Search

Insulin/IGF-like signaling (IIS) and nutrient sensing are among the most potent regulators of health status and aging. Here, a global view of the metabolic changes in C. elegans with impaired function of IIS represented by daf-2 and daf-16 and the intestinal di- and tripeptide transport pept-1 was generated using (1)H nuclear magnetic resonance spectroscopic analysis of worm extracts and spent culture media. We showed that specific metabolic profiles were significantly associated with each type of mutant. On the basis of the metabonomics data, selected underlying processes were further investigated using proteomic and transcriptomic approaches. The observed changes suggest a decreased activity of the one carbon metabolism in pept-1(lg601) mutants. Higher concentration of branched-chain amino acids (BCAA) and altered transcript levels of genes involved in BCAA metabolism were observed in long-living strains daf-2(e1370) and daf-2(e1370);pept-1(lg601) when compared to wild types and daf-16(m26);daf-2(e1370);pept-1(lg601) C. elegans, suggesting a DAF-16-dependent mechanism.

Epidemiological studies have repeatedly found that whole-grain (WG) cereal foods reduce the risk of several lifestyle-related diseases, though consistent clinical outcomes and mechanisms are elusive. To compare the effects of a WG-rich diet with a matched refined-grain (RG) diet on plasma biomarkers and bowel health parameters, seventeen healthy subjects (eleven females and six males) completed an exploratory cross-over study with a 2-week intervention diet based on either WG- or RG-based foods, separated by a washout of at least 5 weeks. Both diets were the same except for the use of WG (150 g/d) or RG foods. Subjects undertook a 4 h postprandial challenge on day 8 of each intervention diet. After 2 weeks, the WG diet tended to decrease plasma total and LDL-cholesterol (bothP = 0·09), but did not change plasma HDL-cholesterol, fasting glucose, C-reactive protein or homocysteine compared with the RG diet. Plasma betaine and alkylresorcinol concentrations were elevated after 1 week of the WG diet (P = 0·01 andP Clostridium leptumpopulations in faeces were increased after the WG diet, along with a trend for decreased faecal water pH (P = 0·096) and increased stool frequency (P

Application of metabonomics to nutritional sciences, also termed as nutrimetabonomics, offers the possibility to measure metabolic responses associated with the consumption of specific nutrients and foods. As dietary differences generally only lead to subtle metabolic changes, measuring diet associated metabolic phenotypes is a challenge, and also an opportunity to develop and test new chemometric strategies that can highlight metabolic information in relation to different dietary habits. While multivariate statistical techniques have long been used to analyse dietary data from diet records and questionnaires, to date no attempt has been made to link dietary patterns with metabolic profiles. Using a three-step strategy, it was possible to merge 1 H NMR plasma metabolic profile data with specific dietary patterns as assessed by Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA). Five dietary patterns (energy intake, plant versus animal based diet, “traditional diet” versus sugar-rich diet, “traditional” versus “modern” diets, and consumption of skim versus whole dairy products) were found by applying PCA to the food frequency questionnaire data which explained 50% of the variation. Metabolic phenotypes associated with these dietary patterns were obtained by PLS-DA and were mainly based on differences in lipids and amino acid profiles in plasma. This new approach to assess relationships between dietary intake and metabolic profiling data will allow greater steps to be made in merging nutritional epidemiology with metabonomics.

In man, living environment and lifestyle influence host physiology and microbial populations, and these interactions determine the health of individuals. In particular, dietary preferences are partially triggered by genetically-mediated taste responses to specific foods and may be reflected in the metabolic phenotype. However, identification of dietary metabolic signatures in free-living populations is made difficult by the relatively low amplitude of nutritional modulations when compared to inherent intra- and inter-individual variability that results from numerous confounding factors, e.g. sampling, lifestyle, gender and ageing. The identification of dietary biomarkers lies in the application of chemometrics to recover key metabolic information from the high density and highly variable metabolic phenotypes. One preferred approach is the use of linear regression models such as Partial Least Squares – Discriminant Analysis, whose reliability depends on appropriate validation procedures. However, the high inter- and intra-individual variability in free-living populations makes difficult the direct application of consolidated validation methodologies such as n-fold cross-validation that often leads to unstable solutions. In the present manuscript, we propose a new validation strategy based on the combination of several methodologies, merging n-fold cross validation and bootstrapping procedures with the confirmation of the reliability of the model through the generation of a set of replicate models. The proposed method was employed to validate the identification of dietary specific metabolic biomarkers in 1 H NMR and UPLC TOFMS urine metabolic profiles obtained from 21 free-living subjects stratified according to their sensitivity to propylthiouracil.

Alkylresorcinols (AR) are of interest as biomarkers of wholegrain wheat and rye intake in epidemiological studies and are currently mainly measured by gas chromatography/mass spectrometry (GC/MS) after labour-intensive sample preparation including liquid-liquid extraction, solid-phase extraction (SPE) and chemical derivatization. This manuscript describes and validates an alternative approach based on normal-phase liquid chromatography/tandem mass spectrometry for the quantification of alkylresorcinols in human plasma. The method requires neither SPE nor chemical derivatization and has a shortened run time compared to GC/MS. Normal- and reversed-phase columns and various mobile phases were evaluated with and without previous SPE of the samples. Normal-phase chromatography allowed separation of AR from the interfering triacylglycerols, diacylglycerols and sterols and enabled detection of AR even without SPE of the samples. The described method has instrumental lower limits of detection in the 25-75 pg range, and lower limits of quantification in the 75-250 pg range. Pooled human plasma and (2)H(4)-nonadecylresorcinol (internal standard) was applied to calibrate the method in the 20-12 000 nM range. The overall method showed intra-batch precision of 8.6% and an averaged accuracy of 100.2%. Applications for diverse human plasma samples are presented and are compared with the results determined by GC/MS. Based on the presented data; this method requiring less sample preparation is suggested for further evaluation as an alternative to GC/MS for analysis of biomarkers of wholegrain wheat and rye intake in epidemiological studies.

Isotope labeled tracers are commonly used to quantify the turnover rates of various metabolic intermediates and yield information regarding physiological regulation. Studies often only consider either one nutritional state (fasted or fed) and/or one question (e.g., measure of lipid or protein turnover). In this article, we consider a novel application combining the global approach of metabonomics with widespread stable isotope labeling as a way of being able to map metabolism in open mammalian systems, an approach we call "isotopomics". A total of 45 15-week-old male Zucker rats were administrated different amounts (from 0.5 to 8 mmol/kg) of sodium [1,2-(13)C(2)] acetate. Plasma samples taken at 1, 4, and 24 h were analyzed with (13)C nuclear magnetic resonance (NMR) and gas chromatography/mass spectrometry (GC/MS) to measure (13)C isotopic enrichment of 39 plasma metabolites across a wide range of compound classes (amino acids, short-chain fatty acids, lactate, glucose, and free fatty acids). Isotopic enrichment from 0.1-7.1 mole percent excess (MPE) for the highest dose could be reliably measured in 16 metabolites, and the kinetics of their (13)C isotopic enrichment are reported. Clustering metabolites based on (13)C kinetic curves enabled highlighting of time dependent patterns of (13)C distribution through the key metabolic pathways. These kinetic and quantitative data were reported into a biochemical map. This type of isotopomic approach for mapping dynamic metabolism in an open system has great potential for advancing our mechanistic knowledge of how different interventions and diseases can impact the metabolic response of animals and humans.

This article reports the development and validation of a liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the comprehensive quantification of flavan-3-ol and phenolic acid constituents of milk-based food products. Isotope dilution-based sample preparation consisted of protein precipitation using acidic methanol enriched with the stable isotope labelled internal standards and ultrafiltration to preserve overall polyphenol composition, but to eliminate milk proteins in order to comply with LC. Reversed-phase liquid chromatography was optimized to achieve separation of 22 analytes in 8 min in order to reduce suppression effects, achieve a wide dynamic range and, most importantly, to resolve isomeric compounds. Negative-ion electrospray mass spectrometric detection and fragmentation of analytes was optimized, final transitions were selected for maximized selectivity, reliable quantification and reduction of false positives. The quantitative performance of the method was validated, the main features include: (1) range of lower limits of detection 5–15 ng/mL for flavan-3-ols, 60–100 ng/mL for procyanidins, 1–60 ng/mL for other phenolic acids, (2) lower limits of quantification 15–45 ng/mL for flavan-3-ols, 200–300 ng/mL for procyanidins, 3–200 ng/mL for other phenolic acids, (3) averaged intra-day precision 9.5%, (4) calibrated range 60–300,000 ng/mL for flavan-3-ols, 900–900,000 ng/mL for procyanidins, 9–225,000 ng/mL for other phenolic acids, (5) averaged accuracy 99.5%. Applications for yoghurt and ice-cream products are given. The presented data suggest that this method will help to better characterize the polyphenol composition of milk-based food products for quality control, assessment of dietary intake and for polyphenol bioavailability/bioefficacy studies.

The present paper describes the performance of online, gas-phase hydrogen/deuterium exchange implemented in the ion mobility cell of a quadrupole time-of-flight mass spectrometer. Deuterium oxide and deuterated methanol were utilized to create deuterated vapor that is introduced into the ion mobility region of the mass spectrometer. Hydrogen/deuterium exchange occurs spontaneously in the milliseconds time frame without the need of switching the instrument into ion mobility mode. The exchange was studied in case of low molecular weight molecules and proteins. The observed number of exchanged hydrogens was equal to the number of theoretically exchangeable hydrogens for all low molecular weight compounds. This method needs only minimal instrumental modifications, is simple, cheap, environment friendly, compatible with ultraperformance liquid chromatography, and can be implemented on commercially available instruments. It does not compromise choice of liquid chromatographic solvents and accurate mass or parallel-fragmentation (MS(E)) methods. The performance of this method was compared to that of conventional alternatives where the deuterated solvent is introduced into the cone gas of the instrument. Although the degree of exchange was similar between the two methods, the "cone gas method" requires 10 times higher deuterated solvent volumes (50 muL/min) and offers reduced sensitivity in the tandem mass spectrometry (MS/MS) mode. The presented method is suggested as a standard future element of mass spectrometers to aid online structural characterization of unknowns and to study conformational changes of proteins with hydrogen/deuterium exchange.

Dietary preferences influence basal human metabolism and gut microbiome activity that in turn may have long-term health consequences. The present study reports the metabolic responses of free living subjects to a daily consumption of 40 g of dark chocolate for up to 14 days. A clinical trial was performed on a population of 30 human subjects, who were classified in low and high anxiety traits using validated psychological questionnaires. Biological fluids (urine and blood plasma) were collected during 3 test days at the beginning, midtime and at the end of a 2 week study. NMR and MS-based metabonomics were employed to study global changes in metabolism due to the chocolate consumption. Human subjects with higher anxiety trait showed a distinct metabolic profile indicative of a different energy homeostasis (lactate, citrate, succinate, trans-aconitate, urea, proline), hormonal metabolism (adrenaline, DOPA, 3-methoxy-tyrosine) and gut microbial activity (methylamines, p-cresol sulfate, hippurate). Dark chocolate reduced the urinary excretion of the stress hormone cortisol and catecholamines and partially normalized stress-related differences in energy metabolism (glycine, citrate, trans-aconitate, proline, beta-alanine) and gut microbial activities (hippurate and p-cresol sulfate). The study provides strong evidence that a daily consumption of 40 g of dark chocolate during a period of 2 weeks is sufficient to modify the metabolism of free living and healthy human subjects, as per variation of both host and gut microbial metabolism.

Life stress promotes gut dysfunction, but underlying biochemical events are not well-understood. In the present study, we describe the metabolic events associated with background stress and its potential influence on the response to novel incoming stress stimulus in healthy subjects. A 15 min cold pain test was carried out in healthy men and women stratified according to low (LS; n = 21) and moderate background stress (MS; n = 9) during jejunal segmental perfusion. Cold pain induced a stronger psychological response in MS compared to LS subjects, but similar increases in heart rate and blood pressure. Urine and plasma were analyzed using 1H NMR-based metabonomics. Basal stress levels were imprinted in the metabolic profiles indicating different energy and lipid homeostasis. Cold pain increased gut permeability, as determined by mannitol and xylose levels, the response being greater in LS subjects. Moreover, the rate of plasma clearance of mannitol and xylose was dependent on background stress level and gender. In addition, cold pain modulated the levels of circulating ketone bodies, Krebs's cycle intermediates, glucose, and the glucogenic alanine and lactate, which brings further evidence of an alteration of energy homeostasis. Therefore, unravelling life stress with metabonomics may provide a system biology basis for the clinical management and therapeutic surveillance of gut health and disorders.

Metabonomics is a well established analytical approach for the analysis of physiological regulatory processes via the metabolic profiling of biofluids and tissues in living organisms. Its potential is fully exploited in the field of “nutrimetabonomics” that aims at assessing the metabolic effects of active ingredients and foods in individuals. Yet, one of the greatest challenges in nutrition research is to decipher the critical interactions between mammalian organisms and environmental factors, including the gut microbiota. “Nutrimetabonomics” is today foreseen as a powerful approach for future nutritional programs tailored at health maintenance and disease prevention.

Symbiotic gut microbes can have a significant influence on host health and disease etiology. Here, we assessed the effects of inoculating germfree mice with human baby microbiota (HBM, n=17) on the biochemical composition of intact intestinal tissues (duodenum, jejunum, ileum, proximal and distal colon) using magic-angle-spinning 1H NMR spectroscopy. We compared the HBM tissue metabolite profiles with those from conventional (n=9) and conventionalized (n=10) mice. Each topographical intestinal region showed a specific metabolic profile that was altered differentially by the various microbiomes, especially for osmolytes. In each animal model, duodenum had higher ethanolamine and myo-inositol, and ileum higher taurine and betaine than other gut regions. HBM mice showed lower taurine and myo-inositol in the colon, and all ex-germfree animals had higher taurine, choline and ethanolamine in the jejunum. Interestingly, the jejunum of HBM mice was marked by a higher glutathione level and lower concentrations of its precursor methionine when compared to other groups. Proximal and distal colon tissues were differentiated in the different microbiome models by the concentrations of bacterial products (higher in conventional animals). These studies show the depth of gut microbiome modulations of the intestinal biochemistry.

Multicompartmental metabolic profiling combined with multivariate data analysis offers a unique opportunity to explore the multidimensional metabolic relationships between various biological matrices. Here, we applied unsupervised chemometric methods for integrating 1H NMR metabolic profiles from mouse plasma, liver, pancreas, adrenal gland and kidney cortex matrices in order to infer intercompartments functional links. Principal Component Analysis (PCA) revealed metabolic differences between matrices but contained limited information on intercompartment metabolic relationships. Multiway PCA enabled the assessment of interindividual metabolic variability across multiple compartments in a single model and, therefore, metabolic correlations between different organs and circulating biofluids. However, this approach does not provide information on the relative contribution of one compartment to another. Integration of metabolic profiles using Multivariate Curve Resolution (MCR) and Parallel Factor Analysis (PARAFAC) methods provided an overview of functional relationships across matrices and enabled the characterization of compartment-specific metabolite signatures, the spectrotypes. In particular, the spectrotypes describe biochemical profiles specific or common to different biological compartments. Consequently, MCR-ALS and PARAFAC appeared to be better adapted for stepwise variable and compartment selection for further correlation analysis. Such a combination of chemometric techniques could provide new research avenues to assess the efficacy of drug or nutritional interventions on targeted organs.

Coevolution shapes interorganismal crosstalk leading to profound and diverse cellular and metabolic changes as observed in gut dysbiosis in human diseases. Here, we modulated a simplified gut microbiota using pro-, pre-, and synbiotics to assess the depth of systemic metabolic exchanges in mice, using a multicompartmental modeling approach with metabolic signatures from 10 tissue/fluid compartments. The nutritionally induced microbial changes modulated host lipid, carbohydrate, and amino acid metabolism at a panorganismal scale. Galactosyl-oligosaccharides reduced lipogenesis, triacylglycerol incorporation into lipoproteins and triglyceride concentration in the liver and the kidney. Those changes were not correlated with decreased plasma lipoproteins that were specifically induced by L. rhamnosus supplementation. Additional alteration of transmethylation metabolic pathways (homocysteine-betaine) was observed in the liver and the pancreas following pre- and synbiotic microbial modulation, which may be of interest for control of glucose metabolism and insulin sensitivity. Probiotics also reduced hepatic glycogen and glutamine and adrenal ascorbate with inferred effects on energy homeostasis, antioxidation, and steroidogenesis. These studies show the breadth and the depth of gut microbiome modulations of host biochemistry and reveal that major mammalian metabolic processes are under symbiotic homeostatic control.

In this article we highlight a novel variation on dynamic time warping (DTW) for aligning chromatogram signals. We are interested in sets of signals that can be aligned well locally, but not globally, by shifting individual signals in time. This kind of alignment is often sufficient for aligning gas chromatography data. Regular DTW often "over-warps" signals and introduces artificial features into the aligned data. To overcome this we introduce a variable penalty into the DTW process. The penalty is added to the distance metric whenever a nondiagonal step is taken. We select our penalty based on a morphological dilation of the two signals. We showcase our method by aligning GC/MS datafiles from 712 blood plasma samples processed in 23 batches over the course of 6 months. The use of variable penalty DTW significantly reduces the number of nondiagonal moves. In the examples presented here, this reduction is by a factor of 30, with no cost to visual quality of the alignment.

Nutrition sciences apply transcriptomics, proteomics and metabolomics to molecularly assess nutritional adaptations. Transcriptomics can generate a holistic overview on molecular changes to dietary interventions. Proteomics is most challenging because of the higher complexity of proteomes as compared to transcriptomes and metabolomes. However, it delivers not only markers but also targets of intervention, such as enzymes or transporters, and it is the platform of choice for discovering bioactive food proteins and peptides. Metabolomics is a tool for metabolic characterization of individuals and can deliver metabolic endpoints possibly related to health or disease. Omics in nutrition should be deployed in an integrated fashion to elucidate biomarkers for defining an individual's susceptibility to diet in nutritional interventions and for assessing food ingredient efficacy.

There is evidence from clinical trials that a low capacity to oxidize dietary fats may predispose human individuals to weight gain, obesity, and weight regain following weight loss. These observations have led to a need to identify plasma markers of fat oxidation capacity in order to avoid time consuming direct measurements by indirect calorimetry. The aim of this study was to investigate whether prediction of fat oxidation capacity in an obese population is possible, using 1 H-NMR and LC-MS-based metabolic profiling of blood plasma samples collected before and after a high fat test meal from 100 obese women, who represented the extremes of fat oxidizing capacity. Subject characteristics (baseline anthropometrics, body composition and dietary records) and clinical data (blood values and derived measures for insulin resistance) were recorded into a phenotypic dataset. Filtering by orthogonal signal correction, variable reduction by spectra segmentation, Mann–Whitney U tests and genetic algorithms were applied to spectral data together with partial least squares regression models for prediction. Our findings suggested that only a small fraction of subject variation contained in metabolic profiles is related to fat oxidation capacity and variable reduction methods improved fat oxidation capacity predictability. The LC-MS dataset led to higher specificity (fasting: 86%; postprandial: 73%) and sensitivity (fasting: 75%; postprandial: 75%) than classification using the 1 H-NMR dataset (specificity: fasting: 50%; postprandial: 60%; sensitivity: fasting: 67%; postprandial: 62%). Inclusion of phenotypic variables increased specificity and sensitivity values in both fasting and postprandial time points. However, the moderate specificity and sensitivity values indicated that fat oxidation capacity may only be reflected in subtle differences in the metabolic profiles analyzed. In future studies, metabolomics data may be supplemented with gene variation and gene expression data to caption the properties of fat oxidation capacity more precisely.

Nutritional research is entering a paradigm shift which necessitates the modeling of complex interactions between diet, genetics, lifestyle, and environmental factors. This requires the development of analytical and processing capabilities for multiple data and information sources to be able to improve targeted and personalized nutritional approaches for the maintenance of health. Ideally, such knowledge will be employed to underpin the development of concepts that combine consumer and medical nutrition with diagnostic targeting for early intervention designed to maintain proper metabolic homeostasis and delay the onset of chronic diseases. Nutritional status is fundamental to any description of health, and when combined with other data on lifestyle, environment, and genetics, it can be used to drive stratified or even personalized nutritional strategies for health maintenance and preventive medicine. In this work, we will discuss the importance of developing new nutrient assessment methods and diagnostic capabilities for nutritional status to generate scientific hypotheses and actionable concepts from which to develop targeted and eventually personalized nutritional solutions for health protection. We describe efforts to develop algorithms for dietary nutrient intake and a holistic nutritional profiling platform as the basis of understanding the complex nutrition and health interactome.

Individual human health is determined by a complex interplay between genes, environment, diet, lifestyle, and symbiotic gut microbial activity. Here, we demonstrate a new “nutrimetabonomic” approach in which spectroscopically generated metabolic phenotypes are correlated with behavioral/ psychological dietary preference, namely, “chocolate desiring” or “chocolate indifferent”. Urinary and plasma metabolic phenotypes are characterized by differential metabolic biomarkers, measured using 1 H NMR spectroscopy, including the postprandial lipoprotein profile and gut microbial co-metabolism. These data suggest that specific dietary preferences can influence basal metabolic state and gut microbiome activity that in turn may have long-term health consequences to the host. Nutrimetabonomics appears as a promising approach for the classification of dietary responses in populations and personalized nutritional management.

Support vector machines (SVMs) were used as a novel learning machine in the authentication of the origin of salmon. SVMs have the advantage of relying on a well-developed theory and have already proved to be successful in a number of practical applications. This paper provides a new and effective method for the discrimination between wild and farm salmon and eliminates the possibility of fraud through misrepresentation of the country of origin of salmon. The method requires a very simple sample preparation of the fish oils extracted from the white muscle of salmon samples. (1)H NMR spectroscopic analysis provides data that is very informative for analysing the fatty acid constituents of the fish oils. The SVM has been able to distinguish correctly between the wild and farmed salmon; however ca. 5% of the country of origins were misclassified.

The combination of 1 H NMR fingerprinting with multivariate analysis provides an original approach to study the profile of olive oil in relation to its geographical origin and processing. The present work aims at illustrating the relevance of 1 H NMR fingerprints for assessing the geographical origin and the year of production for olive oils from various Mediterranean areas. Multivariate (chemometric) techniques are able to filter out the most relevant information from a spectrum, e.g. for a classification. Principal component analysis (PCA) was carried out on the ∼12,000 variables (chemical shifts) and four data sets were defined prior to PCA. Linear discriminant analysis (LDA) of the first 50 PC's was applied for classification of olive oil samples (97 or 91) according to the geographic origin and year of production. The data analysis has been carried out with and without outliers, as well. Variable selection for LDA was achieved using: (i) the best five variables and (ii) an interactive forward stepwise manner. Using LDA on the external validation sets the correct classification varied between 47 and 75% (random selection), and between 35 and 92% (Kennard–Stone selection (KS)) depending on geographic origin (country) and production years. A similar success rate could be achieved using partial least squares discriminant analysis (PLS DA). The success rate can be considerably improved by using probabilistic neural networks (PNN). Correct classification by PNN varied between 58 and 100% on the external validation sets. Other chemometric techniques, such as multiple linear regression, or generalized pair-wise correlation, did not give better results.

Eighteen samples of oleoresin of Pinus nigra ssp. laricio were harvested in six locations in Corsica. Eight diterpene acids, six neutral diterpenes and α-pinene were identified and their contents calculated by 13 C NMR spectroscopy, following a procedure recently developed in our laboratories. The results were submitted to chemometric analysis (k-means and principal component analysis) and two clusters were distinguished with respect to the contents of levopimaric acid and dehydroabietic acid.

Dichloromethane extracts were prepared from 38 samples of cork harvested in different locations of Corsica and Sardinia from individual trees of Quercus suber L. Friedelin, 3-α-hydroxyfriedelan-2-one, betulin, betulinic acid, β-sitosterol and sitost-4-en-3-one were identified and their molar percentages were calculated by 13C NMR spectroscopy, following a procedure recently developed by our group. The results were submitted to chemometric analysis (k-means and principal component analysis), which allowed three groups to be distinguished with respect to the content of friedelin, betulinic acid and 3-α-hydroxyfriedelan-2-one.

A lipidomic approach was employed in a clinically well-defined cohort of healthy obese women to explore blood lipidome phenotype ascribed to body fat deposition, with emphasis on epicardial adipose tissue (EAT).The present investigation delivered a lipidomics signature of epicardial adiposity under healthy clinical conditions using a cohort of 40 obese females (age: 25-45 years, BMI: 28-40 kg/m(2) ) not showing any metabolic disease traits. Lipidomics analysis of blood plasma was employed in combination with in vivo quantitation of mediastinal fat depots by computerized tomography.All cardiac fat depots correlated to indicators of hepatic dysfunctions (ALAT and ASAT), which describe physiological connections between hepatic and cardiac steatosis. Plasma lipidomics encompassed overall levels of lipid classes, fatty acid profiles, and individual lipid species. EAT and visceral fat associated with diacylglycerols (DAG), triglycerides, and distinct phospholipid and sphingolipid species. A pattern of DAG and phosphoglycerols was specific to EAT.Human blood plasma lipidomics appears to be a promising clinical and potentially diagnostic readout for patient stratification and monitoring. Association of blood lipidomics signature to regio-specific mediastinal and visceral adiposity under healthy clinical conditions may help provide more biological insights into obese patient stratification for cardiovascular disease risks.

As centenarians well represent the model of healthy aging, there are many important implications in revealing the underlying molecular mechanisms behind such successful aging. By combining NMR metabonomics and shot-gun lipidomics in serum we analyzed metabolome and lipidome composition of a group of centenarians with respect to elderly individuals. Specifically, NMR metabonomics profiling of serum revealed that centenarians are characterized by a metabolic phenotype distinct from that of elderly subjects, in particular regarding amino acids and lipid species. Shot- gun lipidomics approach displays unique changes in lipids biosynthesis in centenarians, with 41 differently abundant lipid species with respect to elderly subjects. These findings reveal phospho/sphingolipids as putative markers and biological modulators of healthy aging, in humans. Considering the particular actions of these metabolites, these data are suggestive of a better counteractive antioxidant capacity and a well-developed membrane lipid remodelling process in the healthy aging phenotype.

BACKGROUND: The combination of maternal obesity in early pregnancy and high protein intake in infant formula feeding might predispose to obesity risk in later life. METHODS: This study assesses the impact of breast- or formula-feeding (differing in protein content by 1.65 or 2.7g/100 kcal) on the metabolism of term infants from overweight and obese mothers. From birth to 3 mo of age, infants received exclusively either breast- or starter formula-feeding and until 6 mo, exclusively either a formula designed for this study or breast-feeding. From 6 to 12 mo, infants received complementary weaning food. Metabonomics was conducted on the infants' urine and stool samples collected at the age of 3, 6, and 12 mo. RESULTS: Infant formula-feeding resulted in higher protein-derived short-chain fatty acids and amino acids in stools. Urine metabonomics revealed a relationship between bacterial processing of dietary proteins and host protein metabolism stimulated with increasing protein content in the formula. Moreover, formula-fed infants were metabolically different from breast-fed infants, at the level of lipid and energy metabolism (carnitines, ketone bodies, and Krebs cycle). CONCLUSION: Noninvasive urine and stool metabolic monitoring of responses to early nutrition provides relevant readouts to assess nutritional requirements for infants' growth.

Background Inflammatory bowel diseases (IBD) are chronic intestinal inflammatory diseases affecting about 1% of western populations. New eating behaviors might contribute to the global emergence of IBD. Although the immunoregulatory effects of omega-3 fatty acids have been well characterized in vitro, their role in IBD is controversial. Methods The aim of this study was to assess the impact of increased fish oil intake on colonic gene expression, eicosanoid metabolism and development of colitis in a mouse model of IBD. Rag-2 deficient mice were fed fish oil (FO) enriched in omega-3 fatty acids i.e. EPA and DHA or control diet for 4 weeks before colitis induction by adoptive transfer of naïve T cells and maintained in the same diet for 4 additional weeks. Onset of colitis was monitored by colonoscopy and further confirmed by immunological examinations. Whole genome expression profiling was made and eicosanoids were measured by HPLC-MS/MS in colonic samples. Results A significant reduction of colonic proinflammatory eicosanoids in FO fed mice compared to control was observed. However, neither alteration of colonic gene expression signature nor reduction in IBD scores was observed under FO diet. Conclusion Thus, increased intake of dietary FO did not prevent experimental colitis.

Increasing evidence points toward the critical and long-term involvement of prenatal and early nutrition and lifestyle on later health and disease risk predisposition. Metabolomics is now a well-established top-down systems biology approach that explores the genetic-environment-health paradigm. The generalization of such approaches has opened new research areas to deepen our current understanding of many physiological processes, as well as foods and nutrient functionalities in target populations. It is envisioned that this will provide new avenues toward preventive medicine and prognostic strategies for tailored therapeutic and personalized nutrition management. The development of systems biology approaches and the new generation of biomarker patterns will provide the opportunity to associate complex metabolic regulations with the etiology of multifactorial pediatric diseases. This may subsequently lead to the development of system mechanistic hypotheses that could be targeted with new nutritional personalized concepts. Therefore, this review aims to describe recent applications of metabolomics in preclinical and clinical fields with insights into disease diagnostics/monitoring and improvement of homeostasis metabolic regulation that may be translatable to novel therapeutic and nutrition advances in pediatric research.

Objective: A new tool to quantify visceral adipose tissue (VAT) over the android region of a total body dual-energy x-ray absorptiometry (DXA) scan has recently been reported. The measurement, CoreScan, is currently available on Lunar iDXA densitometers. The purpose of the study was to determine the precision of the CoreScan VAT measurement, which is critical for understanding the utility of this measure in longitudinal trials. Design and Methods: VAT precision was characterized in both an anthropomorphic imaging phantom (measured on 10 Lunar iDXA systems) and a clinical population consisting of obese women (n = 32). Results: The intrascanner precision for the VAT phantom across 9 quantities of VAT mass (0–1,800 g) ranged from 28.4 to 38.0 g. The interscanner precision ranged from 24.7 to 38.4 g. There was no statistical dependence on the quantity of VAT for either the inter- or intrascanner precision result (p = 0.670). Combining inter- and intrascanner precision yielded a total phantom precision estimate of 47.6 g for VAT mass, which corresponds to a 4.8% coefficient of variance (CV) for a 1 kg VAT mass. Our clinical population, who completed replicate total body scans with repositioning between scans, showed a precision of 56.8 g on an average VAT mass of 1110.4 g. This corresponds to a 5.1% CV. Hence, the in vivo precision result was similar to the phantom precision result. Conclusions: The study suggests that CoreScan has a relatively low precision error in both phantoms and obese women and therefore may be a useful addition to clinical trials where interventions are targeted towards changes in visceral adiposity.

The aging phenotype in humans has been thoroughly studied but a detailed metabolic profiling capable of shading light on the underpinning biological processes of longevity is still missing. Here using a combined metabonomics approach compromising holistic 1H-NMR profiling and targeted MS approaches, we report for the first time the metabolic phenotype of longevity in a well characterized human aging cohort compromising mostly female’s centenarian, elderly, and young individuals. Within increasing age targeted MS profiling of blood serum displayed a marked decrease in tryptophan concentration, while an unique alteration of specific glycerophospholipids and sphingolipids are seen in the longevity phenotype.We hypothesized that the overall lipidome changes specific to longevity putatively reflect centenarians’ unique capacity to adapt/respond to the accumulating oxidative and chronic inflammatory conditions characteristics of their extreme aging phenotype. Our data in centenarians support promotion of a cellular detoxification mechanisms through specific modulation of the arachidonic acid metabolic cascade as we underpinned increased concentration of 8,9-EpETrE, suggesting enhanced cytochrome P450 (CYP) enzyme activity. Such effective mechanism might results in the activation of an anti-oxidative response, as displayed by decreased circulating levels of 9-HODE, and 9-oxoODE, markers of lipid peroxidation and oxidative products of linoleic acid. Lastly, we also revealed that the longevity process deeply affects the structure and composition of the human gut microbiota as shown by the increased extrection of phenylacetylglutamine (PAG) and p-cresol sulfate (PCS) in urine of centenarians. Together, our novel approach in this representative Italian longevity cohort support the hypothesis that a complex remodeling of lipid, amino acid metabolism, and of gut microbiota functionality are key regulatory processes marking exceptional longevity in humans.

Good health is attributed to a combination of genetics, lifestyle, and diet. Evidence for healthy foods requires novel strategies able to predict personalised responses to the food we eat. Because metabolomics allows the analysis of physiological processes through the monitoring of metabolite concentration, it is suited to measure the metabolic effects of diet. This chapter covers the use of biomarkers in nutrition and applications of state-of-the-art metabolomics technologies to understand nutritional effects on metabolism. Special emphasis is given to the metabolic interaction between host and gut microbiota, a key player in the digestion and biotransformation of metabolites from dietary sources.

Systems biology approaches are providing novel insights into the role of nutrition for the management of health and disease. In the present study, we investigated if dietary preference for dark chocolate in healthy subjects may lead to different metabolic response to daily chocolate consumption. Using NMR- and MS-based metabolic profiling of blood plasma and urine, we monitored the metabolic response of 10 participants stratified as chocolate desiring and eating regularly dark chocolate (CD) and 10 participants stratified as chocolate indifferent and eating rarely dark chocolate (CI) to a daily consumption of 50 g of dark chocolate as part of a standardized diet over a one week period. We demonstrated that preference for chocolate leads to different metabolic response to chocolate consumption. Daily intake of dark chocolate significantly increased HDL cholesterol by 6% and decreased polyunsaturated acyl ether phospholipids. Dark chocolate intake could also induce an improvement in the metabolism of long chain fatty acid, as noted by a compositional change in plasma fatty acyl carnitines. Moreover, a relationship between regular long-term dietary exposure to a small amount of dark chocolate, gut microbiota, and phenolics was highlighted, providing novel insights into biological processes associated with cocoa bioactives.

Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial mammalian cross-talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease aetiology, diagnostic stratification and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR) spectroscopy and mass spectrometry (MS) provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation.

Genome-wide association studies (GWASs) have become a very important tool to address the genetic origin of phenotypic variability, in particular associated with diseases. Nevertheless, these types of studies provide limited information about disease etiology and the molecular mechanisms involved. Recently, the incorporation of metabolomics into the analysis has offered novel opportunities for a better understanding of disease-related metabolic deregulation. The pattern emerging from this work is that gene-driven changes in metabolism are prevalent and that common genetic variations can have a profound impact on the homeostatic concentrations of specific metabolites. A particularly interesting aspect of this work takes into account interactions of environment and lifestyle with the genome and how this interaction translates into changes in the metabolome. For instance, the role of PYROXD2 in trimethylamine metabolism points to an interaction between host and microbiome genomes (host/microbiota). Often, these findings reveal metabolic deregulations, which could eventually be tuned with a nutritional intervention. Here we review the development of gene–metabolism association studies from a single-gene/single-metabolite to a genome-wide/metabolome-wide approach and highlight the conceptual changes associated with this ongoing transition. Moreover, we report some of our recent GWAS results on a cohort of 265 individuals from an ethnically diverse population that validate and refine previous findings on gene–urine metabolism interactions. Specifically, our results confirm the effect of PYROXD2 polymorphisms on trimethylamine metabolism and suggest that a previously reported association of N-acetylated compounds with the ALMS1/NAT8 locus is driven by SNPs in the ALMS1 gene.

Recent advances in molecular biology and microbiology have increased awareness on the importance of the gut microbiota to the overall mammalian host's health status. There is therefore increasing interest in nutrition research to characterise the molecular foundations of the gut microbial mammalian crosstalk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology strategies based on the measurement of metabolites to assess the highly complex metabolic exchanges between diverse biological compartments, including organs, biofluids and microbial symbionts. By opening a direct biochemical window into the metabolome, metabonomics is uniquely suited for the identification of biomarkers providing better understanding of these complex metabolic processes. Recent applications of top-down system biology based on (1)H NMR spectroscopy coupled to advanced chemometric modelling approaches provided compelling evidence that system-wide and organ-specific changes in biochemical processes may be finely tuned by gut microbial activities. This review aims at describing current advances in NMR-based metabonomics where the main objective is to discern the molecular pathways and biochemical mechanisms under the influence of the gut microbiota. Furthermore, emphasis is given on nutritional approaches, where the quest for homeostatic balance is dependent not only on the host but also on the nutritional modulation of the gut microbiota-host metabolic interactions, using, for instance, probiotics and prebiotics.

The discovery of biomarkers able to predict biological age of individuals is a crucial goal in aging research. Recently, researchers' attention has turn toward epigenetic markers of aging. Using the Illumina Infinium HumanMethylation450 BeadChip on whole blood DNA from a small cohort of 64 subjects of different ages, we identified 3 regions, the CpG islands of ELOVL2, FHL2, and PENK genes, whose methylation level strongly correlates with age. These results were confirmed by the Sequenom's EpiTYPER assay on a larger cohort of 501 subjects from 9 to 99 years, including 7 cord blood samples. Among the 3 genes, ELOVL2 shows a progressive increase in methylation that begins since the very first stage of life (Spearman's correlation coefficient = 0.92) and appears to be a very promising biomarker of aging.

A two by two experimental study has been designed to determine the effect of gut microbiota on energy metabolism in mouse models. The metabolic phenotype of germ-free (GF, n = 20) and conventional (n = 20) mice was characterized using a NMR spectroscopy-based metabolic profiling approach, with a focus on sexual dimorphism (20 males, 20 females) and energy metabolism in urine, plasma, liver, and brown adipose tissue (BAT). Physiological data of age-matched GF and conventional mice showed that male animals had a higher weight than females in both groups. In addition, conventional males had a significantly higher total body fat content (TBFC) compared to conventional females, whereas this sexual dimorphism disappeared in GF animals (i.e., male GF mice had a TBFC similar to those of conventional and GF females). Profiling of BAT hydrophilic extracts revealed that sexual dimorphism in normal mice was absent in GF animals, which also displayed lower BAT lactate levels and higher levels of (D)-3-hydroxybutyrate in liver, plasma, and BAT, together with lower circulating levels of VLDL. These data indicate that the gut microbiota modulate the lipid metabolism in BAT, as the absence of gut microbiota stimulated both hepatic and BAT lipolysis while inhibiting lipogenesis. We also demonstrated that (1)H NMR metabolic profiles of BAT were excellent predictors of BW and TBFC, indicating the potential of BAT to fight against obesity.

Dual-energy X-ray absorptiometry (DXA) is a well-accepted technique for measuring body composition. Knowledge of measurement precision is critical for monitoring of changes in bone mineral content (BMC), and fat and lean masses. The purpose of this study was to characterize in vivo precision of total body and regional body composition parameters using the GE Lunar iDXA (GE Healthcare Lunar, Madison, WI) system in a sample of nonobese subjects. We also evaluated the difference between expert and automatic region-of-interest (ROI) analysis on body composition precision. To this end, 2 total body scans were performed on each subject with repositioning between scans. Total body precision for BMC, fat and lean mass were 0.5%, 1.0%, and 0.5% coefficient of variation (CV), respectively. Regional body composition precision error was less than 2.5% CV for all regions except arms. Precision error was higher for the arms (CV: BMC 1.5%; fat mass 2.8%; lean mass 1.6%), likely owing to the placement of arms relative to torso leading to differences in ROI. There was a significant correlation between auto ROI and expert ROI ( r >0.99). Small, but statistically significant differences were found between auto and manual ROI. Differences were small in total body, leg, trunk, and android and gynoid regions (0.004–2.8%), but larger in arm region (3.0–6.3%). Total body and regional precision for iDXA are small and it is suggested that iDXA may be useful for monitoring changes in body composition during longitudinal trials.

Under most physiological conditions, glucose, or carbohydrate (CHO), homeostasis is tightly regulated. In order to mechanistically appraise the origin of circulating glucose (e.g. via either gluconeogenesis, glycogenolysis or oral glucose intake), and its regulation and oxidation, the use of stable isotope tracers is now a well-accepted analytical technique. Methodologically, liquid chromatography coupled to isotope ratio mass spectrometry (LC/IRMS) can replace gas chromatography coupled to combustion-isotope ratio mass spectrometry (GC/C/IRMS) for carrying out compound-specific (13)C isotopic analysis. The LC/IRMS approach is well suited for studying glucose metabolism, since the plasma glucose concentration is relatively high and the glucose can readily undergo chromatography in an aqueous mobile phase. Herewith, we report two main methodological approaches in a single instrument: (1) the ability to measure the isotopic enrichment of plasma glucose to assess the efficacy of CHO-based treatment (cocoa-enriched) during cycling exercise with healthy subjects, and (2) the capacity to carry out bulk isotopic analysis of labeled solutions, which is generally performed with an elemental analyzer coupled to IRMS. For plasma samples measured by LC/IRMS the data show a isotopic precision SD(δ(13)C) and SD(APE) of 0.7 ‰ and 0.001, respectively, with δ(13)C and APE values of -25.48 ‰ and 0.06, respectively, being generated before and after tracer administration. For bulk isotopic measurements, the data show that the presence of organic compounds in the blank slightly affects the δ(13)C values. Despite some analytical limitations, we clearly demonstrate the usefulness of the LC/IRMS especially when (13)C-glucose is required during whole-body human nutritional studies.

The pig is a single-stomached omnivorous mammal and is an important model of human disease and nutrition. As such, it is necessary to establish a metabolic framework from which pathology-based variation can be compared. Here, a combination of one and two-dimensional (1)H and (13)C nuclear magnetic resonance spectroscopy (NMR) and high-resolution magic angle spinning (HR-MAS) NMR was used to provide a systems overview of porcine metabolism via characterisation of the urine, serum, liver and kidney metabolomes. The metabolites observed in each of these biological compartments were found to be qualitatively comparable to the metabolic signature of the same biological matrices in humans and rodents. The data were modelled using a combination of principal components analysis and Venn diagram mapping. Urine represented the most metabolically distinct biological compartment studied, with a relatively greater number of NMR detectable metabolites present, many of which are implicated in gut-microbial co-metabolic processes. The major inter-species differences observed were in the phase II conjugation of extra-genomic metabolites; the pig was observed to conjugate p-cresol, a gut microbial metabolite of tyrosine, with glucuronide rather than sulfate as seen in man. These observations are important to note when considering the translatability of experimental data derived from porcine models.

NELSON, A. R., S. M. PHILLIPS, T. STELLINGWERFF, S. REZZI, S. J. BRUCE, I. BRETON, A. THORIMBERT, P. A. GUY, J. CLARKE, S. BROADBENT, and D. S. ROWLANDS. A Protein–Leucine Supplement Increases Branched-Chain Amino Acid and Nitrogen Turnover But Not Performance. Med. Sci. Sports Exerc., Vol. 44, No. 1, pp. 57–68, 2012. Purpose: This study aimed to determine the effect of postexercise protein–leucine coingestion with CHO–lipid on subsequent high-intensity endurance performance and to investigate candidate mechanisms using stable isotope methods and metabolomics. Methods: In this double-blind, randomized, crossover study, 12 male cyclists ingested a leucine/protein/CHO/fat supplement (LEUPRO 7.5/20/89/22 gIh j1 , respectively) or isocaloric CHO/fat control (119/22 gIh j1 ) 1–3 h after exercise during a 6-d training block (intense intervals, recovery, repeated-sprint performance rides). Daily protein intake was clamped at 1.9 gIkg j1 Id j1 (LEUPRO) and 1.5 gIkg j1 Id j1 (control). Stable isotope infusions (1- 13 C-leucine and 6,6- 2 H2-glucose), mass spectrometry–based metabolomics, and nitrogen balance methods were used to determine the effects of LEUPRO on whole-body branched-chain amino acid (BCAA) and glucose metabolism and protein turnover. Results: After exercise, LEUPRO increased BCAA levels in plasma (2.6-fold; 90% confidence limits = /1.1) and urine (2.8-fold; /1.2) and increased products of BCAA metabolism plasma acylcarnitine C5 (3.0-fold; /0.9) and urinary leucine (3.6-fold; /1.3) and A-aminoisobutyrate (3.4-fold; /1.4), indicating that ingesting E10 g leucine per hour during recovery exceeds the capacity to metabolize BCAA. Furthermore, LEUPRO increased leucine oxidation (5.6-fold; /1.1) and nonoxidative disposal (4.8-fold; /1.1) and left leucine balance positive relative to control. With the exception of day 1 (LEUPRO = 17 T 20 mg NIkg j1 , control = j90 T 44 mg NIkg j1 ), subsequent (days 2–5) nitrogen balance was positive for both conditions (LEUPRO = 130 T 110 mg NIkg j1 , control = 111 T 86 mg NIkg j1 ). Compared with control feeding, LEUPRO lowered the serum creatine kinase concentration by 21%–25% (90% confidence limits = T14%), but the effect on sprint power was trivial (day 4 = 0.4% T 1.0%, day 6 = j0.3% T 1.0%). Conclusions: Postexercise protein–leucine supplementation saturates BCAA metabolism and attenuates tissue damage, but effects on subsequent intense endurance performance may be inconsequential under conditions of positive daily nitrogen balance.

This study reports a liquid chromatography-mass spectrometry method for the detection of polyphenol-derived metabolites in human plasma without enzymatic treatment after coffee consumption. Separation of available standards was achieved by reversed-phase ultra performance liquid chromatography and detection was performed by high resolution mass spectrometry in negative electrospray ionization mode. This analytical method was then applied for the identification and relative quantification of circulating coffee metabolites. A total of 34 coffee metabolites (mainly reduced, sulfated and methylated forms of caffeic acid, coumaric acid, caffeoylquinic acid and caffeoylquinic acid lactone) were identified based on mass accuracy (

The gut microbiota enhances the host’s metabolic capacity for processing nutrients and drugs and modulate the activities of multiple pathways in a variety of organ systems. We have probed the systemic metabolic adaptation to gut colonization for 20 days following exposure of axenic mice (n = 35) to a typical environmental microbial background using high-resolution 1H nuclear magnetic resonance (NMR) spectroscopy to analyze urine, plasma, liver, kidney, and colon (5 time points) metabolic profiles. Acquisition of the gut microbiota was associated with rapid increase in body weight (4%) over the first 5 days of colonization with parallel changes in multiple pathways in all compartments analyzed. The colonization process stimulated glycogenesis in the liver prior to triggering increases in hepatic triglyceride synthesis. These changes were associated with modifications of hepatic Cyp8b1 expression and the subsequent alteration of bile acid metabolites, including taurocholate and tauromuricholate, which are essential regulators of lipid absorption. Expression and activity of major drug-metabolizing enzymes (Cyp3a11 and Cyp2c29) were also significantly stimulated. Remarkably, statistical modeling of the interactions between hepatic metabolic profiles and microbial composition analyzed by 16S rRNA gene pyrosequencing revealed strong associations of the Coriobacteriaceae family with both the hepatic triglyceride, glucose, and glycogen levels and the metabolism of xenobiotics. These data demonstrate the importance of microbial activity in metabolic phenotype development, indicating that microbiota manipulation is a useful tool for beneficially modulating xenobiotic metabolism and pharmacokinetics in personalized health care., IMPORTANCE Gut bacteria have been associated with various essential biological functions in humans such as energy harvest and regulation of blood pressure. Furthermore, gut microbial colonization occurs after birth in parallel with other critical processes such as immune and cognitive development. Thus, it is essential to understand the bidirectional interaction between the host metabolism and its symbionts. Here, we describe the first evidence of an in vivo association between a family of bacteria and hepatic lipid metabolism. These results provide new insights into the fundamental mechanisms that regulate host-gut microbiota interactions and are thus of wide interest to microbiological, nutrition, metabolic, systems biology, and pharmaceutical research communities. This work will also contribute to developing novel strategies in the alteration of host-gut microbiota relationships which can in turn beneficially modulate the host metabolism.

Today metabolomic approaches are aiming at the quest for homeostatic balance which is dependent not only on the host but also on the crucial metabolic interactions with microbial symbionts. Indeed, metabolomics technologies are broadening our knowledge on the roles of the human gut microbiota and how they influence health and disease etiology. While the mechanisms of action of our gut symbionts are only now being unveiled, potential health benefits are being suggested by modulating the microbial functional ecology with the use of probiotics. This chapter discusses latest metabolomics applications to explore mammalian gut microbial metabolic interactions with key emphasis on deciphering bacterial role in maintaining host health balance, as well as preventing and treating metabolic disorders.

A major source of intestinal metabolites results from both host and microbial processing of dietary nutrients. (1)H NMR-based metabolic profiling of mouse feces was carried out over time in different microbiome mouse models, including conventional (n = 9), conventionalized (n = 10), and "humanized" gnotobiotic mice inoculated with a model of human baby microbiota (HBM, n = 17). HBM mice were supplemented with Lactobacillus paracasei with (n = 10) and without (n = 7) prebiotics. Animals not supplemented with prebiotics received a diet enriched in glucose and lactose as placebo. In conventionalized animals, microbial populations and activities converged in term of multivariate mapping toward conventional mice. Both groups decreased bacterial processing of dietary proteins when switching to a diet enriched in glucose and lactose, as described with low levels of 5-aminovalerate, acetate, and propionate and high levels of lysine and arginine. The HBM model differs from conventional and conventionalized microbiota in terms of type, proportion, and metabolic activity of gut bacteria (lower short chain fatty acids (SCFAs), lactate, 5-aminovalerate, and oligosaccharides, higher bile acids and choline). The probiotics supplementation of HBM mice was associated with a specific amino acid pattern that can be linked to L. paracasei proteolytic activities. The combination of L. paracasei with the galactosyl-oligosaccharide prebiotics was related to the enhanced growth of bifidobacteria and lactobacilli, and a specific metabolism of carbohydrates, proteins, and SCFAs. The present study describes how the assessment of metabolic changes in feces may provide information for studying nutrient-microbiota relationships in different microbiome mouse models.

There is a substantial amount of published literature on the bioavailability of various coffee components including the most abundant metabolites, caffeic and ferulic acids. Surprisingly, to date, the appearance of dimethoxycinnamic acid derivatives in humans has not been reported despite the fact that methylated form of catechol-type polyphenols could help maintain, modify or even improve their biological activities. This study reports an LC–MS method for the detection of dimethoxycinnamic acid in human plasma after treatment with an esterase. Liquid chromatography, including the combination of methanol and acetonitrile as organic eluent, was optimized to resolve all interferences and enable reliable detection and identification of 3,4-dimethoxycinnamic and 3,4-dimethoxy-dihydrocinnamic acids. In addition to the good mass accuracy achieved (better than 5 ppm), tandem mass spectrometric and co-chromatography experiments further confirmed the identity of the compounds. The optimized method was applied to analyze samples obtained immediately, 1 and 10 h after coffee ingestion. The results show that in particular 3,4-dimethoxycinnamic acid appears in high abundance (∼380 nM at 60 min) in plasma upon coffee intake, indicating that it is important to consider these derivatives in future bioavailability and bioefficacy studies.

A global metabolic profiling methodology based on gas chromatography coupled to time of flight mass spectrometry (GC TOFMS) for human plasma was applied to a human exercise study focused on the effects of beverages containing glucose galactose or fructose taken after exercise and throughout a recovery period of 6. h and 45. min. One group of 10 well trained male cyclists performed 3 experimental sessions on separate days (randomized single center). After performing a standardized depletion protocol on a bicycle subjects consumed one of three different beverages: maltodextrin (MD). +. glucose (2:1 ratio) MD. +. galactose (2:1) and MD. +. fructose (2:1) consumed at an average of 1.25. g of carbohydrate (CHO) ingested per minute. Blood was taken straight after exercise and every 45. min within the recovery phase. With the resulting blood plasma insulin free fatty acid (FFA) profile glucose and GC TOFMS global metabolic profiling measurements were performed. The resulting profiling data was able to match the results obtained from the other clinical measurements with the addition of being able to follow many different metabolites throughout the recovery period. The data quality was assessed with all the labelled internal standards yielding values of