The Plant Journal (2009) 58, 220–234
doi: 10.1111/j.1365-313X.2008.03771.x
The role of light in soybean seed filling metabolism
Doug K. Allen*, John B. Ohlrogge and Yair Shachar-Hill
Michigan State University, Plant Biology Department, East Lansing, MI 48824, USA
Received 29 October 2008; revised 18 November 2008; accepted 27 November 2008; published online 27 January 2009.
*
For correspondence (fax +1 517 353 1926; e-mail [email protected]).
Summary
Soybean (Glycine max) yields high levels of both protein and oil, making it one of the most versatile and
important crops in the world. Light has been implicated in the physiology of developing green seeds including
soybeans but its roles are not quantitatively understood. We have determined the light levels reaching
growing soybean embryos under field conditions and report detailed redox and energy balance analyses for
them. Direct flux measurements and labeling patterns for multiple labeling experiments including [U-13C6]glucose, [U-13C5]-glutamine, the combination of [U-14C12]-sucrose + [U-14C6]-glucose + [U-14C5]-glutamine + [U-14C4]-asparagine, or 14CO2 labeling were performed at different light levels to give further insight
into green embryo metabolism during seed filling and to develop and validate a flux map. Labeling patterns
(protein amino acids, triacylglycerol fatty acids, starch, cell wall, protein glycan monomers, organic acids),
uptake fluxes (glutamine, asparagine, sucrose, glucose), fluxes to biomass (protein amino acids, oil), and
respiratory fluxes (CO2, O2) were established by a combination of gas chromatography-mass spectrometry,
13
C- and 1H-NMR, scintillation counting, HPLC, gas chromatography-flame ionization detection, C:N and amino
acid analyses, and infrared gas analysis, yielding over 750 measurements of metabolism. Our results show:
(i) that developing soybeans receive low but significant light levels that influence growth and metabolism; (ii) a
role for light in generating ATP but not net reductant during seed filling; (iii) that flux through Rubisco
contributes to carbon conversion efficiency through generation of 3-phosphoglycerate; and (iv) a larger
contribution of amino acid carbon to fatty acid synthesis than in other oilseeds analyzed to date.
Keywords: photosynthesis, seed metabolism, redox balance, isotopic labeling, metabolic flux analysis,
soybean embryo, Rubisco.
Introduction
The proportions of oil, protein, and carbohydrate in soybean
(Glycine max) seeds influence their value, and the control of
their accumulation has been studied extensively. Maternally
supplied substrates (Fabre and Planchon, 2000; Nakasathien
et al., 2000; Pipolo et al., 2004) and seed genotype (Wilcox,
1998; Narvel et al., 2000; Hernandez-Sebastia et al., 2005)
determine the oil and protein levels in the seed. Although the
fatty acid composition of soybeans has been successfully
engineered (Damude and Kinney, 2007), molecular attempts
to modify the proportions of oil and protein have resulted in
only a few successes for related legumes (Rolletschek et al.,
2005a, 2007). In part this reflects the complexity of metabolic
networks (Egli, 1998) and the uncertain relationship between
seed composition and seed metabolism.
One way to facilitate the study of seed metabolic networks
is by growing embryos in vitro. The absence of a vascular
connection between the seed coat and embryo (Thorne,
220
1980, 1981) implies that transfer of substrates from the
plant to the embryo is apoplastic. Thus, by measuring the
apoplastic contents surrounding the embryo, in planta
conditions can be mimicked in vitro (Hsu and Obendorf,
1982; Obendorf and Wettlaufer, 1984). Using embryo cultures, numerous studies have explored the impact of altered
medium composition or environmental conditions on
growth and protein and oil production (Thompson et al.,
1977; Holowach et al., 1984a, b; Saravitz and Raper, 1995;
Hayati et al., 1996; Pipolo et al., 2004). These studies have
not focused on the underlying metabolism nor considered
the effect of light on seed metabolism.
The greenness of soybean and other oilseed embryos
implies the capacity to utilize light. For Brassica, a significant
amount of light is transmitted to embryos (King et al., 1998;
Ruuska et al., 2004). Studies of soybean seeds (Willms et al.,
1999; Rolletschek et al., 2005b) and comparisons between
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd
Role of light in soybean seed filling metabolism 221
linseed (green) and safflower (non-green) embryos (Browse
and Slack, 1985) have led to the inference that light can play
significant roles in providing free energy, reductant, and/or
oxygen. Other studies on oilseed rape have correlated oil
production with light-powered cofactor generation (Asokanthan et al., 1997). In fact, the photosynthetic rates in Brassica
embryos (King et al., 1998) can meet the demands of fatty
acid biosynthesis for reductant and ATP (Ruuska et al.,
2004), and photosynthesis has been shown to contribute
substantially to the carbon economy of these seeds (Schwender et al., 2004a; Goffman et al., 2005). Studies on the
whole pod, seed, and cotyledons of soybean (Quebedeaux
and Chollet, 1975; Sambo et al., 1977; Satterlee and Koller,
1984; Sugimoto et al., 1987; Willms et al., 1999), as well as
other legumes (Flinn et al., 1977; Furbank et al., 2004),
indicate photosynthetic reassimilation of CO2, although
without a net photosynthetic capacity. Quantifying the
contribution of photosynthetic electron transport and CO2
reassimilation to the economy of photoheterotrophic seeds
is challenging, because CO2, oxygen, reductant and energy
are simultaneously consumed and produced in many places
during metabolism. Therefore all flows throughout the
network of central metabolism must be considered in order
to accurately report on their participation.
Metabolic flux analysis (MFA) quantifies the flow of
material through metabolic networks (Stephanopoulos et al.,
1998; Roscher et al., 2000; Ratcliffe and Shachar-Hill, 2006;
Dieuaide-Noubhani et al., 2007) utilizing the patterns of
labeling in metabolites from isotopic labeling experiments
together with uptake and output measurements to establish
flux values. Through the quantification of metabolism at the
systems level MFA facilitates metabolic engineering efforts
(Libourel and Shachar-Hill, 2008; Schwender, 2008). The
resultant flux maps offer insights into the carbon conversion
processes of embryo metabolism and have been reported for
embryos of rapeseed (Schwender et al., 2003, 2006), sunflower (Alonso et al., 2007), and soybean (Sriram et al., 2004).
These studies have revealed higher carbon use efficiency in
green (Schwender et al., 2004a) than in non-green (Alonso
et al., 2007) embryos, and suggested that malate provides
little carbon for fatty acid biosynthesis (Sriram et al., 2004;
Schwender et al., 2006; Alonso et al., 2007). In some
instances these models, which are based upon carbon
balancing, have been partially validated by simplified energetic and redox considerations from the flux maps. However,
independent experimentally derived redox balances that
could add insight into the role of light were not performed.
The present study examines the impact of light on the
growth of soybean embryos and its role in their metabolism.
We have determined the light levels reaching embryos
under field conditions and report the detailed redox balance
and energetic analyses for growing plant embryos. Multiple
labeling experiments and direct flux measurements were
performed to give further insight into green embryo metab-
olism during seed filling, to develop and validate a flux map,
and to improve the identifiability of fluxes in different parts
of the network (Libourel et al., 2007). Our results show:
(i) that developing soybeans receive low but significant light
levels that strongly influence growth; (ii) a role for light
during seed filling in providing significant ATP but not net
reductant; (iii) that flux through Rubisco contributes to
carbon conversion efficiency (CCE) and makes a substantial
portion of the 3-phosphoglycerate (PGA) generated; and
(iv) a larger contribution of amino acid carbon to fatty acid
synthesis than in other oilseeds studied to date, coupled
with an increased supply of pyruvate from malic enzyme
relative to pyruvate kinase.
Results
Developing soybean embryos receive moderate
levels of light
The potential contribution of photosynthesis to embryo
metabolism depends on the amount of light transmitted to
the embryo. We estimated the amount of light with wavelengths between 400 and 700 nm that is incident on developing embryos by measuring light transmission through the
relevant plant tissues (Figure 1). Measurements in the field
after canopy closure and flowering but before seed maturation showed that shading by leaves reduces the light levels
by 80–94%, depending on the location of a fruit within the
canopy (data not shown). Of the light reaching the fruit,
approximately 30% is transmitted through the wall to the
seed coat and the seed coat transmits approximately 50% of
this to the embryo. At a latitude of 43º at noon in a typical
soybean field we calculated that the light received by most
embryos is in the range of 5–30 lE m)2 sec)1. Light is preferentially absorbed by plant tissues at higher and lower
wavelengths, so that the penetrating light is enriched in the
range 525–575 nm. Embryos used in subsequent experiments were at a post-mitotic stage where storage deposition
was close to linear (i.e. approximately 10–15 mg dry weight,
approximately 30–40 days after pollination in the R5–R5.5
reproductive stage of growth; Satterlee and Koller, 1984;
Egli, 1998). Such pods are generally located higher on the
plant relative to the canopy, resulting in higher light intensities. Therefore a 30–35 lE m)2 sec)1 light level was used
for most cultures, with others at 5 or 100 lE m)2 sec)1 for
comparison with a range of possible in planta conditions.
Substrate uptake, biomass production, and carbon
conversion efficiency
Light may contribute to embryo development by providing
reductant for the synthesis of reduced products and/or by
providing free energy for transport, polymerization, and
other endergonic processes in anabolism. To estimate the
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
222 Doug K. Allen et al.
Figure 1. Light transmittance to the embryo.
During the growing season, sunlight in soybean growing regions can average
1000 lE m)2 sec)1 for daylight hours and reach 2000 lE m)2 sec)1. Transmission spectra for a soybean leaf, pod, and seed coat suggest the embryo
may receive up to 39 lE m)2 sec)1 of light. Field measurements in central
Michigan suggest values closer to 5–30 lE m)2 sec)1 depending upon
planting density, pod location on the plant, and sunlight levels at the time
of measurement. Spectra represent an average of two measurements over
different areas of tissue; measurements on other parts of each tissue
consistently gave similar values.
extent to which light may be serving either of these needs
requires measurements of substrate uptake and product
synthesis. Such measurements are also needed to assess
whether seeds are developing normally in culture and
whether they are in metabolic steady state, which is a prerequisite for steady-state flux analysis. The predominant
carbon and nitrogen substrates available to developing soybean embryos in the apoplastic space have been reported to
be sucrose, glucose, glutamine, and asparagine (Hsu et al.,
1984; Rainbird et al., 1984; Gifford and Thorne, 1985; Egli and
Bruening, 2001). These were supplied in culture under conditions (see Experimental Procedures) that resulted in growth
rates of 4.9–7.8 mg dry weight day)1 per embryo (Table S1 in
Supporting Information). In planta growth rates are in the
range of 5–7 mg dry weight day)1 per embryo (Rubel et al.,
1972; Hsu and Obendorf, 1982; Egli et al., 1985). Triacylglycerol and protein levels in cultured embryos were measured to
be 18.4 1.1% and 38.4 1.9% of total biomass, respectively, which is very similar to those of embryos that developed in planta (19.2 3.3% and 40.4 1.2%, respectively;
Table S1a, Figure S1a,b). Embryos cultured for 8, 11, or
14 days gave similar oil, protein, and biomass accumulation
rates, reflecting metabolic steady state and consistent with
previously reported time profile reports for growth in planta
(Rubel et al., 1972; Privett et al., 1973; Dahmer et al., 1991)
and our unpublished results.
The amino acid composition of total protein and the fatty
acid profile of storage triacylglycerol (TAG) were determined using gas chromatography (oil) and a combination
of C and N elemental analysis and amino acid analysis
(protein) of embryo tissue. The amino acid and fatty acid
profiles from cultured embryos were very similar to those
from embryos that developed in planta (Figure S1a,b).
Measurements of embryo composition and dry weight
(see Experimental Procedures) were used to determine
fluxes into biomass (Figure 2). Uptake fluxes were established by measuring the depletion of substrates from the
medium (see Experimental Procedures). The uptake of
glutamine accounts for 81 1.8% of all nitrogen utilized
by the embryo, with asparagine providing the remainder.
Sucrose and glucose provide 52 6.0% and 26 2.9%,
respectively, of the organic carbon taken up (Figure 2).
The rate of CO2 production was determined to be
70.4 5.0 lmol day)1 per embryo by measuring the 14CO2
emitted by embryos cultured in the presence of substrates
that were uniformly labeled with 14C. Infrared gas analysis
(IRGA) measurements were also consistent with this value
(data not shown). Comparing substrate uptake with biomass
and CO2 production yields estimates of carbon use efficiency
of 82–83% (see Experimental Procedures), which compares
with 85–95%, and 50% for developing embryos of oilseed
rape (Brassica napus) and sunflower (Helianthus anuus),
respectively, at physiological conditions (Goffman et al.,
2005; Alonso et al., 2007).
Biosynthesis of storage compounds requires light-driven
ATP synthesis
The oxidation state of carbon in substrates and products was
compared using standard chemical redox state assignments
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 223
Measurement
method
Flux description
Carbon dioxide
production
Oxygen
Paramagnetic/GCMS
consumption
Plastidic acetyl
GC-FID
CoA for oil
14C
Balance
study
Glucose uptake
Sucrose uptake
Glutamine uptake
Asparagine uptake
NMR medium
depletion
7.0
6.5
6.0
5.5
Flux measured
Amino (μmol day–1 embryo–1)
acid
Culture In Planta*
(μmol day–1 Measurement
method
embryo–1)
70.4 ± 5.0
28.5 ± 14.0
35.2 ± 2.7
16.9 ± 3.0
17.0 ± 1.3
14.3 ± 1.0
3.4 ± 0.6
5.0
4.5
C:N & amino
acid analysis
proteinaceous
amino acids*
4.0
His
Ile
Leu
Lys
Met
Phe
Pro
Ser
Thr
Tyr
Val
Ala
Arg
Asp/Asn
Cys
Glu/Gln
Gly
3.5
3.0
0.52 ± 0.03
1.03 ± 0.06
1.81 ± 0.12
1.40 ± 0.06
0.18 ± 0.03
0.92 ± 0.06
1.36 ± 0.11
1.27 ± 0.07
0.93 ± 0.03
0.39 ± 0.09
1.33 ± 0.06
1.57 ± 0.06
1.49 ± 0.28
2.70 ± 0.11
0.11 ± 0.04
3.59 ± 0.26
1.72 ± 0.08
2.5
0.43 ± 0.05
1.03 ± 0.05
1.67 ± 0.10
1.19 ± 0.01
0.23 ± 0.02
0.84 ± 0.07
1.21 ± 0.07
1.73 ± 0.09
1.11 ± 0.03
0.62 ± 0.10
1.14 ± 0.15
1.74 ± 0.33
1.34 ± 0.03
2.79 ± 0.26
0.26 ± 0.01
3.90 ± 0.17
1.82 ± 0.03
ppm
Figure 2. Biosynthetic flux measurements.
The tables list values of uptake, export, and storage deposition rates. Biosynthetic fluxes to biomass, uptake fluxes, and gas fluxes were measured as described in
the Experimental Procedures and text. Figures S1(a) and (b) (protein derived amino acids and triacylglycerol-based fatty acids) show further comparisons with
biomass composition in planta. Data for each of the glucose and glutamine labeling experiments (three replicates each) were modeled separately. Depletion of
substrates from the medium was measured by NMR to determine uptake fluxes for carbon and nitrogen substrates and their standard deviations (n = 3). Gallic acid
served as an internal standard. The spectrum shown is a representative 1H 500-MHz NMR spectrum of spent media. *In planta fluxes were calculated using reported
amino acid compositions (Yazdi-Samadi et al., 1977) of growing embryos with standard deviations established from that study.
(Supplement S2). The average oxidation state of carbon in
the substrates is: glucose (0), sucrose (0), glutamine (+0.4),
and asparagine (+1). From the measured uptake rates, sugars, glutamine, and asparagine represent 79%, 17%, and 4%,
respectively, of carbon uptake. Therefore carbon taken up
has an average oxidation state of +0.11. Based on the measured embryo composition, the average oxidation state for
carbon was found to be )0.06 in protein amino acids, )1.55
in oil, and 0 for cell wall carbohydrates and starch. Therefore,
for a soybean with a biomass composed of 39% protein, 18%
oil, and 43% carbohydrate by weight (data from embryos
from 13C experiments) and which converts 18% of the carbon
taken up into CO2, the average oxidation state of carbon in
products is +0.37. Since the carbon in metabolic products is
on average more oxidized than in the substrates, there is
no formal requirement for reductant produced by lightdriven oxidation of water. Indeed the difference implies the
withdrawal of electrons, which is quantitatively consistent
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
224 Doug K. Allen et al.
consumption (Stephanopoulos et al., 1998). Thus metabolism of exogenous substrates cannot alone supply the ATP
requirements of developing soybean embryos, implying a
significant role for light in their ATP economy.
with the observation that embryos cultured under these
conditions consumed oxygen (measured to be 28.5 14
lmol day)1 per embryo (mean SD, n = 5) using gas chromatography-mass spectrometry (GC-MS) and confirmed
with a paramagnetic response analyzer with independent
culturing experiments (see Experimental Procedures).
We next estimated the demands of biosynthesis for ATP
assuming published stoichiometries for polymerization of
storage products and cell walls (Supplement S3) as being
approximately 168 lmol of ATP equivalents per day per
embryo. Assuming that oxygen not used for fatty acid
desaturation events is consumed to produce ATP via oxidative phosphorylation, and assuming a maximum feasible
rate of substrate-level phosphorylation, we estimate the
maximum ATP production from catabolism of sugars to be
171–178 lmol ATP day)1 per embryo (Supplement S3).
A more realistic estimate of metabolic ATP production is
obtained using the metabolic flux map determined for this
system which shows a deficit of ATP production compared
with the demands of biosynthesis (see below). In addition,
ATP is used in the uptake of substrates, futile cycling,
maintenance of cellular gradients, transport of metabolites
across organelle membranes, turnover of proteins, and the
synthesis and turnover of RNAs. These additional maintenance processes can account for over half of the cellular ATP
P5P
30
PGA
20
Ser
10
Acetyl
CoA
High
Plastid
Serine
Aromatics
(d)
Threonine
0.8
0.18
0.6
0.12
0.4
0.06
0.2
0
Cytosol
0
Low Med High Low Med High
Low
Med High
PGA
Rubisco CO
2
Ser
CO2
Scaled specifc activity
Med
Calvin
Cycle
Rubisco CO
2
PYR
0
0.24
S7P/E4P
Calvin
Cycle
40
(b)
P5P
S7P/E4P
50
Low
Scaled specifc activity
The influence of light on seed metabolism was investigated
by comparing growth and 14CO2 assimilation by embryos at
low (5 lE), medium (30–35 lE), or high (100 lE) light
levels. Moderate light levels significantly enhanced growth
rates in culture compared with low light levels (Figure 3a)
consistent with documented light–biomass correlations for
soybeans (Satterlee and Koller, 1984). Biomass accumulation did not increase further in high light, suggesting
that embryos may be optimized for biomass production
at moderate light levels, consistent with the estimated
in planta light intensities (Figure 1).
Radioactivity levels in different metabolites were measured after 5 days of labeling with 14CO2 (see Experimental
Procedures). Labeling levels were normalized to the specific
activity of intracellular bicarbonate, which was estimated
from the activity in the terminal carbon of arginine that is
synthesized directly from this pool. This internal reference
allows an analysis of the effect of light on the activities of
(c)
Total biomass made
during culture (mg)
(a)
Light stimulates growth and carbon dioxide fixation
0.12
CO2
PYR
Acetyl
CoA
Acetyl carbon groups
0.08
0.04
0
Low
Med
High
Figure 3. The effect of light on growth and the incorporation of 14CO2 into embryo metabolites.
Light levels used were: low (5 lE m)2 sec)1), medium/physiological (30–35 lE m)2 sec)1), and high (100 lE m)2 sec)1) with values plus standard deviations
reported for triplicate samples.
(a) Impact of light on biomass accumulation for embryos in culture.
(b) The molar specific activity of 14C in amino acids made from 3-phosphoglycerate (PGA) (serine), phosphoenol pyruvate (PEP) (aromatics), and oxaloacetate (OAA)
(threonine) scaled to the specific activity of internal inorganic carbon.
(c) Illustration of 14CO2 incorporation by Rubisco (resulting in labeling of serine) and Calvin cycle activity (resulting in labeling in fatty acids). C-1 of serine is derived
from C-1 of PGA which is where label from 14CO2 is incorporated, but label only reaches fatty acids (acetyl-CoA) after scrambling of the label via the aldolase and
ketolase activities of the Calvin cycle or non-oxidative reactions of the pentose phosphate pathway.
(d) The specific activity of 14C in fatty acids per acetyl group.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 225
activity. However, this interpretation is not supported by the
[U-13C5]-glutamine experiment described below.
different metabolic steps that incorporate inorganic carbon.
Label in serine directly reflects labeling in plastidic PGA,
from which it is made under non-photorespiratory conditions (Goffman et al., 2004). Therefore the specific radioactivity of serine reflects Rubisco-based carbon fixation
(Figure 3b). Labeling in aromatic amino acids that are made
from phosphoenol pyruvate (PEP) and erythrose-4P in the
plastid, provide a further indication of CO2 incorporation via
Rubisco (Figure 3b).
Labeling in oxaloacetate-derived metabolites such as
threonine and related amino acids can result from Rubisco-based fixation (if triose leaves the plastid) and/or from
carboxylation of PEP. Labeling in threonine was found to be
higher than in PGA-derived intermediates (Figure 3b) but
was much less influenced by light level than labeling in
plastidic metabolites.
Rubisco activity results in incorporation of label from
14
CO2 into the first carbon position of PGA whereas label
reaches the other positions of PGA after scrambling (Figure 3c). Fatty acids are derived only from the second and
third positions of PGA, so that labeling in fatty acids
(Figure 3d) reflects scrambling events and is consistent with
Calvin cycle activity. For the two higher light conditions
there is a much greater degree of labeling in fatty acids,
consistent with increased Calvin cycle activity at higher light
levels. An alternative interpretation is that labeling was due
to a combination of fixation by PEP carboxylase (PEPC),
import into the mitochondria, scrambling via fumarase,
export to the cytosol, decarboxylation (PEPC kinase), import
into the plastid, and pentose phosphate pathway (PPP)
Contribution of amino acid uptake to biomass production
To more fully resolve the patterns of metabolic flux in soybean we performed 13C labeling experiments in which the
glutamine in the growth medium was replaced with 100%
[U-13C5]-glutamine (Figure 4). The labeling in proteins, lipids, carbohydrates, and organic acids was analyzed by a
combination of NMR and GC-MS. Malate was labeled on
average to over 41% per carbon under these conditions, and
labeling in threonine was similarly high. Both pools contained a substantial proportion of fully labeled molecules
(isotopomers). This shows a high degree of labeling in C4
acid pools (malate and OAA). Thus the [U-13C5]-glutamine
experiment allows us to test whether there is a significant
flux from C4 acids into plastidic PGA, as required if scrambling via the PPP is to explain the labeling from 14CO2 into
plastid-derived pools of PGA, PEP, or pyruvate (resulting in
labeling of serine, fatty acids, and aromatic amino acids).
There was no significant presence of multiply labeled molecules in these metabolite pools when embryos were
labeled with [U-13C5]-glutamine, supporting the idea that
Rubisco and the Calvin cycle rather than gluconeogenesis and PPP are responsible for the results of the 14CO2
experiment.
Forty-one per cent of the total carbon from glutamine is
converted into glutamate-derived amino acids in protein,
26% to carbon dioxide, and 14% to pyruvate-derived
Fatty
Acid
Ala
Val
Leu Acetate
9.4% ± 1.4 9.5% ± 2.2 9.2% ± 4.6 9.7% ± 0.1
<1%
Hexose/
Triose-derived
1% ± 0.2%
CO2
26% ± 1.4%
Pyruvate
Pyruvatederived
14% ± 0.3%
CO2
Thr
47.7% ± 0.6
Aspartatederived
11% ± 0.2%
Lysine/
Isoleucine
7% ± 0.3%
Glutamatederived
41% ± 0.9%
CO2
Acetate
30.0% ± 0.1
Gly
5.5% ± 0.5
Asn
Ala, Val, Leu, Fatty Acids
CO2
Citrate
100%
Isocitrate
Malate
36.5% ± 2.2
40.4% ± 2.2
Malate
Gln
CO2
2-oxoglutarate
C1
Glu
0%
Met
36.8/44.3% ± 0.6/0.6*
Succinate
CO2
57.3% ± 4.8
Pro,
Arg,
Glx
76.8% ± 1.3 71.4% ± 0.3/ 81.4% ± 0.5
80.5% ±0.3*
Figure 4. The distribution of label in different metabolic pools from cultures supplied with [U-13C5]-glutamine. Values are mean standard deviation (n ‡ 3).
(a) Distribution of 13C from [U-13C5]-glutamine into different product pools.
(b) Carbon transitions through the citrate cycle and into lipid. Each pie chart shows the average 13C enrichment in each metabolite. *For methionine and arginine the
first number is based upon the average labeling in all carbons, while the second number discounts the carbon associated with CO2 or C1 metabolism respectively.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
226 Doug K. Allen et al.
(Figure 5). Metabolic flux analysis requires that the system
be in metabolic steady state (as shown above) and also in
isotopic steady state (constant pattern of label distribution;
Szyperski, 1998). We compared labeling patterns in storage
proteins with those of free amino acids and found them to be
very similar (Table S1b), which indicates that isotopic steady
state had been reached during the 14 days of labeling
in culture.
Next we compared the ability of alternative models of
central metabolism that are compatible with the literature to
account for the biomass fluxes, 13C labeling data, and gas
exchange measurements (Supplements S1 and S4). Labeling in plastidic (starch) and cytosolic (cell wall and proteoglycan) carbohydrate pools was found to be very similar
(Figure S1d) and did not allow accurate resolution of glycolytic and nearby fluxes in these two compartments. The
metabolic flux map representing the best estimate of
forward and reverse fluxes is presented in Figure 5 and
Table 1. Cofactor and overall nitrogen balances, not part of
the modeling, were used to validate the results. Modeled
fluxes for glutamine and asparagine uptake represent a
nitrogen source and were compared with the modeled
fluxes for protein amino acid generation. Protein synthesis
fluxes account for 91% of all nitrogen consumed, consistent
with protein being the primary nitrogen sink in soybean
storage metabolism. Secondly, nitrogen measured by
combined amino acid/C:N analysis represents 89% of the
N uptake (NMR depletion), thus independently confirming
metabolites (Figure 4a). Aspartate-derived amino acids
become moderately labeled but represent small fluxes that
require relatively little (11%) of the carbon taken up as
glutamine. Nearly 10% of the carbon in fatty acids is labeled,
indicating a significant flow from malate into pyruvate,
which serves as the precursor to fatty acid synthesis
(Figure 4b). Since malate becomes labeled to over 40%, a
10% labeling in fatty acids implies that approximately a
quarter of fatty acid carbon is derived from this pool, and if it
is made through plastidic malic enzyme it could potentially
be a significant source of plastidic NADPH.
The hexose-derived products (starch and cell wall) show
little or no detectable labeling, indicating a lack of gluconeogenic activity in expanding soybean embryos in the light.
The lack of multiple labeling in glycerol, histidine, aromatic
amino acids, and serine from [U-13C5]-glutamine (Table S1c,
Figure S1c, d) support the same conclusion.
Metabolic flux analysis
The findings described above point to roles for light and
Rubisco in biomass production by developing soybean
seeds. To quantify these roles we performed steady-state
metabolic flux analysis (Zupke and Stephanopoulos, 1994;
Schmidt et al., 1997; Wiechert et al., 2001; Ratcliffe and
Shachar-Hill, 2006) using the uptake, efflux, and 13C labeling
data already described together with additional data
from steady-state [U-13C6]-glucose labeling experiments
Sugars
44.4
± 1.8
15.3
CO2
72.4
± 1.7
Cell Wall
Starch
± 3.5
HP
25.7
± 1.8
C1, CO2
± <0.1
Gly, Ser, Cys
2.1
2.1
± 0.1
± 0.2
X5P
R5P
± 0.1
± 0.5
CO2
1.3
± 1.1
± 0.1
Phe, Tyr
7.8
44.2
±0.4
± 1.5
CO2
Ala, Val, Leu
CO2
Pyruvate
CO2
Lysine
+ CO2
2.1
10.7
± 1.2
Fatty Acids
37.0
CO2
Citrate
7.7
± 0.5
1.4
± 0.1
± 1.9
Fatty Acid Elongation
7.5
± 0.5
7.5
±0.5
Malate
2.6
±0.4
Asx
1.2
± 0.3
Glutamine
Isocitrate
± 0.1
Asparagine
His
C1
7.0
PEP
6.0
Threonine
± <0.1
2.1
PGA
CO2
± <0.1
0.5
Ru5P
± 0.1
± 2.7
1.0
± ~0
3.4
S7P
52.7
Isoleucine
0.1
X5P
E4P
± 2.6
3.9
± 0.1
Fatty Acid
Elongation
T3P
42.6
1.0
5.5
± 0.4
± 0.1
Glycerol
T3P
T3P
1.3
2-oxoglutarate
C1
0.2
± <0.1
Methionine
±0.7
± 0.7
Succinate
± 0.5
6.9
± 0.2
14.4
14.4
13.2
CO2
Glutamate
6.3
± 0.4
CO2
Pro, Arg, Glx
Figure 5. Metabolic flux map of developing soybean embryos as determined from least squares fitting with 755 measurements of uptake, export, and product
deposition rates and 13C labeling results (see Experimental Procedures).
Values represent the optimum values 90% confidence intervals. All fluxes are reported as lmol metabolite per day per embryo. Reversible fluxes are listed in
Table 1.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 227
Table 1 Forward and backward fluxes for reversible fluxes through
metabolism of developing soybean embryos
Flux values (lmol metabolite
day)1 per embryo)
Flux or rate
description
Aldolase
Transketolase one
Transaldolase
Transketolase two
Glyceraldehyde-3-P to
3-phosphoglycerate
Enolase
PEP to OAA
Isocitrate dehydrogenase
Glutamine to glutamate
Glutamate to 2-oxoglutarate
Fumarase
Forward
Reverse
67.5
26.6
26.6
24.7
70.1
41.8
24.5
24.5
21.4
27.6
52.7
6.6
14.3
12.8
43.8
33.9
0.0
0.6
6.8
0.5
36.9
19.5
PEP, phosphoenolpyruvate; OAA, oxaloacetate.
experimental and modeling results. A separate validation
using the oxygen measurements is described in
Supplement S2.
The flux map allows one to quantify the maximum
metabolic ATP production rate by assuming that all
NAD(P)H and FADH produced is consumed via oxidative
phosphorylation to make ATP at stoichiometries of 2.3–2.5
and 1.4–1.5 ATP per NAD(P)H and FADH, respectively
(Hinkle, 2005). This yields a synthesis rate of 124–136 lmol
ATP day)1 per embryo, a deficit of 27–39 lmol day)1 per
embryo compared with biosynthetic needs, confirming that
light is needed for ATP production. A light level of
30 lE m)2 sec)1 can provide approximately 125–195 lmol
ATP day)1 per embryo, assuming stoichiometries estimated
in the literature for photosynthetic ATP synthesis of 1 ATP
per 3.0–4.7 protons (Arnon, 1984; Steigmiller et al., 2008;
Zhu et al., 2008).
Metabolic flux analysis also supports a role for Rubisco in
the metabolism of soybean embryos, as was indicated by
14
CO2 and 13C labeling data. Models that include Rubisco are
better able to account for the 14C labeling, and CO2 efflux
data (Supplement file S4) than those in which the oxidative
pentose phosphate pathway is a major flux. However, at the
moderate light levels received by developing soybeans in
the field, the role of Rubisco is more modest than in B. napus
embryos. The flux map in Figure 5 estimates that Rubisco
assimilates 11% of the CO2 released by the tricarboxylic acid
(TCA) cycle and in fatty acid synthesis, compared with 39%
in B. napus. Reassimilated CO2 therefore contributes to
carbon use efficiency in the embryo.
The flux map shows that mitochondrial metabolism
operates in a conventional mode, with the TCA cycle
consuming 17% of the carbon taken up in the form of sugars
and amino acids, and accounting for 41% of the net CO2
production. This contrasts with developing B. napus
embryos where there is no significant TCA cycle flux
(Schwender et al., 2006) and with sunflower where the
TCA cycle consumes 40% of the substrates and accounts for
71% of the CO2 production. The low proportion of fatty acids
with chain lengths above 18 in soybean oil means that much
less citrate is withdrawn from the mitochondrion to provide
acetyl-CoA units in the cytosol relative to Brassica. Despite
the net forward cyclic flux through the TCA cycle enzymes,
the flux map indicates a high degree of reversibility between
oxaloacetate and fumarate. The C4 dicarboxylic acids are
therefore treated as a single pool (Schwender et al., 2006;
Junker et al., 2007). Labeling with [U-13C5]-glutamine results
in a significant degree of penta-labeled (M + 5) citrate, which
indicates that isocitrate dehydrogenase, conventionally
regarded as catalyzing an irreversible decarboxylation, is
operating reversibly (Figure 6). The MFA analysis confirmed
this conclusion and yields a ratio of approximately 2:1 for
forward to reverse flux. Schwender et al. (2006) also
observed reversible flow through isocitrate dehydrogenase
in developing B. napus embryos, though the result was
even more pronounced with net flux in the direction of
carboxylation.
Metabolic flux analysis also provides evidence for a
significant contribution to threonine turnover and glycine
synthesis by threonine aldolase. This conclusion rests on a
comparison of labeling in glycine on the one hand and
serine and threonine on the other in the [U-13C5]-glutamine
labeling experiment. Under non-photorespiratory conditions, such as those in developing soybean embryos (Goffman et al., 2004), glycine is made from serine via serine
hydroxymethyl transferase or from threonine via threonine
aldolase (Jander et al., 2004). Flux analysis indicates that 6%
of threonine made from aspartate is broken down via
threonine aldolase, contributing 5% of glycine synthesis.
Discussion
Soybean embryos receive light for growth and metabolism
Soybean embryos in agricultural fields are shaded from
direct sunlight but nevertheless receive physiologically
significant amounts of light. Our results indicate that most
embryos receive 5–30 lE m)2 sec)1 during the day in a
temperate climate (Figure 1) and that these amounts of light
increase their growth (Figure 3a) and have significant
impacts on their metabolism including an increase in the
incorporation of carbon derived from CO2 fixation into oil
and other biomass components (Figure 3b, d). The percentage transmittance of light through soybean siliques is
similar to that in a previous report for B. napus (Ruuska
et al., 2004), although rapeseed embryos are more exposed
to sunlight in planta because their pods are located above
the leaf canopy. Indeed the shading of soybean embryos in
agricultural settings may not be typical of the environment
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
228 Doug K. Allen et al.
0.5
Measured
Calculated without reversibility
Modeled with reversibility
0.4
0.3
1
4 3 2 2 1
0.2
+
1
0.1
[M+6]+
[M+5]+
[M+4]+
[M+3]+
Citrate
[M+2]+
1 2 3 4 5
0
[M+1]+
AcCoA
[M]+
[M+2]+
[M+1]+
1 2
[M]+
0.9
0.6
0.3
0
0.8
2-oxoglutarate
[M+1]+
Glutamate
(Proline)
[M+5]
+
1 2 3 4 5
[M+4]+
CO2
0.8
0.6
0.4
0.2
0
0
[M+3]+
[M+4]+
[M+3]+
[M+2]+
[M+1]+
0
[M]+
0.2
0.4
[M+2]+
0.4
[M]+
CO2
1
[M+1]+
Malate
1 2 3 4
[M]+
0.6
Figure 6. Labeling in tricarboxylic acid (TCA) cycle intermediates after culturing with [U-13C]-glutamine. Values are mean SD (n ‡ 3).
Simplified TCA cycle with histograms representing the distribution of mass isomers measured for each intermediate. Labeling in citrate usually reflects that of
malate and acetyl-CoA precursors. However, the labeling pattern in citrate was found to have a high number of molecules with five 13C atoms ([M + 5]+ peak) which
implies that isocitrate dehydrogenase is operating reversibly.
in which ancestral strains evolved; ancestral soybean
(Glycine soja) has a vine-like morphology (Saitoh et al.,
2004a, b).
The observation that the light levels reaching embryos
enhance growth suggests possible opportunities for
enhanced yield through selection of plants with more
exposed seeds. Yield is a reflection of duration of seed
growth and seed growth rate (Egli, 1998) and these are
affected by the daylight characteristics (geographical location) as well as leaf canopy, pod wall, and seed coat
transmittances. Though the seed filling time frame of our
cultures represents only a portion of the total filling period,
silique and seed coat chlorophyll contents (Quebedeaux and
Chollet, 1975) and transmittances (Furbank et al., 2004) can
change during the entire span of reproductive development
in legumes and could represent logical starting points for
increasing yield.
Photosynthesis produces ATP for biomass accumulation
Soybeans require large amounts of ATP for protein and oil
biosynthesis and are dependent upon light to partially fulfill
this demand. Based upon the measured fluxes to biomass
we estimated the ATP requirement for storage protein
polymerization and storage triacylglycerol fatty acid elongation processes. The uptake fluxes of sugars that are not
used in generation of storage carbohydrate can be used to
calculate a maximal rate of substrate level phosphorylation;
the oxygen consumption not required for desaturation
of fatty acids gives a maximal estimate of oxidative
phosphorylation (Supplement file S3). This analysis
suggests, and flux mapping (Figure 5) confirms, that
soybean embryos produce insufficient ATP from oxidative
and substrate-level phosphorylation for their anabolic and
other physiological needs. The light levels reaching developing soybean embryos in planta are sufficient to meet this
need (Supplement file S3). For oilseed rape embryos, metabolic flux analysis has demonstrated a role for light in
providing ATP and reductant for fatty acid synthesis
(Schwender et al., 2006). In developing sunflower seeds,
which lack photosynthetic pigments, catabolism provides
these cofactors (Alonso et al., 2007).
Our analysis of the oxidation state of substrates taken up
and products formed shows that metabolism provides
enough reductant for biosynthesis. This suggests that cyclic
photophosphorylation, which does not produce reductant or
O2 (Allen, 2003), is used more than non-cyclic photophosphorylation. Cyclic photophosphorylation produces ATP
which is consistent with the evidence presented for a role
for light in ATP production. Non-cyclic photophosphorylation would produce more NADPH than the redox balance
analysis shows is needed. It would also produce more O2
than indicated by the gas exchange measurements. The
respiratory O2 consumption predicted by the flux map
agrees with the net O2 consumed (Supplement S2). However, non-cyclic photophosphorylation cannot be excluded
from our results, since excess NADPH produced by this
process in the chloroplast could be used to reduce NAD to
NADH which could be consumed by mitochondrial
respiration together with the excess O2. Cyclic photophos-
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 229
phorylation has previously been suggested to occur in
legumes (Willms et al., 1999; Furbank et al., 2004), and
shown to be significant in the bundle sheath chloroplasts of
C4 plants (Shikanai, 2007).
We found that seeds exposed to higher light levels
produced biomass with a lower net oxygen consumption
per tissue weight (data not shown). Thus non-cyclic
photophosphorylation may be more important at higher
light levels. This would be consistent with the suggestion
that photosynthesis in soybeans does produce oxygen
(Rolletschek et al., 2005b). That suggestion was made on
the basis of measurements of O2 levels in soybeans
exposed to higher light levels than those used in this
study. Experiments using 18O and/or fluorescence spectroscopy would be of interest to establish the contributions
of cyclic and non-cyclic photosynthesis to filling seeds and
biomass accumulation at different light levels.
We have included reversible pentose phosphate reactions with carboxylation by Rubisco in the representation
of seed metabolism in soybeans because this model was
best able to account for the CO2 flux measurement as well
as labeling information (see Supplement S4). In green
tissues, Calvin cycle and oxidative pentose phosphate
pathway (OPPP) activities are reciprocally regulated at
several biochemical levels, including the light-induced pH
change of stroma and thylakoid compartments (Werdan
et al., 1975) as well as the reduction state of thioredoxin
which modulates glucose-6-phosphate dehydrogenase
(G6PDH), Rubisco, and PPP/Calvin cycle enzyme activities
(reviewed in Buchanan, 1980). Ruuska et al. (2004) showed
that in developing soybeans growing in planta in the light,
the activation state of plastidic enzymes is comparable to
illuminated leaves, which is consistent with this aspect of
our model.
Rubisco contributes to the carbon economy of developing
soybeans
Fatty acids are partially made from carbon imported
as amino acids
The combination of CO2 efflux measurement, flux mapping
(Figure 5), and 14CO2 labeling patterns (Figure 3) supports a
role for Rubisco-based carbon reassimilation. In particular,
labeling in fatty acids from 14CO2 suggested a role for
Rubisco and other Calvin cycle enzymes, especially at elevated light levels, but could also have been due to an indirect
route involving the sequential action of PEPC, import to
mitochondrion, reversible flux to fumarate and back
(resulting in label scrambling), export to cytosol, and
decarboxylation to PEP and thence to PGA. However, the
results of the steady-state 13C glutamine labeling experiments were not consistent with the idea that this indirect
route accounts for the results of the 14CO2 experiment.
Alternative flux models with an oxidative pentose phosphate pathway can account for the 13C labeling data but do
not account for the CO2 efflux rates recorded.
The flux mapping results (Figure 5 and Table 1) indicate
that at 30–35 lE m)2 sec)1 Rubisco in soybean embryos
refixes 11% of the CO2 released by lipid synthesis and the
TCA cycle. At 100 lE m)2 sec)1 the contribution of Rubisco
to soybean metabolism appears to be substantially higher
(Figure 3). Such light levels would meet or exceed those
typically experienced by embryos developing near the top of
the plant (with little leaf cover). Rubisco was shown to be
present and activated in soybean embryos (Sugimoto et al.,
1987; Ruuska et al., 2004) but it has not been included in a
previous metabolic flux model of developing soybeans
(Sriram et al., 2004; Iyer et al., 2008). In B. napus embryos,
which are exposed above the leaf canopy, Rubisco refixes
39% of CO2 released by oil synthesis (Schwender et al.,
2004a). This increases the carbon conversion efficiency
(Goffman et al., 2005), making it much higher than in nongreen oilseeds such as sunflower (Alonso et al., 2007).
Flux measurements and 13C labeling results, particularly
those where [U-13C5]-glutamine was supplied, show that
close to 20% of all stored carbon, including 10% of fatty
acid carbon, is imported as glutamine (Figure 4). When
incorporated into flux modeling analysis, these data indicate that the import of malate and/or pyruvate made from
malate into the plastid plays a greater role in oil biosynthesis in soybeans than in rapeseed or sunflower, (Schwender et al., 2004b, 2006; Alonso et al., 2007). Our work
suggests that in soybeans 20% of total pyruvate is made
by malic enzyme. For plants that are capable of providing
their seeds with large amounts of amino acids (i.e.
reduced carbon and nitrogen), such as legumes, amino
acid carbon may play a larger role in the final storage
carbon distribution. Furthermore, nitrogen-fixing plants
may partially offset demands from the embryo for reductant by delivery of these reduced forms of nitrogen and
through their subsequent metabolism in the embryo by
malic enzyme.
The TCA cycle reactions carry fluxes intermediate between
other green and non-green seeds
Flux mapping indicates that flux around the TCA cycle in the
mitochondria of soybean embryos fuels oxidative phosphorylation and yields enough ATP to meet 77–83% of the
ATP demands of biosynthetic metabolism (Supplement S3).
In rapeseed, by contrast, there is no net flux round the TCA
cycle and oxidative phosphorylation accounts for less than
22% of ATP needed for biosynthesis (Schwender et al.,
2006). In sunflower embryos the TCA cycle carries a large
cyclic flux, with the flux through citrate synthase being 85%
of glucose uptake and mitochondrial respiration accounting
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
230 Doug K. Allen et al.
for over 100% of biosynthetic ATP demand (Alonso et al.,
2007). Thus the importance of the TCA cycle in providing
ATP in different oilseeds is inversely related to the availability of, and the capacity to harness, light.
Soybean embryos exhibit a significant exchange flux
through isocitrate dehydrogenase, which is conventionally
thought to be an irreversible step. This reversibility has been
observed in developing rapeseed embryos (Schwender
et al., 2006) where a large demand for acetyl groups
involved in fatty acid elongation in the cytosol result in a
substantial flux of citrate out of the mitochondrion and a net
flux from alpha ketoglutarate to citrate. This is not the case in
soybean embryos, and the net flux through isocitrate
dehydrogenase is in the direction of decarboxylation
(Figure 6 and Table 1).
Additional technical considerations on the metabolic flux
analysis and the potential limitations that arise in its
application to this system are given in Supplements S5
and S6.
Experimental procedures
Chemicals
[U-13C6]-glucose, [U-13C5]-glutamine, as well as [U-14C4]-asparagine
(208 mCi mmol)1) radioisotope were purchased from Sigma (http://
www.sigmaaldrich.com/) and [U-14C12]-sucrose (495 mCi mmol)1),
[U-14C6]-glucose
(245 mCi mmol)1),
[U-14C5]-glutamine
(219 mCi mmol)1)
from
Amersham
Biosciences
(http://
www5.amershambiosciences.com/).
using gas chromatography-flame ionization detection (GC-FID), GCMS, and NMR as previously described (Allen et al., 2007; and Supplement S7). Briefly, oil was quantified as FAMEs using GC-FID,
proteinaceous amino acid levels were determined using a combination of C:N analysis and HPLC-based amino acid analysis, with the
remaining biomass dry weight was presumed to be carbohydrates.
Depletion of carbon and nitrogen sources from the medium was
determined using NMR to compare the medium before and after
culturing using gallic acid as an internal standard (for more details
see Supplement S7 and Allen et al., 2007). Production of CO2 was
measured by trapping and counting 14CO2 produced during a 5-day
experiment in which all organic substrates were labeled to the same
specific activity, as described previously (Goffman et al., 2005).
Analysis of labeling
14
C levels were analyzed by scintillation counting following the
isolation of metabolic products. Protein amino acids were hydrolyzed from biomass under vacuum at 110C in the presence of 6N
HCl, extracted in 20 mM HCl and run with standards on HPLC
(Supplement S7). For 13C labeling protein amino acids and organic
acids were converted to their tert-butyl-dimethylsilyl derivatives
and analyzed with GC-MS as were butylamide derivatives of fatty
acids from triacylglycerol (Allen et al., 2007). Starch and cell walls
were hydrolyzed using amylase/amuloglucosidase or trifluoroacetic
acid (TFA), respectively to monosaccharides that were peracetylated before GC-MS, or converted to the monoacetone glucose
derivative and evaluated via NMR as described in Allen et al. (2007).
Gas exchange measurements
Greenhouse cultivation and embryo culturing of soybeans with
labeled organic substrates has been previously described (Allen
et al., 2007; see Supplement S7) . For 14CO2 labeling experiments,
unlabeled culture medium was prepared and 14CO2 was released by
addition of HCl to a vial of NaH14CO3 in the flask. Flasks were sealed
with air-tight closures containing septa. Harvested embryos were
rinsed, dried and stored at )20C until analysis.
Cultures were grown in 7.5 ml of medium in 120-ml serum bottles
resting on their sides. Five cultures were incubated in each of four
light conditions (0, 5, 30, and 100 lmol m)2 s)1. Embryos were
grown for 3 days in unsealed bottles, after which the medium was
replaced and bottles were sealed. Oxygen levels in headspace
samples were measured after 3 or 5 days using GC-MS. The mass
spectrometer (Agilent MSD 5975, http://www.agilent.com/) was
sensitively tuned for low molecular weight measurement using
water, oxygen, and argon in air by adjusting repeller and electron
voltages and the atomic mass unit gain and offset. Argon was used
as an internal standard to adjust for small system leaks, temperature, pressure, and loading differences.
Oxygen consumption was confirmed independently using a
paramagnetic oxygen analyzer. From the flask cultures, 0.1 ml of
the headspace gas was withdrawn and analyzed for oxygen and CO2
using, respectively, a paramagnetic O2 detector (Series 1100,
Servomex Co., http://www.servomex.com/) and an infrared CO2
detector (ADC 255-MK3, Analytical Development Co.) connected in
series with N2 as a carrier gas with a flow rate of 100 ml min)1
(Lakakul et al., 1999). The oxygen and CO2 concentrations were
calculated relative to a certified gas standard (Matheson Gas
Products, http://www.matheson-trigas.com/) containing 0.979 lLL)1
ethylene, 4.85% CO2, and 1.95% O2 balanced with N2 as previously
described (Mir et al., 2001). Carbon dioxide measurements by IRGA
were used to verify the 14CO2 trapping measurements described
above.
Substrate uptake and product formation rates
Flux modeling
Oil, alcohol soluble extracts, protein, and starch were extracted
successively from cultured embryos and prepared and analyzed
Direct flux measurements of substrate uptake and biomass and CO2
production rates and labeling data from separate [U-13C6]-glucose
Light levels and transmission
Sunlight and the effect of the leaf canopy were measured using
a quantum meter (QMSS, Apogee Instruments, http://www.
apogee-inst.com/) at midday during the soybean growing season
with plants at the R5–R5.5 reproductive stage of development
near East Lansing, MI. Silique, pod, and seed transmission
spectra were recorded with a S2000 fiber optic spectrometer
(Ocean Optics, http://www.oceanoptics.com/), using a probe
source and tungsten lamp with a paper diffuser. Spectra were
measured by placing the sample tissue immediately before a
300-lm optical fiber.
Plant material and culturing conditions
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 231
and [U-13C5]-glutamine experiments were fitted to a stoichiometric
steady-state model (Supplement S8), employing the cumomer formalism (Wiechert et al., 1999; Wiechert and Wurzel, 2001).
The analysis of fluxes in steady-state MFA relies on ‘retrobiosynthesis’ (Szyperski, 1995, 1998) whereby labeling in products is
used to infer labeling in metabolic intermediates in the steady
state. Here the amino acids of protein, organic acids, fatty acids
of triacylglycerol, and monosaccharides of starch and cell walls
were analyzed. Measuring substrate uptake rates and product
synthesis rates, together with isotopomer mass balancing of
intermediates, allows for flux and sensitivity estimation. Models
were generated on PC machines using the 13CFLUX suite of
software provided by W. Wiechert, Department of Simulation,
University of Siegen, Germany (Wiechert et al., 2001 and references therein), and run in the Linux environment (Supplement S8). Best estimates for fluxes were obtained by using
Donlp2 (a sequential quadratic programming optimizer; Spellucci,
1998) to minimize the difference between simulated and experimental measurements by varying the flux values while maintaining stoichiometric constraints. Optimizations were initiated
from random starting values for the free flux variables that were
constrained to be within the feasible solution space (Schuster
and Schuster, 1993). Initial, randomly generated starting points,
many of which lie outside of the feasible space, were orthogonally projected to the nearest feasible point using the lsqlin
function in Matlab and supplying the stoichiometric, equality,
and inequality constraints as matrix inputs to generate 600
feasible starting points.
Statistical analysis
Though all experiments were replicated at least three times and
additional technical replicates were made to verify measurement
precision, triplicate sampling falls far short of the 30 samplings
required to reliably estimate the standard deviation of a population.
Moreover, the measurements were modeled independently as three
separate models. This makes the sample SD unsuitable for use in
weighting input measurements for modeling. Therefore, model
simulations were performed by assigning a 1% error to each of the
GC-MS and NMR label measurements. A 1% error was chosen by
considering the measured differences among multiple MS signals
containing the same metabolite or fragment (e.g. M-85 and M-159)
similar to previous findings (McKinlay et al., 2007). A 1% error was a
conservative estimate compared with standards corrected for natural abundance (Antoniewicz et al., 2007, and our unpublished
results). For several compounds, the correction for naturally
occurring heavy isotopes resulted in potential errors of over 1%. In
these cases the actual error measured for the standard was used if it
was less than 3%, while no data were used from compounds or
fragments for which the standards failed to correct to within 3%.
Similarly, measurements of fluxes into amino acid synthesis were
modeled with a 2.5% error because this allowed for the individual
modeling of each of three sets of fluxes, and is consistent with the
potential inaccuracies involved in amino acid analysis, while the
GC-FID measurements of flux to oil were used to constrain each of
the three models. Substrate uptake and gas exchange measurements were used directly in model evaluation.
The [U-13C5]-glutamine and [U-13C6]-glucose labeling experimental replicate datasets were randomly paired and used for fitting. The
differences among the resulting three sets of optimized fluxes
reflect combined biological variability, technical precision in the
measurements, and the optimization process giving 90% confidence intervals for each parameter (Figure 5, Table 1).
Acknowledgements
The authors gratefully acknowledge: Dr Dan Jones and Beverly
Chamberlin (MSU Mass Spectrometry Facility), Dr Daniel Holmes
(Max T Rogers NMR Facility), Dr Joe Leykam (Macromolecular
Structure, Sequencing and Synthesis Facility), William Cook (Duke
Environmental Stable Isotope Laboratory), Dr Randy Beaudry
(Postharvest Biology and Technology Lab, MSU, IRGA/O2 paramagnetic analysis), and Dr Denis Proshlyakov (optic spectroscopy)
for help with instrumentation; Drs Mike Pollard, Igor Libourel, Jörg
Schwender, and Ana Alonso for valuable discussions; Dr Hart Poskar for Perl script programming; the Michigan Soybean Promotion
Committee, Biotechnology Research and Development Corporation, USDA grant 2006-35318-16661, the DOE Great Lakes Bioenergy
Research Center and DOE contract DE-FG02-87ER13729 for financial
support. Additionally the authors thank the editor and anonymous
referees for helpful comments and suggestions that have improved
the manuscript.
Supporting Information
Additional Supporting Information may be found in the online
version of this article:
Supplement S1. Biomass composition and 13C labeling results.
Figure S1a. Amino acid profile of soybean embryo storage protein.
Figure S1b. Fatty acid profile of soybean embryo triacylglycerol.
Figure S1c. Starch labeling from [U-13C5]-glutamine experiment.
Figure S1d. Cell wall, protein glycan, and starch labeling for
[U-13C6]-glucose experiment.
Table S1a. Biomass accumulation in soybean embryos.
Table S1b. Free and protein amino acid average labeling data.
Table S1c. 13C isotopomer abundances for [U-13C5]-glutamine and
glucose labeling experiments measured by GC-MS.
Table S1d. 13C enrichments and bond connectivity for [U-13C5]glutamine and glucose labeling experiments measured by NMR.
Supplement S2. Redox balance of seed metabolism.
Figure S2a. Redox state of glutamine.
Table S2a. Amino acid redox/oxidation states in soybeans.
Table S2b. Oxidation state for soybean storage triacylglycerol.
Supplement S3. The ATP calculations.
Table S3a. The ATP polymerization events.
Table S3b. Redox requirements for biosynthesis of amino acids from
primary metabolism using imported glutamine and asparagine.
Supplement S4. The oxidative pentosephosphate pathway (OPPP)
versus the Calvin/TCA cycle.
Figure S4a. Flux map with the oxidative pentosephosphate pathway
(OPPP).
Figure S4b. Flux map with TCA cycle.
Supplement S5. Flux analysis in complex systems.
Supplement S6. Potential limitations of using metabolic flux
analysis (MFA) to analyze plant tissues.
Supplement S7. Extended experimental procedures.
Supplement S8. Metabolic network.
Please note: Wiley-Blackwell are not responsible for the content or
functionality of any supporting materials supplied by the authors.
Any queries (other than missing material) should be directed to the
corresponding author for the article.
References
Allen, J.F. (2003) Cyclic, pseudocyclic and noncyclic photophosphorylation: new links in the chain. Trends Plant Sci. 8,
15–19.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
232 Doug K. Allen et al.
Allen, D.K., Shachar-Hill, Y. and Ohlrogge, J.B. (2007) Compartmentspecific labeling information in 13C metabolic flux analysis of
plants. Phytochemistry, 68, 2197–2210.
Alonso, A.P., Goffman, F.D., Ohlrogge, J.B. and Shachar-Hill, Y.
(2007) Carbon conversion efficiency and central metabolic fluxes
in developing sunflower (Helianthus annuus L.) embryos. Plant J.
52, 296–308.
Antoniewicz, M.R., Kelleher, J.K. and Stephanopoulos, G. (2007)
Accurate assessment of amino acid mass isotopomer distributions for metabolic flux analysis. Anal. Chem. 79, 7554–7559.
Arnon, D.I. (1984) The discovery of photosynthetic phosphorylation.
Trends Biochem. Sci. 9, 258–262.
Asokanthan, P.S., Johnson, R.W., Griffith, M. and Krol, M. (1997)
The photosynthetic potential of canola embryos. Physiol. Plant,
101, 353–360.
Browse, J. and Slack, C.R. (1985) Fatty-acid synthesis in plastids
from maturing safflower and linseed cotyledons. Planta, 166, 74–
80.
Buchanan, B.B. (1980) Role of light in the regulation of chloroplast enzymes. Annu. Rev. Plant Physiol. Plant Mol. Biol. 31,
341–374.
Dahmer, M.L., Collins, G.B. and Hildebrand, D.F. (1991) Lipid-concentration and composition of soybean zygotic embryos maturing in vitro and in planta. Crop Sci. 31, 735–740.
Damude, H.G. and Kinney, A.J. (2007) Engineering oilseed plants for
a sustainable, land-based source of long chain polyunsaturated
fatty acids. Lipids, 42, 179–185.
Dieuaide-Noubhani, M., Alonso, A.P., Rolin, D., Eisenreich, W. and
Raymond, P. (2007) Metabolic flux analysis: recent advances
in carbon metabolism in plants. In Plant Systems Biology Vol.
97 (Baginsky, S. and Fernie, A., eds). Basel: Birkhauser-Verlag,
pp. 213–243.
Egli, D.B. (1998) Seed Biology and the Yield of Grain Crops. New
York: CAB International.
Egli, D.B. and Bruening, W.P. (2001) Source-sink relationships, seed
sucrose levels and seed growth rates in soybean. Ann. Bot. 88,
235–242.
Egli, D.B., Guffy, R.D., Meckel, L.W. and Leggett, J.E. (1985) The
effect of source sink alterations on soybean seed growth. Ann.
Bot. 55, 395–402.
Fabre, F. and Planchon, C. (2000) Nitrogen nutrition, yield and protein content in soybean. Plant Sci. 152, 51–58.
Flinn, A.M., Atkins, C.A. and Pate, J.S. (1977) Significance of photosynthetic and respiratory exchanges in carbon economy of
developing pea fruit. Plant Physiol. 60, 412–418.
Furbank, R.T., White, R., Palta, J.A. and Turner, N.C. (2004) Internal
recycling of respiratory CO2 in pods of chickpea (Cicer arietinum
L.): the role of pod wall, seed coat, and embryo. J. Exp. Bot. 55,
1687–1696.
Gifford, R.M. and Thorne, J.H. (1985) Sucrose concentration at the
apoplastic interface between seed coat and cotyledons of developing soybean seeds. Plant Physiol. 77, 863–868.
Goffman, F.D., Ruckle, M., Ohlrogge, J. and Shachar-Hill, Y. (2004)
Carbon dioxide concentrations are very high in developing oilseeds. Plant Physiol. Biochem. 42, 703–708.
Goffman, F.D., Alonso, A.P., Schwender, J., Shachar-Hill, Y. and
Ohlrogge, J.B. (2005) Light enables a very high efficiency of carbon storage in developing embryos of rapeseed. Plant Physiol.
138, 2269–2279.
Hayati, R., Egli, D.B. and CraftsBrandner, S.J. (1996) Independence
of nitrogen supply and seed growth in soybean: Studies using an
in vitro culture system. J. Exp. Bot. 47, 33–40.
Hernandez-Sebastia, C., Marsolais, F., Saravitz, C., Israel, D.,
Dewey, R.E. and Huber, S.C. (2005) Free amino acid profiles
suggest a possible role for asparagine in the control of storageproduct accumulation in developing seeds of low- and highprotein soybean lines. J. Exp. Bot. 56, 1951–1963.
Hinkle, P.C. (2005) P/O ratios of mitochondrial oxidative phosphorylation. Biochim. Biophys. Acta, Bioenerg. 1706, 1–11.
Holowach, L.P., Thompson, J.F. and Madison, J.T. (1984a) Effects
of exogenous methionine on storage protein-composition of
soybean cotyledons cultured in vitro. Plant Physiol. 74, 576–
583.
Holowach, L.P., Thompson, J.F. and Madison, J.T. (1984b) Storage protein-composition of soybean cotyledons grown-in vitro
in media of various sulfate concentrations in the presence and
absence of exogenous L-methionine. Plant Physiol. 74, 584–
589.
Hsu, F.C. and Obendorf, R.L. (1982) Compositional analysis of in
vitro matured soybean seeds. Plant Sci. Lett. 27, 129–135.
Hsu, F.C., Bennett, A.B. and Spanswick, R.M. (1984) Concentrations
of sucrose and nitrogenous compounds in the apoplast of
developing soybean seed coats and embryos. Plant Physiol. 75,
181–186.
Iyer, V.V., Sriram, G., Fulton, D.B., Zhou, R., Westgate, M.E. and
Shanks, J.V. (2008) Metabolic flux maps comparing the effect of
temperature on protein and oil biosynthesis in developing soybean cotyledons. Plant Cell Environ. 31, 506–517.
Jander, G., Norris, S.R., Joshi, V., Fraga, M., Rugg, A., Yu, S.X., Li,
L.L. and Last, R.L. (2004) Application of a high-throughput HPLCMS/MS assay to Arabidopsis mutant screening; evidence that
threonine aldolase plays a role in seed nutritional quality. Plant J.
39, 465–475.
Junker, B.H., Lonien, J., Heady, L.E., Rogers, A. and Schwender, J.
(2007) Parallel determination of enzyme activities and in vivo
fluxes in Brassica napus embryos grown on organic or inorganic
nitrogen source. Phytochemistry, 68, 2232–2242.
King, S.P., Badger, M.R. and Furbank, R.T. (1998) CO2 refixation
characteristics of developing canola seeds and silique wall. Aust.
J. Plant Physiol. 25, 377–386.
Lakakul, R., Beaudry, R.M. and Hernandez, R.J. (1999) Modeling
respiration of apple slices in modified-atmosphere packages.
J. Food Sci. 64, 105–110.
Libourel, I.G.L. and Shachar-Hill, Y. (2008) Metabolic flux analysis in
plants: from intelligent design to rational engineering. Annu. Rev.
Plant Biol. 59, 625–650.
Libourel, I.G.L., Gehan, J.P. and Shachar-Hill, Y. (2007) Design of
substrate label for steady state flux measurements in plant systems using the metabolic network of Brassica napus embryos.
Phytochemistry, 68, 2211–2221.
McKinlay, J.B., Shachar-Hill, Y., Zeikus, J.G. and Vieille, C. (2007)
Determining Actinobacillus succinogenes metabolic pathways
and fluxes by NMR and GC-MS analyses of C-13-labeled metabolic product isotopomers. Metab. Eng. 9, 177–192.
Mir, N.A., Curell, E., Khan, N., Whitaker, M. and Beaudry, R.M.
(2001) Harvest maturity, storage temperature, and 1-MCP
application frequency alter firmness retention and chlorophyll
fluorescence of ‘Redchief Delicious’ apples. J. Am. Soc. Hortic.
Sci. 126, 618–624.
Nakasathien, S., Israel, D.W., Wilson, R.F. and Kwanyuen, P. (2000)
Regulation of seed protein concentration in soybean by supraoptimal nitrogen supply. Crop Sci. 40, 1277–1284.
Narvel, J.M., Fehr, W.R., Ininda, J., Welke, G.A., Hammond, E.G.,
Duvick, D.N. and Cianzio, S.R. (2000) Inheritance of elevated
palmitate in soybean seed oil. Crop Sci. 40, 635–639.
Obendorf, R.L. and Wettlaufer, S.H. (1984) Precocious germination
during in vitro growth of soybean seeds. Plant Physiol. 76, 1023–
1028.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
Role of light in soybean seed filling metabolism 233
Pipolo, A.E., Sinclair, T.R. and Camara, G.M.S. (2004) Protein and oil
concentration of soybean seed cultured in vitro using nutrient
solutions of differing glutamine concentration. Ann. Appl. Biol.
144, 223–227.
Privett, O.S., Doughert, K.A., Erdahl, W.L. and Stolyhwo, A. (1973)
Studies on lipid-composition of developing soybeans. J. Am. Oil
Chem. Soc. 50, 516–520.
Quebedeaux, B. and Chollet, R. (1975) Growth and development of
soybean (Glycine-max [L] merr) pods - CO2 exchange and enzyme
studies. Plant Physiol. 55, 745–748.
Rainbird, R.M., Thorne, J.H. and Hardy, R.W.F. (1984) Role of
amides, amino-acids, and ureides in the nutrition of developing
soybean seeds. Plant Physiol. 74, 329–334.
Ratcliffe, R.G. and Shachar-Hill, Y. (2006) Measuring multiple fluxes
through plant metabolic networks. Plant J. 45, 490–511.
Rolletschek, H., Hosein, F., Miranda, M., Heim, U., Gotz, K.P.,
Schlereth, A., Borisjuk, L., Saalbach, I., Wobus, U. and Weber, H.
(2005a) Ectopic expression of an amino acid transporter (VfAAP1)
in seeds of Vicia narbonensis and pea increases storage proteins.
Plant Physiol. 137, 1236–1249.
Rolletschek, H., Radchuk, R., Klukas, C., Schreiber, F., Wobus, U.
and Borisjuk, L. (2005b) Evidence of a key role for photosynthetic
oxygen release in oil storage in developing soybean seeds. New
Phytol. 167, 777–786.
Rolletschek, H., Nguyen, T.H., Hausler, R.E. et al. (2007) Antisense
inhibition of the plastidial glucose-6-phosphate/phosphate
translocator in Vicia seeds shifts cellular differentiation and promotes protein storage. Plant J. 51, 468–484.
Roscher, A., Kruger, N.J. and Ratcliffe, R.G. (2000) Strategies for
metabolic flux analysis in plants using isotope labelling. J. Biotechnol. 77, 81–102.
Rubel, A., Rinne, R.W. and Canvin, D.T. (1972) Protein, oil, and fattyacid in developing soybean seeds. Crop Sci. 12, 739–741.
Ruuska, S.A., Schwender, J. and Ohlrogge, J.B. (2004) The capacity
of green oilseeds to utilize photosynthesis to drive biosynthetic
processes. Plant Physiol. 136, 2700–2709.
Saitoh, K., Nishimura, K. and Kuroda, T. (2004a) Characteristics of
flowering and pod set in wild and cultivated types of soybean.
Plant Prod. Sci. 7, 172–177.
Saitoh, K., Nishimura, K. and Kuroda, T. (2004b) Comparison of leaf
photosynthesis between wild and cultivated types of soybean.
Plant Prod. Sci. 7, 277–279.
Sambo, E.Y., Moorby, J. and Milthorpe, F.L. (1977) Photosynthesis
and respiration of developing soybean pods. Aust. J. Plant
Physiol. 4, 713–721.
Saravitz, C.H. and Raper, C.D. (1995) Responses to sucrose and
glutamine by soybean embryos grown in vitro. Physiol. Plant, 93,
799–805.
Satterlee, L.D. and Koller, H.R. (1984) Response of soybean fruit
respiration to changes in whole plant light and CO2 environment.
Crop Sci. 24, 1007–1010.
Schmidt, K., Carlsen, M., Nielsen, J. and Villadsen, J. (1997)
Modeling isotopomer distributions in biochemical networks
using isotopomer mapping matrices. Biotechnol. Bioeng. 55,
831–840.
Schuster, R. and Schuster, S. (1993) Refined algorithm and computer-program for calculating all nonnegative fluxes admissible
in steady-states of biochemical reaction systems with or without
some flux rates fixed. Comput. Appl. Biosci. 9, 79–85.
Schwender, J. (2008) Metabolic flux analysis as a tool in
metabolic engineering of plants. Curr. Opin. Biotechnol. 19, 131–
137.
Schwender, J., Ohlrogge, J.B. and Shachar-Hill, Y. (2003) A flux
model of glycolysis and the oxidative pentose phosphate path-
way in developing Brassica napus embryos. J. Biol. Chem. 278,
29442–29453.
Schwender, J., Goffman, F., Ohlrogge, J.B. and Shachar-Hill, Y.
(2004a) Rubisco without the Calvin cycle improves the
carbon efficiency of developing green seeds. Nature, 432, 779–
782.
Schwender, J., Ohlrogge, J. and Shachar-Hill, Y. (2004b) Understanding flux in plant metabolic networks. Curr. Opin. Plant Biol.
7, 309–317.
Schwender, J., Shachar-Hill, Y. and Ohlrogge, J.B. (2006) Mitochondrial metabolism in developing embryos of Brassica napus.
J. Biol. Chem. 281, 34040–34047.
Shikanai, T. (2007) Cyclic electron transport around photosystem I:
Genetic approaches. Annu. Rev. Plant Biol. 58, 199–217.
Spellucci, P. (1998) An SQP method for general nonlinear programs
using only equality constrained subproblems. Math. Program. 82,
413–448.
Sriram, G., Fulton, D.B., Iyer, V.V., Peterson, J.M., Zhou, R.L.,
Westgate, M.E., Spalding, M.H. and Shanks, J.V. (2004) Quantification of compartmented metabolic fluxes in developing soybean embryos by employing biosynthetically directed fractional
C-13 labeling, [C-13, H-1] two-dimensional nuclear magnetic
resonance, and comprehensive isotopomer balancing. Plant
Physiol. 136, 3043–3057.
Steigmiller, S., Turina, P. and Graber, P. (2008) The thermodynamic H+/ATP ratios of the H+-ATP synthases from chloroplasts and Escherichia coli. Proc. Natl Acad. Sci. USA, 105,
3745–3750.
Stephanopoulos, G., Aristidou, A. and Nielsen, J. (1998) Metabolic
Engineering: Principles and Methodologies. San Diego: Academic Press.
Sugimoto, T., Tanaka, K., Momma, M. and Saio, K. (1987) Photosynthetic activity in the developing cotyledon of soybean seeds.
Agric. Biol. Chem. 51, 1227–1230.
Szyperski, T. (1995) Biosynthetically directed fractional C-13-labeling of proteinogenic amino-acids - an efficient analytical tool to
investigate intermediary metabolism. Eur. J. Biochem. 232, 433–
448.
Szyperski, T. (1998) C-13-NMR, ms and metabolic flux balancing in
biotechnology research. Q. Rev. Biophys. 31, 41–106.
Thompson, J.F., Madison, J.T. and Muenster, A.M.E. (1977) In vitro
culture of immature cotyledons of soya bean (Glycine-max-Lmerr). Ann. Bot. 41, 29–39.
Thorne, J.H. (1980) Kinetics of photosynthate-C-14 uptake by
developing soybean fruit. Plant Physiol. 65, 975–979.
Thorne, J.H. (1981) Morphology and ultrastructure of maternal seed
tissues of soybean in relation to the import of photosynthate.
Plant Physiol. 67, 1016–1025.
Werdan, K., Heldt, H.W. and Milovancev, M. (1975) Role of pH in
regulation of carbon fixation in chloroplast stroma - studies on
CO2 fixation in light and dark. Biochim. Biophys. Acta, 396, 276–
292.
Wiechert, W. and Wurzel, M. (2001) Metabolic isotopomer labeling
systems - part I: Global dynamic behavior. Math. Biosci. 169, 173–
205.
Wiechert, W., Mollney, M., Isermann, N., Wurzel, W. and de Graaf,
A.A. (1999) Bidirectional reaction steps in metabolic networks: III.
Explicit solution and analysis of isotopomer labeling systems.
Biotechnol. Bioeng. 66, 69–85.
Wiechert, W., Mollney, M., Petersen, S. and de Graaf, A.A. (2001) A
universal framework for C-13 metabolic flux analysis. Metab. Eng.
3, 265–283.
Wilcox, J.R. (1998) Increasing seed protein in soybean with eight
cycles of recurrent selection. Crop Sci. 38, 1536–1540.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234
234 Doug K. Allen et al.
Willms, J.R., Salon, C. and Layzell, D.B. (1999) Evidence for lightstimulated fatty acid synthesis in soybean fruit. Plant Physiol. 120,
1117–1127.
Yazdi-Samadi, B., Rinne, R.W. and Seif, R.D. (1977) Components of
developing soybean seeds - oil, protein, sugars, starch, organicacids, and amino-acids. Agron. J. 69, 481–486.
Zhu, X.G., Long, S.P. and Ort, D.R. (2008) What is the maximum
efficiency with which photosynthesis can convert solar energy
into biomass? Curr. Opin. Biotechnol. 19, 153–159.
Zupke, C. and Stephanopoulos, G. (1994) Modeling of isotope distributions and intracellular fluxes in metabolic networks using
atom mapping matrices. Biotechnol. Prog. 10, 489–498.
ª 2009 The Authors
Journal compilation ª 2009 Blackwell Publishing Ltd, The Plant Journal, (2009), 58, 220–234