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Plant biotechnology and breeding: allied for years to come
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Opinion
TRENDS in Plant Science
Vol.8 No.2 February 2003
Plant biotechnology and breeding: allied for years to come Piero Morandini1 and Francesco Salamini2 1
Department of Biology, University of Milan, via Celoria 26, 20133 Milan, Italy Max Planck Institut fuer Zuechtungsforschung, Department of Plant Breeding and Yield Physiology, Carl-von-Linne` weg 10, 727272 Koeln, Germany 2
Plant metabolic engineering is lagging behind other kinds of genetic manipulation of plants. Creating metabolic pathways or improving their yields requires a better understanding of plant metabolism and of its regulation. Metabolic Control Analysis provides an interpretation of experimental failures and a guide for manipulators. It suggests also that there might be intrinsic limits to raising yields in already abundant products. At present, these limits can be dealt with more effectively by plant breeding.
…And a job for each Each man to his work. (Choruses from ‘The Rock’ by T.S. Eliot) Agricultural biotechnology has the potential to develop more-sustainable farming practices. For instance, plants expressing single insecticidal proteins, such as Bt cotton, reduce the use of exogenous pesticides [1]. This application of biotechnology usually requires the transfer of single genes from distantly related species and, in spite of the problem of acceptance by consumers, farmers in developed and developing countries have readily taken them up. A less attractive application of biotechnology, which nevertheless holds great promise, is the rational and selective alteration of metabolism (the so-called ‘metabolic engineering’) to increase the production of endogenous metabolites or to achieve the synthesis of metabolites not produced by plants. Metabolic engineering in plants has indeed yielded remarkable and encouraging results by increasing the yield of minor components, such as vitamin A, vitamin E and essential oil [2– 4], as well as the composition of major components, such as fatty acid (e.g. [5]) or starch [6], and by engineering entirely new pathways, as in the case of polyhydroxyalkanoates [7]. The alternative possibility, aimed at improving yields in already abundant metabolic products, such as starch, has been less successful and has been unable to yield viable market products. In certain cases, results were even contrary to expectations: attempts at increasing sink Corresponding author: Piero Morandini ([email protected]).
strength and starch accumulation in potato tubers by increasing sucrose hydrolysis and metabolism, led to the induction of glycolysis but to a decrease in starch content [8,9]. By contrast, plant breeding has been extremely successful in increasing yields, even though, as a technology, it is purely empirical and based on established practices rather than on understanding the molecular-physiological bases of the traits under selection. Are there reasons to explain this contradiction? We argue that plant breeding will not be substituted in a few years by plant biotechnology, rather the two different approaches are and will be cooperating for years to come. Complexity of metabolism Metabolic engineering needs a better understanding of metabolic regulation and plasticity because accumulating data do not fit into conventional theories. For instance, enzymes defined as ‘rate limiting’ can be greatly or significantly reduced (e.g. cytosolic pyruvate kinase, [10] and Rubisco, [11]) or overexpressed several-fold (phosphofructokinase, [12]) without substantial change in metabolic fluxes. Arabidopsis mutants lacking the glyoxylate cycle, once regarded as essential for postgerminative growth, germinate efficiently under favourable conditions [13]. By contrast, enzymes regarded as non-limiting (either because they are non regulated, catalyse near equilibrium reactions or their maximum activities are orders of magnitude higher than the pathway flux) have been shown to cause sensible reduction in flux when reduced (e.g. aldolase and transketolase [14]). We are also unable to predict deleterious effects of overexpressing enzymes in certain compartments (e.g. [15]), possibly because of enzymes competing for common precursors. The conclusion is that metabolic pathways are complex in several ways. Within a cell, a thousand or more metabolites are distributed among several compartments and, even though we know the metabolic routes, the concentrations of intermediates and the forces driving metabolic conversions (the equilibrium constant of the reactions), we are unable to predict the modulation of metabolite concentration because of a change in some environmental or cellular parameter (e.g. enzyme quantity). A change in one enzyme modifies the concentration of its substrate(s) and product(s) which, in turn, will affect the velocity of the same (and of neighbouring)
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Opinion
TRENDS in Plant Science
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Box 1. Metabolic control analysis and its implications Metabolic control analysis (MCA) officially began in 1973 with two seminal works [a,b]. The concept of a ‘rate-limiting enzyme’ was replaced by a coefficient expressing the degree of control over flux exerted by every enzyme (flux-control coefficient, CJ) [c], see also http://bip.cnrs-mrs.fr/bip10/mcainfo.htm for tutorials about MCA). Major theory implications are: † There are intrinsic and serious limits to yield (flux) improvement achievable by single enzyme overexpression [d,e]. In principle, increasing all the enzymes in a metabolic pathway will do the job. Indeed, several physiological flux increases depend on the coordinate activation or induction of several enzymes within a pathway: for instance, several genes in the pathways for oil biosynthesis and oil degradation are upregulated [f,g]. † Even if the transformation of plants with several genes is now technically feasible, a substantial increase in flux might not be possible for those pathways where some enzymes are already at high concentration and close to their physical limit (e.g. Rubisco, triose phosphate translocator, plasma membrane Hþ-ATPase). Moreover, overexpression of an already abundant enzyme could cause a reduction in other enzymes and therefore a reduction in flux [h]. † The extent of flux increase will also depend on being able to buffer the concentration of metabolites available to and produced by the pathway (S and P of Fig. 1). Efficient buffering requires the ability to increase the supply of the pathway substrate and the demand for its product of the same absolute value (the so-called ‘universal method’) [i]. If the substrate is shared by many different pathways, the creation of a new pathway will not affect endogenous metabolism if it diverts only a small fraction of the flux. † The role of conventional crop breeding does not overlap with (and therefore is not replaceable by) plant molecular genetics. This is true not only for quantitative traits depending on several factors, such as for yield or resistance to environmental stress, but also for increasing flux
enzymatic reactions. In other words, flux and metabolite concentrations are systemic variables (i.e. they are properties of the system as a whole and not of isolated enzymes). The next frontier needs better models The completion of the Arabidopsis genomic sequence [16] heralded the age of proteomics, functional genomics and metabolomics for plants. Advances in molecular techniques allow the simultaneous modulation of several enzyme activities [6,17,18], and analytical techniques allow us to measure the concentrations of hundreds of metabolites [19]. Faced with the power of such tools, what is limiting is our capacity to produce models describing the behaviour of metabolic pathways [20]. Tools are already at hand: software for the simulation of metabolic pathways (www.hort.purdue.edu/cfpesp/models/mo00015.htm), as well as a public enzyme database (e.g. www.brenda.uni-koeln.de). Most of these data are limited to in vitro conditions, which could be very different from conditions in vivo. This means that the data might not be good enough to derive a kinetic law (i.e. an equation describing the rate as a function of the concentration of substrate(s), product(s) and other effectors) or that the derived law might be mechanistically perfect, but inadequate to describe enzyme behaviour in vivo [21]. The future of metabolic engineering requires models that are able to predict the behaviour of metabolic networks in terms of flux and metabolite concentrations (e.g. [21]). http://plants.trends.com
in long pathways. At present, only plant breeding seems able to increase the level of several enzymes in a pathway reliably. The manipulation of plant transcription factors offers new chances for the future, but this will still depend on the presence of common regulatory elements.
References a Kacser, H. and Burns, J.A. (1973). The control of flux. Symp. Soc. Exp. Biol. 27, 65 – 104 [Reprinted in. Biochem. Soc. Trans. (1995). 23, 341 – 366] b Heinrich, R. and Rapoport, T.A. (1974) A linear steady-state treatment of enzymatic chains. Eur. J. Biochem. 42, 89 – 95 c Fell, D.A. (1997) Understanding the Control of Metabolism, Portland Press d Small, J.R. and Kacser, H. (1993) Responses of metabolic systems to large changes in enzyme activities and effectors. 1. The linear treatment of unbranched chains. Eur. J. Biochem. 213, 613 – 624 e Niederberger, P. et al. (1992) A strategy for increasing an in vivo flux by genetic manipulations. The tryptophan system of yeast. Biochem. J. 287, 473 – 479 f O’Hara, P. et al. (2002) Fatty acid and lipid biosynthetic genes are expressed at constant molar ratios but different absolute levels during embryogenesis. Plant Physiol. 129, 310 – 320 g Rylott, E.L. et al. (2001) Co-ordinate regulation of genes involved in storage lipid mobilization in Arabidopsis thaliana. Biochem. Soc. Trans. 29, 283 – 287 h Snoep, J.L. et al. (1995) Protein burden in Zymomonas mobilis: negative flux and growth-control due to overproduction of glycolyticenzymes. Microbiology 141, 2329 – 2337 i Kacser, H. and Acerenza, L. (1993) A universal method for achieving increases in metabolite production. Eur. J. Biochem. 216, 361– 367
A quantitative approach to metabolism Metabolic Control Analysis (MCA) is one of the theories trying to describe metabolic pathways and their behaviour in a more quantitative manner than classical biochemistry does (Box 1). The main principle of MCA is that the control of flux in a pathway is usually distributed over many enzymes. It follows that a substantial flux increase cannot be achieved without increasing the catalytic activity at multiple sites. Indeed, many experiments (e.g. [22,21]) support the view that many if not all the enzymes in a metabolic pathway contribute to determine the maximum flux sustainable by the pathway. The observation that most loss-of-function mutations are recessive supports the idea that a substantial reduction (up to 50% is expected in heterozygotes) in many enzymes does not translate into a visible phenotype (i.e. most enzymes are not limiting the flux). The explanation offered is that reducing the amount of an enzyme causes an increase in substrate(s) and a decrease in product(s) concentration. These changes increase the driving force of the reaction, thus causing the diminished number of enzyme molecules to work at higher velocity: the end result is a system sustaining a similar flux but with a different distribution of metabolites. Similarly, increasing the amount of enzyme might result in the reverse effect on metabolite levels without altering the flux substantially. MCA has relevant implications for plant biology and biotechnology (Box 1). For instance, a long-held belief of classical biochemistry is that feed-back inhibition on a biosynthetic enzyme by the
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Box 2. Increasing flux or concentration? Increasing the concentration of free metabolites such as amino acids is not equivalent to increasing their overall quantity: substantial concentrations can be achieved either by slightly increasing the biosynthesis or by slightly decreasing the consumption. Because the pool of amino acids incorporated into proteins (the main fate for most amino acids) is usually much larger than the free pool, a large increase in overall quantity (free and combined) always requires a large increase both in flux and incorporation into protein. Metabolic Control Analysis suggests that relieving feedback inhibition might be effective at increasing the free concentration of metabolites downstream of the inhibited enzyme, with the magnitude of such an increase being dampened away along the pathway, but not necessarily sufficient to increase the overall quantity substantially. The use of desensitized enzymes can therefore have unpleasant effects because some of the intermediate metabolites can become toxic at a certain concentration. At the same time, the strategy could be unable to deliver the desired effect: once the amino acid concentration has increased, the flux will depend on the demand (which has not changed) and, in growing tissues, on the volume increase. For instance, Hagai Karchi et al. [a] reported a several-fold increase in free Thr and Met content of tobacco seeds, but only a modest increase (6.5% for Thr and 6.8 for Met) in total content. Other works stress an increase in free Pro or Trp (e.g. [b]), but no mention is made of the overall quantity. A large increase in free Lys and a twofold (canola) to fivefold (Soybean) increase in total Lys seed content has been reported [c] by overexpressing, respectively, one or two desensitized enzymes in the pathway. Down regulating threonine synthase [d] increased Met free concentration by orders of magnitude in leaves and by an order of magnitude in tubers, but, beyond deleterious effects noted on plant vigour, no data are provided on total Met accumulation. Imposing a large increase in demand by overexpressing proteins rich in the relevant amino acids (e.g. sulfur-rich proteins improving the nutritional quality of some crops) can be more successful [e,f]. When using the other approach (increase in supply), one has to consider that accumulating free metabolites in transgenic plants can have detrimental effects on seed viability [c] and that reducing amino acids catabolism [g] to increase accumulation can produce similar
end-product plays a major role in flux control. Therefore many attempts at increasing the nutritional value of seed crops deficient in essential amino acids make use of desensitized variants of these enzymes (i.e. mutant forms that no longer respond to the feed-back metabolite), which are believed to deliver larger quantities of the relevant amino acids. This approach has not yielded many results and MCA provides an interpretation for the failures (Box 2). Perspectives about success MCA suggests that certain types of metabolic engineering are more likely to succeed than others are (Boxes 1 and 2). Inactivation of a metabolic pathway (Fig. 1b) by insertional mutagenesis [23], co-suppression [18,5] or antisense regulation [6] is a ‘sure’ target, as well as the activation of branches requiring single enzymatic activities (Fig. 1c) (e.g. [3]). Engineering of pathways with multiple enzymes (Fig. 1d), although more challenging, has already been accomplished [2,7]. However, for both single and multiple enzyme pathways, the diverted flux is usually a small fraction of the total. A flux increase in pre-existing pathways by increasing the level of a single enzyme (Fig. 1h) [4,24,25] has been reported, but the increase is usually small compared with the increase in enzyme activity. For example Michico Takahashi et al. [25] http://plants.trends.com
effects [g]. Indeed, incorporation into protein is more successful because it is an irreversible process, effectively removing the product from the free pool, thereby increasing the driving force for amino acids biosynthesis. The reduction in free concentration stimulates the flux also at the level of the enzyme(s) sensitive to feedback inhibition, while avoiding accumulation of intermediate metabolites. The same reasoning can be applied to other pathways (e.g. [h]).
References a Karchi, H. et al. (1993) Seed-specific expression of a bacterial desensitized aspartate kinase increases the production of seed threonine and methionine in transgenic tobacco. Plant J. 3, 721 – 727 b Cho, H. et al. (2000) Increasing tryptophan synthesis in a forage legume Astragalus sinicus by expressing the Tobacco feedback insensitive Anthranilate synthase (ASA2) gene. Plant Physiol. 123, 1069 – 1076 c Falco, S.C. et al. (1995) Transgenic canola and soybean seeds with increased lysine. Biotechnology 13, 577 – 582 d Zeh, M. et al. (2001) Antisense inhibition of threonine synthase leads to high methionine content in transgenic potato plants. Plant Physiol. 127, 792 – 802 e Molvig, L. et al. (1997) Enhanced methionine levels and increased nutritive value of seeds of transgenic lupins (Lupinus angustifolius L.). expressing a sunflower seed albumin gene. Proc. Natl. Acad. Sci. U. S. A. 94, 8393 – 8398 f Galili, G. and Hofgen, R. (2002) Metabolic engineering of amino acids and storage proteins in plants. Metab. Eng. 4, 3 – 11 g Zhu, X. et al. (2001) A T-DNA insertion knockout of the bifunctional lysine-ketoglutarate reductase/saccharopine dehydrogenase gene elevates lysine levels in Arabidopsis seeds. Plant Physiol. 126, 1539 – 1545 h Jain, R.K. et al. (2000) Enhancement of seed oil content by expression of glycerol-3-phosphate acyltransferase genes. Biochem. Soc. Trans. 28, 958– 961
increased the amount of nicotianamine aminotransferase (an enzyme required for phytosiderophores biosynthesis) 60-fold, but achieved only a modest (1.8-fold) flux increase. A large increase in total carotenoid content (50-fold) was obtained by overexpression of phytoene synthase in canola (Brassica napus) [24]. The overexpressed enzyme was not only the most abundant protein in developing seeds, but also the carotenoids were accumulating over a longer period compared with wild-type seeds (therefore instantaneous flux might be increased only a few fold). Moreover, no measurement was made of the activity of other enzymes in the pathway; therefore it is possible that other enzymes could be upregulated, as reported for tomato plants overexpressing phytoene desaturase [26]. The longer the pathway, the more distributed the control and therefore one expects smaller increases in flux upon single enzyme overexpression. Another example of successful flux increase with overexpression of a single gene was reported recently [27]. The gene in question codes for a protein with two different enzymatic activities, both involved in the Calvin cycle and both having a high flux control coefficient, making its overexpression effectively a ‘two-enzyme’ manipulation. Reports of higher starch levels upon manipulation of ADP-glucose pyrophoshorylase could not be reproduced in a different potato cultivar [28].
Opinion
TRENDS in Plant Science
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Fig. 1. Engineering metabolic pathways: likelihood of success. Different strategies for engineering metabolic pathways are classified according to Metabolic Control Analysis (MCA) as likely (b –f) or unlikely (g –i) to be successful. (a) Wild-type configuration for a ‘standard’ metabolic pathway transforming a substrate (S) into a product (P) through different intermediates. (b) Enzyme inactivation. Introduction of a single (c) or multiple (d) enzymes diverting only a small fraction of the flux to new metabolites (Q and G, respectively). (e) Pathway product removal (e.g. sequestered into a compartment by an ATP-driven pump). (f) Overexpression of multiple enzymes by means of a transcriptional activator (TF). (g) Expression of a feedback-insensitive variant of an enzyme. (h) Overexpression of a single enzyme. (i) Overexpression of one or more enzymes belonging to a pathway with coenzyme cycles (Z, W) without compensation for increased coenzyme consumption. Enzymatic reactions are represented by arrows only to imply the direction of flux and not necessarily irreversibility; the thicker the arrow, the higher the flux. Blue arrows indicate endogenous enzymes; the red cross indicates removal of an enzyme or its sensitivity to feedback inhibition; green arrows indicate expression of engineered enzymes (comprising overexpression of endogenous enzymes); broken purple arrows indicate transactivation of gene expression; broken black lines indicate feedback inhibition of a metabolite onto its target enzyme.
Relieving a feedback inhibition on a ‘controlling enzyme’ (Fig. 1g) (Box 2) might be effective for short pathways, such as those leading to proline [29] or cysteine, but it might raise the free concentration rather than the flux. One could achieve an increase in flux more easily by increasing demand for product (Box 2). In this context, it could also be effective using ATP-driven pumps to sequester the end product in otherwise impermeable compartments (Fig. 1e), thereby removing it from the equilibrium. The plethora of naturally occurring pumps uncovered in sequenced genomes or the engineering of new transporters by domain swapping or manipulation could provide the desired specificity and localization of sequestering mechanisms. Further possibilities to control flux reside in the supply of pathway substrate [30]. A pathway consuming a small fraction of a metabolic intermediate (e.g. glutamate flux to proline) is more amenable to flux increases by enzyme(s) overexpression because the intermediate concentration will experience little change. When flux is low, demand is probably the ‘limiting factor’ (large CJ) and increasing demand will increase flux. When flux is high, increasing product demand will not cause a proportional flux increase because pathway substrate availability will be limiting. Further increase will depend also on changes in the enzymes delivering the pathway substrate: when the target is the content of sulfur amino acids, for instance, this might need upregulation of sulfate uptake and cysteine biosynthesis [31]. Attempting to increase the flux in a pathway coupled to coenzyme cycles without increasing the opposite reaction (conversion of W to Z in Fig. 1i) can http://plants.trends.com
be similarly disappointing. In this context, trying to increase glycolysis [12] without increasing ATP consumption might be a red herring [32,33]. By contrast, increasing ATP consumption by introducing futile cycles [8,9,32,33] will stimulate ATP-producing reactions (glycolysis and respiration). However this will divert carbon away from biosynthesis (decreasing starch yield in the case of potato tubers) because a larger share of carbon is respired. Reference [9] probably represents another instance of this effect. A ‘transcriptional’ perspective Last but not least, a coordinate increase of enzymatic activities within a metabolic pathway (Fig. 1f) can be achieved by acting on transcription factors (as suggested in Ref. [34]). Genes coding for enzymes belonging to functional groups are often regulated in a positive or negative manner by common transcription factors (e.g. [35,36]). Using DNA micro arrays one can identify genes that are co-regulated [35]. Co-regulation might uncover common regulatory mechanisms (such as signals, transcription factors and regulatory sequences), as already demonstrated [35], and eventually lead to the identification of the transcription factors involved. Other effective approaches are T-DNA activation tagging [36,37] or insertional inactivation. Plant genomes contain many transcription factors (Arabidopsis contains 1709 proteins with significant similarity to plant transcription factors [16]), and knocking out single genes indicates that many are dispensable or contribute marginally to the phenotype (e.g. [38]). Curiously, transcription factors behave, in this respect, in a
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similar way to enzymes, that is, reduced levels might not decrease the expression of target genes: the control of transcription seems to be combinatorial, with individual transcription factors not sufficient to induce transcription. The manipulation of several transcription factors might then be required to achieve upregulation of target genes. Once these factors and their properties are identified, it could be possible to engineer strong activation (or repressor [39]) domains onto the DNA binding domains to produce dominant activators or repressors. Crucial issues The purpose of this Opinion is neither to assess the present status of plant metabolic engineering nor to explore all future applications [several reviews both broad and specific are already available [34,40– 42]; the whole issue of Metabolic Engineering (2002) 4 (1) is devoted to plant metabolic engineering]. Instead, we want to highlight the following issues: † The chances of success in metabolic engineering can be increased by considering the lessons of MCA. † The role of plant breeding in the generation of better varieties cannot be easily substituted by genetic engineering, particularly when a flux increase in complex pathways is required. † Plant genetic engineering should provide the tools (slow or unavailable in plant breeding) for producing varieties with ‘intelligent’ phenotypes by expressing one or a few genes (e.g. resistance factors [43]), for activating pathways via transcription factors (Fig. 1f), diverting metabolic fluxes (Fig. 1c to 1e) or eliminating the production of toxic compounds (Fig. 1b) [23] via gene knock out or silencing (applicable for instance to the domestication of species not available for consumption). Along the lines of Eliot’s citation, there is plenty of space for different approaches and many problems awaiting a solution. Acknowledgements Thanks to all the people, many indeed, who helped to improve the manuscript. We apologize in advance to people whose work was not mentioned because of space limitations or purely out of ignorance.
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7 Poirier, Y. (1999) Production of new polymeric compounds in plants. Curr. Opin. Biotechnol. 10, 181 – 185 8 Trethewey, R.N. et al. (1999) Tuber-specific expression of a yeast invertase and a bacterial glucokinase in potato leads to an activation of sucrose phosphate synthase and the creation of a sucrose futile cycle. Planta 208, 227 – 238 9 Fernie, A.R. et al. (2002) Altered metabolic fluxes result from shifts in metabolite levels in sucrose phosphorylase expressing potato tubers. Plant Cell Environ. 25, 1219– 1232 10 Gottlob-McHugh, S.G. et al. (1992) Normal growth of transgenic tobacco plants in the absence of cytosolic pyruvate kinase. Plant Physiol. 100, 820 – 825 11 Quick, W.P. et al. (1991) Decreased ribulose 1,5 bisphosphate carboxylase/oxygenase in transgenic tobacco transformed with antisense rbcS. I. Impact on photosynthesis in ambient growth conditions. Planta 183, 542 – 554 12 Burrell, M.M. et al. (1994) Genetic manipulation of 6-PFK in potato tubers. Planta 194, 95 – 101 13 Eastmond, P.J. et al. (2000) Postgerminative growth and lipid catabolism in oilseeds lacking the glyoxylate cycle. Proc. Natl. Acad. Sci. U. S. A. 97, 5669 – 5674 14 Henkes, S. et al. (2001) A small decrease of plastid transketolase activity in antisense tobacco transformants has dramatic effects on photosynthesis and phenylpropanoid metabolism. Plant Cell 13, 535– 551 15 Bohmert, K. et al. (2002) Constitutive expression of the betaketothiolase gene in transgenic plants. A major obstacle for obtaining polyhydroxybutyrate-producing plants. Plant Physiol. 128, 1282– 1290 16 The Arabidopsis Genome Initiative (2000). Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature, 408, 796– 815 17 Fernie, A.R. et al. (2001) Simultaneous antagonistic modulation of enzyme activities in transgenic plants through the expression of a chimeric transcript. Plant Physiol. Biochem. 39, 825 – 830 18 Abbott, J.C. et al. (2002) Simultaneous suppression of multiple genes by single transgenes. Down-regulation of three unrelated lignin biosynthetic genes in tobacco. Plant Physiol. 128, 844– 853 19 Roessner, U. et al. (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11 – 29 20 Giersch, C. (2000) Mathematical modelling of metabolism. Curr. Opin. Plant Biol. 3, 249 – 253 21 Chassagnole, C. et al. (2001) Control of the threonine-synthesis pathway in Escherichia coli: a theoretical and experimental approach. Biochem. J. 356, 433 – 444 22 Niederberger, P. et al. (1992) A strategy for increasing an in vivo flux by genetic manipulations. The tryptophan system of yeast. Biochem. J. 287, 473 – 479 23 Reintanz, B. et al. (2001) bus, a bushy Arabidopsis cyp79f1 knockout mutant with abolished synthesis of short-chain aliphatic glucosinolates. Plant Cell 13, 351 – 367 24 Shewmaker, C.K. et al. (1999) Seed-specific overexpression of phytoene synthase: increase in carotenoids and other metabolic effects. Plant J. 20, 401 – 412 25 Takahashi, M. et al. (2001) Enhanced tolerance of rice to low iron availability in alkaline soils using barley nicotianamine aminotransferase genes. Nat. Biotechnol. 19, 466 – 469 26 Romer, S. et al. (2000) Elevation of the provitamin A content of transgenic tomato plants. Nat. Biotechnol. 18, 666– 669 27 Miyagawa, Y. et al. (2001) Overexpression of a cyanobacterial fructose1,6-/sedoheptulose-1,7-bisphosphatase in tobacco enhances photosynthesis and growth. Nat. Biotechnol. 19, 965 – 969 28 Sweetlove, L.J. et al. (1996) Starch metabolism in tubers of transgenic potato (Solanum tuberosum) with increased ADP glucose pyrophosphorylase. Biochem. J. 320, 493 – 498 29 Hong, Z. et al. (2000) Removal of feedback inhibition of D(1)-pyrroline5-carboxylate synthetase results in increased proline accumulation and protection of plants from osmotic stress. Plant Physiol. 22, 1129– 1136 30 Hofmeyr, J.S. and Cornish-Bowden, A. (2000) Regulating the cellular economy of supply and demand. FEBS Lett. 476, 47 – 51 31 Tabe, L.M. and Droux, M. (2002) Limits to sulfur accumulation in
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transgenic lupin seeds expressing a foreign sulfur-rich protein. Plant Physiol. 128, 1137– 1148 Hofmeyr, J-H.S (1997) Anaerobic energy metabolism in yeast as a supply – demand system. In New Beer in an Old Bottle: Eduard Buchner and the Growth of Biochemical Knowledge (CornishBowden, A., ed.), pp. 225 – 242, Universitat de Valencia Koebmann, B.J. et al. (2002) The glycolytic flux in Escherichia coli is controlled by the demand for ATP. J. Bacteriol. 184, 3909– 3916 DellaPenna, D. (2001) Plant metabolic engineering. Plant Physiol. 125, 160 – 163 Harmer, S.L. et al. (2000) Orchestrated transcription of key pathways in Arabidopsis by the circadian clock. Science 290, 2110 – 2113 van der Fits, L. and Memelink, J. (2000) ORCA3, a jasmonateresponsive transcriptional regulator of plant primary and secondary metabolism. Science 289, 295– 297 Borevitz, J.O. et al. (2000) Activation tagging identifies a conserved
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MYB regulator of phenylpropanoid biosynthesis. Plant Cell 12, 2383– 2394 Meissner, R.C. et al. (1999) Function search in a large transcription factor gene family in Arabidopsis: assessing the potential of reverse genetics to identify insertional mutations in R2R3 MYB genes. Plant Cell 11, 1827– 1840 Markel, H. et al. (2002) Translational fusions with the engrailed repressor domain efficiently convert plant transcription factors into dominant-negative functions. Nucleic Acids Res. 30, 4709– 4719 Broun, P. and Somerville, C. (2000) Progress in plant metabolic engineering. Proc. Natl. Acad. Sci. U. S. A. 98, 8925 – 8927 Somerville, C.R. and Bonetta, D. (2001) Plants as factories for technical materials. Plant Physiol. 125, 168 – 171 Mazur, B. et al. (1999) Gene discovery and product development for grain quality traits. Science 285, 372 – 375 Kramer, K.J. et al. (2000) Transgenic avidin maize is resistant to storage insect pests. Nat. Biotechnol. 18, 670 – 674
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Plant biotechnology and breeding: allied for years to come Piero Morandini1 and Francesco Salamini2 1
Department of Biology, University of Milan, via Celoria 26, 20133 Milan, Italy Max Planck Institut fuer Zuechtungsforschung, Department of Plant Breeding and Yield Physiology, Carl-von-Linne` weg 10, 727272 Koeln, Germany 2
Plant metabolic engineering is lagging behind other kinds of genetic manipulation of plants. Creating metabolic pathways or improving their yields requires a better understanding of plant metabolism and of its regulation. Metabolic Control Analysis provides an interpretation of experimental failures and a guide for manipulators. It suggests also that there might be intrinsic limits to raising yields in already abundant products. At present, these limits can be dealt with more effectively by plant breeding.
…And a job for each Each man to his work. (Choruses from ‘The Rock’ by T.S. Eliot) Agricultural biotechnology has the potential to develop more-sustainable farming practices. For instance, plants expressing single insecticidal proteins, such as Bt cotton, reduce the use of exogenous pesticides [1]. This application of biotechnology usually requires the transfer of single genes from distantly related species and, in spite of the problem of acceptance by consumers, farmers in developed and developing countries have readily taken them up. A less attractive application of biotechnology, which nevertheless holds great promise, is the rational and selective alteration of metabolism (the so-called ‘metabolic engineering’) to increase the production of endogenous metabolites or to achieve the synthesis of metabolites not produced by plants. Metabolic engineering in plants has indeed yielded remarkable and encouraging results by increasing the yield of minor components, such as vitamin A, vitamin E and essential oil [2– 4], as well as the composition of major components, such as fatty acid (e.g. [5]) or starch [6], and by engineering entirely new pathways, as in the case of polyhydroxyalkanoates [7]. The alternative possibility, aimed at improving yields in already abundant metabolic products, such as starch, has been less successful and has been unable to yield viable market products. In certain cases, results were even contrary to expectations: attempts at increasing sink Corresponding author: Piero Morandini ([email protected]).
strength and starch accumulation in potato tubers by increasing sucrose hydrolysis and metabolism, led to the induction of glycolysis but to a decrease in starch content [8,9]. By contrast, plant breeding has been extremely successful in increasing yields, even though, as a technology, it is purely empirical and based on established practices rather than on understanding the molecular-physiological bases of the traits under selection. Are there reasons to explain this contradiction? We argue that plant breeding will not be substituted in a few years by plant biotechnology, rather the two different approaches are and will be cooperating for years to come. Complexity of metabolism Metabolic engineering needs a better understanding of metabolic regulation and plasticity because accumulating data do not fit into conventional theories. For instance, enzymes defined as ‘rate limiting’ can be greatly or significantly reduced (e.g. cytosolic pyruvate kinase, [10] and Rubisco, [11]) or overexpressed several-fold (phosphofructokinase, [12]) without substantial change in metabolic fluxes. Arabidopsis mutants lacking the glyoxylate cycle, once regarded as essential for postgerminative growth, germinate efficiently under favourable conditions [13]. By contrast, enzymes regarded as non-limiting (either because they are non regulated, catalyse near equilibrium reactions or their maximum activities are orders of magnitude higher than the pathway flux) have been shown to cause sensible reduction in flux when reduced (e.g. aldolase and transketolase [14]). We are also unable to predict deleterious effects of overexpressing enzymes in certain compartments (e.g. [15]), possibly because of enzymes competing for common precursors. The conclusion is that metabolic pathways are complex in several ways. Within a cell, a thousand or more metabolites are distributed among several compartments and, even though we know the metabolic routes, the concentrations of intermediates and the forces driving metabolic conversions (the equilibrium constant of the reactions), we are unable to predict the modulation of metabolite concentration because of a change in some environmental or cellular parameter (e.g. enzyme quantity). A change in one enzyme modifies the concentration of its substrate(s) and product(s) which, in turn, will affect the velocity of the same (and of neighbouring)
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Box 1. Metabolic control analysis and its implications Metabolic control analysis (MCA) officially began in 1973 with two seminal works [a,b]. The concept of a ‘rate-limiting enzyme’ was replaced by a coefficient expressing the degree of control over flux exerted by every enzyme (flux-control coefficient, CJ) [c], see also http://bip.cnrs-mrs.fr/bip10/mcainfo.htm for tutorials about MCA). Major theory implications are: † There are intrinsic and serious limits to yield (flux) improvement achievable by single enzyme overexpression [d,e]. In principle, increasing all the enzymes in a metabolic pathway will do the job. Indeed, several physiological flux increases depend on the coordinate activation or induction of several enzymes within a pathway: for instance, several genes in the pathways for oil biosynthesis and oil degradation are upregulated [f,g]. † Even if the transformation of plants with several genes is now technically feasible, a substantial increase in flux might not be possible for those pathways where some enzymes are already at high concentration and close to their physical limit (e.g. Rubisco, triose phosphate translocator, plasma membrane Hþ-ATPase). Moreover, overexpression of an already abundant enzyme could cause a reduction in other enzymes and therefore a reduction in flux [h]. † The extent of flux increase will also depend on being able to buffer the concentration of metabolites available to and produced by the pathway (S and P of Fig. 1). Efficient buffering requires the ability to increase the supply of the pathway substrate and the demand for its product of the same absolute value (the so-called ‘universal method’) [i]. If the substrate is shared by many different pathways, the creation of a new pathway will not affect endogenous metabolism if it diverts only a small fraction of the flux. † The role of conventional crop breeding does not overlap with (and therefore is not replaceable by) plant molecular genetics. This is true not only for quantitative traits depending on several factors, such as for yield or resistance to environmental stress, but also for increasing flux
enzymatic reactions. In other words, flux and metabolite concentrations are systemic variables (i.e. they are properties of the system as a whole and not of isolated enzymes). The next frontier needs better models The completion of the Arabidopsis genomic sequence [16] heralded the age of proteomics, functional genomics and metabolomics for plants. Advances in molecular techniques allow the simultaneous modulation of several enzyme activities [6,17,18], and analytical techniques allow us to measure the concentrations of hundreds of metabolites [19]. Faced with the power of such tools, what is limiting is our capacity to produce models describing the behaviour of metabolic pathways [20]. Tools are already at hand: software for the simulation of metabolic pathways (www.hort.purdue.edu/cfpesp/models/mo00015.htm), as well as a public enzyme database (e.g. www.brenda.uni-koeln.de). Most of these data are limited to in vitro conditions, which could be very different from conditions in vivo. This means that the data might not be good enough to derive a kinetic law (i.e. an equation describing the rate as a function of the concentration of substrate(s), product(s) and other effectors) or that the derived law might be mechanistically perfect, but inadequate to describe enzyme behaviour in vivo [21]. The future of metabolic engineering requires models that are able to predict the behaviour of metabolic networks in terms of flux and metabolite concentrations (e.g. [21]). http://plants.trends.com
in long pathways. At present, only plant breeding seems able to increase the level of several enzymes in a pathway reliably. The manipulation of plant transcription factors offers new chances for the future, but this will still depend on the presence of common regulatory elements.
References a Kacser, H. and Burns, J.A. (1973). The control of flux. Symp. Soc. Exp. Biol. 27, 65 – 104 [Reprinted in. Biochem. Soc. Trans. (1995). 23, 341 – 366] b Heinrich, R. and Rapoport, T.A. (1974) A linear steady-state treatment of enzymatic chains. Eur. J. Biochem. 42, 89 – 95 c Fell, D.A. (1997) Understanding the Control of Metabolism, Portland Press d Small, J.R. and Kacser, H. (1993) Responses of metabolic systems to large changes in enzyme activities and effectors. 1. The linear treatment of unbranched chains. Eur. J. Biochem. 213, 613 – 624 e Niederberger, P. et al. (1992) A strategy for increasing an in vivo flux by genetic manipulations. The tryptophan system of yeast. Biochem. J. 287, 473 – 479 f O’Hara, P. et al. (2002) Fatty acid and lipid biosynthetic genes are expressed at constant molar ratios but different absolute levels during embryogenesis. Plant Physiol. 129, 310 – 320 g Rylott, E.L. et al. (2001) Co-ordinate regulation of genes involved in storage lipid mobilization in Arabidopsis thaliana. Biochem. Soc. Trans. 29, 283 – 287 h Snoep, J.L. et al. (1995) Protein burden in Zymomonas mobilis: negative flux and growth-control due to overproduction of glycolyticenzymes. Microbiology 141, 2329 – 2337 i Kacser, H. and Acerenza, L. (1993) A universal method for achieving increases in metabolite production. Eur. J. Biochem. 216, 361– 367
A quantitative approach to metabolism Metabolic Control Analysis (MCA) is one of the theories trying to describe metabolic pathways and their behaviour in a more quantitative manner than classical biochemistry does (Box 1). The main principle of MCA is that the control of flux in a pathway is usually distributed over many enzymes. It follows that a substantial flux increase cannot be achieved without increasing the catalytic activity at multiple sites. Indeed, many experiments (e.g. [22,21]) support the view that many if not all the enzymes in a metabolic pathway contribute to determine the maximum flux sustainable by the pathway. The observation that most loss-of-function mutations are recessive supports the idea that a substantial reduction (up to 50% is expected in heterozygotes) in many enzymes does not translate into a visible phenotype (i.e. most enzymes are not limiting the flux). The explanation offered is that reducing the amount of an enzyme causes an increase in substrate(s) and a decrease in product(s) concentration. These changes increase the driving force of the reaction, thus causing the diminished number of enzyme molecules to work at higher velocity: the end result is a system sustaining a similar flux but with a different distribution of metabolites. Similarly, increasing the amount of enzyme might result in the reverse effect on metabolite levels without altering the flux substantially. MCA has relevant implications for plant biology and biotechnology (Box 1). For instance, a long-held belief of classical biochemistry is that feed-back inhibition on a biosynthetic enzyme by the
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Box 2. Increasing flux or concentration? Increasing the concentration of free metabolites such as amino acids is not equivalent to increasing their overall quantity: substantial concentrations can be achieved either by slightly increasing the biosynthesis or by slightly decreasing the consumption. Because the pool of amino acids incorporated into proteins (the main fate for most amino acids) is usually much larger than the free pool, a large increase in overall quantity (free and combined) always requires a large increase both in flux and incorporation into protein. Metabolic Control Analysis suggests that relieving feedback inhibition might be effective at increasing the free concentration of metabolites downstream of the inhibited enzyme, with the magnitude of such an increase being dampened away along the pathway, but not necessarily sufficient to increase the overall quantity substantially. The use of desensitized enzymes can therefore have unpleasant effects because some of the intermediate metabolites can become toxic at a certain concentration. At the same time, the strategy could be unable to deliver the desired effect: once the amino acid concentration has increased, the flux will depend on the demand (which has not changed) and, in growing tissues, on the volume increase. For instance, Hagai Karchi et al. [a] reported a several-fold increase in free Thr and Met content of tobacco seeds, but only a modest increase (6.5% for Thr and 6.8 for Met) in total content. Other works stress an increase in free Pro or Trp (e.g. [b]), but no mention is made of the overall quantity. A large increase in free Lys and a twofold (canola) to fivefold (Soybean) increase in total Lys seed content has been reported [c] by overexpressing, respectively, one or two desensitized enzymes in the pathway. Down regulating threonine synthase [d] increased Met free concentration by orders of magnitude in leaves and by an order of magnitude in tubers, but, beyond deleterious effects noted on plant vigour, no data are provided on total Met accumulation. Imposing a large increase in demand by overexpressing proteins rich in the relevant amino acids (e.g. sulfur-rich proteins improving the nutritional quality of some crops) can be more successful [e,f]. When using the other approach (increase in supply), one has to consider that accumulating free metabolites in transgenic plants can have detrimental effects on seed viability [c] and that reducing amino acids catabolism [g] to increase accumulation can produce similar
end-product plays a major role in flux control. Therefore many attempts at increasing the nutritional value of seed crops deficient in essential amino acids make use of desensitized variants of these enzymes (i.e. mutant forms that no longer respond to the feed-back metabolite), which are believed to deliver larger quantities of the relevant amino acids. This approach has not yielded many results and MCA provides an interpretation for the failures (Box 2). Perspectives about success MCA suggests that certain types of metabolic engineering are more likely to succeed than others are (Boxes 1 and 2). Inactivation of a metabolic pathway (Fig. 1b) by insertional mutagenesis [23], co-suppression [18,5] or antisense regulation [6] is a ‘sure’ target, as well as the activation of branches requiring single enzymatic activities (Fig. 1c) (e.g. [3]). Engineering of pathways with multiple enzymes (Fig. 1d), although more challenging, has already been accomplished [2,7]. However, for both single and multiple enzyme pathways, the diverted flux is usually a small fraction of the total. A flux increase in pre-existing pathways by increasing the level of a single enzyme (Fig. 1h) [4,24,25] has been reported, but the increase is usually small compared with the increase in enzyme activity. For example Michico Takahashi et al. [25] http://plants.trends.com
effects [g]. Indeed, incorporation into protein is more successful because it is an irreversible process, effectively removing the product from the free pool, thereby increasing the driving force for amino acids biosynthesis. The reduction in free concentration stimulates the flux also at the level of the enzyme(s) sensitive to feedback inhibition, while avoiding accumulation of intermediate metabolites. The same reasoning can be applied to other pathways (e.g. [h]).
References a Karchi, H. et al. (1993) Seed-specific expression of a bacterial desensitized aspartate kinase increases the production of seed threonine and methionine in transgenic tobacco. Plant J. 3, 721 – 727 b Cho, H. et al. (2000) Increasing tryptophan synthesis in a forage legume Astragalus sinicus by expressing the Tobacco feedback insensitive Anthranilate synthase (ASA2) gene. Plant Physiol. 123, 1069 – 1076 c Falco, S.C. et al. (1995) Transgenic canola and soybean seeds with increased lysine. Biotechnology 13, 577 – 582 d Zeh, M. et al. (2001) Antisense inhibition of threonine synthase leads to high methionine content in transgenic potato plants. Plant Physiol. 127, 792 – 802 e Molvig, L. et al. (1997) Enhanced methionine levels and increased nutritive value of seeds of transgenic lupins (Lupinus angustifolius L.). expressing a sunflower seed albumin gene. Proc. Natl. Acad. Sci. U. S. A. 94, 8393 – 8398 f Galili, G. and Hofgen, R. (2002) Metabolic engineering of amino acids and storage proteins in plants. Metab. Eng. 4, 3 – 11 g Zhu, X. et al. (2001) A T-DNA insertion knockout of the bifunctional lysine-ketoglutarate reductase/saccharopine dehydrogenase gene elevates lysine levels in Arabidopsis seeds. Plant Physiol. 126, 1539 – 1545 h Jain, R.K. et al. (2000) Enhancement of seed oil content by expression of glycerol-3-phosphate acyltransferase genes. Biochem. Soc. Trans. 28, 958– 961
increased the amount of nicotianamine aminotransferase (an enzyme required for phytosiderophores biosynthesis) 60-fold, but achieved only a modest (1.8-fold) flux increase. A large increase in total carotenoid content (50-fold) was obtained by overexpression of phytoene synthase in canola (Brassica napus) [24]. The overexpressed enzyme was not only the most abundant protein in developing seeds, but also the carotenoids were accumulating over a longer period compared with wild-type seeds (therefore instantaneous flux might be increased only a few fold). Moreover, no measurement was made of the activity of other enzymes in the pathway; therefore it is possible that other enzymes could be upregulated, as reported for tomato plants overexpressing phytoene desaturase [26]. The longer the pathway, the more distributed the control and therefore one expects smaller increases in flux upon single enzyme overexpression. Another example of successful flux increase with overexpression of a single gene was reported recently [27]. The gene in question codes for a protein with two different enzymatic activities, both involved in the Calvin cycle and both having a high flux control coefficient, making its overexpression effectively a ‘two-enzyme’ manipulation. Reports of higher starch levels upon manipulation of ADP-glucose pyrophoshorylase could not be reproduced in a different potato cultivar [28].
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Fig. 1. Engineering metabolic pathways: likelihood of success. Different strategies for engineering metabolic pathways are classified according to Metabolic Control Analysis (MCA) as likely (b –f) or unlikely (g –i) to be successful. (a) Wild-type configuration for a ‘standard’ metabolic pathway transforming a substrate (S) into a product (P) through different intermediates. (b) Enzyme inactivation. Introduction of a single (c) or multiple (d) enzymes diverting only a small fraction of the flux to new metabolites (Q and G, respectively). (e) Pathway product removal (e.g. sequestered into a compartment by an ATP-driven pump). (f) Overexpression of multiple enzymes by means of a transcriptional activator (TF). (g) Expression of a feedback-insensitive variant of an enzyme. (h) Overexpression of a single enzyme. (i) Overexpression of one or more enzymes belonging to a pathway with coenzyme cycles (Z, W) without compensation for increased coenzyme consumption. Enzymatic reactions are represented by arrows only to imply the direction of flux and not necessarily irreversibility; the thicker the arrow, the higher the flux. Blue arrows indicate endogenous enzymes; the red cross indicates removal of an enzyme or its sensitivity to feedback inhibition; green arrows indicate expression of engineered enzymes (comprising overexpression of endogenous enzymes); broken purple arrows indicate transactivation of gene expression; broken black lines indicate feedback inhibition of a metabolite onto its target enzyme.
Relieving a feedback inhibition on a ‘controlling enzyme’ (Fig. 1g) (Box 2) might be effective for short pathways, such as those leading to proline [29] or cysteine, but it might raise the free concentration rather than the flux. One could achieve an increase in flux more easily by increasing demand for product (Box 2). In this context, it could also be effective using ATP-driven pumps to sequester the end product in otherwise impermeable compartments (Fig. 1e), thereby removing it from the equilibrium. The plethora of naturally occurring pumps uncovered in sequenced genomes or the engineering of new transporters by domain swapping or manipulation could provide the desired specificity and localization of sequestering mechanisms. Further possibilities to control flux reside in the supply of pathway substrate [30]. A pathway consuming a small fraction of a metabolic intermediate (e.g. glutamate flux to proline) is more amenable to flux increases by enzyme(s) overexpression because the intermediate concentration will experience little change. When flux is low, demand is probably the ‘limiting factor’ (large CJ) and increasing demand will increase flux. When flux is high, increasing product demand will not cause a proportional flux increase because pathway substrate availability will be limiting. Further increase will depend also on changes in the enzymes delivering the pathway substrate: when the target is the content of sulfur amino acids, for instance, this might need upregulation of sulfate uptake and cysteine biosynthesis [31]. Attempting to increase the flux in a pathway coupled to coenzyme cycles without increasing the opposite reaction (conversion of W to Z in Fig. 1i) can http://plants.trends.com
be similarly disappointing. In this context, trying to increase glycolysis [12] without increasing ATP consumption might be a red herring [32,33]. By contrast, increasing ATP consumption by introducing futile cycles [8,9,32,33] will stimulate ATP-producing reactions (glycolysis and respiration). However this will divert carbon away from biosynthesis (decreasing starch yield in the case of potato tubers) because a larger share of carbon is respired. Reference [9] probably represents another instance of this effect. A ‘transcriptional’ perspective Last but not least, a coordinate increase of enzymatic activities within a metabolic pathway (Fig. 1f) can be achieved by acting on transcription factors (as suggested in Ref. [34]). Genes coding for enzymes belonging to functional groups are often regulated in a positive or negative manner by common transcription factors (e.g. [35,36]). Using DNA micro arrays one can identify genes that are co-regulated [35]. Co-regulation might uncover common regulatory mechanisms (such as signals, transcription factors and regulatory sequences), as already demonstrated [35], and eventually lead to the identification of the transcription factors involved. Other effective approaches are T-DNA activation tagging [36,37] or insertional inactivation. Plant genomes contain many transcription factors (Arabidopsis contains 1709 proteins with significant similarity to plant transcription factors [16]), and knocking out single genes indicates that many are dispensable or contribute marginally to the phenotype (e.g. [38]). Curiously, transcription factors behave, in this respect, in a
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similar way to enzymes, that is, reduced levels might not decrease the expression of target genes: the control of transcription seems to be combinatorial, with individual transcription factors not sufficient to induce transcription. The manipulation of several transcription factors might then be required to achieve upregulation of target genes. Once these factors and their properties are identified, it could be possible to engineer strong activation (or repressor [39]) domains onto the DNA binding domains to produce dominant activators or repressors. Crucial issues The purpose of this Opinion is neither to assess the present status of plant metabolic engineering nor to explore all future applications [several reviews both broad and specific are already available [34,40– 42]; the whole issue of Metabolic Engineering (2002) 4 (1) is devoted to plant metabolic engineering]. Instead, we want to highlight the following issues: † The chances of success in metabolic engineering can be increased by considering the lessons of MCA. † The role of plant breeding in the generation of better varieties cannot be easily substituted by genetic engineering, particularly when a flux increase in complex pathways is required. † Plant genetic engineering should provide the tools (slow or unavailable in plant breeding) for producing varieties with ‘intelligent’ phenotypes by expressing one or a few genes (e.g. resistance factors [43]), for activating pathways via transcription factors (Fig. 1f), diverting metabolic fluxes (Fig. 1c to 1e) or eliminating the production of toxic compounds (Fig. 1b) [23] via gene knock out or silencing (applicable for instance to the domestication of species not available for consumption). Along the lines of Eliot’s citation, there is plenty of space for different approaches and many problems awaiting a solution. Acknowledgements Thanks to all the people, many indeed, who helped to improve the manuscript. We apologize in advance to people whose work was not mentioned because of space limitations or purely out of ignorance.
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7 Poirier, Y. (1999) Production of new polymeric compounds in plants. Curr. Opin. Biotechnol. 10, 181 – 185 8 Trethewey, R.N. et al. (1999) Tuber-specific expression of a yeast invertase and a bacterial glucokinase in potato leads to an activation of sucrose phosphate synthase and the creation of a sucrose futile cycle. Planta 208, 227 – 238 9 Fernie, A.R. et al. (2002) Altered metabolic fluxes result from shifts in metabolite levels in sucrose phosphorylase expressing potato tubers. Plant Cell Environ. 25, 1219– 1232 10 Gottlob-McHugh, S.G. et al. (1992) Normal growth of transgenic tobacco plants in the absence of cytosolic pyruvate kinase. Plant Physiol. 100, 820 – 825 11 Quick, W.P. et al. (1991) Decreased ribulose 1,5 bisphosphate carboxylase/oxygenase in transgenic tobacco transformed with antisense rbcS. I. Impact on photosynthesis in ambient growth conditions. Planta 183, 542 – 554 12 Burrell, M.M. et al. (1994) Genetic manipulation of 6-PFK in potato tubers. Planta 194, 95 – 101 13 Eastmond, P.J. et al. (2000) Postgerminative growth and lipid catabolism in oilseeds lacking the glyoxylate cycle. Proc. Natl. Acad. Sci. U. S. A. 97, 5669 – 5674 14 Henkes, S. et al. (2001) A small decrease of plastid transketolase activity in antisense tobacco transformants has dramatic effects on photosynthesis and phenylpropanoid metabolism. Plant Cell 13, 535– 551 15 Bohmert, K. et al. (2002) Constitutive expression of the betaketothiolase gene in transgenic plants. A major obstacle for obtaining polyhydroxybutyrate-producing plants. Plant Physiol. 128, 1282– 1290 16 The Arabidopsis Genome Initiative (2000). Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature, 408, 796– 815 17 Fernie, A.R. et al. (2001) Simultaneous antagonistic modulation of enzyme activities in transgenic plants through the expression of a chimeric transcript. Plant Physiol. Biochem. 39, 825 – 830 18 Abbott, J.C. et al. (2002) Simultaneous suppression of multiple genes by single transgenes. Down-regulation of three unrelated lignin biosynthetic genes in tobacco. Plant Physiol. 128, 844– 853 19 Roessner, U. et al. (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11 – 29 20 Giersch, C. (2000) Mathematical modelling of metabolism. Curr. Opin. Plant Biol. 3, 249 – 253 21 Chassagnole, C. et al. (2001) Control of the threonine-synthesis pathway in Escherichia coli: a theoretical and experimental approach. Biochem. J. 356, 433 – 444 22 Niederberger, P. et al. (1992) A strategy for increasing an in vivo flux by genetic manipulations. The tryptophan system of yeast. Biochem. J. 287, 473 – 479 23 Reintanz, B. et al. (2001) bus, a bushy Arabidopsis cyp79f1 knockout mutant with abolished synthesis of short-chain aliphatic glucosinolates. Plant Cell 13, 351 – 367 24 Shewmaker, C.K. et al. (1999) Seed-specific overexpression of phytoene synthase: increase in carotenoids and other metabolic effects. Plant J. 20, 401 – 412 25 Takahashi, M. et al. (2001) Enhanced tolerance of rice to low iron availability in alkaline soils using barley nicotianamine aminotransferase genes. Nat. Biotechnol. 19, 466 – 469 26 Romer, S. et al. (2000) Elevation of the provitamin A content of transgenic tomato plants. Nat. Biotechnol. 18, 666– 669 27 Miyagawa, Y. et al. (2001) Overexpression of a cyanobacterial fructose1,6-/sedoheptulose-1,7-bisphosphatase in tobacco enhances photosynthesis and growth. Nat. Biotechnol. 19, 965 – 969 28 Sweetlove, L.J. et al. (1996) Starch metabolism in tubers of transgenic potato (Solanum tuberosum) with increased ADP glucose pyrophosphorylase. Biochem. J. 320, 493 – 498 29 Hong, Z. et al. (2000) Removal of feedback inhibition of D(1)-pyrroline5-carboxylate synthetase results in increased proline accumulation and protection of plants from osmotic stress. Plant Physiol. 22, 1129– 1136 30 Hofmeyr, J.S. and Cornish-Bowden, A. (2000) Regulating the cellular economy of supply and demand. FEBS Lett. 476, 47 – 51 31 Tabe, L.M. and Droux, M. (2002) Limits to sulfur accumulation in
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transgenic lupin seeds expressing a foreign sulfur-rich protein. Plant Physiol. 128, 1137– 1148 Hofmeyr, J-H.S (1997) Anaerobic energy metabolism in yeast as a supply – demand system. In New Beer in an Old Bottle: Eduard Buchner and the Growth of Biochemical Knowledge (CornishBowden, A., ed.), pp. 225 – 242, Universitat de Valencia Koebmann, B.J. et al. (2002) The glycolytic flux in Escherichia coli is controlled by the demand for ATP. J. Bacteriol. 184, 3909– 3916 DellaPenna, D. (2001) Plant metabolic engineering. Plant Physiol. 125, 160 – 163 Harmer, S.L. et al. (2000) Orchestrated transcription of key pathways in Arabidopsis by the circadian clock. Science 290, 2110 – 2113 van der Fits, L. and Memelink, J. (2000) ORCA3, a jasmonateresponsive transcriptional regulator of plant primary and secondary metabolism. Science 289, 295– 297 Borevitz, J.O. et al. (2000) Activation tagging identifies a conserved
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MYB regulator of phenylpropanoid biosynthesis. Plant Cell 12, 2383– 2394 Meissner, R.C. et al. (1999) Function search in a large transcription factor gene family in Arabidopsis: assessing the potential of reverse genetics to identify insertional mutations in R2R3 MYB genes. Plant Cell 11, 1827– 1840 Markel, H. et al. (2002) Translational fusions with the engrailed repressor domain efficiently convert plant transcription factors into dominant-negative functions. Nucleic Acids Res. 30, 4709– 4719 Broun, P. and Somerville, C. (2000) Progress in plant metabolic engineering. Proc. Natl. Acad. Sci. U. S. A. 98, 8925 – 8927 Somerville, C.R. and Bonetta, D. (2001) Plants as factories for technical materials. Plant Physiol. 125, 168 – 171 Mazur, B. et al. (1999) Gene discovery and product development for grain quality traits. Science 285, 372 – 375 Kramer, K.J. et al. (2000) Transgenic avidin maize is resistant to storage insect pests. Nat. Biotechnol. 18, 670 – 674
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