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128
Metabolic engineering of plants for osmotic stress resistance
Michael L Nuccio*, David Rhodes†, Scott D McNeil* and
Andrew D Hanson*‡
Genes encoding critical steps in the synthesis of
osmoprotectant compounds are now being expressed in
transgenic plants. These plants generally accumulate low levels
of osmoprotectants and have increased stress tolerance. The
next priority is therefore to engineer greater osmoprotectant
synthesis without detriment to the rest of metabolism. This will
require manipulation of multiple genes, guided by thorough
analysis of metabolite fluxes and pool sizes.
Addresses
*Department of Horticultural Sciences, University of Florida,
Gainesville, FL 32611-0690, USA
† Department of Horticulture, Purdue University, West Lafayette,
IN 47907-1165, USA
‡e-mail: [email protected]
Current Opinion in Plant Biology 1999, 2:128–134
http://biomednet.com/elecref/1369526600200128
© Elsevier Science Ltd ISSN 1369-5266
Abbreviations
GlyBet glycine betaine
MCA
metabolic control analysis
Introduction
Improving crop resistance to osmotic stresses is a longstanding goal of agricultural biotechnology [1,2 •].
Drought, salinity and freeze-induced dehydration constitute direct osmotic stresses; chilling and hypoxia can
indirectly cause osmotic stress via effects on water
uptake and loss. Soil salinity alone affects some 340 million hectares of cultivated land [2•]. To withstand
osmotic stresses, certain plants have evolved a high
capacity to synthesize and accumulate non-toxic solutes
(osmoprotectants or compatible solutes), predominantly
in the cytoplasm, as part of an overall mechanism to
raise osmotic pressure and thereby maintain both turgor
and the driving gradient for water uptake [3]. Many
microorganisms also produce osmoprotectants [4].
Figure 1 shows the structures of some common osmoprotectant compounds; they fall into three
groups — amino acids (e.g. proline), onium compounds
(e.g. glycine betaine, dimethylsulfoniopropionate), and
polyols/sugars (e.g. mannitol, D-ononitol, trehalose).
Being non-toxic, osmoprotectants can accumulate to
osmotically significant levels without disrupting metabolism; some of them can also protect enzymes and
membranes against damage from high salt concentrations [4] and others (especially polyols) protect against
reactive oxygen species [5].
The accumulation of osmoprotectants has been a target for
plant genetic engineering for more than 15 years [6], and
work is now in progress on all the compounds in Figure 1.
In several cases, introduction of a single foreign gene into
a transgenic plant has led to modest accumulation of an
osmoprotectant and, apparently in consequence, a small
increase in stress tolerance. The physiological and agricultural implications of these experiments have been
thoroughly reviewed [2•,5,7–9,10•]. We will focus here on
the metabolic implications of the genetic engineering
work, and on what needs to be done to drive more flux
towards osmoprotectant synthesis, with emphasis on
glycine betaine, polyols and trehalose.
Overview of progress in engineering
osmoprotectant synthesis
Table 1 catalogs the osmoprotectant work published to
date, carried out with tobacco, Arabidopsis, rice and potato.
The table illustrates several important points. First, many
of the transgenes are of a non-plant origin, which reflects
Figure 1
O
OH
Trehalose
Glycine betaine
OH
OH
OH
OH
COOS+
+
N
3-dimethylsulfoniopropionate
CH2OH
OH H2COH
O
OH
Proline
COO-
CH3O
CH2OH
OH
OH
HO
OH
OH
CH2OH
O
OH
COO-
OH
N+
OH
OH
OH
D-ononitol
CH2OH
Mannitol
OH
OH
CH2OH
Sorbitol
Current Opinion in Plant Biology
Structures of various osmoprotectants found in plants.
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
129
Table 1
Experiments designed to metabolically engineer osmoprotectant biosynthesis
Osmoprotectant
Gene constructs
Source
Promoter
Observed phenotype* Product level†
Enzyme activity‡
Stress
Side(% of physiol.) Assayed
Localized
resistance
effects
Mothbean P5CS
35S
√
180
Mannitol
[36,37]
Mannitol
[38]
Mannitol
[39]
E. coli mtldh
√
16
E. coli mtldh
35S
NOS
35S
√
16
E. coli mtldh
35S
Sorbitol
[40]
Sorbitol
[16•]
Apple s6pdh
35S
Apple s6pdh
35S
D-Ononitol
[41,21••]
Ice plant imtl
35S
√
Trehalose
[42]
Trehalose
[17••]
Trehalose
[43]
Yeast tpsl
atslA
√
E. coli tpsl
tpp
Yeast tpsl
35S
Patatin
35S
√
E. coli cdh
35S
√
A. globiformis
cod A
Spinach cmo
35S
√
Proline
[35]
GlyBet
[18]
GlyBet
[19•,20]
GlyBet
[12••]
√
√
8–16
0.7–1.3
√
Metabolic measurements§
Precursor Intermediate
Pathway
pool
pools
flux
√
0.7–300
10–70
√
√
0.8–3.4
√
√
0.8–28
√
√
1.2
35S
√
√
√
√
5
1
√
√
√
√
√
√
√
*A tick under ‘stress resistance’ indicates that the transgenic plant
displayed more resistance than controls. A tick under side-effects
indicates that transgenic plants had a growth defect. † This column
reports the level of osmoprotectant synthesis in osmoticallystressed transgenic plants as a percentage of the level found in a
representative plant that naturally accumulates the osmoprotectant
in similar conditions. These levels (given in mM in tissue water) are:
proline 36mM [35]; polyols 50mM [44]; trehalose 50mM [17 ••];
GlyBet 24mM [45]. ‡ Indicates that the enzyme activity of the
transgene product was assayed and localized to a subcellular
compartment. §Indicates measurements were made of the
endogenous levels of the osmoprotectant’s precursor or of any
pertinent intermediate, or whether flux through the pathway was
measured with isotopic tracer methods.
the lack of investment in plant biochemistry. The plant
gene pool should not be overlooked, as plants have
evolved unique genes to synthesize osmoprotectants [11],
and plant genes can possess particularly useful characteristics. For example, in transgenic tobacco, choline
monooxygenase (CMO) is stabilized by salt-stress via a
post-transcriptional mechanism, which leads to higher
CMO activity when it is most needed [12••]. Second, most
of the transgenes have been expressed from a constitutive
promoter. Tissue-specific and inducible promoters eventually will be necessary, and could be developed from genes
known to be induced when and where high osmoprotectant synthesis is required [13,14]. Third, most of the plants
described express a single transgene and so represent only
the first step in the engineering process, which is by nature
iterative [1]. Finally, very few of the transgenic plants produced to date have been thoroughly analyzed at the
metabolic level. This is critical because most of them accumulate only small amounts of the desired osmoprotectant,
and further progress requires that the metabolic constraints
be identified.
What are these constraints likely to be? First, certain metabolic networks can be rigid in that they have evolved to
maintain metabolite flux distributions that are optimal for
growth, and oppose any flux redistribution following
expression of a transgene [15]. Second, the engineered
pathway may divert flux away from primary metabolism
and so create undesirable side effects [16•]. Finally, a foreign metabolite may be degraded, limiting its
accumulation [17••]. We will now use published results to
illustrate these points.
Glycine betaine synthesis
Glycine betaine (GlyBet) is synthesized in the chloroplast
in two steps from choline (Figure 2a) and can accumulate
to high levels (>20 mM on a tissue water basis, Table 1) in
plants such as spinach and sugar beet under osmotic stress.
130
Plant biotechnology
Figure 2
(a)
Cho
ptd-EA
ptd-MME
ptd-DME
CDP-EA
CDP-MME
CDP-DME CDP-Cho
cmo
codA
Chloroplast
Bet ald
P-MME
P-DME
Bet ald
Cho
cdh
GlyBet
P-Cho
peamt
(b)
GlyBet
ptd-Cho
cdh
P-EA
badh
codA
Storage
Cho
Sucrose
Sucrose-6P
UDP
F6P
UDPG
Glucose
Fructose
PPi
Fructose
UTP
G1P
G6P
F6P
tps1
Trehalose-6P
tpp
F16P2
s6pdh
myo-inositol-1P
Sorbitol-6P
*
Trehalose
Glycolysis/
Krebs cycle
UDP
*
myo-inositol
Sorbitol
Triose
phosphates
mtldh
Mannitol-1P
*
Mannitol
imt1
D-ononitol
Current Opinion in Plant Biology
Metabolic pathways associated with GlyBet, polyol and trehalose
synthesis. (a) GlyBet synthesis (modified from [12••]) and (b) polyol
and trehalose synthesis. The osmoprotectants are given in bold.
Abbreviations are CDP-, cytidyldiphospho-; EA, ethanolamine; MME,
monomethylEA; DME, dimethylEA; Bet ald, betaine aldehyde; cmo,
choline monooxygenase; nsdh, endogenous non-specific aldehyde
dehydrogenase activity; cdh, Cho dehydrogenase; codA, Cho oxidase;
peamt, P-EA-N-methyltransferase; mtldh, mannitol dehydrogenase;
s6pdh, sorbitol dehydrogenase; imt1, inositol methyltransferase;
tps1, trehalose-6-phosphate synthase; tpp, trehalose-6-phosphate
phosphatase. Reactions with an asterisk (*) are non-specific
phosphatase activity.
Several groups have reported engineering GlyBet synthesis by introducing choline-oxidizing genes from E. coli [18],
Arthrobacter spp. [19•,20], and spinach [12••]. GlyBet levels
in the transgenic plants represented just a few percent of
those found in plants that naturally accumulate it. Two
groups have shown that supplying choline in axenic cultured plants enhanced GlyBet synthesis, indicating a
constraint in choline synthesis ([12••], Huang et al. abstract
in Plant Physiol 1997, 114S:120). Detailed analysis of
choline metabolism in tobacco demonstrates that it is
embedded in a rigid network in which choline is directed
almost exclusively to phosphatidyl-choline synthesis, making it difficult to divert choline to GlyBet [12••]. Also, in
tobacco de novo choline synthesis is probably constrained at
the step catalyzed by phosphoethanolamine-N-methyltransferase [12••]. In this context, a comparison of the
demand for choline moieties between a plant that lacks
GlyBet and a plant that synthesizes it is instructive.
Figure 3 makes clear that GlyBet synthesis represents a
huge demand on choline synthesis, requiring more than
90% of the choline moieties. This suggests that the choline
synthesis pathway is far more active in GlyBet accumulators. Increasing the choline supply in tobacco will require
additional engineering steps. One possibility is to increase
choline synthesis Via up-regulation of phosphoethanolamine-N-methyltransferase activity.
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
Trehalose synthesis
The non-reducing disaccharide trehalose is believed to
enable desiccation resistant organisms to survive dehydration
stress
[17••];
it
is
synthesized
from
glucose-6-phosphate and uridine-diphosphoglucose
(Figure 2b). In plants engineered to synthesize trehalose,
only very small amounts accumulate (Table 1). In two
reports trehalose-6-P-synthase (tps) alone was introduced,
leaving dephosphorylation of trehalose-6-P to an endogenous non-specific phosphatase activity. In one report both
tps and trehalose-6-P phosphatase (tpp) were inserted, but
even with both genes, a dramatic increase in trehalose did
not occur due to its degradation by trehalase [17••]. This
was demonstrated by the use of a trehalase inhibitor, which
increased trehalose accumulation and identified a constraint on trehalose synthesis in plants that do not naturally
accumulate it [17••].
Metabolic engineering requires a guided,
iterative approach
As noted above, Table 1 highlights the relative lack of
attention to metabolic analysis of transgenic plants, in particular in vivo estimates of pathway fluxes and intermediate
pool sizes made using isotopic tracer methods. Such data
can be incorporated into metabolic models, which are very
helpful tools to describe and predict the behavior of the target pathway (Figure 4). Models have a long track record of
application to the metabolic engineering of microorganisms
[22••], and to metabolic pathway characterization in plants
[23]. Model development begins with a metabolic map as
shown for GlyBet synthesis (Figure 2a) or polyol synthesis
(Figure 2b). The input data consist of intermediate and
end-product pool size measurements, and flux-rates calculated from timed in vivo isotope labeling data. The
modeling program is used to fit the data to the described
pathway, which is done interactively by varying flux rates
Figure 3
Tobacco
20
Spinach
10
G
lyB
et
ho
C
d-
-C
-P
G
pt
ho
ho
P-
C
ho
0
C
In some plants polyol synthesis is upregulated in response
to osmotic stress, leading to significant polyol accumulation (up to 50 mM on a tissue water basis, Table 1). Polyols
are derived from sugar phosphates by reduction and
dephosphorylation (Figure 2b). Mannitol, sorbitol and Dononitol synthesis have been introduced into transgenic
plants. Two reports are of particular interest from a metabolic standpoint; one illustrates a competitive or
antagonistic effect between transgene activity and hostplant metabolism, and the other a synergistic effect. First,
analysis of sorbitol levels in transgenic tobacco showed that
high sorbitol accumulation was associated with growth
defects and necrosis. This was attributed to myo-inositol
depletion, although sorbitol toxicity and cytosolic Pi depletion due to sorbitol-6-P build-up were not ruled out [16•].
Second, in tobacco, the myo-inositol pool expands as the
plants are salt- or drought-stressed, and in plants engineered to synthesize D-ononitol from myo-inositol, the
increased precursor supply makes D-ononitol production
stress inducible [21••].
µmol g -1fw
Polyol synthesis
131
Molecule
Current Opinion in Plant Biology
Glycine betaine synthesis represents a large demand on choline
synthesis. Total demand for choline moieties in a GlyBet accumulator
(spinach) and a non-accumulator (tobacco). Abbreviations are Cho,
choline; P-Cho, phosphocholine; G-P-Cho, glycerophosphorylcholine;
ptd-Cho, phosphatidylcholine; GlyBet, glycine betaine. The data are
derived from [12••,45–48] and also from the authors’ unpublished results.
and pool sizes (see [23]). Once developed, the model can
be tested experimentally to assess its accuracy. The most
important feature of models is their potential to predict the
impact of a modification (e.g. inserting a transgene to
upregulate a step in the pathway) on pathway flux. This can
guide the engineering process by simulating the outcome
of various experimental strategies. For instance, a model for
choline metabolism in tobacco has been developed to simulate strategies for engineering GlyBet synthesis. It can be
accessed at the world wide web site (http://www.hort.purdue.edu/cfpesp/models/models.htm) for constructing
interactive metabolic models.
A related, but distinct, approach to understanding and predicting metabolic flux is metabolic control analysis (MCA).
MCA is basically concerned with the steady state of a
metabolic pathway, in which the enzyme activities and
metabolite pool sizes remain constant. MCA shows that
control of pathway flux is typically shared among all the
enzyme activities in the pathway, in sharp contrast with the
traditional concept of a single ‘rate-limiting’ step [24].
Each enzyme’s contribution to control of flux can vary and
MCA defines this behavior as it relates to an individual
step, or the entire pathway. The analysis can be used in
simulation experiments similar to those outlined above.
MCA has contributed both to microbial metabolic engineering [22••], and to basic understanding of the control of
metabolism [25••]. For example, a recent report, using
MCA to evaluate transgenic plants, clearly demonstrates
that the control of pathway flux is shared among the component reactions within the pathway and is not limited to
an individual step [26••].
132
Plant biotechnology
Figure 4
A generic biochemical model as displayed at
the modeling website. This web page is part
of a modeling site which has been established
to allow scientists to understand and work
with biochemical models (http://www.hort.
purdue.edu/cfpesp/models/models.htm). By
adjusting fluxes and pool sizes with literature
values as a guide, model curves can be
generated and compared with experimental
radiolabeling data. When the model and
experimental results are in agreement, the
fluxes and pool sizes determined can be very
informative. Manipulating the flux or pool of
interest in the model provides a guide to the
effects of altering that particular flux or pool
size. Each letter in the generic model
represents a metabolic pool (E, A, B, C and
D). The numbers beside the letters designate:
specific activity of that pool at time zero
(nCi/nmol), 1; the initial pool size (nmol/gfw),
2; the flux into the pool (nmol/min/gfw), 3; the
combined rate of utilization from the pool
(nmol/min/gfw), 4. The variable (k) determines
the rate of uptake of the radiolabeled
precursor, E. As the pool of E is drawn down,
its rate of uptake declines proportionately. TS
is the total simulation time in minutes. MR is
the maximum radioactivity (nCi/gfw) for the
left-hand graph and MP is the maximum pool
size (nmol/gfw) for the right-hand graph. DS is
the scaling factor for pool D to allow the curve
to fit on the right graph. This modeling
procedure was used in the analysis of 3dimethylsulfoniopropionate synthesis in S.
alterniflora [23].
Advancing technology to aid the
engineering process
Two useful tools to help diagnose problems in transgenic
plants are DNA micro-array technology and in vivo NMR
spectroscopy. Micro-array technology was developed to
evaluate the expression of many genes at once. The analytical power of this technology has been demonstrated in
yeast [27••], and is being applied to plants [28]. It provides
high-resolution gene expression data which can be used to
identify (unanticipated) changes in expression that follow
the insertion of a transgene. In vivo NMR spectroscopy can
be used to detect and quantitate several metabolites at
once. In some cases the compartmentation of a metabolite
can be distinguished [29••]. Although rarely as sensitive as
standard in vivo biochemical or mass spectral methods, in
vivo NMR techniques can be used to make otherwise
impossible measurements — for instance, high resolution
two-dimensional 31P-NMR spectroscopy was recently
used to directly measure metabolic flux rates [30•].
one at a time. Such an approach was used to manipulate
secondary metabolite production in maize cells [32]. The
basic principle is to manipulate the expression of a regulatory gene (e.g. a specific transcription factor), which in
turn alters the expression of the entire regulon. Overexpression of CBF1, a transcription factor that controls
the expression of cold-responsive genes in Arabidopsis,
demonstrated the feasibility of this approach in a plant
stress context [31••]. Other distinct transcription factors
that may function in a similar way to CBF1 have also been
described [33]. An Arabidopsis regulatory locus (esk1) that
governs genes involved in both the synthesis and breakdown of proline has been identified [34•], and is,
therefore, an attractive candidate for regulon engineering. It is important to note, however, that ectopic
expression of regulatory genes can only modify a plant’s
natural capabilities; it cannot confer new ones (e.g. the
ability to synthesize a novel osmoprotectant).
Conclusions
Regulon engineering — manipulating entire
pathways using regulatory genes
Expression of regulatory genes that control several steps
in a pathway or in related pathways (i.e. a regulon [31••]),
may provide an alternative to introducing pathway genes
Engineering metabolic change is not a trivial endeavor. It
will typically require iterative rounds of transformation
guided by thorough analysis of each transgenic generation.
Interactive metabolic modeling promises to streamline this
process by helping predict which step(s) will require alteration through additional rounds of engineering. Emerging
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
technology including DNA micro-arrays and in vivo NMR
could also speed and simplify the analysis of genetically
engineered plants. Only when a biochemical trait, such as
osmoprotectant biosynthesis, is successfully engineered
can the physiological consequences of that trait be
assessed. Metabolic engineering research will teach us not
only how to engineer biochemical change but also much
about the metabolic pathways themselves.
Acknowledgements
Work in the authors’ laboratories is supported by the National Science
Foundation (IBN 9816075 and IBN 9813999), the United States
Department of Agriculture National Research Initiative Competitive Grants
Program (95-37100-1596 and 98-35100-6149), the Office of Naval Research
(N00014-96-1-0364 and N000149-96-1-0366) and the CV Griffin Sr.
Foundation and the Florida Agricultural Experiment Station. Journal series
number R-06645.
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• of special interest
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••
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•
Transformation of Arabidopsis thaliana with the codA gene for
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shared by the many steps between fructose-6-P and the Krebs cycle.
134
Plant biotechnology
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••
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cDNA microarrays. Plant J 1998, 15:821-833.
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•• compartmentation, and metabolism of homoserine in higher plant
cells: carbon-13- and phosphorus-31-nuclear magnetic
resonance studies. Plant Physiol 1998, 116:547-557.
A good example of how in vivo NMR spectroscopy can complement classical biochemical analysis. 13C- and 31P-NMR were used to monitor the
uptake and metabolism of homoserine. The experiments demonstrate how
metabolite pool size data and enzymatic rate data can be derived from NMR
spectra. An experiment to determine the distribution of phosphohomoserine
between the cytosol and the vacuole is also described.
30. Roscher A, Emsley L, Raymond P, Roby C: Unidirectional steady
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state rates of central metabolism enzymes measured
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to show how each reaction responds to changes in external stimuli.
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freezing tolerance. The experiments show that overexpressing CBF1
induces the acclimation effect and enhances freezing tolerance.
32. Grotewold E, Chamberlin M, Snook M, Siame B, Butler L, Swenson J,
Maddock S, St Clair G, Bowen B: Engineering secondary
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factors. Plant Cell 1998, 10:721-740.
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freezing tolerant. Proc Natl Acad Sci USA 1998, 95:7799-7804.
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proline metabolism, this gene can simultaneously upregulate synthesis
genes and downregulate degradative genes, implying that it is near the top
of a signaling cascade.
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Metabolic engineering of plants for osmotic stress resistance
Michael L Nuccio*, David Rhodes†, Scott D McNeil* and
Andrew D Hanson*‡
Genes encoding critical steps in the synthesis of
osmoprotectant compounds are now being expressed in
transgenic plants. These plants generally accumulate low levels
of osmoprotectants and have increased stress tolerance. The
next priority is therefore to engineer greater osmoprotectant
synthesis without detriment to the rest of metabolism. This will
require manipulation of multiple genes, guided by thorough
analysis of metabolite fluxes and pool sizes.
Addresses
*Department of Horticultural Sciences, University of Florida,
Gainesville, FL 32611-0690, USA
† Department of Horticulture, Purdue University, West Lafayette,
IN 47907-1165, USA
‡e-mail: [email protected]
Current Opinion in Plant Biology 1999, 2:128–134
http://biomednet.com/elecref/1369526600200128
© Elsevier Science Ltd ISSN 1369-5266
Abbreviations
GlyBet glycine betaine
MCA
metabolic control analysis
Introduction
Improving crop resistance to osmotic stresses is a longstanding goal of agricultural biotechnology [1,2 •].
Drought, salinity and freeze-induced dehydration constitute direct osmotic stresses; chilling and hypoxia can
indirectly cause osmotic stress via effects on water
uptake and loss. Soil salinity alone affects some 340 million hectares of cultivated land [2•]. To withstand
osmotic stresses, certain plants have evolved a high
capacity to synthesize and accumulate non-toxic solutes
(osmoprotectants or compatible solutes), predominantly
in the cytoplasm, as part of an overall mechanism to
raise osmotic pressure and thereby maintain both turgor
and the driving gradient for water uptake [3]. Many
microorganisms also produce osmoprotectants [4].
Figure 1 shows the structures of some common osmoprotectant compounds; they fall into three
groups — amino acids (e.g. proline), onium compounds
(e.g. glycine betaine, dimethylsulfoniopropionate), and
polyols/sugars (e.g. mannitol, D-ononitol, trehalose).
Being non-toxic, osmoprotectants can accumulate to
osmotically significant levels without disrupting metabolism; some of them can also protect enzymes and
membranes against damage from high salt concentrations [4] and others (especially polyols) protect against
reactive oxygen species [5].
The accumulation of osmoprotectants has been a target for
plant genetic engineering for more than 15 years [6], and
work is now in progress on all the compounds in Figure 1.
In several cases, introduction of a single foreign gene into
a transgenic plant has led to modest accumulation of an
osmoprotectant and, apparently in consequence, a small
increase in stress tolerance. The physiological and agricultural implications of these experiments have been
thoroughly reviewed [2•,5,7–9,10•]. We will focus here on
the metabolic implications of the genetic engineering
work, and on what needs to be done to drive more flux
towards osmoprotectant synthesis, with emphasis on
glycine betaine, polyols and trehalose.
Overview of progress in engineering
osmoprotectant synthesis
Table 1 catalogs the osmoprotectant work published to
date, carried out with tobacco, Arabidopsis, rice and potato.
The table illustrates several important points. First, many
of the transgenes are of a non-plant origin, which reflects
Figure 1
O
OH
Trehalose
Glycine betaine
OH
OH
OH
OH
COOS+
+
N
3-dimethylsulfoniopropionate
CH2OH
OH H2COH
O
OH
Proline
COO-
CH3O
CH2OH
OH
OH
HO
OH
OH
CH2OH
O
OH
COO-
OH
N+
OH
OH
OH
D-ononitol
CH2OH
Mannitol
OH
OH
CH2OH
Sorbitol
Current Opinion in Plant Biology
Structures of various osmoprotectants found in plants.
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
129
Table 1
Experiments designed to metabolically engineer osmoprotectant biosynthesis
Osmoprotectant
Gene constructs
Source
Promoter
Observed phenotype* Product level†
Enzyme activity‡
Stress
Side(% of physiol.) Assayed
Localized
resistance
effects
Mothbean P5CS
35S
√
180
Mannitol
[36,37]
Mannitol
[38]
Mannitol
[39]
E. coli mtldh
√
16
E. coli mtldh
35S
NOS
35S
√
16
E. coli mtldh
35S
Sorbitol
[40]
Sorbitol
[16•]
Apple s6pdh
35S
Apple s6pdh
35S
D-Ononitol
[41,21••]
Ice plant imtl
35S
√
Trehalose
[42]
Trehalose
[17••]
Trehalose
[43]
Yeast tpsl
atslA
√
E. coli tpsl
tpp
Yeast tpsl
35S
Patatin
35S
√
E. coli cdh
35S
√
A. globiformis
cod A
Spinach cmo
35S
√
Proline
[35]
GlyBet
[18]
GlyBet
[19•,20]
GlyBet
[12••]
√
√
8–16
0.7–1.3
√
Metabolic measurements§
Precursor Intermediate
Pathway
pool
pools
flux
√
0.7–300
10–70
√
√
0.8–3.4
√
√
0.8–28
√
√
1.2
35S
√
√
√
√
5
1
√
√
√
√
√
√
√
*A tick under ‘stress resistance’ indicates that the transgenic plant
displayed more resistance than controls. A tick under side-effects
indicates that transgenic plants had a growth defect. † This column
reports the level of osmoprotectant synthesis in osmoticallystressed transgenic plants as a percentage of the level found in a
representative plant that naturally accumulates the osmoprotectant
in similar conditions. These levels (given in mM in tissue water) are:
proline 36mM [35]; polyols 50mM [44]; trehalose 50mM [17 ••];
GlyBet 24mM [45]. ‡ Indicates that the enzyme activity of the
transgene product was assayed and localized to a subcellular
compartment. §Indicates measurements were made of the
endogenous levels of the osmoprotectant’s precursor or of any
pertinent intermediate, or whether flux through the pathway was
measured with isotopic tracer methods.
the lack of investment in plant biochemistry. The plant
gene pool should not be overlooked, as plants have
evolved unique genes to synthesize osmoprotectants [11],
and plant genes can possess particularly useful characteristics. For example, in transgenic tobacco, choline
monooxygenase (CMO) is stabilized by salt-stress via a
post-transcriptional mechanism, which leads to higher
CMO activity when it is most needed [12••]. Second, most
of the transgenes have been expressed from a constitutive
promoter. Tissue-specific and inducible promoters eventually will be necessary, and could be developed from genes
known to be induced when and where high osmoprotectant synthesis is required [13,14]. Third, most of the plants
described express a single transgene and so represent only
the first step in the engineering process, which is by nature
iterative [1]. Finally, very few of the transgenic plants produced to date have been thoroughly analyzed at the
metabolic level. This is critical because most of them accumulate only small amounts of the desired osmoprotectant,
and further progress requires that the metabolic constraints
be identified.
What are these constraints likely to be? First, certain metabolic networks can be rigid in that they have evolved to
maintain metabolite flux distributions that are optimal for
growth, and oppose any flux redistribution following
expression of a transgene [15]. Second, the engineered
pathway may divert flux away from primary metabolism
and so create undesirable side effects [16•]. Finally, a foreign metabolite may be degraded, limiting its
accumulation [17••]. We will now use published results to
illustrate these points.
Glycine betaine synthesis
Glycine betaine (GlyBet) is synthesized in the chloroplast
in two steps from choline (Figure 2a) and can accumulate
to high levels (>20 mM on a tissue water basis, Table 1) in
plants such as spinach and sugar beet under osmotic stress.
130
Plant biotechnology
Figure 2
(a)
Cho
ptd-EA
ptd-MME
ptd-DME
CDP-EA
CDP-MME
CDP-DME CDP-Cho
cmo
codA
Chloroplast
Bet ald
P-MME
P-DME
Bet ald
Cho
cdh
GlyBet
P-Cho
peamt
(b)
GlyBet
ptd-Cho
cdh
P-EA
badh
codA
Storage
Cho
Sucrose
Sucrose-6P
UDP
F6P
UDPG
Glucose
Fructose
PPi
Fructose
UTP
G1P
G6P
F6P
tps1
Trehalose-6P
tpp
F16P2
s6pdh
myo-inositol-1P
Sorbitol-6P
*
Trehalose
Glycolysis/
Krebs cycle
UDP
*
myo-inositol
Sorbitol
Triose
phosphates
mtldh
Mannitol-1P
*
Mannitol
imt1
D-ononitol
Current Opinion in Plant Biology
Metabolic pathways associated with GlyBet, polyol and trehalose
synthesis. (a) GlyBet synthesis (modified from [12••]) and (b) polyol
and trehalose synthesis. The osmoprotectants are given in bold.
Abbreviations are CDP-, cytidyldiphospho-; EA, ethanolamine; MME,
monomethylEA; DME, dimethylEA; Bet ald, betaine aldehyde; cmo,
choline monooxygenase; nsdh, endogenous non-specific aldehyde
dehydrogenase activity; cdh, Cho dehydrogenase; codA, Cho oxidase;
peamt, P-EA-N-methyltransferase; mtldh, mannitol dehydrogenase;
s6pdh, sorbitol dehydrogenase; imt1, inositol methyltransferase;
tps1, trehalose-6-phosphate synthase; tpp, trehalose-6-phosphate
phosphatase. Reactions with an asterisk (*) are non-specific
phosphatase activity.
Several groups have reported engineering GlyBet synthesis by introducing choline-oxidizing genes from E. coli [18],
Arthrobacter spp. [19•,20], and spinach [12••]. GlyBet levels
in the transgenic plants represented just a few percent of
those found in plants that naturally accumulate it. Two
groups have shown that supplying choline in axenic cultured plants enhanced GlyBet synthesis, indicating a
constraint in choline synthesis ([12••], Huang et al. abstract
in Plant Physiol 1997, 114S:120). Detailed analysis of
choline metabolism in tobacco demonstrates that it is
embedded in a rigid network in which choline is directed
almost exclusively to phosphatidyl-choline synthesis, making it difficult to divert choline to GlyBet [12••]. Also, in
tobacco de novo choline synthesis is probably constrained at
the step catalyzed by phosphoethanolamine-N-methyltransferase [12••]. In this context, a comparison of the
demand for choline moieties between a plant that lacks
GlyBet and a plant that synthesizes it is instructive.
Figure 3 makes clear that GlyBet synthesis represents a
huge demand on choline synthesis, requiring more than
90% of the choline moieties. This suggests that the choline
synthesis pathway is far more active in GlyBet accumulators. Increasing the choline supply in tobacco will require
additional engineering steps. One possibility is to increase
choline synthesis Via up-regulation of phosphoethanolamine-N-methyltransferase activity.
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
Trehalose synthesis
The non-reducing disaccharide trehalose is believed to
enable desiccation resistant organisms to survive dehydration
stress
[17••];
it
is
synthesized
from
glucose-6-phosphate and uridine-diphosphoglucose
(Figure 2b). In plants engineered to synthesize trehalose,
only very small amounts accumulate (Table 1). In two
reports trehalose-6-P-synthase (tps) alone was introduced,
leaving dephosphorylation of trehalose-6-P to an endogenous non-specific phosphatase activity. In one report both
tps and trehalose-6-P phosphatase (tpp) were inserted, but
even with both genes, a dramatic increase in trehalose did
not occur due to its degradation by trehalase [17••]. This
was demonstrated by the use of a trehalase inhibitor, which
increased trehalose accumulation and identified a constraint on trehalose synthesis in plants that do not naturally
accumulate it [17••].
Metabolic engineering requires a guided,
iterative approach
As noted above, Table 1 highlights the relative lack of
attention to metabolic analysis of transgenic plants, in particular in vivo estimates of pathway fluxes and intermediate
pool sizes made using isotopic tracer methods. Such data
can be incorporated into metabolic models, which are very
helpful tools to describe and predict the behavior of the target pathway (Figure 4). Models have a long track record of
application to the metabolic engineering of microorganisms
[22••], and to metabolic pathway characterization in plants
[23]. Model development begins with a metabolic map as
shown for GlyBet synthesis (Figure 2a) or polyol synthesis
(Figure 2b). The input data consist of intermediate and
end-product pool size measurements, and flux-rates calculated from timed in vivo isotope labeling data. The
modeling program is used to fit the data to the described
pathway, which is done interactively by varying flux rates
Figure 3
Tobacco
20
Spinach
10
G
lyB
et
ho
C
d-
-C
-P
G
pt
ho
ho
P-
C
ho
0
C
In some plants polyol synthesis is upregulated in response
to osmotic stress, leading to significant polyol accumulation (up to 50 mM on a tissue water basis, Table 1). Polyols
are derived from sugar phosphates by reduction and
dephosphorylation (Figure 2b). Mannitol, sorbitol and Dononitol synthesis have been introduced into transgenic
plants. Two reports are of particular interest from a metabolic standpoint; one illustrates a competitive or
antagonistic effect between transgene activity and hostplant metabolism, and the other a synergistic effect. First,
analysis of sorbitol levels in transgenic tobacco showed that
high sorbitol accumulation was associated with growth
defects and necrosis. This was attributed to myo-inositol
depletion, although sorbitol toxicity and cytosolic Pi depletion due to sorbitol-6-P build-up were not ruled out [16•].
Second, in tobacco, the myo-inositol pool expands as the
plants are salt- or drought-stressed, and in plants engineered to synthesize D-ononitol from myo-inositol, the
increased precursor supply makes D-ononitol production
stress inducible [21••].
µmol g -1fw
Polyol synthesis
131
Molecule
Current Opinion in Plant Biology
Glycine betaine synthesis represents a large demand on choline
synthesis. Total demand for choline moieties in a GlyBet accumulator
(spinach) and a non-accumulator (tobacco). Abbreviations are Cho,
choline; P-Cho, phosphocholine; G-P-Cho, glycerophosphorylcholine;
ptd-Cho, phosphatidylcholine; GlyBet, glycine betaine. The data are
derived from [12••,45–48] and also from the authors’ unpublished results.
and pool sizes (see [23]). Once developed, the model can
be tested experimentally to assess its accuracy. The most
important feature of models is their potential to predict the
impact of a modification (e.g. inserting a transgene to
upregulate a step in the pathway) on pathway flux. This can
guide the engineering process by simulating the outcome
of various experimental strategies. For instance, a model for
choline metabolism in tobacco has been developed to simulate strategies for engineering GlyBet synthesis. It can be
accessed at the world wide web site (http://www.hort.purdue.edu/cfpesp/models/models.htm) for constructing
interactive metabolic models.
A related, but distinct, approach to understanding and predicting metabolic flux is metabolic control analysis (MCA).
MCA is basically concerned with the steady state of a
metabolic pathway, in which the enzyme activities and
metabolite pool sizes remain constant. MCA shows that
control of pathway flux is typically shared among all the
enzyme activities in the pathway, in sharp contrast with the
traditional concept of a single ‘rate-limiting’ step [24].
Each enzyme’s contribution to control of flux can vary and
MCA defines this behavior as it relates to an individual
step, or the entire pathway. The analysis can be used in
simulation experiments similar to those outlined above.
MCA has contributed both to microbial metabolic engineering [22••], and to basic understanding of the control of
metabolism [25••]. For example, a recent report, using
MCA to evaluate transgenic plants, clearly demonstrates
that the control of pathway flux is shared among the component reactions within the pathway and is not limited to
an individual step [26••].
132
Plant biotechnology
Figure 4
A generic biochemical model as displayed at
the modeling website. This web page is part
of a modeling site which has been established
to allow scientists to understand and work
with biochemical models (http://www.hort.
purdue.edu/cfpesp/models/models.htm). By
adjusting fluxes and pool sizes with literature
values as a guide, model curves can be
generated and compared with experimental
radiolabeling data. When the model and
experimental results are in agreement, the
fluxes and pool sizes determined can be very
informative. Manipulating the flux or pool of
interest in the model provides a guide to the
effects of altering that particular flux or pool
size. Each letter in the generic model
represents a metabolic pool (E, A, B, C and
D). The numbers beside the letters designate:
specific activity of that pool at time zero
(nCi/nmol), 1; the initial pool size (nmol/gfw),
2; the flux into the pool (nmol/min/gfw), 3; the
combined rate of utilization from the pool
(nmol/min/gfw), 4. The variable (k) determines
the rate of uptake of the radiolabeled
precursor, E. As the pool of E is drawn down,
its rate of uptake declines proportionately. TS
is the total simulation time in minutes. MR is
the maximum radioactivity (nCi/gfw) for the
left-hand graph and MP is the maximum pool
size (nmol/gfw) for the right-hand graph. DS is
the scaling factor for pool D to allow the curve
to fit on the right graph. This modeling
procedure was used in the analysis of 3dimethylsulfoniopropionate synthesis in S.
alterniflora [23].
Advancing technology to aid the
engineering process
Two useful tools to help diagnose problems in transgenic
plants are DNA micro-array technology and in vivo NMR
spectroscopy. Micro-array technology was developed to
evaluate the expression of many genes at once. The analytical power of this technology has been demonstrated in
yeast [27••], and is being applied to plants [28]. It provides
high-resolution gene expression data which can be used to
identify (unanticipated) changes in expression that follow
the insertion of a transgene. In vivo NMR spectroscopy can
be used to detect and quantitate several metabolites at
once. In some cases the compartmentation of a metabolite
can be distinguished [29••]. Although rarely as sensitive as
standard in vivo biochemical or mass spectral methods, in
vivo NMR techniques can be used to make otherwise
impossible measurements — for instance, high resolution
two-dimensional 31P-NMR spectroscopy was recently
used to directly measure metabolic flux rates [30•].
one at a time. Such an approach was used to manipulate
secondary metabolite production in maize cells [32]. The
basic principle is to manipulate the expression of a regulatory gene (e.g. a specific transcription factor), which in
turn alters the expression of the entire regulon. Overexpression of CBF1, a transcription factor that controls
the expression of cold-responsive genes in Arabidopsis,
demonstrated the feasibility of this approach in a plant
stress context [31••]. Other distinct transcription factors
that may function in a similar way to CBF1 have also been
described [33]. An Arabidopsis regulatory locus (esk1) that
governs genes involved in both the synthesis and breakdown of proline has been identified [34•], and is,
therefore, an attractive candidate for regulon engineering. It is important to note, however, that ectopic
expression of regulatory genes can only modify a plant’s
natural capabilities; it cannot confer new ones (e.g. the
ability to synthesize a novel osmoprotectant).
Conclusions
Regulon engineering — manipulating entire
pathways using regulatory genes
Expression of regulatory genes that control several steps
in a pathway or in related pathways (i.e. a regulon [31••]),
may provide an alternative to introducing pathway genes
Engineering metabolic change is not a trivial endeavor. It
will typically require iterative rounds of transformation
guided by thorough analysis of each transgenic generation.
Interactive metabolic modeling promises to streamline this
process by helping predict which step(s) will require alteration through additional rounds of engineering. Emerging
Metabolic engineering of plants for osmotic stress resistance Nuccio et al.
technology including DNA micro-arrays and in vivo NMR
could also speed and simplify the analysis of genetically
engineered plants. Only when a biochemical trait, such as
osmoprotectant biosynthesis, is successfully engineered
can the physiological consequences of that trait be
assessed. Metabolic engineering research will teach us not
only how to engineer biochemical change but also much
about the metabolic pathways themselves.
Acknowledgements
Work in the authors’ laboratories is supported by the National Science
Foundation (IBN 9816075 and IBN 9813999), the United States
Department of Agriculture National Research Initiative Competitive Grants
Program (95-37100-1596 and 98-35100-6149), the Office of Naval Research
(N00014-96-1-0364 and N000149-96-1-0366) and the CV Griffin Sr.
Foundation and the Florida Agricultural Experiment Station. Journal series
number R-06645.
References and recommended reading
Papers of particular interest, published within the annual period of review,
have been highlighted as:
• of special interest
•• of outstanding interest
1.
McCue KF, Hanson AD: Drought and salt tolerance: towards
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2. Jain RK, Selvaraj G: Molecular genetic improvement of salt
•
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An excellent review of recent progress towards engineering salt-resistance
in plants. It covers the physiological aspects of salt-tolerance and includes a
discussion of the adaptive strategies found in nature.
3.
Rhodes D, Samaras Y: Genetic control of osmoregulation in plants.
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•
plant physiology. J Exp Botany 1998, 49:915-929.
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number of mechanisms, many of which are unknown. It cautions against
focusing on a single trait such as osmoprotectant synthesis as a solution to
introducing resistance, and favors the identification and exploitation of quantitative trait loci associated with stress resistance.
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