Assessment of 1H NMR spectroscopy and multivariate analysis as a technique for metabolite fingerprinting of Arabidopsis thaliana

An approach to metabolite fingerprinting of crude plant extracts that utilizes 1H nuclear magnetic resonance (NMR) spectroscopy and multivariate statistics has been tested. Using ecotypes of Arabidopsis thaliana as experimental material, a method has been developed for the rapid analysis of unfractionated polar plant extracts, enabling the creation of reproducible metabolite fingerprints. These fingerprints could be readily stored and compared by a variety of chemometric methods. Comparison by principal component analysis using SIMCA-P allowed the generation of residual NMR spectra of the compounds that contributed significantly to the differences between samples. From these plots, conclusions were drawn with respect to the identity and relative levels of metabolites differing between samples.     

Statistical multivariate metabolite profiling for aiding biomarker pattern detection and mechanistic interpretations in GC/MS based metabolomics

A strategy for robust and reliable mechanistic statistical modelling of metabolic responses in relation to drug induced toxicity is presented. The suggested approach addresses two cases commonly occurring within metabonomic toxicology studies, namely; 1) A pre-defined hypothesis about the biological mechanism exists and 2) No such hypothesis exists. GC/MS data from a liver toxicity study consisting of rat urine from control rats and rats exposed to a proprietary AstraZeneca compound were resolved by means of hierarchical multivariate curve resolution (H-MCR) generating 287 resolved chromatographic profiles with corresponding mass spectra. Filtering according to significance in relation to drug exposure rendered in 210 compound profiles, which were subjected to further statistical analysis following correction to account for the control variation over time. These dose related metabolite traces were then used as new observations in the subsequent analyses. For case 1, a multivariate approach, named Target Batch Analysis, based on OPLS regression was applied to correlate all metabolite traces to one or more key metabolites involved in the pre-defined hypothesis. For case 2, principal component analysis (PCA) was combined with hierarchical cluster analysis (HCA) to create a robust and interpretable framework for unbiased mechanistic screening. Both the Target Batch Analysis and the unbiased approach were cross-verified using the other method to ensure that the results did match in terms of detected metabolite traces. This was also the case, implying that this is a working concept for clustering of metabolites in relation to their toxicity induced dynamic profiles regardless if there is a pre-existing hypothesis or not. For each of the methods the detected metabolites were subjected to identification by means of data base comparison as well as verification in the raw data. The proposed strategy should be seen as a general approach for facilitating mechanistic modelling and interpretations in metabolomic studies.     

Metabolomic analysis using optimized NMR and statistical methods

NMR-based metabolomics requires robust automated methodologies, and the accuracy of NMR-based metabolomics data is greatly influenced by the reproducibility of data acquisition and processing methods. Effective water resonance signal suppression and reproducible spectral phasing and baseline traces across series of related samples are crucial for statistical analysis. We assess robustness, repeatability, sensitivity, selectivity, and practicality of commonly used solvent peak suppression methods in the NMR analysis of biofluids with respect to the automated processing of the NMR spectra and the impact of pulse sequence and data processing methods on the sensitivity of pattern recognition and statistical analysis of the metabolite profiles. We introduce two modifications to the excitation sculpting pulse sequence whereby the excitation solvent suppression pulse cascade is preceded by low-power water resonance presaturation pulses during the relaxation delay. Our analysis indicates that combining water presaturation with excitation sculpting water suppression delivers the most reproducible and information-rich NMR spectra of biofluids.     

Metabolomic analysis of the consequences of cadmium exposure in Silene cucubalus cell cultures via 1H NMR spectroscopy and chemometrics

Several essential and non-essential metals (typically those from periods 4, 5 and 6 in groups 11-15 in the periodic table) are commonly detoxified in higher plants by complexation with phytochelatin. The genetic and gross metabolic basis of metal tolerance in plants is, however, poorly understood. Here, we have analyzed plant cell extracts using 1H NMR spectroscopy combined with multivariate statistical analysis of the data to investigate the biochemical consequences of Cd(2+) exposure in Silene cucubalus cell cultures. Principal components analysis of 1H NMR spectra showed clear discrimination between control and Cd(2+) dosed groups, demonstrating the metabolic effects of Cd(2+) and thus allowing the identification of increases in malic acid and acetate, and decreases in glutamine and branched chain amino acids as consequences of Cd(2+) exposure. This work shows the value of NMR-based metabolomic approaches to the determination of biochemical effects of pollutants in naturally selected populations.     

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.     

Use of EDTA to minimize ionic strength dependent frequency shifts in the <Superscript>1</Superscript>H NMR spectra of urine

The ¹H NMR spectrum of urine exhibits a large number of detectable metabolites and is, therefore, highly suitable for the study of perturbations caused by disease, toxicity, nutrition or environmental factors in humans and animals. However, variations in the chemical shifts and intensities due to altered pH and ionic strength present a challenge in NMR-based studies. With a view towards understanding and minimizing the effects of these variations, we have extensively studied the effects of ionic strength and pH on the chemical shifts of common urine metabolites and their possible reduction using EDTA (ethylenediaminetetraacetic acid). ¹H NMR chemical shifts for alanine, citrate, creatinine, dimethylamine, glycine, histidine, hippurate, formate and the internal reference, TSP (trimethylsilylpropionic acid-d₄, sodium salt) obtained under different conditions were used to assess each effect individually. EDTA minimizes the frequency shifts of the metabolites that have a propensity for metal binding. Chelation of such metal ions is evident from the appearance of signals from EDTA complexed to divalent metal ions such as calcium and magnesium. Not surprisingly, increasing the buffer concentration or buffer volume also minimizes pH dependent frequency shifts. The combination of EDTA and an appropriate buffer effectively minimizes both pH dependent frequency shifts and ionic strength dependent intensity variations in urine NMR spectra. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

1H NMR based metabolite profiling for optimizing the ethanol extraction of Wolfiporia cocos

Metabolite profiling of Wolfiporia cocos (family: Polyporaceae) had been much advancement in recent days, and its analysis by nuclear magnetic resonance (NMR) spectroscopy has become well established. However, the highly important trait of W. cocos still needs advanced protocols despite some standardization. Partial least squares discriminant analysis (PLS-DA) was used as the multivariate statistical analysis of the ¹H NMR data set. The PLS-DA model was validated, and the key metabolites contributing to the separation in the score plots of different ethanol W. cocos extract. ¹H NMR spectroscopy of W. cocos identified 33 chemically diverse metabolites in D₂O, consisting of 13 amino acids, 11 organic acids 2 sugars, 3 sugar alcohols, 1 nucleoside, and 3 others. Among these metabolites, the levels of tyrosine, proline, methionine, sarcosine, choline, acetoacetate, citrate, 4-aminobutyrate, aspartate, maltose, malate, lysine, xylitol, lactate threonine, leucine, valine, isoleucine, uridine, guanidoacetate, arabitol, mannitol, glucose, and betaine were increased in the 95% ethanol extraction sample compared with the levels in other samples, whereas level of acetate, phenylalanine, alanine, succinate, and fumarate were significantly increased in the 0% ethanol extraction sample. A biological triterpenoid, namely pachymic acid, was detected from different ethanol P. cocos extract using ¹H-NMR spectra were found in CDCl₃. This is the first report to perform the metabolomics profiling of different ethanol W. cocos extract. These researches suggest that W. cocos can be used to obtain substantial amounts of bioactive ingredients for use as potential pharmacological and nutraceuticals agents.     

Development of analytical methods for NMR spectra and application to a 13C toxicology study

Metabolomics offers the potential to assess the effects of toxicants on metabolite levels. To fully realize this potential, a robust analytical workflow for identifying and quantifying treatment-elicited changes in metabolite levels by nuclear magnetic resonance (NMR) spectrometry has been developed that isolates and aligns spectral regions across treatment and vehicle groups to facilitate analytical comparisons. The method excludes noise regions from the resulting reduced spectra, significantly reducing data size. Principal components analysis (PCA) identifies data clusters associated with experimental parameters. Cluster-centroid scores, derived from the principal components that separate treatment from vehicle samples, are used to reconstruct the mean spectral estimates for each treatment and vehicle group. Peak amplitudes are determined by scanning the reconstructed mean spectral estimates. Confidence levels from Mann–Whitney order statistics and amplitude change ratios are used to identify treatment-related changes in peak amplitudes. As a demonstration of the method, analysis of ¹³C NMR data from hepatic lipid extracts of immature, ovariectomized C57BL/6 mice treated with 30 μg/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) or sesame oil vehicle, sacrificed at 72, 120, or 168 h, identified 152 salient peaks. PCA clustering showed a prominent treatment effect at all three time points studied, and very little difference between time points of treated animals. Phenotypic differences between two animal cohorts were also observed. Based on spectral peak identification, hepatic lipid extracts from treated animals exhibited redistribution of unsaturated fatty acids, cholesterols, and triacylglycerols. This method identified significant changes in peaks without the loss of information associated with spectral binning, increasing the likelihood of identifying treatment-elicited metabolite changes.     

Application of ultra-performance LC-TOF MS metabolite profiling techniques to the analysis of medicinal <Emphasis Type=Italic>Panax</Emphasis> herbs

The morphological appearance and some ingredients of Panax ginseng, Panax notoginseng and Panax japonicus of the Panax genus are similar. However, their pharmacological activities are obviously different due to the significant differences in the types and quantity of saponins in each herb. In the present study, ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS) was used to profile the abundances of metabolites in the three medicinal Panax herbs. Multivariate statistical analysis technique, that is, principle component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discriminate between the Panax samples. PCA of the analytical data showed a clear separation of compositions among the three medicinal herbs. The critical markers such as chikusetsusaponin IVa, ginsenoside R0, ginsenoside Rc, ginsenoside Rb1, ginsenoside Rb2 and ginsenoside Rg2 accountable for such variations were identified through the corresponding loading weights, and the tentative identification of biomarkers is completed by the accurate mass of TOFMS and high resolution and high retention time reproducibility performed by UPLC. The proposed analytical method coupled with multivariate statistical analysis is reliable to analyze a group of metabolites present in the herbal extracts and other natural products. This method can be further utilized to evaluate chemical components obtained from different plants and/or the plants of different geographical locations, thereby classifying the medicinal plant resources and potentially elucidating the mechanism of inherent phytochemical diversity.     

1H NMR and GC/MS metabolomics of earthworm responses to sub-lethal DDT and endosulfan exposure

The metabolic response of the earthworm Eisenia fetida to two pesticides, dichlorodiphenyltrichloroethane (DDT) and endosulfan, was characterized in contact tests using proton nuclear magnetic resonance (¹H NMR) and principal component analysis (PCA). PCA loading plots suggested that maltose, leucine and alanine were important metabolites contributing to the differences in dosed and control earthworms for both compounds at doses of 0.5, 1.0 and 2.0 μg/cm². Gas chromatography/mass spectrometry (GC/MS) was used to quantify the metabolites identified in E. fetida and determine if the changes in maltose, leucine and alanine following exposure to DDT and endosulfan (at 0.5 and 1.0 μg/cm²) were reproducible and greater than the natural variability. Quantification by GC/MS suggested that maltose was not a reliable biomarker since it both increased and decreased in earthworms exposed to DDT and increased by just 3% with exposure to endosulfan. Leucine was not stable with the GC/MS derivitization method used in this study and could not be confirmed as a reliable biomarker. However, alanine consistently increased for both DDT and endosulfan exposed E. fetida. Alanine showed considerable variability in control earthworms (±41.6%), yet the variability in alanine to glycine ratios was just ±10.5%. Increases in the alanine to glycine ratio were statistically significant at the P = 0.05 level for the 1.0 μg/cm² DDT dose and both the 0.5 and 1.0 μg/cm² endosulfan doses, suggesting that deviations from the normal homeostatic ratio of 1.5 for alanine to glycine is a potential biomarker of DDT and endosulfan exposure warranting further study. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Environmental Metabolomics Special Issue of Metabolomics.     

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.     

Positive correlations between hypericin and putative precursors detected in the quantitative secondary metabolite spectrum of Hypericum

A spectrum of eight pharmacologically important secondary compounds, all putatively belonging to the polyketide pathway (hypericin, pseudohypericin, emodin, hyperforin, hyperoside, rutin, quercetin, and quercitrin) were analyzed in several hypericin-producing species of Hypericum by LC–MS/MS. Different organs such as leaves, stems and roots of wild-grown plants of Hypericum hirsutum L., Hypericum maculatum Crantz s. l., Hypericum montanum L., Hypericum tetrapterum Fr. collected in Slovakia and of Hypericum perforatum L. collected in India were examined individually. Highest contents of hypericin, pseudohypericin, and emodin were found in H. montanum, suggesting that there are alternative species to H. perforatum with high pharmaceutical value. Amounts of hyperforin and quercetin were highest in H. perforatum, whereas highest contents of hyperoside and quercitrin were found in H. maculatum. A significant positive correlation between hypericin and pseudohypericin as well as between hypericin and emodin was observed by Kruskal’s multidimensional scaling (MDS), indicating a parallel enhancement of emodin as a common precursor in the biosynthetic pathways of hypericin and pseudohypericin. Furthermore, MDS combined with principal component analysis (PCA) revealed strong correlations in the occurrence of pseudohypericin and emodin, pseudohypericin and quercitrin, hypericin and quercitrin, emodin and quercitrin, hyperoside and quercitrin, rutin and quercetin, and, hyperforin and quercetin. On the other hand, rutin showed a negative correlation with emodin as well as with quercitrin. Furthermore, hierarchical agglomerative cluster analysis (HACA) clustered hypericin and pseudohypericin, grouping emodin at equal distance from both. Considerable infraspecific variability in secondary compound spectrum and load of different populations of H. maculatum from Slovakia underscores the need for detailed studies of genotypic variation and environmental factors in relation to polyketide biosynthesis and accumulation.     

Regional and developmental variations in metabolite concentration in the rat brain and eye: A study using1H NMR spectroscopy and high performance liquid chromatography

Regional and developmental changes in metabolite concentrations were measured by¹H NMR spectroscopy and HPLC of perchloric acid extracts from rat brain and eye. The highest concentrations of N-acetylaspartate were found in grey matter as opposed to white matter with concentration increasing with age from neonate to adult, while the related compound N-acetylaspartylglutamate was highest in adult optic nerve. Creatine and choline-containing compounds were present in all regions throughout development, with higher levels of creatine found in grey matter compared to other regions. Choline-containing compounds were present at the highest concentrations in the eye at all ages examined, and tended to decrease in concentration to minimum values in adulthood in all regions. The presence of hypotaurine in corpus callosum and optic nerve was consistent with the metabolic profiles of O-2A progenitor cells and oligodendrocytes, which are cells composing these tissues. The neurotransmitters glutamate and GABA reached their highest concentrations in the olfactory bulb (higher than in adult cortex). Special issue dedicated to Dr. Herman Bachelard.     

Assessment of similarities of pairs and groups of proteins using transformed amino-acid-residue data

Summary Using as a primary standard a representative set of 208 proteins whose amino-acid-residue mole frequencies have been accurately established, a set of standard distributions of mole frequencies is defined for each amino acid, in terms of which percentile values for the observed mole frequencies of the amino-acid residues in any other protein can be determined. Data so transformed have a distribution much closer to Gaussian than untransformed values, and allow meaningful determinations of correlations between the amino-acid-residue compositions of two proteins as well as between pairs of amino-acid-residues within groups of proteins. Of the 153 possible pairs of amino acids (Asx and Glx are used) 39 are significantly correlated atp 0.01 and 22 atp 0.001. A percentile table is included for those wishing to use the method with programmable calculators.The transformed data for amino-acid compositions have been used to perform principal components analyses on groups of proteins in order to determine if meaningful sub-groupings (observable clusters in scatter diagrams) were detectable. Such analyses are shown for the representative set of proteins and for a group of 184 globins. With regard to the globin chains, a correlation is observed for alpha chains in the first principal component projection (PCP), (accounting for 22% of the variance) with respect to the evolutionary time-scale while beta chains show such a correlation in the first and second PCPs (22% and 18% of the variance respectively). Thus, alpha and beta chains appear to diverge from a common progenitor, similar in position to globin chains from primitive forms. Furthermore, globins from primitive forms are nearer to one another than they are to globins from the vertebrates, a finding without a priori reason, suggesting perhaps that once a chain has reached a stable relationship with its environment, strong constraints are placed on the co-existing globin chains so that they maintain appropriate interaction with one another. In addition, positions of the epsilon, gamma and delta chains are in the order: epsilon (embryonal) more primitive than gamma (foetal) more primitive than delta equal to beta (adult).     

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.     

Factors affecting the occurrence and distribution of entomopathogenic fungi in natural and cultivated soils

Factors affecting the occurrence and distribution of entomopathogenic fungi in 244 soil samples collected from natural and cultivated areas in Spain were studied using an integrated approach based on univariate and multivariate analyses. Entomopathogenic fungi were isolated from 175 of the 244 (71.7 %) soil samples, with only two species found, Beauveria bassiana and Metarhizium anisopliae. Of the 244 soil samples, 104 yielded B. bassiana (42.6 %), 18 yielded M. anisopliae (7.3 %), and 53 soil samples (21.7 %) harboured both fungi. Log-linear models indicated no significant effect of habitat on the occurrence of B. bassiana, but a strong association between M. anisopliae and soils from cultivated habitats, particularly field crops. Also, irrespective of habitat type, B. bassiana predominated over M. anisopliae in soils with a higher clay content, higher pH, and lower organic matter content. Logistic regression analyses showed that pH and clay content were predictive variables for the occurrence of B. bassiana, whereas organic matter content was the predictive variable for M. anisopliae. Also, latitude and longitude predicted the occurrence of these same species, but in opposite directions. Altitude was found to be predictive for the occurrence of B. bassiana. Using principal component analysis, four factors (1 to 4) accounted for 86 % of the total variance; 32.8, 22.9, 19.6 and 10.4 % of the cumulative variance explained, respectively. Factor 1 was associated with high positive weights for soil clay and silt content and high negative weights for soil sand content. Factor 2 was associated with high positive weights for soil organic matter content and high negative weights for soil pH. Factor 3 was associated with high positive weights for latitude and longitude of the sampled localities and factor 4, had high positive weights only for the altitude. Bi-plot displays representing soil samples were developed for different factor combinations and indicated that, irrespective of geographical location, absence of both fungal species was determined by alkaline sandy soils with low organic matter content, whereas heaviness of soil texture, acidity and increasing organic matter content led to progressively higher percentages of samples harbouring entomopathogenic fungi. These results could aid decision-making as to whether or not a particular cultivated or natural soil is suitable for using entomopathogenic fungi as a pest control measure and for selecting the fungal species best suited to a particular soil.     

Complete assignments of the (1)H and (13)C chemical shifts and J(H,H) coupling constants in NMR spectra of D-glucopyranose and all D-glucopyranosyl-D-glucopyranosides

Complete assignment of the (1)H and (13)C NMR spectra of all possible d-glucopyranosyl-d-glucopyranosides was performed and the (1)H chemical shifts and proton-proton coupling constants were refined by computational spectral analyses (using PERCH NMR software) until full agreement between the calculated and experimental spectra was achieved. To support the experimental results, the (1)H and (13)C chemical shifts and the spin-spin coupling constants between the non-hydroxyl protons of alpha- and beta-d-glucopyranose (1a and 1b) were calculated with density functional theory (DFT) methods at the B3LYP/pcJ-2//B3LYP/6-31G(d,p) level of theory. The effects of different glycosidic linkage types and positions on the glucose ring conformations and on the alpha/beta-ratio of the reducing end hydroxyl groups were investigated. Conformational analyses were also performed for anomerically pure forms of methyl d-glucopyranosides (13a and 13b) and fully protected derivatives such as 1,2,3,4,6-penta-O-acetyl-d-glucopyranoses (14a and 14b).     

Development of a 1H NMR structural-reporter-group concept for the primary structural characterisation of alpha-D-glucans

An NMR study of proton chemical shift patterns of known linear alpha-D-glucopyranose di- and trisaccharide structures was carried out. Chemical shift patterns for (alpha1-->2)-, (alpha1-->3)-, (alpha1-->4)- and (alpha1-->6)-linked D-glucose residues were analysed and compared to literature data. Using these data, a 1H NMR structural-reporter-group concept was formulated to function as a tool in the structural analysis of alpha-D-glucans.