Mixtures of dimyristoyl-phosphatidylcholine (DMPC) and dihexanoyl-phosphatidylcholine (DHPC) in water form disks also called bicelles and different bilayer organizations when the mol ratio of the two lipids and the temperature are varied. The spontaneous alignment in a magnetic field of these bilayers above the transition temperature T(m) of DMPC is an attractive property that was successfully used to investigate protein structure by NMR. In this article, we have attempted to give an overview of all structural transformations of DMPC/DHPC mixtures that can be inferred from broad band (31)P-NMR spectroscopy between 5 and 60 degrees C. We show that above a critical temperature, T(v), perforated vesicles progressively replace alignable structures. The holes in these vesicles disappear above a new temperature threshold, T(h). The driving force for these temperature-dependent transformations that has been overlooked in previous studies is the increase of DHPC miscibility in the bilayer domain above T(m). Accordingly, we propose a new model (the "mixed bicelle" model) that emphasizes the consequence of the mixing. This investigation shows that the various structures of DMPC in the presence of increasing mol ratios of the short-chain DHPC is reminiscent of the observation put forward by several laboratories investigating solubilization and reconstitution of biological membranes.

Among all the software packages available for discriminant analyses based on projection to latent structures (PLS-DA) or orthogonal projection to latent structures (OPLS-DA), SIMCA (Umetrics, Umeå Sweden) is the more widely used in the metabolomics field. SIMCA proposes many parameters or tests to assess the quality of the computed model (the number of significant components, R2, Q2, pCV-ANOVA, and the permutation test). Significance thresholds for these parameters are strongly application-dependent. Concerning the Q2 parameter, a significance threshold of 0.5 is generally admitted. However, during the last few years, many PLS-DA/OPLS-DA models built using SIMCA have been published with Q2 values lower than 0.5. The purpose of this opinion note is to point out that, in some circumstances frequently encountered in metabolomics, the values of these parameters strongly depend on the individuals that constitute the validation subsets. As a result of the way in which the software selects members of the calibration and validation subsets, a simple permutation of dataset rows can, in several cases, lead to contradictory conclusions about the significance of the models when a K-fold cross-validation is used. We believe that, when Q2 values lower than 0.5 are obtained, SIMCA users should at least verify that the quality parameters are stable towards permutation of the rows in their dataset.

Most studies reported until now on the magnetically alignable system formed by the binary mixtures of long- and short-chain lipids were based on the mixture of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (D14PC) and 1,2-dihexanoyl-sn-glycero-3-phosphocholine (D6PC) lipids. We have recently shown that a large part of the phase diagrams of this lipid mixture could be understood by taking into account the partial miscibility between the long-chain lipids and the short-chain lipids when the sample was heated above the melting transition temperature (Tm) of the long-chain lipids. In this work, we show by modifying the chain length of either one of the two lipids that it is possible to control their miscibility and thus the intervals of temperature and composition where spontaneous alignment is observed in a magnetic field. By using 31P NMR, we demonstrate that the very special properties of such binary lipid mixtures are correlated with the propensity for short-chain lipids to diffuse into the bilayer regions. We also show that lipid mixtures with comparable properties can be formed with unsaturated lipids such as 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC).

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-014-0740-0) contains supplementary material, which is available to authorized users.

Purpose: Metabolomics depicts metabolic changes in biologic systems using a multiparametric analysis technique. This study assessed the metabolomic profiles of serum, obtained by proton nuclear magnetic resonance (NMR) spectroscopy, from cirrhotic patients with and without hepatocellular carcinoma (HCC).Experimental Design: The study included 154 consecutive patients with compensated biopsy-proven alcoholic cirrhosis. Among these, 93 had cirrhosis without HCC, 28 had biopsy-proven HCC within the Milan criteria and were eligible for curative treatment (small HCC), and 33 had HCC outside the Milan criteria (large HCC). Proton spectra were acquired at 500 MHz. An orthogonal partial latent structure [orthogonal projection to latent structure (OPLS)] analysis model was built to discriminate large HCC spectra from cirrhotic spectra. Small HCC spectra were secondarily projected using previously built OPLS discriminant components.Results: The OPLS model showed discrimination between cirrhotic and large HCC spectra. Metabolites that significantly increased with large HCC were glutamate, acetate, and N-acetyl glycoproteins, whereas metabolites that correlated with cirrhosis were lipids and glutamine. Projection of small HCC samples into the OPLS model showed a heterogeneous distribution between large HCC and cirrhotic samples. Small HCC patients with metabolomic profile similar to those of large HCC group had higher incidences of recurrence or death during follow-up.Conclusions: Serum NMR-based metabolomics identified metabolic fingerprints that could be specific to large HCC in cirrhotic livers. From a metabolomic standpoint, some patients with small HCC, who are eligible for curative treatments, seem to behave as patients with advanced cancerous disease. It would be useful to further prospectively investigate these patients to define a subgroup with a worse prognosis. Clin Cancer Res; 18(24); 6714-22. Ó2012 AACR.

SummaryDietary restriction (DR) is the most universal intervention known to extend animal lifespan. DR also prevents tumor development in mammals, and this effect requires the tumor suppressor PTEN. However, the metabolic and cellular processes that underly the beneficial effects of DR are poorly understood. We identified slcf-1 in an RNAi screen for genes that extend Caenorhabditis elegans lifespan in a PTEN ⁄ daf-18-dependent manner. We showed that slcf-1 mutation, which increases average lifespan by 40%, mimics DR in worms fed ad libitum. An NMR-based metabolomic characterization of slcf-1 mutants revealed lower lipid levels compared to wild-type animals, as expected for dietary-restricted animals, but also higher pyruvate content. Epistasis experiments and metabolic measurements support a model in which the long lifespan of slcf-1 mutants relies on increased mitochondrial pyruvate metabolism coupled to an adaptive response to oxidative stress. This response requires DAF-18 ⁄ PTEN and the previously identified DR effectors PHA-4 ⁄ FOXA, HSF-1 ⁄ HSF1, SIR-2.1 ⁄ SIRT-1, and AMPK ⁄ AAK-2. Overall, our data show that pyruvate homeostasis plays a central role in lifespan control in C. elegans and that the beneficial effects of DR results from a hormetic mechanism involving the mitochondria. Analysis of the SLCF-1 protein sequence predicts that slcf-1 encodes a plasma membrane transporter belonging to the conserved monocarboxylate transporter family. These findings suggest that inhibition of this transporter homolog in mammals might also promote a DR response.

In this study, we present a methodology for metabotyping of C. elegans using 1H high resolution magic angle spinning (HRMAS) whole-organism nuclear magnetic resonance (NMR). We demonstrate and characterize the robustness of our metabolic phenotyping method, discriminating wild-type N2 from mutant sod-1(tm776) animals, with the latter being an otherwise silent mutation, and we identify and quantify several confounding effects to establish guidelines to ensure optimal quality of the raw data across time and space. We monitor the sample stability under experimental conditions and examine variations arising from effects that can potentially confuse the biological interpretation or prevent the automation of the protocol, including sample culture (breeding of the worms by two biologists), sample preparation (freezing), NMR acquisition (acquisition by different spectroscopists, acquisition in different facilities), and the effect of the age of the animals. When working with intact model organisms, some of these exogenous effects are shown to be significant and therefore require control through experimental design and sample randomization.

Assessment of chronic liver failure (CLF) in cirrhotic patients is needed to make therapeutic decisions. A biological score is usually performed, using the Model for End-Stage Liver Disease (MELD), to evaluate CLF. Nevertheless, MELD does not take into account metabolic perturbations produced by liver-function impairment. In contrast, metabolomics can investigate many metabolic perturbations within biological systems. The purpose of this study was to assess whether metabolomic profiles of serum, obtained by proton NMR spectroscopy from cirrhotic patients, are affected by the severity of CLF. An orthogonal projection to latent-structure analysis was performed to compare MELD scores and NMR spectra of 124 patients with cirrhosis. The statistical model obtained showed a good explained variance (R(2)X = 0.87 and R(2)Y = 0.86) and a good predictability (Q(2)Y = 0.64). Metabolomic profiles showed significant differences regarding various metabolites depending of severity of CLF: levels of high-density lipoprotein and phosphocholine resonances were significantly higher in patients with mild CLF compared to severe CLF. Other metabolites such as lactate, pyruvate, glucose, amino acids, and creatinine were significantly higher in patients with severe CLF than mild CLF. Our conclusion is that metabolomic NMR analysis provides new insights into metabolic processes related to the severity of hepatic function impairment in cirrhosis.