometric data was surprisingly low, and we were able to assign only 37 of the 300 predicted compounds. By contrast, we identified approximately 140 sulfur metabolites that have not been assigned to the databases to date. We used our method to characterize the γ‐glutamyl transferase mutant ggt4‐1, which is involved in the vacuolar breakdown of glutathione conjugates in detoxification reactions. Although xenobiotic substrates are well known, only a few endogenous substrates have been described. Among the specifically altered sulfur‐containing masses in the ggt4‐1 mutant, we characterized one endogenous glutathione conjugate and a number of further candidates for endogenous substrates. The small percentage of predicted compounds and the high proportion of unassigned sulfur compounds identified in this study emphasize the need to re‐evaluate our understanding of the sulfur metabolome.     

Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies

We have developed a metabolic profiling scheme based on direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS). The scheme consists of: (1) reproducible data collection under optimized FT-ICR/MS analytical conditions; (2) automatic mass-error correction and multivariate analyses for metabolome characterization using a newly developed metabolomics tool (DMASS software); (3) identification of marker metabolite candidates by searching a species-metabolite relationship database, KNApSAcK; and (4) structural analyses by an MS/MS method. The scheme was applied to metabolic phenotyping of Arabidopsis (Arabidopsis thaliana) seedlings treated with different herbicidal chemical classes for pathway-specific inhibitions. Arabidopsis extracts were directly infused into an electrospray ionization source on an FT-ICR/MS system. Acquired metabolomics data were comprised of mass-to-charge ratio values with ion intensity information subjected to principal component analysis, and metabolic phenotypes from the herbicide treatments were clearly differentiated from those of the herbicide-free treatment. From each herbicide treatment, candidate metabolites representing such metabolic phenotypes were found through the KNApSAcK database search. The database search and MS/MS analyses suggested dose-dependent accumulation patterns of specific metabolites including several flavonoid glycosides. The metabolic phenotyping scheme on the basis of FT-ICR/MS coupled with the DMASS program is discussed as a general tool for high throughput metabolic phenotyping studies.     

Metabolome and water homeostasis analysis of Thellungiella salsuginea suggests that dehydration tolerance is a key response to osmotic stress in this halophyte

Thellungiella salsuginea, a Brassicaceae species closely related to Arabidopsis thaliana, is tolerant to high salinity. The two species were compared under conditions of osmotic stress to assess the relationships between stress tolerance, the metabolome, water homeostasis and growth performance. A broad range of metabolites were analysed by metabolic fingerprinting and profiling, and the results showed that, despite a few notable differences in raffinose and secondary metabolites, the same metabolic pathways were regulated by salt stress in both species. The main difference was quantitative: Thellungiella had much higher levels of most metabolites than Arabidopsis whatever the treatment. Comprehensive quantification of organic and mineral solutes showed a relative stability of the total solute content regardless of the species or treatment, meaning that little or no osmotic adjustment occurred under stress. The reduction in osmotic potential observed in plants under stress was found to result from a passive loss of water. Thellungiella shoots contain less water than Arabidopsis shoots, and have the ability to lose more water, which could contribute to maintain a water potential gradient between soil and plant. Significant differences between Thellungiella and Arabidopsis were also observed in terms of the physicochemical properties of their metabolomes, such as water solubility and polarity. On the whole, the Thellungiella metabolome appears to be more compatible with dehydration. Osmotic stress was also found to impact the metabolome properties in both species, increasing the overall polarity. Together, the results suggest that Thellungiella copes with osmotic stress by tolerating dehydration, with its metabolic configuration lending itself to osmoprotective strategies rather than osmo-adjustment.     

Induced Pluripotent Stem Cells Show Metabolomic Differences to Embryonic Stem Cells in Polyunsaturated Phosphatidylcholines and Primary Metabolism

Induced pluripotent stem cells are different from embryonic stem cells as shown by epigenetic and genomics analyses. Depending on cell types and culture conditions, such genetic alterations can lead to different metabolic phenotypes which may impact replication rates, membrane properties and cell differentiation. We here applied a comprehensive metabolomics strategy incorporating nanoelectrospray ion trap mass spectrometry (MS), gas chromatography-time of flight MS, and hydrophilic interaction- and reversed phase-liquid chromatography-quadrupole time-of-flight MS to examine the metabolome of induced pluripotent stem cells (iPSCs) compared to parental fibroblasts as well as to reference embryonic stem cells (ESCs). With over 250 identified metabolites and a range of structurally unknown compounds, quantitative and statistical metabolome data were mapped onto a metabolite networks describing the metabolic state of iPSCs relative to other cell types. Overall iPSCs exhibited a striking shift metabolically away from parental fibroblasts and toward ESCs, suggestive of near complete metabolic reprogramming. Differences between pluripotent cell types were not observed in carbohydrate or hydroxyl acid metabolism, pentose phosphate pathway metabolites, or free fatty acids. However, significant differences between iPSCs and ESCs were evident in phosphatidylcholine and phosphatidylethanolamine lipid structures, essential and non-essential amino acids, and metabolites involved in polyamine biosynthesis. Together our findings demonstrate that during cellular reprogramming, the metabolome of fibroblasts is also reprogrammed to take on an ESC-like profile, but there are select unique differences apparent in iPSCs. The identified metabolomics signatures of iPSCs and ESCs may have important implications for functional regulation of maintenance and induction of pluripotency.     

Metabolome Analysis of Arabidopsis thaliana Roots Identifies a Key Metabolic Pathway for Iron Acquisition

Fe deficiency compromises both human health and plant productivity. Thus, it is important to understand plant Fe acquisition strategies for the development of crop plants which are more Fe-efficient under Fe-limited conditions, such as alkaline soils, and have higher Fe density in their edible tissues. Root secretion of phenolic compounds has long been hypothesized to be a component of the reduction strategy of Fe acquisition in non-graminaceous plants. We therefore subjected roots of Arabidopsis thaliana plants grown under Fe-replete and Fe-deplete conditions to comprehensive metabolome analysis by gas chromatography-mass spectrometry and ultra-pressure liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry. Scopoletin and other coumarins were found among the metabolites showing the strongest response to two different Fe-limited conditions, the cultivation in Fe-free medium and in medium with an alkaline pH. A coumarin biosynthesis mutant defective in ortho-hydroxylation of cinnamic acids was unable to grow on alkaline soil in the absence of Fe fertilization. Co-cultivation with wild-type plants partially rescued the Fe deficiency phenotype indicating a contribution of extracellular coumarins to Fe solubilization. Indeed, coumarins were detected in root exudates of wild-type plants. Direct infusion mass spectrometry as well as UV/vis spectroscopy indicated that coumarins are acting both as reductants of Fe(III) and as ligands of Fe(II).     

Metabolomics – an overview. From basic principles to potential biomarkers (part 2)

The metabolome, which represents the complete set of molecules (metabolites) of a biological sample (cell, tissue, organ, organism), is the final downstream product of the metabolic cell process that involves the genome and exogenous sources. The metabolome is characterized by a large number of small molecules with a huge diversity of chemical structures and abundances. Exploring the metabolome requires complementary analytical platforms to reach its extensive coverage. The metabolome is continually evolving, reflecting the continuous flux of metabolic and signaling pathways. Metabolomic research aims to study the biochemical processes by detecting and quantifying metabolites to obtain a metabolic picture able to give a functional readout of the physiological state. Recent advances in mass spectrometry (one of the mostly used technologies for metabolomics studies) have given the opportunity to determine the spatial distribution of metabolites in tissues. In a two-part article, we describe the usual metabolomics technologies, workflows and strategies leading to the implementation of new clinical biomarkers. In this second part, we first develop the steps of a metabolomic analysis from sample collection to biomarker validation. Then with two examples, autism spectrum disorders and Alzheimer's disease, we illustrate the contributions of metabolomics to clinical practice. Finally, we discuss the complementarity of in vivo (positron emission tomography) and in vitro (metabolomics) molecular explorations for biomarker research.     

Proton-driven sucrose symport and antiport are provided by the vacuolar transporters SUC4 and TMT1/2

The vacuolar membrane is involved in solute uptake into and release from the vacuole, which is the largest plant organelle. In addition to inorganic ions and metabolites, large quantities of protons and sugars are shuttled across this membrane. Current models suggest that the proton gradient across the membrane drives the accumulation and/or release of sugars. Recent studies have associated AtSUC4 with the vacuolar membrane. Some members of the SUC family are plasma membrane proton/sucrose symporters. In addition, the sugar transporters TMT1 and TMT2, which are localized to the vacuolar membrane, have been suggested to function in proton-driven glucose antiport. Here we used the patch-clamp technique to monitor carrier-mediated sucrose transport by AtSUC4 and AtTMTs in intact Arabidopsis thaliana mesophyll vacuoles. In the whole-vacuole configuration with wild-type material, cytosolic sucrose-induced proton currents were associated with a proton/sucrose antiport mechanism. To identify the related transporter on one hand, and to enable the recording of symporter-mediated currents on the other hand, we electrophysiologically characterized vacuolar proteins recognized by Arabidopsis mutants of partially impaired sugar compartmentation. To our surprise, the intrinsic sucrose/proton antiporter activity was greatly reduced when vacuoles were isolated from plants lacking the monosaccharide transporter AtTMT1/TMT2. Transient expression of AtSUC4 in this mutant background resulted in proton/sucrose symport activity. From these studies, we conclude that, in the natural environment within the Arabidopsis cell, AtSUC4 most likely catalyses proton-coupled sucrose export from the vacuole. However, TMT1/2 probably represents a proton-coupled antiporter capable of high-capacity loading of glucose and sucrose into the vacuole.     

Effect of benzothiadiazole on the metabolome of Arabidopsis thaliana

Benzothiadiazole (BTH) is a functional analog of the plant endogenous hormone-like compound, salicylic acid (SA), which is required for the induction of plant defense genes leading to systemic acquired resistance (SAR). Previous molecular and genetic studies have suggested that BTH itself might potentiate SAR resulting in the induction of several pathogenesis-related (PR) genes. However, the changes in the metabolome, which occur as a result of BTH-treatment, remain unclear. In this study, metabolic alterations in BTH-treated Arabidopsis thaliana were investigated using nuclear magnetic resonance (NMR) spectroscopy followed by multivariate data analyses such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Both PCA and PLS-DA show that increase of glucose, glutamine, inositol, malic acid, sucrose, and threonine as well as BTH and its degraded metabolites contribute to the clear discrimination of the metabolome of BTH-treated Arabidopsis from control plants. However, the levels of phenolic metabolites, which have generally been observed to be induced by other signaling molecules were significantly reduced in BTH-treated Arabidopsis. In addition to these changes due to BTH-treatment, it was also found that the EtOH used as a solvent in this treatment may per se act as an inducer of the accumulation of a flavonoid.     

The Bovine Ruminal Fluid Metabolome

The rumen is a unique organ that serves as the primary site for microbial fermentation of ingested plant material for domestic livestock such as cattle, sheep and goats. The chemical composition of ruminal fluid is thought to closely reflect the healthy/unhealthy interaction between rumen microflora and diet. Just as diet and feed quality is important for livestock production, rumen health is also critical to the growth and production of high quality milk and meat. Therefore a detailed understanding of the chemical composition of ruminal fluid and the influence of diet on its composition could help improve the efficiency and effectiveness of farming and veterinary practices. Consequently we have undertaken an effort to comprehensively characterize the bovine ruminal fluid metabolome. In doing so, we combined NMR spectroscopy, inductively coupled plasma mass-spectroscopy (ICP-MS), gas chromatography-mass spectrometry (GC-MS), direct flow injection (DFI) mass spectrometry and lipidomics with computer-aided literature mining to identify and quantify essentially all of the metabolites in bovine ruminal fluid that can be routinely detected (with today’s technology). The use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these techniques. Tables containing the set of 246 ruminal fluid metabolites or metabolite species, their concentrations, related literature reference and links to their known diet associations for the bovine rumen metabolome are freely available at http://www.rumendb.ca.     

State-of-the-art non-targeted metabolomics in the study of chronic kidney disease

Here we report a metabolomics discovery study conducted on blood serum samples of patients in different stages of chronic kidney disease (CKD). Metabolites were monitored on a quality controlled holistic platform combining reversed-phase liquid chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry in both negative and positive ionization mode and gas chromatography coupled to quadrupole mass spectrometry. A substantial portion of the serum metabolome was thereby covered. Eighty-five metabolites were shown to evolve with CKD progression of which 43 metabolites were a confirmation of earlier reported uremic retention solutes and/or uremic toxins. Thirty-one unique metabolites were revealed which were increasing significantly throughout CKD progression, by a factor surpassing the level observed for creatinine, the currently used biomarker for kidney function. Additionally, 11 unique metabolites showed a decreasing trend.     

Metabolomics approach for investigation of effects of dengue virus infection using the EA.hy926 cell line

This paper describes a multiplatform analytical approach combining proton nuclear magnetic resonance ((1)H NMR) spectroscopy and mass spectrometry (MS), together with pattern recognition tools in a metabolomic study used to investigate the effects of dengue virus infection. The four serotypes of dengue, DEN-1, DEN-2, DEN-3, and DEN-4, were inoculated into the EA.hy926 cell line, which was then incubated for various time intervals. Principal component analysis (PCA) of the (1)H NMR and MS data revealed metabolic profile patterns or fingerprint patterns that can be attributed to specific virus serotypes. Distinct effects of infection by each serotype were demonstrated, and these differences were attributed to changes in levels of metabolites (including amino acids, dicarboxylic acids, fatty acids, and organic acids related to the tricarboxylic acid (TCA) cycle). The study demonstrated application of metabolomics to improve understanding of the effect of dengue infection on endothelial cells' metabolome.     

伞裙追寄蝇滞育关联基因和滞育关联代谢物的联合分析

为探索伞裙追寄蝇蛹滞育调控的分子机制,本文对伞裙追寄蝇Exorista civilis滞育蛹和非滞育蛹进行转录组测序以及代谢组检测,鉴定其关键的滞育关联基因(diapause-associated genes, DEGs)和滞育关联代谢物(diapasuse-associated metabolites, DEMs)。本研究基于高通量测序以及液质联用技术,通过筛选,在转录组中获得了差异表达基因7 513个,在代谢组中,获得差异代谢物501个,其中氨基酸占比最多。将所有差异表达基因与差异表达代谢物同时向KEGG映射,获得两者共同的pathway信息,明确差异表达基因与差异代谢物共同参与的主要生化途径和信号转导途径。本研究通过转录组和代谢组的联合分析,在正、负离子模式下,差异表达基因与差异代谢物共同富集到70条通路。在负离子模式下,滞育关联因子主要参与氨基酸代谢和神经系统;在正离子模式下,滞育关联因子主要参与消化系统和信号转导途径。本研究重点分析了柠檬酸循环、cAMP信号通路、氨酰-tRNA的生物合成,将为进一步深入研究伞裙追寄蝇滞育调控的分子机制奠定理论基础。