Toward the implementation of metabolomic assessments of human health and nutrition

Organic Bioelectronic Devices for Metabolite Sensing

Electrochemical detection of metabolites is essential for early diagnosis and continuous monitoring of a variety of health conditions. This review focuses on organic electronic material-based metabolite sensors and highlights their potential to tackle critical challenges associated with metabolite detection. We provide an overview of the distinct classes of organic electronic materials and biorecognition units used in metabolite sensors, explain the different detection strategies developed to date, and identify the advantages and drawbacks of each technology. We then benchmark state-of-the-art organic electronic metabolite sensors by categorizing them based on their application area (in vitro, body-interfaced, in vivo, and cell-interfaced). Finally, we share our perspective on using organic bioelectronic materials for metabolite sensing and address the current challenges for the devices and progress to come.

Metabolomic understanding of intrinsic physiology in Panax ginseng during whole growing seasons

BACKGROUND

Panax ginseng Meyer has widely been used as a traditional herbal medicine because of its diverse health benefits. Amounts of ginseng compounds, mainly ginsenosides, vary according to seasons, varieties, geographical regions, and age of ginseng plants. However, no study has comprehensively determined perturbations of various metabolites in ginseng plants including roots and leaves as they grow.

METHODS

Nuclear magnetic resonance (1H NMR)-based metabolomics was applied to better understand the metabolic physiology of ginseng plants and their association with climate through global profiling of ginseng metabolites in roots and leaves during whole growing periods.

RESULTS

The results revealed that all metabolites including carbohydrates, amino acids, organic acids, and ginsenosides in ginseng roots and leaves were clearly dependent on growing seasons from March to October. In particular, ginsenosides, arginine, sterols, fatty acids, and uracil diphosphate glucose-sugars were markedly synthesized from March until May, together with accelerated sucrose catabolism, possibly associated with climatic changes such as sun exposure time and rainfall.

CONCLUSION

This study highlights the intrinsic metabolic characteristics of ginseng plants and their associations with climate changes during their growth. It provides important information not only for better understanding of the metabolic phenotype of ginseng but also for quality improvement of ginseng through modification of cultivation.

Metabolic and genetic profiling of young adults with and without a family history of premature coronary heart disease (MAGNETIC). Study design and methodology

INTRODUCTION

First-degree relatives of individuals with premature coronary artery disease (CAD) are at increased risk of CAD. The research hypothesis of this project assumes that there are differences in the metabolic profiles between individuals with and without a positive family history (FH) of premature CAD.

MATERIAL AND METHODS

The study group will comprise healthy patients (n = 500) aged 18-35 years with a FH of premature CAD, and the control group (n = 500) will consist of healthy subjects without a FH of premature CAD. Blood tests assessing the lipid profile will be carried out. Patients will respond to a questionnaire regarding FH and dietary habits. Measurement of carotid intima media thickness will be performed. Analysis of single-nucleotide polymorphisms (SNPs) associated with premature CAD will be carried out for every patient. Metabolomic profiling will be performed using a high-sensitivity Bruker AVANCE II 600 MHz NMR spectroscope.

RESULTS

The results of this study will include a comparison of metabolic profiles assessed by 1H-NMR spectroscopy in the study and control groups and the results of analyses of the relationship between the metabolic profiles and genetic risk score calculated based on evaluated SNPs associated with premature CAD.

CONCLUSIONS

This study will deepen our knowledge of the aetiopathogenesis of atherosclerosis by identifying metabolic patterns associated with a positive FH of premature CAD. Obtaining a detailed FH will enable adjustments for major risk factors of premature CAD in the proband's first-degree relatives. This research project also provides a chance to discover new biomarkers associated with the risk of premature CAD.

Current knowledge of metabolomic approach in infectious fish disease studies

The approaches of transcriptomic and proteomic have been widely used to study host-pathogen interactions in fish diseases, and this is comparable to the recently emerging application of metabolomic in elucidating disease-resistant mechanisms in fish that gives new insight into potential therapeutic strategies to improve fish health. Metabolomic is defined as the large-scale study of all metabolites within an organism and represents the frontline in the 'omics' approaches, providing direct information on the metabolic responses and perturbations in metabolic pathways. In this review, the current research in infectious fish diseases using metabolomic approach will be summarized. The metabolomic approach in economically important fish infected with viruses, bacteria and nematodes will also be discussed. The potential of the metabolomic approach for management of these infectious diseases as well as the challenges and the limitations of metabolomic in fish disease studies will be explored. Current review highlights the impacts of metabolomic studies in infectious fish diseases, which proposed the potential of new therapeutic strategies to enhance disease resistance in fish.

A Non-Targeted Liquid Chromatographic-Mass Spectrometric Metabolomics Approach for Association with Coronary Artery Disease: An Identification of Biomarkers for Depiction of Underlying Biological Mechanisms

Background

We performed non-targeted metabolomics analysis using liquid chromatography-mass spectrometry coupled technique to explore the biological mechanism of coronary artery disease (CAD) events for improved prediction.

Material/Methods

We studied the association of CAD events in 4092 individuals and observed the replication of sphingomyelin (28:1), lysophosphatidylcholine (18:2), lysophosphatidylcholine (18:1), and monoglyceride (18:2), which were independent of main CAD risk factors.

Results

We found that these 4 metabolites were responsible for traditional risk factors and also contributed to the modifications related to reclassification and discrimination. Monoglycerides (MonoGs) were positively associated with C-reactive proteins and body mass index, while lysophosphatidylcholines (LPPCs), which had less evidence of subclinical CAD in an additional 1010 participants, yielded a reverse pattern. An association between monoGs and CAD independence of triglycerides (triGs) were also observed. On the basis of Mendelian randomization analysis, we observed a positive but weak irregular effect (odds ratio per unit increase in standard deviation in monoG=1.11, P-value=0.05) on CAD.

Conclusions

Our work establishes the relationship of metabolome with coronary artery disease and explains the biological mechanism of CAD events, as we identified the above-mentioned metabolites along with the evidence supporting their clinical use.

Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science

Environmental health science aims to link environmental pollution sources to adverse health outcomes to develop effective exposure intervention strategies that reduce long-term disease risks. Over the past few decades, the public health community recognized that health risk is driven by interaction between the human genome and external environment. Now that the human genetic code has been sequenced, establishing this "G × E" (gene-environment) interaction requires a similar effort to decode the human exposome, which is the accumulation of an individual's environmental exposures and metabolic responses throughout the person's lifetime. The exposome is composed of endogenous and exogenous chemicals, many of which are measurable as biomarkers in blood, breath, and urine. Exposure to pollutants is assessed by analyzing biofluids for the pollutant itself or its metabolic products. New methods are being developed to use a subset of biomarkers, termed bioindicators, to demonstrate biological changes indicative of future adverse health effects. Typically, environmental biomarkers are assessed using noninvasive (excreted) media, such as breath and urine. Blood is often avoided for biomonitoring due to practical reasons such as medical personnel, infectious waste, or clinical setting, despite the fact that blood represents the central compartment that interacts with every living cell and is the most relevant biofluid for certain applications and analyses. The aims of this study were to (1) review the current use of blood samples in environmental health research, (2) briefly contrast blood with other biological media, and (3) propose additional applications for blood analysis in human exposure research.

Human metabolome associates with dietary intake habits among African Americans in the atherosclerosis risk in communities study

The human metabolome is a measurable outcome of interactions among an individual's inherited genome, microbiome, and dietary intake. We explored the relationship between dietary intake and serum untargeted metabolomic profiles in a subsample of 1,977 African Americans from the Atherosclerosis Risk in Communities (ARIC) Study in 1987-1989. For each metabolite, we conducted linear regression to estimate its relationships with each food group and food category. Potential confounding factors included age, sex, body mass index (weight (kg)/height (m)(2)), energy intake, kidney function, and food groups. We used a modified Bonferroni correction to determine statistical significance. In total, 48 pairs of diet-metabolite associations were identified, including multiple novel associations. The food group "sugar-rich foods and beverages" was inversely associated with 5 metabolites in the 2-hydroxybutyrate-related subpathway and positively associated with 5 γ-glutamyl dipeptides. The hypothesized mechanism of these associations may be through oxidative stress. "Sugar-rich foods and beverages" were also inversely associated with 7 unsaturated long-chain fatty acids. These findings suggest that the contribution of a sugar-rich dietary pattern to increased cardiovascular disease risk may be partially attributed to oxidative stress and disordered lipid profiles. Metabolomics may reveal novel metabolic biomarkers of dietary intake and provide insight into biochemical pathways underlying nutritional effects on disease development.

Deciphering molecular determinants of chemotherapy in gastrointestinal malignancy using systems biology approaches

Gastrointestinal cancers are asymptomatic in early tumor development, leading to high mortality rates. Peri- or postoperative chemotherapy is a common strategy used to prolong the life expectancy of patients with these diseases. Understanding the molecular mechanisms by which anticancer drugs exert their effect is crucial to the development of anticancer therapies, especially when drug resistance occurs and an alternative drug is needed. By integrating high-throughput techniques and computational modeling to explore biological systems at different levels, from gene expressions to networks, systems biology approaches have been successfully applied in various fields of cancer research. In this review, we highlight chemotherapy studies that reveal potential signatures using microarray analysis, next-generation sequencing (NGS), proteomic and metabolomic approaches for the treatment of gastrointestinal cancers.

Discrimination of white ginseng origins using multivariate statistical analysis of data sets

Background

White ginseng (Panax ginseng Meyer) is commonly distributed as a health food in food markets. However, there is no practical method for distinguishing Korean white ginseng (KWG) from Chinese white ginseng (CWG), except for relying on the traceability system in the market.

Methods

Ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with orthogonal partial least squares discrimination analysis (OPLS-DA) was employed to discriminate between KWG and CWG.

Results

The origins of white ginsengs in two test sets (1.0 μL and 0.2 μL injections) could be successfully discriminated by the OPLS-DA analysis. From OPLS-DA S-plots, KWG exhibited tentative markers derived from ginsenoside Rf and notoginsenoside R3 isomer, whereas CWG exhibited tentative markers derived from ginsenoside Ro and chikusetsusaponin Iva.

Conclusion

Results suggest that ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with OPLS-DA is an efficient tool for identifying the difference between the geographical origins of white ginsengs.

Multivariable analysis of host amino acids in plasma and liver during infection of malaria parasite Plasmodium yoelii

BACKGROUND

Malaria is the most significant human parasitic disease, and yet understanding of the energy metabolism of the principle pathogen, Plasmodium falciparum, remains to be fully elucidated. Amino acids were shown to be essential nutritional requirements since early times and much of the current knowledge of Plasmodium energy metabolism is based on early biochemical work, performed using basic analytical techniques, carried out almost exclusively on human plasma with considerable inter-individual variability.

METHODS

In order to further characterize the fate of amino acid metabolism in malaria parasite, multivariate analysis using statistical modelling of amino acid concentrations (aminogram) of plasma and liver were determined in host infected with rodent malaria parasite, Plasmodium yoelii.

RESULTS AND CONCLUSION

Comprehensive and statistical aminogram analysis revealed that P. yoelii infection caused drastic change of plasma and liver aminogram, and altered intra- and inter-correlation of amino acid concentration in plasma and liver. These findings of the interactions between amino acids and Plasmodium infection may provide insight to reveal the interaction between nutrients and parasites.

Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks

Metabolic profiling is the unbiased detection and quantification of low molecular-weight metabolites in a living system. It is rapidly developing in biological and translational research, contributing to disease mechanism elucidation, environmental chemical surveillance, biomarker detection, and health outcome prediction. Recent developments in experimental and computational technology allow more and more known metabolites to be detected and quantified from complex samples. As the coverage of the metabolic network improves, it has become feasible to examine metabolic profiling data from a systems perspective, i.e. interpreting the data and performing statistical inference in the context of pathways and genome-scale metabolic networks. Recently a number of methods have been developed in this area, and much improvement in algorithms and databases are still needed. In this review, we survey some methods for the analysis of metabolic profiling data based on metabolic networks.

Microfluidic strategies applied to biomarker discovery and validation for multivariate diagnostics

Complex diseases are caused by combinatorial genetic, environmental and lifestyle factors. The emergence of multibiomarker tests to define these diseases and to identify the early, presymptomatic stages offers several advantages to the conventional use of single marker tests. The development of multibiomarker protein-based tests remains constrained by technological and operational limitations in assaying hundreds to thousands of proteins in thousands of samples. In order to develop a multibiomarker test that stratifies risk for Type 2 diabetes, we took a candidate-driven immunoassay approach utilizing a microfluidics platform to analyze 89 candidate proteins in thousands of samples, which allowed us to move from discovery to a commercial test in 2 years. Future multibiomarker test development will be enhanced by advancements in the number of proteins that can be analyzed, analytical sensitivity and throughput, and sample volume requirements, all of which depend on the further advancement of microfluidics, detection technologies and affinity-based reagents.

A sulfur amino acid-free meal increases plasma lipids in humans

The content of sulfur amino acid (SAA) in a meal affects postprandial plasma cysteine concentrations and the redox potential of cysteine/cystine. Because such changes can affect enzyme, transporter, and receptor activities, meal content of SAA could have unrecognized effects on metabolism during the postprandial period. This pilot study used proton NMR ((1)H-NMR) spectroscopy of human plasma to test the hypothesis that dietary SAA content changes macronutrient metabolism. Healthy participants (18-36 y, 5 males and 3 females) were equilibrated for 3 d to adequate SAA, fed chemically defined meals without SAA for 5 d (depletion), and then fed isoenergetic, isonitrogenous meals containing 56 mg·kg(-1)·d(-1) SAA for 4.5 d (repletion). On the first and last day of consuming the chemically defined meals, a morning meal containing 60% of the daily food intake was given and plasma samples were collected over an 8-h postprandial time course for characterization of metabolic changes by (1)H-NMR spectroscopy. SAA-free food increased peak intensity in the plasma (1)H-NMR spectra in the postprandial period. Orthogonal signal correction/partial least squares-discriminant analysis showed changes in signals associated with lipids, some amino acids, and lactate, with notable increases in plasma lipid signals (TG, unsaturated lipid, cholesterol). Conventional lipid analyses confirmed higher plasma TG and showed an increase in plasma concentration of the lipoprotein lipase inhibitor, apoC-III. The results show that plasma (1)H-NMR spectra can provide useful macronutrient profiling following a meal challenge protocol and that a single meal with imbalanced SAA content alters postprandial lipid metabolism.

Use of volatile compound metabolic signatures in poultry liver to back-trace dietary exposure to rapidly metabolized xenobiotics

The study investigated the feasibility of using volatile compound signatures of liver tissues in poultry to detect previous dietary exposure to different types of xenobiotic. Six groups of broiler chickens were fed a similar diet either noncontaminated or contaminated with polychlorinated dibenzo-p-dioxins/-furans (PCDD/Fs; 3.14 pg WHO-TEQ/g feed, 12% moisture), polychlorinated biphenyls (PCBs; 0.08 pg WHO-TEQ/g feed, 12% moisture), polybrominated diphenyl ethers (PBDEs; 1.63 ng/g feed, 12% moisture), polycyclic aromatic hydrocarbons (PAHs; 0.72 μg/g fresh matter), or coccidiostats (0.5 mg/g feed, fresh matter). Each chicken liver was analyzed by solid-phase microextraction - mass spectrometry (SPME-MS) for volatile compound metabolic signature and by gas chromatography - high resolution mass spectrometry (GC-HRMS), gas chromatography - tandem mass spectrometry (GC-MS/MS), and liquid chromatography - tandem mass spectrometry (LC-MS/MS) to quantify xenobiotic residues. Volatile compound signature evidenced a liver metabolic response to PAH although these rapidly metabolized xenobiotics are undetectable in this organ by the reference methods. Similarly, the volatile compound metabolic signature enabled to differentiate the noncontaminated chickens from those contaminated with PBDEs or coccidiostats. In contrast, no clear signature was pointed out for slowly metabolized compounds such as PCDD/Fs and PCBs although their residues were found in liver at 50.93 (±6.71) and 0.67 (±0.1) pg WHO-TEQ/g fat, respectively.

Metabolomic profiling for identification of novel potential biomarkers in cardiovascular diseases

Metabolomics involves the identification and quantification of metabolites present in a biological system. Three different approaches can be used: metabolomic fingerprinting, metabolic profiling, and metabolic footprinting, in order to evaluate the clinical course of a disease, patient recovery, changes in response to surgical intervention or pharmacological treatment, as well as other associated features. Characteristic patterns of metabolites can be revealed that broaden our understanding of a particular disorder. In the present paper, common strategies and analytical techniques used in metabolomic studies are reviewed, particularly with reference to the cardiovascular field.

Recent and potential developments in the analysis of urine: a review

Analysis of urine is a widely used diagnostic tool that traditionally measured one or, at most, a few metabolites. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to urine for disease diagnostics. This review looks at various aspects of urinalysis including sampling and traditional approaches before reviewing recent developments using metabolomics. Spectrometric approaches are covered briefly since there are already a number of very good reviews on NMR spectroscopy and mass spectrometry and other spectrometries are not as highly developed in their applications to metabolomics. On the other hand, there has been a recent surge in chromatographic applications dedicated to characterising the human urinary metabolome. While developments in the analysis of urine encompassing both classical approaches of urinalysis and metabolomics are covered, it must be emphasized that these approaches are not orthogonal - they both have their uses and are complementary. Regardless, the need to normalise analytical data remains an important impediment.

Symposium 2: Modern approaches to nutritional research challenges: Targeted and non-targeted approaches for metabolite profiling in nutritional research

The present report discusses targeted and non-targeted approaches to monitor single nutrients and global metabolite profiles in nutritional research. Non-targeted approaches such as metabolomics allow for the global description of metabolites in a biological sample and combine an analytical platform with multivariate data analysis to visualise patterns between sample groups. In nutritional research metabolomics has generated much interest as it has the potential to identify changes to metabolic pathways induced by diet or single nutrients, to explore relationships between diet and disease and to discover biomarkers of diet and disease. Although still in its infancy, a number of studies applying this technology have been performed; for example, the first study in 2003 investigated isoflavone metabolism in females, while the most recent study has demonstrated changes to various metabolic pathways during a glucose tolerance test. As a relatively new technology metabolomics is faced with a number of limitations and challenges including the standardisation of study design and methodology and the need for careful consideration of data analysis, interpretation and identification. Targeted approaches are used to monitor single or multiple nutrient and/or metabolite status to obtain information on concentration, absorption, distribution, metabolism and elimination. Such applications are currently widespread in nutritional research and one example, using stable isotopes to monitor nutrient status, is discussed in more detail. These applications represent innovative approaches in nutritional research to investigate the role of both single nutrients and diet in health and disease.

Alteration in plasma testosterone levels in male mice lacking soluble epoxide hydrolase

Soluble epoxide hydrolase (Ephx2, sEH) is a bifunctional enzyme with COOH-terminal hydrolase and NH(2)-terminal phosphatase activities. sEH converts epoxyeicosatrienoic acids (EETs) to dihydroxyeicosatrienoic acids (DHETs), and the phosphatase activity is suggested to be involved in cholesterol metabolism. EETs participate in a wide range of biological functions, including regulation of vascular tone, renal tubular transport, cardiac contractility, and inflammation. Inhibition of sEH is a potential approach for enhancing the biological activity of EETs. Therefore, disruption of sEH activity is becoming an attractive therapeutic target for both cardiovascular and inflammatory diseases. To define the physiological role of sEH, we characterized a knockout mouse colony lacking expression of the Ephx2 gene. Lack of sEH enzyme is characterized by elevation of EET to DHET ratios in both the linoleate and arachidonate series in plasma and tissues of both female and male mice. In male mice, this lack of expression was also associated with decreased plasma testosterone levels, sperm count, and testicular size. However, this genotype was still able to sire litters. Plasma cholesterol levels also declined in this genotype. Behavior tests such as anxiety-like behavior and hedonic response were also examined in Ephx2-null and WT mice, as all can be related to hormonal changes. Null mice showed a level of anxiety with a decreased hedonic response. In conclusion, this study provides a broad biochemical, physiological, and behavioral characterization of the Ephx2-null mouse colony and suggests a mechanism by which sEH and its substrates may regulate circulating levels of testosterone through cholesterol biosynthesis and metabolism.

Inter- and intra-individual variations of urinary endogenous metabolites in healthy male college students using (1)H NMR spectroscopy

BACKGROUND

Most human metabolomics studies have shown that spectral outputs of (1)H nuclear magnetic resonance fingerprinting are strongly influenced by inter- and intra-individual variations; however, few studies have been performed to evaluate the inter- and intra-individual variations in urinary endogenous metabolites.

METHODS

We recruited 30 male college students to evaluate the factors affecting intra- and inter-individual variations in urinary endogenous metabolites. Statistical analysis for variations in urinary metabolites was performed after eliminating outliers found in principal component analysis (PCA) plots.

RESULTS

Inter-individual variations were relatively low for 2-oxoglutarate, succinate, citrate, dimethylglycine, and taurine, but high for trimethylaminoxide (TMAO), hippurate, and lactate. Intra-individual variations for 2-oxoglutarate, citrate, dimethylglycine, and taurine were relatively low, but high for TMAO and hippurate. The factors affecting inter-individual variation of lactate were age, body mass index, beverages, and alcohol, whereas the factors affecting intra-individual variation of lactate were age and fish. Kim Chi intake affected the inter-individual variation of succinate, citrate, TMAO, and hippurate; however, it did not affect the intra-individual variation of endogenous metabolites.

CONCLUSIONS

Our results showed that inter- and intra-individual variations in urinary endogenous metabolites were very large, and significant factors affecting inter- and intra-individual variation were diverse, even after eliminating outliers in PCA analysis.

Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics?

The diet is an important environmental exposure, and its measurement is an essential component of much health-related research. However, conventional tools for measuring dietary exposure have significant limitations being subject to an unknown degree of misreporting and dependent upon food composition tables to allow estimation of intakes of energy, nutrients and non-nutrient food constituents. In addition, such tools may be inappropriate for use with certain groups of people. As an alternative approach, the recent techniques of metabolite profiling or fingerprinting, which allows simultaneous monitoring of multiple and dynamic components of biological fluids, may provide metabolic signals indicative of food intake. Samples can be analysed through numerous analytical platforms, followed by multivariate data analysis. In humans, metabolomics has been applied successfully in pharmacology, toxicology and medical screening, but nutritional metabolomics is still in its infancy. Biomarkers of a small number of specific foods and nutrients have been developed successfully but less targeted and more high-throughput methods, that do not need prior knowledge of which signals might be discriminatory, and which may allow a more global characterisation of dietary intake, remain to be tested. A proof a principle project (the MEDE Study) is currently underway in our laboratories to test the hypothesis that high-throughput, non-targeted metabolite fingerprinting using flow injection electrospray mass spectrometry can be applied to human biofluids (blood and urine) to characterise dietary exposure in humans.

Arginine, scurvy and Cartier's "tree of life"

Several conifers have been considered as candidates for "Annedda", which was the source for a miraculous cure for scurvy in Jacques Cartier's critically ill crew in 1536. Vitamin C was responsible for the cure of scurvy and was obtained as an Iroquois decoction from the bark and leaves from this "tree of life", now commonly referred to as arborvitae. Based on seasonal and diurnal amino acid analyses of candidate "trees of life", high levels of arginine, proline, and guanidino compounds were also probably present in decoctions prepared in the severe winter. The semi-essential arginine, proline and all the essential amino acids, would have provided additional nutritional benefits for the rapid recovery from scurvy by vitamin C when food supply was limited. The value of arginine, especially in the recovery of the critically ill sailors, is postulated as a source of nitric oxide, and the arginine-derived guanidino compounds as controlling factors for the activities of different nitric oxide synthases. This review provides further insights into the use of the candidate "trees of life" by indigenous peoples in eastern Canada. It raises hypotheses on the nutritional and synergistic roles of arginine, its metabolites, and other biofactors complementing the role of vitamin C especially in treating Cartier's critically ill sailors.

Mass spectrometry approaches for vitamin E research

Vitamin E is an important nutrient with antioxidant and non-antioxidant functions, and certain evidence suggests that it has a cardiovascular protective role. It is therefore important to maintain an optimal vitamin E status. In the present paper, a number of MS applications to monitor vitamin E status and its interactions, including the use of stable-isotope-labelled vitamin E and metabonomics, are highlighted. Specifically, stable-isotope studies have been used to monitor vitamin E absorption, hepatic processing and lipoprotein transport. As oxidative stress may influence vitamin E status, a number of studies comparing vitamin E biokinetics and metabolism in cigarette smokers and non-smokers have been able to show differences in vitamin E processing in smokers. Metabonomics represents a method to identify changes to metabolite profiles, offering the potential to investigate interactions between vitamin E and metabolic pathways. These applications represent innovative approaches to investigate the role of vitamin E in health and disease.

NMR-based metabolomics approach for the differentiation of ginseng (Panax ginseng) roots from different origins

Agro-herbal materials vary in prices and qualities depending on the origin and age and the differentiation is both scientific and public health issue. Here, we describe a metabolomics approach used to discriminate ginseng roots from different sources. Six different types of ginseng roots from China and Korea were analyzed by NMR-based metabolomics. Chinese Dangsam showed prominent differences and was easily differentiated. The difference was mainly due to the large signals in the sugar region. We further analyzed the metabolomics results in subgroups. Jeonra (Korean), Choongcheong (Korean), and Chinese ginseng in subgroup 1 could be easily differentiated by the first two principal components. The loading plot for PC1 showed that the Jeonra and Chinese ginseng roots were mainly separated by sugar signals and methyl signals but that they were reverse-correlated. A diffusion-ordered spectroscopy (DOSY) analysis showed that the methyl signals are from high molecular weight compounds and that the sugar signals are either from oligosaccharides or ginsenosides. In subgroup 2, composed of Korean Choongcheong ginseng at different ages, we were able to see age-dependent transitions in the score plot. We believe our approach can be applied to detecting the adulteration of ginseng root powders and other herbal products from different origins.

Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome

Background

Biomarker-based assessments of biological samples are widespread in clinical, pre-clinical, and epidemiological investigations. We previously developed serum metabolomic profiles assessed by HPLC-separations coupled with coulometric array detection that can accurately identify ad libitum fed and caloric-restricted rats. These profiles are being adapted for human epidemiology studies, given the importance of energy balance in human disease.

Methods

Human plasma samples were biochemically analyzed using HPLC separations coupled with coulometric electrode array detection.

Results

We identified these markers/metabolites in human plasma, and then used them to determine which human samples represent blinded duplicates with 100% accuracy (N = 30 of 30). At least 47 of 61 metabolites tested were sufficiently stable for use even after 48 hours of exposure to shipping conditions. Stability of some metabolites differed between individuals (N = 10 at 0, 24, and 48 hours), suggesting the influence of some biological factors on parameters normally considered as analytical.

Conclusion

Overall analytical precision (mean median CV, ~9%) and total between-person variation (median CV, ~50–70%) appear well suited to enable use of metabolomics markers in human clinical trials and epidemiological studies, including studies of the effect of caloric intake and balance on long-term cancer risk.

Metabolomics: an emerging post-genomic tool for nutrition

The post-genomic era has been driven by the development of technologies that allow the function of cells and whole organisms to be explored at the molecular level. Metabolomics is concerned with the measurement of global sets of low-molecular-weight metabolites. Metabolite profiles of body fluids or tissues can be regarded as important indicators of physiological or pathological states. Such profiles may provide a more comprehensive view of cellular control mechanisms in man and animals, and raise the possibility of identifying surrogate markers of disease. Metabolomic approaches use analytical techniques such as NMR spectroscopy and MS to measure populations of low-molecular-weight metabolites in biological samples. Advanced statistical and bioinformatic tools are then employed to maximise the recovery of information and interpret the large datasets that are generated. Metabolomics has already been used to study toxicological mechanisms and disease processes and offers enormous potential as a means of investigating the complex relationship between nutrition and metabolism. Examples include the metabolism of dietary substrates, drug-induced disturbances of lipid metabolites in type 2 diabetes mellitus and the therapeutic effects of vitamin supplementation in the treatment of chronic metabolic disorders.

Mass spectrometry-based metabolomics

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

The lipid maps initiative in lipidomics

The Lipid Metabolites and Pathways Strategy (LIPID MAPS) initiative constitutes the first broad scale national exploration of lipidomics and is supported by a U.S. National Institute of General Medical Sciences Large Scale Collaborative "Glue" Grant. The emerging field of lipidomics faces many obstacles to become a true systems biology approach on par with the other "omics" disciplines. With a goal to overcome these hurdles, LIPID MAPS has been developing the necessary infrastructure and techniques to ensure success. This review introduces a few of the challenges and solutions implemented by LIPID MAPS. Among these solutions is the new comprehensive classification system for lipids, along with a recommended nomenclature and structural drawing representation. This classification system was developed by the International Lipids Classification and Nomenclature Committee (ILCNC) in collaboration with LIPID MAPS and representatives from Europe and Asia. The latest changes implemented by the committee are summarized. In addition, we discuss the adoption of mass spectrometry (MS) as the instrumental platform to investigate lipidomics. This platform has the versatility to quantify known individual lipid molecular species and search for novel lipids affecting biological systems.

OMICS-driven biomarker discovery in nutrition and health

While traditional nutrition research has dealt with providing nutrients to nourish populations, it nowadays focuses on improving health of individuals through diet. Modern nutritional research is aiming at health promotion and disease prevention and on performance improvement. As a consequence of these ambitious objectives, the disciplines "nutrigenetics" and "nutrigenomics" have evolved. Nutrigenetics asks the question how individual genetic disposition, manifesting as single nucleotide polymorphisms, copy-number polymorphisms and epigenetic phenomena, affects susceptibility to diet. Nutrigenomics addresses the inverse relationship, that is how diet influences gene transcription, protein expression and metabolism. A major methodological challenge and first pre-requisite of nutrigenomics is integrating genomics (gene analysis), transcriptomics (gene expression analysis), proteomics (protein expression analysis) and metabonomics (metabolite profiling) to define a "healthy" phenotype. The long-term deliverable of nutrigenomics is personalised nutrition for maintenance of individual health and prevention of disease. Transcriptomics serves to put proteomic and metabolomic markers into a larger biological perspective and is suitable for a first "round of discovery" in regulatory networks. Metabonomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible human body fluids like urine, blood and saliva. This feature also holds true to some extent for proteomics, with the constraint that proteomics is more complex in terms of absolute number, chemical properties and dynamic range of compounds present. Apart from addressing the most complex "-ome", proteomics represents the only platform that delivers not only markers for disposition and efficacy but also targets of intervention. The Omics disciplines applied in the context of nutrition and health have the potential to deliver biomarkers for health and comfort, reveal early indicators for disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components. This paper reviews the state-of-the-art of the three Omics platforms, discusses their implication in nutrigenomics and elaborates on applications in nutrition and health such as digestive health, allergy, diabetes and obesity, nutritional intervention and nutrient bioavailability. Proteomic developments, applications and potential in the field of nutrition have been specifically addressed in another review issued by our group.

METLIN: a metabolite mass spectral database

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.

The expanding role of mass spectrometry in metabolite profiling and characterization

Mass spectrometry has a strong history in drug-metabolite analysis and has recently emerged as the foremost technology in endogenous metabolite research. The advantages of mass spectrometry include a wide dynamic range, the ability to observe a diverse number of molecular species, and reproducible quantitative analysis. These attributes are important in addressing the issue of metabolite profiling, as the dynamic range easily exceeds nine orders of magnitude in biofluids, and the diversity of species ranges from simple amino acids to lipids to complex carbohydrates. The goals of the application of mass spectrometry range from basic biochemistry to clinical biomarker discovery with challenges in generating a comprehensive profile, data analysis, and structurally characterizing physiologically important metabolites. The precedent for this work has already been set in neonatal screening, as blood samples from millions of neonates are tested routinely by mass spectrometry as a diagnostic tool for inborn errors of metabolism. In this review, we will discuss the background from which contemporary metabolite research emerged, the techniques involved in this exciting area, and the current and future applications of this field.

Metabolic investigation in psychiatric disorders

A multiplicity of theories have been proposed over the years that aim to conceptualize the pathophysiology of neuropsychiatric disorders, including impaired neurotransmission, viral infections, genetic mutation, energy metabolism deficiency, excitotoxicity, oxidative stress, and others. It is likely that complex disorders such as schizophrenia, bipolar disorder, and major depression are associated with multiple etiologies and pathogenetic mechanisms. In light of the interwoven biochemistry of human organs, identifying a network of multiple interacting biochemical pathways that account for the constellation of clinical and biological features would advance our understanding of these disorders. One such approach is to evaluate simultaneously the multiple metabolites in order to uncover the dynamic relations in the relevant biochemical systems. These metabolites are a group of low-molecular-weight, redox-active compounds, such as antioxidants, amino acids, catecholamines vitamins, lipids, and nucleotides, which reflect the metabolic processes, including anabolism and catabolism as well as other related cellular processes (e.g., signal transduction, regulation, detoxification, etc.). Such an analytic approach has the potential to yield valuable insights into the likely complex pathophysiological mechanisms that affect multiple metabolic pathways and thereby offer multiple windows of therapeutic opportunities.

Genomic medicine: genetic variation and its impact on the future of health care

Advances in genome technology and other fruits of the Human Genome Project are playing a growing role in the delivery of health care. With the development of new technologies and opportunities for large-scale analysis of the genome, transcriptome, proteome and metabolome, the genome sciences are poised to have a profound impact on clinical medicine. Cancer prognostics will be among the first major test cases for a genomic medicine paradigm, given that all cancer is caused by genomic instability, and microarrays allow assessment of patients' entire expressed genomes. Analysis of breast cancer patients' expression patterns can already be highly correlated with recurrence risks. By integrating clinical data with gene expression profiles, imaging, metabolomic profiles and proteomic data, the prospect for developing truly individualized care becomes ever more real. Notwithstanding these promises, daunting challenges remain for genomic medicine. Success will require planning robust prospective trials, analysing health care economic and outcome data, assuaging insurance and privacy concerns, developing health delivery models that are commercially viable and scaling up to meet the needs of the whole population.

Solvent-Dependent Metabolite Distribution, Clustering, and Protein Extraction for Serum Profiling with Mass Spectrometry

The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.

Metabolomics reviewed: a new "omics" platform technology for systems biology and implications for natural products research

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. Metabolomics (or metabonomics) has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. Metabolomics is fast becoming one of the platform sciences of the "omics", with the majority of the papers in this field having been published only in the last two years. In this review metabolomic methodologies are discussed briefly followed by a more detailed review of the use of metabolomics in integrated applications where metabolomics information has been combined with other "omic" data sets (proteomics, transcriptomics) to enable greater understanding of a biological system. The potential of metabolomics for natural product drug discovery and functional food analysis, primarily as incorporated into broader "omic" data sets, is discussed.

Prospects for Personalized Cardiovascular Medicine

Sequencing of the human genome has ushered in prospects for individualizing cardiovascular health care. There is growing evidence that the practice of cardiovascular medicine might soon have a new toolbox to predict and treat disease more effectively. The Human Genome Project has spawned several important "omic" technologies that allow "whole genome" interrogation of sequence variation (re-sequencing, genotyping, comparative genome hybridization), transcription (expression profiling, tissue arrays), proteins (gas or liquid chromatography and tandem mass spectroscopy [MS]), and metabolites (MS or nuclear magnetic resonance profiling); deoxyribonucleic acid, ribonucleic acid, protein, and metabolic approaches all provide more exacting detail of cardiovascular disease mechanisms and, in some cases, are redefining its taxonomy. Pharmacogenomic approaches are emerging across broad classes of cardiovascular therapeutics to assist practitioners in making more precise decisions about which drugs to give to which patients to optimize the benefit-to-risk ratio. Molecular imaging is developing chemical and biological probes that can sense molecular pathway mechanisms that will allow us to monitor health and disease. Together, these tools will enable a paradigm shift from genetic medicine--on the basis of the study of individual inherited characteristics, most often single genes--to genomic medicine, which by its nature is comprehensive and focuses on the functions and interactions of multiple genes and gene products, among themselves and with their environment. The information gained from such analyses, in combination with clinical data, is now allowing us to assess individual risks and guide clinical management and decision-making, all of which form the basis for cardiovascular genomic medicine.

A perspective on DNA microarray technology in food and nutritional science

PURPOSE OF REVIEW

The functions of nutrients and other foods have been revealed at the level of gene regulation. The advent of DNA microarray technology has enabled us to analyze the body's response to these factors in a much more holistic manner than before. This review is intended to overview the present status of this DNA microarray technology, hoping to provide food and nutrition scientists, especially those who are planning to introduce this technology, with hints and suggestions.

RECENT FINDINGS

The number of papers examining transcriptomics analysis in food and nutrition science has expanded over the last few years. The effects of some dietary conditions and administration of specific nutrients or food factors are studied in various animal models and cultured cells. The target food components range from macronutrients and micronutrients to other functional food factors. Such studies have already yielded fruitful results, which include discovery of novel functions of a food, uncovering hitherto unknown mechanisms of action, and analyses of food safety.

SUMMARY

The potency of DNA microarray technology in food and nutrition science is broadly recognized. This technique will surely continue to provide researchers and the public with valuable information on the beneficial and adverse effects of food factors. It should also be acknowledged, however, that there remain problems such as standardization of the data and sharing of the results among researchers in this field.

Global strategies to integrate the proteome and metabolome

A fundamental goal of proteomics is to assign physiological functions to all proteins encoded by eukaryotic and prokaryotic genomes. Of the many activities performed by proteins, the chemical transformations catalyzed by enzymes form the basis for most, if not all, metabolic and signaling pathways. Elucidation of these pathways and their integration into larger cellular networks require new strategies to rapidly and systematically identify physiological substrates of enzymes. Here, we review emerging technologies that aim to assign endogenous biochemical functions to enzymes by profiling the metabolome.

A survey of the methods for the characterization of microbial consortia and communities

A survey of the available literature on methods most frequently used for the identification and characterization of microbial strains, communities, or consortia is presented. The advantages and disadvantages of the various methodologies were examined from several perspectives including technical, economic (time and cost), and regulatory. The methods fall into 3 broad categories: molecular biological, biochemical, and microbiological. Molecular biological methods comprise a broad range of techniques that are based on the analysis and differentiation of microbial DNA. This class of methods possesses several distinct advantages. Unlike most other commonly used methods, which require the production of secondary materials via the manipulation of microbial growth, molecular biological methods recover and test their source materials (DNA) directly from the microbial cells themselves, without the requirement for culturing. This eliminates both the time required for growth and the biases associated with cultured growth, which is unavoidably and artificially selective. The recovered nucleic acid can be cloned and sequenced directly or subpopulations can be specifically amplified using polymerase chain reaction (PCR), and subsequently cloned and sequenced. PCR technology, used extensively in forensic science, provides researchers with the unique ability to detect nucleic acids (DNA and RNA) in minute amounts, by amplifying a single target molecule by more than a million-fold. Molecular methods are highly sensitive and allow for a high degree of specificity, which, coupled with the ability to separate similar but distinct DNA molecules, means that a great deal of information can be gleaned from even very complex microbial communities. Biochemical methods are composed of a more varied set of methodologies. These techniques share a reliance on gas chromatography and mass spectrometry to separate and precisely identify a range of biomolecules, or else investigate biochemical properties of key cellular biomolecules. Like the molecular biological methods, some biochemical methods such as lipid analyses are also independent of cultured growth. However, many of these techniques are only capable of producing a profile that is characteristic of the microbial community as a whole, providing no information about individual members of the community. A subset of these methodologies are used to derive taxonomic information from a community sample; these rely on the identification of key subspecies of biomolecules that differ slightly but characteristically between species, genera, and higher biological groupings. However, when the consortium is already growing in chemically defined media (as is often the case with commercial products), the rapidity and relatively low costs of these procedures can mitigate concerns related to culturing biases. Microbiological methods are the most varied and the least useful for characterizing microbial consortia. These methods rely on traditional tools (cell counting, selective growth, and microscopic examination) to provide more general characteristics of the community as a whole, or else to narrow down and identify only a small subset of the members of that community. As with many of the biochemical methods, some of the microbiological methods can fairly rapidly and inexpensively create a community profile, which can be used to compare 2 or more entire consortia. However, for taxonomic identification of individual members, microbiological methods are useful only to screen for the presence of a few key predetermined species, whose preferred growth conditions and morphological characteristics are well defined and reproducible.Key words: microbial communities, microbial consortia, characterization methods, taxonomic identification.