- Email: [email protected]
Exploitation of molecular profiling techniques for GM food safety assessment
238
Exploitation of molecular profiling techniques for GM food safety assessment Harry A Kuipery, Esther J Kok and Karl-Heinz Engelz Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions. Addresses RIKILT, Institute of Food Safety, PO Box 230, 6700 AE Wageningen, The Netherlands y e-mail: [email protected] z Technische Universita¨t Mu¨nchen, Lehrstuhl fu¨r Allgemeine Lebensmitteltechnologie, Am Forum 2, 85350 Freising-Weihenstephan, Germany
Current Opinion in Biotechnology 2003, 14:238–243 This review comes from a themed section on Food biotechnology Edited by David Archer and Mike Gasson 0958-1669/03/$ – see front matter ß 2003 Elsevier Science Ltd. All rights reserved. DOI 10.1016/S0958-1669(03)00021-1
Abbreviations 2DGE two-dimensional gel electrophoresis FSA Foods Standards Agency GC gas chromatography GM genetically modified MS mass spectrometry NMR nuclear magnetic resonance
Introduction The potential occurrence of unanticipated alterations in the composition of genetically modified (GM) food crops as a result of the genetic modification process is one of the key elements of the safety assessment procedure. Random insertion of genes into the genomic DNA of a host organism may, in addition to the intended effects, result in unexpected shifts in metabolic pathways leading to alterations in concentrations of nutrients and secondary metabolites or, in theory, even to the formation of new toxins. Unintended effects are known to occur in GM Current Opinion in Biotechnology 2003, 14:238–243
food crops, but it is emphasised that this phenomenon is not unique to GM organisms, it happens frequently in conventional plant breeding via point mutations as well as through chromosomal recombination mechanisms [1] (K-H Engel et al., unpublished results). Food safety evaluation strategies for GM crops have been designed and are internationally broadly accepted [2–4]. The concept of substantial equivalence was formulated as a comparative tool to identify similarities and differences between the GM food crop and its non-GM counterpart, which should be further assessed with respect to their potential impact on human and animal health. Kuiper et al. [5] have recently reviewed the issues involved in the safety evaluation of GM foods. This review deals with methods to identify unintended alterations that may occur in GM organisms as a result of the genetic modification. It highlights the activities of the European Thematic Network ‘Safety Assessment of Genetically Modified Food Crops’ (ENTRANSFOOD), which among others is focussed on the development of new methods for safety evaluation of GM foods, including methods for the identification of unintended effects (Figure 1) [6,7].
Strategies for the identification of unintended effects Different strategies may be adopted to identify unintended effects in GM food crops resulting from the genetic modification (Figure 2). The most direct way to predict unintended effects is by analysis of the transgene flanking regions, to establish whether the insertion has taken place within or in proximity to an endogenous gene. Although information on genomes and the regulation of gene expression is still limited, sequencing of the place of insertion(s) will become more important as a tool to predict phenotypic changes in the modified organism. Possible alterations in the phenotype may be identified through a comparative analysis of growth performance, yield, disease resistance, chemical composition and so on. For spotting alterations in the composition of a GM organism compared with the parent, normally a targeted approach is used (i.e. measurements of single known compounds such as macronutrients, micronutrients, toxins or anti-nutrients, that is compounds that negatively affect the digestion of macronutrients like proteins or inhibit the gastro-intestinal uptake of essential elements). Analysis of the chemical composition represents an important part within the safety assessment framework of GM foods, as was demonstrated in the case of tubers www.current-opinion.com
Molecular profiling techniques for GM food safety assessment Kuiper, Kok and Engel 239
Figure 1
Detection of unintended effects (GMOCARE)
New safety testing (SAFOTEST)
GMO detection (QPCRGMOFOOD, GMOCHIPS)
Gene transfer (GMOBILITY)
EUROPEAN THEMATIC NETWORK SAFETY ASSESSMENT OF GENETICALLY MODIFIED FOOD CROPS 'ENTRANSFOOD'
Working group safety testing of transgenic foods
www.entransfood.com
Working group detection of unintended effects
Working group gene transfer
Working group W traceability and T quality assurance Working group consumer involvement
Current Opinion in Biotechnology
Organisation of the EU funded Thematic Network ‘ENTRANSFOOD’ in research projects (green ovals) and working groups (blue ovals).
from insect- and virus-resistant potato plants [8]. This study is a good example of an extensive analysis of major constituents (e.g. fats, proteins and carbohydrates) and of Figure 2
Safety assessment of GM food
Identification of unintended effects
Targeted approach Analysis of: macronutrients micronutrients anti-nutrients toxins secondary metabolites
Non-targeted approach DNA microarray Proteomics Metabolomics
Current Opinion in Biotechnology
The identification of unintended affects resulting from genetic modification. The two different approaches and the techniques they employ are depicted. www.current-opinion.com
minor components (e.g. minerals, vitamins and specific toxins such as glycoalkaloids) and of protein composition. The aim of this work was to demonstrate that the composition of the GM potatoes is not different from conventional varieties. Statistically significant differences between parental and GM lines that went beyond the intended effects of the genetic modification have been observed in two cases: an increased content of glycoalkaloids was seen in a GM potato variety expressing soybean glycinin [9] and an increase of vitamin B content was identified in GM rice expressing soybean glycinin [10]. This targeted approach has its limitations with respect to a restricted and ‘biased’ selection of compounds that can be analysed. Furthermore, the detection of unknown toxicants or anti-nutrients is not possible using this method. To increase the chances of detecting unintended effects, profiling methods have been proposed as a tool for characterising changes in the composition of GM plants [3,11]. This may be of particular relevance for GM food crops with improved nutritional or health-protecting properties, obtained through the insertion of multiple genes. This non-targeted approach using DNA/RNA microarray technology, proteomics and hyphenated (i.e. coupled) analytical techniques allows ‘unbiased’ profiling of possible changes in the physiology and metabolism of the modified host organism at different cellular integration levels. The potential of these methods for studying Current Opinion in Biotechnology 2003, 14:238–243
240 Food biotechnology
molecular genetics and physiology of plants has been discussed in a recent review [12].
Profiling methods Detection of altered gene expression
The development of microarray technology marks the most recent step in the history of gene expression analysis. This technology makes it feasible to monitor the expression of thousands of different genes simultaneously and to link detected differences directly to the underlying gene(s) [13,14]. The technology is now being applied [15] and tested in the medical area [16], plant biology [17,18], and human nutrition [19]. The most crucial part in the detection of altered gene expression using microarray technology is the construction of the array. Several array systems are available commercially that comprise large numbers of the expressed genes in specific organisms, but their number is still very limited especially in the area of food plants. Therefore, research projects have been initiated to develop informative arrays for the tomato and potato as model systems for food plants (GMOCARE project in progress [6], UK Foods Standards Agency [FSA] project in progress [20]). In the case of the tomato, cDNA libraries for use in construction of the array have been obtained that contain specific cDNAs for the green and red stages of ripening (EJ Kok, unpublished data). The green-specific library is likely to contain cDNAs that are related to the formation of natural toxins, such as tomatin, whereas the red-specific library will contain cDNAs that are associated with the metabolism of the positive factors in the tomato, such as vitamins and flavonoids. The idea behind the construction of these specific cDNA libraries is that genetic modification may affect key metabolic pathways involved in the production of natural toxins and/or health-beneficial compounds. Similarly, a potato library has been constructed that aims to further
elucidate the metabolic pathways of the potato natural toxins, especially the glycoalkaloids such as chaconine and solanine. Moreover, more elaborate potato libraries are being developed for both the tuber as well as for the potato plant. In this way the resulting array will not only be able to screen for altered gene expression in the tuber in pathways that are active in traditionally bred potato varieties, but it will also be able to detect potential activation of plant-part-related metabolic routes in the tuber. Proper selection of the mRNA populations to be hybridised is of key importance. It is necessary to sample in a reproducible way comparable tissues of plants that are in the same stage of development and have been grown under (near) identical environmental conditions. To evaluate the microarray fluorescent patterns adequately it will be necessary to gain sufficient insight into the natural variation in gene expression during the different stages of development of the tissues of interest and under different environmental conditions. Detected differences in two plant lines (e.g. a GMO variety versus the traditionally bred parent line) can thus be evaluated against known background patterns. Work is now ongoing to document the natural background variation in specific tissues (Figure 3). The outcome of this analysis will largely determine the usefulness of microarray technology to screen for unintended effects in GM varieties associated with the genetic modification itself. Preliminary results show that, at the least, this methodology can effectively monitor the intended effects in GM tomato varieties. On this basis it seems likely that it will be possible to extend this approach to screen for unintended side-effects of the breeding process (EJ Kok, unpublished data). Proteomics
Proteomics, that is, the study of the entire set of proteins present in a cell, organism or tissue under defined
Figure 3
(a)
(b)
(c)
(d)
Current Opinion in Biotechnology
Part of a microarray with expressed sequence tag sequences that are specific for the red stage of tomato ripening. The array has been hybridised with total RNA samples that were isolated from tomatoes in (a) green, (b) breaker, (c) light red and (d) red stages of ripening. The results reflect the increased expression of ripening-related genes towards the final red-ripe stage. Current Opinion in Biotechnology 2003, 14:238–243
www.current-opinion.com
Molecular profiling techniques for GM food safety assessment Kuiper, Kok and Engel 241
conditions, is a well-established technique enabling analysis after transcript profiling. The main approach currently applied involves two-dimensional gel electrophoresis (2DGE) followed by excision of protein spots from the gel, digestion into fragments by specific proteases, analysis by mass spectrometry (MS) and subsequent computerassisted identification of the fragments using databases [21]. The potential of proteomics to perform comparative analyses of protein patterns may be of importance for food safety assessment. This type of ‘differential display’ proteomics has been applied to follow changes in concentrations of proteins or post-translational modifications upon stimulation by environmental factors or genetic mutations [22–24]. One of the major challenges is the quantification of proteins — only highly expressed proteins are detected by 2DGE techniques [25] and the dynamic range of quantification is limited. Alternatives may be provided by quantification on the basis of isotope-coded affinity tags [26] or the use of multidimensional liquid chromatography coupled to tandem mass spectrometry [27–29]. At present, the applicability of proteomic techniques is being studied within European multidisciplinary projects for the food safety evaluation of GM crops [7,20]. 2DGE protein profiling is being tested on GM potato and tomato varieties (GMOCARE project in progress) and the potential of polypeptide fractionation and profiling using multidimensional column chromatography and quantitative analysis of fractionated peptides using isotope-coded affinity tags and mass spectrometry are under investigation (British FSA project, in progress). The detection of differences related to the genetic modification might prove to be very difficult, taking into account the large number of proteins not connected to such changes and given the natural variations in protein patterns owing to different environmental conditions. The limited knowledge of the natural variability of plant protein patterns demands the development of validated databases and further validation of the methods. It might be useful to focus on proteins involved in important metabolic pathways and a combination of immunoblotting and protein microarrays may offer interesting possibilities in this respect. Metabolite profiling
In order to identify in a GM food crop alterations in the content of cellular compounds such as sugars, fats, acids, and other metabolites that play an essential role in the metabolism, it is preferable to measure as many individual compounds as possible. To this end so-called metabolite profiling approaches are being developed based on gas chromatography (GC), high-performance liquid chromatography, MS, nuclear magnetic resonance (NMR) or Fourier-transform (near) infrared spectroscopy [30–32]. These methods are capable of detecting, identifying, resolving and quantifying a wide range of compounds www.current-opinion.com
in a single sample. Application is totally unbiased or targeted to metabolites in key metabolic pathways [33]. A metabolite profiling methodology has been developed using rice as a model crop [34]. It involves fractionation of total rice extracts, thus enabling analysis of a broad spectrum of major and minor constituents. Profiles of silylated/methylated compounds are obtained by means of GC coupled to flame ionization detection, and identification can be achieved by GC-MS. The applicability of GC-MS to the simultaneous analysis of a broad variety of polar and apolar metabolites in Arabidopsis thaliana leaves and potato tubers has been elegantly demonstrated [35,36]. This method was also used to characterise the genotypes of potatoes modified in sucrose metabolism [37]. The approach revealed the appearance of novel unexpected metabolites in chromatograms from transgenic tubers. Although GC results in highly resolved chromatograms and MS provides valuable information on the structural identity of compounds, the de novo identification of unknown metabolites is difficult. The necessity to derivatise compounds to make them volatile and the limited opportunities to collect them from the eluate of the GC column for further analysis are the main drawbacks of this approach. Metabolite profiling methods applying liquid chromatography may help to overcome these limitations [38]. Off-line coupling of liquid chromatography to NMR was applied to the analysis of GM tomato varieties (with slow ripening characteristics achieved through antisense RNA exogalactanase modification) and to their non-modified counterpart [39,40]. 1 H-NMR spectra of pre-fractionated extracts revealed that a-lycopene was present in the antisense fruit at a concentration two to four times higher than that found in its parental line. This change is not an intended target of the modification, but presumably a consequence of the slow ripening process. NMR and different MS approaches are also being used in the GMOCARE and FSA projects already mentioned on the genetically modified varieties under study. The approaches applied so far for metabolite profiling are powerful tools for unbiased analysis of a broad spectrum of metabolites and are a good compromise between comprehensiveness and specificity. Data analysis
The application of profiling techniques even to a limited number of samples results in a huge amount of data. A meaningful analysis of profiles from a GM food and its non-GM counterpart, with respect to safety implications, should be based on the entirety of potential differences. For this reason, multivariate techniques, for example, principal component analysis (PCA) or hierarchical cluster analysis (HCA) are frequently applied [35,37]. The Current Opinion in Biotechnology 2003, 14:238–243
242 Food biotechnology
application of multivariate methods is useful, but discrimination between intended and unintended effects may not always be possible. The wealth of data generated through the application of profiling methods demands a rigorous analysis with respect to their biological relevance. To this end a set up of linked databases containing gene expression, protein and metabolite profiles, reflecting different developmental stages and environmental conditions, is essential. Different approaches to establish such databases have been described [41,42]. Furthermore, standardisation of sampling procedures and inter-laboratory testing and validation of these methods is needed.
Conclusions The application of molecular profiling techniques for the safety assessment of GM foods may, in principle, provide relevant information regarding alterations in gene expression and associated metabolic consequences as a result of genetic modification. An unbiased, non-selective comparison of GM organisms and their traditional counterparts offers, in theory, almost unlimited possibilities for tracing differences at various integration levels of cells and tissues. However, a bottleneck for the successful application of these techniques is the generation of massive amounts of data for the evaluation of individual GM lines and the inherent difficulties in making a meaningful interpretation. Also very important in this respect is the lack of validated interconnected databases containing information on variations in profiles associated with relevant developmental stages and environmental conditions. The potential of profiling methods to screen for unintended effects possibly associated with genetic modification are obvious, but further exploration with respect to specificity and sensitivity of the methods and validation is needed to demonstrate their usefulness for the safety evaluation of GM foods.
Acknowledgements The authors want to acknowledge the European Commission (DG Research) for financial support of ENTRANSFOOD and GMOCARE, and the Dutch Ministry of Agriculture, Nature Conservation and Fisheries for financial support of the research programme Food and Feed Safety (LNV 390).
References and recommended reading Papers of particular interest, published within the annual period of review, have been highlighted as: of special interest of outstanding interest 1.
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Current Opinion in Biotechnology 2003, 14:238–243
agriculture Organisation of the United Nations. URL: http:// www.fao.org/es/esn/gm/biotec-e.htm 5.
Kuiper HA, Kleter GA, Noteborn HPJM, Kok EJ: Assessment of the food safety issues related to genetically modified foods. Plant J 2001, 27:503-528.
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Rogan GJ, Bookout JT, Duncan DR, Fuchs RL, Lavrik PB, Love SL, Mueth M, Olson T, Owens ED, Raymond PJ, Zalewski J: Compositional analysis of tubers from insect and virus resistant potato plants. J Agric Food Chem 2000, 48:5936-5945.
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Hashimoto W, Momma K, Katsube T, Ohkawa Y, Ishige T, Kito M, Utsumi S, Murata K: Safety assessment of genetically engineered potatoes with designed soybean glycinin: compositional analyses of the potato tubers and digestibility of the newly expressed protein in transgenic potatoes. J Sci Food Agric 1999, 79:1607-1612.
10. Momma K, Hashimoto W, Ozawa S, Kawai S, Katsube T, Takaiwa F, Kito M, Utsumi S, Murata K: Quality and safety evaluation of genetically engineered rice with soybean glycinin: analyses of the grain composition and digestability of glycinin in transgenic rice. Biosci Biotechnol Biochem 1999, 63:314-318. 11. Kuiper HA, Noteborn HPJM, Pejinenburg AACM: Adequacy of methods for testing the safety of genetically modified foods. Lancet 1999, 354:1315-1316. 12. Fiehn O, Kloska S, Altmann T: Integrated studies on plant biology using multiparallel techniques. Curr Opin Biotechnol 2001, 12:82-86. An excellent review on the possibilities and limitations of molecular profiling methods for studies on the molecular genetics and physiology of plants. 13. Schena M, Shalon D, Heller R, Chai A, Brown PO, Davis RW: Parallel human genome analyis: microarray based expression monitoring of 1000 genes. Proc Natl Acad Sci USA 1996, 93:10614-10619. 14. Watson A, Mazumder A, Stewart M, Balasubramanian S: Technology for microarray analysis of gene expression. Curr Opin Biotechnol 1998, 9:609-614. 15. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000, 403:503-511. 16. Ziauddin J, Sabatini DM: Microarrays of cells expressing defined cDNAs. Nature 2001, 411:107-110. 17. Baldwin D, Crane V, Rice D: A comparison of gel-based, nylon filter and microarray techniques to detect differential RNA expression in plants. Curr Opin Plant Biol 1999, 2:96-103. 18. Aharoni A, Vorst O: DNA microarrays for functional plant genomics. Plant Mol Biol 2001, 48:99-118. This article provides a good overview of the current situation in plant functional genomics. 19. Boeuf S, Klingenspor M, Van Hal NLW, Schneider T, Keijer J, Klaus S: Differential gene expression in white and brown preadipocytes. Physiol Genomics 2001, 7:15-25. 20. FSA project (Food Standards Agency): Transcriptome, proteome and metabolome analysis to detect unintended effects in genetically modified potato. URL: http://www. foodstandards.gov.uk/science/research/NovelFoodsResearch/ g02programme/g02projectlist/g02001/#re. 21. Anderson JS, Mann M: Functional genomics by mass spectrometry. FEBS Lett 2000, 480:25-31. 22. Thiellement H, Bahrman N, Damerval C, Plomion C, Rossignol M, Santoni M, de Vienne D, Zivy M: Proteomics of genetic and physiological studies in plants. Electrophoresis 1999, 20:2013-2026. www.current-opinion.com
Molecular profiling techniques for GM food safety assessment Kuiper, Kok and Engel 243
23. Komatsu S, Muhammad A, Rakwal R: Separation and characterization of proteins from green and etiolated shoots of rice (Oryza sativa L.): towards a rice proteome. Electrophoresis 1999, 20:630-636.
array detection to the metabolic profiling of plant isoprenoids. Plant J 2000, 24:551-558. An interesting example of HPLC for metabolic profiling of isoprenoids in tomatoes and Arabidopsis.
24. Kehr J, Haebel S, Blechschmidt-Schneider S, Willmitzer L, Steup M, Fisahn J: Analysis of phloem protein patterns from different organs of Cucurbita maxima Duch. By matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with sodium dodecyl sulphate polyacrylamide gel electrophoresis. Planta 2001, 207:612-619.
34. Frenzel Th, Miller A, Engel KH: Metabolite profiling – a fractionation method for analysis of major and minor compounds in rice grains. Cereal Chemistry 2002, 79:215-221.
25. Gygi SP, Corthals GL, Zhang Y, Rochon Y, Aebersold R: Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology. Proc Natl Acad Sci USA 2000, 97:9390-9395. 26. Gygi SP, Rist B, Gerber SA, Turecek F, Gelb MH, Aebersold R: Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol 1999, 17:994-999. 27. Jensen PK, Pasa-Tolic L, Peden KK, Martinovic S, Lipton MS, Anderson GA, Tolic N, Wong KK, Smith RD: Mass spectrometric detection for capillary isoelectric focusing separations of complex protein mixtures. Electrophoresis 2000, 21:1372-1380. 28. Link AJ, Eng J, Schieltz DM, Carmack E, Mize GJ, Morris DR, Garvik BM, Yates JR: Direct analysis of protein complexes using mass spectrometry. Nat Biotechnol 1999, 17:676-682. 29. Zhang Z, McElvain JS: De novo peptide sequencing by twodimensional fragment correlation mass spectrometry. Anal Chem 2000, 72:2337-2350. 30. Raamsdonk LM, Teusink B, Broadhurst D, Zhang N, Hayes A, Walsh MC, Berden JA, Brindle KM, Kell DB, Rowland JJ et al.: A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat Biotechnol 2001, 19:45-50. 31. Johnson HE, Gilbert RJ, Winson MK, Goodacre R, Smith AR, Rowland JJ, Hall MA, Kell DB: Explanatory analysis of the metabolome using genetic programming of single interpretable rules. Genet Program Evolv Mach 2000, 1:243-258. 32. Taylor J, Goodacre R, Wade WG, Rowland JJ, Kell DB: The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species. FEMS Microbiol Lett 1998, 160:237-246. 33. Fraser PD, Pinto MES, Holloway DE, Bramley PM: Application of high performance liquid chromatography with photodiode
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35. Fiehn O, Kopka J, Do¨ rmann P, Altmann T, Trethewey RN, Willmitzer L: Metabolite profiling for plant functional genomics. Nat Biotechnol 2000, 18:1157-1161. 36. Roessner U, Wagner C, Kopka J, Trethewey RN, Willmitzer L: Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant J 2000, 23:131-142. 37. Roessner U, Luedemann A, Brust D, Fiehn O, Linke T, Willmitzer L, Fernie AR: Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 2001, 13:11-29. Excellent example of metabolic profiling using GC-MS for the phenotype analysis of genetically modified potatoes. 38. Tolstikov VV, Fiehn O: Analysis of highly polar compounds of plant origin: combination of hydrophilic interaction chromatography and electrospray ion trap mass spectrometry. Anal Biochem 2002, 301:298-307. 39. Noteborn HPJM, Lommen A, Weseman JM, van der Jagt RCM, Groenendijk FPF: Chemical fingerprinting and in vitro toxicological profiling for the safety evaluation of transgenic food crops. In Report of the Demonstration Programme on Food Safety Evaluation of Genetically Modified Foods as a Basis for Market Introduction. Edited by Horning M. Ministry of Economic Affairs, The Hague, Netherlands, 1998:51-79. 40. Noteborn HPJM, Lommen A, van der Jagt RC, Weseman JM: Chemical fingerprinting for the evaluation of unintended secondary metabolic changes in transgenic food crops. J Biotechnol 2000, 77:103-114. 41. Mendes P: Emerging bioinformatics for the metabolome. Brief Bioinform 2002, 3:134-145. 42. Baxevanis AD: The molecular biology database collection. An updated complication of biological database resources. Nucleic Acids Res 2001, 29:1-10. This paper contains an extensive list of over 200 different (functional) genomics databases.
Current Opinion in Biotechnology 2003, 14:238–243
Exploitation of molecular profiling techniques for GM food safety assessment Harry A Kuipery, Esther J Kok and Karl-Heinz Engelz Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions. Addresses RIKILT, Institute of Food Safety, PO Box 230, 6700 AE Wageningen, The Netherlands y e-mail: [email protected] z Technische Universita¨t Mu¨nchen, Lehrstuhl fu¨r Allgemeine Lebensmitteltechnologie, Am Forum 2, 85350 Freising-Weihenstephan, Germany
Current Opinion in Biotechnology 2003, 14:238–243 This review comes from a themed section on Food biotechnology Edited by David Archer and Mike Gasson 0958-1669/03/$ – see front matter ß 2003 Elsevier Science Ltd. All rights reserved. DOI 10.1016/S0958-1669(03)00021-1
Abbreviations 2DGE two-dimensional gel electrophoresis FSA Foods Standards Agency GC gas chromatography GM genetically modified MS mass spectrometry NMR nuclear magnetic resonance
Introduction The potential occurrence of unanticipated alterations in the composition of genetically modified (GM) food crops as a result of the genetic modification process is one of the key elements of the safety assessment procedure. Random insertion of genes into the genomic DNA of a host organism may, in addition to the intended effects, result in unexpected shifts in metabolic pathways leading to alterations in concentrations of nutrients and secondary metabolites or, in theory, even to the formation of new toxins. Unintended effects are known to occur in GM Current Opinion in Biotechnology 2003, 14:238–243
food crops, but it is emphasised that this phenomenon is not unique to GM organisms, it happens frequently in conventional plant breeding via point mutations as well as through chromosomal recombination mechanisms [1] (K-H Engel et al., unpublished results). Food safety evaluation strategies for GM crops have been designed and are internationally broadly accepted [2–4]. The concept of substantial equivalence was formulated as a comparative tool to identify similarities and differences between the GM food crop and its non-GM counterpart, which should be further assessed with respect to their potential impact on human and animal health. Kuiper et al. [5] have recently reviewed the issues involved in the safety evaluation of GM foods. This review deals with methods to identify unintended alterations that may occur in GM organisms as a result of the genetic modification. It highlights the activities of the European Thematic Network ‘Safety Assessment of Genetically Modified Food Crops’ (ENTRANSFOOD), which among others is focussed on the development of new methods for safety evaluation of GM foods, including methods for the identification of unintended effects (Figure 1) [6,7].
Strategies for the identification of unintended effects Different strategies may be adopted to identify unintended effects in GM food crops resulting from the genetic modification (Figure 2). The most direct way to predict unintended effects is by analysis of the transgene flanking regions, to establish whether the insertion has taken place within or in proximity to an endogenous gene. Although information on genomes and the regulation of gene expression is still limited, sequencing of the place of insertion(s) will become more important as a tool to predict phenotypic changes in the modified organism. Possible alterations in the phenotype may be identified through a comparative analysis of growth performance, yield, disease resistance, chemical composition and so on. For spotting alterations in the composition of a GM organism compared with the parent, normally a targeted approach is used (i.e. measurements of single known compounds such as macronutrients, micronutrients, toxins or anti-nutrients, that is compounds that negatively affect the digestion of macronutrients like proteins or inhibit the gastro-intestinal uptake of essential elements). Analysis of the chemical composition represents an important part within the safety assessment framework of GM foods, as was demonstrated in the case of tubers www.current-opinion.com
Molecular profiling techniques for GM food safety assessment Kuiper, Kok and Engel 239
Figure 1
Detection of unintended effects (GMOCARE)
New safety testing (SAFOTEST)
GMO detection (QPCRGMOFOOD, GMOCHIPS)
Gene transfer (GMOBILITY)
EUROPEAN THEMATIC NETWORK SAFETY ASSESSMENT OF GENETICALLY MODIFIED FOOD CROPS 'ENTRANSFOOD'
Working group safety testing of transgenic foods
www.entransfood.com
Working group detection of unintended effects
Working group gene transfer
Working group W traceability and T quality assurance Working group consumer involvement
Current Opinion in Biotechnology
Organisation of the EU funded Thematic Network ‘ENTRANSFOOD’ in research projects (green ovals) and working groups (blue ovals).
from insect- and virus-resistant potato plants [8]. This study is a good example of an extensive analysis of major constituents (e.g. fats, proteins and carbohydrates) and of Figure 2
Safety assessment of GM food
Identification of unintended effects
Targeted approach Analysis of: macronutrients micronutrients anti-nutrients toxins secondary metabolites
Non-targeted approach DNA microarray Proteomics Metabolomics
Current Opinion in Biotechnology
The identification of unintended affects resulting from genetic modification. The two different approaches and the techniques they employ are depicted. www.current-opinion.com
minor components (e.g. minerals, vitamins and specific toxins such as glycoalkaloids) and of protein composition. The aim of this work was to demonstrate that the composition of the GM potatoes is not different from conventional varieties. Statistically significant differences between parental and GM lines that went beyond the intended effects of the genetic modification have been observed in two cases: an increased content of glycoalkaloids was seen in a GM potato variety expressing soybean glycinin [9] and an increase of vitamin B content was identified in GM rice expressing soybean glycinin [10]. This targeted approach has its limitations with respect to a restricted and ‘biased’ selection of compounds that can be analysed. Furthermore, the detection of unknown toxicants or anti-nutrients is not possible using this method. To increase the chances of detecting unintended effects, profiling methods have been proposed as a tool for characterising changes in the composition of GM plants [3,11]. This may be of particular relevance for GM food crops with improved nutritional or health-protecting properties, obtained through the insertion of multiple genes. This non-targeted approach using DNA/RNA microarray technology, proteomics and hyphenated (i.e. coupled) analytical techniques allows ‘unbiased’ profiling of possible changes in the physiology and metabolism of the modified host organism at different cellular integration levels. The potential of these methods for studying Current Opinion in Biotechnology 2003, 14:238–243
240 Food biotechnology
molecular genetics and physiology of plants has been discussed in a recent review [12].
Profiling methods Detection of altered gene expression
The development of microarray technology marks the most recent step in the history of gene expression analysis. This technology makes it feasible to monitor the expression of thousands of different genes simultaneously and to link detected differences directly to the underlying gene(s) [13,14]. The technology is now being applied [15] and tested in the medical area [16], plant biology [17,18], and human nutrition [19]. The most crucial part in the detection of altered gene expression using microarray technology is the construction of the array. Several array systems are available commercially that comprise large numbers of the expressed genes in specific organisms, but their number is still very limited especially in the area of food plants. Therefore, research projects have been initiated to develop informative arrays for the tomato and potato as model systems for food plants (GMOCARE project in progress [6], UK Foods Standards Agency [FSA] project in progress [20]). In the case of the tomato, cDNA libraries for use in construction of the array have been obtained that contain specific cDNAs for the green and red stages of ripening (EJ Kok, unpublished data). The green-specific library is likely to contain cDNAs that are related to the formation of natural toxins, such as tomatin, whereas the red-specific library will contain cDNAs that are associated with the metabolism of the positive factors in the tomato, such as vitamins and flavonoids. The idea behind the construction of these specific cDNA libraries is that genetic modification may affect key metabolic pathways involved in the production of natural toxins and/or health-beneficial compounds. Similarly, a potato library has been constructed that aims to further
elucidate the metabolic pathways of the potato natural toxins, especially the glycoalkaloids such as chaconine and solanine. Moreover, more elaborate potato libraries are being developed for both the tuber as well as for the potato plant. In this way the resulting array will not only be able to screen for altered gene expression in the tuber in pathways that are active in traditionally bred potato varieties, but it will also be able to detect potential activation of plant-part-related metabolic routes in the tuber. Proper selection of the mRNA populations to be hybridised is of key importance. It is necessary to sample in a reproducible way comparable tissues of plants that are in the same stage of development and have been grown under (near) identical environmental conditions. To evaluate the microarray fluorescent patterns adequately it will be necessary to gain sufficient insight into the natural variation in gene expression during the different stages of development of the tissues of interest and under different environmental conditions. Detected differences in two plant lines (e.g. a GMO variety versus the traditionally bred parent line) can thus be evaluated against known background patterns. Work is now ongoing to document the natural background variation in specific tissues (Figure 3). The outcome of this analysis will largely determine the usefulness of microarray technology to screen for unintended effects in GM varieties associated with the genetic modification itself. Preliminary results show that, at the least, this methodology can effectively monitor the intended effects in GM tomato varieties. On this basis it seems likely that it will be possible to extend this approach to screen for unintended side-effects of the breeding process (EJ Kok, unpublished data). Proteomics
Proteomics, that is, the study of the entire set of proteins present in a cell, organism or tissue under defined
Figure 3
(a)
(b)
(c)
(d)
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Part of a microarray with expressed sequence tag sequences that are specific for the red stage of tomato ripening. The array has been hybridised with total RNA samples that were isolated from tomatoes in (a) green, (b) breaker, (c) light red and (d) red stages of ripening. The results reflect the increased expression of ripening-related genes towards the final red-ripe stage. Current Opinion in Biotechnology 2003, 14:238–243
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conditions, is a well-established technique enabling analysis after transcript profiling. The main approach currently applied involves two-dimensional gel electrophoresis (2DGE) followed by excision of protein spots from the gel, digestion into fragments by specific proteases, analysis by mass spectrometry (MS) and subsequent computerassisted identification of the fragments using databases [21]. The potential of proteomics to perform comparative analyses of protein patterns may be of importance for food safety assessment. This type of ‘differential display’ proteomics has been applied to follow changes in concentrations of proteins or post-translational modifications upon stimulation by environmental factors or genetic mutations [22–24]. One of the major challenges is the quantification of proteins — only highly expressed proteins are detected by 2DGE techniques [25] and the dynamic range of quantification is limited. Alternatives may be provided by quantification on the basis of isotope-coded affinity tags [26] or the use of multidimensional liquid chromatography coupled to tandem mass spectrometry [27–29]. At present, the applicability of proteomic techniques is being studied within European multidisciplinary projects for the food safety evaluation of GM crops [7,20]. 2DGE protein profiling is being tested on GM potato and tomato varieties (GMOCARE project in progress) and the potential of polypeptide fractionation and profiling using multidimensional column chromatography and quantitative analysis of fractionated peptides using isotope-coded affinity tags and mass spectrometry are under investigation (British FSA project, in progress). The detection of differences related to the genetic modification might prove to be very difficult, taking into account the large number of proteins not connected to such changes and given the natural variations in protein patterns owing to different environmental conditions. The limited knowledge of the natural variability of plant protein patterns demands the development of validated databases and further validation of the methods. It might be useful to focus on proteins involved in important metabolic pathways and a combination of immunoblotting and protein microarrays may offer interesting possibilities in this respect. Metabolite profiling
In order to identify in a GM food crop alterations in the content of cellular compounds such as sugars, fats, acids, and other metabolites that play an essential role in the metabolism, it is preferable to measure as many individual compounds as possible. To this end so-called metabolite profiling approaches are being developed based on gas chromatography (GC), high-performance liquid chromatography, MS, nuclear magnetic resonance (NMR) or Fourier-transform (near) infrared spectroscopy [30–32]. These methods are capable of detecting, identifying, resolving and quantifying a wide range of compounds www.current-opinion.com
in a single sample. Application is totally unbiased or targeted to metabolites in key metabolic pathways [33]. A metabolite profiling methodology has been developed using rice as a model crop [34]. It involves fractionation of total rice extracts, thus enabling analysis of a broad spectrum of major and minor constituents. Profiles of silylated/methylated compounds are obtained by means of GC coupled to flame ionization detection, and identification can be achieved by GC-MS. The applicability of GC-MS to the simultaneous analysis of a broad variety of polar and apolar metabolites in Arabidopsis thaliana leaves and potato tubers has been elegantly demonstrated [35,36]. This method was also used to characterise the genotypes of potatoes modified in sucrose metabolism [37]. The approach revealed the appearance of novel unexpected metabolites in chromatograms from transgenic tubers. Although GC results in highly resolved chromatograms and MS provides valuable information on the structural identity of compounds, the de novo identification of unknown metabolites is difficult. The necessity to derivatise compounds to make them volatile and the limited opportunities to collect them from the eluate of the GC column for further analysis are the main drawbacks of this approach. Metabolite profiling methods applying liquid chromatography may help to overcome these limitations [38]. Off-line coupling of liquid chromatography to NMR was applied to the analysis of GM tomato varieties (with slow ripening characteristics achieved through antisense RNA exogalactanase modification) and to their non-modified counterpart [39,40]. 1 H-NMR spectra of pre-fractionated extracts revealed that a-lycopene was present in the antisense fruit at a concentration two to four times higher than that found in its parental line. This change is not an intended target of the modification, but presumably a consequence of the slow ripening process. NMR and different MS approaches are also being used in the GMOCARE and FSA projects already mentioned on the genetically modified varieties under study. The approaches applied so far for metabolite profiling are powerful tools for unbiased analysis of a broad spectrum of metabolites and are a good compromise between comprehensiveness and specificity. Data analysis
The application of profiling techniques even to a limited number of samples results in a huge amount of data. A meaningful analysis of profiles from a GM food and its non-GM counterpart, with respect to safety implications, should be based on the entirety of potential differences. For this reason, multivariate techniques, for example, principal component analysis (PCA) or hierarchical cluster analysis (HCA) are frequently applied [35,37]. The Current Opinion in Biotechnology 2003, 14:238–243
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application of multivariate methods is useful, but discrimination between intended and unintended effects may not always be possible. The wealth of data generated through the application of profiling methods demands a rigorous analysis with respect to their biological relevance. To this end a set up of linked databases containing gene expression, protein and metabolite profiles, reflecting different developmental stages and environmental conditions, is essential. Different approaches to establish such databases have been described [41,42]. Furthermore, standardisation of sampling procedures and inter-laboratory testing and validation of these methods is needed.
Conclusions The application of molecular profiling techniques for the safety assessment of GM foods may, in principle, provide relevant information regarding alterations in gene expression and associated metabolic consequences as a result of genetic modification. An unbiased, non-selective comparison of GM organisms and their traditional counterparts offers, in theory, almost unlimited possibilities for tracing differences at various integration levels of cells and tissues. However, a bottleneck for the successful application of these techniques is the generation of massive amounts of data for the evaluation of individual GM lines and the inherent difficulties in making a meaningful interpretation. Also very important in this respect is the lack of validated interconnected databases containing information on variations in profiles associated with relevant developmental stages and environmental conditions. The potential of profiling methods to screen for unintended effects possibly associated with genetic modification are obvious, but further exploration with respect to specificity and sensitivity of the methods and validation is needed to demonstrate their usefulness for the safety evaluation of GM foods.
Acknowledgements The authors want to acknowledge the European Commission (DG Research) for financial support of ENTRANSFOOD and GMOCARE, and the Dutch Ministry of Agriculture, Nature Conservation and Fisheries for financial support of the research programme Food and Feed Safety (LNV 390).
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