Laetitia Shintu

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.

Two-dimensional statistical recoupling for the identification of perturbed metabolic networks from NMR spectroscopy.

The development of Statistical Total Correlation Spectroscopy (STOCSY), a representation of the autocorrelation matrix of a spectral data set as a 2D pseudospectrum, has allowed more reliable assignment of one- and two-dimensional NMR spectra acquired from the complex mixtures that are usually used in metabolomics/metabonomics studies, thus, improving precise identification of candidate biomarkers contained in metabolic signatures computed by multivariate statistical analysis. However, the correlations obtained cannot always be interpreted in terms of connectivities between metabolites. In this study, we combine statistical recoupling of variables (SRV) and STOCSY to identify perturbed metabolite systems. The resulting Recoupled-STOCSY (R-STOCSY) method provides a 2D correlation landscape based on the SRV clusters representing physical, chemical, and biological entities. This enables the identification of correlations between distant clusters and extends the recoupling scheme of SRV, which was previously limited to the association of neighboring clusters. This allows the recovery of only meaningful correlations between metabolic signals and significantly enhances the interpretation of STOCSY. The method is validated through the measurement of the distances between the metabolites involved in these correlations, within the whole metabolic network, which shows that the average shortest path length is significantly shorter for the correlations detected in this new way compared to metabolite couples randomly selected from within the entire KEGG metabolic network. This enables the identification without any a priori knowledge of the perturbed metabolic network. The R-STOCSY completes the recoupling procedure between distant clusters, further reducing the high dimensionality of metabolomics/metabonomics data set and finally allows the identification of composite biomarkers, highlighting disruption of particular metabolic pathways within a global metabolic network. This allows the perturbed metabolic network to be extracted through NMR based metabolomics/metabonomics in an automated, and statistical manner.

Metabolomics approach to thyroid nodules: A high-resolution magic-angle spinning nuclear magnetic resonance–based study

BACKGROUND Proton magnetic resonance spectroscopy of operative specimens has been reported to successfully differentiate normal tissue from malignant thyroid tissue. We used a new high-resolution magnetic resonance spectroscopy technique for the differentiation of benign and malignant thyroid neoplasms. METHODS Histological specimens from 72 patients undergoing a total thyroidectomy were processed into a 4-mm ZrO(2) high-resolution magic angle spinning (HRMAS) rotor with 5 μL of D(2)O. A Bruker Avance spectrometer operating at 400 MHz for the (1)H frequency and equipped with a (1)H/(13)C/(31)P HRMAS probe was used. RESULTS Normal and neoplastic thyroid tissues could be discriminated from each other by different relative concentrations of several amino acids and lipids, as well as benign and malignant neoplasms, that differed in terms of a greater lactate and taurine and a lesser lipid choline, phosphocholine, myo-inositol, and scyllo-inositol levels in malignant samples. A statistical analysis with a receiver operating characteristic curve revealed that 77% of the samples were accurately predicted. Similar results were obtained with specimens obtained from ex vivo aspirates. CONCLUSION A further development of this project will be to use the metabolomics approach on specimens obtained from aspirates in vivo after the resolution of technical problems attributable to possible contamination.

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

We 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 glycoproteins 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.

Slow-spinning low-sideband HR-MAS NMR spectroscopy: delicate analysis of biological samples.

High-Resolution Magic-Angle Spinning (HR-MAS) NMR spectroscopy has become an extremely versatile analytical tool to study heterogeneous systems endowed with liquid-like dynamics. Spinning frequencies of several kHz are however required to obtain NMR spectra, devoid of spinning sidebands, with a resolution approaching that of purely isotropic liquid samples. An important limitation of the method is the large centrifugal forces that can damage the structure of the sample. In this communication, we show that optimizing the sample preparation, particularly avoiding air bubbles, and the geometry of the sample chamber of the HR-MAS rotor leads to high-quality low-sideband NMR spectra even at very moderate spinning frequencies, thus allowing the use of well-established solution-state NMR procedures for the characterization of small and highly dynamic molecules in the most fragile samples, such as live cells and intact tissues.

Hepatic metabolic effects of Curcuma longa extract supplement in high-fructose and saturated fat fed rats

The metabolic effects of an oral supplementation with a Curcuma longa extract, at a dose nutritionally relevant with common human use, on hepatic metabolism in rats fed a high fructose and saturated fatty acid (HFS) diet was evaluated. High-resolution magic-angle spinning NMR and GC/MS in combination with multivariate analysis have been employed to characterize the NMR metabolite profiles and fatty acid composition of liver tissue respectively. The results showed a clear discrimination between HFS groups and controls involving metabolites such as glucose, glycogen, amino acids, acetate, choline, lysophosphatidylcholine, phosphatidylethanolamine, and β-hydroxybutyrate as well as an increase of MUFAs and a decrease of n-6 and n-3 PUFAs. Although the administration of CL did not counteract deleterious effects of the HFS diet, some metabolites, namely some n-6 PUFA and n-3 PUFA, and betaine were found to increase significantly in liver samples from rats having received extract of curcuma compared to those fed the HFS diet alone. This result suggests that curcuminoids may affect the transmethylation pathway and/or osmotic regulation. CL extract supplementation in rats appears to increase some of the natural defences preventing the development of fatty liver by acting on the choline metabolism to increase fat export from the liver.

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

We 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.

Diagnosis of post-surgical fine-needle aspiration biopsies of thyroid lesions with indeterminate cytology using HRMAS NMR-based metabolomics

IntroductionUltrasound examination coupled with fine-needle aspiration (FNA) cytology is the gold standard for the diagnosis of thyroid cancer. However, about 10–40% of these analyses cannot be conclusive on the malignancy of the lesions and lead to surgery. The cytological indeterminate FNA biopsies are mainly constituted of follicular—patterned lesions, which are benign in 80% of the cases.ObjectivesThe development of a FNAB classification approach based on the metabolic phenotype of the lesions, complementary to cytology and other molecular tests in order to limit the number of patients undergoing unnecessary thyroidectomy.MethodsWe explored the potential of a NMR-based metabolomics approach to improve the quality of the diagnosis from FNABs, using thyroid tissues collected post-surgically.ResultsThe NMR-detected metabolites were used to produce a robust OPLSDA model to discriminate between benign and malignant tumours. Malignancy was correlated with amino acids such as tyrosine, serine, alanine, leucine and phenylalanine and anti-correlated with myo-inositol, scyllo-inositol and citrate. Diagnosis accuracy was of 84.8% when only indeterminate lesions were considered.ConclusionThese results on model FNAB indicate that there is a clear interest in exploring the possibility to export NMR metabolomics to pre-surgical diagnostics.

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

The 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. Copyright