Ch-25_Vol. 41.MDI

Advanced Proteomic Technologies in Nutraceutical...

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25 Advanced Proteomic Technologies in Nutraceutical and Functional Food Research SHRAVAN SINGH1, PRERNA AGARWAL1, D AMODAR GUPTA1, RAMAN CHAWLA1, RAJ KUMAR1, JUBILEE PURKAYASTHA2 RAJEEV VARSHNEY2 AND RAJESH ARORA2*

ABSTRACT

Hippocrates, the Father of medicine nearly 2500 years ago said that "Let food be thy medicine and medicine be thy food". Food per se and its components are life-giving, life sustaining and have a life-long impact on human health. Human beings have looked towards natural products as a major source of nutrition, since time immemorial. In addition, food is a predominant source of chemical compounds, several of which are prophylactic in nature and prevent a plethora of diseases and ailments in humans. Nutraceuticals consist of a food or part of food with medical and health benefits. Proteomics offers exciting opportunities and opens new doors towards understanding the efficacy or safety of selected food supplements by experimental confirmation of any change in the levels of proteins and their functions. This chapter gives a understanding of the advanced proteomic techniques and their applications in investigation of the effect of food on identification, expression, quantification and interaction of various biomolecules, including regulatory and posttranslationally modified proteins in biological systems. Key words:

Proteomics, Mass spectrometer, Protein microarray, Modulation of proteome, Protein-heterome, Proteininterectome, Personalized nutraceuticals

Radiation Biotechnology Group, Division of Radiation Biosciences and CBRN Defence, Institute of Nuclear Medicine and Allied Sciences, Delhi-110054, India 2 Office of Director, General - Life Sciences, DRDO Headquarters, New Delhi-110011, India * Corresponding author: E-mail: [email protected] 1

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RPMP Vol. 41—Analytical and Processing Techniques

INTRODUCTION

The term “nutraceutical” was coined from “nutrition” and “pharmaceutical” in 1989 by Stephen De Felice, MD, founder and chairman of the Foundation for Innovation in Medicine (FIM), Cranford, NJ, USA. According to De Felice, nutraceutical can be defined as “a substance which is considered as a food or its part that provides extra health benefits including the prevention and/or treatment of a disease or disorder in addition to the basic nutritional value found in foods, includes dietary supplements and functional foods”. Depending on the jurisdiction, the nutraceutical products may claim to prevent chronic disease, improve health, delay the aging process, increase life expectancy or support the structure or function of the body. Such products may range from isolated nutrients, dietary supplements and diets to genetically engineered “designer” foods, herbal products and processed foods and belong to the following under the class of nutraceuticals: a) one is dietary ingredients and b)Functional foods. A dietary supplement includes nutrients derived from food products and is intended to supplement the diet that bears or contains one or more ingredients like vitamins, minerals, herb, amino acids or a concentrate, metabolites, enzyme constituents, extracts, or combinations of these. Functional foods are designed foods which provide enriched foods close to their natural state to consumer rather than manufactured dietary supplements in liquid or capsule form. The process of making enriched food is called Nutrification. These products provide essential nutrients necessary for normal maintenance, growth, development and /or other biologically active components that impart health benefits or desirable physiological effects. Functional foods provide required amount of vitamins, fat, carbohydrates, amino acids etc. to the body. Eventually, functional food should be in their naturally-occurring form, an essential part of daily diet and regulate a biological process in the hope of preventing or controlling diseases. Nutraceuticals have received considerable interest because of their potential nutritional and therapeutic effects. The increasing concern of consumers regarding the potential toxic effects of synthetic drugs has helped the nutraceutical market to grow enormously in the past few years. The preference for the discovery and production of nutraceuticals over pharmaceuticals is well appreciated by the pharmaceutical and biotechnical companies. The use of nutraceuticals as an attempt to accomplish desirable therapeutic outcomes with reduced side effects as compared with other therapeutic agents with great monetary success drives the pharma industry. Some popular nutraceuticals include glucosamine (for arthritis), lutein (for macular degeneration), ginseng (for cold), echinacea (anti-immune), folic acid, cod liver oil capsules etc. Omega-3 eggs, omega-3 enriched yoghurts, calcium-enriched orange juices, green tea are the most popular ones to mention a few. Majority of the nutraceuticals possess multiple preventive and therapeutic benefits and are therefore, consumed by masses world


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over. Nutraceuticals have been claimed to have tremendous purported physiological benefits or provide protection against diseases and act like cardiovascular, antiobese agents, antidiabetics, anticancer agents, immune boosters, chronic inflammatory disorders and degenerative diseases. The global, US and Indian market for these products is anticipated to increase even further in the years to come. However, for each country as per the laws of the land, stringent regulations related to the safety and efficacy of these products are imperative to create a conducive and opportune environment for the sustainable growth of the nutraceutical industry. In the present scenario, awareness among the people regarding their health has increased, which has eventually raised the market for neutraceuticals. Fig. 1 explains the market of various ingredients of neutraceutical products.

Fig. 1: Neutraceutical ingredients market

The Proteome Dynamics The physiological or pathophysiological state of the cell or the tissue depends on the types of proteins expressed, their abundance within the cells and state of modification and ultimately on the dynamics of the Proteome. The interaction of food components with our body at different levels and different modifications can additionally be used as biomarkers in the diagnosis and therapy of diseases as well as biomarkers for the efficacy or safety of selected nutraceuticals. Proteomic studies offer exciting opportunities to understand the efficacy and or safety of selected food supplements by experimental confirmation of any change in the level of proteins and their functions. Fig. 2 describes the various applications of proteomics in various fields. Proteomics plays vital role in 1) diagnosis of various disorders (cancer, kidney, urological, neurological etc) 2) detection of adaptability towards environmental changes and various extreme conditions 3) in Defence for analyzing physiological performance of soldiers, biowarfare threats etc by analyzing different protein based biosensors 4) In prenatal and postnatal disease diagnosis 5) For analyzing the interaction of food components with the body.

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Fig. 2: Diverse applications of proteomics

The Proteome and Proteomics The tremendous success of genomic projects has provided invaluable insights into gene sequence and its associated functions. However, despite the remarkable accomplishments of several genome sequencing projects, resolving the complex mysteries of biological processes has been a farfetched proposition and still a little about the genome is known. While it was traditionally thought that mRNA expression levels in a cell were directly indicative of protein abundance, it later became apparent that this was not so. A more comprehensive understanding of biological function can be gained through the study of the product of gene expression-the proteins. The central role played by proteins has urged scientist to gain a deeper insight about their structure and vast array of functions. The entire complement of proteins expressed by the genome of an organism at any given point of time is known as its “proteome”. The proteome, expressed by a genome, is highly dynamic and varies with respect to cell and tissue types as well as during the different growth and developmental stages of an organism. The complexity of proteome is mainly due to the large number of post-translational modifications following gene expression, the coding of several proteins by a single gene and the dynamic nature of the proteome with time and environment. Post-translational modifications can be the result of different factors and nutritional diet can indeed be one of them. Henze et al. (2008) reported that protein-energy malnutrition can result in the change of transthyretin concentration in the blood leading to posttranslational modifications of the protein. In the post-genomic era, researchers have actively started developing newer techniques in order to harness the information provided by proteins.


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Strategies for proteome profiling can be divided into two categories: the first category, abundance-based proteomics which comprises those techniques that allow for quantization of protein expression, thereby providing an understanding of how each cell responds to changes in its cellular milieu. The second category-functional proteomics involves the identification and characterization of those proteins whose expression levels have been modified by these environmental factors, indicating that they play a key role in the regulation of cellular activity. In recent years, there have been rapid advancements in proteomic techniques from classical gelbased approaches to high throughput gel free system (Fig. 3).

Fig. 3: Discovery workflow in mass spectrometry-based proteomics

Protein microarrays and mass spectrometry-based proteomic studies have witnessed an upsurge to allow for multiplexed functional studies and simpler protein identification techniques. Various protein separation and detection methods have also seen significant improvements, as is evident from the miniaturization, automation, improved sensitivity and selectivity of the assays. A broad spectrum of extremely innovative techniques is on the rise to satisfy the demand for specific and high throughput proteomic studies. Among the potential approaches for studying the proteome on a large-scale, chromatography combined with mass spectrometry (MS) has become a leading method other than techniques such as one- and two-dimensional gel electrophoresis and antibody-based assays such as protein microarrays (Moore and Weeks 2011; Rabilloud, 2002 #533; Rabilloud, 2002).

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Protein and Peptide Separation Gel-based Techniques The classical two dimensional gel electrophoresis (2-DE) is one of the most widely used and accepted technique to obtain data on protein expression levels under various environmental conditions. This technique involves the separation of proteins based on charge in first dimension (isoelectric focousing; IEF) and molecular weight in the second dimension, orthogonal direction (SDS-PAGE). Several thousand proteins have been successfully resolved on a single gel using this fairly routine technique. These gels can also provide additional information such as isoelectric point (pi), molecular weight and quantity of proteins. However, low sensitivity towards the more easily soluble proteins, low degree of automation and poor reproducibility of 2DE have made the high-throughput quantization of proteins considerable challenging. Consistent improvement in protein detection methods over the years has progressively enabled the detection of as little as 1ng of protein. Gel-based protein separation methods have the advantage of physically preserving the protein context and generating real protein images. Classical two-dimensional electrophoresis technologies capable of analyzing the protein content of cells and tissues as well as body fluids such as plasma or urine in combination with mass spectrometry (MS) are being applied extensively by researchers in the field today. Despite several introduced improvements, two dimensional electrophoresis will probably remain a rather low-throughput approach that requires a relatively large amount of sample and labor intensive. The most advanced method for 2D protein separations is differential imaging gel electrophoresis (DIGE) (Sellers et al., 2007), which relies on multiplexed staining (Fig. 4). The problem of comparison of images across gels has been overcome by Modern difference in gel electrophoresis (DIGE) where cyanin dye, Cy3 and Cy5 are used for differential labeling of the same protein from different samples. These dyes are designed to be matched with charge and size so that charged states of the labeled proteins are maintained and it allows precise co-migration of differentially labeled protein species within the same 2-D gel. However, due to spectrally distinct flurophores of Cy2 and Cy3 it allows detection of the signal from one sample without appreciable contribution from the other. Cy2 dye is used to label an internal standard, which consists of a pooled sample comprising of equal amounts of control and treatment samples. DIGE allows the analysis of two or more protein samples simultaneously on a single two dimensional gel, which is not possible with other 2DE techniques. The gold standard for 2D-rooted proteomics is quantification by differential imaging gel electrophoresis, i.e., by differential staining of the separated protein spots and image analysis (Fig. 4). Relative protein abundance of samples can be readily obtained by simple comparison of their fluorescence intensities using a fluorescence gel scanner. One of the drawback of DIGE is the hydrophobicity of the


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Fig. 4: Schematic illustration of DIGE

cyanine dyes, which covalently binds the amino group of surface-exposed lysine residue in proteins leading to decreased solubility of the protein of interest causing it to precipitate prior to electrophoresis. This problem has been addressed by adopting minimal labeling (1-5% of total lysine residue) and by the development of cyanin dyes which selectively label only free cysteine residues in protein. In addition to fluorescent labels, radioactive isotopes have also been employed for labeling procedures and subsequent protein detection and identification in gel based proteomics. Isotope labelling techniques offer a less destructive means for the protein of interest without compromising on the detection sensitivity. It provides a broader dynamic detection range and allows the detection of up to 2ng of protein sample. Protein and Peptide Separation–LC Based Techniques One of the main critical factors for the success of structural or functional protein assay is the availability of good quality purified proteins. Obtaining

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purified proteins can often be a daunting task due to setbacks such as poor expression, insolubility and improper folding in heterogeneous host systems. To overcome the challenges posed in obtaining pure protein, several protein expression systems have been developed in recent years, which have resulted in improvements in the achievement of key features to a large extent e.g., protein yield, proper folding and post-translational modifications and reduced cost. Escherichia coli is one of the simplest and most commonly used expression systems due to ease of use and low cost, but are often unsuitable for the expression of eukaryotic proteins owing to the lack of eukaryotic post-translational modifications and low protein solubility. These drawbacks have been overcome to some extent by the use of Saccharomyces cerevisiae, which has been found to be more suitable for such eukaryotic protein expression. Protein purification utilizing liquid chromatography and electrophoresis has resulted in effective resolution and identification of digested peptide of proteome. Techniques that have been widely employed have resulted in resolutions involving several thousands of proteins/peptides and include high performance liquid chromatography (HPLC) and capillary electrophoresis (CE). Amongst the various HPLC techniques available, ion exchange, strong cation exchange (SCX), Reverse phase (RP), size exclusion and hydrophobic interaction are the major ones. On the other hand, capillary zone, isoelectric focusing (IEF) and affinity electrophoresis are the different types of capillary electrophoresis techniques that are commonly used. High-throughput purification has been made possible through the use of affinity tags, which must bind strongly but reversibly to the protein of interest. Separation of complex peptide mixture is achieved by manipulating either the mobile phase or stationary phase properties since fractionation is based on the interactions of peptides with these phases. Howev er, it is w ell kn own th at no sin gle ch romatogr aph ic or electrophoretic purification technique is sufficient to resolve complex mixture of peptides. A combination of two or more separation procedures, which must be orthogonal and compatible with each other, are therefore usually employed to improve the overall resolution of complex proteome digest. One successful combination method developed and widely used is the multidimensional protein identification technology (MudPIT), which makes use of strong cation exchange chromatography (SCX) in one dimension and reverse phase HPLC in the other dimension (Fig. 3). Combination modalities su ch as RP-HPLC w ith capillary zone electrophoresis (CZE), affinity and RP chromatography, micellarelectrokinetic chromatography (MEKC) with affinity chromatography and several other have been developed. However, each method has its own advantages as well as disadvantages. The ultimate objective of these separation protocols is to reduce the sample complexity in order to facilitate efficient and accurate identification and quantification by MS. Though there have been rapid advancements in MS as well, the best dynamic range measurement capabilities are still a few orders of


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magnitude lower than the range of protein concentration present in a serum sample. A comprehensive characterization of the proteome requires that the number of co-eluting peptides be reduced to a minimum before introduction in to the spectrometer. These workflows run under the terms MudPIT (multidimensional protein identification technology) or shotgun proteomics (Swanson and Washburn, 2005). One major difference compared with gel approaches is that the protein content is physically sacrificed by upstream tryptic digestion of the protein mixture and subsequent separation and analysis at the peptide level. The protein content is then reconstructed in silico by reassigning the peptide identification to the same parent protein. There are a number of modifications in techniques that researchers apply these days, and a number of new techniques keep getting invented with improved resolution capabilities. Mass Spectrometry (MS) Over the years, mass spectrometry, coupled with various protein separation technologies has emerged as one of the most powerful and widely used tools for varied applications including proteomics studies. Any proteomic study, be it in a nutritional or other framework, commences with a protein survey of what can be seen in a given sample and condition. Large-scale identification of protein requires the application of mass spectroscopy. High sensitivity analysis with low sample consumption and high protein sequence coverage is the principal challenge of analytical techniques like MS. Mass spectrometers can identify proteins and peptides by determination of their exact masses and generating information on the amino acid sequences. The basic components of mass spectrometer include an ionization source, a mass analyzer and an ion detector (Fig. 5).

Fig. 5: Data analysis by mass spectrometry

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The most commonly used ionization methods in proteomics for analysis of large biomolecules like proteins and peptides includes electrospray ionization (ESI) and matrixassisted laser desorption/ionization (MALDI). While MALDI requires the sample of interest to be in a crystalline state, ESI can directly ionize molecule in solution, preserving their integrity. The generated ions are then separated by the analyzer based on their mass to charge (m/z) ratio and directed into the detector present in either electric or magnetic fields. The most popular analyzers widely used in proteomics are time-of-flight (TOF) tubes, ion traps, triple-quadruple (triple-Q), Orbitrap, and Fourier-transform ion cyclotron resonance (FT-ICR) with their specific advantages which are: high sensitivity and multiple-stage fragmentation for ion traps; high selectivity for triple-Q; high sensitivity, mass range and speed for TOF; and very high mass accuracy and resolution for orbitrap and FT-ICR (Makarov et al., 2006; Nielsen et al., 2005). Another innovative and robust platform that holds great potential for proteomics investigations is the use of micro-fludic chips coupled with MS. These microfludic devices manipulate the level of fluids at various levels with the help of micrometer sized channel and are emerging as an excellent tool for highly sensitive and simultaneous analysis of the complex proteome. Current technologies for proteome analysis are labor intensive and time consuming. Microfludics promises to play an essential role in sample pretreatment steps such as enzymatic digestion, separation and sample clean up (removal of salts or buffers) prior to MS analysis. It is advantageous in reduced sample and reagent consumption, high throughput and parallel analysis, automation of sample processing, increased reaction speed and easy portability due to miniaturization. Efficient interfacing technique between the microfludic chip and mass spectrometer is the need of the hour, in order to allow these devices to be easily adopted by researchers. Since ESI and MALDI are the most common ionization techniques, most interfaces developed till date has focused on these approaches. Online coupling of microfludic devices with MALDI is a considerable challenge but holds enormous potential for high throughput studies by facilitating direct acquisition of sample information. A fully integrated microfludic platform i.e., a proteomic chip, capable of combining multiple functions on the same chip through automated analysis to provide a complete proteome analysis is the ultimate aim of this technology. The major remaining analytical challenge is not mass accuracy (down to subparts per million), mass resolution (up to several hundred thousand), or absolute sensitivity (down to a picomolar range), but the dynamic range of protein concentrations (e.g., estimated 1012 in human blood) (Jacobs et al., 2005). Absolute quantitative information can be obtained by spiking defined amounts of stable isotope-labeled peptides or entire proteins into the sample of interest and comparing the corresponding mass signals of the sample peptides with those of these internal standards (Brun et al., 2009). The targeted, multiplexed peptide-level version of such a strategy is called AQUA (absolute quantification) (Gerber et al., 2003). The protein level variant is


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described as QConCat (artificial, expressed proteins consisting of stable isotope-coded peptides representing the proteins to be quantified and co processed with the sample) (Pratt et al., 2006) or PSAQ (protein standard absolute quantification, i.e., spiking of the labeled protein of interest and co processing with the sample) (Dupuis et al., 2008). Alternative to differential imaging gel electrophoresis and compatible with online shotgun LC-MS/MS workflows, stable isotopes (e.g., 13C, 2H, or 15N label) can be introduced into the amino acid side chains, entire protein or peptide level by introducing a differential isotopic signature so that the conditions can be quantitatively compared at the MS level. The tag can be introduced metabolically by feeding cells or even small animals (mice, rats) with isotopes labeled essential amino acids and the technique is called “stable isotope labeling of amino acids in cell culture (SILAC)” (de Godoy et al., 2006; Gygi et al., 1999), isobaric tag for relative and absolute quantization (iTRAQ), (Ross et al., 2004), tandem mass tag (TMT) (Thompson et al., 2003). The quantification readout can be obtained at the MS (ICAT, SILAC, AniBAL) or MS/MS (iTRAQ, TMT) level. On the other hand, ‘label free’ approaches have been developed to maximize sample integrity and compare samples directly as they are. They deploy spectral counting of peptide assignments for semi-quantitative analysis or compare the peak intensities of the very same peptide by overlaying LC-MS runs of control and case samples (Mueller et al., 2008; Wong et al., 2008). Protein Arrays The success of DNA microarray for gene expression profiling has gradually led to the increased adoption of protein microarrays for simultaneous analysis of hundreds to thousands of proteins (Haab, 2001). Protein microarrays consist of small quantities of immobilized proteins printed on to solid supports such as glass slides and have exhibited immense potential for classical and functional proteome analysis. The lack of a PCR equivalent amplification process for proteins, the wide range of hybridization chemistry and the need to maintain structural integrity for protein function studies, make the process of construction of protein microarrays a considerably greater challenge compared to DNA microarrays. The efforts required are however, compensated since these microarrays enable researchers to analyze hundreds to thousands of proteins simultaneously with the economical use of sample and reagents (Paweletz et al., 2001). Protein microarrays are broadly classified as abundance based and function based microarrays (Fig. 6). Abundance based microarrays measure bimolecular abundance with the help of analyte-specific reagents like antibodies or aptamers, while function based microarrays investigate biochemical properties and functions of proteins printed by cell-based or cell free technologies in high throughput on the array surface. Arrays can be generated such that either the capture

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Fig. 6: Protein microarray

molecule is printed onto its surface and probed by the test lysate sample (capture arrays) or so that small volumes of the experimental sample are immobilized on the array and then probed by specific detection reagents (reverse phase protein arrays) (Yang et al., 2011). Detection of specific antigen antibody interactions can be carried out either by direct labeling of the target proteins with fluorescent tags or by a sandwich assay in which a labeled secondary antibody recognizing a different epitope of the same analyte is added (Fig. 6). There has been growing interest in cell free expression system for printing protein micro array due to the technical challenges presented by traditional cell based methods. These include difficulties such as protein expression in heterologous hosts, purification, maintenance of protein folding and functionality as well as the time and labor involved. Shelf life and stability of proteins obtained by these cell based methods are other concerns that have motivated researchers to look for alternative techniques. Cell free systems suitably eliminate several drawbacks such as the need to clone and express proteins in host cells, the purification process and the necessity for suitable storage conditions to avoid loss of protein function. They directly make use of DNA templates for in vitro protein synthesis in the presence of crude cell lysate like E. coli S30, Rabbit reticulocyte lysate and wheat germ extract. The synthesized proteins get captured on to the array surface by means of an immobilized tag capturing agent. These are then detected either by means of fluorescent tags, secondary antibodies or more recently, using label free detection techniques. Cell free expression facilitates the parallel synthesis of thousands of proteins in a single reaction process, thereby providing an excellent platform for high throughput studies. An adjustable environment for monitoring proper protein folding, disulphide bond formation and addition of suitable labelling agents are some of the supplementary benefits due to the open nature of the system. High density protein arrays


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have also been successfully generated by the nucleic acid programmable protein Array (NAPPA) technique and multiple spotting technique (MIST). Protein microaarays provide a versatile platform and are increasingly being used for several applications such as biomarker identification, nutraceutical function analysis, protein–protein interaction studies and enzyme assays (Hu et al., 2009). Protein Databases and Processing The advancement and availability of technology in recent times has led to large explosion of genomic, transcriptomic and proteomic data in the public domain. Apart from the ‘wet laboratory’ equipment to generate large proteomic datasets, it takes sophisticated software to acquire, store, retrieve, process, validate, and interpret these data and to eventually transform them into useful biological information. One of the key components to manage, analyze and manipulate these large sets of biological data includes creation of database allowing storage, management and easy access. Protein databases provide information related to protein characterization, domain and families, sequences, biophysical and catalytic properties, function and applications, identification and quantification, annotations, expression and profiling, 2-D/3-D structure and homology models, protein- protein and protein ligand interactions, pathways and networks mutations and disease associations, post-translational modification, structure-activity relationships, structure predictions and sequence analysis tools. The various type of protein database includes: sequence databases, structure databases, databases of post-translational modifications, pathway databases, data repositories and custom databases (e.g. for proteogenomics). These databases help in extracting relevant information from large data sets and understanding the statistical significance of protein identification results. The best case scenario in terms of identification would be to use only the mass information of a peptide as a unique signature. Such approaches have been described by (Conrads et al., 2000) as the accurate mass tag approach. In this technique, identification is based only on the peptide mass. High resolution instruments are needed to provide subpart-per-million mass accuracy (0.1 ppm). But even with such accuracy, high levels of confidence in protein identifications can be achieved only in small eukaryotic systems like yeast. Proteins can furthermore be identified with good throughput (Pappin, 1997) and high sensitivity (Schuerenberg et al., 2000) based on the set of measured proteolytic peptide masses. This process is known as “peptide mass fingerprinting”. The experimental mass profile is matched against those generated in silico from the protein sequences in the database using the same enzyme cleavage sites. The proteins are then ranked according to the number of peptide masses matching their sequence within a certain mass error tolerance. In contrast, MS/MS provides access to sequence data, which enables more

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confident peptide identifications. In an MS/MS experiment, a precursor ion with a known mass is selected from the previous MS scan and is isolated for further collision to produce daughter ions with unique signature. This process is described as peptide mass sequencing as opposite to peptide mass fingerprinting. Identification of proteins using MS/MS data is currently performed using three different approaches: i) peptide sequence tagging (Mann and Wilm, 1994), ii) cross-correlation method (Eng et al., 1994), iii) probability-based matching. Although peptide and protein identification and database search programs such as Mascot (Perkins et al., 1999) and Sequest (Eng et al., 1994) are well established, new software infrastructures for data processing and validation have been built such as the SBEAMS architecture housing the Trans-Proteomic Pipeline and microarray modules that cover gene and protein expressions. The Peptide Prophet (Keller et al., 2002) and Protein Prophet (Nesvizhskii et al., 2003) modules in the Trans-Proteomic Pipeline are based on a robust and accurate statistical model to assess the validity of peptide identifications made by MS/MS and database search. The idea behind such resources is to provide the researcher with means to assess the quality of the data in a datasetdependent manner and to control the tradeoff between false positives (specificity) and false negatives (sensitivity) (Urfer et al., 2006). The second strategy to elucidate the false-positive/false-negative tradeoff relies on a database search using a target-decoy database (Elias and Gygi, 2007): first, an appropriate ‘target’ protein sequence database is generated and then a ‘decoy’ database preserving the general composition of the target database, while minimizing the number of peptide sequences in common (generally done by reversing the target protein sequence) is created. The search is done against the target and the composite database. Assuming that no correct peptides are found in the target and decoy entities and that incorrect assignments from target or decoy sequences are equally good, one can estimate the total number of false positives. The development of protein databases is important for discovery of signature candidates for biomarkers, drug targets, therapeutics and mapping of protein interaction networks. The development of sequence and structure database started in the early days of the postgenomic era. With the generation of specialized data other than sequence data, there was a need to develop databases to store post-translational modification as they play a key role in cellular communication and signaling. Dissecting the system view of the cell requires more global studies, which focus on cascade of events in the celleventually a signaling or metabolic pathway. This had led to accumulation of pathway data in the public domain. Several databases have been developed by various groups that focus on both metabolic and signaling pathways. One of the biggest challenges in the development of database is to assemble the vast amount of data in the published literature which is done in two major ways: i) to use text mining algorithms to extract information, which is often known for its high error rate. ii) to manually read the published literature


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and extract the information that is very cumbersome and time consuming task. The ideal way to tackle this issue to encourage the data producers for contributing to public data repository, which facilitate the data submission with due credit to the data producers and also makes this information accessible in the public domain. There are many instances where there is a need to collect data from multiple databases and create a custom database that fits the current need. This often requires some bioinformatics skills as this kind of software is not available. One such instance is in the creation of database for proteogenomics, where the creation of database for MS/MS interpretation is completely based on the species of the study and the experimental design. Overall, databases play a crucial role in biomedical research both by providing a structured way of storing data and also making it accessible to the community, which is very essential for an integrated systems biology research. APPLICATION OF PROTEOMICS IN NUTRACEUTICAL AND FUNCTIONAL FOOD RESEARCH

Proteomics has emerged as a revolutionary discovery tool in nutraceutical and drug research (Petricoin et al., 2002). Its multiple areas have been greatly advanced by the use of this powerful advance technology. Depending on the proteomic technology used, these analytical approaches can provide real-time kinetic information and mass spectrometry- based mass and sequence characterization (Schweigert, 2005; Tolson et al., 2004). Surprisingly, there have been relatively few studies in nutritional proteomics published so far, and most of these have involved the use of rodent models (tom Dieck et al., 2005) or human cells in culture (Fuchs et al., 2005; Herzog et al., 2004a; Wenzel et al., 2004). Applications of advance proteomic technologies in nutraceutical and functional food intervention are summarized in Fig. 7. There is a need for further studies like absorption, distribution, metabolisms, excretion and toxicity (ADMET) of nutraceuticals, modulation of protein expression and its profiling, modulation of proteinsheterome and interectome (characterization of structural and functional properties of the proteins). Requirements of personalized nutraceutical for growth and health helps in establishing molecular mechanisms for the roles of nutritional ingredient (nutraceutical) and other dietary factors in growth, reproduction and health. Identification and Characterization of Nutraceutical Dietary Peptides and Proteins The composition and characteristics of dietary proteins are major determinants of their nutritional values and potential pathogenic effects.

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Fig. 7: Application of advance proteomics in nutraceutical and functional food research

Traditionally, dietary proteins were determined primarily using the Kjeldahl procedure and acid hydrolysis, which do not yield information about true protein, amino acid sequence, or some amino acids (e.g., glutamine, asparagine, and tryptophan). Such invaluable data can be readily provided from proteomics analysis. Notably, a recent study involving 2DPAGEMALDI-MS revealed that the different effects of dietary soy isolates on humans (e.g., plasma lipids) in U.S. and European clinical studies are related to the differences in composition of the soy proteins used (e.g., 7S globulin products and intact 11S globulin subunits) (Gianazza et al., 2003). In addition, polymorphisms of dietary proteins (e.g., -lactoglobulins A and B in cow’s milk) may explain the formation of subtly but functionally distinct peptides that have remarkably different allergenicity in humans (Corthesy-Theulaz et al., 2005). Absorbtion, Distribution, Metabolisms, Excretion and Toxicity (ADMET) of Nutraceuticals Other than in the field of nutritional science, many pharmacological studies do address the interaction of small molecules such as drugs with plasma proteins as a part of their ADMET (absorption- distribution- metabolismexcretion- toxicology) evaluation. The reason for this is that protein binding (small-molecule protein interactions) in plasma greatly determines the metabolic fate of a given drug (Jenkins and Shapiro, 2003). More importantly, in pharmacology small molecules acting as antagonists to protein function are promising new drug candidates. Proteins targeted by these small molecule antagonists fall into three classes: enzymes, cellular


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receptors and proteins involved in protein-protein interactions (Korc, 2003; Meng et al., 2002; Pagliaro et al., 2004). The nutritional values of dietary nutrients and other factors depend on their digestion and absorption in the gastrointestinal tract. However, knowledge about digestive enzymes and epithelial-cell nutrient transporters remains incomplete and is critical for designing new ways to enhance the entry of low-molecular-weight nutrients into the portal vein. A recent proteomic analysis of the rat smallintestinal proteome indicates the presence of previously unrecognized proteins involved in intestinal molecular chaperones, cytoskeleton plasticity, and vitamin transporters, such as gastrotropin, filamin-a, and vitamin D– binding protein precursor (Tosco et al., 2005). In addition, a MALDI-TOF MS study revealed the presence of 80 proteins in the myenteric plexuslongitudinal muscle layers of each of the rat intestinal segments (jejunum, ileum and colon); these proteins may play a novel role in intestinal function (including digestion and absorption) (Marvin-Guy et al., 2005). Moreover, the ESI-MS-MS technology was used to identify up-regulation of 25 proteins and down-regulation of 18 proteins in intestinal epithelial cells in response to endotoxin or pathogenic bacteria (Alpert et al., 2005), thereby providing an explanation for impaired digestion and absorption of dietary nutrients under inflammatory conditions. There is growing interest in the role of proteomics in advancing our knowledge about nutrient metabolism and its regulation. Using MALDITOF-MS (Yan et al., 2004), reported major differences in cardiac glycolytic or mitochondrial pathways between young and aging monkeys or between males and females, which helps explain an aging-associated gender difference in the risk of cardiovascular disease. Also, proteomics identified up- and down-regulated proteins (including vimentin and glucose-regulated protein (Anderson and Hunter, 2006) in insulin-treated adipocytes (Bluher et al., 2004) and transcription factors in mammalian cells (Forde and McCutchen-Maloney, 2002). Further, the levels of hepatic enzymes involved in glycolysis, gluconeogenesis, fatty acid oxidation and amino acid metabolism vary greatly between lean and obese diabetic mice, which can be normalized with peroxisome proliferatory-activated receptor activators (Edvardsson et al., 2003). The findings from these studies greatly expand our knowledge about the regulatory networks for nutrient metabolism. Modulation of Protein Expression and Its Profiling The human genome consists of Ca. 30,000 genes, which may generate 100,000 proteins due to mRNA splice variants, protein processing, and posttranslational modifications. Protein profiles and characteristics in physiological fluids are excellent indicators of nutritional status and protein post-translational modifications. Protein profiles in plasma/serum can be used as biomarkers to evaluate the adequacy of specific nutraceutical and functional foods, diagnose disease, and monitor therapeutic response as

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the blood pool is readily accessible for noninvasive sampling. There is evidence showing that nutraceutical and nutritional ingredient alters plasma and organ proteomes in humans and animals. Nutrient Deficiencies Interestingly, dietary deficiency of copper (Gianazza et al., 2003), iron (Tosco et al., 2005), folate (Chanson et al., 2005), or zinc (tom Dieck et al., 2005) markedly influences expression of intestinal and hepatic proteins related to cellular redox regulation, lipid metabolism, protein phosphorylation, DNA synthesis, and nutrient transporters. The studies also investigated the consequences of nutrient deficiencies by force-feeding rats with a zincdeficient diet and analyzing the hepatic transcriptome, proteome and lipidome. By combining proteomics, analysis of prime metabolic pathways of hepatic glucose and lipid metabolism and their changes in zinc deficiency the reasons were identified that cause liver lipid accumulation and hepatic inflammation (tom Dieck et al., 2005). In the same context, Fong et al. showed that alleviation of zinc deficiency by zinc supplementation resulted in 80% reduction of cyclo-oxygenase–2 mRNA, a key enzyme involved in inflammation (Fong et al., 2005). However, a few recent examples will serve to illustrate the potential of the technique. By combining microarray and proteome analysis techniques to assess the hepatic responses to experimental Zn deficiency in a rat model, a unique pattern of genes/proteins was identified that indicated down-regulation of all pathways involved in glucose utilizations as well as fatty acid oxidation, but increased mRNA and protein levels of enzymes and transporters required for de novo fatty acid and triacylglycerol synthesis (tom Dieck et al., 2005) (tom Dieck et al., 2005). These findings correlated well with an increased liver fat content (tom Dieck et al., 2005) and impaired fatty acid metabolism frequently observed in Zn deficiency (tom Dieck et al., 2005). Gianazza et al. used 2D gel electrophoresis to investigate the effect of cobalamin deficiency on the proteome of cerebrospinal fluid in two rat models (Gianazza et al., 2003). In gastrectomized animals there was an increase in total protein in cerebrospinal fluid, which reached a peak 4 months after surgery. The 4month peak in protein concentration was associated with a specific increase in 1-antitrypsin, and de novo appearance of thiostatin and hapto globin-b, but all these changes were corrected by supplementation with cobalamin. In addition, inadequate provision of dietary cyanocobalamin induces profound changes in the proteome of the rat cerebrospinal fluid, thus linking cyanocobalamin with neurological functions (Gianazza et al., 2003). Results of a recent MALDI-TOF-MS analysis indicated that glutamine alters the proteome of human intestinal cells, including the proteins that regulate amino acid, lipid, and vitamin A metabolism (Lenaerts et al., 2006). More recently, Linke et al., described the application of proteomics to plasma samples from rats with differing retinol status (Linke et al., 2004). Plasma


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samples were analyzed directly using SELDI-TOF-MS. Pre-fractionation of the samples by anion-exchange chromatography, using 96-well filter plates, was shown to markedly increase the total number of peptides and proteins detectable by this method. Three proteins with molecular mass between 10,000 and 20,000 were shown to be present at reduced concentration in the plasma of retinol-deficient rats, and the authors concluded that their approach provided a promising means of detecting changes in nutritional status at the whole-body level. ATHEROSCLEROTIC AND ATHEROGENIC ACTIVITIES

Putative antiatherosclerotic activities of genistein in endothelial cells stressed with oxidized LDL or homocysteine have also been explored by use of proteome analysis (Fuchs et al., 2005). As mentioned earlier, samples of body fluids are relatively easy to process for proteomic analysis because, unlike complex solid tissues, the separation of cellular fractions is usually not necessary. Notably, proteomic studies determined that dietary supplementation with genistein (the major isoflavone of soy) increases the expression of GTP cyclohydrolase-I [a key protein related to nitric oxide synthesis (Shi et al., 2004) in the rat mammary gland in association with a reduction in cell proliferation and susceptibility to cancer (Rowell et al., 2005; Shi et al., 2004). These studies helped in establishing molecular mechanisms for the roles of nutrients and other dietary factors in growth, reproduction and health. Altered protein expression levels of fructose-induced fatty liver in hamsters have been studied (Zhang et al., 2008). High fructose consumption is associated with the development of fatty liver and dyslipidemia. Matrixassisted laser desorption ionization–MS-based proteomic analysis of the liver tissue from those hamsters revealed a number of proteins whose expression levels were altered more than two-fold. The identified proteins have been grouped into categories such as fatty acid metabolism, cholesterol and triacylglycerol metabolism, molecular chaperones, enzymes in fructose catabolism and proteins with housekeeping functions. Park et al. (2004) recently described the use of proteomic techniques to explore the impact of atherogenic diets on hepatic protein expression in C57BL/6J mice (B6, atherosclerosis-susceptible strain) and C3H/HeJ mice (C3H, atherosclerosisresistant strain). Both strains were fed with atherogenic diets and each showed a different pattern of both plasma lipids and intracellular lipid droplets. Proteomic analysis of liver from the two strains revealed a complex response. Overall, a total of thirty hepatic proteins were significantly changed by exposure to the diets and of these fourteen including carbonic anhydrase III, senescence marker protein 30 and Se-binding protein 2 were differentially changed only in case of B6 mice. The remaining sixteen proteins, including glutathione S-transferase, Apo E and chaperonin protein, were changed in both strains. Another twenty-eight proteins were differentially expressed in the livers of both B6 and C3H mice, regardless of diet feeding conditions.

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The authors concluded that the proteomic approach had revealed clear differences in expression of both oxidative stress proteins and lipid metabolism-related proteins between the two strains in response to the atherogenic diets, and that these differences could account for their differing susceptibility to atherogenesis. Proteomics analysis also showed that the levels of hepatic lipid-metabolic enzymes and prooxidative proteins are increased in mice fed a high-fat diet (Park et al., 2004) and hepatic protein profiles are altered in rainbow trout in response to dietary intake of proteins (Martin et al., 2003). Cancer Proteomics has contributed magnificently in the field of cancer. Combining gene and protein expression profiling and analysis to address biomarkers for protection against cancer (Breikers et al., 2006) identified 30 proteins differentially expressed in the colonic mucosa of healthy mice with increased vegetable intake. Six proteins identified with altered expression levels could be associated with a protective role in colorectal cancer. Tan et al. (2002) assessed the sodium butyrate effects on growth inhibition of human HT-29 cancer cells in vitro by employing a 2DMS–based proteomic strategy. Butyrate treatment altered the expression of various proteins, in particular those of the ubiquitin–proteasome pathway, a result suggesting that proteolysis could be an important mechanism by which butyrate regulates key proteins in the control of the cell cycle, apoptosis, and differentiation. Further combining gene and protein expression profiling in colonic cancer cells, Herzog et al. (2008) identified flavonoids, present in a variety of fruits and vegetables, as a potent apoptosis inducer in human cancerous cells. Aalinkeel et al evaluated the effect(s) of the flavonoid quercetin on normal and malignant prostate cells and identified possible target(s) of quercetin action. Their findings demonstrated that quercetin treatment of prostate cancer cells resulted in decreased cell proliferation and viability. Quercetin also promoted cancer cell apoptosis by down regulating the levels of heat shock protein-90, but exerted no quantifiable effect on normal prostate epithelial cells. Proteome analysis was also applied to identify the target proteins of flavonoid action in colon cancer cells and led to the identification of a new mechanism by which flavones selectively induce apoptosis in transformed cells (Herzog et al., 2004b; Wenzel et al., 2004). Modulation of Protein-Heterome Nutritional intervention studies have looked at gene/protein abundance changes in response to a nutritional intervention. However, several food components may not only alter gene and protein expression, but also target post-translational modifications (Davis and Milner, 2004). Protein


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microheterogeneity can be caused by simple proteolysis or by various sophisticated post-translational modifications. These modifications range from the wide spread, such as glycosylation, phosphorylation, ubiquitination and methylation to the less frequent ones such as glutathioylation, hydroxylation, sulfation and transglutamination. This aspect of modification has recently been summarized under the term heteromics (Schweigert, 2005). Even a small difference between two proteins for instance, a single amino acid modification oftenly affects the function of protein. Such functions may include secretions, plasma transport, receptor binding, degradation and excretion, but may also influence protein-protein complex formation as well. Dietary components such as diallyl disulfide (compound found in processed garlic) have been shown to exert post-translational modifications in proteins. The exposure of cells to DADS did not affect the protein concentration of extracellular signal-regulated kinase (ERK) but its phosphorylation resulted in a modification of its activity and leading to cell cycle arrest (Knowles and Milner, 2003; Nesvizhskii et al., 2003). Thus, post-translational modification driven conformational changes and folding of protein can create a dynamic combinational library of properties that rapidly responds to physiological or Nutraceutical intervention (Davis and Milner, 2004; Hancock, 2002; Mann and Wilm, 1994). With regard to the interaction of single nutrients in a specific diet with food proteins, noncovalent and covalent modifications have been observed for the interaction of selected secondary plant products (e.g., glucosinolate breakdown products, phenolic compounds) with a series of proteins (Rawel et al., 2005). For example, both chymotrypsin and amylase can be modified by covalent attachment of phenolic and related components such as caffeic acid, chlorogenic acid, ferulic acid, gallic acid, quinic acid and benzoquinone etc. Beside changes in protein structure and conformation additional functional consequences were observed with respect to modifications induced by dietary components such as reduction of nutritional protein quality, enzymatic activity in cases of modified enzymes and masking of the biological properties of the reacting small nutrients (e.g., antioxidant potential of the phenolic compounds) (Rawel et al., 2005). This strongly supports the concept that conformational changes in proteins can be induced by the interaction of nutrients with specific proteins. Other studies show that the post-translational regulation of proteins by dietary components involves the modification of the thiol groups of selected proteins (DinkovaKostova et al., 2002). An experiment with respect to this question shows that oleocanthal (component of olive oil) acts as a natural anti-inflammatory compound by inhibiting cyclooxygenase enzymes in the prostaglandinbiosynthesis pathway in a similar way to the pharmacological component ibuprofen. Another example includes the modification of thiol groups in the cytoplasmic protein Keap 1, affecting its binding to Nrf2 protein (transcriptional regulator (Dinkova-Kostova et al., 2002). While there is a growing number of investigations on the level of interaction between dietary

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ingredients with dietary proteins, very few in-vitro and as yet no in-vivo studies are available. Modulation of Proteins-Interectome Protein-protein interactions play a key role in most biological processes – from intracellular communication to programmed cell death. Besides the involvement of such interactions in intracellular signaling, the interaction of proteins in blood plasma contributes to modulations in plasma homoeostasis, receptor binding, degradation or protein excretion through, for instance, glomerular filtration (Grant and Husi, 2001). In relation to these key roles in such biological processes, protein-protein interactions represent a large and important class of targets for therapeutics. The overall description of such protein-protein interactions is summarized with the terminteractomics. In order for two or more proteins to recognize each other and bind in solution, the protein surfaces involved in protein-protein interaction must share a great deal of charged amino acids those are complementary to each other in both shape and juxtaposition. It is thus understandable that any alteration to the surface shape of a protein in a region crucial to the formation of protein-protein interactions will disrupts complementarily and will antagonize the association kinetics and thermodynamics of a protein-protein complex. Such surface changes are not only caused by small molecules that attach to critical regions of the protein, but also by post-translational modifications. Despite the great importance of post-translational modifications and protein-protein interactions for biological function, extended study of these aspects has been hampered by the lack of suitable high-throughput methods. Protein microaarays provide a versatile platform and are increasingly being used for several applications such as Heterome (biomarker) identification, protein –protein interaction studies and enzyme assays (e.g., insulin-like growth factor-binding protein, tumor necrosis factor binding protein and transthyretin (TTR)) (Gong et al., 2006; Martin et al., 2003). Requirements of Personalized Nutraceuticals for Growth and Health OMICS based nutrition research aims at understanding the relationship between diet, disease and health and finally to make recommendations for personalized nutrition (Zhang et al., 2008). System biology merged with different OMICS based technologies (transcriptomics, proteomics, metabolomics etc) provides opportunity in the field of generating personalized nutrition. The interactions between the genome and environment (e.g., nutrition) determine protein expression in organisms.


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Most genes exhibit small sequence differences or polymorphisms among individuals. Single nucleotide polymorphisms are the most common form of human DNA sequence variation and occur every 100–300 bases along the 3-billion-base human genome (Kim et al., 2004) they are responsible for the differences in both metabolism and sensitivity to dietary treatments among individuals. For example, the responses of C57BL/ 6J and C3H/HeJ mice to a high-fat diet differ markedly in the hepatic proteome (Park et al., 2004). Proteomics data can also help guide the development of individualized requirements of nutrients to optimize health and to reduce the risk of diseases. Results of modulated expression, modulated proteins heterome and proteins Interectome would provide the basis for substantial progress in the diagnostics with regards to personalized medicine and eventually personalized nutrition (Hanash, 2003). CONCLUSIONS

Proteomics plays a vital role in the research area of nutraceutical and functional food. Proteomics is not only responsible for identification and quantification of proteins (molecular robots of cell), but also map the networks of their interactions among each other or with neutraceuticals, nutrients, drugs and other molecules. Proteome analysis techniques even allow the changes in steady-state levels of numerous proteins in a biological sample. The classical approach to proteome analysis employs 2D-PAGE for protein separation in combination with MALDI-TOF-TOF & LC-MSMS and more sophisticated mass analysis techniques allow peptide sequencing and characterization of post-translational modifications in proteins. Further, Proteome turn over information will add value to nutraceutical and functional food intervention studies performed with stable isotope-labeled amino acids, peptides, and proteins. These studies will not only provide information regarding the interaction of neutraceuticals and functional food with the genome (determining the level of protein expression) but more importantly information regarding direct or indirect interaction of neutraceuticals with proteins is provided. Functional modifications in the targeted protein can be observed through covalent or non-covalent interactions. Remarkably, MS-based proteomic methods have started to contribute in this regard: Quantitative analysis of human histone post-translational modifications will give opportunities to establish useful new biomarkers for the validation of efficacy and safety of nutraceutical and nutrients with health-promoting effects. New biomarkers will also have potential for early or even pre-symptomatic recognition of nutrition or food related diseases that will allow an efficient intervention to reduce secondary complications and develop prognostic indexes and novel dietary and pharmacological therapies. Application of proteomics to nutraceutical and nutrition-related research has certain limitations such as analytical

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complexity, high cost, resolution, reproducibility and throughput. Nevertheless, the methodologies and advance proteomic technologies as well as the conceptual strategies are promising for making a significant impact on future nutraceutical and nutrition related research. The application of proteomics requires access to specialized equipment and a significant investment in skills and expertise. Proteomics is a pivotal technology in post-genomic nutrition research for assessing the effects of diet composition, specific nutrients and non-nutrient components on the genome and on mammalian metabolism. We can hope and reasonably expect that researchers, specially nutritionists will find new ways of answering the challenges posed at the start of the new millennium (Trayhurn, 2000) to apply this naïve approach in solving major scientific problems related to human nutrition. We wish to develop nutritional proteomics to promote a new area in functional food studies for a better understanding of the role of functional foods in health and disease. ACKNOWLEDGEMENTS

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