An exploratory NMR nutri-metabonomic investigation reveals dimethyl sulfone as a dietary biomarker for onion intake

Inulin Supplementation Modulates the Hepatic Transcriptome, Metabolome, and Ferritin Content in Ovariectomized Rats

SCOPE

Liver is an important metabolic organ regulating whole-body homeostasis. This study aims to investigate how prebiotic-induced changes in the metabolic activity of the gut microbiome (GM) and dietary calcium depletion modulates the hepatic metabolome and transcriptome.

METHODS AND RESULTS

The serum metabolome, liver metabolome, and transcriptome are determined on samples from ovariectomized (OVX) rats fed a control diet (Control, n = 7), a control diet supplemented with 5% w/w inulin (Inulin, n = 7), or a calcium-deficient diet (CaDef, n = 7). Inulin fortification is associated with higher serum concentrations of acetate, 3-hydroxybutyrate, and reduced concentration of dimethyl sulfone, revealing that changes in the metabolic activity of the GM are reflected in circulating metabolites. Metabolomics also reveal that the inulin-fortified diet results in lower concentrations of hepatic glutamate, serine, and hypoxanthine while transcriptomics reveal accompanying effects on the hepatic expression of ferric iron binding-related genes. Inulin fortification also induces effects on the hepatic expression of genes involved in olfactory transduction, suggesting that prebiotics regulate liver function through yet unidentified mechanisms involving olfactory receptors.

CONCLUSION

Inulin ingestion impacts hepatic gene expression and is associated with an upregulation of ferritin synthesis-related genes and liver ferritin content.

1H NMR Combined with Multivariate Statistics for Discrimination of Female and Male Flower Buds of Populus tomentosa

¹H Nuclear Magnetic Resonance (¹H NMR) combined with multivariate statistics was adopted to discriminate female and male flower buds of Populus tomentosa in the study. Samples of 11 female and 16 male flower buds of P. tomentosa were collected in Beijing, China. ¹H NMR spectra were acquired on a 400 MHz spectrometer. In total, 30 chemical compounds were identified with standards and literature according to chemical shifts, peak areas, and multiplicity. Principal component analysis (PCA), hierarchical clustering analysis (HCA), and supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to discriminate female and male flower buds. An apparent grouping trend (R²X, 0.809; Q², 0.903) between female and male groups was exhibited with PCA and HCA. The two groups were also well discriminated with OPLS-DA (R²X, 0.808; R²Y, 0.976; Q², 0.960). Combined with variable importance in projection (VIP) > 1.0 and p < 0.05 of OPLS-DA, it was found that the content of daucosterol, β-sitosterol, ursolic acid, and betulonic acid in male group was higher than that in female, which should be the key differences of chemical constituents in female and male flower buds of P. tomentosa. The study demonstrated that ¹H NMR combined with multivariate statistics could be used to discriminate female and male plants and clarify differences, which provided a novel method to identify the gender of dioecious plants.

A Comprehensive Targeted Metabolomics Assay for Crop Plant Sample Analysis

Metabolomics plays an important role in various fields from health to agriculture. However, the comprehensive quantitative metabolomic analysis of plants and plant metabolites has not been widely performed. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based plant metabolomics offers the sensitivity and breadth of coverage for both phenotyping and disease diagnosis of plants. Here, we report a high-coverage and quantitative MS-based assay for plant metabolite analysis. The assay detects and quantifies 206 primary and secondary plant metabolites, including many key plant hormones. In total, it measures 28 amino acids and derivatives, 27 organic acids, 20 biogenic amines and derivatives, 40 acylcarnitines, 90 phospholipids and C-6 sugars. All the analysis methods in this assay are based on LC-MS/MS techniques using both positive and negative-mode multiple reaction monitoring (MRM). The recovery rates of spiked plant samples at three different concentration levels (low, medium and high) ranged from 80% to 120%, with satisfactory precision values of less than 20%. This targeted plant metabolomic assay has been successfully applied to the analysis of large numbers of pine and spruce needle samples, canola root samples, as well as cannabis samples. Moreover, the assay was specifically developed in a 96-well plate format, which enables automated, high-throughput sample analysis. This assay has already been used to analyze over 1500 crop plant samples in less than two months.

Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet

OBJECTIVES

The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss.

METHODS

The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight.

RESULTS

Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research.

CONCLUSIONS

Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.

Tissue, urine and blood metabolite signatures of chronic kidney disease in the 5/6 nephrectomy rat model

INTRODUCTION

Progressive chronic kidney disease (CKD) is an important cause of morbidity and mortality. It has a long asymptomatic phase, where routine blood tests cannot identify early functional losses, and therefore identifying common mechanisms across the many etiologies is an important goal.

OBJECTIVES

Our aim was to characterize serum, urine and tissue (kidney, lung, heart, spleen and liver) metabolomics changes in a rat model of CKD.

METHODS

A total of 17 male Wistar rats underwent 5/6 nephrectomy, whilst 13 rats underwent sham operation. Urine samples were collected weekly, for 6 weeks; blood was collected at weeks 0, 3 and 6; and tissue samples were collected at week 6. Samples were analyzed on a nuclear magnetic resonance spectroscopy platform with multivariate and univariate data analysis.

RESULTS

Changes in several metabolites were statistically significant. Allantoin was affected in all compartments. Renal asparagine, creatine, hippurate and trimethylamine were significantly different; in other tissues creatine, dimethylamine, dimethylglycine, trigonelline and trimethylamine were significant. Benzoate, citrate, dimethylglycine, fumarate, guanidinoacetate, malate, myo-inositol and oxoglutarate were altered in urine or serum.

CONCLUSION

Although the metabolic picture is complex, we suggest oxidative stress, the gut-kidney axis, acid-base balance, and energy metabolism as promising areas for future investigation.

Use of 1H NMR to Detect the Percentage of Pure Fruit Juices in Blends

The consumption of high-nutritional-value juice blends is increasing worldwide and, considering the large market volume, fraud and adulteration represent an ongoing problem. Therefore, advanced anti-fraud tools are needed. This study aims to verify the potential of ¹H NMR combined with partial least squares regression (PLS) to determine the relative percentage of pure fruit juices in commercial blends. Apple, orange, pineapple, and pomegranate juices were selected to set up an experimental plan and then mixed in different proportions according to a central composite design (CCD). NOESY (nuclear Overhauser enhancement spectroscopy) experiments that suppress the water signal were used. Considering the high complexity of the spectra, it was necessary to pretreat and then analyze by chemometric tools the large amount of information contained in the raw data. PLS analysis was performed using venetian-blind internal cross-validation, and the model was established using different chemometric indicators (RMSEC, RMSECV, RMSEP, R²_CAL, R²_CV, R²_PRED). PLS produced the best model, using five factors explaining 94.51 and 88.62% of the total variance in X and Y, respectively. The present work shows the feasibility and advantages of using ¹H NMR spectral data in combination with multivariate analysis to develop and optimize calibration models potentially useful for detecting fruit juice adulteration.

Biomarkers of food intake for Allium vegetables

Allium vegetables are widely consumed around the world and are known for their potential bioactive components improving human health. These effects have been extensively investigated; however, the results were inconsistent in human studies. Biomarkers of food intake (BFIs) could provide objective measurements of food intake in observational studies and assess compliance in intervention studies. Therefore, the discovery and application of BFIs for Allium vegetables would facilitate the exploring and understanding of the health benefit of Allium vegetables. In this manuscript, we reviewed the currently used and potential candidate BFIs for Allium vegetables and evaluated their levels of validation. S-Allylmercapturic acid (ALMA), allyl methyl sulfide (AMS), allyl methyl sulfoxide (AMSO), allyl methyl sulfone (AMSO2), and S-allylcysteine (SAC), which are derived from organosulfur compounds, were shown to be promising candidate BFIs for garlic consumption. Further validation is needed to assess their robustness and concordance with other measures. Their applicability for the whole food group should be evaluated as well. N-Acetyl-S-(2-carboxypropyl)cysteine (CPMA) was detected in high levels in urine after both garlic and onion intake, suggesting that it may be used for the assessment of intake of Allium food group. The available information regarding its kinetics, robustness, and analytical performance is limited and needs to be assessed in further studies. No candidate BFIs specific to intake of onion, leek, chives, shallots, or ramsons were found. Untargeted metabolomics studies and further validation studies should be performed to discover more reliable BFIs for individual Allium vegetables and the whole food group. This paper serves as an example of Biomarker of Food Intake Reviews (BFIRev) and biomarker of food intake validation procedures.

Simultaneous classification of multiple classes in NMR metabolomics and vibrational spectroscopy using interval-based classification methods: iECVA vs iPLS-DA

Interval based chemometric algorithms have proven to be very powerful for spectral alignments, spectral regressions and spectral classifications. The interval-based methods may not only improve the performance, but also reduce model complexity and enhance the spectral interpretation. Extended Canonical Variate Analysis (ECVA) is a powerful method for multiple group classifications of multivariate data and can easily be extended to an interval approach, iECVA. This study outlines the iECVA method and compares its performance to interval Partial Least Squares Discriminant Analysis (iPLS-DA) on three spectroscopic datasets from Nuclear Magnetic Resonance (NMR), Near Infrared (NIR) and Infrared (IR) spectroscopy, respectively. The results invariantly show that the interval-based classification methods greatly enhance the interpretability of the models by identifying important spectral regions, which facilitate interpretation and biomarker discovery. Although the results for the two methods are similar regarding the number of misclassifications and identified important regions, the model complexity of the PLS-DA proved to consistently lower than the ECVA. The Matlab source codes for both iECVA and iPLS-DA are made freely available at www.

MODELS

life.ku.dk.

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).

Optimized Phenotypic Biomarker Discovery and Confounder Elimination via Covariate-Adjusted Projection to Latent Structures from Metabolic Spectroscopy Data

Metabolism is altered by genetics, diet, disease status, environment, and many other factors. Modeling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data, we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-adjusted projections to latent structures (CA-PLS) are exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS, we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques.

Metabolomics for Plant Improvement: Status and Prospects

Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement.

Integrated Analytical and Statistical Two-Dimensional Spectroscopy Strategy for Metabolite Identification: Application to Dietary Biomarkers

A major purpose of exploratory metabolic profiling is for the identification of molecular species that are statistically associated with specific biological or medical outcomes; unfortunately, the structure elucidation process of unknowns is often a major bottleneck in this process. We present here new holistic strategies that combine different statistical spectroscopic and analytical techniques to improve and simplify the process of metabolite identification. We exemplify these strategies using study data collected as part of a dietary intervention to improve health and which elicits a relatively subtle suite of changes from complex molecular profiles. We identify three new dietary biomarkers related to the consumption of peas (N-methyl nicotinic acid), apples (rhamnitol), and onions (N-acetyl-S-(1Z)-propenyl-cysteine-sulfoxide) that can be used to enhance dietary assessment and assess adherence to diet. As part of the strategy, we introduce a new probabilistic statistical spectroscopy tool, RED-STORM (Resolution EnhanceD SubseT Optimization by Reference Matching), that uses 2D J-resolved 1H NMR spectra for enhanced information recovery using the Bayesian paradigm to extract a subset of spectra with similar spectral signatures to a reference. RED-STORM provided new information for subsequent experiments (e.g., 2D-NMR spectroscopy, solid-phase extraction, liquid chromatography prefaced mass spectrometry) used to ultimately identify an unknown compound. In summary, we illustrate the benefit of acquiring J-resolved experiments alongside conventional 1D 1H NMR as part of routine metabolic profiling in large data sets and show that application of complementary statistical and analytical techniques for the identification of unknown metabolites can be used to save valuable time and resources.

Methylsulfonylmethane: Applications and Safety of a Novel Dietary Supplement

Methylsulfonylmethane (MSM) has become a popular dietary supplement used for a variety of purposes, including its most common use as an anti-inflammatory agent. It has been well-investigated in animal models, as well as in human clinical trials and experiments. A variety of health-specific outcome measures are improved with MSM supplementation, including inflammation, joint/muscle pain, oxidative stress, and antioxidant capacity. Initial evidence is available regarding the dose of MSM needed to provide benefit, although additional work is underway to determine the precise dose and time course of treatment needed to provide optimal benefits. As a Generally Recognized As Safe (GRAS) approved substance, MSM is well-tolerated by most individuals at dosages of up to four grams daily, with few known and mild side effects. This review provides an overview of MSM, with details regarding its common uses and applications as a dietary supplement, as well as its safety for consumption.

Metabolomic fingerprint of severe obesity is dynamically affected by bariatric surgery in a procedure-dependent manner

BACKGROUND

Obesity is associated with multiple diseases. Bariatric surgery is the most effective therapy for severe obesity that can reduce body weight and obesity-associated morbidity. The metabolic alterations associated with obesity and respective changes after bariatric surgery are incompletely understood.

OBJECTIVE

We comprehensively assessed metabolic alterations associated with severe obesity and distinct bariatric procedures.

DESIGN

In our longitudinal observational study, we applied a (1)H-nuclear magnetic resonance-based global, untargeted metabolomics strategy on human serum samples that were collected before and repeatedly ≤1 y after distinct bariatric procedures [i.e., a sleeve gastrectomy, proximal Roux-en Y gastric bypass (RYGB), and distal RYGB]. For comparison, we also analyzed serum samples from normal-weight and less-obese subjects who were matched for 1-y postoperative body mass index (BMI) values of the surgical groups.

RESULTS

We identified a metabolomic fingerprint in obese subjects that was clearly discriminated from that of normal-weight subjects. Furthermore, we showed that bariatric surgery (sleeve gastrectomy and proximal and distal RYGB) dynamically affected this fingerprint in a procedure-dependent manner, thereby establishing new fingerprints that could be discriminated from those of BMI-matched and normal-weight control subjects. Metabolites that largely contributed to the metabolomic fingerprints of severe obesity were aromatic and branched-chain amino acids (elevated), metabolites related to energy metabolism (pyruvate and citrate; elevated), and metabolites suggested to be derived from gut microbiota (formate, methanol, and isopropanol; all elevated).

CONCLUSION

Our data indicate that bariatric surgery, irrespective of the specific kind of procedure used, reverses most of the metabolic alterations associated with obesity and suggest profound changes in gut microbiome-host interactions after the surgery. This trial was registered at clinicaltrials.gov as NCT02480322.

Combined 1H-NMR and 1H-13C HSQC-NMR to improve urinary screening in autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental diseases with complex genetic and environmental etiological factors. Although genetic causes play a significant part in the etiology of ASD, metabolic disturbances may also play a causal role or modulate the clinical features of ASD. The number of ASD studies involving metabolomics is increasing, and sometime with conflicting findings. We assessed the metabolomics profiling of urine samples to determine a comprehensive biochemical signature of ASD. Furthermore, to date no study has combined metabolic profiles obtained from different analytical techniques to distinguish patient with ASD from healthy individuals. We obtained (1)H-NMR spectra and 2D (1)H-(13)C HSQC NMR spectra from urine samples of patients with ASD or healthy controls. We analyzed these spectra by multivariate statistical data analysis. The OPLS-DA model obtained from (1)H NMR spectra showed a good discrimination between ASD samples and non-ASD samples (R(2)Y(cum) = 0.70 and Q(2) = 0.51). Combining the (1)H NMR spectra and the 2D (1)H-(13)C HSQC NMR spectra increased the overall quality and predictive value of the OPLS-DA model (R(2)Y(cum) = 0.84 and Q(2) = 0.71), leading to a better sensitivity and specificity. Urinary excretion of succinate, glutamate and 3-methyl-histidine differed significantly between ASD and non-ASD samples. Urinary screening of children with neurodevelopmental disorders by combining NMR spectroscopies (1D and 2D) in multivariate analysis is a better sensitive and a straightforward method that could help the diagnosis ASD.

Metabolic fingerprint of dimethyl sulfone (DMSO2) in microbial-mammalian co-metabolism

There is growing awareness that intestinal microbiota alters the energy harvesting capacity of the host and regulates metabolism. It has been postulated that intestinal microbiota are able to degrade unabsorbed dietary components and transform xenobiotic compounds. The resulting microbial metabolites derived from the gastrointestinal tract can potentially enter the circulation system, which, in turn, affects host metabolism. Yet, the metabolic capacity of intestinal microbiota and its interaction with mammalian metabolism remains largely unexplored. Here, we review a metabolic pathway that integrates the microbial catabolism of methionine with mammalian metabolism of methanethiol (MT), dimethyl sulfide (DMS), and dimethyl sulfoxide (DMSO), which together provide evidence that supports the microbial origin of dimethyl sulfone (DMSO2) in the human metabolome. Understanding the pathway of DMSO2 co-metabolism expends our knowledge of microbial-derived metabolites and motivates future metabolomics-based studies on ascertaining the metabolic consequences of intestinal microbiota on human health, including detoxification processes and sulfur xenobiotic metabolism.

The human urine metabolome

Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

Advances in Nutritional Metabolomics

Metabolomics is maturing as an experimental approach in nutrition science, and it is a useful analysis for revealing systems biology outcomes associated with changes in diet. A major goal of this review is to present the rapidly evolving body of scientific literature that seeks to reveal connections between an individual's metabolic profile and experimentally manipulated or naturally varied dietary intakes. Metabolite profiles in tissue, serum, urine, or stool reflect changes in metabolic pathways that respond to dietary intervention which makes them accessible samples for revealing metabolic effects of diet. Three broadly defined areas of investigation related to dietary-metabolomic strategies include: (1) describing the metabolite variation within and between dietary exposures or interventions; (2) characterizing the metabolic response to dietary interventions with respect to time; and (3) assessing individual variation in baseline nutritional health and/or disease status. An overview of metabolites that were responsive to dietary interventions as reported from original research in human or animal studies is provided and illustrates the breadth of metabolites affected by dietary intervention. Advantages and drawbacks for assessing metabolic changes are discussed in relation to types of metabolite analysis platforms. A combination of targeted and non-targeted global profiling studies as a component of future dietary intervention trials will increase our understanding of nutrition in a systems context.

Application of one- and two-dimensional NMR spectroscopy for the characterization of Protected Designation of Origin Lambrusco wines of Modena

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.

Investigations of La Rioja terroir for wine production using 1H NMR metabolomics

In this study, La Rioja wine terroir was investigated by the use of (1)H NMR metabolomics on must and wine samples. Rioja is a small wine region in central northern Spain which can geographically be divided into three subareas (Rioja Alta, Rioja Baja, and Rioja Alavesa). The winemaking process from must, through alcoholic and malolactic fermentation, was followed by NMR metabolomics and chemometrics of nine wineries in the Rioja subareas (terroirs). Application of interval extended canonical variate analysis (iECVA) showed discriminative power between wineries which are geographically very close. Isopentanol and isobutanol compounds were found to be key biomarkers for this differentiation.

Metabolomics study on Fuzi and its processed products using ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry coupled with pattern recognition analysis

The lateral root of Aconitum carmichaelii Debx is named "Fuzi" which is widely distributed across Asia and North America and has been used to relieve joint pain and treat rheumatic diseases for over two thousand years. However, it has very narrow therapeutic ranges and despite the toxicological risk, its usage remains very high. A traditional Chinese processing approach (Paozhi, detoxifying measure) is necessary to remove the poisonous Aconitum alkaloids mainly deriving from the diester diterpene alkaloids (DDAs) including aconitine, mesaconitine and hypaconitine. They can be decomposed into less or non-toxic derivatives through Paozhi that plays an essential role in detoxification. Processed Fuzi is mainly focused on the three main forms of Yanfuzi (YFZ), Heishunpian (HSP) and Baifupian (BFP) which are highly desirable in order to guarantee the clinical safety and their low toxicity in decoctions. The difference in metabolomic characters between Fuzi and its processed preparations is still completely unclear. Therefore, this paper was designed to investigate a comprehensive metabolome of Fuzi and its processed products by ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry (UPLC-Q-TOF-HDMS) combined with pattern recognition methods. The difference in metabolic profiles between Fuzi and its processed preparations was well observed by the principal component analysis (PCA) of the MS spectra. Significant changes of 19 metabolite biomarkers were detected in the Fuzi samples and three preparations. The underlying regulations of Paozhi-perturbed metabolic pathways were also discussed according to the identified metabolites. The present study proves that UPLC-Q-TOF-HDMS based metabolomic analysis greatly contributes to the investigation of Fuzi metabolism through Paozhi techniques, and provides useful information to further comprehensively understand the pharmacological activity and potential toxicity of processed Fuzi in a clinical environment.

Assessment of dietary exposure related to dietary GI and fibre intake in a nutritional metabolomic study of human urine

There is a need for a tool to assess dietary intake related to the habitual dietary glycaemic index (GI) and fibre in groups with large numbers of individuals. Novel metabolite-profiling techniques may be a useful approach when applied to human urine. In a long-term, controlled dietary intervention study, metabolomics were applied to assess dietary patterns. A targeted approach was used to evaluate the effects on urinary C-peptide excretion caused by the dietary treatments. Seventy-seven overweight subjects followed an 8-week low-calorie diet (LCD) and were then randomly assigned to a high-GI or low-GI diet for 6 month during which they completed 24-h urine collections at baseline (prior to the 8-week LCD) and after randomisation to the dietary intervention, at month 1, 3 and 6, respectively. Metabolite profiling in 24-h urine was performed by (1)H NMR and chemometrics. Partial least squares (PLS) analysis indicated that urinary formate could discriminate between high-GI and low-GI diets (correlation coefficient r = 0.82), and this finding was confirmed statistically (P = 0.01). PLS analysis also indicated that urinary hippurate could be associated with fibre intake, but this finding was not confirmed statistically. No associations between GI and urinary C-peptide were found. Our results emphasise that application of metabolomics is useful in the assessment of dietary exposure related to dietary GI and fibre seen at group level in a nutritional metabolomic study of human urine. As our design allowed for large variations in individually selected food items, biomarkers identified at group level may be interpreted as more general and robust markers, largely not confounded with markers from single dietary factors.

Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research

Food intake, physical activity (PA), and genetic makeup each affect health and each factor influences the impact of the other 2 factors. Nutrigenomics describes interactions between genes and environment. Knowledge about the interplay between environment and genetics would be improved if experimental designs included measures of nutrient intake and PA. Lack of familiarity about how to analyze environmental variables and ease of access to tools and measurement instruments are 2 deterrents to these combined studies. This article describes the state of the art for measuring food intake and PA to encourage researchers to make their tools better known and more available to workers in other fields. Information presented was discussed during a workshop on this topic sponsored by the USDA, NIH, and FDA in the spring of 2009.

An onion byproduct affects plasma lipids in healthy rats

Onion may contribute to the health effects associated with high fruit and vegetable consumption. A considerable amount of onion production ends up as waste that might find use in foods. Onion byproduct has not yet been explored for potential health benefits. The aim of this study is to elucidate the safety and potential role of onion byproducts in affecting risk markers of cardiovascular disease (CVD). For that purpose, the effects of an onion byproduct, Allium cepa L. cepa 'Recas' (OBP), and its two derived fractions, an ethanolic extract (OE) and a residue (OR), on the distribution of plasma lipids and on factors affecting cholesterol metabolism in healthy rats have been investigated. The OBP or its fractions did not significantly reduce cholesterol or down-regulate hepatic 3-hydroxy-3-methylglutaryl-coenzyme A reductase (Hmgcr) gene expression. The OR even had the effect of increasing plasma triacylglycerides (TAG) and cholesterol in the very low density lipoprotein (VLDL-C) fraction. Neither total bile acids nor total primary or secondary bile acids were significantly affected by feeding rats the OBP or its fractions. Principal component analysis combining all markers revealed that the controls could be completely separated from OBP, OE, and OR groups in the scores plot and also that OE and OR groups were separated. Plasma lipids and bile acid excretion were the discriminating loading factors for separating OE and OR but also contributed to the separation of onion-fed animals and controls. It was concluded that the onion byproduct did not present significant beneficial effects on individual markers related to plasma lipid transport in this healthy rat model but that onion byproduct contains factors with the ability to modulate plasma lipids and lipoprotein levels.