Profiling techniques in nutrition and health research

Omics Technology for the Promotion of Nutraceuticals and Functional Foods

The influence of nutrition and environment on human health has been known for ages. Phytonutrients (7,000 flavonoids and phenolic compounds; 600 carotenoids) and pro-health nutrients—nutraceuticals positively add to human health and may prevent disorders such as cancer, diabetes, obesity, cardiovascular diseases, and dementia. Plant-derived bioactive metabolites have acquired an imperative function in human diet and nutrition. Natural phytochemicals affect genome expression (nutrigenomics and transcriptomics) and signaling pathways and act as epigenetic modulators of the epigenome (nutri epigenomics). Transcriptomics, proteomics, epigenomics, miRNomics, and metabolomics are some of the main platforms of complete omics analyses, finding use in functional food and nutraceuticals. Now the recent advancement in the integrated omics approach, which is an amalgamation of multiple omics platforms, is practiced comprehensively to comprehend food functionality in food science.

Combined extracts of Echinacea angustifolia DC. and Zingiber officinale Roscoe in softgel capsules: Pharmacokinetics and immunomodulatory effects assessed by gene expression profiling

BACKGROUND AND OBJECTIVE

Echinacea angustifolia DC. and Zingiber officinale Roscoe are two natural products with documented immunomodulatory activity, both able to modulate the expression of important immune-related genes. Thus, their use in combination seems to be particularly promising. In this context, we have considered the oral supplementation of a highly standardized lipophilic extract combining both above-mentioned phytocomplexes, formulated in attractive softgel capsules, with two objectives: on the one hand to study oral pharmacokinetic of main active extracts' components and on the other hand to examine the immunomodulation and anti-inflammatory properties by gene expression profiling.

METHODS

Softgel capsules containing a combination of E. angustifolia DC. and Z. officinale Roscoe (5 mg and 25 mg, respectively) were given by oral administration to 10 healthy volunteers. The plasma concentrations of dodeca-2E,4E,8Z,10E/Z-tetraenoic isobutylamide (tetraene) for E. angustifolia DC., 6-gingerol and 6-shogaol (free and glucuronide) for Z. officinale Roscoe were determined by LC-MS analysis, and the pharmacokinetic analysis was performed. To understand the functional mechanisms responsible for the documented health benefits, we also examined the overall transcriptional remodeling induced in the peripheral blood mononuclear cells and performed an integrative functional analysis on the generated gene expression.

RESULTS

All bioactive components were absorbed very rapidly, and their tmax were detected in plasma from 30 min to 1.40 h. The peak concentrations of tetraene, 6-gingerol, 6-shogaol and their glucuronide metabolites were 14.74, 5.66, 9.25, 29.2 and 22.24 ng/ml, respectively. Integrated analysis performed on the generated gene expression data highlighted immunomodulatory and anti-inflammatory effects similar to those exerted by hydrocortisone.

CONCLUSION

These data demonstrated that the bioactive ingredients are highly and rapidly absorbed from softgel capsules containing the combination of the above-mentioned lipophilic extracts, providing evidence to support their immunomodulatory and anti-inflammatory properties. These data also help in defining the mechanistic pathways underlying the health benefits of these plant-derived bioactive compounds.

Bottlenecks in Proteomics: An Update

Mass spectrometry (MS) is the core for advanced methods in proteomic experiments. When effectively used, proteomics may provide extensive information about proteins and their post-translational modifications, as well as their interaction partners. However, there are also many problems that one can encounter during a proteomic experiment, including, but not limited to sample preparation, sample fractionation, sample analysis, data analysis & interpretation and biological significance. Here we discuss some of the problems that researchers should be aware of when performing a proteomic experiment.

Nutrient sensing and metabolic changes after methionine deprivation in primary muscle cells of turbot (Scophthalmus maximus L.)

The low methionine content in plant-based diets is a major limiting factor for feed utilization by animals. However, the molecular consequences triggered by methionine deficiency have not been well characterized, especially in fish species, whose metabolism is unique in many aspects and important for aquaculture industry. In the present study, the primary muscle cells of turbot (Scophthalmus maximus L.) were isolated and treated with or without methionine for 12 h in culture. The responses of nutrient sensing pathways, the proteomic profiling of metabolic processes, and the expressions of key metabolic molecules were systematically examined. Methionine deprivation (MD) suppressed target of rapamycin (TOR) signaling, activated AMP-activated protein kinase (AMPK) and amino acid response (AAR) pathways. Reduced cellular protein synthesis and increased protein degradation by MD led to increased intracellular free amino acid levels and degradations. MD also reduced glycolysis and lipogenesis while stimulated lipolysis, thus resulted in decreased intracellular lipid pool. MD significantly enhanced energy expenditure through stimulated tricarboxylic acid (TCA) cycle and oxidative phosphorylation. Collectively, our results identified a comprehensive set of transcriptional, proteomic, and signaling responses generated by MD and provided the molecular insight into the integration of cell homeostasis and metabolic controls in fish species.

Comparative proteomic analysis of liver antioxidant mechanisms in Megalobrama amblycephala stimulated with dietary emodin

Oxidative stress is a toxicological endpoint that correlates with the nutrition status of fish through cellular damage, inflammation, and apoptosis. In order to understand the antioxidant mechanism induced by dietary emodin in Megalobrama amblycephala liver, a comparative proteomic analysis was performed to investigate the proteome alteration under emodin administration. 27 altered protein spots were separated under 30 mg kg^-1 emodin stimulation based on 2-DE, and were all successfully identified using MALDI-TOF/TOF, representing 17 unique proteins. These proteins were functionally classified into antioxidant, metabolism, cytoskeleton, chaperone, signal transduction and cofactor groups. Network interaction and Gene Ontology annotation indicated 10 unique proteins were closely related to antioxidation and directly regulated by each other. Compared with the control group, administration of 30 mg kg^-1 emodin significantly increased the antioxidant-related mRNA expressions of GPx1, GSTm and HSP70, but decreased the mRNA expressions of GAPDH and Sord, which was consistent with the protein expression. Nevertheless, Pgk1 and Aldh8a1 were up- and down-regulated, and ALDOB was down- and up-regulated at the mRNA and protein levels, respectively. These results revealed that the altered proteins enhanced antioxidation via complex regulatory mechanisms, and 30 mg kg^-1 emodin was a suitable immunostimulant for M. amblycephala.

False precision of mass domain in HPLC-HRMS data representation

The term precision of a value describes the total number of significant digits that are used to express that value. False precision is presented in data, where the sampling and chosen data file format coding return values with extra non-valid digits. The proper precision in value thus depends on so-called magnitude in digital data coding. The presence of the false precision is file format dependent. The amount of dataset points could be decreased by removing false precision (where it is present) to almost 10% of the raw measurement without loss of information.

The genomics of micronutrient requirements

Healthy nutrition is accepted as a cornerstone of public health strategies for reducing the risk of noncommunicable conditions such as obesity, cardiovascular disease, and related morbidities. However, many research studies continue to focus on single or at most a few factors that may elicit a metabolic effect. These reductionist approaches resulted in: (1) exaggerated claims for nutrition as a cure or prevention of disease; (2) the wide use of empirically based dietary regimens, as if one fits all; and (3) frequent disappointment of consumers, patients, and healthcare providers about the real impact nutrition can make on medicine and health. Multiple factors including environment, host and microbiome genetics, social context, the chemical form of the nutrient, its (bio)availability, and chemical and metabolic interactions among nutrients all interact to result in nutrient requirement and in health outcomes. Advances in laboratory methodologies, especially in analytical and separation techniques, are making the chemical dissection of foods and their availability in physiological tissues possible in an unprecedented manner. These omics technologies have opened opportunities for extending knowledge of micronutrients and of their metabolic and endocrine roles. While these technologies are crucial, more holistic approaches to the analysis of physiology and environment, novel experimental designs, and more sophisticated computational methods are needed to advance our understanding of how nutrition influences health of individuals.

System model network for adipose tissue signatures related to weight changes in response to calorie restriction and subsequent weight maintenance

Nutrigenomics investigates relationships between nutrients and all genome-encoded molecular entities. This holistic approach requires systems biology to scrutinize the effects of diet on tissue biology. To decipher the adipose tissue (AT) response to diet induced weight changes we focused on key molecular (lipids and transcripts) AT species during a longitudinal dietary intervention. To obtain a systems model, a network approach was used to combine all sets of variables (bio-clinical, fatty acids and mRNA levels) and get an overview of their interactions. AT fatty acids and mRNA levels were quantified in 135 obese women at baseline, after an 8-week low calorie diet (LCD) and after 6 months of ad libitum weight maintenance diet (WMD). After LCD, individuals were stratified a posteriori according to weight change during WMD. A 3 steps approach was used to infer a global model involving the 3 sets of variables. It consisted in inferring intra-omic networks with sparse partial correlations and inter-omic networks with regularized canonical correlation analysis and finally combining the obtained omic-specific network in a single global model. The resulting networks were analyzed using node clustering, systematic important node extraction and cluster comparisons. Overall, AT showed both constant and phase-specific biological signatures in response to dietary intervention. AT from women regaining weight displayed growth factors, angiogenesis and proliferation signaling signatures, suggesting unfavorable tissue hyperplasia. By contrast, after LCD a strong positive relationship between AT myristoleic acid (a fatty acid with low AT level) content and de novo lipogenesis mRNAs was found. This relationship was also observed, after WMD, in the group of women that continued to lose weight. This original system biology approach provides novel insight in the AT response to weight control by highlighting the central role of myristoleic acid that may account for the beneficial effects of weight loss.

Obesity is an excess fat mass leading to metabolic diseases. Dietary management is a conventional strategy to promote weight loss. As energy buffering, in the form of esterified fatty acids, and secretory organ, the adipose tissue has a pivotal role in obesity and its related complications. A comprehensive insight of adipose tissue response during and after calorie restriction might improve obesity management. Modern nutrition research study the impact of diet on health by combining multiple datasets to provide an holistic view of tissue physiopathology. To identify significant clusters of fatty acids, transcripts or bio-clinical parameters related to weight change along calorie restriction and subsequent weight follow-up in obese individuals, the issue of different datasets integration must be resolved. Here, we implemented an innovative multistep approach to infer multi-data networks and compare clusters of network components. This original strategy highlighted an unexpected central role of a minor adipose tissue fatty acid, myristoleic acid, which is not provided by food. Its link to transcripts encoding enzymes from a pathway converting glucose into fat that mediates favorable metabolic effects makes myristoleic acid a key factor of the positive impact of fat mass reduction.

Nutrigenomics of body weight regulation: a rationale for careful dissection of individual contributors

Body weight stability may imply active regulation towards a certain physiological condition, a body weight setpoint. This interpretation is ill at odds with the world-wide increase in overweight and obesity. Until now, a body weight setpoint has remained elusive and the setpoint theory did not provide practical clues for body weight reduction interventions. For this an alternative theoretical model is necessary, which is available as the settling point model. The settling point model postulates that there is little active regulation towards a predefined body weight, but that body weight settles based on the resultant of a number of contributors, represented by the individual's genetic predisposition, in interaction with environmental and socioeconomic factors, such as diet and lifestyle. This review refines the settling point model and argues that by taking body weight regulation from a settling point perspective, the road will be opened to careful dissection of the various contributors to establishment of body weight and its regulation. This is both necessary and useful. Nutrigenomic technologies may help to delineate contributors to body weight settling. Understanding how and to which extent the different contributors influence body weight will allow the design of weight loss and weight maintenance interventions, which hopefully are more successful than those that are currently available.

Utilization of rye as energy source affects bacterial translocation, intestinal viscosity, microbiota composition, and bone mineralization in broiler chickens

Two independent trials were conducted to evaluate the utilization of rye as energy source on bacterial translocation (BT), intestinal viscosity, gut integrity, gut microbiota composition, and bone mineralization, when compared with a traditional cereal (corn) in broiler chickens. In each experiment, day-of-hatch, broiler chickens were randomly assigned to either a corn or a rye diet (n = 20 chickens/group). At 10 d of age, in both experiments, 12 chickens/group were randomly selected, and given an oral gavage dose of fluorescein isothiocyanate dextran (FITC-d). After 2.5 h of oral gavage, blood samples were collected to determine the passage of FITC-d. The liver was collected from each bird to evaluate BT. Duodenum, ileum, and cecum gut sections were collected to evaluate intestinal viscosity and to enumerate gut microbiota. Tibias were collected for observation of bone parameters. Broilers fed with rye showed increased (p < 0.05) intestinal viscosity, BT, and serum FITC-d. Bacterial enumeration revealed that chickens fed with rye had increased the number of total lactic acid bacteria in all three sections of the gastrointestinal tract evaluated when compared to chickens fed with corn. Chickens fed with rye also had significantly higher coliforms in duodenum and ileum, whereas the total number of anaerobes increased only in duodenum. A significant reduction in bone strength and bone mineralization was observed in chickens fed with rye when compared with corn fed chickens. In conclusion, rye evoked mucosal damage in chickens that alter the intestinal viscosity, increased leakage through the intestinal tract, and altered the microbiota composition as well as bone mineralization. Studies to evaluate dietary inclusion of selected DFM candidates that produce exogenous enzymes in rye fed chickens are currently being evaluated.

Omics and integrated omics for the promotion of food and nutrition science

Transcriptomics, proteomics, and metabolomics are three major platforms of comprehensive omics analysis in the science of food and complementary medicine. Other omics disciplines, including those of epigenetics and microRNA, are matters of increasing concern. The increased use of the omics approach in food science owes much to the recent advancement of technology and bioinformatic methodologies. Moreover, many researchers now put the combination of multiple omics analysis (integrated omics) into practice to exhaustively understand the functionality of food components. However, data analysis of integrated omics requires huge amount of work and high skill of data handling. A database of nutritional omics data was constructed by the authors, which should help food scientists to analyze their own omics data more effectively. In addition, a novel tool for the easy visualization of omics data was developed by the authors’ group. The tool enables one to overview the changes of multiple omics in the KEGG pathway. Research in traditional and complementary medicine will be further facilitated by promoting the integrated omics research of food functionality. Such integrated research will only be possible with the effective collaboration of scientists with different backgrounds.

Perspective: a systems approach to diabetes research

We review here the status of human type 2 diabetes studies from a genetic, epidemiological, and clinical (intervention) perspective. Most studies limit analyses to one or a few omic technologies providing data of components of physiological processes. Since all chronic diseases are multifactorial and arise from complex interactions between genetic makeup and environment, type 2 diabetes mellitus (T2DM) is a collection of sub-phenotypes resulting in high fasting glucose. The underlying gene–environment interactions that produce these classes of T2DM are imperfectly characterized. Based on assessments of the complexity of T2DM, we propose a systems biology approach to advance the understanding of origin, onset, development, prevention, and treatment of this complex disease. This systems-based strategy is based on new study design principles and the integrated application of omics technologies: we pursue longitudinal studies in which each subject is analyzed at both homeostasis and after (healthy and safe) challenges. Each enrolled subject functions thereby as their own case and control and this design avoids assigning the subjects a priori to case and control groups based on limited phenotyping. Analyses at different time points along this longitudinal investigation are performed with a comprehensive set of omics platforms. These data sets are generated in a biological context, rather than biochemical compound class-driven manner, which we term “systems omics.”

The role of metabonomics as a tool for augmenting nutritional information in epidemiological studies

Most chronic diseases have been demonstrated to have a link to nutrition. Within food and nutritional research there is a major driver to understand the relationship between diet and disease in order to improve health of individuals. However, the lack of accurate dietary intake assessment in free-living populations, makes accurate estimation of how diet is associated with disease risk difficulty. Thus, there is a pressing need to find solutions to the inaccuracy of dietary reporting. Metabolic profiling of urine or plasma can provide an unbiased approach to characterizing dietary intake and various high-throughput analytical platforms have been used in order to implement targeted and nontargeted assays in nutritional clinical trials and nutritional epidemiology studies. This review describes first the challenges presented in interpreting the relationship between diet and health within individual and epidemiological frameworks. Second, we aim to explore how metabonomics can benefit different types of nutritional studies and discuss the critical importance of selecting appropriate analytical techniques in these studies. Third, we propose a strategy capable of providing accurate assessment of food intake within an epidemiological framework in order establish accurate associations between diet and health.

Emerging applications of metabolomics in studying chemopreventive phytochemicals

Phytochemicals from diet and herbal medicines are under intensive investigation for their potential use as chemopreventive agents to block and suppress carcinogenesis. Chemical diversity of phytochemicals, together with complex metabolic interactions between phytochemicals and biological system, can overwhelm the capacity of traditional analytical platforms, and thus pose major challenges in studying chemopreventive phytochemicals. Recent progresses in metabolomics have transformed it to become a robust systems biology tool, suitable for examining both chemical and biochemical events that contribute to the cancer prevention activities of plant preparations or their bioactive components. This review aims to discuss the technical platform of metabolomics and its existing and potential applications in chemoprevention research, including identifying bioactive phytochemicals in plant extracts, monitoring phytochemical exposure in humans, elucidating biotransformation pathways of phytochemicals, and characterizing the effects of phytochemicals on endogenous metabolism and cancer metabolism.

Online tools for bioinformatics analyses in nutrition sciences

Recent advances in "omics" research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field.

Responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes: a randomized trial

Background

The ability of subjects to respond to nutritional challenges can reflect the flexibility of their biological system. Nutritional challenge tests could be used as an indicator of health status but more knowledge on metabolic and immune responses of different subjects to nutritional challenges is needed. The aim of this study was to compare the responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes.

Methodology/Principal Findings

In a cross-over design 42 men (age 50–70 y) consumed three high-fat shakes containing saturated fat (SFA), monounsaturated fat (MUFA) or n-3 polyunsaturated (PUFA). Men were selected on BMI and health status (lean, obese or obese diabetic) and phenotyped with MRI for adipose tissue distribution. Before and 2 and 4 h after shake consumption blood was drawn for measurement of expression of metabolic and inflammation-related genes in peripheral blood mononuclear cells (PBMCs), plasma triglycerides (TAG), glucose, insulin, cytokines and ex vivo PBMC immune response capacity. The MUFA and n-3 PUFA challenge, compared to the SFA challenge, induced higher changes in expression of inflammation genes MCP1 and IL1β in PBMCs. Obese and obese diabetic subjects had different PBMC gene expression and metabolic responses to high-fat challenges compared to lean subjects. The MUFA challenge induced the most pronounced TAG response, mainly in obese and obese diabetic subjects.

Conclusion/Significance

The PBMC gene expression response and metabolic response to high-fat challenges were affected by fat type and metabolic risk phenotype. Based on our results we suggest using a MUFA challenge to reveal differences in response capacity of subjects.

Trial Registration

ClinicalTrials.gov NCT00977262

Using gene expression to predict differences in the secretome of human omental vs. subcutaneous adipose tissue

The objective of this study was to characterize differences in the secretome of human omental compared with subcutaneous adipose tissue using global gene expression profiling. Gene expression was measured using Affymetrix microarrays (Affymetrix, Santa Clara, CA) in subcutaneous and omental adipose tissue in two independent experiments (n = 5 and n = 3 independent subjects; n = 16 arrays in total, 2 for each subject). Predictive bioinformatic algorithms were employed to identify secreted proteins. Microarray analysis identified 22 gene probe sets whose expression was significantly different with a fold change (FC) greater than 5 in expression in both experiments between omental and subcutaneous adipose tissue. Using bioinformatic predictive programs 11 of these 22 probe sets potentially coded for secreted proteins. Pathway network analysis of the secreted proteins showed that three of the proteins are part of a common pathway network. These proteins gremlin 1 (GREM1), pleiotrophin (PTN), and secretory leukocyte peptidase inhibitor (SLPI) are expressed respectively 43×, 23×, and 5× in omental adipose tissue relative to subcutaneous adipose tissue as determined by real-time PCR. The presence of GREM1, PTN, and SLPI protein in human adipose tissue was confirmed by western blotting. All three proteins are expressed in the human Simpson-Golabi-Behmel syndrome (SGBS) preadipocyte cell line. The expression of GREM1, PTN, and SLPI changed with the differentiation of the preadipocytes into mature adipocytes. Gene expression coupled with predictive bioinformatic algorithms have identified several genes coding for secreted proteins which are expressed differently in omental adipose tissue compared to subcutaneous adipose tissue proving a valid alternative approach to help further define the adipocyte secretome.

Proteomics at the interface of psychology, gut physiology and dysfunction: an underexploited approach that deserves expansion

Gut functions such as digestion and absorption are essential to life and the emerging insights into the gut-brain axis - that is, the cross talk between the enteric and CNS - point towards critical links between (eating) behavior, psychology, whole body and gut physiology, and digestive and overall health. While proteomics is ideally positioned to shed more light on these interactions, be it applied to the periphery (e.g., blood) or the locus of action (i.e., the gut), it is to date largely underexploited, mainly because of challenging sampling and tissue complexity. In view of the contrast between potential and current delivery of proteomics in the context of intestinal health, this article briefs the reader on the state-of-the-art of molecular intestinal research, reviews current proteomic studies (explicitly focusing on the most recent ones that target inflammatory bowel disease patient samples) and argues for an expansion of this research field.

Mass spectrometry for nutritional peptidomics: How to analyze food bioactives and their health effects

We describe nutritional peptidomics for discovery and validation of bioactive food peptide and their health effects. Understanding nature and bioactivity of nutritional peptides means comprehending an important level of environmental regulation of the human genome, because diet is the environmental factor with the most profound life-long influence on health. We approach the theme from three angles, namely the analysis, the discovery and the biology perspective. Food peptides derive from parent food proteins via in vitro hydrolysis (processing) or in vivo digestion by various unspecific and specific proteases, as opposed to the tryptic peptides typically generated in biomarker proteomics. A food bioactive peptide may be rare or unique in terms of sequence and modification, and many food genomes are less well annotated than e.g. the human genome. Bioactive peptides can be discovered either empirically or by prediction: we explain both the classical hydrolysis strategy and the bioinformatics-driven reversed genome engineering. In order to exert bioactivity, food peptides must be either ingested and then reach the intestine in their intact form or be liberated in situ from their parent proteins to act locally, that is in the gut, or even systemically, i.e. through the blood stream. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

1H NMR-based metabonomic applications to decipher gut microbial metabolic influence on mammalian health

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

Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples

Conventional tools for measuring dietary exposure have well recognized limitations. Measurement of food-derived metabolites in biofluids provides an alternative approach and our aim was to develop an experimental protocol which ensures that extraneous variability does not obscure metabolic signals from ingested foods. Healthy adults consumed a standardized meal in the evening before each test day and collected pooled overnight urine. On each test day of three different studies, urine was collected in the fasted state and at different time points after consumption of a standardized breakfast. Metabolite fingerprinting of samples using Flow Infusion Electrospray-Ionization Mass Spectrometry followed by multivariate data analysis showed strong discrimination between overnight, fasting and postprandial samples, in each study separately and when data from the three studies were pooled. Such differences were robust and highly reproducible within individuals on separate occasions. Urine volume was an efficient data normalization factor for metabolite fingerprinting data. Postprandial urines had a stable chemical composition over a period of 2-4 h after eating a standardized breakfast, suggesting that there is a flexible time window for urine collection. Fasting urine samples provided a stable baseline for universal comparisons with postprandial samples. A dietary exposure biomarker discovery protocol was validated by demonstrating that top-ranked signals discriminating between fasting and 2-4 h postprandial urine samples could be linked to metabolites abundant in some components of the standardized breakfast. We conclude that the protocol developed will have value in the search for biomarker leads of dietary exposure. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0289-0) contains supplementary material, which is available to authorized users.

Metabolic phenotyping of the Crohn's disease-like IBD etiopathology in the TNF(ΔARE/WT) mouse model

The underlying biochemical consequences of inflammatory bowel disease (IBD) on the systemic and gastrointestinal metabolism have not yet been fully elucidated but could help to better understand the disease pathogenesis and to identify tissue-specific markers associated with the different disease stages. Here, we applied a metabonomic approach to monitor metabolic events associated with the gradual development of Crohn's disease (CD)-like ileitis in the TNF(ΔARE/WT) mouse model. Metabolic profiles of different intestinal compartments from the age of 4 up to 24 weeks were generated by combining proton nuclear magnetic resonance ((1)H NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). From 8 weeks onward, mice developed CD similar to the immune and tissue-related phenotype of human CD with ileal involvement, including ileal histological abnormalities, reduced fat mass and body weight, as well as hallmarks of malabsorption with higher energy wasting. The metabonomic approach highlighted shifts in the intestinal lipid metabolism concomitant to the histological onset of inflammation. Moreover, the advanced disease status was characterized by a significantly altered metabolism of cholesterol, triglycerides, phospholipids, plasmalogens, and sphingomyelins in the inflamed tissue (ileum) and the adjacent intestinal parts (proximal colon). These results describe different biological processes associated with the disease onset, including modifications of the general cell membrane composition, alteration of energy homeostasis, and finally the generation of inflammatory lipid mediators. Taken together, this provides novel insights into IBD-related alterations of specific lipid-dependant processes during inflammatory states.

Assessment of research models for testing gene-environment interactions

Throughout the last century, possible effects of exposure to toxicants, nutrients or drugs were examined primarily by studies of groups or populations. Individual variation in responses was acknowledged but could not be analyzed due to lack of information or tools to analyze individual genetic make-ups and lifestyle factors such as diet and activity. The Human Genome, Haplotype Map, 1000Genomes, and Human Variome Projects are identifying and cataloging the variation found within humans. Advances in DNA sequencing technologies will soon permit the characterization of individual genomes in clinical and basic research studies, thus allowing associations to be made between an individual genotype and the response to a particular exposure. Such knowledge and tools have generated a significant challenge for scientists: to design and conduct research studies that account for individual genetic variation. However, before these studies are done in humans, they will be performed in various in vivo and in vitro models. The advantages and disadvantages of some of the model test systems that are being used or developed in relation to individual genetic make-up and responses to xenobiotics are discussed.

Impact of a mechanical massage on gene expression profile and lipid mobilization in female gluteofemoral adipose tissue

BACKGROUND

Gluteofemoral adipose tissue areas are known to be poorly metabolically reactive. Mechanical massage has previously been reported to show morphological and functional impact on this tissue. The present study was carried out to delve more deeply into the mechanistic considerations regarding the incidence of a mechanical massage technique on gene expression profile and β-adrenergic-mediated lipid mobilization in female femoral adipose tissue.

METHODS

Twelve premenopausal healthy women were included and received 12 sessions of calibrated mechanical massage (Endermologie®). Total RNA was extracted from femoral adipose tissue biopsies for gene expression studies. Microdialysis was carried out in the femoral adipose tissue in order to assess lipolytic responsiveness (via glycerol determination) and changes in local blood flow following perfusion of a lipolytic agent, isoproterenol. Evaluations were performed before and after the 6-week experimental period.

RESULTS

Mechanical massage initiated important modifications in gene expression profile. The lipid-mobilizing effect of isoproterenol was enhanced after the experimental period. Basal local blood flow and isoproterenol-induced vasodilatation were also improved.

CONCLUSION

The protocol of mechanical massage used in the study promoted noticeable changes in the expression of genes involved in metabolic pathways. The lipolytic and local adipose tissue blood flow responses initiated by isoproterenol were significantly enhanced.

2D-electrophoresis and multiplex immunoassay proteomic analysis of different body fluids and cellular components reveal known and novel markers for extended fasting

Background

Proteomic technologies applied for profiling human biofluids and blood cells are considered to reveal new biomarkers of exposure or provide insights into novel mechanisms of adaptation.

Methods

Both a non-targeted (classical 2D-electrophoresis combined with mass spectrometry) as well as a targeted proteomic approach (multiplex immunoassay) were applied to investigate how fasting for 36 h, as compared to 12 h, affects the proteome of platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva collected from ten healthy volunteers.

Results

Between-subject variability was highest in the plasma proteome and lowest in the PBMC proteome. Random Forests analysis performed on the entire dataset revealed that changes in the level of the RhoGDI2 protein in PBMC and plasma ApoA4 levels were the two most obvious biomarkers of an extended fasting. Random Forests (RF) analysis of the multiplex immunoassay data revealed leptin and MMP-3 as biomarkers for extended fasting. However, high between-subject variability may have masked the extended fasting effects in the proteome of the biofluids and blood cells.

Conclusions

Identification of significantly changed proteins in biofluids and blood cells using a non-targeted approach, together with the outcome of targeted analysis revealed both known and novel markers for a 36 h fasting period, including the cellular proteins RhoGDI2 and CLIC1, and plasma proteins ApoA4, leptin and MMP-3. The PBMC proteome exhibited the lowest between-subject variability and therefore these cells appear to represent the best biosamples for biomarker discovery in human nutrigenomics.

Metabolomic characterization of Italian sweet pepper (Capsicum annum L.) by means of HRMAS-NMR spectroscopy and multivariate analysis

HRMAS-NMR spectroscopy was used to assess the metabolic profile of sweet pepper (Capsicum Annum L.). One-dimensional and two-dimensional NMR spectra, performed directly on sample pieces of few milligrams, hence without any chemical and/or physical manipulation, allowed the assignment of several compounds. Organic acids, fatty acids, amino acids, and minor compounds such as trigonelline, C4-substituted pyridine, choline, and cinnamic derivatives were observed with a single experiment. A significant discrimination between the two sweet pepper varieties was found by using partial least-squares projections to latent structures discrimination analysis (PLS-DA). The metabolites contributing predominantly to such differentiation were sugars and organic and fatty acids. Also a partial separation according to the geographical origin was obtained always by analyzing the NMR data with PLS-DA. Some of the discriminating molecules are peculiar for pepper and contribute to define the overall commercial and organoleptic quality so that HRMAS-NMR proved to be a complementary analysis to standard tools used in food science and, in principle, can be applied to any foodstuff.

Unraveling human complexity and disease with systems biology and personalized medicine

We are all perplexed that current medical practice often appears maladroit in curing our individual illnesses or disease. However, as is often the case, a lack of understanding, tools and technologies are the root cause of such situations. Human individuality is an often-quoted term but, in the context of human biology, it is poorly understood. This is compounded when there is a need to consider the variability of human populations. In the case of the former, it is possible to quantify human complexity as determined by the 35,000 genes of the human genome, the 1-10 million proteins (including antibodies) and the 2000-3000 metabolites of the human metabolome. Human variability is much more difficult to assess, since many of the variables, such as the definition of race, are not even clearly agreed on. In order to accommodate human complexity, variability and its influence on health and disease, it is necessary to undertake a systematic approach. In the past decade, the emergence of analytical platforms and bioinformatics tools has led to the development of systems biology. Such an approach offers enormous potential in defining key pathways and networks involved in optimal human health, as well as disease onset, progression and treatment. The tools and technologies now available in systems biology analyses offer exciting opportunities to exploit the emerging areas of personalized medicine. In this article, we discuss the current status of human complexity, and how systems biology and personalized medicine can impact at the individual and population level.

Nutritional genomics era: opportunities toward a genome-tailored nutritional regimen

There is increasing evidence indicating that nutritional genomics represents a promise to improve public health. This goal will be reached by highlighting the mechanisms through which diet can reduce the risk of monogenic and common polygenic diseases. Indeed, nutrition is a very relevant environmental factor involved in the development and progression of metabolic disorders, as well as other kind of diseases. The revolutionary changes in the field of genomics have led to the development and implementation of new technologies and molecular tools. These technologies have a useful application in the nutritional sciences, since they allow a more precise and accurate analysis of biochemical alterations, in addition to filling fundamental gaps in the knowledge of nutrient-genome interactions in both health and disease. Overall, these advances will open undiscovered ways in genome-customized diets for disease prevention and therapy. This review summarizes the recent knowledge concerning this novel nutritional approach, paying attention to the human genome variations, such as single-nucleotide polymorphisms and copy number variations, gene expression and innovative molecular tools to reveal them.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Nutrigenomics and personalized nutrition: science and concept

Diet and genomes interact. Nutrition has the most important life-long environmental impact on human health. While nutrigenetics addresses how an individual’s genetic makeup predisposes for dietary susceptibility, nutrigenomics asks how nutrition influences the expression of the genome. Nutrigenomics builds on the three omics disciplines transcriptomics, proteomics and metabolomics. They are a prerequisite for nutritional systems biology, the understanding of the interaction between food components and diet with cells, organs and the whole body. Personalized nutrition is a conceptual analog to personalized medicine. While there are food products available that address requirements or preferences of specific consumer groups, these products are based on empirical consumer science rather than on nutrigenomics and nutrigenetics. The latter two build the science foundation for understanding human variability in preferences, requirements and responses to diet, and may become the future tools for consumer assessment motivated by personalized nutritional counseling for health maintenance and disease prevention.

Towards a systems level analysis of health and nutrition

Although theoretical systems analysis has been available for over half a century, the recent advent of omic high-throughput analytical platforms along with the integration of individual tools and technologies has given rise to the field of modern systems biology. Coupled with information technology, bioinformatics, knowledge management and powerful mathematical models, systems biology has opened up new vistas in our understanding of complex biological systems. Currently there are two distinct approaches that include the inductively driven computational systems biology (bottom-up approach) and the deductive data-driven top-down analysis. Such approaches offer enormous potential in the elucidation of disease as well as defining key pathways and networks involved in optimal human health and nutrition. The tools and technologies now available in systems biology analyses offer exciting opportunities to develop the emerging areas of personalized medicine and individual nutritional profiling.