Metabolites In Plant Extracts Research Articles

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Biosynthesis and Characterization of Silver Nanoparticles Coated with Metabolites Extracted from Clerodendron phlomoides with Its Biochemical Studies in Liver Tissue

Silver nanoparticles (AgNPs) have been used as a potential nanomaterial-based drug delivery vehicle for liver cancer treatment, as it induces cell death and produces cytotoxicity against cancerous cells at a low concentration. The biosynthesis of green metallic nanoparticles uses secondary metabolites in plant extracts instead of toxic chemicals for a reduction-oxidation (redox) reaction. The biosynthesis of AgNPs with the aqueous extract of Clerodendron phlomoides was performed in this study. The phytochemical analysis of C. phlomoides extract using gas chromatography-mass spectrometry (GC-MS) confirmed the presence of redox metabolites. The peak at 489 nm in UV-visible spectra confirmed the formation of bioactive AgNPs reduced from silver nitrate solution, whereas the Fourier-transform infrared (FTIR) spectra indicated the bioactive molecules of plant extracts that are responsible for the formation. Scanning electron microscope (SEM) micrograph revealed the formation of spherical and ovoid structures of AgNPs, whereas transmission electron microscope (TEM) micrograph confirmed the size of AgNPs, which varies from 25 nm to 100 nm. X-ray diffraction (XRD) spectra showed the crystalline nature of AgNPs, and the size of crystallite was 4 nm, while dynamic light scattering (DLS) analysis confirmed the average particle size of AgNPs to be around 125 nm. In vivo studies showed that bioactive AgNPs have a significant anticancer potential against liver cancer, whereas biochemical studies of rats’ liver tissue samples confirmed that bioactive AgNPs produced a potential hepatoprotective effect against diethylnitrosamine-induced liver cancer.

Ultraviolet (UV) light-induced geometrical isomerization of cinnamic acid containing molecules: A plausible, non-enzymatic approach to modify metabolite composition of plant extracts

• UV light can be used to enhance the cinnamic acid containing-metabolite composition of a plant. • LC-MS in combination with multivariate statistics can be used to probe for the presence of photo-induced metabolites in plant extracts. • UV-irradiated plant extracts have a coherent metabolite composition as compared to naturally growing plants. Cinnamic acid containing molecules are widely distributed in plants, and they are known to possess several pharmacological properties. Structurally, these molecules consist of C 6 C 3 skeletal backbone, with an olefin functional group on the C 3 part . Naturally, plants produce a broad spectrum of cinnamic acid derivatives with a trans configuration, however, cis isomers are formed due to excessive UV-light exposure, thereby increasing the already complex metabolomes of plants containing these compounds. In high sunlight intensive areas, the prevalence of the cis isomers of cinnamic acid containing molecules is becoming more prevalent and synonymous with extracts of many plants. It is therefore imperative to develop analytical and data handling strategies to account for the presence of these molecules, which can serve as a template for rational design of pharmacologically active plant extracts or smart photo-switchable drugs. Herein, we show that a combination of ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS) and principal component analysis (PCA) allows differentiation of plants extracts of which metabolome modification through UV-radiation has been carried out. The results of the current study show that geometrical isomerism is a feasible, non-enzymatic approach to modify metabolite composition of plants. This simple method can be used to create “super” extracts of plants containing structurally diverse metabolites to be evaluated for various pharmacological properties in the future.

Two Ways to Achieve the Same Goal-Two Validated Quantitative NMR Strategies for a Low-Abundance Natural Product in Standardized Extracts: The Case of Hepatodamianol in Turnera diffusa.

The quantification of low-abundance secondary metabolites in plant extracts is an analytical problem that can be addressed by different analytical platforms, the most common being those based on chromatographic methods coupled to a high-sensitivity detection system. However, in recent years nuclear magnetic resonance (NMR) has become an analytical tool of primary choice for this type of problem because of its reliability, inherent simplicity in sample preparation, reduced analysis time, and low solvent consumption. The versatility of strategies based on quantitative NMR (qNMR), such as internal and external standards and electronic references, among others, and the need to develop validated analytical methods make it essential to compare procedures that must rigorously satisfy the analytical well-established acceptance criteria for method validation. In this work, two qNMR methods were developed for the quantification of hepatodamianol, a bioactive component of T. diffusa. The first method was based on a conventional external standard calibration, and the second one was based on the pulse length-based concentration determination (PULCON) method using the ERETIC2 module as a quantitation tool available in TopSpin software. The results show that both procedures allow the content of the analyte of interest in a complex matrix to be determined in a satisfactory way, under strict analytical criteria. In addition, ERETIC2 offers additional advantages such as a reduction in experimental time, reagent consumption, and waste generated.

Phytochemical Screening and In Vitro Antifungal Activity of Selected Medicinal Plants against Candida albicans and Aspergillus niger in West Shewa Zone, Ethiopia.

Antimicrobial resistance to commercially available medications has become a global issue, yet there is still the possibility of developing new drugs from medicinal plants. As a result, the aims of the present study were to screen secondary metabolites and to evaluate in vitro antifungal activities of Brucea antidysenterica, Aloe vera, and Justicia schimperiana. After the plants were identified, their leaves were collected, washed, dried under the shade, pulverized, and extracted with methanol (99.8%) using the maceration technique. The presence of secondary metabolites in plant extracts was screened using various laboratory protocols. The antifungal activities of the plant extract against reference fungal strains of Candida albicans and Aspergillus niger at concentrations of 200, 100, and 50 mg/mL were assessed using the agar-well diffusion method. Ketoconazole (15 μg) was used as a positive control, while 5% dimethyl sulfoxide and/or 5% Tween 80 were used as negative controls. All tests were conducted in triplicate. Alkaloids, flavonoids, and phenols were secondary metabolites found in all plant extracts. The extract of leaves of B. antidysenterica and J. schimperiana formed a mean zone of inhibition of 15.5 ± 0.5 mm and 15.3 ± 0.58 mm, respectively, against Candida albicans at a concentration of 200 mg/mL, whereas extracts of A. vera leaves formed a 12.3 ± 0.58 mm inhibition zone only against Aspergillus niger at 200 mg/mL. In conclusion, the current study found that B. antidysenterica, A. vera, and J. schimperiana had antifungal activity. In addition, all these plants had a variety of secondary metabolites that possibly have antifungal activities. Studies on in vivo investigations and isolation of specific antifungal compounds from these medicinal plants are suggested.

GAMBARAN KARAKTERISASI DARI EKSTRAK ETANOL LIMBAH RAMBUT JAGUNG MANIS (Zea mays L.)

Traditional plants in Indonesia, have a variety of benefits to overcome various diseases. For example, sweet corn hair waste (Zea mays L), was the residue from corn which is usually used for culinary purposes. Corn silk in previous studies was thought to have pharmacological activity as anti-inflammatory, antidiabetic, and antihypertensive. This study aims to determine the characterization of the ethanol extract of sweet corn hair waste in a hilly area of Kediri, East Java. Characterization to determine the content of active compounds in the ethanol extract of sweet corn hair waste and to ensure the quality of corn hair waste extract when it will be used as raw material for traditional medicine. Characterization includes specific parameters such as screening for metabolites in plant extracts using Thin Layer Chromatography (TLC) and non-specific parameters including determination of water content and specific gravity. The sample used was ethanol extract of sweet corn hair waste (EELRJM) obtained from the hilly area of Kediri, East Java. The results of the specific parameters of the secondary metabolite compound test by TLC indicated that EELRJM contains quercetin compounds of the flavonoid group. Non-specific parameters resulted that the water content of EELRJM did not meet the requirements of the extract monograph because it was suspected that there was an influence on the weather including rainfall.

GAMBARAN KARAKTERISASI DARI EKSTRAK ETANOL LIMBAH RAMBUT JAGUNG MANIS (Zea mays L.)

Traditional plants in Indonesia, have a variety of benefits to overcome various diseases. For example, sweet corn hair waste ( Zea mays L), was the residue from corn which is usually used for culinary purposes. Corn silk in previous studies was thought to have pharmacological activity as anti-inflammatory, antidiabetic, and antihypertensive. This study aims to determine the characterization of the ethanol extract of sweet corn hair waste in a hilly area of Kediri, East Java. Characterization to determine the content of active compounds in the ethanol extract of sweet corn hair waste and to ensure the quality of corn hair waste extract when it will be used as raw material for traditional medicine. Characterization includes specific parameters such as screening for metabolites in plant extracts using Thin Layer Chromatography (TLC) and non-specific parameters including determination of water content and specific gravity. The sample used was ethanol extract of sweet corn hair waste (EELRJM) obtained from the hilly area of Kediri, East Java. The results of the specific parameters of the secondary metabolite compound test by TLC indicated that EELRJM contains quercetin compounds of the flavonoid group. Non-specific parameters resulted that the water content of EELRJM did not meet the requirements of the extract monograph because it was suspected that there was an influence on the weather including rainfall.

Rapid Identification of Common Secondary Metabolites of Medicinal Herbs Using High-Performance Liquid Chromatography with Evaporative Light Scattering Detector in Extracts.

The discovery and identification of novel natural products of medicinal importance in the herbal medicine industry becomes a challenge. The complexity of this process can be reduced by dereplication strategies. The current study includes a method based on high-performance liquid chromatography (HPLC), using the evaporative light scattering detector (ELSD) to identify the 12 most common secondary metabolites in plant extracts. Twelve compounds including rutin, taxifolin, quercetin, apigenin, kaempferol, betulinic acid, oleanolic acid, betulin, lupeol, stigmasterol, and β-sitosterol were analyzed simultaneously. The polarity of the compounds varied greatly from highly polar (flavonoids) to non-polar (triterpenes and sterols). This method was also tested for HPLC-DAD and HPLC-ESI-MS/MS analysis. Oleanolic acid and ursolic acid could not be separated in HPLC-ELSD analysis but were differentiated using LC-ESI-MS/MS analysis due to different fragment ions. The regression values (R2 > 0.996) showed good linearity in the range of 50–1000 µg/mL for all compounds. The range of LOD and LOQ values were 7.76–38.30 µg/mL and 23.52–116.06 µg/mL, respectively. %RSD and % trueness values of inter and intraday studies were mostly <10%. This method was applied on 10 species of medicinal plants. The dereplication strategy has the potential to facilitate and shorten the identification process of common secondary metabolites in complex plant extracts.

Chitosan-induced production of secondary metabolites in plant extracts of Piper auritum, and the in vitro fungicidal activity against Fusarium oxysporum f. sp. vanillae

&lt;p&gt;Se probó el efecto del quitosano sobre la producción de metabolitos secundarios de extractos etanólicos de &lt;em&gt;Piper auritum&lt;/em&gt;, así como la actividad fungicida&lt;em&gt; in vitro&lt;/em&gt; contra&lt;em&gt; Fusarium oxysporum&lt;/em&gt; f. sp. &lt;em&gt;vanillae&lt;/em&gt;. Las plantas de &lt;em&gt;P. auritum&lt;/em&gt; se dividieron en seis parcelas y se añadió quitosano comercial a la mitad de ellas. Se midieron las concentraciones de flavonoides, fenoles, terpenos, alcaloides y ácido salicílico en extractos etanólicos de &lt;em&gt;P. auritum&lt;/em&gt; y la actividad antifúngica se midió con la concentración efectiva media (CE50). Las concentraciones totales de flavonoides, fenoles y terpenos fueron más altas con el tratamiento con quitosano (sin quitosano 12.8 versus con quitosano 12.4 ?g equivalente de quercetina por mg, 12.6 versus 2.3 ?g equivalente de ácido tánico por 10 mg y 16.3 versus 11.6 mg equivalente de mentol por 100 mg). Mientras que la concentración de alcaloides disminuyó mediante la adición de quitosano (de 148.2 a 84.5 ?g de equivalente de piperina por mg). La adición de quitosano aumentó la concentración de ácido salicílico (de 1.3 a 2.2 ?g de equivalente de ácido salicílico por mg). La concentración de 4 mg mL-1 de extracto etanólico de &lt;em&gt;P. auritum&lt;/em&gt; tratado con quitosano inhibió el 100% del crecimiento micelial. El tratamiento con quitosano generó que la CE50 de &lt;em&gt;P. auritum&lt;/em&gt; contra &lt;em&gt;F. oxysporum&lt;/em&gt; f. sp. &lt;em&gt;vanillae&lt;/em&gt; fuera menor (1.5 mg mL-1) respecto al control (5.1 mg mL-1). Se concluye que la adición de quitosano aumentó la producción de metabolitos secundarios y la actividad antifúngica &lt;em&gt;in vitro&lt;/em&gt; en extractos de &lt;em&gt;P. auritum.&lt;/em&gt;&lt;/p&gt;

Identification of Auxin Metabolites in Brassicaceae by Ultra-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry.

Auxins are signaling molecules involved in multiple stages of plant growth and development. The levels of the most important auxin, indole-3-acetic acid (IAA), are regulated by the formation of amide and ester conjugates with amino acids and sugars. In this work, IAA and IAA amide conjugates with amino acids bearing a free carboxylic group or a methyl ester group, along with some selected IAA metabolites, were studied in positive and negative electrospray ionization (ESI) modes, utilizing high-resolution mass spectrometry (HRMS) as a tool for their structural analysis. HRMS/MS spectra revealed the fragmentation patterns that enable us to identify IAA metabolites in plant extracts from eight vegetables of the Brassicaceae family using a fast and reliable ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS) method. The accurate m/z (mass to charge) ratio and abundance of the molecular and fragment ions of the studied compounds in plant extracts matched those obtained from commercially available or synthesized compounds and confirmed the presence of IAA metabolites.

Identification of antiplasmodial triterpenes from Keetia species using NMR-based metabolic profiling

IntroductionThe increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products.ObjectiveCreate a multivariate model to identify antiplasmodial metabolites from 1H NMR data of two African medicinal plants, Keetia leucantha and K. venosa.MethodsThe extracts of twigs and leaves of Keetia species were measured by 1H NMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation.ResultsUnsupervised 1H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS–DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples.ConclusionNMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region.

High-performance liquid chromatography drift-tube ion-mobility quadrupole time-of-flight/mass spectrometry for the identity confirmation and characterization of metabolites from three statins (lipid-lowering drugs) in the model plant cress (Lepidium sativum) after uptake from water

This work describes the metabolization of three different statins (lipid-lowering drugs) namely Atorvastatin, Fluvastatin and Simvastatin in the model plant cress (Lepidium sativum) after uptake from the growing medium. Analyzing plant extracts with HPLC hyphenated with a drift-tube ion-mobility quadrupole time-of-flight / mass spectrometer allowed the identity confirmation of more than 45 metabolites, resulting from oxidation/dehydrogenation, dehydration or hydroxylation of the parent drug or conjugation with amino acids and sugars. Metabolites were characterized by their retention times, m/z ratios, fragmentation patterns in MS/MS experiments, and their collision cross sections. Furthermore, a targeted analysis method for the trace-level analysis of the parent drugs as well as their metabolites in plant extracts was implemented by using HPLC coupled to triple quadrupole mass spectrometry in the multiple reaction monitoring mode. This approach was applied to study the metabolite distribution within the plant and to detect relative changes in metabolite concentrations as a function of growth time. Using a modified QuEChERS approach for extraction more than 50% of the metabolites could be still detected, if plants were exposed to only 1–10 μg L−1 of each statin.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction.

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.

Absolute quantification of metabolites in tomato fruit extracts by fast 2D NMR

Quantitative NMR metabolomics is a powerful tool to have access to valuable information on metabolism. Unfortunately, the quantitative analysis of metabolic samples is often hampered by peak overlap. Two-dimensional (2D) spectroscopy offers a promising alternative and quantitative results can be obtained provided that a calibration approach is employed. However, the duration of 2D NMR experiments is barely compatible with the metabolomic study of a large number of samples. This drawback can be circumvented by relying on “ultrafast” experiments capable of recording 2D spectra in a single-scan. While such experiments are not sensitive enough to match the concentrations of metabolic samples, a compromise can be reached by hybrid strategies capable of recording 2D NMR spectra of extracts in a few minutes only. The purpose of this study is to demonstrate that these multi-scan single-shot experiments can be successfully applied to the absolute quantification of major metabolites in plant extracts. Fast COSY experiments are recorded in 5 min on tomato fruit pericarp extracts at different stages of development. The concentration of eight major metabolites is determined with a trueness better than 10 % and a technical repeatability of a few percent. The experiments performed at two magnetic fields lead to similar quantitative results, in coherence with the metabolism of tomato fruit. The results show that fast 2D NMR methods form a promising tool for fast targeted metabolomics, and open promising perspective towards the automated and high-throughput quantitative analysis of large groups of plant and other samples for metabolomics and for the modelling of metabolism.

A quantitative structure-retention relationship (QSRR) model to aid plant metabolomic studies

Hyphenated analytical techniques are important tools for metabolomic studies of natural products. Predictive models for chromatographic retention time (tR) can accelerate the identification constituents in complex samples such as plant extracts. We developed a QSRR model using adjusted tR (t'R) information of 50 natural compounds spanning a wide range of chemical structure and polarity (Mr 148.161 – 610.565; calculated logP: -2.8 – 3.1) from the AsterDB [1] in-house compound collection. Chromatographic analysis was carried out by UHPLC-ESI-qTOF-MS/MS using a Dionex Acclaim RSLC 120 (C18, 2.1 × 100 mm, 2.2 µm) column and a binary gradient (MeCN-H2O and 0.1% formic acid), with pure compounds and with mixtures containing 10 and 50 compounds. Nonparametric Kruskal-Wallis test revealed no statistically significant difference for the t'R between the chromatographic analysis (p > 0.05). For designing a correlative model we used t'R as the dependent variable. As independent variables, 2D and 3D Boltzmann weighted molecular descriptors as calculated by MOE software [2] were used. Pre-processing of the descriptors was carried out with the Caret's package from R. Five descriptors were selected by Genetic Algorithm (GA) using MOE. We used four modelling tools: Multilayer Perceptron (MLP) with the back-propagation algorithm and Classifier Tree with the MP5 algorithm (MP5T) using the software Weka, and Linear Regression and PLS regression with five PLS-components using MOE. The training and test sets comprised of 36 and 14 compounds, respectively. The best model was obtained with MLP (Fig. 1), using ASAP1 [3], ASAP3 [3], POE VSA+3, logP and vsurf DD13 [2] as descriptors, and it yielded R2(calibration)= 0.85, Q2(cross validation)= 0.80 and P2(test set prediction)= 0.72. The resulting QSRR model can be used to predict retention data for a wide range of natural products and may become a valuable tool for the dereplication of secondary metabolites in plant extracts.

Screening for bioactive metabolites in plant extracts modulating glucose uptake and fat accumulation.

Dichloromethane and methanol extracts of seven different food and medicinal plants were tested in a screening platform for identification of extracts with potential bioactivity related to insulin-dependent glucose uptake and fat accumulation. The screening platform included a series of in vitro bioassays, peroxisome proliferator-activated receptor (PPAR) γ-mediated transactivation, adipocyte differentiation of 3T3-L1 cell cultures, and glucose uptake in both 3T3-L1 adipocytes and primary porcine myotubes, as well as one in vivo bioassay, fat accumulation in the nematode Caenorhabditis elegans. We found that dichloromethane extracts of aerial parts of golden root (Rhodiola rosea) and common elder (Sambucus nigra) as well as the dichloromethane extracts of thyme (Thymus vulgaris) and carrot (Daucus carota) were able to stimulate insulin-dependent glucose uptake in both adipocytes and myotubes while weekly activating PPARγ without promoting adipocyte differentiation. In addition, these extracts were able to decrease fat accumulation in C. elegans. Methanol extracts of summer savory (Satureja hortensis), common elder, and broccoli (Brassica oleracea) enhanced glucose uptake in myotubes but were not able to activate PPARγ, indicating a PPARγ-independent effect on glucose uptake.

Non-targeted analysis of tea by hydrophilic interaction liquid chromatography and high resolution mass spectrometry.

Tea is the second most consumed beverage in the world and its consumption has been associated with numerous potential health benefits. Factors such as fermentation methods, geographical origin and season can affect the primary and secondary metabolite composition of tea. In this study, a hydrophilic interaction liquid chromatography (HILIC) method coupled to high resolution mass spectrometry in both positive and negative ionisation modes was developed and optimised. The method when combined with principal component analysis to analyse three different types of tea, successfully distinguished samples into different categories, and provided evidence of the metabolites which differed between them. The accurate mass and high resolution attributes of the mass spectrometric data were utilised and relative quantification data were extracted post-data acquisition on 18 amino acids, showing significant differences in amino acid concentrations between tea types and countries. This study highlights the potential of HILIC chromatography combined with non-targeted mass spectrometric methods to provide a comprehensive understanding of polar metabolites in plant extracts.

Evaluation of Nonpolar Metabolites in Plant Extracts by 13C NMR Spectroscopy

(13)C nuclear magnetic resonance (NMR) spectroscopy was explored as a simple and efficient technique for the quantitative analysis of nonpolar metabolites in plants. The method was first optimized with a mixture of known metabolites and then applied to the nonpolar leaf extracts of plants harvested in the Valencian community (eastern Spain) belonging to three different genera: Euphorbia (Euphorbiaceae), Araujia (Apocynaceae), and Morus (Moraceae). Furthermore, an exhaustive analysis of Euphorbia characias leaf and stem extracts from different geographic locations allowed that quantitative (13)C NMR spectroscopy is a suitable tool for metabolic profiling purpose.

Important roles of the hyphenated HPLC‐DAD‐MS‐SPE‐NMR technique in metabonomics

Metabolite identification is a key step for metabonomics study. A fully automated hyphenation of HPLC-diode-array detector (DAD) mass spectrometry (MS) solid phase extraction (SPE)-NMR spectroscopy (HPLC-DAD-MS-SPE-NMR) is one of the most efficient methods to determine the structure of a given unknown metabolite in a complex mixture (metabonome) and hence represents one of the most important analytical techniques for the further development of metabonomics. In this review, some recent applications of this technique in identifying novel and trace metabolites in plant extracts and drug metabolism have been discussed. Modification of this hyphenated technique, enabling multiple trappings of strong polar metabolites for biofluids, needs further development.

A promising method for efficient analysis of secondary metabolites in plant extracts by a matrix-free Desorption/Ionization on self-Assembled Monolayer Surfaces (DIAMS) technique

Plants are one of the major sources for the biologically active organic compounds and play a key role in medicinal chemistry for the treatment of various diseases [1]. DIAMS method is able to determine the secondary metabolites of complex vegetal extracts. The high throughput analyses of vegetal extracts are relatively difficult to perform in MALDI mass spectrometry, since the preparation of the sample involves the co-crystallization of the matrix with the analyte. Moreover irradiation of the matrix ion produces many low-m/z vs high-intensity ions preventing the detection of low molecular weight molecules such as secondary metabolites. We have developed a matrix-free alternative to MALDI analyses by the means of an original desorption/ionization on self-assembled monolayers surfaces (DIAMS) technique [2]. Monolayers were formed by using novel thiophene and coumarin-triazole analogues that absorbs the laser beam at 337nm. We herein disclose our findings with respect to the DIAMS method which is well suitable for the detection and quantification of the low molecular weight compounds that are present in plant extracts. Some of the isoquinoline alkaloids from the root extracts of Thalictrum flavum have been detected by the DIAMS method. Indeed, this technique would be promising suitable for the qualitative and quantitative analysis of polar and non-polar organic components that are widely distributed in the plants, without any preliminary chromatographic resolution [3].