Trends in Food Science & Technology 12 (2002) 215–229

Viewpoint 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 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 -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 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//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, 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 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, , printing technologies for screening plant collections, and , 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 (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

Sweet: The putative identity of the sweetness could lead the way to furnish tailor made specific orga- receptor identified as a G protein coupled recep- nolopetic attributes as well as nutrition needs. tor Tas1r3 (Max et al., 2001). Bioinformatics and food processing The most immediate application of bioinformatics to The discovery of these taste receptors is being trans- food processing will be in optimizing the quantitative lated rapidly into a variety of research programs compositional parameters of traditional unit operations. designed to discover the next generation of taste modi- Food commodities are processed largely to achieve sto- fiers for foods. The sugar substitutes demonstrated the rage stability and safety with considerable excess of potential for replacing the traditional sweet molecules energy applied to ensure a large margin for error. This (simple sugars) with non-caloric, non-cariagenic and margin of error is necessary due to our inexact knowl- non-glycemic alternatives in a variety of food products. edge of the composition and structural complexity of Now, with the balance of taste receptors known, it will biological materials, the natural variability of living be possible to develop flavor systems that either produce organisms as food process input streams and the or enhance positive or mask negative tastes. Much of response of these materials to processing parameters. this work will be possible using combinatorial chemistry With the considerable knowledge of biological organ- approaches that use bioinformatic tools to screen thou- isms from bacteria and viruses to plants and animals sands of molecules and combinations at a time. Such that is emerging from bioinformatics, food process molecular simulations once took weeks and very large design will become optimized with narrower margins of super-computer installations. New developments in all cost-important inputs, especially energy. computing power, computational algorithms and soft- The great future for food processing however is not in ware and the available databases of known structures simply processing for greater safety, but in merging and successful simulations has brought molecular mod- biological knowledge of living organisms with the bio- eling into mainstream food chemistry. Such simulations material knowledge necessary to convert them to foods. will make it possible to develop not only more intense Traditional food processing relies on the aggressive tasting compounds as food additives, but understand input of energy to restructure the biomaterials of living the basis of taste persistence, antagonism and com- organisms into simpler macrostructure forms of stable, plementation. Flavor systems will become more com- relatively uniform foods. In most cases the inherent plex, more attractive and more individualized to biological properties of the living systems are lost to the consumers. final food product in the need to eliminate potentially hazardous properties of some of the constituent mole- Olfaction: a family of 1000 GPCRs, about 300 cules (protease inhibitors, etc.). The arrival of the identified knowledge base of modern bioinformatics, however, is Not far behind the taste receptors the much more providing a detailed description of the inherent com- abundant odor receptors are being identified as well. plexity of biological macromolecules within living cells The full olfactory complement of genes has been pub- together with the structural properties of these mole- lished (Glusman, Yanai, Rubin, & Lancet, 2001). The cules that provide much of their functions. Such number of odor receptors exceeds the number of taste knowledge is the cornerstone of functional genomics receptors by a factor of 100. In spite of this expansion in and proteomics. The arrival of such knowledge, how- size and complexity, bioinformatics will have little diffi- ever, provides an unprecedented opportunity to trans- culty in translating the principles of ligand–receptor late this knowledge into an equally accurate assessment interaction developed with taste into similar applica- of the biomaterial properties of each of the molecules in tions to odor sensations. With such capabilities, sophis- a complex mixture. It will soon be possible to use the ticated flavor systems will be designed from the inherent structural properties of natural food commod- perspective not simply of what is available in natural ities to self-assemble new foods with a minimum of commodities and foods, but with final flavor perception external energy retaining a maximum of biological and as the goal. Ultimately, it will be possible to design fla- nutritional value. The biological structure–function vor systems that optimize flavor perception in highly relationships discovered through bioinformatics of liv- nutritious foods that are currently organoleptically ing systems will be able to be mapped into the struc- undesirable in spite of their superior health value. ture–function relationships of the next generation of Making the next connection, i.e. understanding the foods with delightful results (Fig. 4). basis for healthy and unhealthy food choices, is already All foodstuffs are ostensibly modified tissues. Thus, proceeding. the natural biomaterial properties of the molecules that Recently, the connection between gratification and make up living organisms underlie the basic biomaterial the brain was verified in rats (Cardinal et al., 2001). properties of foods. In most traditional food process- Similar developments in our understanding of the brain ing, however, little advantage is taken of the unique 224 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 properties of specific molecules and instead, all bio- entire protein–protein interaction map of yeast, i.e. all molecules of a particular class, e.g. proteins, are exposed possible interactions between the 6000 proteins of yeast, to substantial physical, thermal and mechanical energy has been completed (Ito, Chiba, Ozawa, Yoshida, Hat- to make these properties uniform in order to restructure tori, & Sazaki, 2001). In the future, the structure func- the material into more stable, and/or more bioavailable tion properties of living organisms that are emerging so food systems. Such processing eliminates the subtle rapidly with bioinformatics will increasingly dictate the differences within most of the classes of the major bio- design of new foods and new food processes. Once such molecules that are inherent to and the basis of complex tools are in hand, process design engineers can then structure–function relationships of living organisms. work in a coordinated fashion with plant bioengineers Processing replaces biological complexity with the to produce crops that are not simply enriched in a single statistical average properties of the broad classes of valuable component, but instead redesigned with a biomaterials, i.e. proteins, carbohydrates, lipids. renewed purpose to increase the myriad values of foods The processing of commodities to eliminate the com- in providing quality of life. plexity of their biological structures are not necessary to the quality of foods, in fact the opposite. There are vivid Flavor analysis examples in which highly specific biological properties The complex flavor profiles of many delightful com- of the original living organism are a key to the proces- modities (e.g. fruits, baked goods) are not due to single sing strategy and ultimately the organoleptic attractive- compounds but rather are the result of the presence and ness of final food products. The renneting of bovine interactions of literally dozens of different molecules. milk to induce the natural aggregation of milk caseins This knowledge will provide the link and the compiler leading to the gelation events of cheese manufacture is integrating processing, quality and nutrition paving the such a process. The final product takes advantage of the road for new product development based on insight unique self-assembly properties of milk casein micelles knowledge of actual consumers’ preferences and needs. that are colloidally stabilized in milk by kappa caseins but destabilized when enzymatically cleaved of their The impact of genomics on the quality assurance of solubilizing glycomacropeptide. Another example is foods leavened bread in which a combination of both compo- Food safety is becoming more and more a major area site processing and biological restructuring is the basis of concern for consumers and the food industry has of breads’ structures, textures and nutrition. In this developed a coherent research programme to ensure case, wheat seeds are ground to disassemble the major- food safety with well-established classical methodolo- ity of their biological structures through mechanical gies but also new state-of-the-art research tools. The energy, but then the biological processes of yeast fer- goal here is to ensure that the inactivation or inhibition mentation achieve simultaneously the enzymatic elim- of undesired microbes is possible using the minimum ination of phytic acid during dough incubation and the treatment of foods necessary, to increase the under- biochemical production of carbon dioxide gas as lea- standing on the ecology of food-born microbial popu- vening within a mechanically reworked protein gel lations, to find-out how these populations respond to structure. In each of these cases, bread and cheese, tak- environmental factors like stress and last but not least ing advantage of the biological properties of the living the toxicological evaluation of foods and food com- organisms, led to substantial value both organolepti- pounds. cally and in greater safety and nutritional value. Fur- The genomics era delivers many new tools like pro- thermore, the inherent variation in biological organisms teomics and DNA-array technology to tackle the that plagues the standardization of simpler food pro- abovementioned problems. These new technologies are cessing objectives is not a disadvantage to these two now a vital part of the scientific strategic plan to serve food staples, but rather a wonderful benefit leading to the diet and health theme and to provide safe food to literally hundreds of distinctly flavored and textured the consumer. cheeses and varieties of breads. Thus, cheeses and , for example, is an emerging field breads provide proof of what is possible when the bio- which utilizes DNA arrays (tox-chips) to test the tox- logical processes of catalysis, self-assembly and restruc- icological effects of a specific compound. These DNA turation is retained as the basis of food processing. arrays probe human or animal genetic material printed Heretofore, empirical trial and error was the major on miniature devices to profile gene expression in cells route to discovery of biodriven food processing. How- exposed to test compounds rather than using animal ever, the biological knowledge that is emerging with pathology to define illness (Lovett, 2000). The advan- functional genomics, proteomics and metabolomics is tages of this test goes beyond the speed and the ease of providing precisely the knowledge necessary to read- use which is typical for DNA expression analysis; it also dress food processing using bimolecular activities rather reduces massively animal testing. Another challenge than simply composite biomaterial properties. The here is the massive amounts of data which are produced F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 225 via these high-density DNA arrays and the analysis and Data mining refers to a new genre of bioinformatics the interpretation of the results is a real challenge. Once tools used to sift through the mass of raw data, finding this task has been tackled, the integration of tox-chip and extracting relevant information and developing data must be integrated into the knowledge basis of the relationships among them. As advances in instrumenta- research institution to draw a maximum of benefit for tion and experimental techniques have led to the accu- the acceleration of the development pipeline. mulation of massive amounts of information, data mining applications are providing the tools to harvest Data integration the fruits of these labors. Maximally useful data mining The explosion of data, ever increasing developments applications should: in information technology, abundant availability of powerful computers and the ability to connect them Process information from disparate experimental worldwide, affects enormous changes in knowledge techniques, and technologies, including data that management. However, in order to gain full access to have both temporal (time studies) and spatial these emerging powerful tools, it is paramount to (organism, organ, cell type, sub-cellular location) resolve the enormous challenge of unifying complex and dimensions; dissimilar data, each describing a large spectrum of Identifying and interpreting outlying, spurious applications, each of which could be extremely far and rare data; apart. The need to combine observations from numer- Analyze data in an iterative process, re-applying ous sources and domains, into a unified, seamlessly gained knowledge to constantly examine and re- searchable database and turning it into knowledge is examine data; only the beginning of this uphill battle that will impact Utilize novel text-mining and pattern recognition every facet of food and nutrition science. algorithms. Advances in data collection, storage and distribution technologies have far outpaced techniques to assist the analysis and digestion of this information. In the past, In the early years of modern scientific discovery, most databases were quite small and utilized as typeset research findings would appear in a journal and then get tables or simple online documents. Today, far larger buried in the depths of poorly accessible library space. and more complex databases are emerging in many Information existed in various formats (e.g. graphic, fields at a level well beyond the reach of the traditional hard copy, tape), and was not easily retrievable. Data model of solitary workers or small groups. (Maurer, analyses were generally limited to slide rule and manual Firestone, & Scriver, 2000). This has led to an all-too- manipulation. However, technological advances in common data glut situation creating a strong need and computational science and scientific instrumentation a valuable opportunity for extracting knowledge from have facilitated the exponential growth, not only in databases collected throughout R&D and elsewhere. data, but also the tools to record and analyze these data. One of the greatest challenges we are facing is how to What was the Computer Age as we entered the 1990s turn this rapidly expanding or even exploding data into has been supplanted by the Information Age. This accessible and actionable knowledge. Moreover, food change was made possible by the advent of the Internet, and nutrition R&D is engaged in an assortment of in particular the World Wide Web. This innovative, complex studies producing enpoint measures comprised truly universal mechanism of information dissemina- of numeric, sensory and perceptions, structure, biologi- tion, in concert with new computation-based analytical cal, chemical and vision data. This need to manage such tools, has provided practically endless opportunities for disparate inputs is critical as the amount of data dou- scientific discovery. bles almost every 20 months (Colbourn & Rowe, 2000). The exponential rate of discovery in the era of mod- Underlying the need to convert data into actionable ern molecular biology is phenomenal, culminating with knowledge, organizations have started an aggressive the June 2000 announcement that preliminary sequen- effort to deploy Knowledge Discovery in Databases cing of the human genome had been completed. This (KDD), Knowledge Management (KM), Data Mining landmark is just a taste of the scientific successes that (DM) and Intellectual Asset Management (IAM). These are to come. As impressive as it is, the determination of areas of common interest to researchers are: pattern the sequence of the approximately 3.2 billion nucleo- recognition, statistics and statistical inference, intelligent tides of the human genome, encoding an estimated databases, knowledge acquisition, data visualization, high 100,000 proteins, represents only the first step down a performance computing and expert systems, to mention long road of knowledge discovery and its application to just a few. Although these high technology information added value to consumers. management systems are starting to play a fundamental Another application of bioinformatics that is growing role for the experts who are working on their develop- extremely fast is Chemometrics, the chemical discipline ment, they are however almost invisible for most users. that applies mathematics and statistical methods, and 226 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 uses designs of experiment to understand the effects and 2. Pharmaceutical industry—Building of huge interactions of several process parameters, and also to combinatorial libraries by automatically synthe- optimize specific outcomes (Otto, 1999). Chemometrics, sizing all possible combinations of components is originally rooted in analytical chemistry, is currently underway. The number of compounds in such a more focused on addressing issues related to molecular database can now be confidently stated to be in conformations and behavior. With the increasing avail- the hundreds of thousands or even millions. The ability of databases (e.g. through WWW), the need for new automated screening technologies can test improved techniques that help extracting information each of these compounds, giving an indication of and turn it into knowledge has been therefore ever whether a compound is going to be effective growing (Brazma, Robinson, Cameron, & Ashburner, against a specific biochemical target and a spe- 2000). cific disease. It should be highlighted that food and nutrition are 3. Chemical industry—Chemical reaction databases related topics and are prone to another more crucial are available and could be used to derive knowl- problem. Generally, advanced data mining and other edge for predicting the course and products of sophisticated search tools are no better than the infor- chemical reactions as well as to design organic mation provided. As the scientific literature may contain syntheses. To reach this goal, the essential fea- both editorial and/or more fundamental errors (e.g. tures of the chemical reaction have only to be false methodology, unjustified conclusions, faulty appa- recognized and generalized. This was achieved by ratus), hence the need for the impartial scrutiny of classifying a set of reactions by unsupervised human editorial judgement is indispensable. One might learning techniques such as self-organizing maps make a compelling case that the value of the databases (Kohonen). In this approach, reactions are char- is compromised most by their inherent bias: in concept acterized by physicochemical features directly and design towards only benefit and in publication derived by computations from the constitution of towards only a positive outcome. Databases are most the starting materials or products of a reaction valuable to data mining and bioinformatics searchers (Gasteiger & Sacher, 1999). when they are balanced. It should be emphasized that if 4. Information industry—Chemical Abstracts Ser- data mining techniques are polling databases that are so vice (CAS) has launched its SciFinder 2000, inherently unbalanced that no matter what the truth empowering the user with greater visualization is, the data mining will invariably reflect the inherent tools and the ability to cross-tabulate and display bias in the databases that has been the result of con- searches graphically. This ‘wizard’ allows a scious or unconscious editorial influence. Hence, like researcher to simultaneously locate information most other computer applications, the outcome in the within a multitude of databases and subse- short term will be only as good as the quality of the quently explore the relationship between them. data. Moreover, the more complex the calculation is, The retrieved data may be displayed in a 3D the more paramount is the need for adequate checks representation that can be further manipulated and balances. The solution is for more balanced data to zero in on the requisite research. The use collection. At present, this is not the norm for nutri- of such data mining could revolutionize the tional research. way scientists approach their research projects Typical examples, far from being representative, yet (Massie, 2000). demonstrating how knowledge management is utilized, 5. Environmental safety—To reduce the need for are provided: animal testing, Unilever has applied data mining techniques (Clementine) to model skin corrosiv- 1. Food industry—A software package (NetStat) ity of organic acids, bases and phenols. This was developed for analyzing reams of data, and facilitated uncovering new information from the is reported to have changed every aspect of the existing database, and eventually will furnish Pillsbury company (i.e. from the way it develops toxicologists with neural network based packa- new products to how it capitalizes on consumers’ ges to help assess and predict corrosivity and tastes). The NetStat uniqueness is its ability to other toxicological properties. This approach is share information across all the company’s nine much more approachable than current tech- brands including manufacturing lines. The pro- niques (e.g. principal component analysis). It gram is implemented as a Web site shared by is hoped that it will lead to a movement away researchers across a 70-country conglomerate, from in vivo and in vitro experimentation towards and allows engineers and scientists to perform ‘in silico’ analyses, reducing costs, time scales rigorous tests and compare them with data for product development, and minimizing the and specifications and consumer information need for animal testing (http://www.spss.com/ (Crockett, 2000). clementine/). F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 227

6. Consumers—Data mining techniques are now Future areas required development are: being used to extract a surprising amount of information on individual customers and their Models—Models that describe a class of reac- buying patterns. These data are then used to tions in an actual food system or food concept develop customer loyalty programs, for carefully ‘in silico’ (Hultzman, 2000). These models should focused marketing or additional services that fit be designed so that they could also be applied for the customer’s individual preferences, and for testing the validity of previous data reported. identifying possible synergies with other compa- This goal also mandates that terminology be nies who might share the same or similar base of harmonized, to improve accessibility. It could customers. Applications are ranging from direct lead to a movement away from in vivo and in marketers, books, to credit card companies, vitro experimentation towards ‘in silico’ ana- which identify trends, potential users, and target lyses, reducing costs, time scales for product marketing strategies. development, and minimizing the need for ani- mal testing. Standardized protocols—Standard experimental Development needs for data integration design and replication must be set if data accu- Computational biology and electronic technologies mulated by different groups and various techni- will be crucial for the future of Life science research and ques should be integrated. Thus, leading to offer in addition promising opportunities to many improved reproducibility, reduce variability, fur- industries. Future central issues for the shortening of nishing truly quantitative data, increase sensitiv- research driven product development and gaining com- ity and provides means for comparing data petitive advantage will be the issue of data integration. obtained from different sets (e.g. Lee, Kuo, Companies which started initiatives in this area are now Whitmore, & Sklar, 2000). struggling to integrate legacy enterprise resource plan- Data integration and storage—Linking, inte- ning and data warehouse technologies with bioinfor- grating interoperable large databases with differ- matics. Compared to this challenge all other issues ent heterogeneous structure and data types is far including electronic commerce fade into insignificance. from being a straightforward task when con- To be successful, companies are now focusing on spe- sidering the vast differences that do exist between cific enabling technologies like Java, message-oriented various domains makes this task immense. Simi- middleware and XML to encourage web-based colla- larly the ever-growing amount of information boration between research teams and operating units. needs adequate storage and maintenance. Cata- Clear integration paths and benchmarks are, however, loging and automated extraction (e.g. Andrade still lacking. & Bork, 2000) are paramount. As the informa- The ability to make better, faster and more innovative tion complexity and quantity grows, the food research decisions is paramount to progress. Emerging practitioners need to define and develop a unified technologies and the exploding amount of data high- and acceptable approach. This task requires sig- light the need for new approaches. The availability of a nificant planning where all facets of the food, large number of fast PC’s connected together allows nutrition, biology and other domains are parallel processing, overcoming barriers due to speed involved. and computer resources. However, the ability to inte- Predictive tools—Techniques allowing the auto- grate the data and utilize KM is a real challenge, which mated discovery from large and different data is compounded by the increased economic pressures and sets need to be further developed before they demanding marketplace, global competition, regulation, could be fully utilized in the food and nutrition and consumer demands. Implementing these new meth- domains. Once implemented, it would open new odologies could open new avenues improving our ability avenues towards broad interdisciplinary science to quickly and efficiently gain new knowledge and that involves both conceptual and practical tools insights from cell structure to consumer perceived sen- for generation, processing, analyzing and propa- sory attributes. Ultimately, one should envision ‘an gation of information leading ultimately to fun- engine’ able to ‘plug and play’ into various data damental understanding. domains, integrating all the facets of a business increas- Data visualization—A large volume of the ing the likelihood of identifying the next target or new human brain is devoted to visual data processing food product for development and quality improvement (Going & Gusterson, 1999). Data visualization addressing the consumers’ real and perceived needs. methods therefore will play a significant role Planning for the future is no longer a luxury; it is a allowing pattern characteristics and recognition. standard operating procedure for the existence and well- Paradigm shift—Food and nutrition science being of the enterprise. should develop a holistic approach, by moving 228 F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229

away from studying ‘vertically’ the role(s) of few Davenport, R.F.(2001).Taste research.New gene may be key to variables to ‘horizontally’ studying simulta- sweet tooth. Science 27, 292(5517), 620. neously many variables and applying advanced DellaPenna, D.(1999).: manipulating plant micronutrients to improve human health. Science, 285, 375–379. modeling and analysis techniques (e.g., Fiehn, Eckhardt, R.B.(2001).Genetic research and nutritional indivi- Kloska, & Altmann, 2001). duality. Journal of Nutrition, 131, 336S–339S. Fiehn, O., Kloska, S., & Altmann, T. (2001). Integared studies using multiparrallel techniques. Current Opinion in Biotechnol, 12, 82–86. Firestein, S.(2000).The good taste of genomics [news; comment]. Conclusions Nature, 404, 552–553. Biomics, comprised of genomics, proteomics and Gasch, A. P., Spellman, P. T., Kao, C. M., Carmel-Harel, O., Eisen, metabolomics, is taking up its position as a lead science M. B., Storz, G., Botstein, D., & Brown, P. O. (2000). Genomic for the 21st century. Its influence is already felt through expression programs in the response of yeast cells to environ- out the biological sciences. Moreover, its influence on mental changes. Mol Biol Cell, 11, 4241–4257. Gasteiger, J., & Sacher, O. (1999). Unsupervised learning in reaction nutrition and food science will generate a unified area of databases.ACS Meeting, March, Anaheim, CA, USA. research where both nutritional benefit and traditional German, B., Schiffrin, E. J., Reniero, R., Mollet, B., Pfeifer, A., & food values become parts of an extended life science Neeser, J.R.(1999).The development of functional foods: lessons driving towards enhanced quality of life. Impacts of the from the gut. Trends in Biotechnology, 17, 492–499. knowledge obtained through this research on raw Glusman, G., Yanai, I., Rubin, I., & Lancet, D. (2001). The complete human olfactory subgenome. Genome Research, 11, 685–702. materials, ingredients, safety, quality and nutrition can Going, I.J.,& Gusterson, B.A.(1999).Moleculare phatology and be expected to have a far greater impact on product future developments. European Journal of Cancer, 35, 1895– improvements than today’s functional food research is 1904. imagining. Future developments in biomics, bioinfor- Harvey, C. B., Hollox, E. J., Poulter, M., Wang, Y., Rossi, M., matics and information technology based approaches to Auricchio, S., Iqbal, T. H., Cooper, B. T., Barton, R., Sarner, M., Korpela, R., & Swallow, D. M. (1998). Lactase haplotype foods will truly change and revolutionize the way food frequencies in Caucasians: association with the lactase industry will satisfy consumer needs and wants. persistence/non-persistence polymorphism. Annals of Human Genetics, 62(Pt 3), 215–223. Uncited references Hockey, K., Anderson, R., Cook, V., Hantgan, R., Weinberg, R., Bender (1999), Firestein (2000), Gasch et al. (2000) Hockey, K., Anderson, R., Cook, V., Hantgan, R., & Weinberg, R. (2001).Effect of the apolipoprotein A-IV Q360H polymorphism and Weggemans et al. (2001). on postprandial plasma triglyceride clearance. Journal of Lipid Research, 42, 2001 211-217. References Hultzman, S.(2000).In silico toxicology. Annals of the New York Academy of Science, 919, 68–74. Andrade, M.A.,& Bork, P.(2000).Minireview: Automated extrac- Ito, T.Chiba, T.Ozawa, R.Yoshida, M.,Hattori, M.,& Sakaki, Y.A. tion of information in molecular biology. FEBS Letters, 476, 12– comprehensive two-hybrid analysis to explore the yeast protein 17. interactome.Proceedings of the National Academy of Sciences Bailey, L.B.,& Gregory, J.F.(1999).3rd Polymorphisms of methyl- of the United States of America, 98(8), 4569–4574. enetetrahydrofolate reductase and other enzymes: metabolic Kuipers, O.P.(1999).Genomics for food biotechnology: prospects significance, risks and impact on folate requirement. Journal of of the use of high-throughput technologies for the improvement Nutrition, 129, 919–922. of food microorganisms. Current Opinion in Biotechnology, 10, Bender, D.A.(1999).Optimum nutrition: thiamin, biotin and 511–516. pantothenate. Proc Nutr Soc., 58, 1999 427-433. Lee, M. L. T., Kuo, F. C., Whitmore, G. A., & Sklar, J. (2000). Impor- Brazma, A., Robinson, A., Cameron, G., & Ashburner, M. (2000). tance of replication in microarray gene expression studies: One-stop shop for microarray data. Nature, 403, 699–700. statistical methods and evidence from repetitive cDNA Cardinal, R. et al. (2001).Impulsive choice induced in rats by lesions hybridizations. Proceedings of the National Acadamy of Sciences of the nucleus accumbens core. Science, 292. of the United States of America, 97, 9834–9839. Clifford, R., Edmonson, M., Hu, Y., Nguyen, C., Scherpbier, T., & Lee, P.S.,& Lee, K.H.(2000).Genomic analysis. Current Opinion in Buetow, K.H.(2000).Expression-based genetic/physical maps Biotechnology, 11, 171–175. of single-nucleotide polymorphisms identified by the cancer Lindee, M.S.(2000).Genetic disease since 1945. Nat Rev Genet, 1, genome anatomy project. Genome Research, 10, 1259–1265. 236–241. Chandrashekar, J., Mueller, K. L., Hoon, M. A., Adler, E., Feng, L., Lovett, R.A.(2000).Toxicogenomics.Toxicologists brace for Guo, W., Zuker, C. S., & Ryba, N. J. (2000). T2Rs function as bitter genomics revolution. Science, 289, 536–537. taste receptors. Cell, 100, 703–711. Marth, G., Yeh, R., Minton, M., Donaldson, R., Li, Q., Duan, S., Colbourn, E., & Rowe, R. (2000, April 3). A logical step forward. Davenport, R., Miller, R. D., & Kwok, P. Y. (2001). Single- Chem & Ind., 252–254. nucleotide polymorphisms in the public domain: Corella, D., Tucker, K., Lahoz, C., Coltell, O., Cupples, L. A., Wilson, how useful are they? Nature Genetics, 27, 371–372. P. W., Schaefer, E. J., & Ordovas, J. M. (2001). Alcohol drinking Massie, B.(2000).Moving towards a new digital environment. Am. determines the effect of the APOE locus on LDL-cholesterol Chem. Soc. 219th National Meeting, Part XI, 26–30 March, concentrations in men: the Framingham Offspring Study. San Francisco, CA. American Journal of Clinical Nutrition, 73, 736–745. Matsunami, H., Montmayeur, J. P., & Buck, L. B. (2000). A family of Crockett, R.O.(2000, April 3).Pillsbury: a digital doughboy. candidate taste receptors in human and mouse. Nature, Business Week. 404(6778), 601–604. F. Desiere et al. / Trends in Food Science & Technology 12 (2002) 215–229 229

Maurer, S. M., Firestone, R. B., & Scriver, C. R. (2000). Science’s Linton, L., Lander, E. S., & Attshuler, D. (2001). The International neglected legacy. Nature, 405, 117–120. SNP Map Working Group A map of human genome sequence Max, M., Shaker, Y., Huang, L., Rong, M., Liu, Z., Campagne, F., variation containing 1.42 million single nucleotide polymorph- Weinstein, H., Damak, S., & Margolskee, R. F. (2001). Nature ism. Nature, 409(6822), 928–933. Genetics, 28, 58–63. Schilling, C.H.,& Palsson, B.O.(2000).Assessment of the meta- Nagel, G., Szellas, T., Riordan, J. R., Friedrich, T., & Hartung, K. bolic capabilities of Haemophilus influenzae Rd through a (2001).Non-specific activation of the epithelial sodium channel genome-scale pathway analysis. Journal of Theoretical Biology, by the CFTR chloride channel. EMBO Reports, 2, 249–254. 203, 249–283. Nichols, B.L.(2000).Nutrigenetics and child development in the Takeoka, S., Unoki, M., Onouchi, Y., Doi, S., Fujiwara, H., Miyatake, 21st century. Nutrition, 16, 493–495. A., Fujita, K., Inoue, I., Nakamura, Y., & Tamari, M. (2001). Amino- Otto, M.(1999). Chemometrics statistical and computer application acid substitutions in the IKAP gene product significantly increase in analytical chemistry.Weinheim, Germany: Wiley VCH. risk for bronchial asthma in children. Journal of Human Genetics, Pimstone, S. N., Clee, S. M., Gagne, S. E., Miao, L., Zhang, H., Stein, 46, 57–63. E.A.,& Hayden, M.R.(1996).A frequently occurring mutation in Ugawa, S., Minami, Y., Guo, W., Saishin, Y., Takatsuji, K., lipoprotein lipase gene (Asn291Ser) results in altered post- Yamamoto, T., Tohyama, M., & Shimada, S. (1998). Receptor that prandial chylomicron triglyceride and retinal palmitate response leaves a sour taste in the mouth. Nature, 395(6702), 555–556. in normolipidemic carriers. Journal of Lipid Research, 37, 1675– Watkins, S. M., Hammock, B. D., Newman, J. W., & German, J. B. 1684. (2001).Individual metabolism should guide agriculture toward Pridmore, R. D., Crouzillat, D., Walker, C., Foley, S., Zink, R., foods for improved health and nutrition. American Journal of Zwahlen, M. C., Brussow, H., Petiard, V., & Mollet, B. (2000). Clinical Nutrition, 74, 283–286. Genomics, molecular genetics and the food industry. Journal of Weggemans, R. M., Zock, P. L., Ordovas, J. M., Pedro-Botet, J., & Biotechnology, 78, 251–258. Katan, M.B.(2001).Apoprotein E genotype and the response of Sachidanandam, R., Weissman, D., Schmidt, S. C., Kakol, J. M., serum cholesterol to dietary fat, cholesterol and cafestol. Stein, L. D., Marth, G., Sherry, S., Mullikin, J. C., Mortimore, B. J., Atherosclerosis, 154, 547–555. Willey, D. L., Hunt, S. E., Cole, C. G., Coggill, P. C., Rice, C. M., Weintraub, M. S., Eisenberg, S., & Breslow, J. L. (1987). Dietary fat Ning, Z., Rogers, J., Bentley, D. R., Kwok, P. Y., Mardis, E. R., Yeh, clearance in normal subjects is regulated by genetic variation in R. T., Schultz, B., Cook, L., Davenport, R., Dante, M., Fulton, L., apolipoprotein E. Journal of Clinical Investigation, 80, 1571–1577. Hillier, L., Waterston, R. H., McPherson, J. D., Gilman, B., Young, V.R.,& Scrimshaw, N.S.(1979).Genetic and biological Schaffner, S., Van Etten, W. J., Reich, D., Higgins, J., Daly, M. J., variability in human nutrient requirements. American Journal of Blumenstiel, B., Baldwin, J., Stange-Thomann, N., Zody, M. C., Clinical Nutrition, 32, 486–500.