Analytical metabolomics: nutritional opportunities for personalized health

Emerging Biomarkers in Metabolomics: Advancements in Precision Health and Disease Diagnosis

Metabolomics has come to the fore as an efficient tool in the search for biomarkers that are critical for precision health approaches and improved diagnostics. This review will outline recent advances in biomarker discovery based on metabolomics, focusing on metabolomics biomarkers reported in cancer, neurodegenerative disorders, cardiovascular diseases, and metabolic health. In cancer, metabolomics provides evidence for unique oncometabolites that are important for early disease detection and monitoring of treatment responses. Metabolite profiling for conditions such as neurodegenerative and mental health disorders can offer early diagnosis and mechanisms into the disease especially in Alzheimer's and Parkinson's diseases. In addition to these, lipid biomarkers and other metabolites relating to cardiovascular and metabolic disorders are promising for patient stratification and personalized treatment. The gut microbiome and environmental exposure also feature among the influential factors in biomarker discovery because they sculpt individual metabolic profiles, impacting overall health. Further, we discuss technological advances in metabolomics, current clinical applications, and the challenges faced by metabolomics biomarker validation toward precision medicine. Finally, this review discusses future opportunities regarding the integration of metabolomics into routine healthcare to enable preventive and personalized approaches.

Screening of metabolites in the treatment of liver cancer xenografts HepG2/ADR by psoralen-loaded lipid nanoparticles

OBJECTIVE

Our study aimed to find potential biomarkers for drug resistance in liver cancer cells using metabolomics and further to evaluate the potential of psoralen-loaded polymer lipid nanoparticles (PSO-PLNs) to reverse the resistance of cells to doxorubicin.

METHODS

We used LC-MS-based non-targeted metabolomics, also known as global metabolite profiling, to screen in serum and urine of mice engrafted with a liver cancer cell line sensitive (HepG2/S) or resistant to doxorubicin (HepG2/ADR) for differentially regulated metabolites. We subsequently quantified the abundance of these metabolites in serum and the urine of mice. The mice were engrafted with HepG2 cells resistant against doxorubicin and were treated with I) doxorubicin, II) a combination of doxorubicin and psoralen and III) a combination of doxorubicin and psoralen packed in polymer lipid nanoparticles.

RESULTS

Metabolites found to be differentially present in urine of mice engrafted with resistant HepG2 cells were: hippuric acid, hyaluronic acid, pantothenic acid, and betaine; retinoic acid and α-linolenic acid were found to be reduced in serum samples of mice with HepG2 cells resistant to doxorubicin. The targeted analysis showed that the degree of regression of metabolic markers in groups differed: treatment group 2 had stronger degree of regression than treatment group 1 and the negative control group had the smallest, which indicates that the PSO-PLNs have superior properties compared with other treatments.

CONCLUSION

Psoralen reverses drug resistance of liver cancer cells and its efficacy can be increased by encapsulation in polymer lipid nanoparticles.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Dynamic changes of postprandial plasma metabolites after intake of corn-soybean meal or casein-starch diets in growing pigs

Background

Postprandial nutrients utilization and metabolism of a certain diet is a complicated process. The metabolic feature of pigs after intake of corn-soybean meal or casein-starch diets are largely unknown. Therefore, this study was conducted to investigate the dynamic postprandial changes of plasma metabolic profile using growing pigs using metabolomics.

Methods

Twenty-four growing pigs with average initial body weight (BW) about 30 kg were placed in metabolic cages and then fitted with precaval vein catheters. Pigs were fed daily 4% of initial body weight. Two experimental diets were included: (i) a starch-casein based purified diet (PD) and (ii) a common corn-soybean meal diet (CD). Plasma was collected before feeding and 0.5 h, 1 h, 2 h, 4 h, 8 h after feeding.

Results

In both diets, compared to prior to feeding, the concentrations of glucose, most amino acids, metabolites such as 5-aminopentanoic acid, pipecolic acid, ornithine and 5-hydroxy-L-tryptophan were significantly increased in plasma during the first hour, whereas the concentrations of plasma triglycerides, glutamate, glycine, palmitelaidic acid, 13-HODE and oleic acid were decreased in the first hour. Compared with PD group, concentration of plasma leucine and isoleucine declined at 30 min in CD group. Plasma linoleic acid, sphingosine and many dipeptides were significantly higher in pigs fed CD.

Conclusion

Most significant metabolic changes occurred during the first hour after feeding and then became relatively stable after 2 h in both diets. These results show a broad scope picture of postprandial changes in plasma metabolites after intake of PD and CD and could be a reference for further nutrition intervention as well as the design of nutritional studies.

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0351-8) contains supplementary material, which is available to authorized users.

Untargeted 1H NMR-Based Metabolomics Analysis of Urine and Serum Profiles after Consumption of Lentils, Chickpeas, and Beans: An Extended Meal Study To Discover Dietary Biomarkers of Pulses

High legume intake has been shown to have beneficial effects on the health of humans. The use of nutritional biomarkers, as a complement to self-reported questionnaires, could assist in evaluating dietary intake and downstream effects on human health. The aim of this study was to investigate potential biomarkers of the consumption of pulses (i.e., white beans, chickpeas, and lentils) by using untargeted NMR-based metabolomics. Meals rich in pulses were consumed by a total of 11 participants in a randomized crossover study and multilevel partial least-squares regression was employed for paired comparisons. Metabolomics analysis indicated that trigonelline, 3-methylhistidine, dimethylglycine, trimethylamine, and lysine were potential, though not highly specific, biomarkers of pulse intake. Furthermore, monitoring of these metabolites for a period of 48 h after intake revealed a range of different excretion patterns among pulses. Following the consumption of pulses, a metabolomic profiling revealed that the concentration ratios of trigonelline, choline, lysine, and histidine were similar to those found in urine. In conclusion, this study identified potential urinary biomarkers of exposure to dietary pulses and provided valuable information about the time-response effect of these putative biomarkers.

Metabolomic profile of systemic sclerosis patients

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by ¹H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726–0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7–0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

Nutrient Intake Is Associated with Longevity Characterization by Metabolites and Element Profiles of Healthy Centenarians

The relationships between diet and metabolites as well as element profiles in healthy centenarians are important but remain inconclusive. Therefore, to test the interesting hypothesis that there would be distinctive features of metabolites and element profiles in healthy centenarians, and that these would be associated with nutrient intake; the short chain fatty acids (SCFAs), total bile acids and ammonia in feces, phenol, p-cresol, uric acid, urea, creatinine and ammonia in urine, and element profiles in fingernails were determined in 90 healthy elderly people, including centenarians from Bama county (China)—a famous longevous region—and elderly people aged 80–99 from the longevous region and a non-longevous region. The partial least squares-discriminant analysis was used for pattern recognition. As a result, the centenarians showed a distinct metabolic pattern. Seven characteristic components closely related to the centenarians were identified, including acetic acid, total SCFA, Mn, Co, propionic acid, butyric acid and valeric acid. Their concentrations were significantly higher in the centenarians group (p < 0.05). Additionally, the dietary fiber intake was positively associated with butyric acid contents in feces (r = 0.896, p < 0.01), and negatively associated with phenol in urine (r = −0.326, p < 0.01). The results suggest that the specific metabolic pattern of centenarians may have an important and positive influence on the formation of the longevity phenomenon. Elevated dietary fiber intake should be a path toward health and longevity.

The Association of Polymorphisms in Leptin/Leptin Receptor Genes and Ghrelin/Ghrelin Receptor Genes With Overweight/Obesity and the Related Metabolic Disturbances: A Review

CONTEXT

Leptin and ghrelin are two important appetite and energy balance-regulating peptides. Common polymorphisms in the genes coding these peptides and their related receptors are shown to be associated with body weight, different markers of obesity and metabolic abnormalities. This review article aims to investigate the association of common polymorphisms of these genes with overweight/obesity and the metabolic disturbances related to it.

EVIDENCE ACQUISITION

The keywords leptin, ghrelin, polymorphism, single-nucleotide polymorphism (SNP), obesity, overweight, Body Mass Index, metabolic syndrome, and type 2 diabetes mellitus (T2DM) (MeSH headings) were used to search in the following databases: Pubmed, Sciencedirect (Elsevier), and Google scholar. Overall, 24 case-control studies, relevant to our topic, met the criteria and were included in the review.

RESULTS

The most prevalent leptin/leptin receptor genes (LEP/LEPR) and ghrelin/ghrelin receptor genes (GHRL/GHSR) single nucleotide polymorphisms studied were LEP G-2548A, LEPR Q223R, and Leu72Met, respectively. Nine studies of the 17 studies on LEP/LEPR, and three studies of the seven studies on GHRL/GHSR showed significant relationships.

CONCLUSIONS

In general, our study suggests that the association between LEP/LEPR and GHRL/GHSR with overweight/obesity and the related metabolic disturbances is inconclusive. These results may be due to unidentified gene-environment interactions. More investigations are needed to further clarify this association.

Beneficial Regulation of Metabolic Profiles by Black Raspberries in Human Colorectal Cancer Patients

Dietary intervention of freeze-dried black raspberries (BRBs) in a group of human colorectal cancer patients has demonstrated beneficial effects, including proapoptosis, antiproliferation, and antiangiogenesis. The aim of this study was to investigate BRB-mediated metabolite changes from this same cohort of patients. Twenty-eight colorectal cancer patients were given 60 g BRB powder daily for 1 to 9 weeks. Urine and plasma specimens were collected before and after BRB intervention. A mass spectrometry-based nontargeted metabolomic analysis was conducted on each specimen. A total of more than 400 metabolites were annotated in each specimen. Of these 34 and 6 metabolites were significantly changed by BRBs in urine and plasma, respectively. Increased levels of 4-methylcatechol sulfate in both post-BRB urine and post-BRB plasma were significantly correlated with a higher level of apoptotic marker (TUNEL) in post-BRB tumors. One tricarboxylic acid (TCA) cycle metabolites, cis-aconitate, was increased in post-BRB urine. Furthermore, BRB-derived polyphenols were absorbed and metabolized to various benzoate species, which were significantly increased in post-BRB specimens. Increased benzoate levels were positively correlated with enhanced levels of amino acid metabolite. These results suggest that BRBs induce significant metabolic changes and affect energy generating pathways.This study supports the hypothesis that BRBs might be beneficial to colorectal cancer patients through the regulation of multiple metabolites.

The biomarkers of fetal growth in intrauterine growth retardation and large for gestational age cases: from adipocytokines to a metabolomic all-in-one tool

Adipose tissue is no longer considered as inert; the literature describes the role it plays in the production of many substances, such as adiponectin, visfatin, ghrelin, S100B, apelin, TNF, IL-6 and leptin. These molecules have specific roles in humans and their potential as biomarkers useful for identifying alterations related to intrauterine growth retardation and large for gestational age neonates is emerging. Infants born in such conditions have undergone metabolic changes, such as fetal hypo- or hyperinsulinemia, which may lead to development of dysmetabolic syndrome and other chronic diseases in adulthood. In this review, these biomarkers are analyzed specifically and it is discussed how metabolomics may be an advantageous tool for detection, discrimination and prediction of metabolic alterations and diseases. Thus, a holistic approach, such as metabolomics, could help the prevention and early diagnosis of metabolic syndrome.

Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments

We present here an innovative hypothesis and report preliminary evidence that the sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The NMR spectra of the urine samples provided by four healthy donors were converted into audio signals that were analyzed in two audio experiments by listeners with both musical and non-musical training. The listeners were first asked to cluster the audio signals of two donors on the basis of perceived similarity and then to classify unknown samples after having listened to a set of reference signals. In the clustering experiment, the probability of obtaining the same results by pure chance was 7.04% and 0.05% for non-musicians and musicians, respectively. In the classification experiment, musicians scored 84% accuracy which compared favorably with the 100% accuracy attained by sophisticated pattern recognition methods. The results were further validated and confirmed by analyzing the NMR metabolic profiles belonging to two other different donors. These findings support our hypothesis that the uniqueness of the metabolic phenotype is preserved even when reproduced as audio signal and warrants further consideration and testing in larger study samples.

High resolution mass spectrometry based techniques at the crossroads of metabolic pathways

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics.

Systems biology in inflammatory bowel diseases: ready for prime time

PURPOSE OF REVIEW

Ulcerative colitis and Crohn's disease are the two predominant types of inflammatory bowel disease (IBD), affecting over 1.4 million individuals in the United States. IBD results from complex interactions between pathogenic components, including genetic and epigenetic factors, the immune response, and the microbiome, through an unknown sequence of events. The purpose of this review is to describe a systems biology approach to IBD as a novel and exciting methodology aiming at developing novel IBD therapeutics based on the integration of molecular and cellular 'omics' data.

RECENT FINDINGS

Recent evidence suggested the presence of genetic, epigenetic, transcriptomic, proteomic, and metabolomic alterations in IBD patients. Furthermore, several studies have shown that different cell types including fibroblasts, epithelial, immune, and endothelial cells together with the intestinal microbiota are involved in IBD pathogenesis. Novel computational methodologies have been developed aiming to integrate high-throughput molecular data.

SUMMARY

A systems biology approach could potentially identify the central regulators (hubs) in the IBD interactome and improve our understanding of the molecular mechanisms involved in IBD pathogenesis. The future IBD therapeutics should be developed on the basis of targeting the central hubs in the IBD network.

NMR-based metabolomic profiling of overweight adolescents: an elucidation of the effects of inter-/intraindividual differences, gender, and pubertal development

The plasma and urine metabolome of 192 overweight 12–15-year-old adolescents (BMI of 25.4 ± 2.3 kg/m²) were examined in order to elucidate gender, pubertal development measured as Tanner stage, physical activity measured as number of steps taken daily, and intra-/interindividual differences affecting the metabolome detected by proton NMR spectroscopy. Higher urinary excretion of citrate, creatinine, hippurate, and phenylacetylglutamine and higher plasma level of phosphatidylcholine and unsaturated lipid were found for girls compared with boys. The results suggest that gender differences in the metabolome are being commenced already in childhood. The relationship between Tanner stage and the metabolome showed that pubertal development stage was positively related to urinary creatinine excretion and negatively related to urinary citrate content. No relations between physical activity and the metabolome could be identified. The present study for the first time provides comprehensive information about associations between the metabolome and gender, pubertal development, and physical activity in overweight adolescents, which is an important subject group to approach in the prevention of obesity and life-style related diseases. While this study is preliminary, these results may have the potential to translate into clinical applicability upon further investigations; if biomarkers for Tanner stage can be established, these might be used for identification of individuals susceptible to an early pubertal development.

The marriage of nutrigenomics with the microbiome: the case of infant-associated bifidobacteria and milk

Broadly, nutrigenomics examines the association of exogenous nutrients and molecular responses to maintain homeostasis in an individual. Phenotypic expression profiling, often transcriptomics, has been applied to identify markers and metabolic consequences of suboptimal diet, lifestyle, or both. The decade after the Human Genome Project has been marked with advances in high-throughput analysis of biological polymers and metabolites, prompting a rapid increase in characterization of the profound nature by which our symbiotic microbiota influences human physiology. Although the technology is widely accessible to assess microbiome composition, genetic potential, and global function, nutrigenomics studies often exclude the microbial contribution to host responses to ingested nutritive molecules. Perhaps a hallmark of coevolution, milk provides a dramatic example of a diet that promotes a particular microbial community structure, because the lower infant gastrointestinal tract is often dominated by bifidobacteria that flourish on milk glycans. Systems-level approaches should continue to be applied to examine the microbial communities in the context of their host's dietary habits and metabolic status. In addition, studies of isolated microbiota species should be encouraged to inform clinical studies and interventions as well as community studies. Whereas nutrigenomics research is beginning to account for resident microbiota, the need remains to consistently consider our microscopic partners in the human holobiont.

Development of a Standard Reference Material for metabolomics research

The National Institute of Standards and Technology (NIST), in collaboration with the National Institutes of Health (NIH), has developed a Standard Reference Material (SRM) to support technology development in metabolomics research. SRM 1950 Metabolites in Human Plasma is intended to have metabolite concentrations that are representative of those found in adult human plasma. The plasma used in the preparation of SRM 1950 was collected from both male and female donors, and donor ethnicity targets were selected based upon the ethnic makeup of the U.S. population. Metabolomics research is diverse in terms of both instrumentation and scientific goals. This SRM was designed to apply broadly to the field, not toward specific applications. Therefore, concentrations of approximately 100 analytes, including amino acids, fatty acids, trace elements, vitamins, hormones, selenoproteins, clinical markers, and perfluorinated compounds (PFCs), were determined. Value assignment measurements were performed by NIST and the Centers for Disease Control and Prevention (CDC). SRM 1950 is the first reference material developed specifically for metabolomics research.

Metabolomics as a diagnostic tool in gastroenterology

Metabolomics has increasingly been applied in addition to other “omic” approaches in the study of the pathophysiology of different gastrointestinal diseases. Metabolites represent molecular readouts of the cell status reflecting a physiological phenotype. In addition, changes in metabolite concentrations induced by exogenous factors such as environmental and dietary factors which do not affect the genome, are taken into account. Metabolic reactions initiated by the host or gut microbiota can lead to “marker” metabolites present in different biological fluids that allow differentiation between health and disease. Several lines of evidence implicated the involvement of intestinal microbiota in the pathogenesis of inflammatory bowel disease (IBD). Also in irritable bowel syndrome (IBS), a role of an abnormal microbiota composition, so-called dysbiosis, is supported by experimental data. These compositional alterations could play a role in the aetiology of both diseases by altering the metabolic activities of the gut bacteria. Several studies have applied a metabolomic approach to identify these metabolite signatures. However, before translating a potential metabolite biomarker into clinical use, additional validation studies are required. This review summarizes contributions that metabolomics has made in IBD and IBS and presents potential future directions within the field.

The human milk metabolome reveals diverse oligosaccharide profiles

Breast milk delivers nutrition and protection to the developing infant. There has been considerable research on the high-molecular-weight milk components; however, low-molecular-weight metabolites have received less attention. To determine the effect of maternal phenotype and diet on the human milk metabolome, milk collected at day 90 postpartum from 52 healthy women was analyzed by using proton nuclear magnetic resonance spectroscopy. Sixty-five milk metabolites were quantified (mono-, di-, and oligosaccharides; amino acids and derivatives; energy metabolites; fatty acids and associated metabolites; vitamins, nucleotides, and derivatives; and others). The biological variation, represented as the percentage CV of each metabolite, varied widely (4-120%), with several metabolites having low variation (<20%), including lactose, urea, glutamate, myo-inositol, and creatinine. Principal components analysis identified 2 clear groups of participants who were differentiable on the basis of milk oligosaccharide concentration and who were classified as secretors or nonsecretors of fucosyltransferase 2 (FUT2) gene products according to the concentration of 2'-fucosyllactose, lactodifucotetraose, and lacto-N-fucopentaose I. Exploration of the interrelations between the milk sugars by using Spearman rank correlations revealed significant positive and negative associations, including positive correlations between fucose and products of the FUT2 gene and negative correlations between fucose and products of the fucosyltransferase 3 (FUT3) gene. The total concentration of milk oligosaccharides was conserved among participants (%CV = 18%), suggesting tight regulation of total oligosaccharide production; however, concentrations of specific oligosaccharides varied widely between participants (%CV = 30.4-84.3%). The variability in certain milk metabolites suggests possible roles in infant or infant gut microbial development. This trial was registered at clinicaltrials.gov as NCT01817127.

Emerging aspects of food and nutrition on gut microbiota

The human gastrointestinal tract contains a highly complex ecosystem that harbors various microorganisms, which together create a unique environment within each individual. There is growing awareness that dietary habits are one of the essential factors contributing to the microbial diversity and community configuration that ultimately affects human health. From an evolutionary perspective, human dietary history can be viewed as a central factor in the selection of the gut microbial community and stabilization of the mutualistic host-microbial interaction, that together drive host phenotype. Herein, current knowledge concerning the influence of major dietary macrostructure and individual food ingredients is presented. This knowledge will provide perspectives for personalized gut microbiota management and, ultimately, movement toward an era of personalized nutrition and medicine.

Doping control using high and ultra-high resolution mass spectrometry based non-targeted metabolomics-a case study of salbutamol and budesonide abuse

We have detected differences in metabolite levels between doped athletes, clean athletes, and volunteers (non athletes). This outcome is obtained by comparing results of measurements from two analytical platforms: UHPLC-QTOF/MS and FT-ICR/MS. Twenty-seven urine samples tested positive for glucocorticoids or beta-2-agonists and twenty samples coming from volunteers and clean athletes were analyzed with the two different mass spectrometry approaches using both positive and negative electrospray ionization modes. Urine is a highly complex matrix containing thousands of metabolites having different chemical properties and a high dynamic range. We used multivariate analysis techniques to unravel this huge data set. Thus, the several groups we created were studied by Principal Components Analysis (PCA) and Partial Least Square regression (PLS-DA and OPLS) in the search of discriminating m/z values. The selected variables were annotated and placed on pathway by using MassTRIX.

Spectral deconvolution for gas chromatography mass spectrometry-based metabolomics: current status and future perspectives

Mass spectrometry coupled to gas chromatography (GC-MS) has been widely applied in the field of metabolomics. Success of this application has benefited greatly from computational workflows that process the complex raw mass spectrometry data and extract the qualitative and quantitative information of metabolites. Among the computational algorithms within a workflow, deconvolution is critical since it reconstructs a pure mass spectrum for each component that the mass spectrometer observes. Based on the pure spectrum, the corresponding component can be eventually identified and quantified. Deconvolution is challenging due to the existence of co-elution. In this review, we focus on progress that has been made in the development of deconvolution algorithms and provide thoughts on future developments that will expand the application of GC-MS in metabolomics.

The evolution of nutrition research

"The doctor of the future will no longer treat the human frame with drugs, but will rather cure and prevent disease with nutrition". Thomas Edison's contemplation may come to fruition if the nutritional revolution continues in its current course. Two realizations have propelled the world into a new age of personalized nutrition: (i) food can provide benefits beyond its intrinsic nutrient content, and (ii) we are not all created equal in our ability to realize to these benefits. Nutrigenomics is concerned with delineating genomic propensities to respond to various nutritional stimuli and the resulting impact on individual health. This review will examine the current technologies utilized by nutrigeneticists, the available literature regarding nutrient-gene interactions, and the translation of this new awareness into public health.

Global metabolic profiling of animal and human tissues via UPLC-MS

Obtaining comprehensive, untargeted metabolic profiles for complex solid samples, e.g., animal tissues, requires sample preparation and access to information-rich analytical methodologies such as mass spectrometry (MS). Here we describe a practical two-step process for tissue samples that is based on extraction into 'aqueous' and 'organic' phases for polar and nonpolar metabolites. Separation methods such as ultraperformance liquid chromatography (UPLC) in combination with MS are needed to obtain sufficient resolution to create diagnostic metabolic profiles and identify candidate biomarkers. We provide detailed protocols for sample preparation, chromatographic procedures, multivariate analysis and metabolite identification via tandem MS (MS/MS) techniques and high-resolution MS. By using these optimized approaches, analysis of a set of samples using a 96-well plate format would take ~48 h: 1 h for system setup, 8-10 h for sample preparation, 34 h for UPLC-MS analysis and 2-3 h for preliminary/exploratory data processing, representing a robust method for untargeted metabolic screening of tissue samples.

Multivariate Analysis in Metabolomics

Metabolomics aims to provide a global snapshot of all small-molecule metabolites in cells and biological fluids, free of observational biases inherent to more focused studies of metabolism. However, the staggeringly high information content of such global analyses introduces a challenge of its own; efficiently forming biologically relevant conclusions from any given metabolomics dataset indeed requires specialized forms of data analysis. One approach to finding meaning in metabolomics datasets involves multivariate analysis (MVA) methods such as principal component analysis (PCA) and partial least squares projection to latent structures (PLS), where spectral features contributing most to variation or separation are identified for further analysis. However, as with any mathematical treatment, these methods are not a panacea; this review discusses the use of multivariate analysis for metabolomics, as well as common pitfalls and misconceptions.

Nutrimetabolomic strategies to develop new biomarkers of intake and health effects

Correctly assessing the metabolic status of subjects after consumption of specific diets is an important challenge for modern nutrition. Recently, metabolomics has been proposed as a powerful tool for exploring the complex relationship between nutrition and health. Nutritional metabolomics, through investigating the role that dietary components play in the maintenance of health and development of risk disease, aims to identify new biomarkers that allow the intake of these compounds to be monitored and related to their expected biological effects. This review offers an overview of the application of nutrimetabolomic strategies in the discovery of new biomarkers in human nutritional research, suggesting three main categories: (1) assessment of nutritional and dietary interventions; (2) diet exposure and food consumption monitoring; and (3) health phenotype and metabolic impact of diet. For this purpose, several examples of these applications will be used to provide evidence and to discuss the advantages and drawbacks of these nutrimetabolomic strategies.

Potential value of nutrigenomics in Crohn's disease

Crohn's disease is a chronic relapsing condition that has no certain cure. Both genetic susceptibility and nutrition have key roles, but their level of involvement varies between patients. Interacting gene pathways influence the probability of disease development, but these are affected by stress and various environmental factors, including diet. In addition, the role of the gut microbiome must not be underestimated, as it is substantially altered in patients with Crohn's disease. Although an elemental diet might lead to disease remission, reintroducing real foods and sustainable diets in patients with Crohn's disease is currently difficult, and would benefit from the sensitivity and rapid feedback provided by the field of nutrigenomics. Nutrigenomics utilizes high-throughput genomics technologies to reveal changes in gene and protein expression that are modulated by the patient's nutrition. The most widely used technique thus far is transcriptomics, which permits measurement of changes in the expression of thousands of genes simultaneously in one sample. Given the volume of numbers generated in such studies, data-basing and bioinformatics are essential to ensure the correct application of nutrigenomics at the population level. These methods have been successfully applied to animal models of Crohn's disease, and the time is right to move them to human studies.