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The post genomic era aims to establish a link between the phenotype and the genotype of an organism. However, it was soon revealed that environment also plays an important role in this non-linear relationship. Among the environmental factors, nutrition deals with our genetic predisposition and susceptibility toward diet. Nutrigenomics addresses how diet influences gene transcription, protein expression and metabolism. This led to the advent of Metagenomics. Metagenomics finds its application in validating the health benefits of functional foods like probiotics in particular. It provides nutrition with a tool for determining the distributions of metabolite concentrations, their composition and consequences to health. The review focuses on recent applications of metabolomics in nutrition research, the potential limitations and future prospects. It has to be added that further efforts are needed in developing better analytical tools and sophisticated softwares for the analysis of the results in metagenomics.
Metagenomics, Probiotics, Nutrigenomics, Metabolic profiling, Proteomics,
Life scientists are driven by a curiosity to unravel the layers of biological evolutionary complexity of life forms. The findings of Watson and Crick, led scientists to follow the channel from DNA to mRNA to proteins to establish the relationship between gene activity and cell function. But it was soon realized that the connection between genotype and its phenotype is not linear. There could be a change in phenotype that is heritable but does not involve a change in DNA sequence or mutation. This is because genetic traits in humans and other organisms are determined by genetic and environmental components. Apart from air, food is the only environmental matter we take into our body. Nutrition is therefore the most important life-long environmental impact on human health. Consumers throughout the world are increasingly interested in their diets and how the foods they eat influence their health. Much of this interest stems from mounting evidence that bioactive food components can have a significant influence on the quality of life and modifies the risk of a variety of disease conditions.
Dietary habits as a determinant of health and illness are based on individual variability due to genetic and non genetic regulation of cellular components. This has spurred interest in personalized nutrition. Nutrigenetics or nutritional genomics is the growing field that deals with our genetic predisposition and susceptibility towards diet. To comprehend the molecular interplay between food and health requires holistic approaches beyond genomics. Applications of tools like nutritranscriptomics, nutriproteomics and nutrimetabolomics will greatly facilitate the discovery of new biomarkers associated with dietary factors and provide personalized dietary recommendations for disease prevention (1). Current research in the area of functional foods or foods that provide some thing 'beyond nutrition' is focussing into the intestinal microbiome and obtaining genomic data from probiotic microorganisms that appear to actively promote health. Nutrigenomics and metabolomics are rapidly developing new bodies of knowledge that will change future research and practice in human nutrition. On these lines this paper aims to review the applications of metabolomics as a tool to understand the relation between probiotic food composition, consumption and its consequences in the human body.
2.0 OMIC era
The suffix 'Ome' was already used in the beginning of the last century to indicate the 'wholeness' of biological systems, such as in 'biome' or 'rhizome'. But it is in recent past that the field of 'omics' became popular in the community of nutritionists and clinicians. Thus emerged the field of functional genomics, wherein the products of gene transcription and translation were conferred a name with the suffix 'ome' to indicate their relationship with the genome which consequently ushered in the 'omic' revolution.
OMICS means a comprehensive analysis of biochemical molecular species or interactions of molecules belonging to a specific layer in a cellular system, say gene, transcripts, proteins or their metabolites (2). A schematic drawing showing the OMIC interaction among the various functional layers in a cellular system is shown in Figure 1. Multiple omic analysis is necessary as multiple functional cellular layers (mRNA, protein, metabolite layers) are interacting with each other simultaneously. Thus, the response to a total cellular system cannot be captured by a single layer or a single omic study. As a consequence a number of omic branches stemmed out, a few of which relevant to the context are explained in a simplified form by the authors in Table 1.
3.0 Nutrigenomics -make way for personalized nutrition
Food is no longer merely a means to satisfy hunger, prevent diet-deficiency diseases or provide the essential building blocks of nutrition. It has gained another dimension of being a factor for social health and well-being. During the second half of the century, knowledge of cellular and molecular biology allowed for further optimising the diet towards a balanced micro and macro-composition with the purpose of increasing general wellness (3). Nutritionists soon indicated the involvement of diet in large number of diseases and disorders like Type 2 diabetes, cardiovascular diseases and colon cancer. Functional foods which are dietary compounds with "added health benefit" became prominent in 1990's.
While designing functional foods, one has to take into consideration that genetic polymorphisms among the consumers can bring about varying responses to dietary inputs and susceptibilities to diet responsive diseases (4). The term Nutrigenetics was first coined by Dr. R. O. Brennan (5) in his book Nutrigenetics: New Concepts for Relieving Hypoglycemia. While nutrigenetics addresses how an individual's genetic makeup predisposes for dietary susceptibility, nutrigenomics addresses how nutrition influences the expression of the genome (6). The advent of omics created unprecedented opportunities for increasing our understanding of how nutrients modulate gene and protein expression and ultimately influence metabolism. In nutrigenomics, the lookout is for a biomarker based on genetic studies that can establish the link between the diet and its effect on individual physiology. In the case of cardiovascular disease, a single biomolecule (e.g. total cholesterol) as a biomarker may be insufficient to fully estimate the risk of developing the disease at an early stage. The apolipoprotein E gene could explain the inter-individual variability observed in response to LDL-cholesterol levels upon a low-fat dietary intervention. Biomarkers for nutrigenomics have also been identified in cell cycle, apoptosis and differentiation, age-related gene expression changes (7, 8). OMIC tools take into consideration inter and intra variability in the effect of diet on health. Metabolomics presents itself with promising results in the field of functional foods and their health claim validation.
Metabolomics is a diagnostic tool for metabolic classification of individuals (9). Metabolomics has been used to identify the function of genes, describe the effects of toxicological, pharmaceutical, nutritional and environmental interventions, and to build integrated databases of metabolite concentrations across human and animal populations. Metabolomics provides nutrition with an invaluable tool for determining the distributions of metabolite concentrations in humans, the relationship of these metabolite concentrations to disease, and the extent to which nutrition can modulate metabolite concentrations (10). The following passages attempts to understand the concept and applications of metabolomics in nutrition.
The effort towards metabolomics began as early as in 1970s and was then known as "quantitative estimation" like measuring sugar for diabetes or cholesterol for coronary heart diseases. The concept of the 'metabolome' was first reported as a way to quantitatively and qualitatively measure specific or defined phenotypes to assess gene function in yeast (11). This approach to reveal phenotypes for proteins active in metabolic regulation via comparative metabolomics was termed as FANCY (Functional Analysis by Co-responses in Yeast) (12). Metabolomics also finds its origin in a pioneering work carried out to discuss the spot intensities of a gene that controlled a number of metabolic genes in response to nutrient limitation in Escherichia coli (13). Metabolomics can give us an instantaneous picture of the entire physiology of the cell (14). The different terminologies used in metabolomics are defined and presented in Table 2.
Metabolites provide a great deal of information on the status of the functioning of the cell, its effects caused by changes in the genetic expression and also differences in the lifestyle and diet. Estimates for the number of metabolites present in microbial metabolomes based on genome information range from 241 for a ''simple'' bacterium such as Mycoplasma pneumoniae to 794 for the well-studied Escherichia coli (15). We shall now peruse the requirements to conduct a metabolomics experiment.
4.2 Protocol for Metabolomics Experiment:
Metabolomics deals with many endogenous and exogenous chemical entities, diverse in physicochemical characteristics and concentration, leaving the analysis of the full metabolomes an almost ''impossible task" (16, 17). This diversity caused difficulties to scientists analyzing each set of metabolites with different techniques like UV/visible absorption, fluorescence, enzyme-based tests and many more. However, such a fragmented approach was not the solution and the challenge remained of developing an improved technology for global profiling of metabolites and the integration and dissemination of data. Like the effectiveness of proteomics depends on the choice of the gel, metabolomics efficiency depends on the selection of analytical technique. There are two main approaches in Metabolomic experiments. (1) Chemometric approach where in the chemical compounds are not generally identified, only their spectral patterns and intensities are recorded, statistically compared and used to identify the relevant spectral features that distinguish sample classes (18,19). (2) Quantitative metabolomics or targeted profiling (20). Here the focus is on attempting to identify and/or quantify as many compounds in the sample as possible. Thus when genomics and proteomics give us only data, metabolomics gives us information and biological conclusions. There is a growing preference for quantitative metabolomics in many areas of food science and nutrition research (21,22). To perform a metabolomic experiment, following steps and points need to be considered.
4.2.1 Sampling and Sample Preparation:
In metabolic analysis a large number of samples are commonly analyzed. Several techniques such as freezing in liquid nitrogen, freeze clamping, acid treatment, quenching in salt containing aqueous methanol at low temperatures (23, 24) are employed for sample preparation. Sample preparation and sample introduction methods include direct injection, liquid-liquid extraction (LLE), solid-phase extraction (SPE), supercritical fluid extraction, accelerated solvent extraction, microwave-assisted extraction, protein precipitation, and membrane methods, such as dialysis or ultracentrifugation (25). As only volatile and thermally stable compounds are to be run through the Gas Chromatorgraphy-Mass Spectroscopy(GC-MS) it is mandatory for the free metabolite mixture to react with a derivatizing agent prior to running a GC-MS. A derivatizing agent is used to make an involatile substance volatile to adapt to the GC-MS mode of data gathering tool.
4.2.2 Metabolic Profiling
Metabolic Profiling includes techniques like Mass Spectrometric profiling, Electrospray ionization (ESI) with tandem mass spectrometry (MS/MS), flow injection analysis (FIA) with positive-mode ESI and LC-ESI-MS/MS. Yeast intracellular metabolites were analysed by direct injection ESI in positive mode and triple quadruple MS (26). Direct injection high-resolution mass spectrometry has been performed using time of flight mass spectrometers (TOF-MS) and Fourier transform ion cyclotron mass spectrometers (FT-ICR-MS). Flux analysis provides a true dynamic picture of the phenotype because it captures the metabolome in its functional interactions with the environment and the genome.
4.2.3 Data Export
Another key element in the metabolomics workflow is the data analysis. The complexity of metabolic profiles makes the use of efficient data mining techniques, a pre-requisite for maximizing the recovery of relevant information. There are softwares available that are supplied by the instrument manufacturers themselves of independent software developers. A universal mzXML format is becoming more widely accepted (27). Next step is the selection of a multivariate analysis tool to explore the overall statistical variance with the goal of clustering the metabolic profiles and detecting outliers. If the aim is sample classification and prior information about the sample identity is unknown, unsupervised methods such as hierarchical clustering analysis (HCA), principal component analysis (PCA), or independent component analysis (ICA) are used. On the other hand, when the sample identity is known and the aim of the study is to discover characteristic biomarkers (e.g., search for biomarkers of a disease comparing samples from healthy and diseased subjects) the principal least square (PLS) or soft-independent method of class analogy (SIMCA) can be used as well (25). For annotation of the various MS signals, four kinds of tools can be distinguished: (i) general chemical databases (e.g., PubChem) (ii) metabolic databases that deal with annotated metabolic pathways, (iii) metabolomics databases that originate from metabolomic research project in a specific field (e.g., LipidMaps in lipidomics) and (iv) mass spectral databases.
4.2.4 Data analysis and identification
A final and significant step in metabolomic studies is metabolite identification. There are chiefly three ways of doing it (i) de novo identification (2) GC MS libraries (3) LC-MS libraries (25). The Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/ kegg/) contain databases that aid in metabolic identity like databases chemical building blocks of both endogenous and exogenous metabolites (KEGG LIGAND) and molecular wiring diagrams of interaction and reaction networks (KEGG PATHWAY). The metabolomics workflow terminates with the transformation of metabolic information into a biological hypothesis that can be achieved through direct inspection of established metabolic pathways or with the help of mathematical modelling of metabolic networks (28).
4.3 Prospects of Metabolomics in nutrition:
While genomic information remains same throughout the life time, metabolic information will change with the changing metabolism patterns, be it a state of disease or ageing. This information can be exploited to meet today's challenge of devising "individualized health". Wishart (29) categorically summed up that metabolomics essentially opens the door to studying many aspects including: (1) food component analysis; (2) food quality/authenticity detection; (3) food consumption monitoring; and (4) physiological monitoring in food intervention or diet challenge studies. Metabolomics also finds its application in plant nutrigenomics where analysis of wild-type and transgenic plants demonstrated that the individual plant types each had a distinct metabolite profile (30). These findings suggested a potential use for metabolomics in the monitoring of genetically modified foods (31,32,33,34). Similary by characterising metabolite disturbances in serum, individuals with CHD could be differentiated from patients with angiographically normal coronary arteries using NMR-based methods (35). A major application of metabolite profiling is in the field of toxicology where it provides a means to rapidly determine the disturbances in metabolite populations of body fluids and tissues following the administration of various chemicals and drugs to experimental animals (36). German (37) listed the possible roles of metabolomics in nutrition as shown in Table 3. Other studies that have interlinked metabolomic and nutrition include are the effects of soy-derived proteins and soy isoflavones (38), metabolism of ethyl glycoside (39), effects of fruit and vegetable diversity on the levels of oxidative biomarkers (40), the influence of whole-grain and wheat flour diets on rats (41) and the effect of extra virgin olive oil on plasma inflammatory and oxidative stress markers (42). In the field of nutrition, probiotics are gaining great interest, especially as functional dietary components and their role in health and disease.
5.0 Metabolomics and Probiotics
The intestinal microbiota plays a role in human health and disease. The human gastrointestinal tract contains approximately ten times more prokaryotic cells than the total number of eukaryotic cells within the human body, equating to 1010-1011 CFU per gram of luminal contents at its peak within the colon, and up to half the volume of faeces (43). The colonization process of the gastrointestinal tracts begins at birth and is highly impacted by the route of that process (vaginal versus caesarean), the method of feeding (human milk versus formula), genetics, environment, diet and disease. The microbial ecosystem varies among individuals, just as it does along the length of the gastrointestinal tract. Even in individuals with an intact and normally functioning gastrointestinal tract, the commensal microbiota provide an important function by fermenting dietary fiber into usable short-chain fatty acids, thereby salvaging important nutrients that would be lost in the feces due to the inability of the human intestine to digest dietary fiber (44).
In healthy individuals, the gastrointestinal microbiota exists in a state of eubiosis. However, this dynamic equilibrium can be 'disturbed' by the stresses of modern-day living, or antimicrobial intake, with serious repercussions for the host. The failure of antibiotics to treat infection as a consequence of increased microbial resistance and the dearth of new successful antibiotics is a point of concern. These circumstances, in combination with the consumer demand for dietary supplements to maintain gastrointestinal health, have fuelled scientific research into alternative approaches. In the pursuit of a panacea between drug and diet lies the candidate "probiotics". Efforts to optimize this microbiome date back to over 2000 years ago when the Nomads in Bulgaria consumed soured milks. However, this concept officially entered the scientific literature around the turn of the 20th century when Metchnikoff linked the Bulagarian's longevity to the consumption of a fermented milk product that contained lactobacillus that are functional in colonizing the intestine. The word 'probiotic' is a compound of a Latin and Greek word meaning 'favorable to life'. The Food and Agricultural Organization (FAO) of the United Nations defines a probiotic as 'live microorganisms, which when administered in adequate amounts, confer a beneficial health effect on the host (45). The knowledge driven society of today wants scientific facts and figures to back up a health claim and so does the regulatory authorities for permitting health claims on functional foods like probiotic supplements or products. Metabolomics have found its application in this area and that have been reviewed in the following texts.
5.2 Prospects of metabolomics in probiotic study:
Sequencing of the human genome has increased our understanding of the role of genetic factors in health and disease, but it is understood now that each human being harbors many more genes than those in their own genome. These belong to commensal and probiotic intestinal microorganisms - our intestinal 'microbiome' (46). The complete sequencing of a number of probiotic organisms like Lactococcus lactis (47), bifidobacteria (48) and other lactic-acid bacteria (49) gives insight into the adhesive mechanisms of these microorganisms, which provide the basis both for populating the gut and for communicating developmental signals to specific areas and sites in the gut mucosa. What is needed in inidvidulaized health situations is an understanding of the cross-talk between the intestinal microbiota and its host that would expand our understanding of the relationship between microbiota and health.
Most of the details concerning our gut microbiota remain obscure. The factors that impact its assembly, and that define the spatial distribution of its component members, are largely unknown. In addition, the manner in which the composition and metabolic operations of this microbial 'organ' are regulated, and how its functional stability is maintained in varied environmental exposures are ill-defined. To understand the mechanistic basis of the biological differences between healthy and diseased, pathogenic and non pathogenic organisms, the semi-quantitative differences in samples as an outcome of genomic, transcriptional of proteomic analysis is not enough. There has to be a quantitative analysis and that is provided by metabolomics. Metabolomics have made it possible to measure large numbers of different metabolites, and are currently being applied to increase our understanding of the health and disease continuum (50).
A study adopted an NMR-based metabolomic approach that characterized the plasma metabolic profile of T. spiralis infected mice fed with probiotics and showed an increased energy metabolism, fat mobilization and a disruption of amino acid metabolism related to the intestinal hypercontractility (51). Such findings suggest that probiotics may be beneficial in patients with Irritable Bowel Syndrome. The same team in 2008 showed perturbation of metabolic profiles triggered by symbiotic microbiota at a 'global system' level by analyzing several metabolite pools simultaneously from different biofluids and tissues (52). Kekkonen et al. (53) concluded through metabolomic approaches that probiotic LGG intervention may lead to changes in serum global lipid profiles, as reflected in decreased glycerophosphatidylcholines, LysoGPCho and sphingomyelins as well as mainly increased triacylglycerols. The impact of our modern lifestyles, ranging from our highly synthetic cookery to use of broad-spectrum antibiotics, beginning at early stages of postnatal life have a great effect on the gut microbiota. H NMR spectroscopy was applied for studying the changes of the metabolic profiles of human faecal slurries on consumption of synbiotic foods (54). The comparison of the data indicated that the intake of the synbiotic food alters the host metabolism in a measure dependent on the initial level of lactobacilli and bifidobacteria, detected in the faecal specimens. The analysis of H NMR profiles allowed a separation of faecal samples of the subjects on the basis of the synbiotic food intake while the multivariate statistical approach used, demonstrated the potential of NMR metabolic profiles to provide biomarkers of the gut-microbial activity related to dietary supplementation of probiotics. Metabonomics has the capacity to measure the metabolic kinetic or flux of metabolites through an ecosystem at a particular point in time or over a time course. Metabonomics thus derives data on the function of the gut microbiota in situ and how it responds to different environmental stimuli e.g. substrates like prebiotics, antibiotics and other drugs and in response to disease. Such approaches are providing novel insight into the composition, function and evolution of gut microbiota.
In a recent study on sequencing of a novel probiotic strain by pyrosequencing, 523 genes were analysed by use of BLAST and KEGG metabolic database. L. helveticus DPC 5471 was the reference strain in the bioinformatic analysis which showed that 118 genes were associated with metabolism related functions (33 in carbohydrate metabolism; 34 in amino acid metabolism and protein hydrolysis; 10 in lipid metabolism; 6 in vitamins and cofactor metabolism; 21 in nucleotide salvage and synthesis; 3 in energy metabolism and 11 in glycan biosynthesis). Total of 126 genes were involved in genetic information processing (35 in replication, recombination and repair; 14 in transcription; 53 in translation; 12 were rRNA genes; 12 in sorting and degradation). About 94 genes were found to be involved in intracellular and membrane transport. Apart from these, 74 genes contributed to other biological processes (which could not be assigned a specific role). The remaining 111 genes were annotated to be transposons (55). Such data can be further put into use to improve strains for biomedical purposes and even validate the health claim of the probiotic strain. Thus metabolomics comes as a golden tool that can benefit the area of probiotics in large measures.
David Wishart, a noted scientist in the field of metabolomics, once stated that if we ask a person to stop breathing, it would not cause any change in its genome but it surely will cause a plenty of changes in the chemical metabolites in its cells, the metabolome. This analogy will surely describe the relationship of metabolomics to time and spatial dependent information of the biochemical metabolites in a living body. As is the case of other 'omic' tools, metabolomics also have some limitation to work on. These can be summed up as three grand challenges to the science of metabolomics (56). They are (1) Metabolomic technologies allow multi-parallel analysis of hundreds of metabolites. However, the majority of covered metabolic components in metabolite profiles still remain non-identified. (2) Well known key metabolites and signalling compounds are still not accessible by routine multi-parallel profiling methods. (3) All of the above tasks can only be achieved through a highly cooperative and interactive metabolomics community and thus the demand and challenge emerges to establish an efficient exchange of metabolite identifications and quantitative results. The third limitation is being looked up by Metabolomics Society who is there to promote the International growth and development of the field of metabolomics, to provide the opportunity for collaboration among researchers in metabolomics, including connections between academia, government and industry. Thus, the future of metabolomics, as a common and reliable tool in the field of food and dairy will be bright with advances in sophisticated and standardized study designs to global analysis of cellular molecules and appropriate data processing and interpretation of resulting structured data. Metabolomics is here to stay.
Conflict of Interest Statement: none declared
Financial support: none