No abstract

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.

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.

Metabolomics plays a pivotal role in systems biology, and NMR is a central tool with high precision and exceptional resolution of chemical information. Most NMR metabolomic studies are based on 1 H 1D spectroscopy, severely limited by peak overlap. 13 C NMR benefits from a larger signal dispersion but is barely used in metabolomics due to ca. 6000-fold lower sensitivity. We introduce a new approach, based on hyperpolarized 13 C NMR at natural abundance, that circumvents this limitation. A new untargeted NMR-based metabolomic workflow based on dissolution dynamic nuclear polarization (d-DNP) for the first time enabled hyperpolarized natural abundance 13 C metabolomics. Statistical analysis of resulting hyperpolarized 13 C data distinguishes two groups of plant (tomato) extracts and highlights biomarkers, in full agreement with previous results on the same biological model. We also optimize parameters of the semiautomated d-DNP system suitable for high-throughput studies.

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.

No abstract

Across the evolutionary history of insects, the shift from nitrogen-rich carnivore/omnivore diets to nitrogen-poor herbivorous diets was made possible through symbiosis with microbes. The herbivorous turtle ants Cephalotes possess a conserved gut microbiome which enriches the nutrient composition by recycling nitrogen-rich metabolic waste to increase the production of amino acids. This enrichment is assumed to benefit the host, but we do not know to what extent. To gain insights into nitrogen assimilation in the ant cuticle we use gut bacterial manipulation, 15N isotopic enrichment, isotope-ratio mass spectrometry, and 15N nuclear magnetic resonance spectroscopy to demonstrate that gut bacteria contribute to the formation of proteins, catecholamine cross-linkers, and chitin in the cuticle. This study identifies the cuticular components which are nitrogen-enriched by gut bacteria, highlighting the role of symbionts in insect evolution, and provides a framework for understanding the nitrogen flow from nutrients through bacteria into the insect cuticle.

Quantitative analysis by nuclear magnetic resonance (NMR) requires highly precise measurements to achieve reliable quantification. It is particularly true in (13)C site-specific natural isotope fractionation studied by nuclear magnetic resonance, where the range of values of (13)C isotopic deviations at natural abundance is highly restricted. Consequently, an NMR method capable of measuring δ(13)C ‰ values with a very high precision (a few per mil) is indispensable. This high degree of precision has already been achieved by one-dimensional (13)C acquisitions; however, this approach is limited by peak overlaps which reduce the precision of the isotope content determination, even for certain small molecules. It is therefore necessary to extend this promising methodology to a higher dimensionality. In this context, this paper aims at determining conditions that allow the achievement of two-dimensional (2D) (1)H-(13)C heteronuclear experiments with a precision of a few per mil in a reasonable time. Our results demonstrate that a high precision (repeatability of 2 per mil) can be reached with the (1)H-(13)C HSQC (Heteronuclear Single Quantum Correlation) experiment, thus satisfying the conditions needed to perform (13)C isotope analysis by 2D NMR. We also consider the impact of several approaches which have been proposed to reduce the duration of heteronuclear 2D experiments. Two of these common time-saving strategies, spectral aliasing and linear prediction, are fully compatible with the high-precision requirements of isotopic NMR, while a third one, nonuniform sampling, leads to dramatic precision losses. In conclusion, this study demonstrates the feasibility of very precise 2D NMR measurements and opens a number of application perspectives.