Trends in Food Science & Technology 12 (2002) 215–229
Viewpoint Bioinformatics and structural and biological properties of food commodities data knowledge: leading to new crops, processes and foods with greater quality in all aspects.Bioinformatics will improve the tox- icological assessment of foods making them even safer. the new frontiers Eventually, bioinformatics will extend the already existing trend of personalized choice in the food marketplace to enable consumers to match their food product choices for nutrition and with their own personal health.To build this new knowl- edge and to take full advantage of these tools there is a foods need for a paradigm shift in assessing, collecting and shar- ing databases, in developing new integrative models of biological structure and function, in standardized experi- mental methods, in data integration and storage, and in ,y analytical and visualization tools. # 2001 Elsevier Science Frank Desiere,* Ltd.All rights reserved. ,x Bruce German,* Introduction Heribert Watzke,* Bioinformatics and genomics are rapidly expanding fields and in a matter of months have become a crucial Andrea Pfeifer* and technology in Life Science Research. Bioinformatics { and knowledge integration have played and will con- Sam Saguy tinue to play a enabling role in Food Research inte- *Nestle´ Research Center, PO Box 44, 1000 Lausanne grating the massive amounts of data that are generated 26, Switzerland (tel: +41-21-785-8054; fax: +41-21- through new genome-wide experimental procedures 785-8925; e-mail: [email protected]) with other more traditional techniques. {The Institute of Biochemistry, Food Science and Bioinformatics is defined as: ‘‘Research, development, Nutrition, Faculty of Agriculture, Food and or application of computational tools and approaches Environmental Quality Sciences, The Hebrew for expanding the use of biological, medical, behavioral, University of Jerusalem, PO Box 12, health and nutrition data, including those to acquire, Rehovot 76100, Israel store, organize, archive, analyze, visualize or build bio- x logical knowledge from very large and traditionally unre- Department of Food Science and Technology, lated sources’’. It is about to revolutionize biological University of California, Davis, California, 95616, USA research and more importantly to apply this research to the human condition. With the availability of the human The recent publication of the Human Genome poses the genome, the completion of the rice genome, the mapping question: how will genome technologies influence food and sequencing of other major crop plants and the publicly development? Food products will be very different within available complete genome sequences of ever-growing the decade with considerable new values added as a result number of micro-organisms (http://www.ncbi.nlm.nih.- of the biological and chemical data that bioinformatics is gov/PMGifs/Genomes/org.html), Bioinformatics has, rapidly converting to usable knowledge.Bioinformatics will out of necessity, become a key aspect in Life Science provide details of the molecular basis of human health.The Research and Food Research. Bioinformatics is essen- immediate benefits of this information will be to extend our tially a cross-disciplinary activity which includes aspects understanding of the role of food in the health and well- of computer science, software-engineering and mole- being of consumers.In the future, bioinformatics will impact cular and physiological biology. foods at a more profound level, defining the physical, Although database management seems to be the major task, bioinformatics goes much deeper; it provides y Corresponding author. possible gene-function and cellular role of molecular
0924-2244/02/$ - see front matter # 2001 Elsevier Science Ltd.All rights reserved. PII: S0924-2244(01)00089-9 216 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 entities, new theoretical frameworks for complex biolo- edge will allow intervention through foods to prevent gical systems and new biological hypotheses for wet-lab health problems long before deleterious effects are research. The combination of genomic data, informa- apparent and the consumer will finally take advantage tion technology and other advanced research tools will of the technological breakthrough in these areas which give biologists the opportunity to think more broadly— will yield healthy, high quality foods with positive to investigate not only the workings of a single gene, but nutritive properties. This is just a part of the promise of to study all of the elements of a complex biological sys- how new scientific knowledge of food, gained and made tem at the same time. In the future, the starting point available through bioinformatics will influence the for a biological investigation will still be the generation everyday lives of consumers. of an hypothesis, but that hypothesis will first be tested theoretically, by modeling and polling existing data- Information and computer technology bases. A scientist will begin with a theoretical con- Bioinformatics is absolutely dependant on integrated jecture, test it on existing data and only then turning to and mature software solutions, which are available experiment as a last, not first resort. through electronic telecommunications to the individual The same knowledge doctrine is applicable to food scientist (Table 1). With the massive computing power science. Food science is a coherent and systematic body of modern computer systems we are facing fewer and of knowledge and understanding of the nature and fewer limitations in storage space and calculation time, composition of food biomaterials, and their behavior the only limiting factor becoming the lack of informa- under the various conditions to which they may be tion on specific topics. subject. Food technology is the application of food sci- ence to the practical treatment of food materials so as to Applications and examples in the food industry convert them into food products of the kind, quality and Food-grade organisms like bacteria, molds and yeasts stability, and packaged and distributed, so as to meet are the basis for a variety of biologically based indus- the needs of consumers for safe, wholesome, nutritious trial food processes (Kuipers, 1999). The fast growing and attractive foods. (http://www.ifst.org/fst.htm). number of complete genomic sequences of organisms In this respect, food science integrates the knowledge relevant to food research (Table 2) promotes the rapid of several sciences. It includes the knowledge of the increase in valuable knowledge that can be used in chemical composition of food materials, their physical, many different areas such as metabolic engineering, biological and biochemical properties and behaviors as improvement of cells as microprocess factories and the well as human nutritional requirements and the nutri- development of novel preservation methods.Bioinfor- tional and trophic factors in food materials; the nature matics will hasten the development of novel risk assess- and behavior of enzymes; the microbiology of foods; the ment procedures (Fig. 1). Furthermore, genomic interaction of food components with each other, with knowledge of bacteria and other microorganisms will additives and contaminants, and with packaging mate- revolutionize pre- and probiotic research making it rials; the pharmacology and toxicology of food materi- possible to, characterizate the broad range of bacterial als; and the effects of various manufacturing operations, properties from growth to stress responses, to multi- processes and storage conditions; Thus, food science is species microbial ecology within the human host. an information-based science which integrates knowl- edge from widely disparate sources. Metabolic pathway reconstruction The research focus in the food industry is directed by Microbial metabolism has been the basis of a major the consumers need for high quality, convenient, tasty, segment of food processing for centuries. Fermentation safe and affordable food. The scientific advances in of food takes advantage of the ability of desirable genome research and their biotechnological exploitation microbes to convert substrates (usually carbohydrates) alike represent unique opportunities to enhance food to organic tailor-made compounds contributing to the performance and to build sound scientific knowledge flavor, structure, texture, stability and safety of the food about its multiple functionalities. In the era before product. Due to its fundamental importance to such a bioinformatics and genomics, biological effects were wide variety of foods from breads to cheeses, wines to measurable only according to markers for specific con- sausage, literally over a century of research has focused ditions (e.g. nutrient deficiencies and impairment of on understanding microbial metabolism. The potential health). Research was therefore targeted solely to con- to build this knowledge into even greater value in foods sumer health problems such as high blood pressure, has been dramatically expanded by the availability of high cholesterol, lactose intolerance, osteoporosis and tools to understand and control microbial metabolism diabetes. As our biological knowledge develops in this using modern genomic and bioinformatic approaches. new era, metabolic conditions consistent with improve- The production of diacetyl, alanine and ethanol from ments in health will be the new markers (Watkins, this sugar metabolism has already been engineered in Hammock, Newman, & German, 2001). This knowl- lactic acid bacteria. With the metabolic reaction network F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 217
Table 1. Several bioinformatics resourcesa Bioinformatics companies Company URL Product Area Affymetrix www.affymetrix.com Gene Chip Data Micro-array analysis Mining Tool Applied Biosynthesis www.appliedbiosynthesis.com BioMerge Server, Genetic analysis system, LIMS BioLIMS Axon Instruments Inc www.axon.com GenePix Pro 3.0 Micro-array analysis Biodiscovery GeneSight www.biodiscovery.com GeneSight Micro-array analysis Biomax Informatics www.biomax.de BioRS Databases GMBH Pedant-Pro Bioinformatics analysis HarvESTer EST-clustering Compugen Inc. www.cgen.com Z3 2D-GE analysis LEADS Expression analysis Gencarta database Doubletwist.com www.doubletwist.com Prophecy Human genome DB GeneForest DB of expressed genes Clustering Alignment EST-clustering Tools (CAT) Genomica www.genomica.com LinkMapper Information management Discovery Manager Hitachi Genetic www.miraibio.com analysis DNASIS Mol-bio application Systems CHIP Space ChipSpace Expression-analysis DNASpace Bioinformatics analysis IBM www-4.ibm.com/software/data DB2 DB-management
Incyte Genomics www.incyte.com LifeExpress, GEMTools, Bioinformatics tools LifeArray Human genome database LifeSeq Gold Gene-expression microarrays
Informax www.informax.com GenoMax Bioinformatics tools Vector NTI Suite Mol-bio tools Integrated Genomics Inc.www.integratedgenomics WITpro, MPW, Sequencing, genome analysis, MicroAceTM metabolic design Lion Bioscience www.lionbioscience.com bioSCOUT Bioinformatics tools arraySCOUT Expression analysis genomeSCOUT Genome comparisons SRS DB management ArrayTAG CDNA arrayBase DB of annotated cDNA Molecular Mining Corp. www.molecularmining.com GeneLinker Expression analysis Packard Biochip www.packardbiochip.com QuantArray Windows Expression analysis Technologies Celera www.paracel.com GeneMatcher Hardware accelerator Paracel Inc CAP4 EST-clustering GeneWise Bioinformatics tools Rosetta Inpharmatics www.rii.com Rosetta Resolver Expression analysis Silicon Genetics www.sigenetics.com Gene Spring Expression analysis, DB Allele Sorter SNP Analysis Silicon Graphics Inc. www.sgi.com MineSet Data-mining Spotfire Inc. www.spotfire.com Spotfire.net Data-mining Spotfire Array Expression analysis
Commercial bioinformatics web-portals Company Tool URL Ebioinformatics Inc. Bionavigator www.bionavigator.com Over 200 bioinformatics tools, more than 20 databases, access to GCG Doubletwist.com Doubletwist.com www.doubletwist.com Integrated Genomics portal, access to an annotated Human Genome sequence, research agents with many bioinformatics tools Incyte IncyteGenomics www.incyte.com LifeSeq-ZooSeq-sequence DBs and bioinformatics (Continued on next page) 218 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229
Table 1 (continued) Commercial bioinformatics web-portals Company Tool URL OnLine Research Tools, LifeExpress expression DB Compugen LabOnWeb.com www.labonweb.com Bioinformatics tools and genome, transcriptome and Z3OnWeb.com www.2dgels.com Proteome DBs, access to PathoGenome Celera Celera Discovery System www.celera.com Access the Celera Human genome sequence, many bioinformatics tools
Free bioinformatics resources EMBL www.embl-heidelberg.de/ CMS Molecular Biology Resource www.sdsc.edu/restools National Centre or Biotechnology Information NCBI www.ncbi.nlm.nih.gov European Bioinformatics Institute EBI www.ebi.ac.uk ExPASy www.expasy.ch/ The Institute of Genomic Research TIGR ww.tigr.org UK Human Genome Mapping Project Resource Centre www.hgmp.mrc.ac.uk/ Weizmann Institute of Science http://bioinformatics.weizmann.ac.il/ Whitehead Institute http://www-genome.wi.mit.edu/ MIPS www.mips.biochem.mpg.uk The Sanger Centre www.sanger.ac.uk GOLD: Genomes OnLine Database http://wit.integratedgenomics.com/GOLD/
Food Research related public bioinformatics sites USDA Biotechnology Information Centre www.nal.usda.gov/bic/ UK Crop Plant Bioinformatics Network (UK CropNet) http://ukcrop.net/ The USDA-ARS Centre for Bioinformatics and Comparative Genomics http://ars-genome.cornell.edu/
a The selection of companies and web-links is not exhaustive and is not an endorsement of the entities mentioned.These resources represent the current status.Due to the dynamic nature of bioinformatics, they may change rapidly. established it becomes possible to determine its under- struction models will become more important in study- lying pathway structure by pathway models (Schilling & ing the dynamic response of cells to external stimuli. Palsson, 2000). An important approach to a holistic look at such biological processes uses genomic infor- Plants mation to reconstruct entire metabolic pathways. The Plant genome research will provide the knowledge to integration of the extensive information on metabolic increase the success of genetics and breeding to produce pathways available in the literature and databases plants of interest for the food industry. Major objectives (as in KEGG (http://www.genome.ad.jp/kegg/), EcoCyc of plant research are to improve the raw materials of the (http://ecocyc.doubletwist.com/ecocyc/), WIT (http:// food supply for higher-quality, better processability, wit.integratedgenomics.com/IGwit) with the genomic lower cost and safer food. The nutritional health and sequences of bacteria and eventually with stochiometric well-being that plant based foods provide is tradition- models will deliver tools to describe cellular processes in ally (DellaPenna, 1999) dominated by their provision of detail and to link genotype and phenotype. The match- essential vitamins and minerals and only recently has ing of well annotated genes and their expression level the potential of a number of other health-promoting from a new organism with a collection of known meta- phytochemicals been recognized to be valuable in the bolic pathways from databases is already feasible today. daily diet. Genome sequencing projects are providing However, the inclusion of kinetic information, which is novel approaches for identifying plant biosynthetic indispensable to describing the dynamic evolution of genes of more specific health importance. Genome these models, remains extremely complex. Beyond that, research can therefore directly be used to increase the many of the transcription, regulation and enzymatic efficiency and effectiveness of breeding for improvement control pathways are not well understood. As the of plants. Biotechnology, accelerated by genomics and knowledge increases in these areas, metabolic recon- bioinformatics, will increase the quality of food, reducing F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 219 all aspects of the cost including the impact of food crop anisms underlying the relationships between food and production on the environment. health, from basic nutrient actions to the interactions Cocoa (Theobroma cacao; Fig. 2) as an example is the between food microorganisms and the human intestinal raw material for all chocolate containing foods and system, including the gut and immunocompetent cells, drinks. The breeding and selection of higher quality and the mechanisms underlying the interactions of the beans with superior flavor characteristics has been diffi- microbial community in the intestinal tract (German, cult in the past, since the trees must be maintained at Schiffrin, Reniero, Mollet, Pfeifer, & Neeser, 1999). least 3–5 years before the cacao bean can be harvested With the recent explosion of genome data, including and analyzed. With the establishment of DNA finger- genomics, transcriptomics, proteomics, metabolomics printing technologies for screening plant collections, and structural genomics, bioinformatics is addressing RFLP markers for the detection of genotypic relation- the task of developing computational methods to deal ships between breeds or species and the determination with the massive flows of data emerging from modern of more than 300 molecular markers, breeding pro- experimental approaches in relating genotype to pheno- grams have been greatly enhanced. The future avail- type (Lee & Lee, 2000). The approaches include func- ability of EST sequences and genome comparisons to tional and comparative genomics and high-throughput other sequenced plants, which rely heavily on bioinfor- technologies such as genome sequencing and DNA matic tools, will result in a further acceleration with the microarrays. The knowledge developed from this new possibility to select for desired traits in an early stage of science will expand nutrition in three dimensions, plant development based on the genotype and the phe- mechanism, human variation and time: the genetic notype (Pridmore et al., 2000). mechanisms underlying health, the basis of individual variations in metabolism and the time scales during Implication of genomics/bioinformatics for health which diet influences metabolism. and nutrition The scientific knowledge of both the genetic variation Genomics, enabled by bioinformatics will contribute amongst humans and the response of individual genes to to an improved understanding of the molecular mech- ingested molecules (drugs, foods and toxins) is growing
Table 2. Genome projects of organisms interesting for the food industrya Organism Genome size (Mbp)b Organism Genome size (Mbp) Spoilage/pathogens Food-grade Bacillus anthracis 4.5/progr. Aspergillus nidulans 29/progr. Bacillus stearothermophilus 10/progr. Bacillus subtilis 4.20/published Candida albicans 15/progr. Lactobacillus acidophilus 1.9/progr. Campylobacter jejuni 1.641/published Lactobacillus sp. 2/progr. Clostridium acetobutylicum 4.1/progr. Lactococcus lactis 2.365/published Enterococcus faecalis 3/progr. Saccharomyces cerevisiae 12.069/published Escherichia coli O157:H7 4.1/published Streptococcus thermophilus 2/progr. Helicobacter pylori 1.667/published Listeria innocua 3.2/progr. Listeria monocytogenes 2.9/completed Mycobacterium bovis 4.4/progr. Others: Mycobacterium leprae 3.2/published Mycobacterium tuberculosis 4.411/published Arabidopsis thaliana (thale cress) 115.428/published Pseudomonas aeruginosa 6.264/published Bos taurus (Cattle) Mapping Pseudomonas putida 6.1/progr. Canis familiaris (Dog) Mapping Salmonella enteritidis 4.5/progr. Felis catus (Cat) Mapping Salmonella paratyphi A 4.6/progr. Glycine max (Soybean) Mapping Salmonella typhi 4.5/progr. Homo sapiens (Human) 3200/published Salmonella typhimurium 4.5/progr. Mus musculus (Mouse) Progr. Shewanella putrefaciens 4.5/progr. Oryza sativa (Rice) 450/finished Shigella flexneri 4.7/progr. Phaseolus vulgaris (Bean) Progr. Staphylococcus aureus 2.8/published Rattus norvegicus (Rat) Progr. Staphylococcus epidermidis 2.4/progr. Solanum tuberosum (Potato) EST-sequencing Streptococcus mutans 2.2/progr. Triticum aestivum (Wheat) Mapping Streptococcus pneumoniae 2/completed Zea mays (Maize) Mapping Streptococcus pyogenes 1.8/published Thermus thermophilus 1.8/progr. Vibrio cholerae 4/published
a This table represents the current status.Due to the dynamic nature of bioinformatics it may change rapidly. b MBP, number of mega base pairs; progr., project in progress. 220 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 exponentially as a result of the arrival of the human of nutritional science allowing researchers to apply genome and the tools of functional genomics (DNA genomic information to technologies that can quantify arrays, etc.). This explosion of information is only being the amount of actively transcribing genes in any cell at converted into usable knowledge because of the arrival any time (e.g. gene expression arrays). With this tech- of the massive computing power and the bioinformatic nology in place, scientists of every biological discipline tools needed to apply them to large data sets being are discovering the interaction between organisms and generated by nutrition-related research. This knowledge their environment with an intimacy never thought pos- will not only drive a new generation of foods with sible. Nutrition is at its heart, a multidisciplinary field additional values but change dramatically the ability of focusing on integrative metabolism of animals and foods to influence individual quality of life. This humans. Nutritionists have strived for the last century knowledge promises also to drive a new value system to deduce the mechanistic basis of the apparent strong for agriculture itself. relationship between diet and health through under- standing the interaction of nutrients with metabolic Genetic responsiveness or gene expression pathways. Needless to say, this was a daunting task with The ability of nutrients to directly control the expres- the traditional tools of reductionism biochemistry. Most sion of particular genes is at the heart of a new generation nutrients affect a wide range of biochemical pathways. The net result is that nutrients exert multiple effects: pleiotropic dysfunctions in their relative absence, i.e. deficiencies, and pleiotropic benefits in their return to appropriate, optimal intakes. Reductionism biochemical
Fig. 1. Electron micrograph of Streptococcus thermophilus (oval chains) and Lactobacillus johnsonii (rod-like chains) cells used for starters cultures in food fermentations. Fig. 3. The perceived food qualities are driven by flavors and tex- ture.Both are composite events whose disparate elements show specific interactions.While the elements can be controlled sepa- rately, only understanding the underlying neuro-physiological processes will lead to optimizing the flavor and texture impact of foods.
Fig. 4. Food production is based on biological raw materials which are refined into food ingredients.A unifiying approach is proposed Fig. 2. Example of a Cacao plant (Theobroma cacao L.) in natural on the basis of common basic and material properties of the form as fruits, as beans and finally as ground powder.Cacao trees comprising molecules in both domains.Moreover, the vast store of must be maintained approx.3–5 years before harvesting the knowledge currently being produced by the biomical sciences cacao.Selection of specific traits based on genotype in the early (genomics, proteomics, metabolomics) will improve the knowledge development of the plant is therefore highly desirable. on ingredient characteristics and behaviours. F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 221 approaches describe very well the effects of a single which produce dysfunctional enzyme and in regulatory nutrient’s interaction with a single target; however, they regions of the genome that prevent perfectly functional fail to adequately explore the multiplicity of metabolic lactase enzyme from being produced in adults (Harvey effects on the entire organism. The perspective of mod- et al., 1998). With genomics will come the knowledge of ern genomics is ostensibly the reverse (expansionist) the integrative nature of multiple genes in predicting approach, to measure everything. Genomic-based health. The potential opportunity of bioinformatics to investigations do not avoid pleiotropic behavior of exo- deliver that knowledge to the individual consumer will genous nutrients; quite the contrary, they reveal it. The eventually lead to individualized dietary choices in the goal of differential gene expression array experiments hands of the consumer. This bold future is arriving are to describe the full spectrum of transcriptional because of bioinformatic tools capable of managing the responses to any variable, including nutrients. Such volume of data implied by quantitatively assessing indi- global experimental designs are only possible due to the vidual metabolism and intervening in an that indivi- advent of bioinformatic tools to adequately manage and dual’s metabolism using foods to improve their health. analyze the sheer volume of data that are produced. Genomic and bioinformatic tools will improve human With the arrival of broadly parallel assessment tools clinical research. Historically, many nutrition trials including gene expression arrays and metabolomics, failed to find statistically significant effects of various single biomarkers of disease risk will no longer be con- nutrients and food choices not because there was no sidered useful (Watkins et al., 2001). Since it will be as benefit, but because the magnitude of the benefit was straightforward to measure the expression of 30,000 small relative to the overall variability in a sample of genes as the expression of one gene, knowledge from humans chosen at random from the population. expression profiling will impact health assessment. It is Humans do not respond homogeneously to even the equally certain that the days of building dossiers of effi- most straightforward nutritional variables. A great cacy and safety based on a single metabolic endpoint, value of genotyping individuals in clinical trials is to e.g. cholesterol, are limited. Such comprehensive begin to assign the variation of the population to spe- knowledge of the effects of discrete food and nutritional cific genetic differences. Clinical and epidemiological variables to overall metabolism will add new under- trials are now being analyzed using SNP data as inde- standing to their health value. pendent input variables (Takeoka et al., 2001). Most clinical trials are already cataloguing the SNPs of genes Genetic variability whose variation in function have shown to be important With the genome of one ‘individual’ human com- to the endpoint measures of these trials, for example pleted, the effective technologies to establish variations cancer, autoimmunity and heart disease (Marth et al., from that single genome, are being implemented. The 2001). Such ‘data-mining’ approaches have been suc- Single Nucleotide Polymorphisms (SNP) Consortium cessful not only in identifying the causes of statistical (http://snp.cshl.org/) is mapping the polymorphic variation among trial participants but in identifying the regions of the genome that control individual pheno- potential biochemical mechanisms responsible for the typic differences among the population (Sachida- variation in response. This approach is already proving nandam et al., 2001). While these variations are being so powerful that scientific agencies are recognizing that viewed initially as the key to the discovery of genetic traditional avenues of scientific publishing aren’t ade- diseases, they are also the keys to individual variation in quate and the processes of scientific discovery of genetic diet and health. Sequence variation in particular genes polymorphism and health are accelerated by the avail- even as slight as single nucleotides can influence the ability of SNP data sets and bioinformatic packages quantitative need for and physiological response to on the internet (Clifford, Edmonson, Hu, Nguyen, various nutrients. Knowing that genes influence nutri- Scherpbier, & Buetow, 2000). tion, of course is not new. An understanding of this variation is inherent in population recommendations for Genetic polymorphism and nutrient requirements essential nutrients (Young & Scrimshaw, 1979). How- Polymorphisms in the various genes encoding ever, allowing for the variation in human genetics by enzymes, transporters and regulatory proteins affect the incorporating a large margin for error in quantitative absolute quantities of essential nutrients that are neces- recommendations is not the same as designing diets for sary to achieve sufficiency, including vitamins, minerals, specific individuals according to their genetic profiles etc. (Bailey & Gregory, 1999). Thus, the variation in the (Eckhardt, 2001; Nichols, 2000). An example of poly- population’s nutrient status is not simply the result of morphisms that influence nutrition and disease is phe- variations in food intakes but also the result of inherent nylketonuria, in which the inability to metabolize variation amongst individuals within the population in phenylalanine renders this nutrient toxic (Lindee, 2000). their genetically defined abilities to absorb, metabolize The occurrence of lactose intolerance is due to poly- and utilize these nutrients. Recommended daily allow- morphisms both in the structure of the lactase gene ances of each nutrient are determined to meet the needs 222 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 of a statistically representative fraction of the popula- recommendation how to alter the intakes of dietary fat tion; however, the range of responses to both micro- for those affected. Thus, the information of how an and macronutrients in the general population is large. individual responds to foods provides that individual Very recent research using genomic tools is highlighting with the means to change their diet to improve their just how specifically individual food choices, genetics health. With each new discovery of genetic polymorph- and nutrition are linked. Polymorphism in a recently isms linked to health, the complexity of the science identified sweet receptor protein has been proposed to increases. Fortunately, modern bioinformatics tools are be the basis for the varying intakes of caloric-rich foods, inherently integrative adding each new discovery into a i.e. the famous sweet tooth (Davenport, 2001). rapidly expanding coherent picture of diet and health of As genomics begins to reveal the basis for food pre- individual consumers. ference and the respective roles of genetics and envir- onment, nutritional superior foods could be made more Food quality organoleptically attractive to precisely the subset of the Food is one of life’s great delights. Modern science population for whom they are most appropriate. How- and technology have provided unparalleled value to ever, an important step is still missing. At this point, consumers in the breadth of individual choices in deli- while the technologies to describe the effects of diet on cious, safe and nutritious foods. This great value has various individuals experimentally are widely used for been driven by scientific knowledge at all levels of the example in clinical trials, the technologies are not yet agricultural food chain from genetic improvements in part of routine consumer assessment. Therefore, con- production agriculture to food process engineering to sumers cannot take advantage of nutritional knowledge precision in the analysis of consumer sensation. With its about themselves, because they do not have it. This lack power to build detailed molecular knowledge of biolo- of knowledge transfer is clearly the largest single factor gical organisms, modern bioinformatic technologies are constraining a more widespread improvement in nutri- assembling the means to re-invent the food supply. In tional health in the consumer population. no other aspect of life do humans interface with other biological organisms to the same extent as in the con- Genetic variation and the response to variations in sumption of food. Thus, the most tangible, daily value overall diet that genomics will eventually produce for humans is a Genetic differences affect the basic metabolism of dramatic increase in the quality of their lives through macronutrients and in particular fat and carbohydrate the quality of their foods. Bioinformatics will help in humans. For example, polymorphisms in the apo- understand the basis of different food flavors, and tex- protein genes (apoE, apoAIV) or lipoprotein catalysts tures and even further why we find them delicious, and (lipoprotein lipase) have been shown to directly affect hence how to enhance that experience. Bioinformatics the clearance of dietary lipids. Hence polymorphisms in will not only define in molecular detail which foods are lipid metabolic genes dictate the response of these indi- safe, but develop foods that make consumers themselves viduals to dietary fat (Hockey et al., 2001; Pimstone et safer. Bioinformatics will not only improve the processes al., 1996). Polymorphism in the genes encoding for the of forming foods, but design foods that form themselves. apoE protein influence the functionality of this protein The understanding of the biomolecular basis of flavor in clearing liver-derived lipoproteins (VLDL and LDL) perception has been a major success of the last 5 years from blood (Weintraub, Eisenberg, & Breslow, 1986). of scientific investigation in the molecular biology of Health outcomes beyond heart disease including Alz- sensation (Fig. 3). heimer’s disease have been shown to be correlated to Success in identifying, in molecular and genetic apoE phenotypes. Once again, diet plays a differential details, the taste and flavor receptors has been remark- role in the development of these diseases according to able in the past months. These include: genotype through the role of diet in influencing the quantitative flux of hepatic lipoprotein metabolism Bitter: A family of 50 G protein-coupled (Corella et al., 2001). receptors (GPCRs) identified in human taste cells Many consumers are concerned about the widespread (Chandrashekar et al., 2000); application of genomic testing in the population because Salt: The epithelial ion channel, ENaC is they see little value to themselves. However, there is responsible for over 80% of salt taste transduc- great value in acquiring knowledge about individual tion (Nagel, Szellas, Riordan, Friedrich, & Har- variation in diet-responsive genes if it can lead to suc- tung, 2001); cessful intervention. For example, genotype predicts a Sour: An ion channel, identical to degenerin-1, is difference in post-prandial lipid metabolism of dietary proposed to be the receptor (Ugawa et al., 1998); fat (Hockey et al., 2001). The most exciting aspect of Umami: A ‘splice variant’ of brain glutamate this discovery is the realization that this knowledge is receptor, mGluR4 identified in rat taste cells not just academic, but leads to an immediate individual (Matsunami, Montmayeur, & Buck, 2000); and F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 223