Metabolomic profiling of Cheonggukjang during fermentation by 1H NMR spectrometry and principal components analysis

Metabolomic analysis of extracts of Cheonggukjang was carried out using ¹H nuclear magnetic resonance (NMR) spectrometry and principal components analysis (PCA). The major peaks in the ¹H NMR spectra of the 50% methanol fraction were assigned to isoleucine/leucine, lactate, alanine, acetic acid, citric acid, choline, fructose, sucrose, tyrosine, phenylalanine and formic acid. The first two principle components (PC1 and PC2) of the ¹H NMR spectra of the aqueous fraction allowed discrimination of Cheonggukjang extracts of samples obtained after different periods of fermentation. These two principal components cumulatively accounted for 98.5% of the total variation of all variables. The major peaks within the ¹H NMR spectra that contributed to discrimination of different samples were assigned to isoleucine/leucine, lactate, acetic acid, citric acid, choline, fructose, glucose and sucrose. This metabolomic analysis of samples of Cheonggukjang extract demonstrates that NMR and PCA can be used to obtain standard trajectory plots and related information for Cheonggukjang and other fermented foods.     

Metabolic fingerprinting of wild type and transgenic tobacco plants by 1H NMR and multivariate analysis technique

The metabolomic analysis of wild type and constitutive salicylic acid producing tobacco plants (CSA tobacco, Nicotiana tabacum 'Samsun' NN) plants overexpressing salicylate biosynthetic genes was carried out by 1H NMR spectrometry and multivariate analysis techniques. The principle component analysis (PCA) of the 1H NMR spectra showed a clear discrimination between those samples by PC1 and PC2. The discrimination of non-inoculated, TMV-virus inoculated, and systemic leaves or veins could also be obtained by PCA analysis. Major peaks in 1H NMR spectra contributing to the discrimination were assigned as those of chlorogenic acid, malic acid, and sugars. This method allows an efficient differentiation between wild type and transgenic plants without any pre-purification steps.     

Metabolic Discrimination of Catharanthus roseus Calli According to Their Relative Locations Using 1H-NMR and Principal Component Analysis

Creating a plant-cell suspension culture involves first transferring the callus into liquid media, but there are no objective criteria for selecting the location of the callus to be transferred. In this study, inner and outer cells of Catharanthus roseus with various elicitors in solid-state cultures were differentiated by ¹H NMR (nuclear magnetic resonance) spectrometry and principal component analysis (PCA). It was found that the samples of various elicitors and relative locations could be separated in PCA-derived score plots. Especially, there was a clear separation between nontreated samples and those cotreated with silver nitrate and methyl jasmonate. Loading-plot analysis was therefore applied to data obtained from nontreated samples and those cotreated with silver nitrate and methyl jasmonate to determine the separation of major metabolites on score plots. The levels of valine, lactic acid, threonine, alanine, arginine, acetic acid, malic acid, succinic acid, citric acid, asparagine, choline, lactose, fumaric acid, phenylalanine, tryptophan, and formic acid were higher in the inner callus than in the outer callus, whereas 2-oxoglutaric acid, oxalacetic acid, sucrose, and glucose dominated in the outer callus. The results obtained in this study suggest that inner and outer calli can be differentiated by ¹H-NMR-based metabolomic analysis.     

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

Background and Aims

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (¹H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although ¹H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors.

Methods and Results

We applied ¹H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses.

Conclusions

Differences in grape-derived metabolites associated with genetic differences alone are a major source of ¹H NMR-based discrimination of wines and ¹H NMR has the capacity to discriminate between very closely related cultivars.

Significance of the Study

The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by ¹H NMR-PCA/PLS and indicates that ¹H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.     

<Superscript>1</Superscript>H NMR metabolic fingerprinting of saffron extracts

The aim of this study was to explore feasibility of ¹H NMR metabolic fingerprinting for discrimination of authenticity of saffron using principal component analysis (PCA) modeling. Authentic reference Iranian saffron (n = 31) and commercial samples (n = 32) were used. Cross-validated PCA models based on ¹H NMR spectra of solutions prepared by direct extraction of grinded saffron with methanol-d ₄ distinguished reference Iranian saffron samples from commercial samples that formed several distinct clusters, some of which represent falsified samples as confirmed by microscopic analysis. The production sites and drying conditions of the authentic reference Iranian samples were not reflected in the current dataset. Picrocrocin and glycosyl esters of crocetin emerged as the most important ¹H NMR markers of authentic saffron by using statistical correlation spectroscopy. In conclusion, ¹H NMR spectra of saffron extracts combined with pattern recognition by PCA provide immediate means of unsupervised classification of saffron samples.     

Taxonomic discrimination of cyanobacteria by metabolic fingerprinting using proton nuclear magnetic resonance spectra and multivariate statistical analysis

When whole-cell extracts are analyzed, proton nuclear magnetic resonance (¹H NMR) spectroscopy provides biochemical profiles that contain overlapping signals of the majority of the compounds. To determine whether cyanobacteria could be taxonomically discriminated on the basis of metabolic fingerprinting, we subjected whole-cell extracts of the cyanobacteria to¹H NMR. The¹H NMR spectra revealed a predominance of signals in the aliphatic region. Principal component analysis (PCA) of the data then enabled discrimination of the cyanobacteria. The hierarchical dendrogram, based on PCA of the aliphatic region data, showed that six cyanobacterial taxa were discriminated from two eukaryotic microalgal species, and that the six taxa could be subsequently divided into three groups. This agrees with the current taxonomy of cyanobacteria. Therefore, our overall results indicate that metabolic fingerprinting using¹H NMR spectra and multivariate statistical analysis provide a simple, rapid method for the taxonomical discrimination of cyanobacteria.     

A metabolomic approach to study the rhizodeposition in the tritrophic interaction: tomato,Pochonia chlamydosporia and Meloidogyne javanica

A combined chemometrics-metabolomics approach [excitation–emission matrix (EEM) fluorescence spectroscopy, nuclear magnetic resonance (NMR) and high performance liquid chromatography–mass spectrometry (HPLC–MS)] was used to analyse the rhizodeposition of the tritrophic system: tomato, the plant-parasitic nematode Meloidogyne javanica and the nematode-egg parasitic fungus Pochonia chlamydosporia. Exudates from M. javanica roots were sampled at root penetration (early) and gall development (late). EMM indicated that late root exudates from M. javanica treatments contained more aromatic amino acid compounds than the rest (control, P. chlamydosporia or P. chlamydosporia and M. javanica). ¹H NMR showed that organic acids (acetate, lactate, malate, succinate and formic acid) and one unassigned aromatic compound (peak no. 22) were the most relevant metabolites in root exudates. Robust principal component analysis (PCA) grouped early exudates for nematode (PC1) or fungus presence (PC3). PCA found (PC1, 73.31 %) increased acetate and reduced lactate and an unassigned peak no. 22 characteristic of M. javanica root exudates resulting from nematode invasion and feeding. An increase of peak no. 22 (PC3, 4.82 %) characteristic of P. chlamydosporia exudates could be a plant “primer” defence. In late ones in PC3 (8.73 %) the presence of the nematode grouped the samples. HPLC–MS determined rhizosphere fingerprints of 16 (early) and 25 (late exudates) m/z signals, respectively. Late signals were exclusive from M. javanica exudates confirming EEM and ¹H NMR results. A 235 m/z signal reduced in M. javanica root exudates (early and late) could be a repressed plant defense. This metabolomic approach and other rhizosphere -omics studies could help to improve plant growth and reduce nematode damage sustainably.     

Metabolic classification of South American Ilex species by NMR-based metabolomics

The genus Ilex to which mate (Ilex paraguariensis) belongs, consists of more than 500 species. A wide range of metabolites including saponins and phenylpropanoids has been reported from Ilex species. However, despite the previous works on the Ilex metabolites, the metabolic similarities between species which can be used for chemotaxonomy of the species are not clear yet. In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomics was applied to the classification of 11 South American Ilex species, namely, Ilex argentina, Ilex brasiliensis, Ilex brevicuspis, Ilex dumosa var. dumosa, I. dumosa var. guaranina, Ilex integerrima, Ilex microdonta, I. paraguariensis var. paraguariensis, Ilex pseudobuxus, Ilex taubertiana, and Ilex theezans. ¹H NMR combined with principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) showed a clear separation between species and resulted in four groups based on metabolomic similarities. The signal congestion of ¹H NMR spectra was overcome by the implementation of two-dimensional (2D)-J-resolved and heteronuclear single quantum coherence (HSQC). From the results obtained by 1D- and 2D-NMR-based metabolomics it was concluded that species included in group A (I. paraguariensis) were metabolically characterized by a higher amount of xanthines, and phenolics including phenylpropanoids and flavonoids; group B (I. dumosa var. dumosa and I. dumosa var. guaranina) with oleanane type saponins; group C (I. brasiliensis, I. integerrima, I. pseudobuxus and I. theezans) with arbutin and dicaffeoylquinic acids, and group D (I. argentina, I. brevicuspis, I. microdonta and I. taubertiana) with the highest level of ursane-type saponins. Clear metabolomic discrimination of Ilex species and varieties in this study makes the chemotaxonomic classification of Ilex species possible.     

Urinary metabolomic phenotyping of nickel induced acute toxicity in rat: an NMR spectroscopy approach

The metabolomic approach has been widely used in toxicology to investigate mechanisms of toxicity. To understand the mammalian system??s response to nickel exposure, we analysed the NiCl₂ induced metabolomic changes in urine of rats using ¹H nuclear magnetic resonance (¹H NMR) spectroscopy together with clinically relevant biochemical parameters. Male Sprague?CDawley rats were administered intraperitoneally with NiCl₂ at doses of 4, 10 and 20?mg/kg body weight. Urine samples were collected at 8, 16, 24, 72, 96 and 120?h post treatment. The metabolomic profile of rat urine showed prominent changes in citrate, dimethylamine, creatinine, choline, trimethylamine oxide (TMAO), phenyl alanine and hippurate at all doses. Principal component analysis of urine ¹H NMR spectra demonstrated the dose and time dependent development of toxicity. The metabolomic time trajectory, based on pattern recognition analysis of ¹H NMR spectra of urine, illustrated clear separation of pre and post treatments (temporal). Only animals treated with a low dose of NiCl₂ returned to normal physiology. The ¹H NMR spectral data correlated well with the clinically relevant nephrotoxic biomarkers. The urinary metabolomic phenotyping for NiCl₂ induced nephrotoxicity was defined according to the predictive ability of the known metabolite biomarkers, creatinine, citrate and TMAO. The current approach demonstrates that metabolomics, one of the most important platform in system biology, may be a promising tool for identifying and characterizing biochemical responses to toxicity.     

Chemometric variance analysis of 1H NMR metabolomics data on the effects of oral rinse on saliva

Saliva is an easy to obtain bodily fluid that is specific to the oral environment. It can be used for metabolomic studies as it is representative of the overall wellbeing of an organism, as well as mouth health and bacterial flora. The metabolomic structure of saliva varies greatly depending on the bacteria present in the mouth as they produce a range of metabolites. In this study we have investigated the metabolomic profiles of human saliva that were obtained using ¹H NMR (nuclear magnetic resonance) analysis. 48 samples of saliva were collected from 16 healthy subjects over 3 days. Each sample was split in two and the first half treated with an oral rinse, while the second was left untreated as a control sample. The 96 ¹H NMR metabolomic profiles obtained in the dataset are affected by three factors, namely 16 subjects, 3 sampling days and 2 treatments. These three factors contribute to the total variation in the dataset. When analysing datasets from saliva using traditional methods such as PCA (principal component analysis), the overall variance is dominated by subjects’ contributions, and we cannot see trends that would highlight the effect of specific factors such as oral rinse. In order to identify these trends, we used methods such as MSCA (multilevel simultaneous component analysis) and ASCA (ANOVA simultaneous component analysis), that provide variance splits according to the experimental factors, so that we could look at the particular effect of treatment on saliva. The analysis of the treatment effect was enhanced, as it was isolated from the overall variance and assessed without confounding factors.

     

Classification of commercial cultivars of Humulus lupulus L. (hop) by chemometric pixel analysis of two dimensional nuclear magnetic resonance spectra

The development of fast and effective spectroscopic methods that can detect most compounds in an untargeted manner is of increasing interest in plant extracts fingerprinting or profiling projects. Metabolite fingerprinting by nuclear magnetic resonance (NMR) is a fast growing field which is increasingly applied for quality control of herbal products, mostly via 1D ¹H NMR coupled to multivariate data analysis. Nevertheless, signal overlap is a common problem in ¹H NMR profiles that hinders metabolites identification and results in incomplete data interpretation. Herein, we introduce a novel approach in coupling 2D NMR datasets with principal component analysis (PCA) exemplified for hop resin classification. Heteronuclear multiple bond correlation (HMBC) profile maps of hop resins (Humulus lupulus) were generated for a comparative study of 13 hop cultivars. The method described herein combines reproducible metabolite fingerprints with a minimal sample preparation effort and an experimental time of ca. 28 min per sample, comparable to that of a standard HPLC run. Moreover, HMBC spectra provide not only unequivocal assignment of hop major secondary metabolites, but also allow to identify several isomerization and degradation products of hop bitter acids including the sedative principal of hop (2-methylbut-3-en-2-ol). We do believe that combining 2D NMR datasets to chemometrics, i.e. PCA, has great potential for application in other plant metabolome projects of (commercially relevant) nutraceuticals and or herbal drugs.     

Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics

¹H nuclear magnetic resonance (¹H NMR)-based metabolomics was utilized to elucidate the earthworm sub-lethal toxicity after exposure to the persistent environmental contaminant phenanthrene. Earthworms were exposed to 0.05, 0.2 and 0.4 mg/cm² of phenanthrene [which correspond to 1/32nd to 1/4th of the 48-h LC₅₀ (concentration that causes 50 % mortality), respectively] via contact tests over 1, 2 and 3 days of dermal contact. ¹H NMR-based metabolomic analysis of the polar and non-polar fractions of the earthworm tissue extracts revealed heightened Eisenia fetida toxic responses with both longer exposure times and higher phenanthrene concentrations. Principal component analysis (PCA) of the polar fraction showed significant separation between control and exposed earthworms along PC1 for all phenanthrene concentrations on each day. The PCA of the non-polar fraction showed significant separation between the controls and exposed earthworms for only the first day of exposure. These results suggested that alanine, glutamate, maltose, and fatty acids were potential indicators of phenanthrene exposure. Interruption in energy production due to a deactivation of the succinate dehydrogenase enzyme in the Krebs cycle was also postulated in exposed earthworms. Cross-validated partial least squares-regression models showed that the polar metabolic profile of E. fetida was weakly but significantly correlated to phenanthrene exposure concentrations after day 1 and day 2 of exposure. Overall, this study indicates that with longer exposures, contact time becomes more important than concentration in discriminating between control and exposed earthworms. This study also shows that NMR-based metabolomics has promise as a powerful ecotoxicological tool for elucidating the mode of toxicity of contaminants.     

Genetic discrimination between<Emphasis Type="Italic">Catharanthus roseus</Emphasis> cultivars by metabolic fingerprinting using<Superscript>1</Superscript>H NMR spectra of aromatic compounds

When whole cell extracts are subjected to proton nuclear magnetic resonance spectroscopy (¹H NMR), metabolite profiles are generated that contain overlapping signals of the majority of compounds within the extract. In order to determine whether pattern recognition based on the metabolite profiles of higher plants is able to genetically discriminate between plants, we analyzed leaf samples of eight cultivars ofCatharanthus roseus by¹H NMR. Hierarchical dendrograms, based on the principal component analysis of the¹H NMR total, aliphatic carbohydrate and aromatic region data, revealed possible relationships between the cultivars. The dendrogram based on the aromatic region data was in general agreement with the genetic relationships determined by conventional DNA fingerprinting methods. Secologanin and polyphenols were assigned to the signals of the¹H NMR spectra, and contributed most profoundly to the discrimination between cultivars. The overall results indicate that the genetic relationships betweenC. roseus cultivars are reflected in the differences of the aromatic compounds in the leaves.     

NMR metabolomic of frontal cortex extracts: First study comparing two neurodegenerative diseases,Alzheimer disease and amyotrophic lateral sclerosis

ObjectiveThis study was designed to assess the brain metabolites’ variability between two neurodegenerative diseases in frontal cortex samples obtained post-mortem. NMR metabolomics was used for the first time in this context.Materials and methods¹H NMR metabolomic was applied to tissue extracts from patients with Alzheimer disease (ALZ) and patients with amyotrophic lateral sclerosis (ALS) to investigate qualitative and quantitative variations of brain metabolites.ResultsThe Alzheimer disease metabolic signature was characterized by a high concentration of alanine, acetate, glutamate and glutamine, and low concentrations of lactate and creatine, while the ALS metabolic signature appears to be marked by high concentrations of lactate, N-acetyl aspartate, creatine, choline and myo-inositol. Moreover, in vitro ¹H NMR could detect metabolites such as 3-hydroxybutyrate, alanine, succinate and aspartate that cannot be detected with in vivo NMR.DiscussionThe neurodegenerative diseases exhibit diverging metabolic pathways. Some of the metabolites responsible for the discrimination between the two diseases were detected before in vivo. However, this in vitro metabolomic investigation demonstrates the involvement of metabolites not detected with in vivo studies.ConclusionUpon these findings, in vitro metabolomics appears to be an efficient tool to investigate the fundamentals of the metabolic pathway modulations in these neurodegenerative diseases to help the interpretation of clinical data obtained with in vivo NMR spectroscopy.     

Biological variation of Vanilla planifolia leaf metabolome

The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out using ¹H-nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis in order to evaluate their variation. Ontogenic changes of the metabolome were considered since leaves of different ages were collected at two different times of the day and in two different seasons. Principal component analysis (PCA) and partial least square modeling discriminate analysis (PLS-DA) of ¹H NMR data provided a clear separation according to leaf age, time of the day and season of collection. Young leaves were found to have higher levels of glucose, bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A) and bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-(2-butyl)-tartrate (glucoside B), whereas older leaves had more sucrose, acetic acid, homocitric acid and malic acid. Results obtained from PLS-DA analysis showed that leaves collected in March 2008 had higher levels of glucosides A and B as compared to those collected in August 2007. However, the relative standard deviation (RSD) exhibited by the individual values of glucosides A and B showed that those compounds vary more according to their developmental stage (50%) than to the time of day or the season in which they were collected (19%). Although morphological variations of the V. planifolia accessions were observed, no clear separation of the accessions was determined from the analysis of the NMR spectra. The results obtained in this study, show that this method based on the use of ¹H NMR spectroscopy in combination with multivariate analysis has a great potential for further applications in the study of vanilla leaf metabolome.     

高分辨魔角旋转核磁共振和主成分分析研究人类低级星形细胞瘤和脑膜瘤的代谢组特征

采用高分辨魔角旋转核磁共振（HRMAS ^1H NMR）技术结合主成分分析（PCA）方法研究了39例人体脑肿瘤组织的代谢组特征．39例肿瘤样本分别来自39个脑肿瘤患者,包括15例低级星形细胞瘤,13例纤维型脑膜瘤和11例过渡型脑膜瘤．核磁共振波谱分析结果表明,脑肿瘤组织的代谢组中丰要含有脂肪酸、乳酸、胆碱代谢物（如胆碱、磷酸胆碱和甘油磷酸胆碱）、氯基酸（如丙氨酸、谷氨酸、谷氮酰胺、牛磺酸）、N-乙酰天门冬氨酸（NAA）和谷胱甘肽等代谢物．通过对核磁共振谱进行主成分分析（PCA）,发现低级星形细胞瘤和脑膜瘤的代谢组之间具有明显的差异,而在过渡型和纤维型两个亚类脑膜瘤之间该差别相对较小．与脑膜瘤相比,低级星形细胞瘤中甘油磷酸胆碱、磷酸胆碱、肌醇与肌酸的含量较高,而丙氨酸、谷氨酸、谷氨酰胺、谷胱甘肽和牛磺酸的含量较低．NAA的含量在低级星形细胞瘤中尽管较低但能观察到,而脑膜瘤中却未发现NAA的信号．结果衷明,HRMAS ^1H NMR和多变量统计分析相结合的组织代谢组学方法,不仅能有效区分不同类型的脑肿瘤,而且还可以为脑肿瘤提供丰富的代谢组信息,这些信息对研究肿瘤发生发展的机制具有潜在的意义．     

Classification of Fermented Soymilk during Fermentation by 1H NMR Coupled with Principal Component Analysis and Elucidation of Free-Radical Scavenging Activities

Changes in metabolites in fermented soymilk prepared with selected Bifidobacterium and Streptococci strains were analyzed using a ¹H-NMR-based metabolomic technique. Principal components analysis (PCA) allowed the clear separation of 50% methanol extracts from fermented soymilk with different fermentation times by combining principal components PC1 and PC3, which accounted for 55.1% of the total variance. Loading plot analysis was performed to select major compounds contributing to the separation, and the relative levels of selected metabolites were determined. In addition, the free-radical scavenging activities of each sample were investigated, and the underlying mechanisms were elucidated by determining the total phenolics and total flavonoids contents of each sample. The present study suggests the usefulness of combining ¹H-NMR with PCA in discriminating fermented soymilk samples with different fermentation times, and elucidates of the factors affecting free-radical scavenging activities of fermented soymilk.     

Evaluation of Metabolomic Changes as a Biomarker of Chondrogenic Differentiation in 3D-cultured Human Mesenchymal Stem Cells Using Proton (1H) Nuclear Magnetic Resonance Spectroscopy

Purpose

The purpose of this study was to evaluate the metabolomic changes in 3D-cultured human mesenchymal stem cells (hMSCs) in alginate beads, so as to identify biomarkers during chondrogenesis using ¹H nuclear magnetic resonance (NMR) spectroscopy.

Materials and Methods

hMSCs (2×10⁶ cells/mL) were seeded into alginate beads, and chondrogenesis was allowed to progress for 15 days. NMR spectra of the chondrogenic hMSCs were obtained at 4, 7, 11, and 15 days using a 14.1-T (600-MHz) NMR with the water suppression sequence, zgpr. Real-Time polymerase chain reaction (PCR) was performed to confirm that that the hMSCs differentiated into chondrocytes and to analyze the metabolomic changes indicated by the NMR spectra.

Results

During chondrogenesis, changes were detected in several metabolomes as hMSC chondrogenesis biomarkers, e.g., fatty acids, alanine, glutamate, and phosphocholine. The metabolomic changes were compared with the Real-Time PCR results, and significant differences were determined using statistical analysis. We found that changes in metabolomes were closely related to biological reactions that occurred during the chondrogenesis of hMSCs.

Conclusions

In this study, we confirm that metabolomic changes detected by ¹H-NMR spectroscopy during chondrogenic differentiation of 3D-cultured hMSCs in alginate beads can be considered as biomarkers of stem cell differentiation.     

Comparative metabolite profiling and fingerprinting of medicinal licorice roots using a multiplex approach of GC–MS,LC–MS and 1D NMR techniques

Glycyrrhiza glabra, commonly known as licorice, is a popular herbal supplement used for the treatment of chronic inflammatory conditions and possesses anticancer and antiviral activities. This species contains a plethora of phytochemicals including terpenoids, saponins, flavonoids, polyamines and polysaccharides. The full complement of bioactive compounds has yet to be elucidated, a step necessary in order to explain its medicinal use. There are over 30 species in the Glycyrrhiza genus world-wide, most of which have been little characterized in terms of phytochemical or pharmacological properties. Here, large scale multi-targeted metabolic profiling and fingerprinting techniques were utilized to help gain a broader insight into Glycyrrhiza species chemical composition. UV, MS and NMR spectra of extracted components were connected with NMR, MS, and multivariate analyses data from Glycyrrhiza glabra, Glycyrrhiza uralensis, Glycyrrhiza inflata and Glycyrrhiza echinata. Major peaks in ¹H NMR and MS spectra contributing to the discrimination among species were assigned as those of glycyrrhizin, 4-hydroxyphenyl acetic acid, and glycosidic conjugates of liquiritigenin/isoliquiritigenin. Primary metabolites profiling using GC–MS revealed the presence of cadaverine, an amino acid, exclusively found in G. inflata roots. Both LC–MS and NMR were found effective techniques in sample classification based on genetic and or geographical origin as revealed from derived PCA analysis.     

Two Cyclic Dipeptides from Pseudomonas fluorescens GcM5-1A Carried by the Pine Wood Nematode and Their Toxicities to Japanese Black Pine Suspension Cells and Seedlings in vitro

Pseudomonas fluorescens GcM5-1A, isolated from the pine wood nematode (PWN), Bursaphelenchus xylophilus, was cultured in Luria Broth medium (LB). The clarified culture was extracted with ethyl acetate, and two dipeptides were purified from the extract. The chemical structures of 1 and 2 were identified as cyclo(-Pro-Val-)and cyclo(-Pro-Tyr-), respectively, by MS, ¹H NMR, ¹³C NMR,¹H-¹H COSY, 1H -¹³C COSY spectra. Bioassay results showed that the two compounds were toxic to both suspension cells and seedlings of Pinus thunbergii, which may offer some clues to research the mechanism of pine wilt disease caused by PWN.