Journal of Experimental Botany, Vol. 65, No. 13, pp. 3459–3470, 2014
doi:10.1093/jxb/eru127 Advance Access publication 6 April, 2014
Review paper
Carbon isotope discrimination as a tool to explore C4
photosynthesis
Susanne von Caemmerer1, Oula Ghannoum2, Jasper J. L. Pengelly1 and Asaph B. Cousins3
1 Research School of Biology, The Australian National University, Canberra ACT 0200, Australia
Hawkesbury Institute for the Environment, University of Western Sydney, Hawkesbury campus, Locked Bag 1797, Penrith 2751, NSW,
Australia
3 School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
2 * To whom correspondence should be addressed. E-mail: [email protected]
Received 3 December 2013; Revised 28 February 2014; Accepted 3 March 2014
Abstract
Photosynthetic carbon isotope discrimination is a non-destructive tool for investigating C4 metabolism. Tuneable
diode laser absorption spectroscopy provides new opportunities for making rapid, concurrent measurements of carbon isotope discrimination and CO2 assimilation over a range of environmental conditions, and this has facilitated the
use of carbon isotope discrimination as a probe of C4 metabolism. In spite of the significant progress made in recent
years, understanding how photosynthetic carbon isotope discrimination measured concurrently with gas exchange
relates to carbon isotope composition of leaf and plant dry matter remains a challenge that requires resolution if this
technique is to be successfully applied as a screening tool in crop breeding and phylogenetic research. In this review,
we update our understanding of the factors and assumptions that underlie variations in photosynthetic carbon isotope discrimination in C4 leaves. Closing the main gaps in our understanding of carbon isotope discrimination during
C4 photosynthesis may help advance research aimed at developing higher productivity and efficiency in key C4 food,
feed, and biofuel crops.
Keywords: 13C discrimination, C4 grasses, C4 photosynthesis, carbon isotope discrimination, NAD-ME subtype, NADP-ME
subtype, gas exchange.
Introduction
During photosynthetic CO2 fixation, plants discriminate
(preferential consumption of one isotopologue over another)
against the minor, naturally occurring stable isotope 13C (ca.
1.1149% in CO2 in air). In C3 species, the carbon isotope composition of plant material is primarily caused by the discrimination occurring during carboxylation by the rate-limiting
enzyme Rubisco (ribulose-1,5-bisphosphate carboxylase/
oxygenase), and during the diffusion of CO2 from the atmosphere to the chloroplast (Farquhar et al., 1982). The discrimination factor of Rubisco is 29–30 per mil (‰), whereas
discrimination during diffusion in air and the liquid phase
are 4.4 and 1.8‰, respectively. Farquhar et al. (1982) defined
carbon isotope discrimination as Δ=Rair/Rp–1, where Rair and
Rp stand for the 13C/12C ratio in air and the photosynthetic
product, respectively. They predicted a strong linear relationship between carbon isotope discrimination (Δ) and the
ratio of intercellular to ambient CO2 partial pressure (Ci/Ca).
However, internal diffusion of the CO2 from the substomatal cavity to site of Rubisco carboxylation in the chloroplast
stroma also affects discrimination and results in a dependency of Δ on photosynthetic rates. For example, Δ can vary
by 6–8‰ with variation in rates of photosynthesis driven by
changes in light intensity (Evans et al., 1986; von Caemmerer
and Evans, 1991). These variations in Δ are integrated into
the isotopic signature of leaf dry matter (δ), which is usually referenced to the standard Pee Dee Belemnite (PDB)
and defined as δ=Rp/RPDP−1, where Rp and RPDB stand for
the 13C/12C ratio in leaf dry matter and the standard PDB,
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3460 | Caemmerer et al.
respectively (Farquhar et al., 1989a). This provides an integrated measure of carbon isotope discrimination over time,
and averages –22‰ for most C3 species.
The key feature of C4 photosynthesis is the operation of
a CO2 concentrating mechanism across the mesophyll cell
(MC) and bundle sheath cell (BSC). The primary steps of
CO2 hydration and subsequent fixation into C4 acids occur
in the MC; these acids diffuse into the BSC where they are
decarboxylated, releasing CO2 for fixation by Rubisco. C4
photosynthesis has three biochemical subtypes depending on
the major C4 acid decarboxylase: nicotinamide adenine dinucleotide phosphate malic enzyme (NADP-ME), NAD malic
enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK). Specialized leaf anatomy, biochemistry,
and physiology are associated with each of the C4 subtypes
(Hatch, 1987). Carbon isotope discrimination in C4 species
reflects biochemical fractionation of Rubisco and phosphoenol pyruvate carboxylase (PEPC) as well as their interconnectivity (Farquhar, 1983). The initial hydration of CO2 to
bicarbonate and PEP carboxylation has a combined fractionation of –5.7‰ at 25 °C and is dependent on temperature and
the amount of carbonic anhydrase present (Cousins et al.,
2006; Farquhar, 1983; Henderson et al., 1992). The extent of
Rubisco fractionation is dependent on bundle sheath leakiness (ϕ), defined as the ratio of bundle sheath leak rate to
PEP carboxylase rate (assumed to be equal to the rate of C4
acid decarboxylation). Henderson et al. (1992) estimated ϕ
using concurrent measurements of gas exchange and carbon isotope discriminating to be about 0.2 in a number of
C4 species representing different decarboxylation types under
a range of environmental conditions. These additional fractionation steps associated with C4 photosynthesis cause the
carbon isotope composition of C4 species to fall in a narrow
range between –12 and –15‰, which clearly distinguishes C4
species from C3 species (Cernusak et al., 2013; Henderson
et al., 1992; O’Leary, 1981; Peisker and Henderson, 1992).
Measurements of the carbon isotope ratio of leaf dry matter provide an integrated measure of leaf carbon isotope
exchange; however, leaf dry matter carbon is in part derived
from photosynthesis from older leaves rather than current
photosynthate. In addition, isotopic discrimination during
respiration and the day/night variations in respiration rates
may also affect the carbon isotope composition of leaf dry
matter (Henderson et al., 1992; Hobbie and Werner, 2004).
Therefore, measurements of dry matter carbon isotope composition provide less insight into primary carbon metabolism
compared with concurrent measurements of gas exchange
and carbon isotope discrimination, which can measure
instantaneous photosynthetic carbon isotope discrimination
under different environmental conditions. New development
of laser technologies improved the ease with which these
measurements can be made, opening up new opportunities
for detailed investigations of the relationship between carbon
isotope discrimination and C4 photosynthesis (Cousins et al.,
2008; Cousins et al., 2007; King et al., 2012; Kromdijk et al.,
2010; Pengelly et al., 2011; Pengelly et al., 2010; Pengelly
et al., 2012; Sun et al., 2012; Ubierna et al., 2011; Ubierna
et al., 2013). This is driving a better understanding of the
processes influencing the carbon isotope composition of C4
plant dry matter. In C3 species carbon isotope signature of
plant dry matter has been used successfully as a breeding tool
for improved plant water use efficiency in C3 crops, such as
wheat (Farquhar et al., 1989b; Rebetzke et al., 2002) and provided a tool in ecophysiological studies (e.g. Cernusak et al.,
2009b; Korner et al., 1991). In C4 plants, it has been used
less, but there is a renewed interest in the study of C4 species, including phylogenetic studies exploring the evolution of
C4 photosynthesis (Denton et al., 2013; Edwards and Smith,
2010; Griffiths et al., 2013; Heckmann et al., 2013; Sage et al.,
2012), as well as directed studies seeking to use carbon isotope discrimination as a screening tool for crop improvement
(Gresset et al., 2014). This review provides an update on our
understanding of carbon isotope discrimination during C4
photosynthesis.
Theory of carbon isotope discrimination
during C4 photosynthesis
Theoretical models of carbon isotope discrimination occurring during C4 photosynthesis have shown that CO2 leakage
from the bundle sheath is one of the main factors influencing
carbon isotope discrimination during CO2 uptake (Farquhar,
1983; O’Leary, 1981; Peisker, 1982). Farquhar (1983) provided
a detailed theoretical relationship to gas exchange measurements and examined in detail the possible fractionations
that contribute to carbon isotope discrimination (Δ) during
C4 photosynthesis. He also provided a succinct formulation
relating Δ to the ratio of intercellular to ambient CO2 partial
pressure (Ci/Ca) and leakiness (ϕ), which is simplified as:
∆ = a + ( b4 + ( b3 − s ) φ − a )
Ci
Ca
(1)
where a is the fractionation during diffusion of CO2 in air
(4.4‰), b4 is the fractionation associated with PEP carboxylation and the preceding isotopic equilibrium during dissolution and conversion to bicarbonate (fractionations defined
below), s is the fractionation during the leakage of CO2 out
of the bundle sheath cells (1.8‰), and b3 is the fractionation
during Rubisco carboxylation. Equation (1) predicts a positive (high values of ϕ) or negative (low values of ϕ) relationship to Ci/Ca (Henderson et al., 1992).
The theory defined by equation (1) has recently been
updated to include the ternary formulation to take into
account the influence of transpiration on CO2 diffusion
between the atmosphere and the intercellular air spaces
(Farquhar and Cernusak, 2012). Although equations used
to calculate gas exchange include ternary effects of transpiration rate on the rate of CO2 assimilation through stomata
(von Caemmerer and Farquhar, 1981), the equations describing carbon isotope discrimination had been derived without
the ternary effects. A detailed description of the equations
and definitions of discrimination factors are given in the
Appendix and Fig. 1. In Fig. 2 the effect of temperature on
the predicted photosynthetic carbon isotope discrimination
Carbon isotope discrimination in C4 species | 3461
Fig. 1. Schematic of C4 photosynthetic pathway and associated carbon isotope fractionations (shown in red). Discrimination against 13C occurs first
during diffusion of CO2 in air through the boundary layer (with a discrimination factor, ab=2.9‰) and stomata (a=4.4‰) and during dissolution and
diffusion through liquid in the cytoplasm (ai=1.8‰). In the mesophyll cytosol 13C concentrates in HCO3– at equilibrium by –7.9‰ at 25 °C and PEP
carboxylase discriminates against 13C by 2.2‰ such that the net fractionation is b4=–5.7‰. No further discrimination could occur if the bundle sheath
were completely gas tight, but some CO2 is likely to leak out, which allows for some discrimination against 13C by Rubisco (b3=29‰). Discrimination
during leakage is taken to be that during dissolution and diffusion of CO2 in liquid (s=1.8‰). Fractionation during respiration (e) is variable (0–5‰)
and photorespiratory fraction (f) ranges from (8–16‰). The process of discrimination has been summarized in the equations developed by (Farquhar,
1983), which are given in a modified version in the Appendix and discrimination factors are described in (Evans and von Caemmerer, 2013; Farquhar,
1983; Henderson et al., 1992). Ca, Cls, Ci, Cm, Cs are the CO2 partial pressures in the ambient air, at the leaf surface, the intercellular airspaces and the
mesophyll cytosol, and the bundle sheath, respectively. Leakiness is given by ϕ=L/Vp, where L is the rate of inorganic carbon leakage out of the bundle
sheath and Vp is the rate of PEP carboxylation (assumed to equal C4 acid decarboxylation). A denotes CO2 assimilation rate, Vc and Vo stand for Rubisco
carboxylation and oxygenation, and Rm and Rs for mitochondrial respiration in the mesophyll and bundle sheath cells, respectively. Orange markers
indicate carbon isotope discrimination measurement have been made in transgenic F. bidentis. These include transgenics with reductions in 1) Rubisco
content, 2) malic enzyme, 3) carbonic anhydrase, and 4) over expression of tobacco carbonic anhydrase.
is shown as a function of intercellular to ambient CO2. Evans
and von Caemmerer (2013) compared the effect the ternary
formulation had on the estimation of mesophyll conductance from Δ during C3 photosynthesis, and found significant
differences at high temperatures (see discussion in Cernusak
et al., 2013). Although a detailed analysis has yet to be done
in many C4 plants, Ubriena et al. (2013) found that the ternary calculations had little effect on their estimates of ϕ.
However, it should be noted that this might not be true under
all experimental conditions, particularly when the vapour
pressure deficit between the leaf and the atmosphere is large
and variable. As demonstrated in Fig. 5, the ternary correction makes only a small difference to the estimation of leakiness in response to changes in leaf temperature.
Fig. 2. Modelled photosynthetic carbon isotope discrimination as a
function of the ratio of intercellular to ambient CO2 (Ci/Ca). Carbon isotope
discrimination is either referenced to the surrounding atmosphere (Δ)
or the standard PDB (δ). Δ = Rair/Rp–1 and δ= Rp /RPDB−1, where R
stands for the ratio 13C/12C and the subscripts air, p, and PDB stand
for 13C/12C ratio in air, photosynthetic product, and the standard PDB,
respectively. Δ = (δair–δ)/(1–δ). The lines are modelled with equation A1
at three temperatures. Parameters were a′= 4.33, b3′=27.1, s=1.8, e=
3.3, b4′=–6.34, –5.3, –4.35, and t=0.16, 0.033, 0.057, CO2 assimilation,
A, and respiration rate, Rd, were 30, 43, 48, and 1.3, 2.3, 4.2 μmol m–2
s–1at 20, 30, and 40 °C, respectively. These values were derived from
measurements made using Cenchrus ciliaris shown in Fig. 5. Mesophyll
conductance gm was assumed to be infinite.
How does mesophyll conductance
influence C4 carbon isotope discrimination
and estimates of leakiness?
In C3 species, the conductance of CO2 from intercellular airspace to the chloroplast, termed mesophyll conductance, gm,
has been shown to have a major influence on carbon isotope
discrimination, such that carbon isotope discrimination
is not only related to Ci/Ca but also CO2 assimilation rate
(Evans et al., 1986; Evans and von Caemmerer, 2013; Flexas
et al., 2008; Tazoe et al., 2011; von Caemmerer and Evans,
1991; Walker et al., 2013). Indeed, concurrent measurements
of gas exchange and carbon isotope discrimination have
3462 | Caemmerer et al.
become a convenient tool to estimate gm, and the influence
of gm on the isotope composition of dry matter needs to be
considered when using Δ as a breeding tool for improved
water use efficiency (Barbour et al., 2010; Rebetzke et al.,
2002).
In C4 species the initial CO2 fixation occurs in the mesophyll cytosol where CO2 is converted to bicarbonate and fixed
by PEPC. Therefore, unlike in C3 species, CO2 has to diffuse
across the cell wall but only one membrane, the plasmalemma. However, PEPC is probably distributed throughout
the cytoplasm and not appressed only against the intercellular airspace. This raises questions about the diffusion path
length of CO2 to the site of carboxylation by PEPC. In C4
plants, the limitations to CO2 diffusion across this interface
have been difficult to assess because of the low Δ during C4
photosynthesis. The high rates of C4 photosynthesis require
high rates of CO2 diffusion from intercellular airspace to mesophyll cytosol and thus gm values must be high. However, it is
not possible to use carbon isotope discrimination to quantify
gm, because photosynthetic fractionations during C4 photosynthesis are low. This is illustrated by simulations in Fig. 3,
which contrasts the isotope fractionation associated with gm
in C3 and C4 species. In C3 species, a low gm value can reduce
observed carbon isotope discrimination by 6‰ or more
when rates of CO2 assimilation are high (von Caemmerer
and Evans, 1991). However, in C4 species the effect of gm is
much less. For example, at ϕ values of 0.2 or less the presence
of gm increases Δ, whereas when ϕ is high the values of Δ
decrease with gm (Henderson et al., 1992). This influence of
gm was highlighted in the analysis of carbon isotope discrimination in the crassulacean acid metabolism (CAM) species
Kalanchoe daigremontiana where measurements of Δ during
Ci-Cm=123 µbar
Ci-Cm=12 µbar
Fig. 3. Carbon isotope discrimination associated with mesophyll
conductance (equation A10) from intercellular airspace to the mesophyll
cytosol (in C4 species) or to the chloroplast stroma (for C3 species). The
simulation used measurements made for Cenchrus ciliaris (buffel grass) at
high light and 25 °C and ambient CO2 (Fig. 5) assimilation rate =38 μmol
m–2 s–1 and Ca=380 μbar. The same values were used for Δgm simulation
during C3 photosynthesis but ∆gm =
1+ t
A
ai − b3′
.
1− t
(gmCa )
(
)
the night time, where CO2 is fixed solely through CO2 hydration and PEPC carboxylation, were higher than could be predicted from the photosynthetic fractionation and Ci/Ca alone
(Griffiths et al., 2007). In summary, the uncertainty in both
gm and ϕ complicate the interpretation of C4 photosynthetic
carbon isotope discrimination.
Frequently, the aim of measuring Δ concurrently with
gas exchange is to obtain insights into the efficiency of the
CO2 concentrating mechanism in C4 plants by estimation
of ϕ (King et al., 2012; Kromdijk et al., 2008; Kubasek
et al., 2007; Sun et al., 2012; Tazoe et al., 2008; Ubierna
et al., 2011; Ubierna et al., 2013), so it is worthwhile to ask
how assumptions of gm influence estimates of ϕ. In Fig. 4
we have used the measurements made for the C4 grass,
Cenchrus ciliaris at 25 °C and calculated ϕ from equation
A8 with various assumed values of gm. The minimum gm
for C4 photosynthesis can be estimated from the ratio of
CO2 assimilation and intercellular CO2 (Ci) because the CO2
compensation point (the CO2 concentration where the net
CO2 assimilation is zero) is close to zero (Evans and von
Caemmerer, 1996). In this example, the minimum conductance value is 0.28 mol m–2 s–1 bar–1 (see legend to Fig. 4).
Large photosynthetic rates of many C4 species suggest that
gm values have to be greater than those commonly observed
in C3 species to maintain the supply of HCO3– to the initial carboxylation by PEPC (Evans and von Caemmerer,
1996; von Caemmerer et al., 2007). Fig. 4 demonstrates that
if low values are assumed for gm then estimates of ϕ are
lower. Because of the uncertainty in gm most calculations of
ϕ assume high values of gm; therefore, it is possible that ϕ is
overestimated in many cases. Measurements of C18OO discrimination may provide more insights into the range of gm
in C4 species although there are also limitations associated
with that technique (Gillon and Yakir, 2000; Henderson
et al., 1992).
Fig. 4. Estimates of leakiness (ϕ) made with various assumed values of
gm. Calculations were made using measurements made at with Cenchrus
ciliaris (buffel grass) at high light, 25 °C and ambient CO2 (Fig. 5). CO2
assimilation rate =38 μmol m–2 s–1 and Ca=380 μbar, Ci=133 μbar,
Δ=3.14‰. Other parameters were a′=4.33‰, e=3.3‰, b4′=5.81‰,
b3′=27.1‰, t=0.0248, Rd=1.7 μmol m–2 s–1.
Carbon isotope discrimination in C4 species | 3463
Fig. 5. Temperature dependence of CO2 assimilation rate, carbon isotope discrimination Δ, Ci/Ca, in Cenchrus ciliaris (buffel grass) measured at
1500 μmol quanta m–2 s–1, 380 μbar CO2, 2% O2 and various leaf temperatures. Also shown are discrimination factors b4’and b3’ and leakiness, ϕ
calculated with (filled circle) and without ternary correction (open circle, t=0) from equation A8. Photorespiratory fractionation was ignored because
measurements were made at 2% O2. Combined measurements of gas exchange and carbon isotope discrimination were made as described by (Evans
and von Caemmerer, 2013).
Photosynthetic and respiratory
fractionation factors
The fractionation of Rubisco is difficult to measure and only
a limited number of measurements exist (McNevin et al.,
2007 and references therein). In most models of photosynthetic carbon isotope discrimination, the fractionation factor
of Rubisco (b3) is assumed to be ~29–30‰. This value was
derived in vitro for spinach Rubisco (Roeske and O’Leary,
1984) and supported by in vivo measurements of carbon
isotope discrimination in transgenic tobacco with reduced
amounts of Rubisco (Evans et al., 1994). However, the evolutionary diversity in Rubisco catalysis between C3 and C4
species, and within C4 species (Badger and Andrews, 1987;
Ghannoum et al., 2005; Seemann et al., 1984; Tcherkez et al.,
2006; Yeoh et al., 1981), raises the question whether there
may also be diversity in b3. Very few measurements for b3 exist
for C4 species. Whelan et al. (1973) measured higher average
b3 values for Sorghum bicolor Rubisco (33.7 ± 6.6‰) but with
a large standard error. Transplastomic tobacco producing
chimeric Rubisco comprising tobacco Rubisco small subunits and the catalytic large subunits from either the C4 species
Flaveria bidentis or the C3-C4 species Flaveria floridana had b3
values of 27.8 ± 0.8 and 28.6 ± 0.6‰, respectively. However,
these values were not significantly different from tobacco
Rubisco (von Caemmerer et al., 2014). The fractionation factor b3 has been shown experimentally to be independent of
temperature (O’Leary et al., 1992) although theoretical considerations suggest a small decrease of b3 (0.04‰ °C–1) with
increasing temperature (Tcherkez and Farquhar, 2005).
To take into account the influence of day-respiration and
photorespiration on leaf CO2 isotope exchange the parameter b3’ (A7) incorporates b3, the contribution of day-respiration and the photorespiratory fractionation (Farquhar,
3464 | Caemmerer et al.
1983). The respiratory fractionation e is thought to range
between 0–5‰; however, when concurrent measurements of
gas exchange and carbon isotope discrimination are made
under conditions where the carbon isotope composition of
CO2 in the plant growth environment and that of the measurement CO2 are different, then the apparent respiratory
fractionation (e’) should be included (Kromdijk et al., 2010;
Tazoe et al., 2011; Wingate et al., 2007). The value e’ can be
estimated as in Wingate et al. (2007) where e’=e*+e; e is the
respiratory fractionation during decarboxylation, mentioned
above, e* is the difference between the use of recent photoassimilate and the use of other substrates for day-respiration.
Assuming all respiratory consumption of substrates occurs
using recent photoassimilates, then e* =[δ13Csample –(δ13Csample
–Δ)– Δ], where δ13Csample and Δ are the isotopic signature of
the measurement CO2 and the photosynthetic discrimination
during the measurement, respectfully. Alternatively, the use
of old photoassimilates can be modelled with e* =[δ13Csample
–(δ13Cgrowth –(δ13Cgrowth – δ13Cdry))– Δ] where δ13Cgrowth is the
isotopic signature of the air that plants were grown in and
δ13Cdry is the isotopic signature of the plant dry matter (Stutz
et al., 2014).These assumptions have considerable influence at
low assimilation rates as occur at low light or low CO2, and
make it difficult to estimate leakiness under these conditions
(Kromdijk et al., 2010; Pengelly et al., 2010; Stutz et al., 2014;
Ubierna et al., 2011; Ubierna et al., 2013). As can be seen
in Fig. 5, the effect of mitochondrial respiratory fractionation can have a large influence on b3’ in response to temperature and more experiments are needed to look at the effect
of variation in the isotope composition of CO2 used during
measurements.
Various estimates for photorespiratory fractionation (f)
have been reported in the literature (for review see Evans
and von Caemmerer, 2013). The rate of photorespiration is
thought to be low in C4 species but may be significant at low
light and CO2 concentrations. For example, Kromdijk et al.
(2010) made combined measurements of carbon isotopes
discrimination at low light and varying O2 partial pressures,
and observed differences in carbon isotope discrimination.
The term associated with photorespiratory fractionation
(equation A7, Table 1) varies with bundle sheath CO2 partial pressure (Cs) and Γ*. The term Γ* is defined as the CO2
partial pressure where the rate of Rubisco carboxylation
is offset by photorespiratory CO2 release. Values of Γ* are
defined by Rubisco specificity of CO2 over O2 and increase
linearly with O2 partial pressure. The O2 dependency of Γ*
can have a significant impact on rates of net CO2 assimilation as some C4 species have significant amounts of photosystem II present in the bundle sheath cells (Ghannoum
et al., 2005). This can lead to O2 partial pressure around
Rubisco exceeding ambient partial pressures as the bundle
sheath conductance to O2 is much less than that to CO2
(Berry and Farquhar, 1978; von Caemmerer, 2000). Table 1
gives examples of carbon isotope fractionation associated
with photorespiration at different bundle sheath CO2 and
O2 partial pressures demonstrating that ignoring photorespiration under certain conditions can lead to an underestimation of ϕ.
Table 1. Photorespiratory fractionation at different bundle sheath
CO2 partial pressures (Cs) and bundle sheath O2 partial pressures
(Os) at f=16.2‰
Os (mbar)
200
300
500
Γ*(μbar)
38.6
57.9
96.5
Cs (μbar)
500
1000
2000
5000
10000
Photorespiratory fractionation f
1.25
0.63
0.31
0.13
0.06
Γ*
(‰)
Cs
1.88
0.94
0.47
0.19
0.09
3.13
1.56
0.78
0.31
0.16
The fractionation factor b4’ is the combined fractionation
of PEP carboxylation and the preceding isotopic equilibrium
during dissolutions of CO2 and conversion to HCO3– as well
as a respiratory term relating to mesophyll cell respiration
(equation A3 and A4). Little is known about diversity of PEP
carboxylase fractionation, and a value of 2.2‰ is universally
used (O’Leary et al., 1992). The known temperature dependence of the isotopic equilibrium during dissolution and conversion of CO2 to HCO3– (given by equation A5) together
with the temperature dependence of the ratio of respiration
to CO2 assimilation give b4’ a strong temperature dependence
(Fig. 5). It is usually assumed that there is sufficient carbonic
anhydrase in the mesophyll cytosol to ensure full equilibration
between CO2 and HCO3–; however, if this is not the case equation (A6) needs to be used. This is further discussed below.
Carbon isotope discrimination in
transgenic C4 species with impaired
photosynthesis
Compartmentation of the C4 pathway between mesophyll
and bundle sheath cells has made it experimentally difficult to
study the biochemical interactions between C3 and C4 cycles.
Evidence for coordination between C3 and C4 cycle activity
has come from measurements of ϕ with combined measurements of carbon isotope discrimination and CO2 exchange
(Henderson et al., 1992). These measurements suggested
that leakiness remained relatively constant with moderate
short-term environmental variation in CO2 and light, and
such examples are also shown in Figs 5 and 6. This suggested
that it is difficult to greatly perturb C3–C4 cycle coordination
through environmental perturbation. However, at low light,
carbon isotope discrimination has been shown to increase,
and a number of studies have focused on estimations of leakiness at low light (Bellasio and Griffiths, 2013; Henderson
et al., 1992; Pengelly et al., 2010; Sun et al., 2012; Tazoe et al.,
2008; Ubierna et al., 2013).
Molecular perturbations of the C4 photosynthetic pathway via antisense technology have provided a useful means to
study photosynthethic carbon isotope discrimination and the
coordination of the C3 and C4 cycles. Several enzymes involved
in photosynthesis have been targeted in transgenic Flaveria
Carbon isotope discrimination in C4 species | 3465
bidentis and carbon isotope discrimination has been measured
(Fig 1). The first plants to be studied were transgenic F. bidentis with reduced amounts of Rubisco (Pengelly et al., 2012; von
Caemmerer et al., 1997b). These studies showed that reducing
Rubisco amount relative to PEPC content increased carbon
isotope discrimination because of increased ϕ and these plants
also had altered carbon isotope composition of leaf dry matter. Reducing the amount of NADP-malic enzyme decreased
carbon isotope discrimination and ϕ (Fig. 5, Pengelly et al.,
2012). These combined measurements of CO2 assimilation
rate and ϕ through carbon isotope discrimination allowed for
the calculation of C4 cycle and leak rates (Fig. 6, equations
A12, A13). In principal, the leak rate could then be used to
calculate bundle sheath CO2 partial pressure, but this requires
estimates of bundles sheath conductance (equation A14).
Transgenic F. bidentis with reduced amount of carbonic
anhydrase located in the mesophyll cytosol confirmed that
carbon isotope discrimination increased as predicted by
equation A6 (Cousins et al., 2006). Wild-type F. bidentis had
large amounts of cytosolic carbonic anhydrase; the amount
of carbonic anhydrase could be reduced to less than 10%
of wild type before effects on carbon isotope discrimination were detected. In contrast, many C4 monocot species
have much lower carbonic anhydrase content than F. bidentis
(Cousins et al., 2008; Gillon and Yakir, 2001); therefore, carbon isotope discrimination in these species may be influenced
by low carbonic anhydrase activity. Alternatively, transgenic
F. bidentis that expressed higher levels of carbonic anhydrase
in the cytosol of both mesophyll and bundle sheath cells
(Ludwig et al., 1998) demonstrated that too much carbonic
anhydrase in the bundle sheath increased CO2 leakage out of
that compartment and most likely decreased the fractionation factor s as predicted by Farquhar (1983; see appendix).
Although molecular manipulation of photosynthesis in
F. bidentis induced large disequilibria in the C3 and C4 cycles,
these studies help to point out what may cause some of the
natural variation in carbon isotope of dry matter amongst
diverse C4 species or between genotypes of a particular species.
Photosynthetic carbon isotope
discrimination and the carbon isotope
composition of dry matter
As discussed above, in C4 plants the main factors influencing leaf CO2 isotope exchange are diffusional fractionation,
carboxylation reactions, and variation in ϕ. However, in C4
species it has been difficult to relate the carbon isotope values of plant dry matter to the photosynthetic carbon isotope
discrimination. Typically the carbon isotope composition of
leaf material is more depleted in 13C compared with estimates
made from measurements of photosynthetic carbon isotope
discrimination (Cousins et al., 2008; Henderson et al., 1992;
Henderson et al., 1998; Kubasek et al., 2007). For example,
the isotopic signature of plant dry matter in NAD-ME type
C4 plants is typically depleted compared with NADP-ME
species (e.g. supplementary Table S1; Fig. 7), and this has
primarily been attributed to differences in ϕ (Buchmann
Fig. 6. (a) Measurements of CO2 assimilation rate (A) as a function of
intercellular CO2 in transgenic Flaveria bidentis with reduced amounts of
Rubisco (αSSU), reduced amounts of NADP malic enzyme (αNADP-ME)
and wild type. Measurements were made at 1500 μmol quanta m–2 s–1,
380 μbar CO2, 2% O2, and a leaf temperature of 25 °C. (b) Leakiness
(ϕ) calculated from concurrent measurements of carbon isotope
discrimination. (c) C4 cycle rates, and (d) bundle sheath leak rates
calculated from A and ϕ with the use of equations A11 and A12. Data
were taken from Pengelly JJL, Tan J, Furbank RT, von Caemmerer S.
2012. Antisense reduction of NADP-malic enzyme in Flaveria bidentis
reduces flow of CO2 through the C4 Cycle. Plant Physiology 160,
1070–1080. www.plantphysiol.org, Copyright American Society of Plant
Biologists”.
et al., 1996; Hattersley, 1982; Ohsugi et al., 1988). It has
been hypothesized that the presence of a suberized lamella
in NADP-ME species may reduce ϕ by reducing the physical conductance to CO2 diffusion across the bundle sheath.
However, the difference in dry matter δ13C does not seem to
be linked to differences in photosynthetic carbon isotope discrimination. Both Henderson et al. (1992) and Cousins et al.
(2008) found no significant differences in ϕ or Ci/Ca between
C4 subtypes when gas exchange and carbon isotope discrimination were measured concurrently, Cousins et al. (2008)
examined photosynthetic discrimination at different light
intensities and although Δ increased at lower light intensities,
it did so similarly for both subtypes. This suggests that the
difference in leaf δ13C between NAD-ME and NADP-ME
plants is in part due to post-photosynthetic fractionations.
The isotopic composition of organic compounds within a
leaf vary owing to the isotope effects of the biochemical pathways used for their synthesis, and it is well-known that different
carbon pools have different 13C signatures (Bowling et al., 2008;
Cernusak et al., 2009a; Hobbie and Werner, 2004; Tcherkez
et al., 2011). For example, lipid, lignin, protein, and organic
acids are typically depleted in 13C compared with the bulk leaf
isotopic signature, whereas sucrose, starch, and cellulose are
typically isotopically enriched. Therefore, the bulk leaf δ13C
differences between NAD-ME and NADP-ME could be due
to variation in the composition of organic material within the
3466 | Caemmerer et al.
suggests that leaves of Panicum NADP-ME should be more
enriched in 13C than the NAD-ME plants if sugars (sucrose)
was the primary form of carbon exported from NADP-ME
plants compared with NAD-ME; however, additional experiments are needed to confirm this across C4 subtypes.
Differences in respiratory processes between NAD-ME and
NADP-ME plants might also explain their δ13C signatures.
Typically, the CO2 released during respiration is enriched in
13
C compared with the bulk leaf signatures (Duranceau et al.,
1999; Ghashghaie et al., 2001). However, the isotopic signature of respired CO2 can vary depending on whether carbohydrates (enriched) or lipids (depleted) are the substrates
for respiration. Differences between subtypes in the utilization of sucrose or starch as precursors for respiration could
also influence the isotopic signature of CO2 released during
both day and night respiration. However, to our knowledge
there have not been side-by-side comparisons of the isotopic
release of CO2 from either day or night respiration in C4
plants. Presently, the reasons for the difference in dry matter
and cellulose δ13C between NAD-ME and NADP-ME species is not clear and therefore still needs to be resolved.
Conclusions
Fig. 7. Box-whisker plots of leaf dry matter (a, c, e) or leaf cellulose (b, d, f)
carbon isotope composition (δ) of NADP-ME or NAD-ME C4 grasses grown
in common garden experiments. The box and whisker represent the 25–75
percentile and minimum-maximum distributions of the data, respectively.
Closed circles give the overall means (see also supplementary Table S1).
Data were taken from Ghannoum et al., 2001a, b, 2002 and a list of species
used in the different experiments is given in Table 2.
leaves. However, it has been previously demonstrated that the
difference in leaf δ13C between C4 subtypes is also expressed
in cellulosic material and is present under different environmental growth conditions (Table S1; Fig. 7) suggesting that the
difference in leaf δ13C is not exclusively related to the composition of organic material (Ghannoum et al., 2001a, b, 2002).
Additionally, variation in leaf δ13C and the composition of constituents within a leaf does not necessarily lead to differences in
bulk leaf δ13C unless there is a net loss or gain of carbon from
the system. The conservation of mass requires that for a change
in δ13C of one compound to influence the bulk leaf δ13C there
must be a loss of carbon from the leaf, for example, via respiration or phloem export (Cernusak et al., 2009a).
Differences in the δ13C of leaf carbohydrates exported
from source leaves may also contribute to δ13C differences
between NAD-ME and NADP-ME plants. As previously
noted, both sucrose and starch are generally enriched compared with bulk leaf material; however, sucrose from transitory starch breakdown is relatively enriched in 13C compared
with sucrose synthesized directly from triose phosphates
(Hobbie and Werner, 2004). Therefore, source leaves exporting carbon derived from transitory starch degradation would
be depleted in 13C compared with leaves primarily exporting
sucrose derived directly from triose phosphates. In the genus
Panicum, after two hours of 14CO2 labelling the NADP-ME
plants had higher sugar to starch content compared with
NAD-ME subtypes (Leonardos and Grodzinski, 2000). This
Recent laser technological developments have allowed for rapid
concurrent measurements of carbon isotope discrimination
and CO2 assimilation. With increased interest in using dry matter carbon isotope compositions as a screening tool, the next
step is to close the gap in our understanding of how dry matter
carbon isotope composition is related to photosynthetic carbon
isotope discrimination. Solving the riddle belying the consistent
differences in dry matter carbon isotope composition between
NAD-ME and NADP-ME C4 grasses can help uncover the
main non-photosynthetic carbon isotopic fractionations in C4
plants. To this end, new methods such as compound-specific 13C
stable isotope ratio mass spectrometry show great promise for
determining the isotopic composition of organic compounds,
including carbohydrates and amino acids (Dungait et al., 2011;
Lynch et al., 2011; Merchant et al., 2011). Recently, Cernusak
et al. (2009a) reviewed several hypotheses that may explain differences in isotopic patterns between photosynthetic and heterotrophic tissues in C3 plants. Similar studies are required for C4
species to unravel the impact of post photosynthetic fractionations on carbon isotope composition.
Appendix
Following Farquhar (1983) and including the ternary formulation suggested by Farquhar and Cernusak (2012), Pengelly
et al. (2012) showed that carbon isotope discrimination during C4 photosynthesis can be given by:
1+ t
A
(ai − a ′ ) ( g C ) +
1− t
m a


Ci − A 

gm 

1+ t ′
.
b4 + (b3′ − s )f − a ′
Ca
1− t
∆=
1
(1− t)
(
a′ +
)
(A1)
Carbon isotope discrimination in C4 species | 3467
Table 2. List of C4 grass species for Fig. 7
Species
Subtype
Winter/ summer
(Fig. 7a,b)
Well watered/
water stressed
(Fig. 7c,d)
Ambient/ elevated
CO2 (Fig. 7e,f)
Bothriochloa biloba
Bothriochloa bladhii
Bothriochloa pertusa
Cenchrus ciliaris
Cymbopogon ambiguus
Cymbopogon bombycinus
Dichanthium aristatum
Dichanthium sericeum
Digitaria brownii
Digitaria smutsii
Panicum antidotale
Paspalum dilatatum
Pennisetum alopecuroides
Pennisetum clandestinum
Sehima nervosum
Astrebla lappacea
Astrebal pectinata
Astrebla squarrosa
Cynadon dactylon
Eleusine coracana
Eragrostis superba
Leptochloa dubia
Panicum coloratum
Panicum decompositum
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NADP-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
NAD-ME
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
This formulation is essentially similar to the original formulation by Farquhar (1983) but has incorporated net CO2 assimilation rate, A, rather than Rubisco and PEP carboxylation Vc
and Vp into the equations. This makes the equations easier to
use in conjunction with gas exchange measurements.
(1 + a ¢ ) E
The ternary effect is described by t =
where E
t
2 gac
denotes the transpiration rate and gtac the total conductance
to CO2 diffusion including boundary layer and stomatal conductance (von Caemmerer and Farquhar, 1981). The symbol
a’ denotes the combined fractionation factor through the leaf
boundary layer and through stomata and
a¢ =
ab (Ca −Cls ) + a (Cls −Ci )
(Ca −Ci )
(A2)
where Cls is the CO2 partial pressure at the leaf surface, ab
(2.9‰) is the fractionation occurring through diffusion in
the boundary layer and a (4.4‰) is the fractionation due to
diffusion in air (Evans et al., 1986). The fractionation factor
associated with the dissolution of CO2 and diffusion through
water is given by ai =es+al (1.1+0.7=1.8‰).
The fractionation factors b4’ and b3’ are associated with
fractionation occurring during PEP carboxylation and
Rubisco carboxylation.
b4¢ = b4 − e
0.5Rd
( A + 0.5Rd ) (A3)
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
The fractionation factor e is associated with respiration is
often calculated from the difference between δ13C in the CO2
cylinder used during experiments and that in the atmosphere
under growth conditions (Kromdijk et al., 2010; Tazoe et al.,
2009; Wingate et al., 2007). A and Rd denote the CO2 assimilation rate and day respiration respectively.
b4 = bp + es + eb (A4)
is the combined fractionation during PEP carboxylation
(bp=2.2‰) and the conversion of CO2 to HCO3–, where
es=1.1‰ is the fractionation during the dissolution of CO2,
eb (–9‰) is the equilibrium fractionation factor of the catalysed hydration and dehydration reactions of CO2 and
HCO3– (Mook et al., 1974). The fractionation factor eb=h–
d, were h=1.1‰ is the fractionation during hydration of
CO2, and d=10.1‰ the fractionation during dehydration of
HCO3– (b4=–5.74‰ at 25 °C). The value of b4 decreases with
increasing temperature, owing to temperature dependence of
the isotopic equilibrium during dissolution and conversion
of CO2 to HCO3– and the temperature dependence derived
by Mook et al. (1974) is used (Henderson et al., 1992):
(
( ))
b4 = ( −9.483 ⋅1000 ) / 273 + T oC + 23.89 + 2.2 (A5).
Equations (A3) and (A4) assume that CO2 and HCO3– are
in equilibrium in the mesophyll cytoplasm. If carbonic anhydrase were present in insufficient quantities to ensure equilibrium, the b4 term needs to be modified. In this case, b4 needs
to be replaced by
3468 | Caemmerer et al.
b4 + ( h − es − bp )
Vp
Vh
where Vp/Vh is the ratio of the rates of PEP carboxylase to the
rate of CO2 hydration (Farquhar, 1983; Henderson et al., 1992).
The combined fractionation of Rubisco (b3=29–30‰), respiration and photorespiration can be given by
 R
0.5Rd 
G*
d
b3′ = b3 − e 
−
(A7)
 − f
(A + Rd ) (A + 0.5Rd )
Cs
(Farquhar, 1983; Pengelly et al., 2010). The parameter f is the
fractionation during photorespiration. It has been estimated at
16.2‰ (Evans and von Caemmerer, 2013) and 11.6‰ (Lanigan
et al., 2008), but this fractionation factor remains uncertain. Γ*
is the CO2 partial pressure where rate of photorespiratory CO2
release balances the rate of carboxylation and Cs is the CO2
partial pressure in the bundle sheath (von Caemmerer, 2000).
Note that the last term in equation 7 had been incorrectly
0.5Vo
given as f Vo instead of f
in some recent publications,
Vc
Vc
G
the latter is equivalent to f * (Cousins et al., 2006; Pengelly
Cs
et al., 2010; Ubierna et al., 2011).
The fractionation factor s associated with CO2 leakage out
of the bundle sheath equals ai, assuming there is no HCO3–
leakage out of the bundle sheath. Depending on the amount
of carbonic anhydrase in the bundle sheath s can vary between
1.8‰ to –6.3‰ when there is complete equilibration between
CO2 and HCO3– in the bundle sheath (Farquhar, 1983; von
Caemmerer et al., 1997a).
Equation (1) can be rearranged to calculate leakiness ϕ and
C
A
1− t
a′
∆−
− (ai − b4′ )
− (b4′ − a ′ ) i Ca
gmCa
1+ t
1+ t
f=
(A8)


C
A
i
′


(b3 − s )C − g C 
a
m a
Equation (A1) can also be rearranged to highlight the impact
of mesophyll conductance gm:
∆=
(Ci )
1
1+ t ¢
a ¢ + ∆ gm +
b4 + ( b3¢ − s ) φ − a ¢
1 −t
Ca
(1 −t )
(
)
(A9)
where
∆ gm =
1+ t
A
ai − b4¢ + ( b3¢ − s ) φ
1 −t
g
( mCa )
( (
))
(A10)
In equation (A1) the assumption is made that Cs>>Cm. If this
is not the case, this may overestimate leakiness using equation (A8), particularly under low light. More complex equations were given by (Ubierna et al., 2011) and (Farquhar and
Cernusak, 2012):
1+ t
A
(ai − a ′ ) ( g C )
1− t
m a
(A11)
 
 ′  ′ Cs


A
 b + b

 Ci −
− s f
4
 3 Cs −Cm

 
gm 
1 + t 
′
+
− a 


fCm
Ca
1− t 
1
+



Cs − C m

∆=
(A6)
1
(1− t)
a′ +
However it is important to note that bundle sheath CO2
partial pressure is not usually known, making it difficult to
use this form of the equation without additional models of
C4 photosynthesis.
Calculations of C4 cycle rates, bundle sheath leak rate
and bundle sheath CO2 partial pressure
The values of leakiness calculated from carbon isotope discrimination measurements together with the measurements
of CO2 assimilation rate can be used to calculate the C4
cycle rate (Vp) and the bundles sheath leak rate (L) from the
equation:
Vp = ( A + Rd ) / (1 − φ )(A12)
(von Caemmerer and Furbank, 1999). Bundle sheath leak
rate (L) can then be calculated from
L = φVp (A13)
This provides insights into C4 metabolism. To estimate
bundle sheath CO2 partial pressure a bundles sheath conductance, gbs must be assumed and then
Cs = Cm + L / gbs(A14)
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