NMR metabolomic approaches for plants, toxicology and medicine

NMR metabolomic approaches for plants, toxicology and medicine This article describes the principles as well as the analytical and chemometric tools that support the development of NMR metabolomic approaches. These analytical methods are illustrated through a range of selected examples in various domains of biology and medicine, concerning the study of genetically modified organisms, plant/environment interactions, environmental toxicology, pharmacology, cancerology, or molecular epidemiology

Développement d une méthodologie combinée RMN Haute Résolution à Rotation à l Angle Magique (HRMAS) et chimiométrie pour l étude de produits alimentaires

Pour déterminer l authenticité de produits alimentaires, plusieurs techniques analytiques (CLHP, SM, RMN liquide) sont traditionnellement utilisées. Celles-ci sont d autant plus efficaces que les substances analysées sont homogènes. Cependant, de nombreux aliments n étant ni liquides, ni solides, il est nécessaire de procéder à des extractions susceptibles d altérer l échantillon. Cette thèse illustre le potentiel de la RMN Haute Résolution à Rotation à l Angle Magique (HRMAS) pour l étude de produits alimentaires bruts (fromage, viande), permettant l attribution de la majorité des signaux 1H, ainsi que l exploitation des informations contenues dans leurs spectres 1H HRMAS par des méthodes statistiques multivariées (ACP, AD, PLS-DA) afin d en extraire des marqueurs de qualité ou d origine. La méthode HRMAS/Chimiométrie a permis la caractérisation du Parmigiano Reggiano suivant son âge d affinage, et de l Emmental et de la viande de bœuf séchée suivant leur origine géographique.AIX-MARSEILLE3-BU Sc.St Jérô (130552102) / SudocSudocFranceF

Molecular signal suppression by in situ microextraction in nuclear magnetic resonance spectroscopy.

International audienceThe detailed characterization of complex mixtures by NMR is often hampered by the presence of signals from uninformative compounds, the resonances of which overlap with those of the molecules of interest. We provide here a proof of principle for an approach to NMR signal suppression in complex samples using Molecularly Imprinted Polymers (MIPS). Addition of a few milligrams of polymer to a solution traps the target molecule in typical micromolar to millimolar concentration, thus achieving in situ signal suppression, without altering any other spectral features. This method minimized any manipulation or perturbation of the spectrum and was applied to a complex mixture of known compounds and to a plant extract, in both cases spiked with a compound (bisphenol A), which was subsequently removed by selective binding to a complementary MIP. What is described in this report is comparable with microextraction and may in due course be applied to a large number of analytical challenges

La métabolomique par RMN et ses applications en biologie végétale, toxicologie et médecine

National audienceCet article présente les principes ainsi que les outils analytiques et chimiométriques qui sont au cœur du développement des approches d'analyse métabolomique par RMN. Il en illustre les applications variées au travers d'exemples choisis dans différents domaines de la biologie et de la médecine, concernant l'étude des organismes génétiquement modifiés, les interactions plantes/environnement, la toxicologie environnementale, la pharmacologie, la cancérologie ou l'épidémiologie moléculaire

Proteomics, and metabolomics: magnetic resonance spectroscopy for the presurgical screening of thyroid nodules.

none3siWe review the progress and state-of-the-art applications of studies in Magnetic Resonance Spectroscopy (MRS) and Imaging as an aid for diagnosis of thyroid lesions of different nature, especially focusing our attention to those lesions that are cytologically undetermined. It appears that the high-resolution of High-Resolution Magic-Angle-Spinning (HRMAS) MRS improves the overall accuracy of the analysis of thyroid lesions to a point that a significant improvement in the diagnosis of cytologically undetermined lesions can be expected. This analysis, in the meantime, allows a more precise comprehension of the alterations in the metabolic pathways induced by the development of the different tumors. Although these results are promising, at the moment, a clinical application of the method to the common workup of thyroid nodules cannot be used, due to both the limitation in the availability of this technology and the wide range of techniques, that are not uniformly used. The coming future will certainly see a wider application of these methods to the clinical practice in patients affected with thyroid nodules and various other neoplastic diseases.Minuto, MN; Shintu, L; Caldarelli, SMinuto, Michele; Shintu, L; Caldarelli, S

Metabolomics and the Detection of Unintended Effects in Genetically Modified Crops

The chapter describes current procedures for the safety assessment of genetically modified crops and foods. The concepts of substantial equivalence, the conventional comparator, and intended and unintended effects are introduced. Most published examples of substantial equivalence testing deal with crops that have been modified for insect resistance or herbicide tolerance. A standard procedure has developed based on broadly similar field trial designs, sampling schemes and targeted analyses of a consensus set of compounds for each crop. The main characteristics of the procedure are summarised with reference to published analyses of this type of crop and different statistical approaches to judging 'equivalence' are discussed. There is a current trend towards development of crops with enhanced nutritional properties or health-related benefits through genetic modification of metabolic pathways. These more complex modifications have greater potential for introducing unpredictable unintended effects, and it may be advisable to supplement current targeted analysis procedures with metabolomics methods. The second part of the chapter discusses the application of metabolomics to substantial equivalence testing. As yet there is no standard procedure for this approach so individual studies, which differ greatly in size and scope, are discussed. The major analytical techniques (GC/MS, LC/MS and NMR) are briefly described and examples of their use are given: a few studies have shown how the massive amounts of data produced by non-targeted profiling methods may be treated to judge equivalence. Some limitations need to be overcome before metabolomics can be adopted as part of the official safety assessment procedure

Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats

International audienceWe explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and gly-coproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR

Challenges in the decomposition of 2D NMR spectra of mixtures of small molecules

International audienceAnalytical methods for mixtures of small molecules requires specificity (is a certain molecule present in the mix?) and speciation capabilities. NMR has been a tool of choice for both of these issues since its early days, due to its quantitative (linear) response, sufficiently high resolving power and capabilities of inferring molecular structures from spectral features (even in the absence of a reference database). However, the analytical performances of NMR are being stretched by the increased complexity of the sample at hands, the dynamic range of the components , and the need of a reasonable turnover time. One approach that has been actively pursued for disentangling the composition complexity is the use of 2D NMR spectroscopy. While any of the many experiments from this family will increase the spectral resolution, some are more apt for mixtures, as they are capable to unveil signals belonging to whole molecules or fragments of it. Among the most popular ones one can enumerate HSQC-TOCSY , DOSY and Maximum-Quantum (MaxQ) NMR. For multicomponent samples, the development of robust mathematical methods of signal decomposition would provide a clear edge towards identification. We have been pursuing, along these lines, Blind Source Separation (BSS). Here, the un-mixing of the spectra is achieved relying on correlations detected on a series of datasets. The series could be associated to samples of different relative composition or in a classically acquired 2D experiment by the mathematical laws underlying the construction of the indirect dimension, the one not recorded by the spectrometer. Many algorithms have been proposed for BSS in NMR since the seminal work of Nuzillard. In this paper, we use rather standard algorithms in BSS in order to disentangle NMR spectra. We show on simulated data (both 1D and 2D HSQC) that these approaches enable to disentangle accurately multiple components, and provide good estimates for concentrations of compounds. Furthermore, we show that after proper realignment of the signals, the same algorithms are able to disentangle real 1D NMR spectra. We obtain similar results on 2D HSQC spectra, where BSS algorithms are able to disentangle successfully components, and provide even better estimates for concentrations

Challenges in the decomposition of 2D NMR spectra of mixtures of small molecules

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Statistical Recoupling Prior to Significance Testing in Nuclear Magnetic Resonance Based Metabonomics

Significance testing is a crucial step in metabolic biomarker recovery from the metabolome-wide latent variables computed by multivariate statistical analysis. In this study we propose an algorithm based on the landscape of the covariance/correlation ratio of consecutive variables along the chemical shift axis to restore, prior to significance testing, the spectral dependency and recouple variables in clusters which correspond to physical, chemical, and biological entities: statistical recoupling of variables (SRV). Variables are associated into a series of clusters, which are then considered as individual objects for the control of the false discovery rate. Compared to classical procedures, it is found that SRV allows efficient recovery of statistically significant metabolic variables. The proposed SRV method when associated with the Benjamini-Yekutieli correction retains a low level of significant variables in the noise areas of the nuclear magnetic resonance (NMR) spectrum, close to that observed using the conservative Bonferroni correction (false positive rate), while also allowing successful identification of statistically significant metabolic NMR signals in cases where the classical procedures of Benjamini-Yekutieli and Benjamini-Hochberg (false discovery rate) fail. This procedure improves the interpretability of latent variables for metabolic biomarker recovery