Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-18T07:42:58.422Z Has data issue: false hasContentIssue false

Biological models for phytochemical research: from cell to human organism

Published online by Cambridge University Press:  01 May 2008

Alicja Mortensen
Affiliation:
National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, SøborgDK-2860, Denmark
Ilona K. Sorensen
Affiliation:
National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, SøborgDK-2860, Denmark
Colin Wilde
Affiliation:
AvantiCell Science Ltd, GibbsYard Building, Auchincruive, Ayr KA6 5HW, Scotland, UK
Stefania Dragoni
Affiliation:
Department of Biomedical Sciences, University of Siena, Banchi di Sotto, Siena55 - 53110, Italy
Dana Mullerová
Affiliation:
Institute of Health Promotion, Medical faculty in Pilsen, Charles University, Lidicka 4, Pilsen301 66, Czech Republic
Olivier Toussaint
Affiliation:
Department of Biology, Unit of Cellular Biochemistry and Biology, University of Namur (FUNDP), Namur5000, France
Zdeněk Zloch
Affiliation:
Institute of Health Promotion, Medical faculty in Pilsen, Charles University, Lidicka 4, Pilsen301 66, Czech Republic
Giampietro Sgaragli
Affiliation:
Institute of Health Promotion, Medical faculty in Pilsen, Charles University, Lidicka 4, Pilsen301 66, Czech Republic
Jaroslava Ovesná*
Affiliation:
Crop Research Institute, Drnovská 507, Prague 6-Ruzyne161 06, Czech Republic
*
*Corresponding author: J. Ovesná, fax +42 02 33 02 22 86, email ovesna@vurv.cz
Rights & Permissions [Opens in a new window]

Abstract

Nutrigenomics represents a shift of nutrition research from epidemiology and physiology to molecular biology and genetics. Nutrigenomics seeks to understand nutrition influences on homeostasis, the mechanism of genetic predispositions for diseases, to identify the genes influencing risk of diet related diseases. This review presents some in vitro models applicable in nutrigenomic studies, and discuses the use of animal models, their advantages and limitations and relevance for human situation. In vitro and in vivo models are suitable for performance of DNA microarrays, proteomic and transcriptomic analyses. In vitro models (intracellular organelles and suborganellar compartments, cell cultures, or tissue samples/cultures) give insight in metabolic pathways and responses to test stimuli on cellular and molecular levels. Animal models allow evaluation of the biological significance of the effects recorded in vitro and testing of the hypothesis on how a specific factor affects specific species under specific circumstances. Therefore, the evaluation of the data in relation to human organism should be done carefully, considering the species differences. The use of in vitro and in vivo models is likely to continue as the effects of nutrition on health and disease cannot be fully explained without understanding of nutrients action at nuclear level and their role in the intra- and intercellular signal transduction. Through advances in cell and molecular biology (including genomic and proteomic), the use of these models should become more predictively accurate. However, this predictive value relies on an underpinning knowledge of the advantages and limitations of the model in nutrigenomic research as in other fields of biomedical research.

Type
Full Papers
Copyright
Copyright © The Authors 2008

It is widely recognized nowadays that human health is influenced by genetic and environmental factors, and that nutrition is of fundamental importance. Increasing incidence of so called “lifestyle diseases” like obesity, type 2 diabetes, cardiovascular disease (CVD) or cancer is recognized to be related to Western-style diet. Several reports indicate that a diet rich in vegetables and fruits and low in fat may protect against these diseases(Reference Donaldson1Reference Goh, Woodman, Pepe, Cao, Quin and Ritchie3). In the last two decades nutritionists have become increasingly aware of the significance of gene–nutrient interactions, and their possible use as tools to improve the health of the individual. Thus, the application of nutrigenomic analysis in nutrition represents an important paradigm shift in nutrition research, from epidemiology and physiology to molecular biology and genetics. Nutrigenomics (nutritional genomics) represents the junction between the health, diet, and genomics, and is focused upon genetic polymorphism and the interaction of the genome with diet(Reference Afman and Müller4). Nutrients are judged as potential signals, which influence cellular sensor systems to modify gene expression and subsequently metabolite production. Nutrigenomics seeks to understand how nutrition influences homeostasis and to identify the genes influencing risk of diet-related diseases as well as to understand the mechanism of the genetic predispositions for the diseases. For example, a nutrigenomics approach offers promise in modulating the risk of diseases of ageing because of the effects of certain nutrients on gene expression, through both epigenetic mechanisms or modification of transcription factors. Therefore it might be the first step to a personalised nutrition health policy.

It is accepted that the genetic material of each cell is not a rigid but a dynamic structure changing in response to various stimuli including food(Reference van den Veyver5). The knowledge of the genome and its expression in living organisms, coupled with the tools of molecular biology create the prospect of examining the health benefits of dietary phytochemicals on cellular level in in vitro model systems and scrutinizing the most potent compounds in in vivo model systems (animal models of cancer, atherosclerosis, diabetes) and in human subjects. In applying these various approaches there is an over-arching expectation that research is ethically-acceptable, and that researchers apply the three “Rs” (reduction, replacement, refinement)(Reference de Boom, Rennie, Buchanan-Smith and Hendriksen6) with respect to the use of animals in biological research.

Every human possesses a unique genotype reacting in its own way upon food contituents(Reference Ordovacs and Corella17, Reference Buttriss, Hughes, Colette and Stanner8). Clearly, it is impossible for practical reasons to study response to food constituents for each individual separately, and so the interaction of nutrition with mammalian gene expression is routinely studied in model systems, whose cellular and molecular biology can be defined in qualitative and (preferably) quantitative terms. Depending on the question to be elucidated, a model can consist of cell structures, cell cultures, tissue sample/culture (in vitro models) or of group of living organisms like animals or humans (in vivo models). Both in vitro and in vivo model systems are suitable for performance of DNA microarrays, proteomics and transcriptomics analyses.

This review presents some of the in vitro and in vivo models, which are applicable for studies of biological effects of phytochemicals on gene expression, cellular metabolism, activity of enzymes metabolizing xenobiotics, clinical biomarkers and end points of lifestyle diseases (e.g. cancer, atherosclerosis), and discusses the use of animal models, their advantages, limitations and relevance to the human situation.

In vitro models

In vitro models are based on the use of intracellular organelles and suborganellar compartments, cell cultures, or tissue slice/organoid bioassays. Studies in such model systems give insight into responses to the tested factors on a cellular level. This insight and its overall value must, however, be tempered by recognition of the limitations of the model system, not least whether it can be considered of physiological relevance or indicative of the biology of a multi-organellar environment in vivo. In this section we review the advantages and limitations of a range of in vitro systems in ascending degree of sophistication.

Microsomes, a small inclusion of ribosomes and fragments of the endoplasmic reticulum (ER) serves as example of a subcellular in vitro model. Microsomes are broadly used to investigate the metabolising actions of the phase I and phase II xenobiotic-metabolising enzymes, which typically include the cytochrome P450 isoforms. Testing of nutritional factors in this cell-free system can indicate likely patterns of metabolism, but is not necessarily indicative of the fate of the test molecule in a more complex environment, not least one in which cellular uptake is a significant factor.

Yeast, as an eukaryotic organism, represents a simple but useful model genome of which is fully sequenced and individual metabolic pathways are well know. At present several precisely defined mutant and transformed lines exist. The advantage of this model system is that growth conditions can be fully controlled and response upon stimuli easily measured. Therefore yeast has been successfully used e.g. as a model system for screening of phytochemicals for estrogenic activity(Reference Breinholt and Larsen9).

Cell lines of various origin, some of which may be clonally derived from single cells have some attraction for the study of gene–nutrient interactions. With careful control of cell passaging and culture conditions, the availability of a homogeneous cell population can offer advantages in terms of reproducibility of response and experiment replication. The practical convenience of an easily-handled and renewable test platform is also suited to medium to high-throughput, should screening of large number of test molecules be required. On the other hand, cell lines may have been in culture for extended periods (months, years or decades), and through de-differentiation and/or genetic damage can bear little or no resemblance to their tissue of origin.

One example of a cell line frequently used in nutritional modelling is the Caco-2 cell line. Caco-2 is derived from human colorectal carcinoma but it retains many of the morphological features typical for normal human enterocytes(Reference Pinto, Robine-Leon, Appay, Kedinger, Triadou, Dussaulx, Lacroix, Simon-Assmann, Haffen, Fogh and Zweibaum10). Caco-2 cells have been extensively studied and there is a considerable literature concerning their characteristics(Reference Hidalgo and Borchardt11Reference Jumarie and Malo18). Caco-2 cells may serve as a model system for predicting intestinal absorption of drugs or nutraceuticals(Reference Artrusson19Reference Trotter and Storch20) and are also used for evaluating of dietary constituents as well as food additives, contaminants, toxicants and oxidants and for testing of possible anti-cancer/protective effects of phenolic compounds(Reference Giovannini, Straface, Modesti, Coni, Cantafora, de Vincenti, Malorni and Masella21). The advantage of this test system is that the cells are of human origin, and that experiments can be carried out over a relatively long period permitting the reversibility of any effects to be assessed(Reference Anderberg and Artursson22). The Caco-2 cell line is also the basis of the so-called follicle associated epithelium (FAE), consisting of co-culturing of Caco-2 cells with human B lymphoma Raji cells to induce Caco-2 cells differentiation into M cells(Reference des Rieux, Fievez, Théate, Mast, Préat and Schneider23). The FAE model may be useful for study of potential toxicological effects on the human gut epithelium of different nanoparticles and their potential capacity to cross the intestinal epithelium.

A second example of a cell line in widespread use for nutritional/metabolic studies is the human hepatoma cell line HepG2(Reference Aden, Fogel, Plotkin, Damjanov and Knowles24) and its sub-clones. HepG2 continues to find application in the evaluation of a range of nutritional factors, including spice constituents(Reference Cao, Liu, Jia, Zhou, Kong, Yang, Jiang, Li and Zhong25), soybean derivatives(Reference Carter, Taylor, Prendergast, Zimmerman, Von Furstenberg, Moore and Karpen26) and tuber essential oils(Reference Chung, Woo Park, Heon Kim, Kim, Pill Baek, Bang, Choi and Lee27), as well as providing a means of evaluating medicinal materials from natural sources(Reference Gomes, Giri, Kole, Saha, Debnath and Gomes28, Reference Westerink and Schoonen29). However, whilst a valuable tool, the HepG2 cell line does not necessarily reflect faithfully the performance of test materials in vivo. Cytochrome P450 enzyme activities and Phase II metabolic functions are relatively low, and a recent study demonstrated the failure of HepG2 cultures to detect compounds with known toxicity in primary hepatocytes or in vivo (Reference Westerink and Schoonen30).

Recognition of the limitation of cell lines as models of metabolic performance in vivo is increasingly encouraging investment in the production of fresh or cryopreserved primary cell cultures prepared from animal or human tissues. For instance, cultured endothelial cells and macrophages can be applied as in vitro model for studying flavonoids in redox-dependent gene expression(Reference Rimbach, Saliou, Canali and Virgilli31). The technology for enzymic tissue digestion and cell isolation is well-established for many animal tissues, including liver and intestine, from a range of species(Reference Mashek and Grummer32, Reference Rusu, Loret, Peulen, Mainil and Dandrifosse34), and with it the potential to cryopreserve cells with retention of xenobiotic-metabolising activity (see, for example, Stevenson et al. (Reference Stevenson, Morgan, Goldie, Connel and Grant35)). Increasing access, with appropriate ethical permission, to human tissue is similarly enabling the isolation and use of human cells which can, under appropriate conditions, retain a differentiated phenotype in culture for days and even weeks(Reference Baten, Sakamoto and Shamsuddin36, Reference Pichard, Raulet, Fabre, Ferrini, Ourlin and Maurel37). The benefit of such a primary cell-culture approach in nutritional research was demonstrated as much as 30 years ago in cultured skin fibroblasts, whose use led to discovery of the low-density lipoprotein receptor (LDLR) on the cell surface, and facilitated understanding of endogenous pathways in cholesterol metabolism(Reference Goldstein and Brown38).

It has long been recognised that use of freshly isolated cells is not by itself sufficient to confer physiological relevance on data obtained using these cultures. Primary cell performance is dependent on their microenvironment and their potential for paracrine interaction with neighbouring cells of the same or different cell type. One way to reproduce these microenvironmental influences in vitro, not least for nutrigenomic research, is to avoid cell dissociation through the use of organ slices or tissue explants. Organ slices represent a multicellular three-dimensional in vitro model, which possesses the biologically-relevant structural and functional features of in vivo tissues through the presence of various cell types in an architectural organization that supports both cell–cell and cell–extracellular matrix interactions. Organ slice methodology is readily adaptable to various organs and various species. The availability of human tissue for organ slice studies augments the utility of this model, and provides an important bridge between animal-derived data and the human situation. Precision-cut tissue slices are increasingly being used in toxicology(Reference de Kanter, Olinga, de Jager, Merema, Meijer and Groothius39, Reference Lerche-Langrand and Toutain40), to evaluate the toxicity of chemicals(Reference Miller, Beyer, Hall, De Graffenried and Adams41Reference van de Bovenkamp, Groothuis, Draaisma, Merema, Bezuijen, Van Gils, Meijer, Friedman and Olinga43), to evaluate the genotoxic and antigenotoxic potential of chemicals(Reference Baumann, Kerdar, Cramer, Feser, Blode, Salomon and Kuhnz44, Reference Lake, Beamand, Tredger, Barton, Renwick and Price45), to unravel the metabolic pathways of xenobiotics(Reference Ekins46), to study the regulation of enzyme systems such as the cytochromes P450(Reference Meredith, Scott, Renwick, Price and Lake47), to investigate the hepatic uptake of drugs(Reference Onderwater, Commandeur, Rooseboom and Vermeulen48), activation of signalling pathways(Reference Pfaff, Powaga, Akinci, Schutz, Banno, Wiegand, Kummer, Wess and Haberberger49) and to determine chemically-induced apoptosis(Reference Moronvalle-Halley, Sacre-Salem, Sallez, Labbe and Gautier50). This broad spectrum of potential applications for precision-cut tissue slices in nutrigenomic research is likely to promote their use in future nutrigenomic research.

In many cases, the demonstrable metabolic performance of tissue slices will outweigh their inherent disadvantage of short functional lifespan and unsuitability for medium to large-scale analysis. In other circumstances, where treatment periods of more than a few hours are required, or volume and throughput of samples are important, technology development has focused on the creation in cell culture of conditions that elicit in vivo cellular responses. At its simplest, this involves the use of biological substrata such as collagen or reconstituted basement membrane for cell attachment(Reference Kleinman, McGarvey, Hassall, Star, Cannon, Laurie and Martin51) or through co-culture with helper cells, or both(Reference VanHaecke and Rogiers52). More recently, biocompatible substrata have offered the possibility of creating architecturally-sophisticated 3-dimensional cell cultures. For study of transport phenomena this may involve the use of a biocompatible membrane, suitably coated with collagen or other extracellular matrix components, onto which the cells of choice are seeded. With this approach primary cultures of epithelial cells can become polarised, displaying distinctive basal and apical surfaces (the former forming the substratum anchorage) and demonstrating the vectorial transport characteristics of an epithelial monolayer. One example of such a system utilises mammary epithelial cells to recreate the lactating epithelium, allowing study of the transport of xenobiotics from the bloodstream into milk (C Wilde; unpublished).

The adaptation of technology aimed principally at tissue regeneration is, in addition, progressively creating 3-dimensional, biocompatible cell scaffolds in which cells can be seeded, grown and encouraged to reproduce the functions of their tissue of origin. This biomaterials technology can take the form of fibrous scaffolds spun in 3 dimensions, and may also incorporate fibre coatings that promote, for example, cell attachment or particular cell functions. Such technology has, for example, been applied to enhance cytochrome P450 activity in primary hepatocyte cultures(Reference Chua, Tang, Quej, Ramakrishna, Leong and Mao53). Indeed, for hepatocytes alone, numerous other approaches to the creation of 3-D cultures are currently under development, based variously on hydrogels(Reference Turner, Schmelzer, McClelland, Wauthier, Chen and Reid54), poly-lactic acid(Reference Huang, Hanada, Kojima and Sakai55), alginates(Reference Elkiyam, Amitay-Shaprut, Dvir-Ginsburg, Harel and Cohen56) or chitosan(Reference Li, Pan, Zhang, Guo and Yu57) amongst many other materials.

Combination of biomaterials technology with stem cell science is opening up new opportunities for tissue regeneration, and with it a further in vitro option for cell-based analysis through the generation of differentiated cell types from stem cell lineages. With this approach, scaffold composition and architecture can, for example, direct the maturation of hepatocyte progenitor cell lines, with realisation of cytochrome P450 activities(Reference Semino, Merok, Crane, Panagiotakos and Zhang58). This approach has the considerable attraction of a renewable source of normal human cells with consistent performance, albeit with the caveat that extensive research and development is still required to define the soluble and fixed-scaffold cues that elicit a stable, differentiated phenotype(Reference Beckstead, Santosa and Giachelli59, Reference Mei, Goldberg and Anderson60).

While in vitro studies give insight into responses at a cellular level, they are not able to provide definitive information on how the studied factor may affect the organism as a whole. Thus, the biological significance of an effect at the gene level observed in vitro should be further assessed in in vivo test(s) involving whole organisms, where exposure to a nutritional factor for instance dietary phytochemical is evaluated systemically through application of metabolomics, and pharmacokinetics such that gene–nutrient interactions of the test substance are demonstrably the aggregate of primary action at an organellar level and any secondary response due to inter-organellar cross-talk.

Animals in nutritional research

To bridge the gap between in vitro test systems and the whole organism, and to overcome the obvious constraints of human clinical studies, animal studies are widely applied in nutrition research. Animal studies can be performed in a relatively short time, enabling chronic study, potentially from in utero-exposure to death, and also research into inter-generational effects. Such pre-clinical studies, which may measure validated biomarkers of nutritional response, can be supported by post mortem examination of end-points, and further investigations on molecular level on gene expression patterns in sampled tissues. The influence of environmental factors on the results is minimised by standardization of laboratory conditions and the use of the subjects (organisms) with known genetic and health status, so called “defined animals”(Reference Öbrink and Rehbinde61).

Relevance of animal studies

Nutrigenomics provide powerful approaches to investigate the relationship between dietary factors and genes, providing insight into how test compounds affect gene-expression patterns (transcriptome), organisation of the chromatin (epigenome), protein expression paterns, including post-translational modifications (proteome), as well as metabolite profile (metabolome). In this regard, laboratory animals are used as complex biological instruments to obtain knowledge on gene–nutrient interaction, whilst always recognising that extrapolation to human biology must be done with caution and recognition of sometimes-fundamental species differences. While recognising that phenomena studied in one species can sometimes be extrapolated to another(Reference Meyer, Svendsen, Hau and van Hoosier62), and recognising that present knowledge of human biochemistry, physiology, endocrinology and pharmacology relies fundamentally on studies in animal models(Reference Coffey, Isaacs and Murphy63), and that several advances in nutrigenomics were made using murine animal models(Reference Mutch, Wahli and Williamson64), it is important to stress, that animal studies including nutrigenomic research are not inherently predictive of the human situation. Animal studies can neither confirm nor refute hypotheses about human physiology or pathology; human clinical investigation is the only way to test such hypotheses.

The purpose of animal studies is to test hypothesis on how the specific factor affects the specific species under specific circumstances. Their value is speeding up the process of discovery by generation of ideas or suggesting hypotheses that might be relevant to humans, assistance in predicting effects in humans, and providing support for particular conclusions reached in the population studies. The differences in biological characteristics (e.g. anatomy, physiology, metabolic rate) between animals and man should be kept in mind while studying qualitative questions devoted to identification of the diet component responsible for a specific function in the body, or quantitative questions concerning a dose of a diet component necessary to cause the specific reaction in the body. In this regard a comparative biology continues to be a useful tool for choosing an appropriate animal model.

Animal models

A widely accepted scientific definition of an animal model is as a living organism in which normative biology or behaviour can be studied, or in which a spontaneous or induced pathological process can be investigated, and in which the phenomenon in one or more respects resembles the same phenomenon in humans(Reference Wessler65).

Based on this definition, animal models can be categorised in five groups: (1) normative, (2) spontaneous models in which the phenomenon under investigation occurs spontaneously e.g. ApcMin mice a model of human adenomatous poliposis coli(Reference Moser, Pitot and Dove66), or a Watanabe Heritable Hyperlipidemic (WHHL) rabbit a model of human familiar hypercholesterolemia(Reference Goldstein, Kita and Brown67), (3) experimental models in which the phenomenon is induced either chemically e.g., 1,2-dimethylhydrazine dihydrochloride or azoxymethane induced colon cancer in rats, or surgically e.g. uraemia induced by nephrotectomy, or by a genetic manipulation e.g. TG.NK mice with MMTV/C-neu transgene as a model of breast cancer(Reference Muller, Sinn, Pattengale, Wallace and Leder68), (4) negative models in which the phenomenon never occurs/is suppressed either as consequence of normative physiology e.g. dog in atherosclerosis research, or due to genetic manipulation e.g. mice lacking the S100A4(mts1) gene have suppressed tumour development and lack of metastases(Reference Grum-Schwesen, Klingeholhofer, Berg, El-Naaman, Grigorian, Lukanidin and Ambartsumian69) and (5) orphan models where a disease is first recognised and described in an animal species, after which a human counterpart may emerge(Reference Thomsen, Almstrup, Nielsen, Sørensen, Petersen, Leffers and Breinholt70).

As an example of application of normative animal model to study biological effects of phytochemicals an investigation of influence of isoflavone intake on mammary gland morphogenesis and gene expression profile in the juvenile mammary gland of mice can be given(Reference Lund, Mortensen, Nilas, Breinholt, Larsen and Ottesen71). A study of soy isoflavones effect on gene expression of endothelial nitric oxide synthase in cerebral arteries in Watanabe heritable hyperlipidemic rabbits(Reference Lund, Mortensen, Nilas, Breinholt, Larsen and Ottesen72) is an example of application of a spontaneous model of human disease (familial hypercholesterolemia) to investigate health beneficial effects of phytochemicals. Similarly studies of effect of lignans or soy isoflavone on intestinal neoplasia in Apc Min mice(Reference van Kranen, Mortensen, Sørensen, van den Berg-Wijnands, Beems, Nurmi, Adlercreutz and van Kreijl73, Reference Sørensen, Kristiansen, Mortensen, Nicolaisen, Wijnands, van Kranen and van Kreijl74) are examples of application of a spontaneous model, while investigations of cancer-preventing effect of soy and/or isoflavones in rats induced by dimethylbenz[a]anthracene(Reference Mukhopathyay, Ballard, Mukherjee, Kabir and Das75), or DMBA(Reference Day, Besch-Williford, McMann, Hufford, Lubahn and MacDonald76, Reference Rowlands, HeL, Hakkak, Ronis and Badger77) or in transgenic TG.NK mice(Reference Thomsen, Mortensen, Breinholt, Lindecrona, Penalvo and Sørensen78) illustrate application of so called experimental models to study cancer-preventive potential of phytochemicals.

Choice of the animal model

The decision to use an animal model in nutritional research will be informed, first, by the non-availability of ethically more acceptable in vitro alternatives. Thereafter, the choice of model will depend on their validity with respect to the nature of phenomenon under study and its expression in the biology of the chosen species. An additional consideration will be the practical aspects of the experimental procedure, husbandry and economic considerations. All these factors are routinely considered within legislative frameworks (which vary by country and institution), which ensure sound ethical practice.

When using animal models it is necessary to recognize their predictive validity (performance in the animal study predicts performance in real (non-experimental) conditions), face validity (phenomenological analogy with the modelled condition) and construct validity (the model has a sound theoretical rationale).

Biology of the chosen species

In considering the biology of the chosen species, it is essential that characterization of the biological system is sufficient to allow sound interpretation of the results. Therefore the chosen species should have defined genetic characteristics. The use of outbred and inbred strains should be considered as both have their advantages and limitations. In general outbred strains are recognized to represent populations, which are more likely to mimic the genetic diversity in human populations. The use of inbred strains is believed to minimalize the inter-individual variation in the response to a studied factor allowing smaller experimental groups and with attraction for mechanistic studies.

The anatomy, biochemistry and physiology should be close to those of man with regard to the dietary requirements and function of digestive system (Table 1). The differences in metabolic rates between the laboratory animal species and between the chosen species and humans should be considered. The latter is important in choice of the dose of test compound for animal dietary interventions(Reference Freireich, Gehan, Rall, Schmidt and Skipper79, Reference Hau and Poulsen80), and an appropriate animal versus human compensation factor should be applied (Table 2).

Table 1 Selected variables and characteristics relevant when choosing a laboratory species as a model in nutrition research

a The presented values are a guidance for repeated blood sampling at weekly intervals. The volume of a sample corresponds to approximately 7.5 % of total blood volume, and to 0·5 % of body weight.

b The normal quantum drawn from blood donors.

c The cost of a pig exceeds that of laboratory rodent. Pigs need more space and special housing facilities, and large quantities of feed and of test compounds compared to laboratory rodents. Thus availability of facilities for housing and expenses to experimental feed/test compounds should be considered.

* Rats do not have a bile bladder.

Table 2 Mouse dosage compensation factor – examples

The type of experimental diet and feeding regimens (ad libitum versus diet restriction or pair feeding) should also be considered(Reference Rao81). Factors to consider include the choice between the standard fixed open-formula diets based on natural plant ingredients and therefore containing diverse phytochemicals like phytoestrogens, isoflavones and lignans, respectively(Reference Thigpen, Li, Richter, Lebetkin and Jameson82, Reference Degen, Janning, Diel and Bolt83), or purified semi-synthetic or synthetic diets. These diets are composed of a refined, invariant, and restricted set of ingredients, which offer less variable and more easily controlled experimental conditions. Additionally, the use of purified or synthetic diets instead of natural ingredient chows, gives more precise control over the metabolizable energy, dietary composition of nutrient, and provides better repeatable experimental conditions(Reference Ritskes Hoitinga84). On the other hand, casein in purified semi-synthetic diet aggravates hypercholesterolemia in rabbit models of atherosclerosis(Reference Hausner, Schlingmann, Chen, Gillies, Kieras, Ross and van Pelt85) and can therefore mask potential hypocholesterolemic effects of phytochemicals in a rabbit model of atherosclerosis or naturally occurring phytochemicals in standard laboratory chow may be confounding factors in studies of anti-atherogenic effects of phytochemicals(Reference Frederiksen, Mortensen, Schrøder, Frandsen, Bysted, Knuthsen and Rasmussen86) or in studies of other biological effects of test phytochemicals. Switching from standard laboratory chow to purified diet (and vice versa) changes the gut flora, which may lead to altered endogenous vitamin synthesis. Furthermore, the occurrence of common contaminants in natural-ingredient non-purified (standard) diets such as heavy metals (e.g. Pb and As), N-nitrosamines, residua of pesticides and antioxidants (BHA and BHT) may serve to confound experiment outcomes(Reference Rao and Knapka87).

An optimal diet for laboratory animals should have adequate concentrations of all the nutrients for growth and maintenance without substantial excess of high energy and growth-enhancing nutrients such as fat and protein. However, depending on the aim of the study, it is an open question if the experimental diet should be a standard for the chosen species or should mimic the human Western diet with regard to fat, fibre, and calcium content(Reference Saarinen, Bingham, Lorenzetti and Mortensen88). Feeding a Western style diet instead of a standard chow diet to a rodent model of cancer can exacerbate cancer development(Reference Luijten, Thomsen, van den Berg, Wester, Verhoef, Nagelkerke, Adlercreutz, van Kranen, Piersma, Sørensen, Rao and van Kreijl89). While choosing the feeding regimens it is worthwhile remembering that diet restriction may modify the responses to (phyto)chemicals, and that the practice is labour-intensive.

Another potential source of experimental variation can arise from homeostatic compensatory reactions, which can result in low precision and scattering of results and even misinterpretations(Reference Öbrink and Rehbinde61).

In conclusion, whilst nutrigenomic studies in animal models have value in predicting the human situation, their use must be justified on sound biological criteria, on practical grounds (with respect to housing, feeding and intervention for sample collection) and from an ethical perspective (availability of alternatives, and predictive value). Ultimately, the effects observed in animal models should be demonstrated in humans.

Human studies

Human nutritional studies can be divided into intervention studies (trials), which under defined circumstances (such as clinical trials), apply nutritional intervention and measure the biological outcome (effect), and observational epidemiological studies, divided into descriptive (correlational, case report-series, cross sectional) and analytical experimentation (case–control, cohort), and meta-analyses. Studies, according to study design, may be prospective or retrospective and may use epidemiological instruments to evaluate biological outcome of an identified nutritional factor or nutrition–genomic relationship.

Intervention studies

Intervention studies differentiate between double blind/(nonblinded) and randomized/(non-randomized) controlled trials. Nutritional trials in human volunteers may typically examine the biological effects of nutrient/nutrients [as e.g. glucan enriched fruit juice(Reference Naumann, van Rees, Önning, Öste, Wydra and Mensink90) or polyphenols in olive oils(Reference Covas, Nyyssönen and Poulsen91)], or whole foodstuffs [e.g. dried cranberry juice(Reference Valentová, Stejskal, Bednár, Vostálová, Číhalík, Večerová, Koukalová, Kolár, Reichenbach, Škňourilová, Ulrichová and Šimánek92)] or food commodities [e.g. vegetables and fruit(Reference John, Ziebland, Yudkin, Roe and Neil93, Reference Watzl, Girrbach and Roller94)] or the effect of different, albeit sometimes imprecisely defined types of diet [e.g.Mediterranean-style(Reference Estruch, Martinez-Gonzales and Corella95) or low fat dietary pattern(Reference Beresford, Johnson and Ritenbaugh96)]. The principle of a nutrigenomic approach i.e. an investigation of whether certain nutrients have direct effects on gene expression is exemplified by a randomised controlled trial studying the effect of omega-3, omega-6, and omega-9 unsaturated fatty acids on unstimulated and stimulated monocytes cytokine gene expression(Reference Baumann, Hessel, Larass, Müller, Angerer, Kielf and von Schacky97), and by a trial of conjugated linoleic acid supplementation(Reference Mullen, Moloney, Nugent, Doyle, Cashman and Roche98). Another type of nutrigenomic approach may test a hypothesis that, for example, a particular gene polymorphism is more or less indicative of a biological outcome determined by special type of diet/nutrients. This type of study is represented by work on human volunteers identifying the cholesterol 7-hydroxylase (CYP7A1) gene and its role in determining the LDL-cholesterol (LDL-C) concentration response to a high-fat diet(Reference Kovar, Suchanek, Hubacek and Poledne99).

Observational epidemiological studies

A particularly critical point in nutritional epidemiology is the ability of the epidemiological instrument to measure habitual dietary intake. Dietary-assessment instruments are used in nutritional descriptional or analytical studies. An example of a descriptive cross sectional study is the study dealing with the fruit and vegetable intakes and bone density(Reference Prynne, Mishra, O'Connell, Muniz, Laskey, Yan, Prentice and Ginty100) or a population-based study on diabetes mellitus and serum carotenoids(Reference Coyne, Ibiebele, Baade, Dobson, McClintock, Dunn, Leonard and Shaw101).

Analytical, case–control nutritional studies are based on long-term recall of feeding history. They are especially valid for assessment of gene–environment interactions, where there is a critical demand to improve the accuracy in measurements of both genetic and nutritional factors.

Meta-analyses of observational studies try on a comprehensive, systematic bibliographic search of published medical literature to arrive at quantitative conclusions about the contribution of nutritional factors to the occurrence of disease, for example the relationship between fruit and vegetable intake and the occurrence of oral cancer(Reference Pavia, Pileggi, Nobile and Angelillo102).

Summarizing the current knowledge and experience within the nutrition research in human studies indicates that methodological as well as heuristic limits of epidemiological (including interventional) and clinical trials have been reached. The effects of nutrition on health and disease cannot be fully explained without a more comprehensive understanding of how nutrients act at nuclear level and what role they play in the intra- and intercellular signal transduction.

Concluding remarks

Direct, definitive information on the effects of dietary factors, whether they be nutritional or non-nutritional dietary components, on human health can only be obtained through investigation in human subjects. However, the obvious ethical and practical limitations of interventionist human studies limit their applicability. Because of these limitations, intervention trials in healthy subjects and patients often provide information only on early or short-lasting biological effects of the treatment. In consequence, the duration of the intervention is usually much too short to allow study of patho-physiological end-points of interest (e.g. development of tumours or atherosclerotic lesions), and therefore disease indicators are typically measured as clinico-chemical biomarkers. Furthermore, the confounding factors of lifestyle and poor compliance of human subjects with the study protocol may influence the results obtained. Epidemiological studies can be resource-effective but time-consuming, and interpretation of the results is difficult because of the multifactorial nature of the effect. Other more technical obstacles also exist.

The limitations related to human studies are the reason for using alternative model systems in nutritional research and nutrigenetics. Well-characterized in vitro model systems give insight in metabolic pathways and responses to test stimuli on cellular and molecular levels, while studies in animal models permit evaluation of the biological significance of the effects recorded in in vitro studies. Human nutritional trials may then become justifiable, based on primary knowledge obtained from studies in vitro, animal models or observational epidemiological studies.

Nutrigenomics will promote an increased understanding of how nutrition influences metabolic pathways and homeostatic control, how this regulation is disturbed in the early phases of diet-related disease, and the extent to which individual sensitizing genotypes contribute to such diseases. Keeping in mind the limitations of human studies, the use of in vitro and in vivo models will continue and, through advances in cell and molecular biology (including genomic and proteomic), should become more predictively accurate. However, this predictive value relies on an underpinning knowledge of the advantages and limitations of the model in nutrigenomic research as in other fields of biomedical research.

Acknowledgements

The publication of this paper was made possible by the financial support of the European Co-operation in the field of Scientific and Technical (COST) Research Action 926 “Impact of new technologies on the health benefits and safety of bioactive plant compounds” (2004–2008) and the projects of the Czech Ministry of Education 1P05OC054 and MZe 002700602. The authors had no conflicts of interest to disclose.

References

1Donaldson, MS (2004) Nutrition and cancer: a review of the evidence for anti-cancer diet. Nutr J 3, 19, Published online 2004 October 20. doi: 10.1186/1475-2891-3-19. Available fromhttp:/www.nutritionj.com/content/3/1/19.CrossRefGoogle ScholarPubMed
2Alonso, A & Martínez-González, MA (2004) Olive oil consumption and reduced incidence of hypertension: The SUN study. Lipids 39, 12331238.CrossRefGoogle ScholarPubMed
3Goh, SSC, Woodman, OL, Pepe, S, Cao, AH, Quin, C & Ritchie, RH (2007) The red wine antioxidant resveratrol prevents cardiomyocyte injury following ischemia-reperfusion via multiple sites and mechanisms. Antioxid Redox Signal 9, 101113.CrossRefGoogle ScholarPubMed
4Afman, L & Müller, M (2006) Nutrigenomics: from molecular nutrition to prevention of disease. J Am Diet Assoc 106, 569576.CrossRefGoogle ScholarPubMed
5van den Veyver, IB (2002) Genetic effects of methylation diets. Annu Rev Nutr 22, 255282.CrossRefGoogle ScholarPubMed
6de Boom, MJ, Rennie, AE, Buchanan-Smith, HM & Hendriksen, CFM (2005) The interplay between replacement, reduction and refinement: Considerations where the three Rs interact. Anim Welf 14, 327332.CrossRefGoogle Scholar
7Ordovacs, JM & Corella1, D (2004) Nutritional genomics. Annu Rev Genomics Hum Genet 5, 71118.CrossRefGoogle Scholar
8Buttriss, JL, Hughes, J, Colette, NMK & Stanner, S (2002) Antioxidants in food: a summary of the review conducted for the Food Standards Agency 2002, British Nutrition Foundation. Nutr Bull 27, 227236.CrossRefGoogle Scholar
9Breinholt, V & Larsen, JC (1998) Detection of weak estrogenic flavonoids using a recombinant yeast strain and a modified MCF7 cell proliferation assay. Chem Res Toxicol 11, 622629.CrossRefGoogle Scholar
10Pinto, M, Robine-Leon, S, Appay, M-D, Kedinger, M, Triadou, N, Dussaulx, E, Lacroix, B, Simon-Assmann, P, Haffen, K, Fogh, J, Zweibaum, A, et al. (1983) Enterocyte-like differentiation and polarization of the human colon carcinoma cell line Caco-2 in culture. Biol Cell 47, 323330.Google Scholar
11Brandsch, M, Miyamoto, Y, Ganapathy, V & Leibach, FH (2004) Expression and protein kinase C-dependent regulation of peptide/H+ co-transport system in the Caco-2 human colon carcinoma cell line. Biochem J 299, 253260.CrossRefGoogle Scholar
12Hidalgo, IJ & Borchardt, RT (1990) Transport of bile acids in a human intestinal epithelial cell line, Caco-2. Biochim Biophys Acta 1035, 97103.CrossRefGoogle Scholar
13Yamamoto, T, Seino, Y, Fukumoto, H, Koh, G, Yano, H, Inagaki, N, Yamada, Y, Inoue, K, Manabe, T & Imura, H (1990) Over-expression of facilitative glucose transporter genes in human cancer. Biochem Biophys Res Commun 170, 223230.CrossRefGoogle ScholarPubMed
14Hochman, JH, Fix, JA & LeCluyse, EL (1994) In vitro and in vivo analysis of the mechanism of absorption enhancement by palmitoylcarnitine. J Pharmacol Exp Ther 269, 813822.Google ScholarPubMed
15Grasset, E, Pinto, M, Dussaulx, E, Zweibaum, A & Desjeux, JF (1984) Epithelial properties of human colonic carcinoma cell line Caco-2: electrical parameters. Am J Physiol Cell Physiol 247, C260C267.CrossRefGoogle ScholarPubMed
16Pinto, M, Appay, MD, Simonassmann, P, Chevalier, G, Dracopoli, N, Fogh, J & Zweibaum, A (1982) Enterocytic differentiation of cultured human-colon cancer-cells by replacement of glucose by galactose in the medium. Biol Cell 44, 193196.Google Scholar
17Chantret, I, Barbat, A, Dussaulx, E, Brattain, MG & Zweibaum, A (1988) Epithelial polarity, villin expression, and enterocytic differentiation of cultured human colon carcinoma cells: a survey of twenty cell lines. Cancer Res 48, 19361942.Google Scholar
18Jumarie, C & Malo, C (1991) Caco-2 cells cultured in serum-free medium as a model for the study of enterocytic differentiation in vitro. J Cell Physiol 149, 2433.CrossRefGoogle Scholar
19Artrusson, P (1990) Epithelial transport of drugs in cell culture. I: a model for studying the passive diffusion of drugs over intestinal absorptive (Caco-2) cells. J Pharm Sci 79, 476482.CrossRefGoogle Scholar
20Trotter, PJ & Storch, J (1991) Fatty acid uptake and metabolism in a human intestinal cell line (Caco-2): comparison of apical and basolateral incubation. J Lipid Res 32, 293304.CrossRefGoogle Scholar
21Giovannini, C, Straface, E, Modesti, D, Coni, E, Cantafora, A, de Vincenti, M, Malorni, W & Masella, R (1999) Tyrosol, the major olive oil biophenol, protects against oxidized-LDL induced injury in Caco-2 Cells. J Nutr 129, 12691276.CrossRefGoogle ScholarPubMed
22Anderberg, EK & Artursson, P (1993) Epithelial transport of drugs in cell culture. VIII: Effects of the pharmaceutical surfactant excipient sodium dodecyl sulphate on cell membrane and tight junction permeability in human intestinal epithelial (Caco-2) cells. J Pharm Sci 82, 392398.CrossRefGoogle Scholar
23des Rieux, A, Fievez, V, Théate, I, Mast, J, Préat, V & Schneider, YJ (2007) An improved in vitro model of human intestinal follicle-associated epithelium to study nanoparticle transport by M cells. Eur J Pharm Sci 30, 380391.CrossRefGoogle ScholarPubMed
24Aden, DP, Fogel, A, Plotkin, S, Damjanov, I & Knowles, BB (1979) Controlled synthesis of HBsAg in a differentiated human liver carcinoma-derived cell line. Nature 282, 615616.CrossRefGoogle Scholar
25Cao, J, Liu, Y, Jia, L, Zhou, HM, Kong, Y, Yang, G, Jiang, LP, Li, QJ & Zhong, LF (2007) Curcumin induces apoptosis through mitochondrial hyperpolarization and mtDNA damage in human hepatoma G2 cells. Free Radic Biol Med 43, 968975.CrossRefGoogle ScholarPubMed
26Carter, BA, Taylor, OA, Prendergast, DR, Zimmerman, TL, Von Furstenberg, RV, Moore, DD & Karpen, SJ (2007) Stigmasterol, a soy lipid-derived phytosterol, is an antagonist of the bile acid nuclear receptor FXR. Pediatr Res 62, 301306..CrossRefGoogle ScholarPubMed
27Chung, MJ, Woo Park, K, Heon Kim, K, Kim, CT, Pill Baek, J, Bang, KH, Choi, YM & Lee, SJ (2008) Asian plaintain (Plantago asiatica) essential oils suppress 3-hydroxy-3-methyl-glutaryl-co-enzyme A reductase expression in vitro and in vivo and show hypocholesterolaemic properties in mice. Br J Nutr 99, 6775.CrossRefGoogle Scholar
28Li, LM, Weng, ZY, Huang, SX, Pu, JX, Li, SH, Huang, H, Yang, BB, Han, Y, Xiao, WL, Li, ML, Han, QB & Sun, HD (2007) Cytotoxic ent-Kauranoids from the medicinal plant Isodon xerophilus. J Nat Prod 70, 12951301.CrossRefGoogle ScholarPubMed
29Gomes, A, Giri, B, Kole, L, Saha, A, Debnath, A & Gomes, A (2007) A crystalline compound (BM-ANF1) from the Indian toad (Bufo melanostictus, Schneider) skin extract, induced antiproliferation and apoptosis in leukemic and hepatoma cell line involving cell cycle proteins. Toxicon 50, 835849.CrossRefGoogle ScholarPubMed
30Westerink, WM & Schoonen, WG (2007) Cytochrome P450 enzyme levels in HepG2 cells and cryopreserved primary human hepatocytes and their induction in HegG2 cells Toxicol In Vitro 21, 15811591.CrossRefGoogle Scholar
31Rimbach, G, Saliou, C, Canali, R & Virgilli, F (2001) Interaction between cultured endothelial cells and macrophages: in vitro model for studying flavonoids in redox-dependent gene expression. Methods Enzymol 335, 387397.CrossRefGoogle ScholarPubMed
32Mashek, DG & Grummer, RR (2004) Effect of conjugated linoleic acid isomers on lipid metabolism and gluconeogenesis in monolayer cultures of bovine hepatocytes. J Dairy Sci 87, 6772.CrossRefGoogle ScholarPubMed
33Papeleu, P, Vanhaecke, T, Henkens, T, Elaut, G, Vinken, M, Snykers, S & Rogiers, V (2006) Isolation of rat hepatocytes. Methods Mol Biol 320, 229237.Google ScholarPubMed
34Rusu, D, Loret, S, Peulen, O, Mainil, J & Dandrifosse, G (2005) Immunochemical, biomolecular and biochemical characterisation of bovine epithelial intestinal primocultures. BMC Cell Biol 6, 4252.CrossRefGoogle ScholarPubMed
35Stevenson, DJ, Morgan, C, Goldie, E, Connel, G & Grant, MH (2004) Cryopreservation of viable hepatocyte monolayers in cryoprotectant media with high serum content: metabolism of testosterone and kaempherol post-cryopreservation. Cryobiology 49, 97113.CrossRefGoogle ScholarPubMed
36Baten, A, Sakamoto, K & Shamsuddin, AM (1992) Long term culture of normal human colonic epithelial cells in vitro. FASEB J 6, 27262734.CrossRefGoogle ScholarPubMed
37Pichard, L, Raulet, E, Fabre, G, Ferrini, JB, Ourlin, JC & Maurel, P (2006) Human hepatocyte culture. Methods Mol Biol 320, 283293.Google ScholarPubMed
38Goldstein, JL & Brown, MS (1977) The low density lipoprotein pathway and its relation to atherosclerosis. Annu Rev Biochem 46, 897930.CrossRefGoogle ScholarPubMed
39de Kanter, R, Olinga, P, de Jager, MH, Merema, MT, Meijer, DKF & Groothius, GMM (1999) Organ slices as an in vitro test system for drug metabolism in human liver, lung and kidney. Toxicol in Vitro 13, 737744.CrossRefGoogle Scholar
40Lerche-Langrand, C & Toutain, HJ (2000) Precsion-cut liver slices: characteristics and use for in vitro pharmaco-toxicology. Toxicology 153, 221253.CrossRefGoogle ScholarPubMed
41Miller, MG, Beyer, J, Hall, GL, De Graffenried, IA & Adams, PE (1993) Predictive value of liver slices for metabolism and toxicity in vivo: use of acetaminophen as a model hepatotoxicant. Toxicol Appl Pharmacol 122, 108116.CrossRefGoogle ScholarPubMed
42Prince, RJ, Mistry, H, Wield, PT, Renwick, AB, Beamand, JA & Lake, BG (1996) Comparison of the toxicity of allyl alcohol, coumarin and menadione in precision-cut rat, guinea-pig, cynomolgus monkey and human liver slices. Arch Toxicol 71, 107111.CrossRefGoogle Scholar
43van de Bovenkamp, M, Groothuis, GMM, Draaisma, AL, Merema, MT, Bezuijen, JI, Van Gils, MJ, Meijer, DKF, Friedman, SL & Olinga, P (2005) Precision-cut liver slices as a new model to study toxicity-induced hepatic stellate cell activation in a physiologic milieu. Toxicol Sci 85, 632638.CrossRefGoogle Scholar
44Baumann, P, Kerdar, RS, Cramer, P, Feser, W, Blode, H, Salomon, A & Kuhnz, W (1996) Use of rat and human liver slices for the detection of steroid hormone-induced DNA-adducts in vitro by means of the 32P-postlabelling technique. Pharmacol Toxicol 78, 214223.CrossRefGoogle Scholar
45Lake, BG, Beamand, JA, Tredger, JM, Barton, PT, Renwick, AB & Price, RJ (1999) Inhibition of xenobiotic-induced genotoxicity in cultured precision-cut rat liver slices. Mutat Res 440, 91100.CrossRefGoogle Scholar
46Ekins, S (1996) Past, present, and future applications of precision-cut liver slices for in vitro xenobiotic metabolism. Drug Metabol Rev 28, 591623.CrossRefGoogle ScholarPubMed
47Meredith, C, Scott, MP, Renwick, AB, Price, RJ & Lake, BG (2003) Studies on the induction of rat hepatic CYP1A, CYP2B, CYP3A and CYP4A subfamily form mRNAs in vivo and in vitro using precision-cut rat liver slices. Xenobiotica 33, 511527.CrossRefGoogle ScholarPubMed
48Onderwater, RC, Commandeur, JN, Rooseboom, M & Vermeulen, NP (2005) Uptake-toxicity relationships of a series of N-substituted N′-(4-imidazole-ethyl)thiourea in precision-cut rat liver slices. Xenobiotica 35, 391404.CrossRefGoogle ScholarPubMed
49Pfaff, M, Powaga, N, Akinci, S, Schutz, W, Banno, Y, Wiegand, S, Kummer, W, Wess, J & Haberberger, RV (2005) Activation of the SPHK/SIP signalling pathway is coupled to muscarinic receptor-dependent regulation of peripheral airways. Respiratory Research 6, 48; available athttp://respiratory-research.com/content/6/1/48.Google Scholar
50Moronvalle-Halley, V, Sacre-Salem, B, Sallez, V, Labbe, G & Gautier, JC (2005) Evaluation of cultured, precision-cut rat liver slices as a model. Toxicology 207, 203214.CrossRefGoogle ScholarPubMed
51Kleinman, HK, McGarvey, ML, Hassall, JR, Star, VL, Cannon, FB, Laurie, GW & Martin, GR (1986) Basement membrane complexes with biological activity. Biochemistry 25, 312318.CrossRefGoogle ScholarPubMed
52VanHaecke, T & Rogiers, V (2006) Hepatocyte cultures in drug metabolism and toxicological research and testing. Methods Mol Biol 320, 209227.Google ScholarPubMed
53Chua, KN, Tang, YN, Quej, CH, Ramakrishna, S, Leong, KW & Mao, HQA (2007) A dual-functional fibrous scaffold enhances P450 activity of cultured primary rat hepatocytes. Acta Biomater 3, 643650.CrossRefGoogle ScholarPubMed
54Turner, WS, Schmelzer, E, McClelland, R, Wauthier, E, Chen, W & Reid, LM (2007) Human hepatoblast phenotype maintained by hyaluronan hydrogels. J Biomed Mater B 82, 1560–1168.Google ScholarPubMed
55Huang, H, Hanada, S, Kojima, N & Sakai, Y (2006) Enhanced functional maturation of fetal porcine hepatocytes in three-dimensional polu-L-lactic acid scaffolds: a culture condition suitable for engineered Liver tissues in large-scale animal studies. Cell Transplant 15, 799809.CrossRefGoogle ScholarPubMed
56Elkiyam, T, Amitay-Shaprut, S, Dvir-Ginsburg, M, Harel, T & Cohen, S (2006) Enhancing the drug metabolism of C3A – a human hepatocyte cell line – by tissue engineering within alginate scaffolds. Tissue Eng 12, 13571368.CrossRefGoogle Scholar
57Li, J, Pan, J, Zhang, L, Guo, X & Yu, Y (2003) Culture of primary rat hepatocytes within porous chitosan scaffolds. J Biomed Mater Res A 67, 938943.CrossRefGoogle ScholarPubMed
58Semino, CE, Merok, JR, Crane, GG, Panagiotakos, G & Zhang, S (2003) Functional differentiation of hepatocyte-like spheroid structures from putative liver progenitor cells in three-dimensional peptide scaffolds. Differentiation 71, 262270.CrossRefGoogle ScholarPubMed
59Beckstead, BL, Santosa, DM & Giachelli, CM (2006) Mimicking cell-cell interactions at the biomaterial-cell interface for control of stem cell differentiation. J Biomed Mater Res A 79, 94103.CrossRefGoogle ScholarPubMed
60Mei, Y, Goldberg, M & Anderson, D (2007) The development of high-throughput screening approaches for stem cell engineering. Curr Opin Chem Biol, Aug 14 (Epub ahead of print).Google Scholar
61Öbrink, KJ & Rehbinde, C (1993) The defined animal. Scand J Lab Anim Sci 20, 59.Google Scholar
62Meyer, O & Svendsen, O (2003) Animal models in pharmacology and toxicology. In Handbook of Laboratory Animal Science, (volume II), 2nd ed., pp. 1139 [Hau, J and van Hoosier, GL Jr, editors]. CRC Press LLC.Google Scholar
63Coffey, DS & Isaacs, JT (1980) Requirements for an idealized animal model in prostatic cancer. In Models for Prostate Cancer, pp. 379391 [Murphy, GP, editor]. New York: Alan R Liss.Google Scholar
64Mutch, DM, Wahli, W & Williamson, G (2005) Nutrigenomics and nutrigenetics: the emerging faces of nutrition. FASEB J 19, 16021616.CrossRefGoogle ScholarPubMed
65Wessler, S (1976) Introduction: What is a Model? In: Animal Models of Thrombosis and Hemorrhagic Diseases, xi-xvi. Bethesda, Md: National Institutes of Health.Google Scholar
66Moser, AR, Pitot, HC & Dove, WF (1989) A dominant mutation that predisposes to multiple intestinal neoplasia in the mouse. Science 247, 322324.CrossRefGoogle Scholar
67Goldstein, JL, Kita, T & Brown, MS (1983) Defective lipoprotein receptor and atherosclerosis. Lesson from an animal counterpart of familial hypercholesterolemia. N Engl J Med 309, 288296.Google ScholarPubMed
68Muller, WJ, Sinn, E, Pattengale, PK, Wallace, R & Leder, P (1988) Single-step induction of mammary adenocarcinoma in transgenic mice bearing activated c-neu oncogene. Cell 54, 105115.CrossRefGoogle ScholarPubMed
69Grum-Schwesen, B, Klingeholhofer, J, Berg, CH, El-Naaman, C, Grigorian, M, Lukanidin, E & Ambartsumian, N (2005) Suppression of tumour development and metastasis formation in mice lacking the S100A4(mts1) gene. Cancer Res 65, 37723780.CrossRefGoogle Scholar
70Hau, J, Andersen, LLI, Rye Nielsen, B & Poulsen, OM (1989) Laboratory animal models. Scand J Lab Anim Sci 16, Suppl. 1, 79.Google Scholar
71Thomsen, AR, Almstrup, K, Nielsen, JE, Sørensen, IK, Petersen, OW, Leffers, H & Breinholt, VM (2006) Estrogenic effect of soy isoflavones on mammary gland morphogenesis and gene expression profile. Toxicol Sci 93, 357357.CrossRefGoogle ScholarPubMed
72Lund, CO, Mortensen, A, Nilas, L, Breinholt, VM, Larsen, J-J & Ottesen, B (2007) Estrogen and phytoestrogens: Effect on eNOS expression and in vito vasodilation in cerebral arteries in ovariectomized Watanabe heritable hyperlipidemic rabbits. Eur J Obstet Gynecol Reprod Biol 130, 8492.CrossRefGoogle Scholar
73van Kranen, HJ, Mortensen, A, Sørensen, IK, van den Berg-Wijnands, J, Beems, R, Nurmi, T, Adlercreutz, & van Kreijl, CF (2003) Lignan precursors from flaxseed or rye bran do not protect against the development of intestinal neoplasia in Apc Min mice. Nutr Cancer 45, 203210.CrossRefGoogle Scholar
74Sørensen, IK, Kristiansen, E, Mortensen, A, Nicolaisen, GM, Wijnands, JAH, van Kranen, HJ & van Kreijl, CF (1998) The effect of soy isoflavones on development of intestinal neoplasia in Apc Min mice. Cancer Lett 130, 217225.CrossRefGoogle Scholar
75Mukhopathyay, S, Ballard, BR, Mukherjee, S, Kabir, SM & Das, SK (2006) Beneficial effects of soy protein in the initiation and progression against dimethylbenz [a] anthracene-induced breast tumors in female rats. Mol Cell Biochem 290, 169176.CrossRefGoogle Scholar
76Day, JK, Besch-Williford, C, McMann, TR, Hufford, MG, Lubahn, DB & MacDonald, RS (2001) Dietary genistein increased DMBA-induced mammary adenocarcinoma in wild-type, but not ER alpha KO, mice. Nutr Res 39, 226232.Google Scholar
77Rowlands, JC, HeL, , Hakkak, R, Ronis, MJ & Badger, TM (2001) Soy and whey proteins downregulate DMBA-induced liver and mammary gland CYP1 expression in female rats. J Nutr 131, 32813287.CrossRefGoogle ScholarPubMed
78Thomsen, AR, Mortensen, A, Breinholt, VM, Lindecrona, RH, Penalvo, JL & Sørensen, IK (2005) Influence of Prevastein, an isoflavone-rich soy product, on mammary gland development and tumorigenesis in Tg.NK (MMTV/c-neu) mice. Nutr Cancer 52, 176188.CrossRefGoogle ScholarPubMed
79Freireich, EJ, Gehan, EA, Rall, DP, Schmidt, LH & Skipper, HE (1966) Quantitative comparison of toxicity of anticancer agents in mouse, rat, hamster, dog, monkey, and man. Cancer Chemother Rep 50, 219244.Google ScholarPubMed
80Hau, J & Poulsen, OM (1988) Doses of laboratory animals based on metabolic rate. Scand J Lab Anim Sci 15, 8183.Google Scholar
81Rao, GN (1988) Rodent diets for carcinogenesis studies. J Nutr 118, 929931.CrossRefGoogle ScholarPubMed
82Thigpen, JE, Li, L-A, Richter, CB, Lebetkin, EH & Jameson, CW (1987) The mouse bioassay for detection of estrogenic activity in rodent diets: II.Comparative estrogenic activity of purified, certified and standard open and closed formula rodent diets. Lab Anim Sci 37, 602605.Google ScholarPubMed
83Degen, GH, Janning, P, Diel, P & Bolt, HM (2002) Estrogenic isoflavones in rodent diets. Tox Letters 128, 145157.CrossRefGoogle ScholarPubMed
84Ritskes Hoitinga, M (2001) The need for defined diets and refined feeding methods. Scand J Anim Sci 28, 5154.Google Scholar
85Hausner, EA, Schlingmann, KL, Chen, WH, Gillies, PG, Kieras, CJ, Ross, PE & van Pelt, CS (1995) Hepaticand adrenal changes in rabbits associated with hyperlipidemia caused by a semi-synthetic diet. Lab Anim Sci 45, 663670.Google Scholar
86Frederiksen, H, Mortensen, A, Schrøder, M, Frandsen, H, Bysted, A, Knuthsen, P & Rasmussen, S (2007) Effects of red grape skin and seed extraxt supplementation on atherosclerosis in Watanabe heritable hyperlilidemic rabbits. Mol Nutr Food Res 51, 564571.CrossRefGoogle Scholar
87Rao, GN & Knapka, JJ (1987) Contaminant and nutrient concentrations of natural ingredient rat and mouse diet used in chemical toxicology studies. Fund Appl Toxicol 9, 329338.CrossRefGoogle ScholarPubMed
88Saarinen, NM, Bingham, C, Lorenzetti, S, Mortensen, A, et al. (2006) Tools to evaluate estrogenic potency of dietary phytoestrogens: a consensus paper from the EU Thematic Network “Phyohealth” (QLKI-2002–2453). Genes Nutr 3/4, 143158.CrossRefGoogle Scholar
89Luijten, M, Thomsen, AR, van den Berg, JAH, Wester, PW, Verhoef, A, Nagelkerke, NJD, Adlercreutz, H, van Kranen, HJ, Piersma, AH, Sørensen, IK, Rao, GN & van Kreijl, CF (2004) Effects of soy-derived isoflavones and a high-fat diet on spontaneous mammary tumor development in Tg.NK (MMTV/c-neu) mice. Nutr Cancer 50, 4654.CrossRefGoogle Scholar
90Naumann, E, van Rees, AB, Önning, G, Öste, R, Wydra, M & Mensink, RP (2006) Beta-glucan incorporated into a fruit drink effectively lowers serum LDL-cholesterol concentrations. Am J Clin Nutr 83, 601605.CrossRefGoogle ScholarPubMed
91Covas, M-I, Nyyssönen, K, Poulsen, HE, EUROLIVE Study Group, et al. (2006) The effect of polyphenols in olive oil on heart disease risk factors: a randomized trial. Ann Intern Med 145, 333341.CrossRefGoogle ScholarPubMed
92Valentová, K, Stejskal, D, Bednár, P, Vostálová, J, Číhalík, Č, Večerová, R, Koukalová, D, Kolár, M, Reichenbach, R, Škňourilová, L, Ulrichová, J & Šimánek, V (2007) Biosafety, antioxidants status and metabolites in urine after consumption of dried cranberry juice in healthy women: a pilot double-blind placebo-controlled trial. J Agric Food Chem 55, 32173224.CrossRefGoogle ScholarPubMed
93John, JH, Ziebland, S, Yudkin, P, Roe, LS, Neil, H & Oxford Fruit and Vegetable Study Group (2002) Effects of fruit and vegetable consumption on plasma antioxidant concentrations and blood pressure: a randomised controlled trial. Lancet 359, 19691974.CrossRefGoogle ScholarPubMed
94Watzl, B, Girrbach, S & Roller, M (2005) Inulin, oligofructose and immunomodulation. Br J Nutr 93, Suppl. 1, S49S55.CrossRefGoogle ScholarPubMed
95Estruch, R, Martinez-Gonzales, MA, Corella, D, et al. (2006) PREDIMED study investigators. Effects of a Mediterranean-style diet on cardiovascular risk factors: a randomized trial. Ann Intern Med 145, 1111.CrossRefGoogle Scholar
96Beresford, SAA, Johnson, KC, Ritenbaugh, C, et al. (2006) Low-fat dietary pattern and risk of colorectal cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. JAMA 295, 643654.CrossRefGoogle ScholarPubMed
97Baumann, KH, Hessel, F, Larass, I, Müller, T, Angerer, P, Kielf, R & von Schacky, C (1999) Dietary omega-3, omega-6, and omega-9 unsaturated fatty acids and growth factor and cytokine gene expression in unstimulated and stimulated monocytes. A randomized volunteer study. Arterioscler Thromb Vasc Biol 19, 5966.CrossRefGoogle ScholarPubMed
98Mullen, A, Moloney, F, Nugent, AP, Doyle, L, Cashman, KD & Roche, HM (2007) Conjugated linoleic acid supplementation reduces peripheral blood mononuclear cell interleukin-2 production in healthy middle-aged males. J Nutr Biochem, Mar 16; (Epub ahead of print).CrossRefGoogle Scholar
99Kovar, J, Suchanek, P, Hubacek, JA & Poledne, R (2004) The A-204C polymorphism in the cholesterol 7alpha-hydroxylase (CYP7A1) gene determines the cholesterolemia responsiveness to a high-fat diet. Physiol Res 53, 565568.CrossRefGoogle ScholarPubMed
100Prynne, CJ, Mishra, GD, O'Connell, MA, Muniz, G, Laskey, MA, Yan, L, Prentice, A & Ginty, F (2006) Fruit and vegetable intakes and bone mineral status: a cross sectional study in 5 age and sex cohorts. Am J Clin Nutr 83, 14201428.CrossRefGoogle ScholarPubMed
101Coyne, T, Ibiebele, TI, Baade, PD, Dobson, A, McClintock, C, Dunn, S, Leonard, D & Shaw, J (2005) Diabetes mellitus and serum carotenoids: findings of a population-based study in Queensland, Australia. Am J Clin Nutr 82, 685693.CrossRefGoogle ScholarPubMed
102Pavia, M, Pileggi, C, Nobile, CGA & Angelillo, IF (2006) Association between fruit and vegetable consumption and oral cancer: a meta-analysis of observational studies. Am J Clin Nutr 83, 11261134.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Selected variables and characteristics relevant when choosing a laboratory species as a model in nutrition research

Figure 1

Table 2 Mouse dosage compensation factor – examples