1H NMR metabolite fingerprinting and metabolomic analysis of perchloric acid extracts from plant tissues

Metabolome guided treasure hunt - learning from metabolic diversity

Metabolomics is a rapidly evolving field focused on the comprehensive identification and quantification of small molecules in biological systems. As the final layer of the biological hierarchy following of the genome, transcriptome and proteome, it presents a dynamic snapshot of phenotype, influenced by genetic, environmental and physiological factors. Whilst the metabolome sits downstream of genes and proteins, there are multiple higher levels-tissues, organs, the entire organism, and interactions with other organisms, which need to be considered in order to fully comprehend organismal biology. Advances in metabolomics continue to expand its applications in plant biology, biotechnology, and natural product discovery unlocking many of nature's most beneficial colors, tastes, nutrients and medicines. Flavonoids and other specialized metabolites are essential for plant defense against oxidative stress and function as key phytonutrients for human health. Recent advancements in gene-editing and metabolic engineering have significantly improved the nutritional value and flavor of crop plants. Here we highlight how advanced metabolic analysis is driving improvements in crops uncovering genes that influence nutrient and flavor profile and plant derived compounds with medicinal potential.

High-performance ratiometric fluorescent probe for rapid, visual and ultrasensitive monitoring/bioimaging of hypochlorite in real-life samples and living systems

Hypochlorite (ClO-) is a highly reactive chemical extensively used in households, public areas, and various industries due to its multiple functions of disinfection, bleaching, and sterilization. However, overuse of ClO- may contaminate the water, soil, air and food, leading to negative impacts on the environments, ecosystems and food safety. Meanwhile, excessive ClO- in human body can also cause severe damage to the immune system. Thus, the development of effective and precise detection tools for ClO- is of great significance to better understand its complicated roles in environments and biosystems. Herein, a new high-performance ratiometric fluorescent probe 2-amino-3-((10-propyl-10H-phenothiazin-3-yl)methylene)-amino)maleonitrile (PD) was developed for effective detection of ClO- in various bio/environmental and food samples. Probe PD exhibits highly-specific "ratiometric" fluorescent response to ClO- with rapid response (< 1 min), excellent sensitivity (detection limit, 47.4 nM), wide applicable pH range (4 -12), and excellent versatility in practical applications. In practical applications, PD enables the sensitive and quantitative detection of ClO- levels in various water samples, bio-fluids, dairy products, fruits and vegetables with high-precision (recoveries, 97.00 -104.40 %), as well as the successful application for visual tracking ClO- in fresh fruits and vegetables. Furthermore, test strips containing PD offer a visual and convenient tool for quick identification of ClO- in aqueous media by the naked eye. Importantly, the good biocompatibility of PD enables its practical applications in real-time bioimaging of endogenous/exogenous ClO- levels in living cells, bacteria, onion cells, Arabidopsis, as well as zebrafish. This study provided an effective method for visual monitoring and bioimaging of ClO- levels in various environments, foods and living biosystems.

Sample Preparation from Plant Tissue for Gas Chromatography-Mass Spectrometry (GC-MS)we

Metabolites are intermediate products formed during metabolism. Metabolites play different roles, including providing energy, supporting structure, transmitting signals, catalyzing reactions, enhancing defense, and interacting with other species. Plant metabolomics research aims to detect precisely all metabolites found within tissues of plants through GC-MS. This chapter primarily focuses on extracting metabolites using chemicals such as methanol, chloroform, ribitol, MSTFA, and TMCS. The metabolic analysis method is frequently used according to the specific kind of sample or matrix being investigated and the analysis objective. Chromatography (LC, GC, and CE) with mass spectrometry and NMR spectroscopy is used in modern metabolomics to analyze metabolites from plant samples. The most frequently used method for metabolites analysis is the GC-MS. It is a powerful technique that combines gas chromatography's separation capabilities with mass spectrometry, offering detailed information, including structural identification of each metabolite. This chapter contains an easy-to-follow guide to extract plant-based metabolites. The current protocol provides all the information needed for extracting metabolites from a plant, precautions, and troubleshooting.

Metabolomics-Based Mechanistic Insights into Revealing the Adverse Effects of Pesticides on Plants: An Interactive Review

In plant biology, metabolomics is often used to quantitatively assess small molecules, metabolites, and their intermediates in plants. Metabolomics has frequently been applied to detect metabolic alterations in plants exposed to various biotic and abiotic stresses, including pesticides. The widespread use of pesticides and agrochemicals in intensive crop production systems is a serious threat to the functionality and sustainability of agroecosystems. Pesticide accumulation in soil may disrupt soil-plant relationships, thereby posing a pollution risk to agricultural output. Application of metabolomic techniques in the assessment of the biological consequences of pesticides at the molecular level has emerged as a crucial technique in exposome investigations. State-of-the-art metabolomic approaches such as GC-MS, LC-MS/MS UHPLC, UPLC-IMS-QToF, GC/EI/MS, MALDI-TOF MS, and ¹H-HR-MAS NMR, etc., investigating the harmful effects of agricultural pesticides have been reviewed. This updated review seeks to outline the key uses of metabolomics related to the evaluation of the toxicological impacts of pesticides on agronomically important crops in exposome assays as well as bench-scale studies. Overall, this review describes the potential uses of metabolomics as a method for evaluating the safety of agricultural chemicals for regulatory applications. Additionally, the most recent developments in metabolomic tools applied to pesticide toxicology and also the difficulties in utilizing this approach are discussed.

Epitranscriptome changes triggered by ammonium nutrition regulate the proteome response of maritime pine roots

Epitranscriptome constitutes a gene expression checkpoint in all living organisms. Nitrogen is an essential element for plant growth and development that influences gene expression at different levels such as epigenome, transcriptome, proteome, and metabolome. Therefore, our hypothesis is that changes in the epitranscriptome may regulate nitrogen metabolism. In this study, epitranscriptomic modifications caused by ammonium nutrition were monitored in maritime pine roots using Oxford Nanopore Technology. Transcriptomic responses mainly affected transcripts involved in nitrogen and carbon metabolism, defense, hormone synthesis/signaling, and translation. Global detection of epitranscriptomic marks was performed to evaluate this posttranscriptional mechanism in un/treated seedlings. Increased N⁶-methyladenosine (m⁶A) deposition in the 3'-UTR was observed in response to ammonium, which seems to be correlated with poly(A) lengths and changes in the relative abundance of the corresponding proteins. The results showed that m⁶A deposition and its dynamics seem to be important regulators of translation under ammonium nutrition. These findings suggest that protein translation is finely regulated through epitranscriptomic marks likely by changes in mRNA poly(A) length, transcript abundance and ribosome protein composition. An integration of multiomics data suggests that the epitranscriptome modulates responses to nutritional, developmental and environmental changes through buffering, filtering, and focusing the final products of gene expression.

Cellular Lactate Spectroscopy Using 1.5 Tesla Clinical Apparatus

Cellular lactate is a key cellular metabolite and marker of anaerobic glycolysis. Cellular lactate uptake, release, production from glucose and glycogen, and interconversion with pyruvate are important determinants of cellular energy. It is known that lactate is present in the spectrum of neoplasms and low malignancy (without necrotic lesions). Also, the appearance of lactate signals is associated with anaerobic glucose, mitochondrial dysfunction, and other inflammatory responses. The aim of this study was the detection of lactate in cell cultures with the use of proton magnetic resonance (¹H MRS) and a 1.5 Tesla clinical apparatus (MR OPTIMA 360), characterized as a medium-field system. In this study, selected metabolites, together with cellular lactate, were identified with the use of an appropriate protocol and management algorithm. This paper describes the results obtained for cancer cell cultures. This medium-field system has proven the possibility of detecting small molecules, such as lactate, with clinical instruments. ¹H MRS performed using clinical MR apparatus is a useful tool for clinical analysis.

Metabolite Fingerprinting Based on 1H-NMR Spectroscopy and Liquid Chromatography for the Authentication of Herbal Products

Herbal medicines (HMs) are regarded as one of the traditional medicines in health care to prevent and treat some diseases. Some herbal components such as turmeric and ginger are used as HMs, therefore the identification and confirmation of herbal use are very necessary. In addition, the adulteration practice, mainly motivated to gain economical profits, may occur by substituting the high price of HMs with lower-priced ones or by addition of certain chemical constituents known as Bahan Kimia Obat (chemical drug ingredients) in Indonesia. Some analytical methods based on spectroscopic and chromatographic methods are developed for the authenticity and confirmation of the HMs used. Some approaches are explored during HMs authentication including single-component analysis, fingerprinting profiles, and metabolomics studies. The absence of reference standards for certain chemical markers has led to exploring the fingerprinting approach as a tool for the authentication of HMs. During fingerprinting-based spectroscopic and chromatographic methods, the data obtained were big, therefore the use of chemometrics is a must. This review highlights the application of fingerprinting profiles using variables of spectral and chromatogram data for authentication in HMs. Indeed, some chemometrics techniques, mainly pattern recognition either unsupervised or supervised, were applied for this purpose.

Metabolism-mediated mechanisms underpin the differential stomatal speediness regulation among ferns and angiosperms

Recent results suggest that metabolism-mediated stomatal closure mechanisms are important to regulate differentially the stomatal speediness between ferns and angiosperms. However, evidence directly linking mesophyll metabolism and the slower stomatal conductance (g_s ) in ferns is missing. Here, we investigated the effect of exogenous application of abscisic acid (ABA), sucrose and mannitol on stomatal kinetics and carried out a metabolic fingerprinting analysis of ferns and angiosperms leaves harvested throughout a diel course. Fern stomata did not respond to ABA in the time period analysed. No differences in the relative decrease in g_s was observed between ferns and the angiosperm following provision of sucrose or mannitol. However, ferns have slower g_s responses to these compounds than angiosperms. Metabolomics analysis highlights that ferns have a higher accumulation of secondary rather than primary metabolites throughout the diel course, with the opposite being observed in angiosperms. Our results indicate that metabolism-mediated stomatal closure mechanisms underpin the differential stomatal speediness regulation among ferns and angiosperms, in which the slower stomatal closure in ferns is associated with the lack of ABA-responsiveness, to a reduced capacity to respond to mesophyll-derived sucrose and to a higher carbon allocation toward secondary metabolism, which likely modulates both photosynthesis-g_s and growth-stress tolerance trade-offs.

Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics

Metabolite profiling of cancer cells presents many opportunities for anticancer drug discovery. The Chinese, Indian, and African flora, in particular, offers a diverse source of anticancer therapeutics as documented in traditional folklores. In-depth scientific information relating to mechanisms of action, quality control, and safety profile will promote their extensive usage in cancer therapy. Metabolomics may be a more holistic strategy to gain valuable insights into the anticancer mechanisms of action of plants but this has remained largely unexplored. This review, therefore, presents the available metabolomics studies on the anticancer effects of herbal medicines commonly used in Africa and Asia. In addition, we present some scientifically understudied ‘candidate plants’ for cancer metabolomics studies and highlight the relevance of metabolomics in addressing other challenges facing the drug development of anticancer herbs. Finally, we discussed the challenges of using metabolomics to uncover the underlying mechanisms of potential anticancer herbs and the progress made in this regard.

Exploring the genic resources underlying metabolites through mGWAS and mQTL in wheat: From large-scale gene identification and pathway elucidation to crop improvement

Common wheat (Triticum aestivum L.) is a leading cereal crop, but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize. The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets. Meanwhile, the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals. One such productive avenue is combining metabolomics approaches with genetic designs. However, this trial is not as widespread as that for sequencing technologies, especially when the acquisition, understanding, and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized. In this review, we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes. Considerable progress has been made in delivering improved varieties, suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and, as such, this procedure could serve as an -omics-informed roadmap for executing similar improvement strategies in wheat and other species.

A Comprehensive Workflow for the Analysis of Bio-Macromolecular Supplements: Case Study of 20 Whey Protein Products

The presence of bio-macromolecules as major ingredients is a primary factor in marketing many biologically derived macromolecular supplements. Workflows for analyzing these supplements for quality assurance, adulteration, and other supply-chain difficulties must include a qualitative assessment of small-molecule and macromolecular components; however, no such integrated protocol has been reported for these bio-macromolecular supplements. Twenty whey protein supplements were analyzed using an integrated workflow to identify protein content, protein adulteration, inorganic elemental content, and macromolecular and small-molecule profiles. Orthogonal analytical methods were employed, including NMR profiling, LC-DAD-QToF analysis of small-molecule components, ICP-MS analysis of inorganic elements, determination of total protein content by a Bradford assay, SDS-PAGE protein profiling, and bottom-up shotgun proteomic analysis using LC-MS-MS. All 20 supplements showed a reduced protein content compared to the claimed content but no evidence of adulteration with protein from an unclaimed source. Many supplements included unlabeled small-molecule additives (but nontoxic) and significant deviations in metal content, highlighting the importance of both macromolecular and small-molecule analysis in the comprehensive profiling of macromolecular supplements. An orthogonal, integrated workflow allowed the detection of crucial product characteristics that would have remained unidentified using traditional workflows involving either analysis of small-molecule nutritional supplements or protein analysis.

A fluorescent sensor for selective detection of hypochlorite and its application in Arabidopsis thaliana

Hypochlorite, as one of reactive oxygen species, has drawn much attention due to its essential roles in special biological events and disorders. The exogenous hypochlorite remains a risk for human, animals and plants. In this work, a novel water soluble quinolin-containing nitrone derivative T has been developed for fluorometric sensing hypochlorite. The response mechanism of T towards ClO^- was reported for the first time. In comparison with the reported sensors for ClO^-, the sensor T in this work exhibited advantages including high selectivity (80 fold over other analytes), rapid response (within 5 s) and lipid-water distribution transformation (LogP from 2.979 to 6.131). Further biological applications suggested that T was capable of monitoring both exogenous and endogenous ClO^- in living cells. The imaging in Arabidopsis thaliana indicated that the absorption and transmission of ClO^- in plant could be monitored by this sensor through the chlorine-related mechanism. This work might raise referable information for further investigations in the physiological and pathological events in both tumor and plants.

Plant Metabolomics Using NMR Spectroscopy

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.

Inorganic Nitrogen Form Determines Nutrient Allocation and Metabolic Responses in Maritime Pine Seedlings

Nitrate and ammonium are the main forms of inorganic nitrogen available to plants. The present study aimed to investigate the metabolic changes caused by ammonium and nitrate nutrition in maritime pine (Pinus pinaster Ait.). Seedlings were grown with five solutions containing different proportions of nitrate and ammonium. Their nitrogen status was characterized through analyses of their biomass, different biochemical and molecular markers as well as a metabolite profile using ¹H-NMR. Ammonium-fed seedlings exhibited higher biomass than nitrate-fed-seedlings. Nitrate mainly accumulated in the stem and ammonium in the roots. Needles of ammonium-fed seedlings had higher nitrogen and amino acid contents but lower levels of enzyme activities related to nitrogen metabolism. Higher amounts of soluble sugars and L-arginine were found in the roots of ammonium-fed seedlings. In contrast, L-asparagine accumulated in the roots of nitrate-fed seedlings. The differences in the allocation of nitrate and ammonium may function as metabolic buffers to prevent interference with the metabolism of photosynthetic organs. The metabolite profiles observed in the roots suggest problems with carbon and nitrogen assimilation in nitrate-supplied seedlings. Taken together, this new knowledge contributes not only to a better understanding of nitrogen metabolism but also to improving aspects of applied mineral nutrition for conifers.

Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis

Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.

Optimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing

INTRODUCTION

Proton nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic profiling has a range of applications in plant sciences.

OBJECTIVES

The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances.

METHODS

An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed 1H-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis.

RESULTS

Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups.

CONCLUSION

Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

A Metabologenomic Approach Reveals Changes in the Intestinal Environment of Mice Fed on American Diet

Intestinal microbiota and their metabolites are strongly associated with host physiology. Developments in DNA sequencing and mass spectrometry technologies have allowed us to obtain additional data that enhance our understanding of the interactions among microbiota, metabolites, and the host. However, the strategies used to analyze these datasets are not yet well developed. Here, we describe an original analytical strategy, metabologenomics, consisting of an integrated analysis of mass spectrometry-based metabolome data and high-throughput-sequencing-based microbiome data. Using this approach, we compared data obtained from C57BL/6J mice fed an American diet (AD), which contained higher amounts of fat and fiber, to those from mice fed control rodent diet. The feces of the AD mice contained higher amounts of butyrate and propionate, and higher relative abundances of Oscillospira and Ruminococcus. The amount of butyrate positively correlated with the abundance of these bacterial genera. Furthermore, integrated analysis of the metabolome data and the predicted metagenomic data from Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) indicated that the abundance of genes associated with butyrate metabolism positively correlated with butyrate amounts. Thus, our metabologenomic approach is expected to provide new insights and understanding of intestinal metabolic dynamics in complex microbial ecosystems.

Comparative analysis of 1H NMR and 1H-13C HSQC NMR metabolomics to understand the effects of medium composition in yeast growth

In nuclear magnetic resonance (NMR) metabolomics, most of the studies have been focused on the analysis of one-dimensional proton (1D ¹H) NMR, whereas the analysis of other nuclei, such as ¹³C, or other NMR experiments are still underrepresented. The preference of 1D ¹H NMR metabolomics lies on the fact that it has good sensitivity and a short acquisition time, but it lacks spectral resolution because it presents a high degree of overlap. In this study, the growth metabolism of yeast ( Saccharomyces cerevisiae) was analyzed by 1D ¹H NMR and by two-dimensional (2D) ¹H-¹³C heteronuclear single quantum coherence (HSQC) NMR spectroscopy, leading to the detection of more than 50 metabolites with both analytical approaches. These two analyses allow for a better understanding of the strengths and intrinsic limitations of the two types of NMR approaches. The two data sets (1D and 2D NMR) were investigated with PCA, ASCA, and PLS DA chemometric methods, and similar results were obtained regardless of the data type used. However, data-analysis time for the 2D NMR data set was substantially reduced when compared with the data analysis of the corresponding ¹H NMR data set because, for the 2D NMR data, signal overlap was not a major problem and deconvolution was not required. The comparative study described in this work can be useful for the future design of metabolomics workflows, to assist in the selection of the most convenient NMR platform and to guide the posterior data analysis of biomarker selection.

Transformed Root Culture: From Genetic Transformation to NMR-Based Metabolomics

Hairy root (HR) culture is considered as "green factory" for mass production of bioactive molecules with pharmaceutical relevance. As such, HR culture has an immense potential as a valuable platform to elucidate biosynthetic pathways and physiological processes, generate recombinant therapeutic proteins, assist molecular breeding, and enhance phytoremediation efforts. However, some plant species appear recalcitrant to the classical Agrobacterium rhizogenes transformation techniques. Sonication-assisted Agrobacterium-mediated transformation (SAArT) is a highly effective method to deliver bacteria to target plant tissues that includes exposure of the explants to short periods of ultrasound in the presence of the bacteria.Nuclear magnetic resonance (NMR)-based metabolomics is one of the most powerful and suitable platforms for identifying and obtaining structural information on a wide range of compounds with a high analytical precision. In terms of plant science, NMR metabolomics is used to determine the phytochemical variations of medicinal plants or commercial cultivars in certain environments and conditions, including biotic stress and plant biotic interaction, structural determination of natural products, quality control of herbal drugs or dietary supplements, and comparison of metabolite differences between plants and their respective in vitro cultures.In this chapter, we attempt to summarize our knowledge and expertise in induction of hairy roots from rare and recalcitrant plant species by SAArT technique and further methodology for extraction of secondary metabolites of moderate to high polarity and their identification by using NMR-based metabolomics.

Metabolomics 20 years on: what have we learned and what hurdles remain?

The term metabolome was coined in 1998, by analogy to genome, transcriptome and proteome. The first research papers using the terms metabolomics, metabonomics, metabolic profiling or metabolite profiling were published shortly thereafter. In this short review we reflect on the major achievements brought about by the use of these approaches, and document the knowledge and technology gaps that are currently constraining its further development. Finally, we detail why we think that the time is ripe to refocus our efforts on the understanding of metabolic function.

High-Resolution Magic-Angle-Spinning NMR and Magnetic Resonance Imaging Spectroscopies Distinguish Metabolome and Structural Properties of Maize Seeds from Plants Treated with Different Fertilizers and Arbuscular mycorrhizal fungi

Both high-resolution magic-angle-spinning (HRMAS) and magnetic resonance imaging (MRI) NMR spectroscopies were applied here to identify the changes of metabolome, morphology, and structural properties induced in seeds (caryopses) of maize plants grown at field level under either mineral or compost fertilization in combination with the inoculation by arbuscular mycorrhizal fungi (AMF). The metabolome of intact caryopses was examined by HRMAS-NMR, while the morphological aspects, endosperm properties and seed water distribution were investigated by MRI. Principal component analysis (PCA) was applied to evaluate ¹H CPMG (Carr-Purcel-Meiboom-Gill) HRMAS spectra as well as several MRI-derived parameters ( T₁, T₂, and self-diffusion coefficients) of intact maize caryopses. PCA score-plots from spectral results indicated that both seeds metabolome and structural properties depended on the specific field treatment undergone by maize plants. Our findings show that a combination of multivariate statistical analyses with advanced and nondestructive NMR techniques, such as HRMAS and MRI, enables the evaluation of the effects induced on maize caryopses by different fertilization and management practices at field level. The spectroscopic approach adopted here may become useful for the objective appraisal of the quality of seeds produced under a sustainable agriculture.

Environmental metabolomics with data science for investigating ecosystem homeostasis

A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches.

Simultaneous untargeted and targeted metabolomics profiling of underivatized primary metabolites in sulfur-deficient barley by ultra-high performance liquid chromatography-quadrupole/time-of-flight mass spectrometry

BACKGROUND

Metabolomics based on mass spectrometry analysis are increasingly applied in diverse scientific domains, notably agronomy and plant biology, in order to understand plants' behaviors under different stress conditions. In fact, these stress conditions are able to disrupt many biosynthetic pathways that include mainly primary metabolites. Profiling and quantifying primary metabolites remain a challenging task because they are poorly retained in reverse phase columns, due to their high polarity and acid-base properties. The aim of this work is to develop a simultaneous untargeted/targeted profiling of amino acids, organic acids, sulfur metabolites, and other several metabolites. This method will be applied on sulfur depleted barley, in order to study this type of stress, which is difficult to detect at early stage. Also, this method aims to explore the impact of this stress on barley's metabolome.

RESULTS

Ultra-high performance liquid chromatography-high resolution mass spectrometry-based method was successfully applied to real samples allowing to discriminate, detect, and quantify primary metabolites in short-runs without any additional sampling step such as derivatization or ion pairing. The retention of polar metabolites was successfully achieved using modified C18 columns with high reproducibility (relative standard deviation below 10%). The quantification method showed a high sensitivity and robustness. Furthermore, high resolution mass spectrometry detection provided reliable quantification based on exact mass, eliminating potential interferences, and allowing the simultaneous untargeted metabolomics analysis. The untargeted data analysis was conducted using Progenesis QI software, performing alignment, peak picking, normalization and multivariate analysis. The simultaneous analysis provided cumulative information allowing to discriminate between two plant batches. Thus, discriminant biomarkers were identified and validated. Simultaneously, quantification confirmed coherently the relative abundance of these biomarkers.

CONCLUSIONS

A fast and innovated simultaneous untargeted/targeted method has successfully been developed and applied to sulfur deficiency on barley. This work opens interesting perspectives in both fundamental and applied research. Biomarker discovery give precious indication to understand plant behavior during a nutritional deficiency. Thus, direct or indirect measurement of these compounds allows a real time fertilization management and encounter the challenges of sustainable agriculture.

NMR-Based Identification of Metabolites in Polar and Non-Polar Extracts of Avian Liver

Metabolites present in liver provide important clues regarding the physiological state of an organism. The aim of this work was to evaluate a protocol for high-throughput NMR-based analysis of polar and non-polar metabolites from a small quantity of liver tissue. We extracted the tissue with a methanol/chloroform/water mixture and isolated the polar metabolites from the methanol/water layer and the non-polar metabolites from the chloroform layer. Following drying, we re-solubilized the fractions for analysis with a 600 MHz NMR spectrometer equipped with a 1.7 mm cryogenic probe. In order to evaluate the feasibility of this protocol for metabolomics studies, we analyzed the metabolic profile of livers from house sparrow (Passer domesticus) nestlings raised on two different diets: livers from 10 nestlings raised on a high protein diet (HP) for 4 d and livers from 12 nestlings raised on the HP diet for 3 d and then switched to a high carbohydrate diet (HC) for 1 d. The protocol enabled the detection of 52 polar and nine non-polar metabolites in ¹H NMR spectra of the extracts. We analyzed the lipophilic metabolites by one-way ANOVA to assess statistically significant concentration differences between the two groups. The results of our studies demonstrate that the protocol described here can be exploited for high-throughput screening of small quantities of liver tissue (approx. 100 mg wet mass) obtainable from small animals.

The Genetics of Plant Metabolism

Plant metabolic studies have traditionally focused on the role and regulation of the enzymes catalyzing key reactions within specific pathways. Within the past 20 years, reverse genetic approaches have allowed direct determination of the effects of the deficiency, or surplus, of a given protein on the biochemistry of a plant. In parallel, top-down approaches have also been taken, which rely on screening broad, natural genetic diversity for metabolic diversity. Here, we compare and contrast the various strategies that have been adopted to enhance our understanding of the natural diversity of metabolism. We also detail how these approaches have enhanced our understanding of both specific and global aspects of the genetic regulation of metabolism. Finally, we discuss how such approaches are providing important insights into the evolution of plant secondary metabolism.

Aluminium-induced excessive ROS causes cellular damage and metabolic shifts in black gram Vigna mungo (L.) Hepper

Aluminium-induced oxidative damage caused by excessive ROS production was evaluated in black gram pulse crop. Black gram plants were treated with different aluminium (Al³⁺) concentrations (10, 50 and 100 μM with pH 4.7) and further the effects of Al³⁺ were characterised by means of root growth inhibition, histochemical assay, ROS content analysis, protein carbonylation quantification and ¹H-NMR analysis. The results showed that aluminium induces excessive ROS production which leads to cellular damage, root injury, stunt root growth and other metabolic shifts. In black gram, Al³⁺ induces cellular damage at the earliest stage of stress which was characterised from histochemical analysis. From this study, it was observed that prolonged stress can activate certain aluminium detoxification defence mechanism. Probably excessive ROS triggers such defence mechanism in black gram. Al³⁺ can induce excessive ROS initially in the root region then transported to other parts of the plant. As much as the Al³⁺ concentration increases, the rate of cellular injury and ROS production also increases. But after 72 h of stress, plants showed a lowered ROS level and cellular damage which indicates the upregulation of defensive mechanisms. Metabolic shift analysis also showed that the black gram plant under stress has less metabolic content after 24 h of treatment, but gradually, it was increased after 72 h of treatment. It was assumed that ROS played the most important role as a signalling molecule for aluminium stress in black gram.

NMR window of molecular complexity showing homeostasis in superorganisms

NMR offers tremendous advantages in the analyses of molecular complexity. The “big-data” are produced during the acquisition of fingerprints that must be stored and shared for posterior analysis and verifications.

Evidence for impaired glucose metabolism in the striatum, obtained postmortem, from some subjects with schizophrenia

Studies using central nervous system tissue obtained postmortem suggest pathways involved in energy and metabolism contribute to the pathophysiology of schizophrenia; neuroimaging studies suggesting glucose metabolism is particularly affected in the striatum. To gain information on the status of pathways involved in glucose metabolism in the striatum, we measured levels of glucose, pyruvate, acetyl-CoA and lactate as well as the β subunit of pyruvate dehydrogenase, a rate limiting enzyme, in the postmortem tissue from subjects with schizophrenia and age/sex-matched controls. The subjects with schizophrenia were made up of two subgroups, which could be divided because they either had (muscarinic receptor deficit schizophrenia (MRDS)), or did not have (non-MRDS), a marked deficit in cortical muscarinic receptors. Compared to controls, levels of β subunit of pyruvate dehydrogenase were lower (Δ mean=-20%) and levels of pyruvate (Δ mean=+47%) and lactate (Δ mean=+15%) were significantly higher in the striatum from subjects with schizophrenia. Notably, in subjects with non-MRDS, striatal levels of β subunit of pyruvate dehydrogenase were lower (Δ mean=-29%), whereas levels of pyruvate (Δ mean=-66%), acetyl-CoA (Δ mean=-28%) and glucose (Δ mean=-27%) were higher, whereas levels of lactate (Δ mean=+17%) were higher in MRDS. Finally, discriminate analyses using levels the β subunit of pyruvate dehydrogenase and glucose, or better still, β subunit of pyruvate dehydrogenase and glucose in combination with pyruvate, lactate or acetyl-CoA could separate subjects with non-MRDS from controls with high levels of specificity (up to 93%) and selectivity (up to 91%). Our data show the benefit of being able to study defined subgroups within the syndrome of schizophrenia as such an approach has revealed that changes in glucose metabolism may be a significant contributor to the pathophysiology of non-MRDS.

Metabolomics by Proton High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance of Tomato Plants Treated with Two Secondary Metabolites Isolated from Trichoderma

Trichoderma fungi release 6-pentyl-2H-pyran-2-one (1) and harzianic acid (2) secondary metabolites to improve plant growth and health protection. We isolated metabolites 1 and 2 from Trichoderma strains, whose different concentrations were used to treat seeds of Solanum lycopersicum. The metabolic profile in the resulting 15 day old tomato leaves was studied by high-resolution magic-angle-spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy directly on the whole samples without any preliminary extraction. Principal component analysis (PCA) of HRMAS NMR showed significantly enhanced acetylcholine and γ-aminobutyric acid (GABA) content accompanied by variable amount of amino acids in samples treated with both Trichoderma secondary metabolites. Seed germination rates, seedling fresh weight, and the metabolome of tomato leaves were also dependent upon doses of metabolites 1 and 2 treatments. HRMAS NMR spectroscopy was proven to represent a rapid and reliable technique for evaluating specific changes in the metabolome of plant leaves and calibrating the best concentration of bioactive compounds required to stimulate plant growth.

Applications of NMR spectroscopy to systems biochemistry

The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other 'omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

A Urinary Metabolic Signature for Multiple Sclerosis and Neuromyelitis Optica

Urine is a metabolite-rich biofluid that reflects the body's effort to maintain chemical and osmotic homeostasis. Clinical diagnosis routinely relies on urine samples because the collection process is easy and noninvasive. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). Nuclear magnetic resonance spectroscopy (NMR) has become a common approach for analyzing urinary metabolites for disease diagnosis and biomarker discovery. For illustration of the potential of urinary metabolites for diagnosing and treating MS patients, and for differentiating between MS and other illnesses, 38 urine samples were collected from healthy controls, MS patients, and neuromyelitis optica-spectrum disorder (NMO-SD) patients and analyzed with NMR, multivariate statistics, one-way ANOVA, and univariate statistics. Urine from MS patients exhibited a statistically distinct metabolic signature from healthy and NMO-SD controls. A total of 27 metabolites were differentially altered in the urine from MS and NMO-SD patients and were associated with synthesis and degradation of ketone bodies, amino acids, propionate and pyruvate metabolism, tricarboxylic acid cycle, and glycolysis. Metabolites altered in urine from MS patients were shown to be related to known pathogenic processes relevant to MS, including alterations in energy and fatty acid metabolism, mitochondrial activity, and the gut microbiota.

SpinCouple: Development of a Web Tool for Analyzing Metabolite Mixtures via Two-Dimensional J-Resolved NMR Database

A new Web-based tool, SpinCouple, which is based on the accumulation of a two-dimensional (2D) (1)H-(1)H J-resolved NMR database from 598 metabolite standards, has been developed. The spectra include both J-coupling and (1)H chemical shift information; those are applicable to a wide array of spectral annotation, especially for metabolic mixture samples that are difficult to label through the attachment of (13)C isotopes. In addition, the user-friendly application includes an absolute-quantitative analysis tool. Good agreement was obtained between known concentrations of 20-metabolite mixtures versus the calibration curve-based quantification results obtained from 2D-Jres spectra. We have examined the web tool availability using nine series of biological extracts, obtained from animal gut and waste treatment microbiota, fish, and plant tissues. This web-based tool is publicly available via http://emar.riken.jp/spincpl.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

Cytotoxicity of TSP in 3D Agarose Gel Cultured Cell

Purpose

A reference reagent, 3-(trimethylsilyl) propionic-2, 2, 3, 3-d4 acid sodium (TSP), has been used frequently in nuclear magnetic resonance (NMR) and magnetic resonance spectroscopy (MRS) as an internal reference to identify cell and tissue metabolites, and determine chemical and protein structures. This reference material has been exploited for the quantitative and dynamic analyses of metabolite spectra acquired from cells. The aim of this study was to evaluate the cytotoxicity of TSP on three-dimensionally, agarose gel, cultured cells.

Materials and Methods

A human osteosarcoma cell line (MG-63) was selected, and cells were three dimensionally cultured for two weeks in an agarose gel. The culture system contained a mixture of conventional culture medium and various concentrations (0, 1, 3, 5, 7, 10, 20 30 mM) of TSP. A DNA quantification assay was conducted to assess cell proliferation using Quant-iT PicoGreen dsDNA reagent and kit, and cell viability was determined using a LIVE/DEAD Viability/Cytotoxicity kit. Both examinations were performed simultaneously at 1, 3, 7 and 14 days from cell seeding.

Results

In this study, the cytotoxicity of TSP in the 3D culture of MG-63 cells was evaluated by quantifying DNA (cell proliferation) and cell viability. High concentrations of TSP (from 10 to 30 mM) reduced both cell proliferation and viability (to 30% of the control after one week of exposure), but no such effects were found using low concentrations of TSP (0–10mM).

Conclusions

This study shows that low concentrations of TSP in 3D cell culture medium can be used for quantitative NMR or MRS examinations for up to two weeks post exposure.

Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis

Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles' age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers' adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.

Artefacts in 1H NMR-based metabolomic studies on cell cultures

OBJECT

Metabolomic studies on cultured cells involve assays of cell extracts and culture medium, both of which are often performed by (1)H NMR. Cell culture is nowadays performed in plastic dishes or flasks, and the extraction of metabolites from the cells is typically performed with perchloric acid, methanol-chloroform, or acetonitrile, ideally while the cells are still adherent to the culture dish. We conducted this investigation to identify contaminants from cell culture plasticware in metabolomic studies.

MATERIALS AND METHODS

Human diploid fibroblasts (IMR90) (n = 6), HeLa cells (n = 6), and transformed astrocytes with HIF-1 knockout (Astro-KO) (n = 6) were cultured. Cells were seeded in 100 mm Petri dishes with 10 ml complete growth medium (Dulbecco's minimum essential medium) containing 10 % foetal bovine serum (FBS). Cell cultures were incubated at 37 °C in 5 % CO2 for approximately 3 days. Metabolites were extracted by use of a perchloric acid procedure. (1)H NMR spectroscopy was used for metabolite analysis. "Null sample" (i.e. cell-free) experiments were performed by either rinsing dishes with medium or incubating the medium in Petri dishes from five different manufacturers for 72 h and then by performing a dummy "extraction" of each Petri dish by the perchloric acid, methanol-chloroform, or acetonitrile procedures. Principal components analysis was used for classification of samples and to determine the contaminants arising from plasticware.

RESULTS

We found that even brief rinsing of cell culture plasticware with culture medium elutes artefactual chemicals, the (1)H NMR signals of which could confound assays of acetate, succinate, and glycolate. Incubation of culture medium in cell-culture dishes for 72 h (as in a typical cell-culture experiment) followed by perchloric extraction in the dishes enhanced elution of the artefacts. These artefacts were present, but somewhat less pronounced, in the (1)H NMR spectra of null samples extracted with methanol and acetonitrile. Ethanol, lactate, alanine, fructose, and fumarate signals that appear in the (1)H NMR spectrum of the unused (pure) medium originate from FBS.

CONCLUSIONS

Plastic Petri dishes from five different manufacturers gave rise to essentially identical artefactual peaks. Use of a pH indicator to assist neutralisation introduced still more artefactual signals in the aromatic region, as well as methanol and ethanol signals. Methanol and acetonitrile extracts also contained artefacts arising from the plasticware, although the amounts were less than in the perchloric acid extracts. Finally, we provide suggestions for minimizing these artefacts. The best practice would be to run a "null" extraction with every batch of cellular metabolomics experiments to test for contamination and to provide a "background" spectrum.

Metabolite profiling reveals abiotic stress tolerance in Tn5 mutant of Pseudomonas putida

Pseudomonas is an efficient plant growth–promoting rhizobacteria (PGPR); however, intolerance to drought and high temperature limit its application in agriculture as a bioinoculant. Transposon 5 (Tn5) mutagenesis was used to generate a stress tolerant mutant from a PGPR Pseudomonas putida NBRI1108 isolated from chickpea rhizosphere. A mutant NBRI1108T, selected after screening of nearly 10,000 transconjugants, exhibited significant tolerance towards high temperature and drought. Southern hybridization analysis of EcoRI and XhoI restricted genomic DNA of NBRI1108T confirmed that it had a single Tn5 insertion. The metabolic changes in the polar and non-polar extracts of NBRI1108 and NBRI1108T were examined using ¹H, ³¹P nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS). Thirty six chemically diverse metabolites consisting of amino acids, fatty acids and phospholipids were identified and quantified. Insertion of Tn5 influenced amino acid and phospholipid metabolism and resulted in significantly higher concentration of aspartic acid, glutamic acid, glycinebetaine, glycerophosphatidylcholine (GPC) and putrescine in NBRI1108T as compared to that in NBRI1108. The concentration of glutamic acid, glycinebetaine and GPC increased by 34%, 95% and 100%, respectively in the NBRI1108T as compared to that in NBRI1108. High concentration of glycerophosphatidylethanolamine (GPE) and undetected GPC in NBRI1108 indicates that biosynthesis of GPE may have taken place via the methylation pathway of phospholipid biosynthesis. However, high GPC and low GPE concentration in NBRI1108T suggest that methylation pathway and phosphatidylcholine synthase (PCS) pathway of phospholipid biosynthesis are being followed in the NBRI1108T. Application of multivariate principal component analysis (PCA) on the quantified metabolites revealed clear variations in NBRI1108 and NBRI1108T in polar and non-polar metabolites. Identification of abiotic stress tolerant metabolites from the NBRI1108T suggest that Tn5 mutagenesis enhanced tolerance towards high temperature and drought. Tolerance to drought was further confirmed in greenhouse experiments with maize as host plant, where NBRI1108T showed relatively high biomass under drought conditions.

Aluminum stress inhibits root growth and alters physiological and metabolic responses in chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) roots were treated with aluminum (Al3+) in calcium chloride (CaCl2) solution (pH 4.7) and growth responses along with physiological and metabolic changes were investigated. Al3+ treatment for 7d resulted in a dose dependent decline of seed germination and inhibition of root growth. A significant (p ≤ 0.05) decline in fresh and dry biomass were observed after 7d of Al3+ stress.The root growth (length) was inhibited after 24 and 48 h of stress imposition. The hydrogen peroxide (H2O2) levels increased significantly (p ≤ 0.05) with respect to control in Al3+ treated roots. The hematoxylin and Evans blue assay indicated significant (p ≤ 0.05) accumulation of Al3+ in the roots and loss of plasma membrane integrity respectively. The time-course evaluation of lipid peroxidation showed increase in malondialdehyde (MDA) after 12, 24 and 48 h of stress imposition. Al3+ treatment did not alter the MDA levels after 2 or 4 h of stress, however, a minor increase was observed after 6 and 10 h of treatment. The proton (1H) nuclear magnetic resonance (NMR) spectrum of the perchloric acid extracts showed variation in the abundance of metabolites and suggested a major metabolic shift in chickpea root during Al3+ stress. The key differences that were observed include changes in energy metabolites. Accumulation of phenolic compounds suggested its possible role in Al3+ exclusion in roots during stress. The results suggested that Al3+ alters growth pattern in chickpea and induces reactive oxygen species (ROS) production that causes physiological and metabolic changes.

Extraction for metabolomics: access to the metabolome

INTRODUCTION

The value of information obtained from a metabolomic study depends on how much of the metabolome is present in analysed samples. Thus, only a comprehensive and reproducible extraction method will provide reliable data because the metabolites that will be measured are those that were extracted and all conclusions will be built around this information.

OBJECTIVE

To discuss the efficiency and reliability of available sample pre-treatment methods and their application in different fields of metabolomics.

METHODS

The review has three sections: the first deals with pre-extraction techniques, the second discusses the choice of extraction solvents and their main features and the third includes a brief description of the most used extraction techniques: microwave-assisted extraction, solid-phase extraction, supercritical fluid extraction, Soxhlet and a new method developed in our laboratory--the comprehensive extraction method.

RESULTS

Examination of over 200 studies showed that sample collection, homogenisation, grinding and storage could affect the yield and reproducibility of results. They also revealed that apart from the solvent used for extraction, the extraction techniques have a decisive role on the metabolites available for analysis.

CONCLUSION

It is essential to evaluate efficacy and reproducibility of sample pre-treatment as a first step to ensure the reliability of a metabolomic study. Among the reviewed methods, the comprehensive extraction method appears to provide a promising approach for extracting diverse types of metabolites.

The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a flexible balance between the cytosolic and plastidic contributions to carbohydrate oxidation in response to phosphate limitation

Understanding the mechanisms that allow plants to respond to variable and reduced availability of inorganic phosphate is of increasing agricultural importance because of the continuing depletion of the rock phosphate reserves that are used to combat inadequate phosphate levels in the soil. Changes in gene expression, protein levels, enzyme activities and metabolite levels all point to a reconfiguration of the central metabolic network in response to reduced availability of inorganic phosphate, but the metabolic significance of these changes can only be assessed in terms of the fluxes supported by the network. Steady-state metabolic flux analysis was used to define the metabolic phenotype of a heterotrophic Arabidopsis thaliana cell culture grown on a Murashige and Skoog medium containing 0, 1.25 or 5 mm inorganic phosphate. Fluxes through the central metabolic network were deduced from the redistribution of (13) C into metabolic intermediates and end products when cells were labelled with [1-(13) C], [2-(13) C], or [(13) C6 ]glucose, in combination with (14) C measurements of the rates of biomass accumulation. Analysis of the flux maps showed that reduced levels of phosphate in the growth medium stimulated flux through phosphoenolpyruvate carboxylase and malic enzyme, altered the balance between cytosolic and plastidic carbohydrate oxidation in favour of the plastid, and increased cell maintenance costs. We argue that plant cells respond to phosphate deprivation by reconfiguring the flux distribution through the pathways of carbohydrate oxidation to take advantage of better phosphate homeostasis in the plastid.

An optimized method for NMR-based plant seed metabolomic analysis with maximized polar metabolite extraction efficiency, signal-to-noise ratio, and chemical shift consistency

An optimized method for NMR-based plant seed metabolomic analysis was established with extraction solvent, cell-breaking method and extract-to-buffer ratio.