Biomarkers for cheese authentication by detailed and fast gas chromatographic profiling of triacylglycerol fatty acids.

Unsaturated fatty acid isomers and odd- and branched-chain fatty acids (OBCFAs) in milk triacylglycerols (TAGs) can be quantitated using gas chromatography (GC), providing access to biomarkers of animal species, breeds, diet, geographic origin, and environmental conditions. Such analysis requires expensive cyanopropyl siloxane or ionic liquid columns of at least 50 m in length, which increases the elution time. Aiming to use GC for cheese authentication and characterization while keeping the experiment time short and maintaining a good separation between fatty acid (FA) isomers, we considered using a 30 m polyethylene glycol-2-nitroterephthalate column. The FAs thus quantitated allowed the discovery of specific biomarkers for the origins of cheese varieties highly consumed in several countries. In addition, the simple and multivariate correlations we found between FAs in the cheese TAG matrix were alternative means for characterization and authentication purposes.

Radio-frequency pulse calibration using the MISSTEC sequence.

NMR sequences are composed of multiple radio-frequency pulses. Probe adjustment, sample concentration and solvent influence the loading factor, therefore these parameters also impact the validity of flip angles. The commonly used method to calibrate RF pulses is to measure a nutation curve by varying the pulse duration. However, this method is impacted by off-resonance effects, radiation damping and B1 and B0 inhomogeneities. Furthermore, it is important to avoid partial saturation. In this work, the MISSTEC sequence is proposed for pulse calibration. This sequence takes only 8 s or 2 min for 1H or 13C calibration, respectively. High accuracy (with an error below 1%) was obtained for both nuclei. Therefore, the calibrations can be done rapidly and accurately. Furthermore, the MISSTEC measurement could be performed on each sample - in an automated way- before acquisitions, after which the calibration found could be automatically used.

Consequences of blunting the mevalonate pathway in cancer identified by a pluri-omics approach.

We have previously shown that the combination of statins and taxanes was a powerful trigger of HGT-1 human gastric cancer cells' apoptosis1. Importantly, several genes involved in the "Central carbon metabolism pathway in cancer", as reported in the Kyoto Encyclopedia of Genes and Genomes, were either up- (ACLY, ERBB2, GCK, MYC, PGM, PKFB2, SLC1A5, SLC7A5, SLC16A3,) or down- (IDH, MDH1, OGDH, P53, PDK) regulated in response to the drug association. In the present study, we conducted non-targeted metabolomics and lipidomics analyses by complementary methods and cross-platform initiatives, namely mass spectrometry (GC-MS, LC-MS) and nuclear magnetic resonance (NMR), to analyze the changes resulting from these treatments. We identified several altered biochemical pathways involved in the anabolism and disposition of amino acids, sugars, and lipids. Using the Cytoscape environment with, as an input, the identified biochemical marker changes, we distinguished the functional links between pathways. Finally, looking at the overlap between metabolomics/lipidomics and transcriptome changes, we identified correlations between gene expression modifications and changes in metabolites/lipids. Among the metabolites commonly detected by all types of platforms, glutamine was the most induced (6-7-fold), pointing to an important metabolic adaptation of cancer cells. Taken together, our results demonstrated that combining robust biochemical and molecular approaches was efficient to identify both altered metabolic pathways and overlapping gene expression alterations in human gastric cancer cells engaging into apoptosis following blunting the cholesterol synthesis pathway.

The FAQUIRE Approach: FAst, QUantitative, hIghly Resolved and sEnsitivity Enhanced 1H, 13C Data.

The targeted analysis of metabolites in complex mixtures is a challenging issue. NMR is one of the major tools in this field, but there is a strong need for more sensitive, better-resolved, and faster quantitative methods. In this framework, we introduce the concept of FAst, QUantitative, hIghly Resolved and sEnsitivity enhanced (FAQUIRE) NMR to push forward the limits of metabolite NMR analysis. 2D 1H, 13C 2D quantitative maps are promising alternatives for enhancing the spectral resolution but are highly time-consuming because of (i) the intrinsic nature of 2D, (ii) the longer recycling times required for quantitative conditions, and (iii) the higher number of scans needed to reduce the level of detection/quantification to access low concentrated metabolites. To reach this aim, speeding up the recently developed QUantItative Perfected and pUre shifted HSQC (QUIPU HSQC) is an interesting attempt to develop the FAQUIRE concept. Thanks to the combination of spectral aliasing, nonuniform sampling, and variable repetition time, the acquisition time of 2D quantitative maps is reduced by a factor 6 to 9, while conserving a high spectral resolution thanks to a pure shift approach. The analytical potential of the new Quick QUIPU HSQC (Q QUIPU HSQC) is evaluated on a model metabolite sample, and its potential is shown on breast-cell extracts embedding metabolites at millimolar to submillimolar concentrations.

Olive oil characterization and classification by 13C NMR with a polarization transfer technique: A comparison with gas chromatography and 1H NMR.

In a previous work, we optimized and used a fast adiabatic 13C-INEPT (Insensitive Nuclei Enhanced by Polarization Transfer) experiment for the isotopomic analysis of olive oil samples, which allowed us quantifying individual fatty acids within triacylglycerols through multivariate linear regression models. The goal of this study was to validate these models and to evaluate the power of 13C-INEPT in the authentication of olive oils relative to gas chromatography (GC) and 1H NMR. In this respect, a new set of olive oil samples was analyzed by these three techniques. The analytical variables thus obtained as well as their corresponding long-term repeatability were compared. As a result, the reliability of the fatty acid quantification models was proven and the best classification of olive oils according to the altitude of the olive grove and to the morphological aspect (color) of the olives was achieved by means of 13C-INEPT.

Suppression of radiation damping for high precision quantitative NMR.

True quantitative analysis of concentrated samples by (1)H NMR is made very difficult by Radiation Damping. A novel NMR sequence (inspired by the WET NMR sequence and by Outer Volume Saturation methods) is therefore proposed to suppress this phenomenon by reducing the spatial area and consequently the number of spins contributing to the signal detected. The size of the detected volume can be easily chosen in a large range and line shape distortions are avoided thanks to a uniform signal suppression of the outer volume. Composition of a mixture can as a result be determined with very high accuracy (precision and trueness) at the per mille level whatever the concentrations and without hardware modification.

Fast determination of absolute metabolite concentrations by spatially encoded 2D NMR: application to breast cancer cell extracts.

Two-dimensional nuclear magnetic resonance (2D NMR) forms a powerful tool for the quantitative analysis of complex mixtures such as samples of metabolic relevance. However, its use for quantitative purposes is far from being trivial, not only because of the associated experiment time, but also due to its subsequent high sensitivity to hardware instabilities affecting its precision. In this paper, an alternative approach is considered to measure absolute metabolite concentrations in complex mixtures with a high precision in a reasonable time. It is based on a "multi-scan single shot" (M3S) strategy, which is derived from the ultrafast 2D NMR methodology. First, the analytical performance of this methodology is compared to the one of conventional 2D NMR. 2D correlation spectroscopy (COSY) spectra are obtained in 10 min on model metabolic mixtures, with a precision in the 1-4% range (versus 5-18% for the conventional approach). The M3S approach also shows a better linearity than its conventional counterpart. It ensures that accurate quantitative results can be obtained provided that a calibration procedure is carried out. The M3S COSY approach is then applied to measure the absolute metabolite concentration in three breast cancer cell line extracts, relying on a standard addition protocol. M3S COSY spectra of such extracts are recorded in 20 min and give access to the absolute concentration of 14 major metabolites, showing significant differences between cell lines.

Absolute quantification of metabolites in breast cancer cell extracts by quantitative 2D (1) H INADEQUATE NMR.

Metabolomic studies by NMR spectroscopy are increasingly employed for a variety of biomedical applications. A very standardized 1D proton NMR protocol is generally employed for data acquisition, associated with multivariate statistical tests. Even if targeted approaches have been proposed to quantify metabolites from such experiments, quantification is often made difficult by the high degree of overlap characterizing (1) H NMR spectra of biological samples. Two-dimensional spectroscopy presents a high potential for accurately measuring concentrations in complex samples, as it offers a much higher discrimination between metabolite resonances. We have recently proposed an original approach relying on the (1) H 2D INADEQUATE pulse sequence, optimized for fast quantitative analysis of complex metabolic mixtures. Here, the first application of the quantitative (1) H 2D INADEQUATE experiment to a real metabonomic study is presented. Absolute metabolite concentrations are determined for different breast cancer cell line extracts, by a standard addition procedure. The protocol is characterized by high analytical performances (accuracy better than 1%, excellent linearity), even if it is affected by relatively long acquisition durations (15 min to 1 h per spectrum). It is applied to three different cell lines, expressing different hormonal and tyrosine kinase receptors. The absolute concentrations of 15 metabolites are determined, revealing significant differences between cell lines. The metabolite concentrations measured are in good agreement with previous studies regarding metabolic profile changes of breast cancer. While providing a high degree of discrimination, this methodology offers a powerful tool for the determination of relevant biomarkers.

Strategy for choosing extraction procedures for NMR-based metabolomic analysis of mammalian cells.

Metabolomic analysis of mammalian cells can be applied across multiple fields including medicine and toxicology. It requires the acquisition of reproducible, robust, reliable, and homogeneous biological data sets. Particular attention must be paid to the efficiency and reliability of the extraction procedure. Even though a number of recent studies have dealt with optimizing a particular protocol for specific matrices and analytical techniques, there is no universal method to allow the detection of the entire cellular metabolome. Here, we present a strategy for choosing extraction procedures from adherent mammalian cells for the global NMR analysis of the metabolome. After the quenching of cells, intracellular metabolites are extracted from the cells using one of the following solvent systems of varying polarities: perchloric acid, acetonitrile/water, methanol, methanol/water, and methanol/chloroform/water. The hydrophilic metabolite profiles are analysed using (1)H nuclear magnetic resonance (NMR) spectroscopy. We propose an original geometric representation of metabolites reflecting the efficiency of extraction methods. In the case of NMR-based analysis of mammalian cells, this methodology demonstrates that a higher portion of intracellular metabolites are extracted by using methanol or methanol/chloroform/water. The preferred method is evaluated in terms of biological variability for studying metabolic changes caused by the phenotype of four different human breast cancer cell lines, showing that the selected extraction procedure is a promising tool for metabolomic and metabonomic studies of mammalian cells. The strategy proposed in this paper to compare extraction procedures is applicable to NMR-based metabolomic studies of various systems.

Fast and precise quantitative analysis of metabolic mixtures by 2D 1H INADEQUATE NMR.

Quantitative analysis of metabolic mixtures by (1)H 1D NMR offers a limited potential for precise quantification of biomarkers, due to strong overlap between the peaks. Two-dimensional spectroscopy is a powerful tool to unambiguously and simultaneously measure a larger number of metabolite contributions. However, it is still rarely used for quantification, first because quantitative analysis by 2D NMR requires a calibration procedure due to the multi-impulsional nature of 2D NMR experiments, and above all because of the prohibitive experiment duration that is necessary to obtain such a calibration curve. In this work, we develop and evaluate a 2D (1)H INADEQUATE protocol for a fast determination of metabolite concentrations in complex mixtures. The 2D pulse sequence is carefully optimized and evaluated in terms of precision and linearity. Quantitative (1)H INADEQUATE 2D spectra of metabolic mixtures are obtained in 7 min with a repeatability better than 2% for metabolite concentrations as small as 100 µM and an excellent linearity. The method described in this work allows a fast and precise quantification of metabolic mixtures, and it forms a promising tool for metabonomic studies.

Lactate doublet quantification and lipid signal suppression using a new biexponential decay filter: application to simulated and 1H MRS brain tumor time-domain data.

A new postprocessing filter based on the continuous wavelet transform (CWT) method modeled as a biexponential decay function to isolate the lactate doublet from overlapping lipid resonance(s) and estimate its magnetic resonance spectroscopy (MRS) parameters (signal amplitude, resonance frequencies, and apparent relaxation time (T(*) (2))) is proposed. The new filter employs the same iterative process used in the previously single exponential decay filter. A comparison of the results obtained from application of both filters to simulated data and real (1)H MRS data collected from human blood plasma and brain tumors demonstrates that the new filter provides a better estimate of MRS parameters of lactate, with less computation time. Furthermore, the results show that the new filter is less sensitive to noise and provides a direct estimate of J-coupling value of the lactate doublet.