INFORMATION SYSTEMS FOR BIOTECHNOLOGY


January 2006
COVERING AGRICULTURAL AND ENVIRONMENTAL BIOTECHNOLOGY DEVELOPMENTS


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IN THIS ISSUE:



OPENING PANDORA'S BOX: GOVERNANCE FOR GENETICALLY MODIFIED FORESTS
Claire Williams

Planting genetically modified (GM) or transgenic forest trees for wood production is now feasible on a commercial scale worldwide. What are the benefits? What are the risks? This became an open question two years ago on December 10, 2003, when the United Nations declared that every sovereign nation should decide on its own whether or not to use genetically modified forests for carbon sequestration.

Although feasible on a commercial scale, we are still in the early stages of GM technology for forest trees. Some of the major determinants shaping risks of commercial-scale use include type(s) of inserted DNA construct or transgene,1 but also 1) reproductive biology of the forest species, and 2) the forest production or silvicultural systems.2 To date, GM forest trees are being tested in small trials worldwide. Only China is planting GM forest trees on a commercial scale.

Central to the issue of GM forest trees is the question of biosafety. Will effective biosafety protocols eventually become available, or should we accept that escape of GM forest trees is inevitable and study ecological consequences instead? Here I present the argument for the latter and propose a public-private partnership for this purpose, a technology trust.

Commercial GM Forests: Predicting the Long-term Consequences
Each nation sanctioning genetically engineering forest trees must decide 1) what biosafety protocols should be considered, if any, and 2) weigh the consequences in the event that gene flow from GM forest plantations to the surrounding forest is not deterred. Two opposing schools of thought are emerging in response to these two queries. The first is the Biosafety Premise, which ascertains that effective biosafety protocols will eventually be possible for GM forest trees. The opposing view, the Ecological Premise, is that transgene escape into the indigenous forest is inevitable, so studying ecological consequences deserves a higher research priority than continuing research leading to better biosafety protocols. Each nation must also consider the lengthy timeframe inherent to forest policy. To quote poet Wendell Berry: "Invest in the millennium. Plant a sequoia." Here we are reminded that the impact of GM commercialization, whether harmful or not, will outlast a human life span and certainly extend well beyond the purview of regulatory oversight.

Biosafety Premise: Biosafety measures can prevent transgene escape from GM forest trees
In the U.S. and Canada, regulatory agencies now recognize that one set of regulations do not fit all plants. GM forest trees are only one of many examples that require customized guidelines. Consider the case of biocontainment zones commonly used for GM crop plants. The width of the biocontainment zone around the transgenic planting is usually determined by gene flow data collected experimentally,3 but the distance for wind-pollinated conifers occurs on the scale of kilometers that is too vast to be deterred by a biocontainment zone around the GM planting. Using detailed model simulations of pollen and seed trajectories in a turbulent atmosphere shows that escape of seeds or pollen beyond a 1-kilometer periphery of the transgenic planting has a 100% certainty.4,5 Biosafety for GM conifers will not parallel protocols used for GM agricultural plants.

At the heart of the biosafety issue for any GM forest species is the question of how to manage for long-distance dispersal (LDD). Preliminary model simulations show that, although local neighborhood diffusion (LND) accounts for roughly 99% of the seeds and pollen, the dispersal process of real interest is LDD, which accounts for dispersal of the remaining 1%. With long-distance dispersal, seeds and pollen are vertically uplifted above the canopy by updrafting air currents, where they are rapidly moved

on the order of kilometers from the source.5 Transgene escapes via LDD pose the greatest risk of remote GM colonization for forest trees.

Models predicting LDD distances for Pinus taeda (Fig. 1) not only predict dispersal distances but also point to some testable hypotheses germane to developing biosafety protocols. Proponents argue that this type of research is too preliminary to be conclusive. Consider the following four caveats as indications of how much more research still remains to be done on GM forest biosafety.

1) Published LDD predictions and associated diffusion rates for GM colonies4,5,6 (Fig. 1) model dispersal from the GM source into a continuous forest canopy composed of the same species at the same age and height. This means that LDD predictions cannot be extrapolated accurately to the case where the GM planting is surrounded by a taller forest canopy at its periphery. Using old-growth forests as a biocontainment zone around a commercial transgenic plantation is an interesting but untested hypothesis for reducing transgene escapes. This complex scenario could be modeled using mechanistic approaches but reducing, not deterring, gene flow from GM trees is the likely outcome.

2) A lower volume of dispersed seeds and pollen corresponds to a drop in the absolute number of LDD escapes. If number of LDD escapes is the risk criterion, one could hypothesize that even leaky reproductive sterility methods can provide an acceptable biosafety protocol. Absolute suppression of reproduction may not be needed. If so, how low must diaspore volume drop before LDD escapes fall below an acceptable level? How does one determine the acceptable level? The leaky mitigation hypothesis can also be addressed using mechanistic models coupled with gene flow models. Here, too, the argument is for reduced gene flow, not an absolute deterrent.

3) LDD predictions are so specific to the mating system particulars of each forest tree species that this question must be considered on a case-by-case basis. To date, dispersal distance and colonization predicted for GM seedlings are specific to the mating system of one forest tree species, Pinus taeda. But all forest trees are not wind-pollinated; some plantation species are insect-pollinated or even self-pollinated. Even among wind-pollinated pines, some require fire for seed dispersal. Age of reproductive onset varies widely among commodity forest species, as does the volume of seed and pollen dispersed each year. Many forest tree species produce a high number of empty seeds due to physiology or pest predation. In any event, predictions of LDD numbers are sensitive to these input variables (Fig. 1) from each species' mating system, so generalizations from one commodity species may not apply to each species in question. Gene flow modeling is needed over a wider range of species.

4) Dispersal is only the first part of the gene flow equation. We still do not know much about actual gene flow via LDD at this time for any forest tree species. LND dispersal distance has a close corollary to average gene flow distances reported using organellar markers, so LDD, as a rare event, goes undetected in most experimental gene flow studies. Escaped LDD pollen can travel long distances for many hours or even days, so it is subjected to harsh conditions during flight. What is the viability for LDD pollen? Is it capable of germination or even fertilization? Experimental data on viability along these intermediate steps are needed before dispersal distances can be translated into actual gene flow estimates.

Ecological Premise: Emphasis should be on ecological consequences, not deterring GM escape
Proponents here argue that gene flow from GM plants is inevitable so research funding should be directed away from developing sophisticated methods of mitigating transgene dispersal and re-allocated to the study of ecological consequences of transgene colonization.7 Similarly, Canadian regulatory agencies also view transgene escape in forest trees as inevitable,8 and once the escape of transgenes has occurred into feral forest tree populations, it cannot be reversed. If biosafety protocols prove futile given the scale of gene flow from certain GM forest commodity species then only two choices remain: 1) abandon the GM technology for forest trees; or 2) opt for deregulation of GM forest trees.

Indeed, some nations may decide that a moratorium on GM forest trees is the best fit. For others, pressure to deregulate GM forest trees will come from the market place if GM technology is viewed as a critical part of the portfolio for preserving national competitiveness in global markets. Plantations do provide a disproportionate share of the world's wood relative to the land area they occupy, so here the relevant ecological question becomes whether transgenic forest plantations, justified as a means of sparing timber harvests in more fragile forested ecosystems, will do harm to the very resource they purport to protect.

Despite market forces, deregulation must be balanced against the impact of transgene escapes on small family forests that surround larger corporate forest plantations. In the U.S., it seems doubtful that even the most affluent of the family forest owners will be early adopters of transgenic seedlings for their own forest regeneration, but with deregulation these owners will have to contend with the unknown consequences of transgene escapes coming from adjoining plantations. Transgenic effects of GM forest trees, once released, constitutes a Pandora's Box. Will the effects be beneficial, benign, or harmful? This unanswered question is troubling for those who seek deregulated use of transgenic pine plantations and the question is deeply disturbing to those who view the forest as symbolic of nature itself.a

Studying ecological consequences of deregulation implies a short timeframe for detecting transgene effects, whether good, neutral, or bad. By favoring short timeframes for research, we must overlook evolutionary consequences as a criterion for decision-making. Consider the following example. Pines, among the oldest seed plant lineage on earth, have persisted for nearly 200 million years. Few advocates of GM pine plantations in the 21st century have considered this decision from the perspective of evolution. Many pine species have an open-ended hybridization system, so conditions can favor indefinite persistence of transgenes in groups of neighboring or sympatric species, also known as species complexes.

Species complexes with a reticulating, open-ended fate of hybrids, known as the homogamic hybrid system, occurs in several forest tree species.9 From this system, one can predict the conditions that will lead to a persistent fate for any transgene. A DNA construct or transgene escapes from a transgenic pine plantation into sympatric populations of a closely related species. Interspecific hybrid adults are fertile and readily cross not only with the original parent species but are also capable of hybridizing with other related species. The transgene can persist indefinitely under two conditions: 1) if the transgene confers a positive selective advantage; or 2) if the transgene is selectively neutral within a large random-mating population.

In some cases, deregulation will result in a sharp tradeoff between meeting global wood demand while ignoring unknown ecological (and evolutionary) consequences. A better alternative is proposed here: form a public-private partnership or a technology trust for studying ecological consequences of GM forest trees.

A Caveat to the Ecological Premise: A Technology Trust
An alternative to deregulation is to form a technology trusta short-term regulatory solution for collecting data on risks and benefits.2 The technology trust, formed as a public-private research partnership has three parts: 1) a subset of transgenic forest field tests designated as long-term study sites for collecting relevant data for sound benefits and risk analyses; 2) a technology tax on transgenic forest field testing which carries a hold-harmless provision to the payee or protection against future liability claims; and 3) formalizing a federal gene conservation program as a hedge against molecular domestication of forests. Relevant data on benefits and risks would be openly available and published in peer-reviewed journals. The technology trust would thus provide a platform for public dialogue about emerging technology. The proposed technology trust could be designed and run with scientific oversight from government, university, and private-sector research organizations.2

The main advantage of a technology trust is that it provides experimental data. It protects national forests against risks inherent to molecular domestication on private lands. And it opens public dialogue on the risks and benefits associated with for-profit research in long-lived forests. The latter is important in the U.S. and other developed nations where private investment is funding the creation of novel GM trees at a rate that is outpacing biosafety and scientific assessment of ecological impact. In the case of the U.S., no platform for public dialogue has been formalized, yet this nation is the world's most powerful advocate for biotechnology advance.

In summary, using GM technology for forest trees is raising controversy but this is the least of genomics-based technology yet to come. Using a snippet of DNA inserted into chromosomes of naturally-occurring plants and animals is only the beginning, not the finish, of the controversy. Compare this recombinant DNA technology to the commercial potential of synthetic DNA genomes. With new technology looming in the future, now is the time to center dialogue on the real question behind the controversy of GM forests, a question which has no parallel in medicine or agriculture biotechnology: what are the limits to our biotechnology governance in the natural world? Will we protect fragile ecosystems at the interface with production forests? At the very least, a technology trust is essential for shaping the fate of the forest itselfand a necessary part of the portfolio for any nation deciding to go forward with the use of GM forests for carbon sequestration.

a On November 10, 2005, the Global Justice Ecology Project and the STOP GE Trees Campaign announced the release of A Silent Forest: The Growing Threat, Genetically Engineered Trees, a 45-minute documentary narrated by Dr. David Suzuki, host of PBS The Nature of Things.

References

Strauss SH (2003) Genomics, genetic engineering and domestication of crops. Science 300, 61-62

Williams CG (2006) Questioning commercial use of transgenic conifers. In Landscapes, Genomics and Transgenic Conifers, ed. CG Williams, 31-34. Dordrecht Netherlands: Springer Press

Linacre NA, Ades PK (2004) Estimating isolation distances for genetically modified trees in plantation forestry. Ecological Modelling 179, 247-257

Katul GG, Williams CG, Siqueira M, Poggi D, Porporato A, McCarthy H, Oren R (2006) Dispersal of transgenic conifer pollen. In Landscapes, Genomics and Transgenic Conifers, ed. CG Williams, 121-143. Dordrecht Netherlands: Springer Press

Williams CG, LaDeau SL, Oren R, Katul GG (2006) Modeling seed dispersal distances: implications for transgenic Pinus taeda. Ecological Applications (in press)

Williams CG, Davis BH (2005) Rate of transgene spread via long-distance seed dispersal in Pinus taeda. Forest Ecology and Management 217, 95-102

Lu B-R (2003) Transgene containment by molecular means it is possible and cost-effective? Environmental Biosafety Research 2, 3-8

Bonfils A-C (2006) Canada's Regulatory Approach. In Landscapes, Genomics and Transgenic Conifers, ed. CG Williams, 229-243. Dordrecht Netherlands: Springer Press

Grant V. (1981) Plant Speciation. New York: Columbia University Press

Claire Williams
Duke University, Department of Biology
Durham NC

Claire.Williams@duke.edu


RISK ASSESSMENT FOR INSECT RESISTANCE TRANSGENES
Colleen K. Kelly

Insect resistance (IR) transgenes offer the advantage to agricultural plants of protection from herbivory. There is concern that should IR transgenes escape from the agricultural setting through pollen or seed flow, the advantage conferred by the transgene will not only allow them to persist, but to 'take over' natural populations. Transgene take-over is seen as a problem in that a transformed plant may be unavailable to the herbivores natural to the system, making them more vulnerable to extinction through lowered population size, and so on up the food chain.1, 2

To address the concern that resistance transgenes might persist in the natural system, Kelly et al.3 have produced an analytical model targeting the ecological interaction between IR transformed and untransformed plants in the natural community. Successful establishment of a novel allele in a population is a combination of not just the allele's ability to disperse through pollen and propagule, but also the novel allele's compatibility with the genome of the natural population and the ecological dynamic between plants with and without the new allele, i.e., effective gene flow.4 Kelly et al.'s analytical model specifies the overall character of interactions between factors, allowing predictions outside the range of tested conditions. By so doing, the model not only assesses the risk of any particular transgene, it also identifies points in the dynamic that are sensitive to or may best reward manipulation for control of transgene impact.

Kelly et al. approached the problem of insect resistance transgenes in natural populations by recognizing that temporal fluctuations are the central character of the ecological dynamic: year to year variability in herbivory is the rule in both natural and agricultural systems.5 The appropriate class of models is therefore a storage dynamic, called so because the long-term persistence of a population through periods of low reproduction is 'stored' in either long-term reproductive capacity or dormant propagules. Storage models focus on the probability of recruitment into the reproductive class. The action of the selective factor is thus most important at immature stages of the plant, a schedule also consistent with herbivory, where the same amount of herbivore damage can kill young or small plants but has little effect on larger, mature plants.

For a competitive interaction between plants with and without an IR allele, the dynamic is a two-member lottery model comprising one plant type that is more sensitive to the selective factor than the otherthe untransformed and transformed lineages, respectively. Differential sensitivity dictates that when the selective factor is present (here, herbivory), the resistant type has the advantage. However, when the selective factor is absent, the resistant type has no advantage, and if there is any net cost associated with resistance, that cost will set the resistant type at a competitive disadvantage for the period the selective factor is not acting.3,6,7 Whether transformed and untransformed plants may stably coexist and in what relative abundances or whether the IR transgene will take over the population depends on 1) the relative frequency of good and bad conditions (high and low herbivory), 2) the relative advantage the IR transgene gives a transformed plant, and 3) the relative disadvantage, if any, the IR transgene carries with it. The differential sensitivity (DS) model was applied to oilseed rape (OSR), where it was found that under levels of herbivore variability established in the field5, it takes relatively little disadvantage of carrying the transgene to limit domination of the natural population by the IR allele (Fig. 1).

This may be treated as a general conclusion. However, the larger point is not that IR transgenes may be relatively easily contained. Rather, the ecological model provides a tool with which to determine how best to do this, as well as to assess how well it has been done. In the model, all terms are ratios of the character in question in the transformed versus untransformed plants. The risk of a transgene can thus be assessed under protected conditions and calibrated by the response of the untransformed plant under more natural conditions, as at least a first pass evaluation.

It may be possible to manipulate either costs or benefits in order to contain the transgene. Benefit, which is quantified in the model as growth in the absence of competition (), by definition is maximized for commercial return on the crop, and so may not be available for manipulation. Costs may therefore be the more likely target for manipulation: if you are going to have a magic helmet then you must have an Achilles heel. Some costs are a function of resistance itself, e.g., additional protein construction. It is not possible to have the transgene without these costs and the trade-off between costs and benefits in this case would be in choosing the transgene. As with any 'cost', its usefulness as a control will come in two parts: the extent to which it does not cut into commercial returns on the transgene; and the reliability of its genetic linkage to the transgene over time.

The model delineates control possibilities in addition to costs inherent to the transgene. Costs most amenable to manipulation are included in two composite variables: seedling competitive ability (β) and seeds viable in the first season after seed set (Υ). β includes factors such as overtopping, and this is where construction costs would be taken into account. Υ is not simply seed set; Υ determines not just seedlings in year t + 1, but the character of the seed bank. Υ interacts with the behavior of seeds in the seed bank (germination fraction, persistence from season to season) to produce seedlings in future seasons. It is an essential part of the population persistence of a species that has a chance of producing few or no successful offspring in any one year. Υ, the number of seeds that make it through the first winter viable, is the first level of control for any novel allele. If Υ is low, then there are few viable seeds to remain in the seed bank and the capacity to get through bad years is severely limited. If Ε is high, then control shifts to the germination fraction Ε. If Ε is high, then, again, there are few seeds in the seed bank to get through bad years. If Ε is low, control shifts to S, the fraction of seeds that survive from one year to the next. Persistence over hard times is then limited by a low S. Pollen viability, η, where male sterility manipulation may be applied, plays a similar role to Y.

The equations of the model may be iterated numerically but Kelly et al. also provide a useful calculation for doubling time to assess the rate of spread of the transgene at early stages (when hemizygotes, individuals with only one copy of the transgene, comprise approximately less than 20% of the population). Although it requires the same information as the more detailed calculations that gave rise to the above conclusions, the doubling time equation is easier to calculate and provides a reasonable estimate of hemizygote spread.

The focus on the natural population may seem to imply that the ecological interaction will be of importance only once the allele arrives there. In fact, it is likely that the ecological dynamic will have an effect at every step of the journey of the allele from crop to natural community. As introgression of the allele into the natural genome proceeds, the increment of protection that the allele offers will decrease in the context of the already well-protected wild genome;8 any cost it incurs is likely to have greater impact in a natural situation in which nutrient supplements become less and less available with increasing distance from the 'home' agricultural field. The model can be applied to determine this, by specifying the values of the factors that go in the applicable ratios.

The goal of the model is to clarify the components and importance of fitness in the interaction between individuals with and without IR alleles in nature. The model may be usefully modified to include pathogens and seed predators that work either on the seed while it is still retained on the parent plant or in the seed bank. However, the model is also of significance to the basic ecology of sexually compatible invasive-native pairs where the active difference is in vulnerability to local herbivores, pathogens, or seed predators, whether the invasive individual is a crop, unwanted alien, or new mutation3.

References

1. GM Science Review Panel. (2003) GM science review (first report): an open review of the science relevant to GM crops and food based on interests and concerns of the public. Department of Trade and Industry, London, pp. 109-194

2. Information Systems for Biotechnology (2004) ISB News Report, January 2004, available online: http://www.isb.vt.edu/news/2004/news04.Jan.html

3. Kelly CK, Bowler MG, Breden FM, Fenner M, Poppy GM. (2005) An analytical model assessing the potential threat to natural habitats from insect resistance transgenes. Proceedings of the Royal Society of London B 272, 1759-1767

4. Hendry AP, Taylor EB, McPhail JD (2002) Adaptive divergence and the balance between selection and gene flow: Lake and stream stickleback in the misty system. Evolution 56, 1199-1216

5. NERC Centre for Population Biology, Imperial College (1999) The global population dynamics database. Available online: http:www.sw.ic.ac.uk/cpb/cpb/gpdd.html

6. Kelly CK, Hanley ME (2005) Juvenile growth and palatability in congeneric British herbs. American Journal of Botany 92, 1586-1589

7. Kelly CK, Bowler MG (2005) A new application of storage dynamics: differential sensitivity, diffuse competition and temporal niches. Ecology 86, 1012-1022

8. Belsky AJ, Carson WP, Jensen CL, Fox GA (1993) Overcompensation by plants herbivore optimization or red herring? Evolutionary Ecology 7, 109-121

Colleen K. Kelly
Senior Research Associate, Department of Zoology
University of Oxford, South Parks Road, Oxford OX1 3PS UK
colleen.kelly@zoo.ox.ac.uk


PROTEOMIC PROFILING AND UNINTENDED EFFECTS IN GENETICALLY MODIFIED CROPS
Sirpa O. Kärenlampi and Satu J. Lehesranta

It is generally accepted that traditional food is safe for the majority of consumers. For the introduction of a new variant or cultivar developed from a traditional crop plant, maximum limits have been set in some cases, e.g., for potato and oilseed rape, to the content of known toxins. The requirements are much more stringent if the crop is developed by using genetic engineering. Why is it so? In a majority of cases seen so far, a new gene, often derived from other plants or microbial species, has been introduced to a non-predetermined location in the plant genome. It is quite feasible to ask the question whether the new gene products are safe or not. Therefore, for all genetically modified crop plants, the safety of the newly introduced proteins needs to be demonstrated before the plants can be released into the market.

Another point of concern is the random integration of the new gene into the plant genome. Both the new gene itself and its site of integration may give rise to unintended adverse effects. For example, transgene integration might interrupt regulatory sequences or open reading frames leading to novel fusion proteins and, thereby, modify plant metabolism.1 These modifications could compromise the safety of the food crops by, for instance, leading to the production of new allergens or toxins. Having the gene and the integration site well characterised should provide a good basis for the safety assessment. However, it is a common practice today to perform a large number of analyses, so-called targeted analyses, to demonstrate that the characteristics of the novel crop are comparable with those of the conventional counterpart, in addition to the intended alterations. Targeted analyses include key macronutrients, micronutrients, antinutrients, and toxins. In certain cases, toxicity studies on experimental animals are advised. And yet, the question about the unintended effects does not seem to be covered in a way that would escape all criticism.

Cellini et al.2 have considered transgene integration in the context of naturally occurring DNA recombination. It is well known that genetic variation is the cornerstone of plant breeding. Natural chromosomal recombination plays a central role in generating new variation. Non-homologous end joining, which is the predominant form of recombination in plants, rarely occurs without any sequence alterations, and usually gives rise to deletions of up to more than 1 kb and introduction of new filler DNA. Since the double-strand break repair system involved in recombination is more error-prone in plants than in other organisms, errors that change the original sequence occur at a very high frequency. The fact that gene-rich regions (and genes) are hotspots for recombination has facilitated the emergence of novel characteristics in crop plants.

Integration of exogenous DNA (transgene) occurs via the same mechanism as natural recombination. Several types of rearrangements are thus observed, both in transgene integration sites and in natural recombination sites. While this mechanism provides a selection of natural variation for breeders, it is also a source of unintended effects similar to that in genetically engineered crop plants.

In the light of variation generated by natural recombination and by the repertoire of conventional breeding technologies exploited for decades, the question is how much variation in the overall genetic makeup of a crop plant might be generated by the transfer and integration of a single gene, compared to the variation already existing. A related question is how probable are the unintended effects that extend beyond this variation.

To answer these and other questions, we made a comparative analysis of eight GM lines of potato, including vector-only lines without the target gene.3 The parent cultivar, Desirée, and a line that had undergone tissue culture only, were included as non-GM comparators. Nine of 730 proteins showed statistically significant differences among the GM lines and controls. No new proteins that would be unique to the individual GM lines were observed. The conclusion from this study, supported by the EU-funded GMOCARE project, was that there was no evidence for any major changes in protein patterns of the GM lines tested.

It can be argued that proteomics is not sensitive enough to find differences between potato lines or varieties. The European breeders have developed a large number of very different potato cultivars, many of them with genes introgressed from other Solanum species. Of that diversity, we analysed 32 non-GM potato genotypes, including 21 conventional cultivars, eight landraces, and three lines of S. phureja. From that study it was obvious that there is a great deal of variation in the protein patterns of the different potato genotypes: out of 1111 protein spots analyzed, 1077 differed significantly among two or more genotypes. The protein profile of the diploid species S. phureja could be clearly distinguished from the ones of the tetraploid S. tuberosum genotypes.

These studies indicated that the variation between the non-GM cultivars/genotypes was much greater than the differences between the GM lines. This was further confirmed by direct comparison of some of the GM lines with two non-GM genotypes; there was no separation among the GM lines and their control, but the two non-GM genotypes separated very clearly from each other and from all Desirée-based lines. In other words, there were considerably fewer differences between the GM and non-GM lines of the same genetic background than between different non-GM cultivars. Many of the proteins that contributed to the separation of the non-GM genotypes appeared to be involved in disease and defense responses, sugar and energy metabolism, or protein targeting and storage, and are presently considered to convey no safety risk.

Our results have been corroborated recently by Catchpole et al.,4 who compared several GM potato lines and cultivars using metabolic profiling. The authors found differences between the GM lines only in those metabolites that were targets of the genetic modification; apart from those compounds, the GM lines could not be distinguished from their controls. On the other hand, all cultivars could be clearly distinguished from one another.

The results of both profiling studies are not surprising, considering what is now known about the nature of plant genome and its dynamics. Even though genetic modification does not generate major changes apart from the ones targeted, a protein identified at an increased level in the GM line compared to the conventional counterpart might be worth further attention if the level clearly falls outside the normal variation. This is to exclude any risks from, for example, potent allergens. As current profiling methods produce a huge amount of data, it is almost inevitable that some statistically significant differences will be found. Therefore the focus should be in truly consistent differences.

How feasible are profiling techniques in general as tools to provide additional data for the risk assessment of GM crops? Do they provide added value worth the investment? Do they give reassurance that unintended adverse effects have not occurred? Non-targeted methods, such as transcriptional, protein, and metabolite profiling, offer potentially unbiased approaches to the detection of unintended effects. Of these, transcriptomics is possibly the most comprehensive, with full genome arrays currently available for a limited number of plant species. While it is clear that a comprehensive coverage of all proteins and metabolites present in a given tissue is difficult to obtain with current technologies, proteins are the key molecules of interest, as they are potential allergens and catalyse the synthesis of metabolites, some of which are potential toxins.

To assess observed differences within the context of natural variation in composition, comparative data of 'normal' protein levels are needed to understand the effect of genetic background, developmental stages, physiological states, environmental conditions, and cultivation techniques, and to be able to set the criteria against which a determination of a significant difference worth considering as a possible safety risk can be made. Currently there is very little information publicly available on protein patterns in potato tubers or in any other crops.

As with other profiling methods, proteomic screening is not yet routine for assessing the safety of GM products. However, proteomic profiling has the potential to reduce uncertainty by providing much more information about crop composition than does targeted analysis alone, especially in combination with other profiling methods. In addition, multivariate statistical methods can give a much better overall picture of how the given samples relate to each other than does the comparison of single compounds. These facts may make proteomics increasingly important when developing second generation GM crops with multiple genes, engineered metabolic pathways, or edible pharmaceuticals.

References

Kuiper HA, Kleter GA, Noteborn HPJM & Kok EJ (2001) Assessment of the food safety issues related to genetically modified foods. Plant J 27, 503-528

Cellini F et al. (2004) Unintended effects and their detection in genetically modified crops. Food Chem Toxicol 42, 1089-1125

Lehesranta SJ, Davies HV, Shepherd LVT, Nunan N, McNicol JW, Auriola S, Koistinen KM, Suomalainen S, Kokko HI, & Kärenlampi SO (2005) Comparison of tuber proteomes of potato (Solanum sp.) varieties, landraces and genetically modified lines. Plant Physiol 138, 1690-1699

Catchpole GS, Beckmann M, Enot DP, Mondhe M, Zywicki B, Taylor J, Hardy N, Smith A, King RD, Kell DB, Fiehn O & Draper J (2005) Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc Natl Acad Sci USA 102, 14458-14462

Sirpa O. Kärenlampi and Satu J. Lehesranta
Institute of Applied Biotechnology, University of Kuopio
FIN-70211 Kuopio, Finland

skarenla@messi.uku.fi



PEW INITIATIVE WORKSHOPS SCRUTINIZE ANIMAL BIOTECHNOLOGY
Phillip B. C. Jones

Late last year, the Pew Initiative on Food and Biotechnology released proceedings from two 2005 workshops on ethical, regulatory, and commercial aspects of genetically modified (GM) animals. Workshop participants included animal biotechnology researchers from academia and industry; industry representatives from biotech, food, and agricultural sectors; consumer and animal welfare advocates; ethicists; and officials from federal and state regulatory agencies. The Pew Initiative website (http://pewagbiotech.org/) offers copies of workshop reports. Here are some highlights.

Ethics and Animal Biotechnology

One GM animal has entered the U.S. marketplace so far: the GloFish™, a fluorescent zebra fish. The Food and Drug Administration did not see a need for its regulatory oversight and allowed the fish to swim in the stream of commerce. Other types of GM animals await FDA approval for commercialization, including a GM salmon engineered for accelerated growth. The near future may bring GM animals that produce pharmaceuticals in their milk, express desirable production attributes, or contain organs suitable for transplantation into humans. The FDA has also been reviewing an ongoing study on the safety of animal clones and their offspring in the human food supply.

The commercial success of any products derived from GM or cloned animals will partly depend on the public's acceptance of those products. Yet public opinion studies indicate that attitudes about the engineering and cloning of farm animals tend to be strongly negative in a vague sort of way. That is, many base their opposition on objections to "playing God" or some report that they "just don't like it."

In January 2005, the Pew Initiative hosted a workshop on moral and ethical aspects of GM and cloned animals designed for use in agricultural production. Dr. James Robl, president and chief scientific officer of Hematech, LLC (Sioux Falls, South Dakota), offered an overview of genetic engineering and cloning research in animal agriculture. For example, researchers have investigated methods for increasing milk protein content by inserting extra copies of beta or kappa casein genes into dairy cattle. To reduce fat and increase feed efficiency in swine, investigators have introduced an insulin-like growth hormone gene.

Researchers have also used genetic engineering to produce human therapeutic proteins in the milk of transgenic animals. Engineered sheep, goats, and cows, for instance, produce human antithrombin III, monoclonal antibodies, alpha lactalbumin, serum albumin, lactoferrin, and other therapeutic proteins. These animal production systems, Robl said, prove most valuable when the proteins cannot be produced in any other way. Consequently, Robl suggested that the use of mammary glands of transgenic animals would probably never support a huge industry.

More generally, Robl said that the agricultural transgenics industry consists of only a handful of people, and that the majority of them perform academic research, not commercial research. Most potential investors have decided to wait and monitor public opinion before they spend millions of dollars to place a transgenic animal-derived agricultural product on the market.

Dr. Chester Gipson, deputy administrator of animal care at the USDA's Animal and Plant Health Inspection Service, explored the topic of animal welfare. While legislators designed the Animal Welfare Act to protect animals, Gibson said that the Act excludes farm animals engineered to produce more meat or to grow faster. However, the Act does encompass transgenic livestock used in biomedical research, such as those designed to produce human vaccines in milk. Confusion remains about whether the Act's provisions will cover those animals after the research ends and the commercialization of the products begins.

Dr. Mickey Gjerris, assistant professor at the Danish Centre for Bioethics and Risk Assessment in Copenhagen, offered insights about European concerns. The Eurobarometer survey, an appraisal of the views of 1,000 people in each country, revealed Europeans' skepticism about biotechnology applied to animals or food production. In Europe, the focus in debates about genetic engineering and cloning of animals tends to shift down a slippery slope to possible consequences of applying the technology to humans.

These European surveys have also uncovered a lack of evidence for the view that educating people about biotechnology will increase their acceptance of it. Education may help people make up their minds about biotechnology, but they do not necessarily become more positive about the technology.

Europe has rejected GM crops, partly because the ethical concerns of the public have been deemed irrelevant or less important, Gjerris suggested. The public must have the opportunity to voice concerns, and these worries must be taken into consideration. You have to make people feel that you take them seriously, he said, in order for them to take you seriously.

Gjerris' advice applies to the United States as well. The Pew Initiative's executive director Michael Fernandez underscored this point in a press release about his organization's 2005 poll of U.S. consumers. "From the survey results," he said, "it is clear that moral and ethical concerns play a big role in forming consumer attitudes, particularly towards animal cloning, and that U.S. consumers want these issues to be part of the public debate. Despite these concerns, consumers do not support banning new uses of biotechnology, but are looking to government regulators to provide assurance that new products are safe."

Participants of the second animal biotech workshop also looked for that assurance.

Ad Hoc Regulation of Animal Biotech?

At the regulatory and commercial issues workshop, Pew Initiative founding executive director Mike Rodemeyer described the principles of the 1986 Coordinated Framework: biotechnology as a process does not pose unique risks; agencies should base regulation on the nature and intended use of the product, not on the process used to obtain the product; and existing laws can regulate biotechnology products. Under the Framework, the White House Office of Science and Technology Policy coordinated the efforts of the FDA, the U.S. Department of Agriculture, and the Environmental Protection Agency.

The FDA received authority to regulate the safety of food, food additives, animal feed, animal and human drugs, biologics, and devices derived from GM plants and animals. This diversity of responsibilities has sparked controversy. In particular, the lack of FDA guidance or regulations specific to transgenic animals, Rodemeyer said, has led to concerns about how an agency designed for supervision of drugs will regulate live animals.

Fred Degnan, a partner with King & Spalding, LLP (Washington, D.C.), explained that researchers who want to develop a marketable product from a transgenic animal typically establish an investigational new animal drug file with the FDA, and then perform research under the agency's requirements. Before a business can introduce its products into the marketplace, it must file a new animal drug application. The FDA then reviews the product for safety and efficacy.

How can the FDA consider a transgenic animal to be a drug? It doesn't, exactly. Although regulations on new animal drugs were written for conventional pharmaceuticals, the FDA applies the rules to GM animals, because the agency considers an introduced genetic construct to meet the definition of "animal drug" if it changes the structure or function of the transgenic animal.

Tom Bundy, who served as deputy assistant general counsel at the USDA, described how the USDA can weave regulation of transgenic animals into its rules. Bundy said that, although no USDA statutes explicitly provide authority to regulate transgenic animals, the Animal Health Protection Act could encompass transgenic animals engineered with a livestock disease or pest. The Act, a consolidation of animal quarantine laws, could also cover regulation of a transgenic animal if researchers had introduced a knockout or silencing gene to alter resistance to a livestock disease or pest.

Larry Culleen, an attorney in Arnold & Porter's environmental practice group (Washington, D.C.), spoke about the EPA's authority to regulate transgenic animals. The Toxic Substances Control Act covers broadly defined "chemical substances," excluding foods, drugs, cosmetics, pesticides, and tobacco. The EPA views TSCA as a safety net to capture any biotech product not covered by other laws. The agency's expansive interpretation of the Act can create a situation in which a developer of a transgenic animal will have to comply with both TSCA and FDA regulations.

Workshop participants repeatedly called on the federal government to clarify which agencies and statutory authorities will support regulation of the animal biotechnology industry. An FDA official responded that regulatory agencies have been working at the "highest levels" for at least two years to determine how to regulate transgenic animals and their products within the Coordinated Framework. The official admitted, however, that it is difficult to predict when these jurisdictional issues will be resolved. After 20 years, the Coordinated Framework may require more than reshaping; it may require a reinvention.

Phill Jones
BiotechWriter.com
PhillJones@nasw.org




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