A Computational Selection of Metabolite Biomarkers Using Emerging Pattern Mining: A Case Study in Human Hepatocellular Carcinoma.

The biomarker development in metabolomics aims at discriminating diseased from normal subjects and at creating a predictive model that can be used to diagnose new subjects. From a case study on human hepatocellular carcinoma (HCC), we studied for the first time the potential usefulness of the emerging patterns (EPs) that come from the data mining domain. When applied to a metabolomics data set labeled with two classes (e.g., HCC patients vs healthy subjects), EP mining can capture differentiating combinations of metabolites between the two classes. We observed that the so-called jumping emerging patterns (JEPs), which correspond to the combinations of metabolites that occur in only one of the two classes, achieved better performance than individual biomarkers. Particularly, the implementation of the JEPs in a rules-based diagnostic tool drastically reduced the false positive rate, i.e., the rate of healthy subjects predicted as HCC patients.

Amyotrophic lateral sclerosis and denervation alter sphingolipids and up-regulate glucosylceramide synthase.

Amyotrophic lateral sclerosis (ALS) is a fatal adult-onset disease characterized by upper and lower motor neuron degeneration, muscle wasting and paralysis. Growing evidence suggests a link between changes in lipid metabolism and ALS. Here, we used UPLC/TOF-MS to survey the lipidome in SOD1(G86R) mice, a model of ALS. Significant changes in lipid expression were evident in spinal cord and skeletal muscle before overt neuropathology. In silico analysis also revealed appreciable changes in sphingolipids including ceramides and glucosylceramides (GlcCer). HPLC analysis showed increased amounts of GlcCer and downstream glycosphingolipids (GSLs) in SOD1(G86R) muscle compared with wild-type littermates. Glucosylceramide synthase (GCS), the enzyme responsible for GlcCer biosynthesis, was up-regulated in muscle of SOD1(G86R) mice and ALS patients, and in muscle of wild-type mice after surgically induced denervation. Conversely, inhibition of GCS in wild-type mice, following transient peripheral nerve injury, reversed the overexpression of genes in muscle involved in oxidative metabolism and delayed motor recovery. GCS inhibition in SOD1(G86R) mice also affected the expression of metabolic genes and induced a loss of muscle strength and morphological deterioration of the motor endplates. These findings suggest that GSLs may play a critical role in ALS muscle pathology and could lead to the identification of new therapeutic targets.

Integrated comparison of drug-related and drug-induced ultra performance liquid chromatography/mass spectrometry metabonomic profiles using human hepatocyte cultures.

The biochemical variations induced in human primary hepatocyte cultures by reference activators of xenoreceptor CAR (NR1I3) and PXR (NR1I2), i.e., rifampicin, phenobarbital, and 6-(4-chlorophenyl)imidazo[2,1-b] [1,3]thiazole-5-carbaldehyde O-3,4-dichlorobenzyl) oxime (CITCO), were investigated using a global metabonomics approach. Cultured human hepatocytes were treated with the three drugs before analysis of intracellular and extracellular media by ultra performance liquid chromatography/time-of-flight-mass spectrometry (UPLC/TOF-MS) technique, in order to list endogenous compounds potentially related to a PXR or CAR induction mechanism and to identify drug metabolites related to each treatment. The emphasis was put on the quality of the analytical data (dilution/filtration strategy before data processing) and on the appropriate pattern recognition techniques. In cellular media, the most significant variations seen in the data are not related to the treatments but to the source of hepatocytes, illustrating the importance of the genetic and/or environmental background in human liver experiments. However when applying classical multivariate statistical approaches (principal component analysis (PCA) and orthogonal partial least squares (O-PLS)), the statistical weight due to drug metabolites, present only in the treated groups, hinders the interpretation because of their predominance compared to most of the changes seen in endogenous metabolites. A new statistical approach, called shared and unique structure (SUS) plot, enabling the comparison of different treatments having the same control has been applied, allowing separation of clearly exogenous variables (drug metabolites) from endogenous biomarkers. Endogenous variables (either up- or down-regulated) have been attributed specifically to the impact of rifampicin (PXR ligand), CITCO (CAR ligand), and phenobarbital (CAR and PXR activator) on the biological regulation pathways of the hepatocytes. This global approach coupled to a statistical pretreatment of the data, enabling the separate capture of both drug related and drug induced biomarkers, represents a powerful technique for future mechanistic studies using cellular tools.

Mass spectrometry-based metabolomics: accelerating the characterization of discriminating signals by combining statistical correlations and ultrahigh resolution.

A strategy combining autocorrelation matrices and ultrahigh resolution mass spectrometry (MS) was developed to optimize the characterization of discriminating ions highlighted by metabolomics. As an example, urine samples from rats treated with phenobarbital (PB) were analyzed by ultrahigh-pressure chromatography with two different eluting conditions coupled to time-of-flight mass spectrometric detection in both the positive and negative electrospray ionization modes. Multivariate data analyses were performed to highlight discriminating variables from several thousand detected signals: a few hundred signals were found to be affected by PB, whereas a few tenths of them were linked to its metabolism. Autocorrelation matrices were then applied to eliminate adduct and fragment ions. Finally, the characterization of the ions of interest was performed with ultrahigh-resolution mass spectrometry and sequential MS(n) experiments, by using a LC-LTQ-Orbitrap system. The use of different eluting conditions was shown to drastically impact on the chromatographic retention and ionization of compounds, thus providing a way to obtain more exhaustive metabolic fingerprints, whereas autocorrelation matrices allowed one to focus the identification work on the most relevant ions. By using such an approach, 14 PB metabolites were characterized in rat urines, some of which have not been reported in the literature.

Sphingolipid Metabolism Is Dysregulated at Transcriptomic and Metabolic Levels in the Spinal Cord of an Animal Model of Amyotrophic Lateral Sclerosis.

Lipid metabolism is drastically dysregulated in amyotrophic lateral sclerosis and impacts prognosis of patients. Animal models recapitulate alterations in the energy metabolism, including hypermetabolism and severe loss of adipose tissue. To gain insight into the molecular mechanisms underlying disease progression in amyotrophic lateral sclerosis, we have performed RNA-sequencing and lipidomic profiling in spinal cord of symptomatic SOD1G86R mice. Spinal transcriptome of SOD1G86R mice was characterized by differential expression of genes related to immune system, extracellular exosome, and lysosome. Hypothesis-driven identification of metabolites showed that lipids, including sphingomyelin(d18:0/26:1), ceramide(d18:1/22:0), and phosphatidylcholine(o-22:1/20:4) showed profound altered levels. A correlation between disease severity and gene expression or metabolite levels was found for sphingosine, ceramide(d18:1/26:0), Sgpp2, Sphk1, and Ugt8a. Joint-analysis revealed a significant enrichment of glycosphingolipid metabolism in SOD1G86R mice, due to the down-regulation of ceramide, glucosylceramide, and lactosylceramide and the overexpression of genes involved in their recycling in the lysosome. A drug-gene interaction database was interrogated to identify potential drugs able to modulate the dysregulated genes from the signaling pathway. Our results suggest that complex lipids are pivotally changed during the first phase of motor symptoms in an animal model of amyotrophic lateral sclerosis.

The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age.

Metabolomic approaches are increasingly used to identify new disease biomarkers, yet normal values of many plasma metabolites remain poorly defined. The aim of this study was to define the "normal" metabolome in healthy volunteers. We included 800 French volunteers aged between 18 and 86, equally distributed according to sex, free of any medication and considered healthy on the basis of their medical history, clinical examination and standard laboratory tests. We quantified 185 plasma metabolites, including amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexose, using tandem mass spectrometry with the Biocrates AbsoluteIDQ p180 kit. Principal components analysis was applied to identify the main factors responsible for metabolome variability and orthogonal projection to latent structures analysis was employed to confirm the observed patterns and identify pattern-related metabolites. We established a plasma metabolite reference dataset for 144/185 metabolites. Total blood cholesterol, gender and age were identified as the principal factors explaining metabolome variability. High total blood cholesterol levels were associated with higher plasma sphingomyelins and phosphatidylcholines concentrations. Compared to women, men had higher concentrations of creatinine, branched-chain amino acids and lysophosphatidylcholines, and lower concentrations of sphingomyelins and phosphatidylcholines. Elderly healthy subjects had higher sphingomyelins and phosphatidylcholines plasma levels than young subjects. We established reference human metabolome values in a large and well-defined population of French healthy volunteers. This study provides an essential baseline for defining the "normal" metabolome and its main sources of variation.

Metabonomic studies on human hepatocyte in primary culture.

Mechanisms involved in induction processes have been investigated using fresh human hepatocytes in culture as a cellular model and using mass spectrometry-based metabonomics as a global investigation tool. Sample preparation to data analysis have been detailed in an approach enabling to separate drug-induced (endogenous metabolites) and drug-related (drug metabolites) biomarkers for reference inducers. Rifampicin, a nuclear pregnane X receptor (PXR) ligand; CITCO, a nuclear constitutive androstane receptor (CAR) ligand; and phenobarbital, which activates both CAR and PXR, have been used. Specific intra-cellular metabolites have been isolated for rifampicin and CITCO as potential endogenous biomarkers of their respective induction mechanism. A mixture of these two types of biomarkers modified in the same way after treatment with either rifampicin or CITCO on the one hand and with phenobarbital on the other hand has been found.

Coordinate Transcriptomic and Metabolomic Effects of the Insulin Sensitizer Rosiglitazone on Fundamental Metabolic Pathways in Liver, Soleus Muscle, and Adipose Tissue in Diabetic db/db Mice.

Rosiglitazone (RSG), developed for the treatment of type 2 diabetes mellitus, is known to have potent effects on carbohydrate and lipid metabolism leading to the improvement of insulin sensitivity in target tissues. To further assess the capacity of RSG to normalize gene expression in insulin-sensitive tissues, we compared groups of 18-day-treated db/db mice with increasing oral doses of RSG (10, 30, and 100 mg/kg/d) with untreated non-diabetic littermates (db/+). For this aim, transcriptional changes were measured in liver, inguinal adipose tissue (IAT) and soleus muscle using microarrays and real-time PCR. In parallel, targeted metabolomic assessment of lipids (triglycerides (TGs) and free fatty acids (FFAs)) in plasma and tissues was performed by UPLC-MS methods. Multivariate analyses revealed a relationship between the differential gene expressions in liver and liver trioleate content and between blood glucose levels and a combination of differentially expressed genes measured in liver, IAT, and muscle. In summary, we have integrated gene expression and targeted metabolomic data to present a comprehensive overview of RSG-induced changes in a diabetes mouse model and improved the molecular understanding of how RSG ameliorates diabetes through its effect on the major insulin-sensitive tissues.

A cylinder-shaped double ribbon structure formed by an amyloid hairpin peptide derived from the beta-sheet of murine PrP: an X-ray and molecular dynamics simulation study.

A structural model of the murine PrP small beta-sheet was obtained by synthesizing the RGYMLGSADPNGNQVYYRG peptide comprising the two beta-strands 127-133 and 159-164 linked by a four-residue sequence of high turn propensity. The DPNG turn sequence is a "short circuit" replacing the original protein sequence between the two strands. This 19-residue peptide spontaneously forms very long single fibrils as observed by electron microscopy. The X-ray diffraction patterns of a partially oriented sample reveals an average arrangement of the hairpin peptides into a structure which can be geometrically approximated by an empty-core cylinder. The hairpins are oriented perpendicular to the cylinder axis and a 130 A helix period is observed. Based on X-ray diffraction constraints and on more indirect general protein structure considerations, a precise and consistent fibril model was built. The structure consists of two beta-sheet ribbons wound around a cylinder and assembled into a single fibril with a hairpin orientation perpendicular to the fibril axis. Subsequent implicit and explicit solvent molecular dynamics simulations provided the final structure at atomic resolution and further insights into the stabilizing interactions. Particularly important are the zipper-like network of polar interactions between the edges of the two ribbons, including the partially buried water molecules. The hydrophobic core is not optimally compact explaining the low density of this region seen by X-ray diffraction. The present findings provide also a simple model for further investigating the sequence-stability relationship using a mutational approach with a quasi-independent consideration of the polar and apolar interactions.