Evaluation of Genetically Engineered Crops Using Transcriptomic, Proteomic, and Metabolomic Profiling Techniques

A major principle and guiding tool for the food safety assessment of genetically engineered (GE) crops is the concept of “substantial equivalence” according to principles outlined in the Organization for Economic Cooperation and Development (OECD) consensus documents (OECD, 2006) and further elaborated by the Food and Agriculture Organization of the United Nations/World Health Organization. In this safety assessment, GE crop-derived foods and feeds are compared with their counterparts from parental or near isogenic lines in order to identify differences, which are subsequently evaluated with respect to safety for humans and animals as well as nutritional quality. The question addressed is: may the improvement of a plant variety through the acquisition of a new desired GE trait lead to unintended effects (i.e. going beyond that of the original genetic modification) and, if so, does this have an impact on health? Possible mediators of such pleiotropic effects could be altered expression of untargeted genes or metabolic effects of a novel gene product. Current tools to assess the food safety of GE crops include extensive multisite and multiyear agronomic evaluations, compositional analyses, animal nutrition, and classical toxicology evaluations. In the 2000s, new methodologies were developed to allow, in theory, a holistic search for alterations in GE crops at different biological levels (transcripts, proteins, metabolites). These methodologies include cDNA microarrays, microRNA fingerprinting, proteome, metabolome, and toxicological profiling. The term “omics” in relation to food and feed safety appeared for the first time in 2005 (Li et al., 2005). This review highlights the knowledge generated by recently published profiling studies regarding the effect of genetic modification itself, compared with environmental and intervariety variation, for major crops (44 studies) and for Arabidopsis (Arabidopsis thaliana) as a reference plant. Arabidopsis is a well-established model plant that offers comprehensive resources such as the entire genome sequence, a large collection of natural variants, a number of molecular tools, and several information platforms and databases. In addition, as illustrated below, Arabidopsis provides valuable information about the potential impact of transgenesis. The first question to be addressed is whether the insertion of genes that are not believed to alter biological processes in plants will lead to transcriptome changes. To answer this question, El Ouakfaoui and Miki (2005) used selectable marker (nptII) and reporter (uidA) genes. Under controlled growth conditions, they found no reproducible changes for the approximately 24,000 genes screened when comparing transgenic lines with their wild-type progenitor. Their conclusion was that the stable insertion of T-DNA did not cause detectable pleiotropic effects to the transcriptome. This finding was not obvious since, due to the gene density on the Arabidopsis genome, insertion could have been anticipated to cause major disturbances altering gene expression. Strikingly, under abiotic stresses (salt, drought, cold, and heat), the authors found approximately 8,000 genes (35% of the genome) with changed expression in both wild-type and transgenic plants. In contrast, Ren et al. (2009a) attributed some unintended effects to the presence of a selectable marker gene (bar, encoding phosphinotricin acetyl transferase). Metabolic fingerprinting revealed that the major contributors distinguishing the wild type and four transgenic lines were modified levels of Ala and Thr. The authors attributed this trend to the bar gene, since it was common to all lines. However, protein analysis by two-dimensional electrophoresis (2DE) on 12 bar-containing lines showed no consistent differences (four to 14 protein spots did change in intensity depending on the line, but most of them were different; Ren et al., 2009b). In that study, cold treatment triggered changes in only 10 protein spots. In another study, Abdeen and Miki (2009) found only four genes differentially expressed in transgenic lines expressing bar. A second question to be examined is whether expression of a protein affecting regulatory processes (e.g. a transcription factor affecting drought tolerance; Abdeen et al., 2010) will necessarily have pleiotropic effects. These authors found no effect on the transcriptome in such plants without drought. As can be expected, in response to drought, changes in the level or timing of expression of some drought-responsive genes occurred between transgenic and wild-type plants. A third question to address is whether deliberate modification of a metabolic pathway using transgenesis will have pleiotropic effects. Kristensen et al. (2005) inserted one to three genes from a pathway converting Tyr to a cyanogenic glucoside (dhurrin). They found only marginal inadvertent effects on the transcriptome and metabolome when the whole pathway or only the first enzyme was inserted. However, the combination of the first two genes leads to the predicted synthesis of a toxic cyanohydrin intermediate. In this case, plants responded by metabolism and detoxification reactions, as was evident from an altered metabolite profile showing the accumulation of detoxification products and changes in the transcriptome. Metzdorff et al. (2006) developed and characterized six independent lines transformed with an antisense chalcone synthase gene to decrease flavonoid biosynthesis. The lines differed in the type of integration (site and copy numbers, level of gene silencing). Unintended effects on gene expression included few genes (up to 15 in flower and up to 13 in leaf out of the 1,500 analyzed), and the affected genes were involved in stress response and photosynthesis. Lines differed with respect to the affected genes, and analyses of one such gene by PCR did not show a consistent trend with the microarray data, which the authors explain by a large biological variation in expression for this gene. One conclusion of Metzdorff et al. (2006) is that “it is crucial to have substantial information on the natural variation of crop plants in order to be able to interpret ‘omic’ data correctly.” Interestingly, Arabidopsis also provides some insight concerning the above-mentioned issue. Ruebelt et al. (2006) qualitatively and quantitatively analyzed its seed proteome and showed that existing natural variability can be important. When various ecotypes were grown side by side in a growth chamber under controlled conditions, the authors found that nearly half of the 2DE-resolved spots were present or absent depending on the ecotype and that 95% of the spots present in all ecotypes varied quantitatively. Twelve transgenic lines were also compared with their parental line as well as with 12 ecotype lines: the genetic modification of Arabidopsis using three different genes and three different promoters did not cause unintended changes to the analyzed seed proteome. In conclusion, these data on a model plant for research point to a greater influence of genetic background and stress (from the environment or new metabolites) than of transgene insertion itself. To determine whether these conclusions are also valid for crop plants, the following two sections examine the conclusions of profiling strategies in a systematic species-by-species approach. The main data from the publications discussed below are listed in Supplemental Table S1, which also includes data from earlier publications or on other species (cabbage [Brassica capitata] and potato [Solanum tuberosum]) and on GE plants producing bioproducts (such as antibodies), which are not discussed below. The search strategy used to find these references is presented in Supplemental Table S1. Using field-grown barley (Hordeum vulgare) lines expressing either a chitinase or a β-glucanase, Kogel et al. (2010) compared changes in the leaf transcriptome and metabolome caused by transgenes, cultivar, or biotic interactions in the root. Transgene effects were negligible in the first case and low in the second, while the difference caused by the genetic background of cultivars (even if down to a low number of alleles) was of a greater magnitude. Effects of exposing roots to the spores of mycorrhizal fungi could be visualized by metabolome but not transcriptome analysis. Based on this result, the authors conclude that the metabolome represents a more immediate probe of the physiological status of the plant. When performing transcriptomic studies using in vitro- or field-grown maize (Zea mays) plants, Coll et al. (2008, 2009) found differential expression for a minority of transcripts between in vitro-grown MON810 (insect-resistant of Bt type) and control lines, and most of these differences were not observed in the field. In real agricultural conditions, under two farming practices (conventional and low-nitrogen fertilization), Coll et al. (2010a) found differential expression for only 0.14% of the analyzed sequences (approximately one-third of the maize genome). Analysis of the expression of a subset of sequences in a different MON810/non-GE pair indicated that varietal differences had the highest impact on gene expression patterns, followed by nitrogen availability, while the MON810 characteristic had the lowest impact. Coll et al. (2010b) found the grain proteome of two field-grown MON810/non-GE variety pairs to be virtually identical, with very few spots showing variations in the 1- to 1.8-fold range, which were all variety specific. Previously, Albo et al. (2007) had also found limited changes in the grain proteome of two different MON810 varieties (also field et al. also used two MON810 variety pairs but found more differences, environment growth more changes. To explain the differences from genetic these authors about genome by the but did not the that the control lines were not The between these since one of the two pairs used by Coll et al. (2010b) was the MON810/non-GE pair used by et al. In a first grain metabolome out on a MON810 line, et al. (2006) found differences in the levels of from nitrogen metabolism in transgenic grain Using a different MON810 line, grown in a growth et al. (2009) and found a for in the GE different from of et al. et al. (2009) found in some from in three field-grown MON810 lines compared with their were only 10 with levels when two different were One of had been in a by the et al., to be a for Bt maize that both studies analyzed the which provides no be out that these various did not find which may be by their of different genetic different growth and also different In this the of et al. (2010) is important. Using proteome, and metabolome profiling to two GE maize lines and with the control lines, they found that the environment were grown three in one affected gene protein and metabolite more than the genetic In addition, the authors found for the three that were also of their one variability also Using MON810 and control lines, and (2010) compared protein spots from either from plants different of different maize or from plants. some they a variability between from the line and that these differences were in the other variability was observed between and also between The authors that differences not to the genetic such as natural to be when using et al. (2010) compositional data for GE maize and varieties GE crop from a of and their which is not on but represents the most comprehensive of GE crop data to the authors conclude that compositional differences between GE varieties and their are the natural variability of the crop and that the of and crops be two cultivars producing a et al. (2009) found seed protein spots showing changes in in pair not the was at levels in both differences were for one they were more quantitatively and qualitatively and of protein for the second The authors that differences of between In a different cultivar, et al. (2009) that differentially in lines compared with the parental line, three of which were with the expression of The were with the A number of the spots to seed such are common food the authors that these be to food in with GE to of and to new are listed in Supplemental Table et al. (2010) found transcriptomic differences in of in vitro-grown lines producing an They could differences due to transgene insertion transgene expression and half of the genes expression was affected by the transgene also had their expression affected in plants et al. (2009) compared of from metabolism in three GE lines transformed with the two their data were with of the wild-type line grown side by They found three to be present in greater in the GE (up to in other were the as of the wild type under various growth be that wild-type lines at different of (up to and change in the levels of four The by et al. (2010) provides some on transgenic changes in the of varietal changes in two lines with different of genes and one with two genes with their the authors found or between lines, from to for to for to for and to for These changes were all the varieties to A in protein was observed for one GE line, which was by the authors to be et al. addressed the following which of the or transgenic plants are more to present unintended expression was analyzed in of four of plants stable and transgenic plants producing an or developed for stress and their In all the modification in transcriptome was greater in than in transgenic plants. these were with grown on is et al. found that gene expression in in a growth more between varieties than between two GE varieties the transgenic and their The authors also that the the the the difference in gene expression developed cultivars are more which the question of which varieties be to a reference for the crop using a variety grown in a growth but et al. and the main in the in were found in GE and in its parental However, differences were observed in some the were found for three and for was not in the GE some of these differences could be by modification in the of the pathway in GE is by a transgenic synthase enzyme that the The on natural variation in crop and the impact of transgenesis by et al. (2010) been Using protein expression was found not to be altered genetic modification in Supplemental Table et al. (2005) found that the expression of a gene had no effect on the gene expression in the from plants were at three different seed The differences observed genes expressed a of seed This highlights the of of microarray when extensive changes as is the case for and when is to et al. (2007) analyzed lines with either a combination of three or a one of for plants, they found only differences in the flavonoid profile between GE lines and their control lines. In contrast, the different genetic background of the control lines in a quantitatively different (up to for some flavonoid In a field did not influence flavonoid whether the lines were by or These profiling studies are growth of They have to be as (i.e. not for the assessment of GE This on the profiling of GE crop lines with agronomic but without deliberate to metabolic that some differences when compared with control lines. However, the data on various lines show more This to be to the that GE lines have been by a not only on the expression of a new trait but also on and compositional with a followed by a number of to the new trait lines. A number of environmental time the or at different have also been to a greater influence than transgenesis. The substantial concept a of with a line to be However, GE crop lines have been developed to feed or food whether this concept can be used to address the to assess the safety of these new the following the conclusions of are in Supplemental Table publications not to the unintended effects of transgenesis but are discussed below or listed in Supplemental Table et al. (2005) generated maize lines with an of and in the due to the of its synthesis and levels of a from field-grown plants in addition, in the of two and up to of other but with only marginal changes for et al. (2005) major and differences in the proteome of field-grown varieties and but found only limited differences between GE lines either in or and their Using the lines, as well as lines expressing a and antisense gene grown in conclusions were using metabolic profiling et al., or compositional analysis et al., The most obvious differences were found between the two were also found between and from with the This the that variation to in depending on may be for an of using field-grown engineered to et al. (2005) found their metabolite to be to the line and variations to be the found in classical from the in and et al. (2009) found transcriptomic changes in with altered levels of but their data were not compared with varietal changes. (i.e. influence of is by et al. found that of modified metabolite patterns, but the expression of or synthase triggered In of two lines et al. (2006) found an in the of other to a than that of and of which was the relation between the pathway and the of this growth However, they found no major change for other The et al., also found limited metabolic and transcriptomic differences in of lines with et al. (2009) limited changes in roots and of by of Ala et al. analyzed metabolic and the potential unintended effects when two transcription were to The levels of at 15 other were found to be different between the GE and but according to the authors did not the growth these changes are the natural variation observed in a field-grown et al. (2006) found no in in and transgenic lines altered in genes for and the of did not in from plants. In a more comprehensive study, but also limited to conditions, et al. (2007) characterized the metabolic changes with the of of metabolism were altered in some metabolic changes with showed the change in levels of of the were in synthesis regulatory for but these effects without altering the of the plant and In addition, as expected, several can be either in or in transgenic lines, when regulatory genes are such as involved in et al., other in Supplemental Table or growth and et al. (2009) the transcriptomic of GE and lines in a expressing a of seed to determine quality. in and leaf transcriptome between GE and lines were (up to six differences (up to genes in were observed between this line and another The of different the of as the GE line and showed differences (up to with the GE line than with the of the GE et al. (2006) also using lines in their of They found some differences in between GE and parental lines, but they were in the of differences caused by the environment grown in on different and in different differences were observed between two parental lines, between and between different than between the GE and control lines. or barley lines with a modified of seed are listed in Supplemental Table of these studies their in with the potential effects of the the data are since they that GE lines with altered metabolic not necessarily pleiotropic changes. This is for the of transgenesis to food and feed quality. However, some pleiotropic effects when are A for crops with altered in a substantial is the of a for GE lines. The published studies did not examine the question of the be or a crop that most the new variety with respect to the altered metabolic the other it can be up to a not a major GE crops well as with altered have been and by (e.g. crops with authors a of Supplemental Table that profiling provides of gene, and metabolite analysis that be by A analysis of the metabolome, for offers new for plant and for a of the variation in to and However, as et al. (2006) does with (i.e. systematic as well as other with number of and As this review is an obvious of in and the published studies a biological of observed differences between GE crops and their include no biological in proteome, or metabolome are depending on growth conditions, or all of in data it to conclusions from variations to a GE such as the of a as a for a type of GE crop et al., However, as discussed below, the data point to concerning transgenesis. Current assessment of GE crops includes the analysis of to on the crop by consensus documents (OECD, 2006) as the for that using these the of of in seed and 95% of in maize a few (i.e. the metabolite some of which are the of studies in relation to GE crop assessment, it does not to that can be and Using be a change of more but with for GE crop assessment but or no for food safety since it does not the used et al., In addition, when studies have used different in the were obvious et al., As can be in Table is the approach. authors that can substantial et al., Table However, few studies have used different side by a assessment of these is The number of published studies and the number with transcriptomic or data are publications various profiling The number of published studies and the number with transcriptomic or data are publications various profiling published profiling studies of GE crops a of data, and of these in GE food safety assessment be research be out to and the of the A for a of the of the observed differences, and of their and of their biological are all is to observed differences in various a to the potential of could be which a from safety and on a whether is or Food cDNA could be et al. (2009) used this to the transcriptome of two different potato varieties to variation due to genetic differences or environmental The of natural variation of gene expression was examined to biological toxicological with are used to identify the spots that and are also able to and information on the levels of new Table GE crop lines have to be for and compositional and to existing varieties from the new it from a plant point of that a new transgenic line that metabolite as well as seed altered gene or metabolite not from a point of some differences attributed to transgenesis were in the published However, when a of references was included in the (i.e. beyond the of a GE line and its near isogenic the most differences were found between the various a trend to the crop or by plant This be in that is as the that the of the changes in new cultivars is et al., effects due to the environment were also observed on gene and metabolite levels in some studies et al., et al., et al., et al., The present knowledge by profiling the to differences between GE lines and their in a is to in that the by the and Agriculture Organization of the United Nations/World Health Organization was substantial than and that is no or biological to In other no of have been regarding In addition, plant is a differences between a GE line and its are than natural near isogenic lines by a number of which could explain a number of differences attributed to transgenesis. the substantial concept more than a guiding for the 15 of GE crop the of this However, the on GE it is to that the expressed by food safety (i.e. of GE crops with have been at the and levels by recently published of the published new safety about GE Based on their extensive of compositional data of maize and et al. (2010) that regulatory is to be with the potential for compositional is no to crops on the of genetic modification transgenesis crops genetically modified or et al. in the case that the observed transcriptome was greater in than in transgenic plants. be that as as a by the of of the had that is no that in the of or in the of genes between and the the in as genetic the data from as well as that transgenesis impact than lead at to a of for various crop on a this the regulatory for GE crops that have not been for GE crops 15 of the time may have to the assessment of products and This assessment more for or However, that GE crop have been due to in the and it is more that the and first of will be line with the GE In addition, is no that more food safety is for GE one can that a is be will for the of in their The following are in the of this Supplemental Table S1. GE varieties with agronomic Supplemental Table on the of “omics” to identify food Supplemental Table GE varieties with altered metabolic Supplemental Table the of “omics” in food safety